Domain generalization for cross-domain fault diagnosis: An application-oriented perspective and a benchmark study
•The first taxonomy for domain generalization-based fault diagnosis is proposed.•A basic and reproducible code framework is provided.•A broad discussion of critical challenges and future directions is presented. Most data-driven methods for fault diagnostics rely on the assumption of independently a...
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| Vydané v: | Reliability engineering & system safety Ročník 245; s. 109964 |
|---|---|
| Hlavní autori: | , , |
| Médium: | Journal Article |
| Jazyk: | English |
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Elsevier Ltd
01.05.2024
Elsevier |
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| ISSN: | 0951-8320, 1879-0836 |
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| Abstract | •The first taxonomy for domain generalization-based fault diagnosis is proposed.•A basic and reproducible code framework is provided.•A broad discussion of critical challenges and future directions is presented.
Most data-driven methods for fault diagnostics rely on the assumption of independently and identically distributed data of training and testing. However, domain shift between the phases of training and testing is common in practice. Recently, domain generalization-based fault diagnosis (DGFD) has gained widespread attention for learning fault diagnosis knowledge from multiple source domains and applying it to unseen target domains. This paper summarizes the developments in DGFD from an application-oriented perspective. Firstly, basic definitions of DGFD and its variant applications are formulated. Then, motivations, goals, challenges and state-of-the-art solutions for different applications are discussed. The limitations of existing technologies are highlighted. A comprehensive benchmark study is carried out on eight open-source and two self-collected datasets to provide an understanding of the existing methods and a unified framework for researchers. Finally, several future directions are given. Our code is available at https://github.com/CHAOZHAO-1/DG-PHM. |
|---|---|
| AbstractList | •The first taxonomy for domain generalization-based fault diagnosis is proposed.•A basic and reproducible code framework is provided.•A broad discussion of critical challenges and future directions is presented.
Most data-driven methods for fault diagnostics rely on the assumption of independently and identically distributed data of training and testing. However, domain shift between the phases of training and testing is common in practice. Recently, domain generalization-based fault diagnosis (DGFD) has gained widespread attention for learning fault diagnosis knowledge from multiple source domains and applying it to unseen target domains. This paper summarizes the developments in DGFD from an application-oriented perspective. Firstly, basic definitions of DGFD and its variant applications are formulated. Then, motivations, goals, challenges and state-of-the-art solutions for different applications are discussed. The limitations of existing technologies are highlighted. A comprehensive benchmark study is carried out on eight open-source and two self-collected datasets to provide an understanding of the existing methods and a unified framework for researchers. Finally, several future directions are given. Our code is available at https://github.com/CHAOZHAO-1/DG-PHM. Most data-driven methods for fault diagnostics rely on the assumption of independently and identically distributed data of training and testing. However, domain shift between the phases of training and testing is common in practice. Recently, domain generalization-based fault diagnosis (DGFD) has gained widespread attention for learning fault diagnosis knowledge from multiple source domains and applying it to unseen target domains. This paper summarizes the developments in DGFD from an application-oriented perspective. Firstly, basic definitions of DGFD and its variant applications are formulated. Then, motivations, goals, challenges and state-of-the-art solutions for different applications are discussed. The limitations of existing technologies are highlighted. A comprehensive benchmark study is carried out on eight open-source and two self-collected datasets to provide an understanding of the existing methods and a unified framework for researchers. Finally, several future directions are given. Our code is available at https://github.com/CHAOZHAO-1/DG-PHM. |
| ArticleNumber | 109964 |
| Author | Shen, Weiming Zhao, Chao Zio, Enrico |
| Author_xml | – sequence: 1 givenname: Chao surname: Zhao fullname: Zhao, Chao organization: State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science & Technology, Wuhan 430074, China – sequence: 2 givenname: Enrico surname: Zio fullname: Zio, Enrico organization: MINES Paris PSL University, CRC, Sophia Antipolis, France – sequence: 3 givenname: Weiming surname: Shen fullname: Shen, Weiming email: shenwm@hust.edu.cn organization: State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science & Technology, Wuhan 430074, China |
| BackLink | https://hal.science/hal-04835827$$DView record in HAL |
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| Cites_doi | 10.1016/j.jmsy.2022.12.001 10.1016/j.isatra.2022.03.014 10.1049/cim2.12047 10.1016/j.ymssp.2023.110139 10.1016/j.ymssp.2022.108990 10.1109/TII.2018.2864759 10.1016/j.measurement.2020.108516 10.1109/TITS.2022.3203871 10.1177/1475921720980718 10.1016/j.ymssp.2022.110011 10.1016/j.knosys.2020.106236 10.1016/j.neucom.2020.05.040 10.1109/TIM.2020.3016068 10.1016/j.ymssp.2023.110579 10.1109/TIE.2019.2953010 10.1109/TIM.2022.3216413 10.1016/j.measurement.2021.109650 10.1109/TIM.2022.3154000 10.1016/j.rcim.2023.102668 10.1016/j.neucom.2020.05.014 10.1016/j.knosys.2022.109880 10.1016/j.compind.2021.103399 10.1016/j.asoc.2022.109164 10.1109/TIM.2022.3177138 10.1371/journal.pone.0164111 10.1016/j.ymssp.2021.108036 10.1016/j.engappai.2023.107765 10.1109/ACCESS.2020.2994310 10.1109/TAI.2021.3054609 10.1088/1361-6501/acc04a 10.1109/ACCESS.2019.2939876 10.1016/j.ress.2023.109380 10.1088/1361-6501/ace841 10.1109/TIE.2021.3095804 10.1016/j.ress.2022.108672 10.1016/j.compind.2022.103810 10.1109/JSEN.2019.2949057 10.3901/JME.2013.01.063 10.1109/TII.2022.3175018 10.1016/j.ymssp.2023.110228 10.1016/j.measurement.2019.02.073 10.1109/TII.2023.3256400 10.1016/j.ymssp.2022.110074 10.1016/j.ymssp.2015.10.025 10.1109/ACCESS.2018.2878491 10.1016/j.ress.2023.109528 10.1109/TII.2019.2934901 10.1016/j.neucom.2020.04.045 10.1155/2022/3024590 10.1109/72.788640 10.1016/j.jsv.2005.03.007 10.1088/1361-6501/ac100e 10.1109/TASE.2020.2969485 10.1016/j.ress.2022.108358 10.3390/s130608013 10.1007/978-3-031-20044-1_4 10.1109/TIM.2020.2995441 10.1016/j.ymssp.2021.108487 10.1016/j.ymssp.2019.106587 10.1016/j.eswa.2021.116197 10.1109/TIE.2019.2898619 10.1109/TSMC.2017.2754287 10.1016/j.isatra.2019.08.012 10.1016/j.ress.2022.108883 10.1016/j.ymssp.2015.04.021 10.1016/j.isatra.2019.08.040 10.1109/TIE.2019.2942548 10.1016/j.ress.2023.109188 10.1016/j.ress.2021.108119 |
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| Keywords | Fault diagnosis Domain shift Deep learning Domain generalization |
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| References | Yang, Yin, Zheng, Li, Xu, Chen (bib0064) 2020; 8 Li, Huang, Li, Liao, Chen, He (bib0040) 2022; 167 Wang, Luo, Qiu, Huang, Baktashmotlagh (bib0093) 2021 Zhao, Liu, Shen (bib0008) 2022 Wang, Huang, Wang, Shen, Zhu (bib0017) 2022; 71 Tzeng E, Hoffman J, Zhang N, Saenko K, Darrell T. Deep Domain Confusion: Maximizing for Domain Invariance 2014. Uk, Ha, Kim, Bae, Lee, Youn (bib0041) 2021; 125 Ben-David, Blitzer, Crammer, Pereira (bib0061) 2007 Niu, Liu, Wang, Song (bib0015) 2021; 1 Ren, Wang, Zhu, Shi, Huang (bib0085) 2023; 200 Zhao, Liu, Shen, Gao (bib0027) 2021; 182 Liao, Huang, Li, Chen, Li (bib0083) 2020; 69 Xiong, Tang, Deng, Zhao, Yu (bib0020) 2021; 169 Yang, Zheng, Ge (bib0110) 2022 Cheng, Zhou, Ma, Wu, Yuan (bib0025) 2020; 409 Zheng, Wang, Yang, Li, Xu (bib0035) 2020; 67 Zhou, Lei, Zio, Wen, Liu, Su (bib0011) 2023; 191 Wang, Lei, Naipeng (bib0100) 2016; 6 Liu, Cao, Luo (bib0073) 2023; 237 Zhou, Wang, Zio, Wen, Liu, Su (bib0003) 2023; 239 Sun, Saenko (bib0105) 2016; 9915 LNCS Yang, Member, Lei, Member, Xu, Lee (bib0106) 2022; 69 Li, Gao, Cao, Huang, Weng, Mi (bib0091) 2021 He, Chen, Zhou, Huang (bib0006) 2023; 66 Zhao, Shen (bib0080) 2023 Lu, Wang, Ragulskis, Cheng (bib0099) 2016; 11 Vapnik (bib0103) 1999; 10 Xu, Zhou, Zhao, Fan, Ding, Yuan (bib0046) 2022; 190 . Zhang, Cisse, Dauphin, Lopez-Paz (bib0057) 2018 Li, Zhang, Qin, Estupinan (bib0038) 2020; 407 Li, Zhao, Sun, Yan, Chen (bib0030) 2021; 70 Cong, Song, Li, Jia (bib0081) 2023 Peng, Qiao, Zhao (bib0092) 2022; 14 Chen, He, Li, Liao, Gryllias, Li (bib0034) 2020; 69 Dong, Su, Gao, Wu, Jiang, Chen (bib0076) 2023 Zhao, Zhang, Yu, Sun, Wang, Yan (bib0039) 2021; 70 Zhao, Shen (bib0094) 2022; 19 He, Shen (bib0014) 2023 Zheng, Yang, Yin, Li, Wang, Xu (bib0070) 2021; 70 Ma, Zhang, Fan, Wang (bib0019) 2020; 99 Qin, Qian, Luo, Pu (bib0023) 2022 Zhao, Shen (bib0078) 2024; 130 Shi, Deng, Deng, Li, Xu, Zhang (bib0068) 2022 Li, Wang, Zi, Zhang, Wan (bib0077) 2021 Ren, Mo, Cheng (bib0066) 2023 Smith, Randall (bib0097) 2015; 64–65 Zhao, Shen (bib0084) 2023; 189 Li, Zhang, Ma, Luo, Li (bib0055) 2020; 403 Jia, Lei, Lin, Zhou, Lu (bib0005) 2016; 72–73 Wen, Gao, Li (bib0026) 2019; 49 Deng, Huang, Du, Li, Zhao, Lv (bib0031) 2021; 127 Zhao, Shen (bib0087) 2022; 226 Qiu, Lee, Lin, Yu (bib0095) 2006; 289 Lei, Yang, Jiang, Jia, Li, Nandi (bib0004) 2020; 138 Maniyar U, Joseph KJ. Zero Shot Domain Generalization n.d. Zheng, Wang, Yang, Yin, Li, Li (bib0013) 2019; 7 Zhao, Shen (bib0009) 2022; 221 Yan, Su, Huang, Mo (bib0032) 2020 Shi, Chen, Zhang, Zi, Li, Chen (bib0069) 2023; 188 Han, Li, Qian (bib0056) 2021; 70 Xu Y, Feng K, Yan X, Sheng X, Sun B. Cross-modal Fusion Convolutional Neural Networks with Online Soft Label Training Strategy for Mechanical Fault Diagnosis 2023. Liu, Shen, Gao, Kusiak (bib0050) 2022 Wang, Huang, Shi, Wang, Shen, Zhu (bib0079) 2022; 256 Chen, Li, Shen, Zhu, Wang, Xia (bib0062) 2021; 3203 Guo, Zhang, Yang, Lyu, Gao (bib0042) 2020; 67 Yu, Fu, Ma, Lin, Li (bib0028) 2021; 20 Shao, McAleer, Yan, Baldi (bib0048) 2019; 15 Li, Ping, Wang, Chen, Cao (bib0096) 2013; 13 Guo, Li, Song, Wang, Chen (bib0033) 2020; 16 Zha D, States U. Data-centric Artificial Intelligence: A Survey 2023;1. Yang, Lei, Jia, Li, Du (bib0022) 2020; 67 Zhao, Liu, Shen (bib0049) 2021; 32 Yang Y, Wang H, Katabi D. On multi-domain long-tailed recognition, Imbalanced Domain Generalization and Beyond 2022:57–75. Zhang, Zhao, Zhang, Liu, Sun, Li (bib0063) 2021; 70 Zio (bib0002) 2022; 218 Li, Wang, Zi, Zhang (bib0036) 2021 Lessmeier, Kimotho, Zimmer, Sextro (bib0098) 2016; 2016 Ren Y, Liu J, Wang Q, Zhang H. HSELL-Net : A Heterogeneous Sample Enhancement Network With Lifelong Learning Under Industrial Small Samples 2022:1–13. Jiao, Lin, Zhao, Liang (bib0029) 2020; 205 Chen, Shen, Wang, Kong, Chen, Zhu (bib0045) 2022; 71 Qian, Li, Yi, Zhang (bib0001) 2019; 138 Yang, Kong, Wang, Li, Cheng, Yu (bib0018) 2021; 186 Fan, Xu, Jiang, Ding (bib0058) 2023; 1 Xing, Lei, Wang, Lu, Li (bib0047) 2022; 162 Xu, Baraldi, Lu, Zio (bib0010) 2022; 23 Jia, Li, Wang, Sun, Deng (bib0072) 2023; 192 Chen B, Shen C, Member S, Wang D, Kong L, Chen L, et al. A Lifelong Learning Method for Gearbox Diagnosis With Incremental Fault Types 2022;71. Zhao, Shen (bib0054) 2022; 173 Wang, He, Chen, Lai (bib0012) 2013; 49 Li, Shen, Kong, Wang, Xia, Zhu (bib0086) 2022; 71 Yan, Shen, Sun, Chen (bib0037) 2020; 20 Li, Wang, Member, Zi, Zhang, Li (bib0071) 2022; 3203 Han, Liu, Yang, Jiang (bib0021) 2020; 97 Li, Pan, Wang, Kot (bib0104) 2018 Ragab, Chen, Zhang, Eldele, Wu, Kwoh (bib0065) 2022; 71 Wang, Wen, Li, Gao (bib0074) 2023 Qian, Zhou, Qin (bib0075) 2023 Zhang, Chen, Zio (bib0051) 2022; 126 Zhang, Li, Li, Ng (bib0101) 2018; 6 Wang, Bai, Wang, Tan, Liu (bib0067) 2022; 71 He, Zhao, Zhou, Shen (bib0016) 2024; 86 Tang, Liu, Sun, Bo (bib0053) 2022; 71 Song, Liu (bib0082) 2023 Kaddour J, Lynch A, Liu Q, Kusner MJ, Silva R. Causal Machine Learning: A Survey and Open Problems 2022. He, Xiang, Zhou, Chen (bib0007) 2023; 145 Zhao, Shen (bib0109) 2023 Chen, Zhang, Wang, Zio, Dui, Zhang (bib0052) 2023; 230 Yao H, Yang X, Zhou A, Finn C. Multi-Domain Long-Tailed Learning by Augmenting Disentangled Representations 2022:1–22. Yang, Zhou, Liu (bib0102) 2021 Shi, Deng, Deng, Xu, Liu, Ding (bib0059) 2023; 235 He, Li, Li, Zhang, Zhang, Zhou (bib0060) 2022; 2022 Zhao, Shen (bib0088) 2023; 1 Han (10.1016/j.ress.2024.109964_bib0021) 2020; 97 Zhao (10.1016/j.ress.2024.109964_bib0054) 2022; 173 Smith (10.1016/j.ress.2024.109964_bib0097) 2015; 64–65 10.1016/j.ress.2024.109964_bib0112 10.1016/j.ress.2024.109964_bib0111 Zhang (10.1016/j.ress.2024.109964_bib0101) 2018; 6 He (10.1016/j.ress.2024.109964_bib0060) 2022; 2022 Ben-David (10.1016/j.ress.2024.109964_bib0061) 2007 Vapnik (10.1016/j.ress.2024.109964_bib0103) 1999; 10 Ma (10.1016/j.ress.2024.109964_bib0019) 2020; 99 Qian (10.1016/j.ress.2024.109964_bib0001) 2019; 138 Li (10.1016/j.ress.2024.109964_bib0086) 2022; 71 Chen (10.1016/j.ress.2024.109964_bib0034) 2020; 69 Ren (10.1016/j.ress.2024.109964_bib0066) 2023 10.1016/j.ress.2024.109964_bib0089 Wen (10.1016/j.ress.2024.109964_bib0026) 2019; 49 He (10.1016/j.ress.2024.109964_bib0014) 2023 Yang (10.1016/j.ress.2024.109964_bib0110) 2022 Wang (10.1016/j.ress.2024.109964_bib0093) 2021 Liu (10.1016/j.ress.2024.109964_bib0073) 2023; 237 Wang (10.1016/j.ress.2024.109964_bib0100) 2016; 6 Yu (10.1016/j.ress.2024.109964_bib0028) 2021; 20 Fan (10.1016/j.ress.2024.109964_bib0058) 2023; 1 Wang (10.1016/j.ress.2024.109964_bib0012) 2013; 49 Song (10.1016/j.ress.2024.109964_bib0082) 2023 Deng (10.1016/j.ress.2024.109964_bib0031) 2021; 127 Li (10.1016/j.ress.2024.109964_bib0071) 2022; 3203 Guo (10.1016/j.ress.2024.109964_bib0042) 2020; 67 Dong (10.1016/j.ress.2024.109964_bib0076) 2023 Qiu (10.1016/j.ress.2024.109964_bib0095) 2006; 289 Shi (10.1016/j.ress.2024.109964_bib0068) 2022 Zhao (10.1016/j.ress.2024.109964_bib0087) 2022; 226 Chen (10.1016/j.ress.2024.109964_bib0062) 2021; 3203 Yang (10.1016/j.ress.2024.109964_bib0064) 2020; 8 Wang (10.1016/j.ress.2024.109964_bib0017) 2022; 71 Zio (10.1016/j.ress.2024.109964_bib0002) 2022; 218 Jiao (10.1016/j.ress.2024.109964_bib0029) 2020; 205 Guo (10.1016/j.ress.2024.109964_bib0033) 2020; 16 Zhao (10.1016/j.ress.2024.109964_bib0049) 2021; 32 Shi (10.1016/j.ress.2024.109964_bib0069) 2023; 188 Xu (10.1016/j.ress.2024.109964_bib0010) 2022; 23 Shi (10.1016/j.ress.2024.109964_bib0059) 2023; 235 Lessmeier (10.1016/j.ress.2024.109964_bib0098) 2016; 2016 Zhao (10.1016/j.ress.2024.109964_bib0084) 2023; 189 Uk (10.1016/j.ress.2024.109964_bib0041) 2021; 125 Zhao (10.1016/j.ress.2024.109964_bib0078) 2024; 130 10.1016/j.ress.2024.109964_bib0108 10.1016/j.ress.2024.109964_bib0107 Zheng (10.1016/j.ress.2024.109964_bib0013) 2019; 7 Cheng (10.1016/j.ress.2024.109964_bib0025) 2020; 409 Zheng (10.1016/j.ress.2024.109964_bib0035) 2020; 67 Wang (10.1016/j.ress.2024.109964_bib0079) 2022; 256 Han (10.1016/j.ress.2024.109964_bib0056) 2021; 70 Zhao (10.1016/j.ress.2024.109964_bib0088) 2023; 1 He (10.1016/j.ress.2024.109964_bib0007) 2023; 145 Zhao (10.1016/j.ress.2024.109964_bib0080) 2023 Li (10.1016/j.ress.2024.109964_bib0091) 2021 Zhao (10.1016/j.ress.2024.109964_bib0009) 2022; 221 Zheng (10.1016/j.ress.2024.109964_bib0070) 2021; 70 Yang (10.1016/j.ress.2024.109964_bib0106) 2022; 69 Li (10.1016/j.ress.2024.109964_bib0038) 2020; 407 Zhao (10.1016/j.ress.2024.109964_bib0008) 2022 Lu (10.1016/j.ress.2024.109964_bib0099) 2016; 11 Zhang (10.1016/j.ress.2024.109964_bib0063) 2021; 70 10.1016/j.ress.2024.109964_bib0043 Yang (10.1016/j.ress.2024.109964_bib0102) 2021 Li (10.1016/j.ress.2024.109964_bib0055) 2020; 403 Li (10.1016/j.ress.2024.109964_bib0096) 2013; 13 Jia (10.1016/j.ress.2024.109964_bib0005) 2016; 72–73 Chen (10.1016/j.ress.2024.109964_bib0045) 2022; 71 10.1016/j.ress.2024.109964_bib0044 Cong (10.1016/j.ress.2024.109964_bib0081) 2023 Li (10.1016/j.ress.2024.109964_bib0104) 2018 Lei (10.1016/j.ress.2024.109964_bib0004) 2020; 138 Li (10.1016/j.ress.2024.109964_bib0036) 2021 Yang (10.1016/j.ress.2024.109964_bib0022) 2020; 67 Shao (10.1016/j.ress.2024.109964_bib0048) 2019; 15 Liao (10.1016/j.ress.2024.109964_bib0083) 2020; 69 Qian (10.1016/j.ress.2024.109964_bib0075) 2023 Jia (10.1016/j.ress.2024.109964_bib0072) 2023; 192 Sun (10.1016/j.ress.2024.109964_bib0105) 2016; 9915 LNCS Qin (10.1016/j.ress.2024.109964_bib0023) 2022 He (10.1016/j.ress.2024.109964_bib0016) 2024; 86 Zhang (10.1016/j.ress.2024.109964_bib0057) 2018 Zhao (10.1016/j.ress.2024.109964_bib0027) 2021; 182 Wang (10.1016/j.ress.2024.109964_bib0074) 2023 10.1016/j.ress.2024.109964_bib0090 Liu (10.1016/j.ress.2024.109964_bib0050) 2022 Xu (10.1016/j.ress.2024.109964_bib0046) 2022; 190 Zhang (10.1016/j.ress.2024.109964_bib0051) 2022; 126 Xiong (10.1016/j.ress.2024.109964_bib0020) 2021; 169 Li (10.1016/j.ress.2024.109964_bib0077) 2021 Ragab (10.1016/j.ress.2024.109964_bib0065) 2022; 71 Zhao (10.1016/j.ress.2024.109964_bib0039) 2021; 70 Chen (10.1016/j.ress.2024.109964_bib0052) 2023; 230 Ren (10.1016/j.ress.2024.109964_bib0085) 2023; 200 Zhou (10.1016/j.ress.2024.109964_bib0011) 2023; 191 Peng (10.1016/j.ress.2024.109964_bib0092) 2022; 14 Zhao (10.1016/j.ress.2024.109964_bib0094) 2022; 19 Li (10.1016/j.ress.2024.109964_bib0030) 2021; 70 He (10.1016/j.ress.2024.109964_bib0006) 2023; 66 10.1016/j.ress.2024.109964_bib0024 Wang (10.1016/j.ress.2024.109964_bib0067) 2022; 71 Zhou (10.1016/j.ress.2024.109964_bib0003) 2023; 239 Tang (10.1016/j.ress.2024.109964_bib0053) 2022; 71 Zhao (10.1016/j.ress.2024.109964_bib0109) 2023 Li (10.1016/j.ress.2024.109964_bib0040) 2022; 167 Niu (10.1016/j.ress.2024.109964_bib0015) 2021; 1 Yan (10.1016/j.ress.2024.109964_bib0032) 2020 Yan (10.1016/j.ress.2024.109964_bib0037) 2020; 20 Yang (10.1016/j.ress.2024.109964_bib0018) 2021; 186 Xing (10.1016/j.ress.2024.109964_bib0047) 2022; 162 |
| References_xml | – volume: 20 start-page: 2182 year: 2021 end-page: 2198 ident: bib0028 article-title: Simulation data driven weakly supervised adversarial domain adaptation approach for intelligent cross-machine fault diagnosis publication-title: Struct Heal Monit – volume: 205 year: 2020 ident: bib0029 article-title: Double-level adversarial domain adaptation network for intelligent fault diagnosis publication-title: Knowledge-Based Syst – year: 2023 ident: bib0082 article-title: Federated domain generalization for intelligent fault diagnosis based on pseudo-siamese network and robust global model aggregation publication-title: Int J Mach Learn Cybern – year: 2022 ident: bib0008 article-title: A balanced and weighted alignment network for partial transfer fault diagnosis publication-title: ISA Trans – volume: 138 start-page: 514 year: 2019 end-page: 525 ident: bib0001 article-title: A novel transfer learning method for robust fault diagnosis of rotating machines under variable working conditions publication-title: Meas J Int Meas Confed – volume: 256 year: 2022 ident: bib0079 article-title: Federated adversarial domain generalization network: a novel machinery fault diagnosis method with data privacy publication-title: Knowledge-Based Syst – start-page: 1 year: 2023 end-page: 11 ident: bib0014 article-title: MSiT: a cross-machine fault diagnosis model for machine-level CNC spindle motors publication-title: IEEE Trans Reliab – volume: 7 start-page: 129260 year: 2019 end-page: 129290 ident: bib0013 article-title: Cross-Domain fault diagnosis using knowledge transfer strategy: a review publication-title: IEEE Access – start-page: 0046 year: 2021 ident: bib0102 article-title: SuperGraph: spatial-temporal graph-based feature extraction for rotating machinery diagnosis publication-title: IEEE Trans Ind Electron – volume: 70 start-page: 1 year: 2021 end-page: 28 ident: bib0039 article-title: Applications of unsupervised deep transfer learning to intelligent fault diagnosis: a survey and comparative study publication-title: IEEE Trans Instrum Meas – volume: 3203 start-page: 1 year: 2022 end-page: 10 ident: bib0071 article-title: Causal consistency network : a collaborative multi-machine generalization method for bearing fault diagnosis publication-title: IEEE Trans Ind Informatics – start-page: 5400 year: 2018 end-page: 5409 ident: bib0104 article-title: Domain generalization with adversarial feature learning publication-title: Proc IEEE Comput Soc Conf Comput Vis Pattern Recognit – volume: 97 start-page: 269 year: 2020 end-page: 281 ident: bib0021 article-title: Deep transfer network with joint distribution adaptation: a new intelligent fault diagnosis framework for industry application publication-title: ISA Trans – volume: 221 year: 2022 ident: bib0009 article-title: Dual adversarial network for cross-domain open set fault diagnosis publication-title: Reliab Eng Syst Saf – volume: 20 start-page: 8374 year: 2020 end-page: 8393 ident: bib0037 article-title: Knowledge transfer for rotary machine fault diagnosis publication-title: IEEE Sens J – start-page: 1 year: 2023 end-page: 11 ident: bib0066 article-title: Meta-Learning based domain generalization framework for fault diagnosis with gradient aligning and semantic matching publication-title: IEEE Trans Ind Info – reference: Xu Y, Feng K, Yan X, Sheng X, Sun B. Cross-modal Fusion Convolutional Neural Networks with Online Soft Label Training Strategy for Mechanical Fault Diagnosis 2023. – volume: 1 start-page: 1 year: 2023 end-page: 20 ident: bib0088 article-title: Imbalanced domain generalization via semantic-discriminative augmentation for intelligent fault diagnosis publication-title: Adv Eng Informatics – reference: Kaddour J, Lynch A, Liu Q, Kusner MJ, Silva R. Causal Machine Learning: A Survey and Open Problems 2022. – volume: 226 year: 2022 ident: bib0087 article-title: Adaptive open set domain generalization network : Learning to diagnose unknown faults under unknown working conditions publication-title: Reliab Eng Syst Saf – start-page: 1 year: 2018 end-page: 13 ident: bib0057 article-title: MixUp: Beyond empirical risk minimization publication-title: Proc 6th Int Conf Learn Represent ICLR 2018 - Conf Track Proc – start-page: 1679 year: 2023 end-page: 1684 ident: bib0109 article-title: An application-oriented perspective of domain generalization for cross-domain fault diagnosis publication-title: Proc 2023 26th Int Conf Comput Support Coop Work Des – volume: 200 year: 2023 ident: bib0085 article-title: Domain fuzzy generalization networks for semi-supervised intelligent fault diagnosis under unseen working conditions publication-title: Mech Syst Signal Process – volume: 218 year: 2022 ident: bib0002 article-title: Prognostics and Health Management (PHM): Where are we and where do we (need to) go in theory and practice publication-title: Reliab Eng Syst Saf – volume: 64–65 start-page: 100 year: 2015 end-page: 131 ident: bib0097 article-title: Rolling element bearing diagnostics using the case western reserve university data: a benchmark study publication-title: Mech Syst Signal Process – volume: 99 start-page: 465 year: 2020 end-page: 478 ident: bib0019 article-title: A diagnosis framework based on domain adaptation for bearing fault diagnosis across diverse domains publication-title: ISA Trans – volume: 289 start-page: 1066 year: 2006 end-page: 1090 ident: bib0095 article-title: Wavelet filter-based weak signature detection method and its application on rolling element bearing prognostics publication-title: J Sound Vib – volume: 186 year: 2021 ident: bib0018 article-title: A multi-source ensemble domain adaptation method for rotary machine fault diagnosis publication-title: Meas J Int Meas Confed – volume: 71 year: 2022 ident: bib0086 article-title: A new adversarial domain generalization network based on class boundary feature detection for bearing fault diagnosis publication-title: IEEE Trans Instrum Meas – volume: 173 year: 2022 ident: bib0054 article-title: A domain generalization network combing invariance and specificity towards real-time intelligent fault diagnosis publication-title: Mech Syst Signal Process – volume: 71 year: 2022 ident: bib0065 article-title: Conditional contrastive domain generalization for fault diagnosis publication-title: IEEE Trans Instrum Meas – volume: 2016 start-page: 152 year: 2016 end-page: 156 ident: bib0098 article-title: Condition monitoring of bearing damage in electromechanical drive systems by using motor current signals of electric motors: a benchmark data set for data-driven classification publication-title: Third Eur Conf Progn Heal Manag Soc – start-page: 1 year: 2023 end-page: 9 ident: bib0080 article-title: Federated domain generalization : a secure and robust framework for intelligent fault diagnosis publication-title: IEEE Trans Ind Informatics – volume: 8 start-page: 91103 year: 2020 end-page: 91115 ident: bib0064 article-title: Learn generalization feature via convolutional neural network: a fault diagnosis scheme toward unseen operating conditions publication-title: IEEE Access – start-page: 1 year: 2021 end-page: 14 ident: bib0036 article-title: Whitening-Net: a generalized network to diagnose the faults among different machines and conditions publication-title: IEEE Trans Neural Networks Learn Syst – year: 2023 ident: bib0076 article-title: Fine-grained transfer learning based on deep feature decomposition for rotating equipment fault diagnosis publication-title: Meas Sci Technol – volume: 49 start-page: 63 year: 2013 end-page: 72 ident: bib0012 article-title: Basic research on machinery fault diagnosis-what is the prescription publication-title: Jixie Gongcheng Xuebao/Journal Mech Eng – volume: 32 year: 2021 ident: bib0049 article-title: A dual-view alignment-based domain adaptation network for fault diagnosis publication-title: Meas Sci Technol – volume: 145 year: 2023 ident: bib0007 article-title: In-situ fault detection for the spindle motor of CNC machines via multi-stage residual fusion convolution neural networks publication-title: Comput Ind – volume: 407 start-page: 121 year: 2020 end-page: 135 ident: bib0038 article-title: A systematic review of deep transfer learning for machinery fault diagnosis publication-title: Neurocomputing – reference: Yao H, Yang X, Zhou A, Finn C. Multi-Domain Long-Tailed Learning by Augmenting Disentangled Representations 2022:1–22. – volume: 69 start-page: 8064 year: 2020 end-page: 8075 ident: bib0083 article-title: Deep semisupervised domain generalization network for rotary machinery fault diagnosis under variable speed publication-title: IEEE Trans Instrum Meas – volume: 9915 LNCS start-page: 443 year: 2016 end-page: 450 ident: bib0105 article-title: Deep CORAL: correlation alignment for deep domain adaptation publication-title: Lect Notes Comput Sci (Including Subser Lect Notes Artif Intell Lect Notes Bioinformatics) – volume: 192 year: 2023 ident: bib0072 article-title: Deep causal factorization network: a novel domain generalization method for cross-machine bearing fault diagnosis publication-title: Mech Syst Signal Process – volume: 70 year: 2021 ident: bib0030 article-title: Domain adversarial graph convolutional network for fault diagnosis under variable working conditions publication-title: IEEE Trans Instrum Meas – volume: 67 start-page: 9747 year: 2020 end-page: 9757 ident: bib0022 article-title: A polynomial kernel induced distance metric to improve deep transfer learning for fault diagnosis of machines publication-title: IEEE Trans Ind Electron – year: 2022 ident: bib0050 article-title: Knowledge transfer in fault diagnosis of rotary machines publication-title: IET Collab Intell Manuf – volume: 191 year: 2023 ident: bib0011 article-title: Conditional feature disentanglement learning for anomaly detection in machines operating under time-varying conditions publication-title: Mech Syst Signal Process – volume: 13 start-page: 8013 year: 2013 end-page: 8041 ident: bib0096 article-title: Sequential fuzzy diagnosis method for motor roller bearing in variable operating conditions based on vibration analysis publication-title: Sensors (Switzerland) – volume: 69 start-page: 8702 year: 2020 end-page: 8712 ident: bib0034 article-title: Domain adversarial transfer network for cross-domain fault diagnosis of rotary machinery publication-title: IEEE Trans Instrum Meas – volume: 70 start-page: 1 year: 2021 end-page: 11 ident: bib0056 article-title: A hybrid generalization network for intelligent fault diagnosis of rotating machinery under unseen working conditions publication-title: IEEE Trans Instrum Meas – volume: 69 start-page: 7372 year: 2022 end-page: 7382 ident: bib0106 article-title: An optimal transport-embedded similarity measure for diagnostic knowledge transferability analytics across machines publication-title: IEEE Trans Ind Electron – volume: 11 start-page: 1 year: 2016 end-page: 22 ident: bib0099 article-title: Fault diagnosis for rotating machinery: a method based on image processing publication-title: PLoS One – volume: 138 year: 2020 ident: bib0004 article-title: Applications of machine learning to machine fault diagnosis: a review and roadmap publication-title: Mech Syst Signal Process – volume: 126 year: 2022 ident: bib0051 article-title: A framework for predicting the remaining useful life of machinery working under time-varying operational conditions [Formula presented] publication-title: Appl Soft Comput – start-page: 1 year: 2023 end-page: 11 ident: bib0075 article-title: Relationship transfer domain generalization network for rotating machinery fault diagnosis under different working conditions publication-title: IEEE Trans Ind Informatics – volume: 10 start-page: 988 year: 1999 end-page: 999 ident: bib0103 article-title: An overview of statistical learning theory publication-title: IEEE Trans Neural Networks – volume: 125 year: 2021 ident: bib0041 article-title: Computers in industry Multi-task Learning of Classification and Denoising (MLCD) for noise-robust rotor system diagnosis publication-title: Comput Ind – volume: 409 start-page: 35 year: 2020 end-page: 45 ident: bib0025 article-title: Wasserstein distance based deep adversarial transfer learning for intelligent fault diagnosis with unlabeled or insufficient labeled data publication-title: Neurocomputing – volume: 403 start-page: 409 year: 2020 end-page: 420 ident: bib0055 article-title: Domain generalization in rotating machinery fault diagnostics using deep neural networks publication-title: Neurocomputing – volume: 71 start-page: 1 year: 2022 end-page: 10 ident: bib0017 article-title: Multisource domain feature adaptation network for bearing fault diagnosis under time-varying working conditions publication-title: IEEE Trans Instrum Meas – volume: 16 start-page: 2044 year: 2020 end-page: 2053 ident: bib0033 article-title: Intelligent fault diagnosis method based on full 1-D convolutional generative adversarial network publication-title: IEEE Trans Ind Informatics – volume: 23 start-page: 23408 year: 2022 end-page: 23421 ident: bib0010 article-title: Generative adversarial networks with AdaBoost ensemble learning for anomaly detection in high-speed train automatic doors publication-title: IEEE Trans Intell Transp Syst – volume: 239 year: 2023 ident: bib0003 article-title: Hybrid system response model for condition monitoring of bearings under time-varying operating conditions publication-title: Reliab Eng Syst Saf – reference: Chen B, Shen C, Member S, Wang D, Kong L, Chen L, et al. A Lifelong Learning Method for Gearbox Diagnosis With Incremental Fault Types 2022;71. – volume: 67 start-page: 1293 year: 2020 end-page: 1304 ident: bib0035 article-title: Intelligent fault identification based on multisource domain generalization towards actual diagnosis scenario publication-title: IEEE Trans Ind Electron – start-page: 1 year: 2020 end-page: 9 ident: bib0032 article-title: Chiller fault diagnosis based on VAE-Enabled generative adversarial networks publication-title: IEEE Trans Autom Sci Eng – reference: Zha D, States U. Data-centric Artificial Intelligence: A Survey 2023;1. – start-page: 1 year: 2022 end-page: 11 ident: bib0068 article-title: Domain transferability-based deep domain generalization method towards actual fault diagnosis scenarios publication-title: IEEE Trans Ind Informatics – volume: 162 year: 2022 ident: bib0047 article-title: A label description space embedded model for zero-shot intelligent diagnosis of mechanical compound faults publication-title: Mech Syst Signal Process – volume: 3203 year: 2021 ident: bib0062 article-title: Adversarial domain-invariant generalization: a generic domain-regressive framework for bearing fault diagnosis under unseen conditions publication-title: IEEE Trans Ind Informatics – volume: 15 start-page: 2446 year: 2019 end-page: 2455 ident: bib0048 article-title: Highly accurate machine fault diagnosis using deep transfer learning publication-title: IEEE Trans Ind Informatics – volume: 49 year: 2019 ident: bib0026 article-title: A new deep transfer learning based on sparse auto-encoder for fault diagnosis publication-title: IEEE Trans Syst Man, Cybern Syst – volume: 70 year: 2021 ident: bib0063 article-title: Conditional adversarial domain generalization with a single discriminator for bearing fault diagnosis publication-title: IEEE Trans Instrum Meas – volume: 6 start-page: 66367 year: 2018 end-page: 66384 ident: bib0101 article-title: Intelligent fault diagnosis under varying working conditions based on domain adaptive convolutional neural networks publication-title: IEEE Access – start-page: 1 year: 2022 end-page: 11 ident: bib0023 article-title: Deep joint distribution alignment: a novel enhanced-domain adaptation mechanism for fault transfer diagnosis publication-title: IEEE Trans Cybern – volume: 235 year: 2023 ident: bib0059 article-title: Domain augmentation generalization network for real-time fault diagnosis under unseen working conditions publication-title: Reliab Eng Syst Saf – reference: Tzeng E, Hoffman J, Zhang N, Saenko K, Darrell T. Deep Domain Confusion: Maximizing for Domain Invariance 2014. – volume: 169 year: 2021 ident: bib0020 article-title: Multi-block domain adaptation with central moment discrepancy for fault diagnosis publication-title: Measurement – volume: 71 year: 2022 ident: bib0053 article-title: Fault diagnosis of rotating machinery under multiple operating conditions generalization: a representation gradient muting paradigm publication-title: IEEE Trans Instrum Meas – volume: 2022 year: 2022 ident: bib0060 article-title: A hybrid matching network for fault diagnosis under different working conditions with limited data publication-title: Comput Intell Neurosci – volume: 1 start-page: 1 year: 2023 end-page: 10 ident: bib0058 article-title: Deep mixed domain generalization network for intelligent fault diagnosis under unseen conditions publication-title: IEEE Trans Ind Electron – volume: 190 year: 2022 ident: bib0046 article-title: Zero-shot learning for compound fault diagnosis of bearings publication-title: Expert Syst Appl – start-page: 814 year: 2021 end-page: 823 ident: bib0093 article-title: Learning to diversify for single domain generalization publication-title: Proc IEEE Int Conf Comput Vis – volume: 230 year: 2023 ident: bib0052 article-title: Importance measures for critical components in complex system based on Copula Hierarchical Bayesian Network publication-title: Reliab Eng Syst Saf – reference: Ren Y, Liu J, Wang Q, Zhang H. HSELL-Net : A Heterogeneous Sample Enhancement Network With Lifelong Learning Under Industrial Small Samples 2022:1–13. – reference: Yang Y, Wang H, Katabi D. On multi-domain long-tailed recognition, Imbalanced Domain Generalization and Beyond 2022:57–75. – volume: 130 year: 2024 ident: bib0078 article-title: A federated distillation domain generalization framework for machinery fault diagnosis with data privacy publication-title: Eng Appl Artif Intell – volume: 14 start-page: 1 year: 2022 end-page: 14 ident: bib0092 article-title: Out-of-Domain generalization from a single source: an uncertainty quantification approach publication-title: IEEE Trans Pattern Anal Mach Intell – start-page: 137 year: 2007 end-page: 144 ident: bib0061 article-title: Analysis of representations for domain adaptation publication-title: Adv Neural Inf Process Syst – start-page: 1 year: 2022 end-page: 12 ident: bib0110 article-title: Lifelong Bayesian learning machines for streaming industrial big data publication-title: IEEE Trans Syst Man, Cybern Syst – year: 2023 ident: bib0081 article-title: Federated domain generalization with global robust model aggregation strategy for bearing fault diagnosis publication-title: Meas Sci Technol – volume: 19 start-page: 2909 year: 2022 end-page: 2918 ident: bib0094 article-title: Adversarial mutual information-guided single domain generalization network for intelligent fault diagnosis publication-title: IEEE Trans Ind Informatics – volume: 6 start-page: 173 year: 2016 end-page: 182 ident: bib0100 article-title: A hybrid prognostics approach for estimating remaining useful life of rolling element bearings publication-title: IEEE Trans Reliab – volume: 71 start-page: 1 year: 2022 end-page: 10 ident: bib0045 article-title: A lifelong learning method for gearbox diagnosis with incremental fault types publication-title: IEEE Trans Instrum Meas – volume: 237 year: 2023 ident: bib0073 article-title: An information-induced fault diagnosis framework generalizing from stationary to unknown nonstationary working conditions publication-title: Reliab Eng Syst Saf – start-page: 1 year: 2021 end-page: 13 ident: bib0077 article-title: Causal disentanglement: a generalized bearing fault diagnostic framework in continuous degradation mode publication-title: IEEE Trans Neural Networks Learn Syst – volume: 188 year: 2023 ident: bib0069 article-title: A reliable feature-assisted contrastive generalization net for intelligent fault diagnosis under unseen machines and working conditions publication-title: Mech Syst Signal Process – volume: 182 year: 2021 ident: bib0027 article-title: A multi-representation-based domain adaptation network for fault diagnosis publication-title: Measurement – start-page: 1 year: 2023 end-page: 11 ident: bib0074 article-title: Adaptive class center generalization network: a sparse domain-regressive framework for bearing fault diagnosis under unknown working conditions publication-title: IEEE Trans Instrum Meas – volume: 167 year: 2022 ident: bib0040 article-title: A perspective survey on deep transfer learning for fault diagnosis in industrial scenarios: theories, applications and challenges publication-title: Mech Syst Signal Process – reference: . – volume: 189 year: 2023 ident: bib0084 article-title: Mutual-assistance semisupervised domain generalization network for intelligent fault diagnosis under unseen working conditions publication-title: Mech Syst Signal Process – volume: 127 year: 2021 ident: bib0031 article-title: A double-layer attention based adversarial network for partial transfer learning in machinery fault diagnosis publication-title: Comput Ind – volume: 86 year: 2024 ident: bib0016 article-title: Robotics and Computer-Integrated Manufacturing MJAR : a novel joint generalization-based diagnosis method for industrial robots with compound faults publication-title: Robot Comput Integr Manuf – volume: 70 year: 2021 ident: bib0070 article-title: Deep domain generalization combining a priori diagnosis knowledge toward cross-domain fault diagnosis of rolling bearing publication-title: IEEE Trans Instrum Meas – start-page: 224 year: 2021 end-page: 233 ident: bib0091 article-title: Progressive domain expansion network for single domain generalization publication-title: Proc IEEE Comput Soc Conf Comput Vis Pattern Recognit – volume: 67 start-page: 8005 year: 2020 end-page: 8015 ident: bib0042 article-title: Multitask convolutional neural network with information fusion for bearing fault diagnosis and localization publication-title: IEEE Trans Ind Electron – reference: Maniyar U, Joseph KJ. Zero Shot Domain Generalization n.d. – volume: 1 start-page: 151 year: 2021 end-page: 166 ident: bib0015 article-title: A decade survey of transfer learning (2010–2020) publication-title: IEEE Trans Artif Intell – volume: 66 start-page: 233 year: 2023 end-page: 247 ident: bib0006 article-title: In-situ fault diagnosis for the harmonic reducer of industrial robots via multi-scale mixed convolutional neural networks publication-title: J Manuf Syst – volume: 72–73 start-page: 303 year: 2016 end-page: 315 ident: bib0005 article-title: Deep neural networks: A promising tool for fault characteristic mining and intelligent diagnosis of rotating machinery with massive data publication-title: Mech Syst Signal Process – volume: 71 year: 2022 ident: bib0067 article-title: Generalization on unseen domains via model-agnostic learning for intelligent fault diagnosis publication-title: IEEE Trans Instrum Meas – volume: 66 start-page: 233 year: 2023 ident: 10.1016/j.ress.2024.109964_bib0006 article-title: In-situ fault diagnosis for the harmonic reducer of industrial robots via multi-scale mixed convolutional neural networks publication-title: J Manuf Syst doi: 10.1016/j.jmsy.2022.12.001 – start-page: 1679 year: 2023 ident: 10.1016/j.ress.2024.109964_bib0109 article-title: An application-oriented perspective of domain generalization for cross-domain fault diagnosis – volume: 14 start-page: 1 year: 2022 ident: 10.1016/j.ress.2024.109964_bib0092 article-title: Out-of-Domain generalization from a single source: an uncertainty quantification approach publication-title: IEEE Trans Pattern Anal Mach Intell – year: 2022 ident: 10.1016/j.ress.2024.109964_bib0008 article-title: A balanced and weighted alignment network for partial transfer fault diagnosis publication-title: ISA Trans doi: 10.1016/j.isatra.2022.03.014 – year: 2022 ident: 10.1016/j.ress.2024.109964_bib0050 article-title: Knowledge transfer in fault diagnosis of rotary machines publication-title: IET Collab Intell Manuf doi: 10.1049/cim2.12047 – ident: 10.1016/j.ress.2024.109964_bib0089 – volume: 191 year: 2023 ident: 10.1016/j.ress.2024.109964_bib0011 article-title: Conditional feature disentanglement learning for anomaly detection in machines operating under time-varying conditions publication-title: Mech Syst Signal Process doi: 10.1016/j.ymssp.2023.110139 – volume: 173 year: 2022 ident: 10.1016/j.ress.2024.109964_bib0054 article-title: A domain generalization network combing invariance and specificity towards real-time intelligent fault diagnosis publication-title: Mech Syst Signal Process doi: 10.1016/j.ymssp.2022.108990 – ident: 10.1016/j.ress.2024.109964_bib0043 – volume: 15 start-page: 2446 year: 2019 ident: 10.1016/j.ress.2024.109964_bib0048 article-title: Highly accurate machine fault diagnosis using deep transfer learning publication-title: IEEE Trans Ind Informatics doi: 10.1109/TII.2018.2864759 – start-page: 137 year: 2007 ident: 10.1016/j.ress.2024.109964_bib0061 article-title: Analysis of representations for domain adaptation publication-title: Adv Neural Inf Process Syst – volume: 169 year: 2021 ident: 10.1016/j.ress.2024.109964_bib0020 article-title: Multi-block domain adaptation with central moment discrepancy for fault diagnosis publication-title: Measurement doi: 10.1016/j.measurement.2020.108516 – volume: 23 start-page: 23408 year: 2022 ident: 10.1016/j.ress.2024.109964_bib0010 article-title: Generative adversarial networks with AdaBoost ensemble learning for anomaly detection in high-speed train automatic doors publication-title: IEEE Trans Intell Transp Syst doi: 10.1109/TITS.2022.3203871 – volume: 20 start-page: 2182 year: 2021 ident: 10.1016/j.ress.2024.109964_bib0028 article-title: Simulation data driven weakly supervised adversarial domain adaptation approach for intelligent cross-machine fault diagnosis publication-title: Struct Heal Monit doi: 10.1177/1475921720980718 – volume: 9915 LNCS start-page: 443 year: 2016 ident: 10.1016/j.ress.2024.109964_bib0105 article-title: Deep CORAL: correlation alignment for deep domain adaptation publication-title: Lect Notes Comput Sci (Including Subser Lect Notes Artif Intell Lect Notes Bioinformatics) – volume: 188 year: 2023 ident: 10.1016/j.ress.2024.109964_bib0069 article-title: A reliable feature-assisted contrastive generalization net for intelligent fault diagnosis under unseen machines and working conditions publication-title: Mech Syst Signal Process doi: 10.1016/j.ymssp.2022.110011 – volume: 205 year: 2020 ident: 10.1016/j.ress.2024.109964_bib0029 article-title: Double-level adversarial domain adaptation network for intelligent fault diagnosis publication-title: Knowledge-Based Syst doi: 10.1016/j.knosys.2020.106236 – volume: 409 start-page: 35 year: 2020 ident: 10.1016/j.ress.2024.109964_bib0025 article-title: Wasserstein distance based deep adversarial transfer learning for intelligent fault diagnosis with unlabeled or insufficient labeled data publication-title: Neurocomputing doi: 10.1016/j.neucom.2020.05.040 – start-page: 1 year: 2021 ident: 10.1016/j.ress.2024.109964_bib0077 article-title: Causal disentanglement: a generalized bearing fault diagnostic framework in continuous degradation mode publication-title: IEEE Trans Neural Networks Learn Syst – ident: 10.1016/j.ress.2024.109964_bib0108 – ident: 10.1016/j.ress.2024.109964_bib0111 – volume: 70 year: 2021 ident: 10.1016/j.ress.2024.109964_bib0070 article-title: Deep domain generalization combining a priori diagnosis knowledge toward cross-domain fault diagnosis of rolling bearing publication-title: IEEE Trans Instrum Meas doi: 10.1109/TIM.2020.3016068 – volume: 200 year: 2023 ident: 10.1016/j.ress.2024.109964_bib0085 article-title: Domain fuzzy generalization networks for semi-supervised intelligent fault diagnosis under unseen working conditions publication-title: Mech Syst Signal Process doi: 10.1016/j.ymssp.2023.110579 – volume: 67 start-page: 9747 year: 2020 ident: 10.1016/j.ress.2024.109964_bib0022 article-title: A polynomial kernel induced distance metric to improve deep transfer learning for fault diagnosis of machines publication-title: IEEE Trans Ind Electron doi: 10.1109/TIE.2019.2953010 – volume: 71 start-page: 1 year: 2022 ident: 10.1016/j.ress.2024.109964_bib0017 article-title: Multisource domain feature adaptation network for bearing fault diagnosis under time-varying working conditions publication-title: IEEE Trans Instrum Meas doi: 10.1109/TIM.2022.3216413 – volume: 182 year: 2021 ident: 10.1016/j.ress.2024.109964_bib0027 article-title: A multi-representation-based domain adaptation network for fault diagnosis publication-title: Measurement doi: 10.1016/j.measurement.2021.109650 – volume: 70 year: 2021 ident: 10.1016/j.ress.2024.109964_bib0063 article-title: Conditional adversarial domain generalization with a single discriminator for bearing fault diagnosis publication-title: IEEE Trans Instrum Meas – volume: 71 year: 2022 ident: 10.1016/j.ress.2024.109964_bib0065 article-title: Conditional contrastive domain generalization for fault diagnosis publication-title: IEEE Trans Instrum Meas doi: 10.1109/TIM.2022.3154000 – volume: 86 year: 2024 ident: 10.1016/j.ress.2024.109964_bib0016 article-title: Robotics and Computer-Integrated Manufacturing MJAR : a novel joint generalization-based diagnosis method for industrial robots with compound faults publication-title: Robot Comput Integr Manuf doi: 10.1016/j.rcim.2023.102668 – volume: 403 start-page: 409 year: 2020 ident: 10.1016/j.ress.2024.109964_bib0055 article-title: Domain generalization in rotating machinery fault diagnostics using deep neural networks publication-title: Neurocomputing doi: 10.1016/j.neucom.2020.05.014 – volume: 256 year: 2022 ident: 10.1016/j.ress.2024.109964_bib0079 article-title: Federated adversarial domain generalization network: a novel machinery fault diagnosis method with data privacy publication-title: Knowledge-Based Syst doi: 10.1016/j.knosys.2022.109880 – volume: 127 year: 2021 ident: 10.1016/j.ress.2024.109964_bib0031 article-title: A double-layer attention based adversarial network for partial transfer learning in machinery fault diagnosis publication-title: Comput Ind doi: 10.1016/j.compind.2021.103399 – volume: 126 year: 2022 ident: 10.1016/j.ress.2024.109964_bib0051 article-title: A framework for predicting the remaining useful life of machinery working under time-varying operational conditions [Formula presented] publication-title: Appl Soft Comput doi: 10.1016/j.asoc.2022.109164 – ident: 10.1016/j.ress.2024.109964_bib0044 doi: 10.1109/TIM.2022.3177138 – volume: 11 start-page: 1 year: 2016 ident: 10.1016/j.ress.2024.109964_bib0099 article-title: Fault diagnosis for rotating machinery: a method based on image processing publication-title: PLoS One doi: 10.1371/journal.pone.0164111 – volume: 162 year: 2022 ident: 10.1016/j.ress.2024.109964_bib0047 article-title: A label description space embedded model for zero-shot intelligent diagnosis of mechanical compound faults publication-title: Mech Syst Signal Process doi: 10.1016/j.ymssp.2021.108036 – volume: 186 year: 2021 ident: 10.1016/j.ress.2024.109964_bib0018 article-title: A multi-source ensemble domain adaptation method for rotary machine fault diagnosis publication-title: Meas J Int Meas Confed – volume: 130 year: 2024 ident: 10.1016/j.ress.2024.109964_bib0078 article-title: A federated distillation domain generalization framework for machinery fault diagnosis with data privacy publication-title: Eng Appl Artif Intell doi: 10.1016/j.engappai.2023.107765 – volume: 71 year: 2022 ident: 10.1016/j.ress.2024.109964_bib0086 article-title: A new adversarial domain generalization network based on class boundary feature detection for bearing fault diagnosis publication-title: IEEE Trans Instrum Meas – volume: 8 start-page: 91103 year: 2020 ident: 10.1016/j.ress.2024.109964_bib0064 article-title: Learn generalization feature via convolutional neural network: a fault diagnosis scheme toward unseen operating conditions publication-title: IEEE Access doi: 10.1109/ACCESS.2020.2994310 – volume: 1 start-page: 151 year: 2021 ident: 10.1016/j.ress.2024.109964_bib0015 article-title: A decade survey of transfer learning (2010–2020) publication-title: IEEE Trans Artif Intell doi: 10.1109/TAI.2021.3054609 – year: 2023 ident: 10.1016/j.ress.2024.109964_bib0076 article-title: Fine-grained transfer learning based on deep feature decomposition for rotating equipment fault diagnosis publication-title: Meas Sci Technol doi: 10.1088/1361-6501/acc04a – volume: 7 start-page: 129260 year: 2019 ident: 10.1016/j.ress.2024.109964_bib0013 article-title: Cross-Domain fault diagnosis using knowledge transfer strategy: a review publication-title: IEEE Access doi: 10.1109/ACCESS.2019.2939876 – volume: 6 start-page: 173 year: 2016 ident: 10.1016/j.ress.2024.109964_bib0100 article-title: A hybrid prognostics approach for estimating remaining useful life of rolling element bearings publication-title: IEEE Trans Reliab – volume: 71 start-page: 1 year: 2022 ident: 10.1016/j.ress.2024.109964_bib0045 article-title: A lifelong learning method for gearbox diagnosis with incremental fault types publication-title: IEEE Trans Instrum Meas – start-page: 1 year: 2022 ident: 10.1016/j.ress.2024.109964_bib0023 article-title: Deep joint distribution alignment: a novel enhanced-domain adaptation mechanism for fault transfer diagnosis publication-title: IEEE Trans Cybern – start-page: 1 year: 2022 ident: 10.1016/j.ress.2024.109964_bib0068 article-title: Domain transferability-based deep domain generalization method towards actual fault diagnosis scenarios publication-title: IEEE Trans Ind Informatics – volume: 237 year: 2023 ident: 10.1016/j.ress.2024.109964_bib0073 article-title: An information-induced fault diagnosis framework generalizing from stationary to unknown nonstationary working conditions publication-title: Reliab Eng Syst Saf doi: 10.1016/j.ress.2023.109380 – year: 2023 ident: 10.1016/j.ress.2024.109964_bib0081 article-title: Federated domain generalization with global robust model aggregation strategy for bearing fault diagnosis publication-title: Meas Sci Technol doi: 10.1088/1361-6501/ace841 – volume: 69 start-page: 7372 year: 2022 ident: 10.1016/j.ress.2024.109964_bib0106 article-title: An optimal transport-embedded similarity measure for diagnostic knowledge transferability analytics across machines publication-title: IEEE Trans Ind Electron doi: 10.1109/TIE.2021.3095804 – volume: 3203 year: 2021 ident: 10.1016/j.ress.2024.109964_bib0062 article-title: Adversarial domain-invariant generalization: a generic domain-regressive framework for bearing fault diagnosis under unseen conditions publication-title: IEEE Trans Ind Informatics – volume: 226 year: 2022 ident: 10.1016/j.ress.2024.109964_bib0087 article-title: Adaptive open set domain generalization network : Learning to diagnose unknown faults under unknown working conditions publication-title: Reliab Eng Syst Saf doi: 10.1016/j.ress.2022.108672 – volume: 145 year: 2023 ident: 10.1016/j.ress.2024.109964_bib0007 article-title: In-situ fault detection for the spindle motor of CNC machines via multi-stage residual fusion convolution neural networks publication-title: Comput Ind doi: 10.1016/j.compind.2022.103810 – volume: 20 start-page: 8374 year: 2020 ident: 10.1016/j.ress.2024.109964_bib0037 article-title: Knowledge transfer for rotary machine fault diagnosis publication-title: IEEE Sens J doi: 10.1109/JSEN.2019.2949057 – start-page: 0046 year: 2021 ident: 10.1016/j.ress.2024.109964_bib0102 article-title: SuperGraph: spatial-temporal graph-based feature extraction for rotating machinery diagnosis publication-title: IEEE Trans Ind Electron – volume: 49 start-page: 63 year: 2013 ident: 10.1016/j.ress.2024.109964_bib0012 article-title: Basic research on machinery fault diagnosis-what is the prescription publication-title: Jixie Gongcheng Xuebao/Journal Mech Eng doi: 10.3901/JME.2013.01.063 – volume: 19 start-page: 2909 year: 2022 ident: 10.1016/j.ress.2024.109964_bib0094 article-title: Adversarial mutual information-guided single domain generalization network for intelligent fault diagnosis publication-title: IEEE Trans Ind Informatics doi: 10.1109/TII.2022.3175018 – volume: 192 year: 2023 ident: 10.1016/j.ress.2024.109964_bib0072 article-title: Deep causal factorization network: a novel domain generalization method for cross-machine bearing fault diagnosis publication-title: Mech Syst Signal Process doi: 10.1016/j.ymssp.2023.110228 – year: 2023 ident: 10.1016/j.ress.2024.109964_bib0082 article-title: Federated domain generalization for intelligent fault diagnosis based on pseudo-siamese network and robust global model aggregation publication-title: Int J Mach Learn Cybern – volume: 138 start-page: 514 year: 2019 ident: 10.1016/j.ress.2024.109964_bib0001 article-title: A novel transfer learning method for robust fault diagnosis of rotating machines under variable working conditions publication-title: Meas J Int Meas Confed doi: 10.1016/j.measurement.2019.02.073 – start-page: 1 year: 2023 ident: 10.1016/j.ress.2024.109964_bib0014 article-title: MSiT: a cross-machine fault diagnosis model for machine-level CNC spindle motors publication-title: IEEE Trans Reliab – volume: 69 start-page: 8064 year: 2020 ident: 10.1016/j.ress.2024.109964_bib0083 article-title: Deep semisupervised domain generalization network for rotary machinery fault diagnosis under variable speed publication-title: IEEE Trans Instrum Meas – ident: 10.1016/j.ress.2024.109964_bib0112 doi: 10.1109/TII.2023.3256400 – volume: 189 year: 2023 ident: 10.1016/j.ress.2024.109964_bib0084 article-title: Mutual-assistance semisupervised domain generalization network for intelligent fault diagnosis under unseen working conditions publication-title: Mech Syst Signal Process doi: 10.1016/j.ymssp.2022.110074 – volume: 72–73 start-page: 303 year: 2016 ident: 10.1016/j.ress.2024.109964_bib0005 article-title: Deep neural networks: A promising tool for fault characteristic mining and intelligent diagnosis of rotating machinery with massive data publication-title: Mech Syst Signal Process doi: 10.1016/j.ymssp.2015.10.025 – ident: 10.1016/j.ress.2024.109964_bib0107 – volume: 6 start-page: 66367 year: 2018 ident: 10.1016/j.ress.2024.109964_bib0101 article-title: Intelligent fault diagnosis under varying working conditions based on domain adaptive convolutional neural networks publication-title: IEEE Access doi: 10.1109/ACCESS.2018.2878491 – volume: 239 year: 2023 ident: 10.1016/j.ress.2024.109964_bib0003 article-title: Hybrid system response model for condition monitoring of bearings under time-varying operating conditions publication-title: Reliab Eng Syst Saf doi: 10.1016/j.ress.2023.109528 – volume: 70 start-page: 1 year: 2021 ident: 10.1016/j.ress.2024.109964_bib0039 article-title: Applications of unsupervised deep transfer learning to intelligent fault diagnosis: a survey and comparative study publication-title: IEEE Trans Instrum Meas – volume: 16 start-page: 2044 year: 2020 ident: 10.1016/j.ress.2024.109964_bib0033 article-title: Intelligent fault diagnosis method based on full 1-D convolutional generative adversarial network publication-title: IEEE Trans Ind Informatics doi: 10.1109/TII.2019.2934901 – volume: 407 start-page: 121 year: 2020 ident: 10.1016/j.ress.2024.109964_bib0038 article-title: A systematic review of deep transfer learning for machinery fault diagnosis publication-title: Neurocomputing doi: 10.1016/j.neucom.2020.04.045 – start-page: 1 year: 2023 ident: 10.1016/j.ress.2024.109964_bib0080 article-title: Federated domain generalization : a secure and robust framework for intelligent fault diagnosis publication-title: IEEE Trans Ind Informatics – volume: 71 year: 2022 ident: 10.1016/j.ress.2024.109964_bib0053 article-title: Fault diagnosis of rotating machinery under multiple operating conditions generalization: a representation gradient muting paradigm publication-title: IEEE Trans Instrum Meas – volume: 2022 year: 2022 ident: 10.1016/j.ress.2024.109964_bib0060 article-title: A hybrid matching network for fault diagnosis under different working conditions with limited data publication-title: Comput Intell Neurosci doi: 10.1155/2022/3024590 – volume: 10 start-page: 988 year: 1999 ident: 10.1016/j.ress.2024.109964_bib0103 article-title: An overview of statistical learning theory publication-title: IEEE Trans Neural Networks doi: 10.1109/72.788640 – volume: 289 start-page: 1066 year: 2006 ident: 10.1016/j.ress.2024.109964_bib0095 article-title: Wavelet filter-based weak signature detection method and its application on rolling element bearing prognostics publication-title: J Sound Vib doi: 10.1016/j.jsv.2005.03.007 – volume: 32 year: 2021 ident: 10.1016/j.ress.2024.109964_bib0049 article-title: A dual-view alignment-based domain adaptation network for fault diagnosis publication-title: Meas Sci Technol doi: 10.1088/1361-6501/ac100e – volume: 71 year: 2022 ident: 10.1016/j.ress.2024.109964_bib0067 article-title: Generalization on unseen domains via model-agnostic learning for intelligent fault diagnosis publication-title: IEEE Trans Instrum Meas – start-page: 1 year: 2020 ident: 10.1016/j.ress.2024.109964_bib0032 article-title: Chiller fault diagnosis based on VAE-Enabled generative adversarial networks publication-title: IEEE Trans Autom Sci Eng doi: 10.1109/TASE.2020.2969485 – volume: 2016 start-page: 152 year: 2016 ident: 10.1016/j.ress.2024.109964_bib0098 article-title: Condition monitoring of bearing damage in electromechanical drive systems by using motor current signals of electric motors: a benchmark data set for data-driven classification publication-title: Third Eur Conf Progn Heal Manag Soc – volume: 221 year: 2022 ident: 10.1016/j.ress.2024.109964_bib0009 article-title: Dual adversarial network for cross-domain open set fault diagnosis publication-title: Reliab Eng Syst Saf doi: 10.1016/j.ress.2022.108358 – volume: 13 start-page: 8013 year: 2013 ident: 10.1016/j.ress.2024.109964_bib0096 article-title: Sequential fuzzy diagnosis method for motor roller bearing in variable operating conditions based on vibration analysis publication-title: Sensors (Switzerland) doi: 10.3390/s130608013 – start-page: 814 year: 2021 ident: 10.1016/j.ress.2024.109964_bib0093 article-title: Learning to diversify for single domain generalization publication-title: Proc IEEE Int Conf Comput Vis – ident: 10.1016/j.ress.2024.109964_bib0090 doi: 10.1007/978-3-031-20044-1_4 – volume: 69 start-page: 8702 year: 2020 ident: 10.1016/j.ress.2024.109964_bib0034 article-title: Domain adversarial transfer network for cross-domain fault diagnosis of rotary machinery publication-title: IEEE Trans Instrum Meas doi: 10.1109/TIM.2020.2995441 – volume: 3203 start-page: 1 year: 2022 ident: 10.1016/j.ress.2024.109964_bib0071 article-title: Causal consistency network : a collaborative multi-machine generalization method for bearing fault diagnosis publication-title: IEEE Trans Ind Informatics – volume: 70 year: 2021 ident: 10.1016/j.ress.2024.109964_bib0030 article-title: Domain adversarial graph convolutional network for fault diagnosis under variable working conditions publication-title: IEEE Trans Instrum Meas – volume: 167 year: 2022 ident: 10.1016/j.ress.2024.109964_bib0040 article-title: A perspective survey on deep transfer learning for fault diagnosis in industrial scenarios: theories, applications and challenges publication-title: Mech Syst Signal Process doi: 10.1016/j.ymssp.2021.108487 – start-page: 5400 year: 2018 ident: 10.1016/j.ress.2024.109964_bib0104 article-title: Domain generalization with adversarial feature learning publication-title: Proc IEEE Comput Soc Conf Comput Vis Pattern Recognit – volume: 138 year: 2020 ident: 10.1016/j.ress.2024.109964_bib0004 article-title: Applications of machine learning to machine fault diagnosis: a review and roadmap publication-title: Mech Syst Signal Process doi: 10.1016/j.ymssp.2019.106587 – volume: 190 year: 2022 ident: 10.1016/j.ress.2024.109964_bib0046 article-title: Zero-shot learning for compound fault diagnosis of bearings publication-title: Expert Syst Appl doi: 10.1016/j.eswa.2021.116197 – start-page: 1 year: 2023 ident: 10.1016/j.ress.2024.109964_bib0075 article-title: Relationship transfer domain generalization network for rotating machinery fault diagnosis under different working conditions publication-title: IEEE Trans Ind Informatics – start-page: 1 year: 2023 ident: 10.1016/j.ress.2024.109964_bib0066 article-title: Meta-Learning based domain generalization framework for fault diagnosis with gradient aligning and semantic matching publication-title: IEEE Trans Ind Info – volume: 125 year: 2021 ident: 10.1016/j.ress.2024.109964_bib0041 article-title: Computers in industry Multi-task Learning of Classification and Denoising (MLCD) for noise-robust rotor system diagnosis publication-title: Comput Ind – volume: 1 start-page: 1 year: 2023 ident: 10.1016/j.ress.2024.109964_bib0058 article-title: Deep mixed domain generalization network for intelligent fault diagnosis under unseen conditions publication-title: IEEE Trans Ind Electron – volume: 67 start-page: 1293 year: 2020 ident: 10.1016/j.ress.2024.109964_bib0035 article-title: Intelligent fault identification based on multisource domain generalization towards actual diagnosis scenario publication-title: IEEE Trans Ind Electron doi: 10.1109/TIE.2019.2898619 – start-page: 224 year: 2021 ident: 10.1016/j.ress.2024.109964_bib0091 article-title: Progressive domain expansion network for single domain generalization publication-title: Proc IEEE Comput Soc Conf Comput Vis Pattern Recognit – volume: 49 year: 2019 ident: 10.1016/j.ress.2024.109964_bib0026 article-title: A new deep transfer learning based on sparse auto-encoder for fault diagnosis publication-title: IEEE Trans Syst Man, Cybern Syst doi: 10.1109/TSMC.2017.2754287 – volume: 97 start-page: 269 year: 2020 ident: 10.1016/j.ress.2024.109964_bib0021 article-title: Deep transfer network with joint distribution adaptation: a new intelligent fault diagnosis framework for industry application publication-title: ISA Trans doi: 10.1016/j.isatra.2019.08.012 – start-page: 1 year: 2022 ident: 10.1016/j.ress.2024.109964_bib0110 article-title: Lifelong Bayesian learning machines for streaming industrial big data publication-title: IEEE Trans Syst Man, Cybern Syst – volume: 230 year: 2023 ident: 10.1016/j.ress.2024.109964_bib0052 article-title: Importance measures for critical components in complex system based on Copula Hierarchical Bayesian Network publication-title: Reliab Eng Syst Saf doi: 10.1016/j.ress.2022.108883 – volume: 64–65 start-page: 100 year: 2015 ident: 10.1016/j.ress.2024.109964_bib0097 article-title: Rolling element bearing diagnostics using the case western reserve university data: a benchmark study publication-title: Mech Syst Signal Process doi: 10.1016/j.ymssp.2015.04.021 – volume: 99 start-page: 465 year: 2020 ident: 10.1016/j.ress.2024.109964_bib0019 article-title: A diagnosis framework based on domain adaptation for bearing fault diagnosis across diverse domains publication-title: ISA Trans doi: 10.1016/j.isatra.2019.08.040 – ident: 10.1016/j.ress.2024.109964_bib0024 – volume: 67 start-page: 8005 year: 2020 ident: 10.1016/j.ress.2024.109964_bib0042 article-title: Multitask convolutional neural network with information fusion for bearing fault diagnosis and localization publication-title: IEEE Trans Ind Electron doi: 10.1109/TIE.2019.2942548 – start-page: 1 year: 2021 ident: 10.1016/j.ress.2024.109964_bib0036 article-title: Whitening-Net: a generalized network to diagnose the faults among different machines and conditions publication-title: IEEE Trans Neural Networks Learn Syst – start-page: 1 year: 2023 ident: 10.1016/j.ress.2024.109964_bib0074 article-title: Adaptive class center generalization network: a sparse domain-regressive framework for bearing fault diagnosis under unknown working conditions publication-title: IEEE Trans Instrum Meas – volume: 70 start-page: 1 year: 2021 ident: 10.1016/j.ress.2024.109964_bib0056 article-title: A hybrid generalization network for intelligent fault diagnosis of rotating machinery under unseen working conditions publication-title: IEEE Trans Instrum Meas – start-page: 1 year: 2018 ident: 10.1016/j.ress.2024.109964_bib0057 article-title: MixUp: Beyond empirical risk minimization – volume: 235 year: 2023 ident: 10.1016/j.ress.2024.109964_bib0059 article-title: Domain augmentation generalization network for real-time fault diagnosis under unseen working conditions publication-title: Reliab Eng Syst Saf doi: 10.1016/j.ress.2023.109188 – volume: 1 start-page: 1 year: 2023 ident: 10.1016/j.ress.2024.109964_bib0088 article-title: Imbalanced domain generalization via semantic-discriminative augmentation for intelligent fault diagnosis publication-title: Adv Eng Informatics – volume: 218 year: 2022 ident: 10.1016/j.ress.2024.109964_bib0002 article-title: Prognostics and Health Management (PHM): Where are we and where do we (need to) go in theory and practice publication-title: Reliab Eng Syst Saf doi: 10.1016/j.ress.2021.108119 |
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| Snippet | •The first taxonomy for domain generalization-based fault diagnosis is proposed.•A basic and reproducible code framework is provided.•A broad discussion of... Most data-driven methods for fault diagnostics rely on the assumption of independently and identically distributed data of training and testing. However,... |
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| SubjectTerms | Deep learning Domain generalization Domain shift Engineering Sciences Fault diagnosis |
| Title | Domain generalization for cross-domain fault diagnosis: An application-oriented perspective and a benchmark study |
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