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A multi-sensor relation model for recognizing and localizing faults of machines based on network analysis

Frontiers of Mechanical Engineering 2023, Volume 18, Issue 2, doi: 10.1007/s11465-022-0736-9

Abstract: Recently, advanced sensing techniques ensure a large number of multivariate sensing data for intelligent faultadvantage of obtaining accurate diagnosis results, multi-sensor fusion has long been studied in the faulttypes and localize fault sources with the help of multi-sensor relations (MSRs).First, an MSR model is developed to learn MSRs automatically and further obtain fault recognition resultsResults show the proposed method’s validity in diagnosing fault types and sources.

Keywords： fault recognition     fault localization     multi-sensor relations     network analysis     graph neural network    

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Fault Pattern Recognition of Rolling Bearing Based on Radial Basis Function Neural Networks

Lu Shuang,Zhang Zida,Li Meng

Strategic Study of CAE 2004, Volume 6, Issue 2,   Pages 56-60

Abstract: In the light of the theory of radial basis function neural networks, fault pattern of rolling bearingTheory and experiment show that the recognition of fault pattern of rolling bearing based on radial basis

Keywords： rolling bearing     vibration signal     AR model     RBF neural networks     pattern recognition    

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Multiobjective image recognition algorithm in the fully automatic die bonder

JIANG Kai, CHEN Hai-xia, YUAN Sen-miao

Frontiers of Mechanical Engineering 2006, Volume 1, Issue 3,   Pages 313-316 doi: 10.1007/s11465-006-0026-y

Abstract: It is a very important task to automatically fix the number of die in the image recognition system ofA multiobjective image recognition algorithm based on clustering Genetic Algorithm (GA), is proposedAs a result, time consumed by one image recognition is shortened, the performance of the image recognition

Keywords： clustering     different     recognition algorithm     Algorithm     multiobjective    

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Advances in tissue state recognition in spinal surgery: a review

Hao Qu, Yu Zhao

Frontiers of Medicine 2021, Volume 15, Issue 4,   Pages 575-584 doi: 10.1007/s11684-020-0816-3

Abstract: has become the focus of spinal surgery research so as to strengthen the objectivity of tissue state recognitionThis article reviews the progress of different tissue state recognition methods in spinal surgery and

Keywords： spinal surgery     tissue state recognition     image     force sensing     bioelectrical impedance    

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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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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.In recent years, machine learning has been widely used in various pattern recognition tasks and has demonstratedan excellent performance in traction system fault diagnosis.Then, 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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View-invariant human action recognition via robust locally adaptive multi-view learning

Jia-geng FENG,Jun XIAO

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 11,   Pages 917-920 doi: 10.1631/FITEE.1500080

Abstract: Human action recognition is currently one of the most active research areas in computer vision.However, some extrinsic factors are barriers for the development of action recognition; e.g., human actionsThus, view-invariant analysis becomes important for action recognition algorithms, and a number of researchersExperiments on three public view-invariant action recognition datasets, i.e., ViHASi, IXMAS, and WVU,proposed algorithm stably outperforms state-of-the-art counterparts and obtains about 6% improvement in recognition

Keywords： View-invariant     Action recognition     Multi-view learning     L1-norm     Local learning    

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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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Online recognition of drainage type based on UV-vis spectra and derivative neural network algorithm

Frontiers of Environmental Science & Engineering 2021, Volume 15, Issue 6, doi: 10.1007/s11783-021-1430-6

Abstract:

• UV-vis absorption analyzer was applied in drainage type online recognition

Keywords： Drainage online recognition     UV-vis spectra     Derivative spectrum     Convolutional neural network    

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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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Finite element simulation for elastic dislocation of the North-Tehran fault: The effects of geologic

Pooya ZAKIAN; Hossein ASADI HAYEH

Frontiers of Structural and Civil Engineering 2022, Volume 16, Issue 4,   Pages 533-549 doi: 10.1007/s11709-022-0802-8

Abstract: method for simulating the crustal deformation due to the dislocation of a segment of the North-Tehran faultIn this regard, a geological map of Karaj that includes the fault segment is utilized in order to createFirst, finite element analysis of homogeneous counterpart of the fault’s domain with two different sectionsThe fault was modeled with the existing heterogeneity of the domain having been considered.usefulness of the proposed models in the dislocation analysis for the Karaj segment of North-Tehran fault

Keywords： finite element method     fault dislocation     slip distribution     the North-Tehran fault     heterogeneity     geological    

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Title Author Date Type Operation

A multi-sensor relation model for recognizing and localizing faults of machines based on network analysis

Journal Article

Fault Pattern Recognition of Rolling Bearing Based on Radial Basis Function Neural Networks

Lu Shuang,Zhang Zida,Li Meng

Journal Article

Multiobjective image recognition algorithm in the fully automatic die bonder

JIANG Kai, CHEN Hai-xia, YUAN Sen-miao

Journal Article

Advances in tissue state recognition in spinal surgery: a review

Hao Qu, Yu Zhao

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

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

View-invariant human action recognition via robust locally adaptive multi-view learning

Jia-geng FENG,Jun XIAO

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

Online recognition of drainage type based on UV-vis spectra and derivative neural network algorithm

Journal Article

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

Journal Article

Finite element simulation for elastic dislocation of the North-Tehran fault: The effects of geologic

Pooya ZAKIAN; Hossein ASADI HAYEH

Journal Article