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An approach for mechanical fault classification based on generalized discriminant analysis

LI Wei-hua, SHI Tie-lin, YANG Shu-zi

Frontiers of Mechanical Engineering 2006, Volume 1, Issue 3,   Pages 292-298 doi: 10.1007/s11465-006-0022-2

Abstract: To deal with pattern classification of complicated mechanical faults, an approach to multi-faults classificationKPCA is good at detection of machine abnormality while GDA performs well in multi-faults classificationWhen the proposed method is applied to air compressor condition classification and gear fault classification, an excellent performance in complicated multi-faults classification is presented.

Keywords： generalized discriminant     non-separable     abnormality     classification     multi-faults classification    

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Fault classification and reconfiguration of distribution systems using equivalent capacity margin method

K. Sathish KUMAR, T. JAYABARATHI

Frontiers in Energy 2012, Volume 6, Issue 4,   Pages 394-402 doi: 10.1007/s11708-012-0211-0

Abstract: This paper investigates the capability of support vector machines (SVM) for prediction of fault classificationHere, the SVM has been used as a classification.An equation has been developed for the prediction of the fault in the power system based on the developed

Keywords： vector machines (SVM)     structural risk minimization (SRM)     equivalent capacity margin (ECM)     restoration     faultclassification    

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

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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One-Variable Attack on The Industrial Fault Classification System and Its Defense Article

Yue Zhuo, Yuri A.W. Shardt, Zhiqiang Ge

Engineering 2022, Volume 19, Issue 12,   Pages 240-251 doi: 10.1016/j.eng.2021.07.033

Abstract:

Recently developed fault classification methods for industrial processes are mainly data-driven.Notably, models based on deep neural networks have significantly improved fault classification accuracyclassification system: Only one variable can be perturbed to craft adversarial samples.types, which can help understand the geometric characteristics of fault classification systems.For industrial fault classification systems, the attack success rate of our method is close to (on TEP

Keywords： Adversarial samples     Black-box attack     Industrial data security     Fault classification system    

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enhanced active learning mixture discriminant analysis model and its application for semi-supervised faultclassification Research Article

Weijun WANG, Yun WANG, Jun WANG, Xinyun FANG, Yuchen HE

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 12,   Pages 1814-1827 doi: 10.1631/FITEE.2200053

Abstract: the limited sampling condition or expensive laboratory analysis, which may lead to deterioration of classification

Keywords： Semi-supervised     Active learning     Ensemble learning     Mixture discriminant analysis     Fault classification    

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Development of a new method for RMR and Q classification method to optimize support system in tunneling

Asghar RAHMATI,Lohrasb FARAMARZI,Manouchehr SANEI

Frontiers of Structural and Civil Engineering 2014, Volume 8, Issue 4,   Pages 448-455 doi: 10.1007/s11709-014-0262-x

Abstract: Rock mass classification system is very suitable for various engineering design and stability analysisclassification method is confirmed by Japan Highway Public Corporation that this method can figure outThese equations as a new method were able to optimize the support system for and classification systemsFrom classification and its application in these case studies, it is pointed out that the methodfor the design of support systems in underground working is more reliable than the and classification

Keywords： JH classification     Q and RMR classification     new method    

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Molecular classification and precision therapy of cancer: immune checkpoint inhibitors

Yingyan Yu

Frontiers of Medicine 2018, Volume 12, Issue 2,   Pages 229-235 doi: 10.1007/s11684-017-0581-0

Abstract: Taking gastric cancer as an example, its molecular classification is built on genome abnormalities, butSubsequently, by using their findings, oncologists will carry out targeted therapy based on molecular classification

Keywords： molecular classification     precision medicine     pembrolizumab     PD-1/PD-L1     MSI-H    

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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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EAI-oriented information classification code system in manufacturing enterprises

WANG Junbiao, DENG Hu, JIANG Jianjun, YANG Binghong, WANG Bailing

Frontiers of Mechanical Engineering 2008, Volume 3, Issue 1,   Pages 81-85 doi: 10.1007/s11465-008-0011-8

Abstract: Although the traditional information classification coding system in manufacturing enterprises (MEs)integration (EAI) in manufacturing enterprises, an enterprise application integration oriented information classificationEAIO-ICCS expands the connotation of the information classification code system and assures the identity

Keywords： EAI     EAIO-ICCS     management     classification     connotation    

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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: Rotating machine fault signal extraction becomes increasingly important in practical engineering applicationsHowever, fault signals with low signal-to-noise ratios (SNRs) are difficult to extract, especially atthe early stage of fault diagnosis.As a result, fault signals with high SNRs can be obtained for fault feature extraction.

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 faultAs 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.experimental verifications confirm that the proposed strategy is more effective for enhancing the bearing fault

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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Title Author Date Type Operation

An approach for mechanical fault classification based on generalized discriminant analysis

LI Wei-hua, SHI Tie-lin, YANG Shu-zi

Journal Article

Fault classification and reconfiguration of distribution systems using equivalent capacity margin method

K. Sathish KUMAR, T. JAYABARATHI

Journal Article

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

Journal Article

One-Variable Attack on The Industrial Fault Classification System and Its Defense

Yue Zhuo, Yuri A.W. Shardt, Zhiqiang Ge

Journal Article

enhanced active learning mixture discriminant analysis model and its application for semi-supervised faultclassification

Weijun WANG, Yun WANG, Jun WANG, Xinyun FANG, Yuchen HE

Journal Article

Development of a new method for RMR and Q classification method to optimize support system in tunneling

Asghar RAHMATI,Lohrasb FARAMARZI,Manouchehr SANEI

Journal Article

Molecular classification and precision therapy of cancer: immune checkpoint inhibitors

Yingyan Yu

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

EAI-oriented information classification code system in manufacturing enterprises

WANG Junbiao, DENG Hu, JIANG Jianjun, YANG Binghong, WANG Bailing

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