Výsledky vyhledávání - "stacked sparse autoencoder–based deep neural network"

Construction of a Sensitive and Speed Invariant Gearbox Fault Diagnosis Model Using an Incorporated Utilizing Adaptive Noise Control and a Stacked Sparse Autoencoder-Based Deep Neural Network

Autoři: Cong Dai Nguyen Alexander E. Prosvirin Cheol Hong Kim a další

Zdroj: Sensors, Vol 21, Iss 1, p 18 (2020)

Témata: adaptive noise reducer, Gaussian reference signal, gearbox fault diagnosis, stacked sparse autoencoder–based deep neural network, varying rotational speed, Chemical technology, TP1-1185

Popis souboru: electronic resource

Relation: https://www.mdpi.com/1424-8220/21/1/18; https://doaj.org/toc/1424-8220

Přístupová URL adresa: https://doaj.org/article/0655be0ec3ba4534af97edb245871774

Reliable Fault Diagnosis of Rotary Machine Bearings Using a Stacked Sparse Autoencoder‐Based Deep Neural Network

Autoři: Muhammad Sohaib Jong-Myon Kim

Zdroj: Shock and Vibration, Vol 2018 (2018)

Témata: Physics, QC1-999, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Popis souboru: text/xhtml

Přístupová URL adresa: http://downloads.hindawi.com/journals/sv/2018/2919637.pdf
https://doaj.org/article/522d93384ff848a29088a01c8193d071
https://downloads.hindawi.com/journals/sv/2018/2919637.pdf
https://paperity.org/p/129818144/reliable-fault-diagnosis-of-rotary-machine-bearings-using-a-stacked-sparse-autoencoder
https://www.hindawi.com/journals/sv/2018/2919637/
https://core.ac.uk/display/158441758
http://downloads.hindawi.com/journals/sv/2018/2919637.pdf

Combustion stability monitoring through flame imaging and stacked sparse autoencoder based deep neural network

Autoři: Jian Li Yuwei Wang Md. Moinul Hossain a další

Přispěvatelé: Jian Li Yuwei Wang Md. Moinul Hossain a další

Zdroj: Applied Energy. 259:114159

Témata: 13. Climate action, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Popis souboru: application/pdf

Přístupová URL adresa: https://kar.kent.ac.uk/79003/
https://ideas.repec.org/a/eee/appene/v259y2020ics030626191931846x.html
https://pubag.nal.usda.gov/catalog/6761807
https://www.sciencedirect.com/science/article/pii/S030626191931846X

Reliable Fault Diagnosis of Rotary Machine Bearings Using a Stacked Sparse Autoencoder-Based Deep Neural Network.

Autoři: Sohaib, Muhammad Kim, Jong-Myon

Zdroj: Shock & Vibration; 5/7/2018, p1-11, 11p

Témata: ROTARY combustion engines, FAULT diagnosis, NEURAL circuitry, COST effectiveness, ALGORITHMS

Construction of a Sensitive and Speed Invariant Gearbox Fault Diagnosis Model Using an Incorporated Utilizing Adaptive Noise Control and a Stacked Sparse Autoencoder-Based Deep Neural Network.

Autoři: Nguyen, Cong Dai Prosvirin, Alexander E. Kim, Cheol Hong a další

Zdroj: Sensors (14248220); Jan2021, Vol. 21 Issue 1, p18, 1p

Témata: FAULT diagnosis, NOISE control, ADAPTIVE control systems, GEARBOXES, NATURAL language processing

Determination of Coal and Biomass Co-Combustion Process States Using Convolutional Neural Networks.

Autoři: Kotyra, Andrzej Gromaszek, Konrad

Zdroj: Energies (19961073); Oct2025, Vol. 18 Issue 19, p5219, 17p

Témata: COAL, CO-combustion, CONVOLUTIONAL neural networks, HEAT of combustion, MACHINE learning, EMISSION control, BIOMASS, FLAME photometry

A deep learning framework for gender sensitive speech emotion recognition based on MFCC feature selection and SHAP analysis.

Autoři: Hu, Qingqing Peng, Yiran Zheng, Zhong

Zdroj: Scientific Reports; 8/5/2025, Vol. 15 Issue 1, p1-19, 19p

Témata: EMOTION recognition, DEEP learning, NATURAL language processing, RECURRENT neural networks, LONG short-term memory, CONVOLUTIONAL neural networks

Exploration of Unsupervised Deep Learning-Based Gear Fault Detection for Wind Turbine Gearboxes.

Autoři: Kiczek, Bartłomiej Batsch, Michał

Zdroj: Energies (19961073); Jul2025, Vol. 18 Issue 14, p3630, 18p

Témata: MACHINE learning, WIND turbines, DEEP learning, ARTIFICIAL neural networks, GEARING machinery vibration, DIAGNOSTIC examinations, VIBRATION measurements

An adaptive hierarchical hybrid kernel ELM optimized by aquila optimizer algorithm for bearing fault diagnosis.

Autoři: Yan, Hao Shang, Liangliang Chen, Wan a další

Zdroj: Scientific Reports; 4/8/2025, Vol. 15 Issue 1, p1-26, 26p

Témata: EXTREME learning machines, MACHINE learning, ARTIFICIAL intelligence, FAULT diagnosis, AUTOENCODERS

BEARING FAULT DETECTION BY USING AUTOENCODER CONVOLUTIONAL NEURAL NETWORK.

Alternate Title: ВИЯВЛЕННЯ НЕСПРАВНОСТІ ПІДШИПНИКА ЗА ДОПОМОГОЮ ЗГОРТКОВОЇ НЕЙРОННОЇ МЕРЕЖІ АВТОКОДУВАЛЬНИКА. (Ukrainian)

Autoři: K., Kysarin M.

Zdroj: Radio Electronics, Computer Science, Control; 2025, Issue 2, p116-125, 10p

Témata: AUTOENCODERS, CONVOLUTIONAL neural networks, MACHINE learning, OPTIMIZATION algorithms, FAULT diagnosis, MECHANICAL vibration research, NONDESTRUCTIVE testing

Fault Diagnosis of Mechanical Rolling Bearings Using a Convolutional Neural Network–Gated Recurrent Unit Method with Envelope Analysis and Adaptive Mean Filtering.

Autoři: Zhu, Huiyi Sui, Zhen Xu, Jianliang a další

Zdroj: Processes; Dec2024, Vol. 12 Issue 12, p2845, 18p

Témata: FAULT diagnosis, CONVOLUTIONAL neural networks, ADAPTIVE filters, MECHANICAL efficiency, ROTATING machinery, ROLLER bearings

Enhancing Accuracy of Flame Equivalence Ratio Measurements: An Attention-Based Convolutional Neural Network Approach for Overcoming Limitations in Traditional Color Modeling.

Autoři: Zheng, Lukai Yang, Tiantian Liu, Wenjia a další

Zdroj: Sensors (14248220); Nov2024, Vol. 24 Issue 21, p6853, 14p

Témata: CONVOLUTIONAL neural networks, FEATURE extraction, ERROR rates, OBJECTIVITY, SUBJECTIVITY

Gear Fault Detection Method Based on Convex Hull Clustering of Autoencoder's Latent Space.

Autoři: Batsch, Michał Kiczek, Bartłomiej

Zdroj: Applied Sciences (2076-3417); Jun2024, Vol. 14 Issue 12, p5282, 21p

Témata: ARTIFICIAL neural networks, GENERATIVE adversarial networks, SUPERVISED learning, PRINCIPAL components analysis, SIGNAL processing, MACHINE learning

Iterative singular value decomposition-based in-band denoising approach with envelope order analysis for sun gear fault diagnosis of planetary system under varying speed.

Autoři: Fan, Hongwei Huang, Jiexiang Ren, Zhongfu a další

Zdroj: Journal of Low Frequency Noise, Vibration & Active Control; Jun2024, Vol. 43 Issue 2, p920-938, 19p

Témata: FAULT diagnosis, PLANETARY gearing, PLANETARY systems, SINGULAR value decomposition, HILBERT-Huang transform

Detection of Precursors of Thermoacoustic Instability in a Swirled Combustor Using Chaotic Analysis and Deep Learning Models.

Autoři: Xu, Boqi Wang, Zhiyu Zhou, Hongwu a další

Zdroj: Aerospace (MDPI Publishing); Jun2024, Vol. 11 Issue 6, p455, 24p

Témata: DEEP learning, COMBUSTION

RESEARCH ON COMBUSTION VISUALIZATION OF COAL-FIRED BOILERS BASED ON THERMAL IMAGING TECHNOLOGY.

Autoři: Zi-Guo ZHANG Liang PAN Hao WANG

Zdroj: Thermal Science; 2024, Vol. 28 Issue 3B, p2403-2412, 10p

Témata: THERMOGRAPHY, COAL-fired boilers, COMBUSTION, GAS furnaces, HEAT of combustion, INFRARED cameras, INFRARED imaging, BOILERS, COAL combustion

Condition-based maintenance using machine learning and role of interpretability: a review.

Autoři: Sharma, Jeetesh Mittal, Murari Lal Soni, Gunjan

Zdroj: International Journal of Systems Assurance Engineering & Management; Apr2024, Vol. 15 Issue 4, p1345-1360, 16p

Fault Diagnosis for Power Batteries Based on a Stacked Sparse Autoencoder and a Convolutional Block Attention Capsule Network.

Autoři: Zhou, Juan Zhang, Shun Wang, Peng

Zdroj: Processes; Apr2024, Vol. 12 Issue 4, p816, 19p

Témata: CAPSULE neural networks, FAULT diagnosis, ELECTRIC vehicle batteries, ELECTRIC vehicles, ELECTRIC power failures, ELECTRIC fault location, FAILURE mode & effects analysis

Fault identification with limited labeled data.

Autoři: Berenji, Amirhossein Taghiyarrenani, Zahra Rohani Bastami, Abbas

Zdroj: Journal of Vibration & Control; Apr2024, Vol. 30 Issue 7/8, p1502-1510, 9p

Témata: DEEP learning, FAULT diagnosis, ROLLER bearings

Open Set Bearing Fault Diagnosis with Domain Adaptive Adversarial Network under Varying Conditions.

Autoři: Zhang, Bo Li, Feixuan Ma, Ning a další

Zdroj: Actuators; Apr2024, Vol. 13 Issue 4, p121, 19p

Témata: FAULT diagnosis, MONITORING of machinery, DEEP learning, ROTATING machinery, KURTOSIS