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Unknown fault detection for EGT multi-temperature signals based on self-supervised feature learning and

Frontiers in Energy 2023, Volume 17, Issue 4,   Pages 527-544 doi: 10.1007/s11708-023-0880-x

Abstract: The scarcity of fault data and a large amount of normal data in practical use pose great challenges tofault detection algorithms.Therefore, a fault detection method based on self-supervised feature learning was proposed to address

Keywords： fault detection     unary classification     self-supervised representation learning     multivariate nonlinear    

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Multiple fault separation and detection by joint subspace learning for the health assessment of wind

Zhaohui DU, Xuefeng CHEN, Han ZHANG, Yanyang ZI, Ruqiang YAN

Frontiers of Mechanical Engineering 2017, Volume 12, Issue 3,   Pages 333-347 doi: 10.1007/s11465-017-0435-0

Abstract: Thus, this paper presents a joint subspace learning-based multiple fault detection (JSL-MFD) techniqueto construct different subspaces adaptively for different fault patterns.Consequently, multiple fault patterns are reliably identified by utilizing the maximum fault informationThe superiority of JSL-MFD in multiple fault separation and detection is comprehensively investigatedand enhancing detection accuracy.

Keywords： joint subspace learning     multiple fault diagnosis     sparse decomposition theory     coupling feature separation    

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Application of Uncertainty Reasoning Theory to Satellite Fault Detection and Diagnosis

Yang Tianshe,Li Huaizu,Cao Yuping

Strategic Study of CAE 2003, Volume 5, Issue 2,   Pages 68-74

Abstract: The reason is that detection and diagnosis of these faults requires reasonable reasoning and fault-tolerant

Keywords： satellite     fault     detection     diagnosis     uncertainty reasoning theory    

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The On-line Fault Detection of the Wheelset Bearing Based

Huang Cailun ,Yu Xiaohua ,Chen Anhua ,Zhang Jian

Strategic Study of CAE 2007, Volume 9, Issue 7,   Pages 61-64

Abstract:

The fault of wheelset bearing is one of the most important factors whichThe experiments indicate that the abnormity of wheelset bearing high-accuracy detection can be realized

Keywords： wheelset bearing     spectrum zoom     abnormity     detection    

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Extended stochastic resonance (SR) and its applications in weak mechanical signal processing

Niaoqing HU, Min CHEN, Guojun QIN, Lurui XIA, Zhongyin PAN, Zhanhui FENG,

Frontiers of Mechanical Engineering 2009, Volume 4, Issue 4,   Pages 450-461 doi: 10.1007/s11465-009-0072-3

Abstract: This paper presents a method based on stochastic resonance (SR) to detect weak fault signal.applied to extract the weak characteristic component from heavy noise to indicate the little crack fault

Keywords： extended stochastic resonance (SR)     stability analysis of SR     scale transform     weak signal detection     incipientfault detection     envelope analysis    

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Active fault-tolerant tracking control of a quadrotorwith model uncertainties and actuator faults None

Yu-jiang ZHONG, Zhi-xiang LIU, You-min ZHANG, Wei ZHANG, Jun-yi ZUO

Frontiers of Information Technology & Electronic Engineering 2019, Volume 20, Issue 1,   Pages 95-106 doi: 10.1631/FITEE.1800570

Abstract:

This paper presents a reliable active fault-tolerant tracking control system (AFTTCS) for actuatorFurthermore, a fault detection and diagnosis estimator is constructed to diagnose lossof-control-effectivenessBased on the fault information, a fault compensation term is added to the control law to compensate for

Keywords： Model reference adaptive control     Neural network     Quadrotor     Fault-tolerant control     Fault detection and    

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Three-dimensional finite difference analysis of shallow sprayed concrete tunnels crossing a reverse faultor a normal fault: A parametric study

Masoud RANJBARNIA, Milad ZAHERI, Daniel DIAS

Frontiers of Structural and Civil Engineering 2020, Volume 14, Issue 4,   Pages 998-1011 doi: 10.1007/s11709-020-0621-8

Abstract: In this paper, the effects of a reverse and a normal fault movement on a transversely crossing shallowas the sprayed concrete thickness, the geo-mechanical properties of soil, the tunnel depth, and the fault

Keywords： urban tunnel     sprayed concrete     reverse fault     normal fault     finite difference analysis    

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Identification of faults through wavelet transform vis-à-vis fast Fourier transform of noisy vibration signals emanated from defective rolling element bearings

Deepak PALIWAL,Achintya CHOUDHURY,T. GOVANDHAN

Frontiers of Mechanical Engineering 2014, Volume 9, Issue 2,   Pages 130-141 doi: 10.1007/s11465-014-0298-6

Abstract:

Fault diagnosis of rolling element bearings requires efficient signal processing techniques.For this purpose, the performances of envelope detection with fast Fourier transform (FFT) and continuousproposed wavelets overcomes the short coming of FFT while processing a noisy vibration signals for defect detection

Keywords： Fault detection     spline wavelet     continuous wavelet transform     fast Fourier transform    

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Basic research on machinery fault diagnostics: Past, present, and future trends

Xuefeng CHEN, Shibin WANG, Baijie QIAO, Qiang CHEN

Frontiers of Mechanical Engineering 2018, Volume 13, Issue 2,   Pages 264-291 doi: 10.1007/s11465-018-0472-3

Abstract:

Machinery fault diagnosis has progressed over the past decades with the evolution of machineries inHigh-value machineries require condition monitoring and fault diagnosis to guarantee their designed functionsResearch on machinery Fault diagnostics has grown rapidly in recent years.The review discusses the special contributions of Chinese scholars to machinery fault diagnostics.On the basis of the review of basic theory of machinery fault diagnosis and its practical applications

Keywords： fault diagnosis     fault mechanism     feature extraction     signal processing     intelligent diagnostics    

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Machine learning for fault diagnosis of high-speed train traction systems: A review

Frontiers of Engineering Management doi: 10.1007/s42524-023-0256-2

Abstract: Therefore, performing fault monitoring and diagnosis on the traction system of the HST is necessary.various pattern recognition tasks and has demonstrated an excellent performance in traction system faultprimarily aims to review the research and application of machine learning in the field of traction system faultThen, the research and application of machine learning in traction system fault diagnosis are comprehensivelyFinally, the challenges for accurate fault diagnosis under actual operating conditions are revealed,

Keywords： high-speed train     traction systems     machine learning     fault diagnosis    

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Acoustic fault signal extraction via the line-defect phononic crystals

Frontiers of Mechanical Engineering 2022, Volume 17, Issue 1,   Pages 10-10 doi: 10.1007/s11465-021-0666-y

Abstract: However, fault signals with low signal-to-noise ratios (SNRs) are difficult to extract, especially atthe early stage of fault diagnosis.phononic crystals (PCs) consisting of periodic acrylic tubes with slit are proposed for weak signal detectionAs a result, fault signals with high SNRs can be obtained for fault feature extraction.The effectiveness of weak harmonic and periodic impulse signal detection via line-defect PCs are investigated

Keywords： phononic crystals     line-defect     fault signal extraction     acoustic enhancement    

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Iterative HOEO fusion strategy: a promising tool for enhancing bearing fault feature

Frontiers of Mechanical Engineering 2023, Volume 18, Issue 1, doi: 10.1007/s11465-022-0725-z

Abstract: energy operator (EO) and its variants have received considerable attention in the field of bearing faultfeature detection.As a result, the fault-related transients strengthened by these improved EO techniques are still subjectTo address these issues, this paper presents a novel EO fusion strategy for enhancing the bearing faultThird, the intrinsic manifolds are weighted to recover the fault-related transients.

Keywords： higher order energy operator     fault diagnosis     manifold learning     rolling element bearing     information    

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Deep convolutional tree-inspired network: a decision-tree-structured neural network for hierarchical fault

Frontiers of Mechanical Engineering 2021, Volume 16, Issue 4,   Pages 814-828 doi: 10.1007/s11465-021-0650-6

Abstract: The fault diagnosis of bearings is crucial in ensuring the reliability of rotating machinery.However, the inexplicability and low generalization ability of fault diagnosis models still bar themneural network, that is, the deep convolutional tree-inspired network (DCTN), for the hierarchical faultunique advantages in 1) the hierarchical structure that can support more accuracy and comprehensive faultThe multiclass fault diagnosis case and cross-severity fault diagnosis case are executed on a multicondition

Keywords： bearing     cross-severity fault diagnosis     hierarchical fault diagnosis     convolutional neural network    

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A new automatic convolutional neural network based on deep reinforcement learning for fault diagnosis

Frontiers of Mechanical Engineering 2022, Volume 17, Issue 2, doi: 10.1007/s11465-022-0673-7

Abstract: Convolutional neural network (CNN) has achieved remarkable applications in fault diagnosis.Tuning requires considerable experiences on the knowledge on CNN training and fault diagnosis, and isTo solve this problem, this paper proposes a novel automatic CNN (ACNN) for fault diagnosis, which canThe results show that ACNN outperforms these HPO and ML/DL methods, validating its potential in fault

Keywords： deep reinforcement learning     hyper parameter optimization     convolutional neural network     fault diagnosis    

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Gear fault diagnosis using gear meshing stiffness identified by gearbox housing vibration signals

Frontiers of Mechanical Engineering 2022, Volume 17, Issue 4, doi: 10.1007/s11465-022-0713-3

Abstract: Gearbox fault diagnosis based on vibration sensing has drawn much attention for a long time.Numerical simulation and experimental results demonstrate the proposed method can realize gear faultThe identified GMS has a clear physical meaning and is thus very useful for fault diagnosis of the complicated

Keywords： gearbox fault diagnosis     meshing stiffness     identification     transfer path     signal processing    

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Title Author Date Type Operation

Unknown fault detection for EGT multi-temperature signals based on self-supervised feature learning and

Journal Article

Multiple fault separation and detection by joint subspace learning for the health assessment of wind

Zhaohui DU, Xuefeng CHEN, Han ZHANG, Yanyang ZI, Ruqiang YAN

Journal Article

Application of Uncertainty Reasoning Theory to Satellite Fault Detection and Diagnosis

Yang Tianshe,Li Huaizu,Cao Yuping

Journal Article

The On-line Fault Detection of the Wheelset Bearing Based

Huang Cailun ,Yu Xiaohua ,Chen Anhua ,Zhang Jian

Journal Article

Extended stochastic resonance (SR) and its applications in weak mechanical signal processing

Niaoqing HU, Min CHEN, Guojun QIN, Lurui XIA, Zhongyin PAN, Zhanhui FENG,

Journal Article

Active fault-tolerant tracking control of a quadrotorwith model uncertainties and actuator faults

Yu-jiang ZHONG, Zhi-xiang LIU, You-min ZHANG, Wei ZHANG, Jun-yi ZUO

Journal Article

Three-dimensional finite difference analysis of shallow sprayed concrete tunnels crossing a reverse faultor a normal fault: A parametric study

Masoud RANJBARNIA, Milad ZAHERI, Daniel DIAS

Journal Article

Identification of faults through wavelet transform vis-à-vis fast Fourier transform of noisy vibration signals emanated from defective rolling element bearings

Deepak PALIWAL,Achintya CHOUDHURY,T. GOVANDHAN

Journal Article

Basic research on machinery fault diagnostics: Past, present, and future trends

Xuefeng CHEN, Shibin WANG, Baijie QIAO, Qiang CHEN

Journal Article

Machine learning for fault diagnosis of high-speed train traction systems: A review

Journal Article

Acoustic fault signal extraction via the line-defect phononic crystals

Journal Article

Iterative HOEO fusion strategy: a promising tool for enhancing bearing fault feature

Journal Article

Deep convolutional tree-inspired network: a decision-tree-structured neural network for hierarchical fault

Journal Article

A new automatic convolutional neural network based on deep reinforcement learning for fault diagnosis

Journal Article

Gear fault diagnosis using gear meshing stiffness identified by gearbox housing vibration signals

Journal Article