An on-board detection framework for polygon wear of railway wheel based on vibration acceleration of axle-box

•It exploits the vertical axle-box vibration acceleration signal that it is helpful to simplify the hardware of monitoring system of high-speed train.•The proposed angular synchronous average technique perfectly enhances the fault-related signal of wheel polygon wear by mitigating the asynchronous c...

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Vydané v:	Mechanical systems and signal processing Ročník 153; s. 107540
Hlavní autori:	Sun, Qi, Chen, Chunjun, Kemp, Andrew H., Brooks, Peter
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Berlin Elsevier Ltd 15.05.2021 Elsevier BV
Predmet:	Angle domain synchronous averaging technique Axle-box vibration acceleration Axleboxes Background noise Field investigations Mechanical components Parameters Passenger comfort Polygons Railroad wheels Railway wheel polygonization Rotating machine fault diagnosis Vibration Wear PSD Rotating machine fault diagnosis CRH1/CRH2/CRH3/CRH5 PWRW FSWT IVW FV Angle domain synchronous averaging technique Axle-box vibration acceleration ABVA OOR FE-SEA DAQ HHT SNR ADSAT Railway wheel polygonization RMS DTFT
ISSN:	0888-3270, 1096-1216
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Abstract	•It exploits the vertical axle-box vibration acceleration signal that it is helpful to simplify the hardware of monitoring system of high-speed train.•The proposed angular synchronous average technique perfectly enhances the fault-related signal of wheel polygon wear by mitigating the asynchronous coherent and random background noise.•The proposed method can detect the order and the rough degree of railway wheel polygonization fault in real-time. The polygon wear of railway wheel (PWRW) is a wear fault that is ubiquitous in railway vehicles. PWRW can induce a strong periodic excitation to both vehicle and track, which not only decreases passenger comfort but also is detrimental to the operational reliability and safety. Both the degree and the order of PWRW are important parameters used to quantify the fault. Because the fault-related components distribute at a wide range in the frequency domain, it is easy to alias with some radiated vibrations from vehicle and track components, which makes the on-board detection for both parameters of PWRW very difficult. To address the practical engineering problem, this paper proposes a detection framework based on the angle domain synchronous averaging technique (ADSAT). The detection method employs the vertical axle-box vibration acceleration (ABVA), which is easy to obtain and can also be used to monitor the conditions of axle-box bearings. The paper compares the proposed and traditional methods. The results reveal that the proposed method not only achieves the order detection which the traditional method cannot, but also mitigates the influence of background noise. The feasibility and effectiveness of the proposed method to improve the detection accuracy of PWRW is demonstrated through simulation and real field investigations.
AbstractList	The polygon wear of railway wheel (PWRW) is a wear fault that is ubiquitous in railway vehicles. PWRW can induce a strong periodic excitation to both vehicle and track, which not only decreases passenger comfort but also is detrimental to the operational reliability and safety. Both the degree and the order of PWRW are important parameters used to quantify the fault. Because the fault-related components distribute at a wide range in the frequency domain, it is easy to alias with some radiated vibrations from vehicle and track components, which makes the on-board detection for both parameters of PWRW very difficult. To address the practical engineering problem, this paper proposes a detection framework based on the angle domain synchronous averaging technique (ADSAT). The detection method employs the vertical axle-box vibration acceleration (ABVA), which is easy to obtain and can also be used to monitor the conditions of axle-box bearings. The paper compares the proposed and traditional methods. The results reveal that the proposed method not only achieves the order detection which the traditional method cannot, but also mitigates the influence of background noise. The feasibility and effectiveness of the proposed method to improve the detection accuracy of PWRW is demonstrated through simulation and real field investigations. •It exploits the vertical axle-box vibration acceleration signal that it is helpful to simplify the hardware of monitoring system of high-speed train.•The proposed angular synchronous average technique perfectly enhances the fault-related signal of wheel polygon wear by mitigating the asynchronous coherent and random background noise.•The proposed method can detect the order and the rough degree of railway wheel polygonization fault in real-time. The polygon wear of railway wheel (PWRW) is a wear fault that is ubiquitous in railway vehicles. PWRW can induce a strong periodic excitation to both vehicle and track, which not only decreases passenger comfort but also is detrimental to the operational reliability and safety. Both the degree and the order of PWRW are important parameters used to quantify the fault. Because the fault-related components distribute at a wide range in the frequency domain, it is easy to alias with some radiated vibrations from vehicle and track components, which makes the on-board detection for both parameters of PWRW very difficult. To address the practical engineering problem, this paper proposes a detection framework based on the angle domain synchronous averaging technique (ADSAT). The detection method employs the vertical axle-box vibration acceleration (ABVA), which is easy to obtain and can also be used to monitor the conditions of axle-box bearings. The paper compares the proposed and traditional methods. The results reveal that the proposed method not only achieves the order detection which the traditional method cannot, but also mitigates the influence of background noise. The feasibility and effectiveness of the proposed method to improve the detection accuracy of PWRW is demonstrated through simulation and real field investigations.
ArticleNumber	107540
Author	Brooks, Peter Sun, Qi Chen, Chunjun Kemp, Andrew H.
Author_xml	– sequence: 1 givenname: Qi surname: Sun fullname: Sun, Qi email: SsSunqiqi@163.com organization: School of Mechanical Engineering, Southwest Jiaotong University, Chengdu, Sichuang, China – sequence: 2 givenname: Chunjun orcidid: 0000-0002-3110-7316 surname: Chen fullname: Chen, Chunjun organization: School of Mechanical Engineering, Southwest Jiaotong University, Chengdu, Sichuang, China – sequence: 3 givenname: Andrew H. orcidid: 0000-0003-0362-7653 surname: Kemp fullname: Kemp, Andrew H. organization: Institute for High Speed Rail and System Integration, University of Leeds, Leeds, UK – sequence: 4 givenname: Peter surname: Brooks fullname: Brooks, Peter organization: Institute for High Speed Rail and System Integration, University of Leeds, Leeds, UK
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Cites_doi	10.1006/jsvi.1999.2590 10.1016/j.wear.2017.12.023 10.1243/0954409001531351 10.1631/jzus.A1400233 10.1080/23248378.2014.994260 10.1016/j.ymssp.2020.106654 10.1080/00423110500184649 10.1080/00423114.2018.1439589 10.1016/0022-460X(88)90434-8 10.1007/s004190050208 10.1080/00423114.2012.695022 10.1533/9781845696788.1.245
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Keywords	PSD Rotating machine fault diagnosis CRH1/CRH2/CRH3/CRH5 PWRW FSWT IVW FV Angle domain synchronous averaging technique Axle-box vibration acceleration ABVA OOR FE-SEA DAQ HHT SNR ADSAT Railway wheel polygonization RMS DTFT
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Snippet	•It exploits the vertical axle-box vibration acceleration signal that it is helpful to simplify the hardware of monitoring system of high-speed train.•The... The polygon wear of railway wheel (PWRW) is a wear fault that is ubiquitous in railway vehicles. PWRW can induce a strong periodic excitation to both vehicle...
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StartPage	107540
SubjectTerms	Angle domain synchronous averaging technique Axle-box vibration acceleration Axleboxes Background noise Field investigations Mechanical components Parameters Passenger comfort Polygons Railroad wheels Railway wheel polygonization Rotating machine fault diagnosis Vibration Wear
Title	An on-board detection framework for polygon wear of railway wheel based on vibration acceleration of axle-box
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