Multi-Condition-Fault-Diagnosis

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Multi-Condition-Fault-Diagnosis

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## Multi-Condition Fault Diagnosis: A Survey, Insights, and Prospects
We have released a review paper named [Multi-Condition Fault Diagnosis of Dynamic Systems: A Survey, Insights, and Prospects](https://arxiv.org/pdf/2412.19497) to the community.

In this review, we provide a comprehensive analysis of the literature on multi-condition fault diagnosis (MCFD), a rapidly evolving research area. To establish a clear foundation, we propose a mathematical definition of multi-condition scenarios. The paper categorizes MCFD methods, summarizes approximately 210 studies from the past two decades, and evaluates the metrics used to assess these methods. Additionally, we discuss the application scenarios, challenges, and future directions of MCFD research, aiming to offer a systematic and insightful overview for researchers and practitioners in the field.

To further support the community, we plan to continuously update this repository with newly collected articles and corresponding code implementations. We hope these efforts will foster collaboration and innovation in the field of MCFD. If you have any questions or suggestions, please feel free to reach out to us.

![image](https://github.com/user-attachments/assets/bbf18644-64c3-4db7-be43-af81ebd600d0)

### Different framworks in multi-condition fault diagnosis
| Symbol | `HF` | `LR` | `FG` | `IG` |
| --- | --- | --- | --- | --- | 
|Framework|Handcrafted Features|Learned Representations|Fusion-Guided|Identification-Guided|

### Citation
If this repository is helpful to you, please cite our survey.
```
@article{han2024multiconditionfaultdiagnosisdynamic,
  title={Multi-Condition Fault Diagnosis of Dynamic Systems: A Survey, Insights, and Prospects}, 
  author={Pengyu Han and Zeyi Liu and Xiao He and Steven X. Ding and Donghua Zhou},
  year={2024},
  eprint={2412.19497},
  archivePrefix={arXiv},
  url={https://arxiv.org/abs/2412.19497}, 
}
```

### Recent papers on MCFD (Updated on 2024 December)
| Title | Journal | Year |  Technical Roadmap | Code Availability|
| :----- | :------ | :-------: | :---: | --- |
| [Deep subdomain adversarial network with self-supervised learning for aero-engine high speed bearing fault diagnosis with unknown working conditions](https://linkinghub.elsevier.com/retrieve/pii/S0263224124015537)|Measurement|2024| `LR` |
| [Few-shot bearing fault diagnosis by semi-supervised meta-learning with graph convolutional neural network under variable working conditions](https://linkinghub.elsevier.com/retrieve/pii/S0263224124012879)|Measurement|2024| `LR` |
| [An optimized CNN-BiLSTM network for bearing fault diagnosis under multiple working conditions with limited training samples](https://linkinghub.elsevier.com/retrieve/pii/S0925231224000559)|Neurocomputing|2024| `LR` |
| [Cross-Domain Class Incremental Broad Network for Continuous Diagnosis of Rotating Machinery Faults Under Variable Operating Conditions](https://ieeexplore.ieee.org/document/10381829/)|IEEE Transactions on Industrial Informatics|2024| `LR` |
| [A Fault Diagnosis Method for Rotating Machinery by Multimode Feature Entropy and Mutual Cooperation Broad Learning System](https://ieeexplore.ieee.org/document/10363130/)|IEEE Sensors Journal|2024| `LR` |
| [A novel transformer-based few-shot learning method for intelligent fault diagnosis with noisy labels under varying working conditions](https://linkinghub.elsevier.com/retrieve/pii/S0951832024004721)|Reliability Engineering & System Safety|2024| `LR` |
| [Online Open-Circuit Fault Diagnosis for Neutral Point Clamped Inverter Based on an Improved Convolutional Neural Network and Sample Amplification Method Under Varying Operating Conditions](https://ieeexplore.ieee.org/document/10379190/)|IEEE Transactions on Instrumentation and Measurement|2024| `LR` |
| [ProbSparse Attention-Based Fault Diagnosis for Industrial Robots Under Different Working Conditions](https://ieeexplore.ieee.org/document/10465665/)|IEEE Transactions on Instrumentation and Measurement|2024| `LR` |
| [Contrastive feature-based learning-guided elevated deep reinforcement learning: Developing an imbalanced fault quantitative diagnosis under variable working conditions](https://linkinghub.elsevier.com/retrieve/pii/S0888327024000906)|Mechanical Systems and Signal Processing|2024| `LR` |
| [An Iterative Resampling Deep Decoupling Domain Adaptation method for class-imbalance bearing fault diagnosis under variant working conditions](https://linkinghub.elsevier.com/retrieve/pii/S0957417424011060)|Expert Systems with Applications|2024| `LR` | [Official](https://github.com/minelabwot/Decoupling-Deep-Domain-Adaptation-Method) |
| [PSNN-TADA: Prototype and Stochastic Neural Network-Based Twice Adversarial Domain Adaptation for Fault Diagnosis Under Varying Working Conditions](https://ieeexplore.ieee.org/document/10339383/)|IEEE Transactions on Instrumentation and Measurement|2024| `LR` |
| [Multi-modal data cross-domain fusion network for gearbox fault diagnosis under variable operating conditions](https://linkinghub.elsevier.com/retrieve/pii/S0952197624003944)|Engineering Applications of Artificial Intelligence|2024| `LR` |
| [Unknown working condition fault diagnosis of rotate machine without training sample based on local fault semantic attribute](https://linkinghub.elsevier.com/retrieve/pii/S1474034624001630)|Advanced Engineering Informatics|2024| `LR` |
| [Reciprocating compressors intelligent fault diagnosis under multiple operating conditions based on adaptive variable scale morphological filter](https://linkinghub.elsevier.com/retrieve/pii/S0263224123013428)|Measurement|2024| `HF` |
| [Interpretable multi-domain meta-transfer learning for few-shot fault diagnosis of rolling bearing under variable working conditions](https://iopscience.iop.org/article/10.1088/1361-6501/ad36d9)|Measurement Science and Technology|2024| `LR` |
| [CA-MSPNet: Multiscale Module and Coordinate Attention Mechanism Strategy Combined With ProtoNet for Gearbox Fault Diagnosis Using Limited Infrared Thermal Images Under Variable Working Conditions](https://ieeexplore.ieee.org/document/10677378/)|IEEE Transactions on Instrumentation and Measurement|2024| `LR` |
| [Low-Rank Constrained Multikernel General Parameterized Time-Frequency Transform and Its Application in Rotating Machine Fault Diagnosis Under Varying Speed Condition](https://ieeexplore.ieee.org/document/10680559/)|IEEE Transactions on Instrumentation and Measurement|2024| `HF` |
| [Semi-supervised diagnosis method for coupling faults of key rotating components based on EEMD-KPCA under cross working conditions](https://iopscience.iop.org/article/10.1088/1361-6501/ad076c)|Measurement Science and Technology|2024| `LR` |
| [A GTI&Ada-Act LMCNN Method for Intelligent Fault Diagnosis of Motor Rotor-Bearing Unit Under Variable Conditions](https://ieeexplore.ieee.org/document/10385175/)|IEEE Transactions on Instrumentation and Measurement|2024| `LR` |
| [Adaptive Multiscale Convolution Manifold Embedding Networks for Intelligent Fault Diagnosis of Servo Motor-Cylindrical Rolling Bearing Under Variable Working Conditions](https://ieeexplore.ieee.org/document/10266815/)|IEEE/ASME Transactions on Mechatronics|2024| `LR` |
| [PeriodNet: Noise-Robust Fault Diagnosis Method Under Varying Speed Conditions](https://ieeexplore.ieee.org/document/10130447/)|IEEE Transactions on Neural Networks and Learning Systems|2024| `LR` |
| [Fault Diagnosis of Rotating Machinery Toward Unseen Working Condition: A Regularized Domain Adaptive Weight Optimization](https://ieeexplore.ieee.org/document/10495728/)|IEEE Transactions on Industrial Informatics|2024| `LR` |
| [A multi-source domain information fusion network for rotating machinery fault diagnosis under variable operating conditions](https://linkinghub.elsevier.com/retrieve/pii/S1566253524000563)|Information Fusion|2024| `FG` |
| [Multi-source subdomain negative transfer suppression and multiple pseudo-labels guidance alignment: A method for fault diagnosis under cross-working conditions](https://linkinghub.elsevier.com/retrieve/pii/S0019057824003847)|ISA Transactions|2024| `FG` |
| [A gray texture image data-driven intelligent fault diagnosis method of induction motor rotor-bearing system under variable load conditions](https://linkinghub.elsevier.com/retrieve/pii/S0263224124006274)|Measurement|2024| `LR` |
| [A Flexible Probabilistic Framework With Concurrent Analysis of Continuous and Categorical Data for Industrial Fault Detection and Diagnosis](https://ieeexplore.ieee.org/document/10032730/)|IEEE Transactions on Industrial Informatics|2023| `LR` |
| [Multi-grained mode partition and robust fault diagnosis for multimode industrial processes](https://linkinghub.elsevier.com/retrieve/pii/S0951832022006263)|Reliability Engineering & System Safety|2023| `FG` |
| [Evidential Ensemble Preference-Guided Learning Approach for Real-Time Multimode Fault Diagnosis](https://ieeexplore.ieee.org/document/10342662/)|IEEE Transactions on Industrial Informatics|2023| `FG` |
| [Rotating Machinery Fault Diagnosis Under Multiple Working Conditions via a Time-Series Transformer Enhanced by Convolutional Neural Network](https://ieeexplore.ieee.org/document/10262178/)|IEEE Transactions on Instrumentation and Measurement|2023| `LR` |
| [A Multisource Domain Adaptation Network for Process Fault Diagnosis Under Different Working Conditions](https://ieeexplore.ieee.org/document/9849441/)|IEEE Transactions on Industrial Electronics|2023| `FG` |
| [A Meta-Learning Method for Electric Machine Bearing Fault Diagnosis Under Varying Working Conditions With Limited Data](https://ieeexplore.ieee.org/document/9749912/)|IEEE Transactions on Industrial Informatics|2023| `LR` |
| [Intelligent Fault Diagnosis of Gearbox Under Variable Working Conditions With Adaptive Intraclass and Interclass Convolutional Neural Network](https://ieeexplore.ieee.org/document/9670459/)|IEEE Transactions on Neural Networks and Learning Systems|2023| `LR` |
| [Mode-Decoupling Auto-Encoder for Machinery Fault Diagnosis Under Unknown Working Conditions](https://ieeexplore.ieee.org/document/10323261/)|IEEE Transactions on Industrial Informatics|2023| `LR` |
| [A reliable feature-assisted contrastive generalization net for intelligent fault diagnosis under unseen machines and working conditions](https://linkinghub.elsevier.com/retrieve/pii/S0888327022010792)|Mechanical Systems and Signal Processing|2023| `LR` |
| [Class Subdomain Adaptation Network for Bearing Fault Diagnosis Under Variable Working Conditions](https://ieeexplore.ieee.org/document/9999324/)|IEEE Transactions on Instrumentation and Measurement|2023| `LR` |
| [Deep imbalanced domain adaptation for transfer learning fault diagnosis of bearings under multiple working conditions](https://linkinghub.elsevier.com/retrieve/pii/S0951832022005075)|Reliability Engineering & System Safety|2023| `LR` |
| [TSN: A novel intelligent fault diagnosis method for bearing with small samples under variable working conditions](https://linkinghub.elsevier.com/retrieve/pii/S0951832023004891)|Reliability Engineering & System Safety|2023| `LR` |
| [An information-induced fault diagnosis framework generalizing from stationary to unknown nonstationary working conditions](https://linkinghub.elsevier.com/retrieve/pii/S0951832023002946)|Reliability Engineering & System Safety|2023| `LR` |
| [Cross-domain augmentation diagnosis: An adversarial domain-augmented generalization method for fault diagnosis under unseen working conditions](https://linkinghub.elsevier.com/retrieve/pii/S0951832023000868)|Reliability Engineering & System Safety|2023| `LR` |
| [Domain adaptation network base on contrastive learning for bearings fault diagnosis under variable working conditions](https://linkinghub.elsevier.com/retrieve/pii/S0957417422018206)|Expert Systems with Applications|2023| `LR` |
| [Domain augmentation generalization network for real-time fault diagnosis under unseen working conditions](https://linkinghub.elsevier.com/retrieve/pii/S0951832023001035)|Reliability Engineering & System Safety|2023| `LR` |
| [Domain fuzzy generalization networks for semi-supervised intelligent fault diagnosis under unseen working conditions](https://linkinghub.elsevier.com/retrieve/pii/S0888327023004879)|Mechanical Systems and Signal Processing|2023| `LR` |
| [Relationship Transfer Domain Generalization Network for Rotating Machinery Fault Diagnosis Under Different Working Conditions](https://ieeexplore.ieee.org/document/10018483/)|IEEE Transactions on Industrial Informatics|2023| `LR` |
| [Mutual-assistance semisupervised domain generalization network for intelligent fault diagnosis under unseen working conditions](https://linkinghub.elsevier.com/retrieve/pii/S0888327022011426)|Mechanical Systems and Signal Processing|2023| `LR` |
| [Multiscale Deep Graph Convolutional Networks for Intelligent Fault Diagnosis of Rotor-Bearing System Under Fluctuating Working Conditions](https://ieeexplore.ieee.org/document/9740445/)|IEEE Transactions on Industrial Informatics|2023| `LR` |
| [Passive Thermography Based Bearing Fault Diagnosis Using Transfer Learning With Varying Working Conditions](https://ieeexplore.ieee.org/document/9748172/)|IEEE Sensors Journal|2023| `LR` |
| [Intelligent fault diagnosis of planetary gearboxes under time-varying conditions based on dynamic adversarial balance adaptation with multi-label information confusion](https://iopscience.iop.org/article/10.1088/1361-6501/acc34a)|Measurement Science and Technology|2023| `LR` |
| [Multispectral Balanced Automatic Fault Diagnosis for Rolling Bearings under Variable Speed Conditions](https://www.hindawi.com/journals/schm/2023/9369850/)|Structural Control and Health Monitoring|2023| `LR` |
| [Synchro-Reassigned Extracting Transform: An Effective Tool for Rotating Machinery Fault Diagnosis Under Varying Speed Condition](https://ieeexplore.ieee.org/document/10254611/)|IEEE Transactions on Instrumentation and Measurement|2023| `HF` |
| [Intelligent fault diagnosis of gear crack based on side frequency feature under different working conditions](https://iopscience.iop.org/article/10.1088/1361-6501/acd9df)|Measurement Science and Technology|2023| `HF` |
| [Intelligent fault diagnosis of rotating machinery under varying working conditions with global-local neighborhood and sparse graphs embedding deep regularized autoencoder](https://linkinghub.elsevier.com/retrieve/pii/S0952197623007741)|Engineering Applications of Artificial Intelligence|2023| `LR` |
| [Bearing multi-fault diagnosis with iterative generalized demodulation guided by enhanced rotational frequency matching under time-varying speed conditions](https://linkinghub.elsevier.com/retrieve/pii/S0019057822003573)|ISA Transactions|2023| `HF` |
| [Novel Time-Frequency Mode Decomposition and Information Fusion for Bearing Fault Diagnosis Under Varying-Speed Condition](https://ieeexplore.ieee.org/document/10078305/)|IEEE Transactions on Instrumentation and Measurement|2023| `HF` |
| [Deep Adversarial Hybrid Domain-Adaptation Network for Varying Working Conditions Fault Diagnosis of High-Speed Train Bogie](https://ieeexplore.ieee.org/document/10124762/)|IEEE Transactions on Instrumentation and Measurement|2023| `LR` |
| [Vibration amplitude normalization enhanced fault diagnosis under conditions of variable speed and extremely limited samples](https://iopscience.iop.org/article/10.1088/1361-6501/aced4e)|Measurement Science and Technology|2023| `HF` |
| [A non-linear time-frequency tool for machinery fault diagnosis under varying speed condition](https://linkinghub.elsevier.com/retrieve/pii/S0888327022009177)|Mechanical Systems and Signal Processing|2023| `HF` |
| [Correlation analysis based relevant variable selection for wind turbine condition monitoring and fault diagnosis](https://linkinghub.elsevier.com/retrieve/pii/S2213138823004320)|Sustainable Energy Technologies and Assessments|2023| `LR` |
| [Category-aware dual adversarial domain adaptation model for rolling bearings fault diagnosis under variable conditions](https://iopscience.iop.org/article/10.1088/1361-6501/acd6ac)|Measurement Science and Technology|2023| `LR` |
| [Intelligent Fault Diagnosis of Bearings With Both Working Condition Variation and Target Data Scarcity](https://ieeexplore.ieee.org/document/10243087/)|IEEE Transactions on Instrumentation and Measurement|2023| `LR` |
| [Domain Adaptation Networks With Parameter-Free Adaptively Rectified Linear Units for Fault Diagnosis Under Variable Operating Conditions](https://ieeexplore.ieee.org/document/10210313/)|IEEE Transactions on Neural Networks and Learning Systems|2023| `LR` |
| [Decision Self-Regulating Network for Imbalanced Working Conditions Identification in the Application of Gearbox Intelligent Fault Diagnosis](https://ieeexplore.ieee.org/document/10192392/)|IEEE Transactions on Instrumentation and Measurement|2023| `FG` |
| [A Novel Meta-Learning Network With Adaptive Input Length and Attention Mechanism for Bearing Fault Diagnosis Under Different Working Conditions](https://ieeexplore.ieee.org/document/10285654/)|IEEE Sensors Journal|2023| `LR` |
| [VIT-GADG: A Generative Domain-Generalized Framework for Chillers Fault Diagnosis Under Unseen Working Conditions](https://ieeexplore.ieee.org/document/10216370/)|IEEE Transactions on Instrumentation and Measurement|2023| `LR` |
| [A hierarchical adversarial multi-target domain adaptation for gear fault diagnosis under variable working condition based on raw acoustic signal](https://linkinghub.elsevier.com/retrieve/pii/S0952197623006334)|Engineering Applications of Artificial Intelligence|2023| `LR` |
| [Intelligent Fault Diagnosis of Rolling Bearings Based on an Improved Empirical Wavelet Transform and ResNet Under Variable Conditions](https://ieeexplore.ieee.org/document/10251121/)|IEEE Sensors Journal|2023| `HF` |
| [Prior knowledge-embedded meta-transfer learning for few-shot fault diagnosis under variable operating conditions](https://linkinghub.elsevier.com/retrieve/pii/S0888327023003990)|Mechanical Systems and Signal Processing|2023| `LR` |
| [Deep continual transfer learning with dynamic weight aggregation for fault diagnosis of industrial streaming data under varying working conditions](https://linkinghub.elsevier.com/retrieve/pii/S1474034623000113)|Advanced Engineering Informatics|2023| `LR` |
| [Explainable Deep Ensemble Model for Bearing Fault Diagnosis Under Variable Conditions](https://ieeexplore.ieee.org/document/10144572/)|IEEE Sensors Journal|2023| `LR` |
| [A New Multisensor Partial Domain Adaptation Method for Machinery Fault Diagnosis Under Different Working Conditions](https://ieeexplore.ieee.org/document/10262195/)|IEEE Transactions on Instrumentation and Measurement|2023| `LR` |
| [Adaptive Class Center Generalization Network: A Sparse Domain-Regressive Framework for Bearing Fault Diagnosis Under Unknown Working Conditions](https://ieeexplore.ieee.org/document/10121353/)|IEEE Transactions on Instrumentation and Measurement|2023| `LR` |
| [Fractional Fourier and time domain recurrence plot fusion combining convolutional neural network for bearing fault diagnosis under variable working conditions](https://linkinghub.elsevier.com/retrieve/pii/S0951832022006913)|Reliability Engineering & System Safety|2023| `HF` |
| [Time-frequency Transformer with shifted windows for journal bearing-rotor systems fault diagnosis under multiple working conditions](https://webofscience.clarivate.cn/api/gateway?GWVersion=2&SrcAuth=DOISource&SrcApp=UA&KeyAID=10.1088%2F1361-6501%2Facd2f3&DestApp=DOI&SrcAppSID=USW2EC0A2DLzxEOLxu1E0KJJUW9iC&SrcJTitle=MEASUREMENT+SCIENCE+AND+TECHNOLOGY&DestDOIRegistrantName=IOP+Publishing)|MEASUREMENT SCIENCE AND TECHNOLOGY|2023| `HF` |
| [An improved GNN using dynamic graph embedding mechanism: A novel end-to-end framework for rolling bearing fault diagnosis under variable working conditions](https://linkinghub.elsevier.com/retrieve/pii/S0888327023004429)|Mechanical Systems and Signal Processing|2023| `LR` |
| [Fault transfer diagnosis of rolling bearings across multiple working conditions via subdomain adaptation and improved vision transformer network](https://linkinghub.elsevier.com/retrieve/pii/S1474034623002033)|Advanced Engineering Informatics|2023| `LR` |
| [Adaptive fault diagnosis method for rotating machinery with unknown faults under multiple working conditions](https://linkinghub.elsevier.com/retrieve/pii/S0278612522000449)|Journal of Manufacturing Systems|2022| `LR` |
| [A multi-level adaptation scheme for hierarchical bearing fault diagnosis under variable working conditions](https://linkinghub.elsevier.com/retrieve/pii/S0278612522001030)|Journal of Manufacturing Systems|2022| `LR` |
| [A novel method based on meta-learning for bearing fault diagnosis with small sample learning under different working conditions](https://www.sciencedirect.com/science/article/pii/S0888327021010803)|Mechanical Systems and Signal Processing|2022| `LR` |
| [Deep Negative Correlation Multisource Domains Adaptation Network for Machinery Fault Diagnosis Under Different Working Conditions](https://ieeexplore.ieee.org/document/9841514/)|IEEE/ASME Transactions on Mechatronics|2022| `FG` |
| [Intelligent Fault Diagnosis for Bearings of Industrial Robot Joints Under Varying Working Conditions Based on Deep Adversarial Domain Adaptation](https://ieeexplore.ieee.org/document/9733373/)|IEEE Transactions on Instrumentation and Measurement|2022| `LR` |
| [Imbalanced bearing fault diagnosis under variant working conditions using cost-sensitive deep domain adaptation network](https://linkinghub.elsevier.com/retrieve/pii/S0957417421017425)|Expert Systems with Applications|2022| `LR` |
| [Bearing Fault Diagnosis Under Variable Working Conditions Base on Contrastive Domain Adaptation Method](https://ieeexplore.ieee.org/document/9865985/)|IEEE Transactions on Instrumentation and Measurement|2022| `LR` |
| [Intelligent worm gearbox fault diagnosis under various working conditions using vibration, sound and thermal features](https://linkinghub.elsevier.com/retrieve/pii/S0003682X21005570)|Applied Acoustics|2022| `HF` |
| [A wavelet packet transform-based deep feature transfer learning method for bearing fault diagnosis under different working conditions](https://linkinghub.elsevier.com/retrieve/pii/S0263224122008090)|Measurement|2022| `LR` |
| [A Novel Fault Diagnosis Method Under Dynamic Working Conditions Based on a CNN With an Adaptive Learning Rate](https://ieeexplore.ieee.org/document/9780130/)|IEEE Transactions on Instrumentation and Measurement|2022| `LR` |
| [Across working conditions fault diagnosis for chillers based on IoT intelligent agent with deep learning model](https://linkinghub.elsevier.com/retrieve/pii/S0378778822003590)|Energy and Buildings|2022| `LR` |
| [Multisource Domain Feature Adaptation Network for Bearing Fault Diagnosis Under Time-Varying Working Conditions](https://ieeexplore.ieee.org/document/9761066/)|IEEE Transactions on Instrumentation and Measurement|2022| `LR` |
| [Multi-perspective deep transfer learning model: A promising tool for bearing intelligent fault diagnosis under varying working conditions](https://linkinghub.elsevier.com/retrieve/pii/S0950705122001824)|Knowledge-Based Systems|2022| `LR` |
| [A novel method based on deep transfer unsupervised learning network for bearing fault diagnosis under variable working condition of unequal quantity](https://linkinghub.elsevier.com/retrieve/pii/S0950705122001459)|Knowledge-Based Systems|2022| `LR` |
| [Transfer learning network for nuclear power plant fault diagnosis with unlabeled data under varying operating conditions](https://linkinghub.elsevier.com/retrieve/pii/S0360544222012610)|ENERGY|2022| `LR` |
| [Sparse and low-rank decomposition of the time-frequency representation for bearing fault diagnosis under variable speed conditions](https://linkinghub.elsevier.com/retrieve/pii/S0019057821005978)|ISA TRANSACTIONS|2022| `HF` |
| [Intelligent fault diagnosis of rolling bearings under varying operating conditions based on domain-adversarial neural network and attention mechanism](https://linkinghub.elsevier.com/retrieve/pii/S0019057822001896)|ISA Transactions|2022| `LR` |
| [Matching Synchroextracting Transform for Mechanical Fault Diagnosis Under Variable-Speed Conditions](https://ieeexplore.ieee.org/document/9645564/)|IEEE Transactions on Instrumentation and Measurement|2022| `HF` |
| [Prototype-guided bi-level adversarial domain adaptation network for intelligent fault diagnosis of rotating machinery under various working conditions](https://iopscience.iop.org/article/10.1088/1361-6501/ac819e)|Measurement Science and Technology|2022| `LR` |
| [A bearing fault diagnosis method without fault data in new working condition combined dynamic model with deep learning](https://linkinghub.elsevier.com/retrieve/pii/S1474034622002531)|Advanced Engineering Informatics|2022| `LR` |
| [Global contextual residual convolutional neural networks for motor fault diagnosis under variable-speed conditions](https://linkinghub.elsevier.com/retrieve/pii/S0951832022002599)|Reliability Engineering & System Safety|2022| `LR` |
| [Deep multiple auto-encoder with attention mechanism network: A dynamic domain adaptation method for rotary machine fault diagnosis under different working conditions](https://linkinghub.elsevier.com/retrieve/pii/S0950705122002891)|Knowledge-Based Systems|2022| `LR` |
| [Signal-Transformer: A Robust and Interpretable Method for Rotating Machinery Intelligent Fault Diagnosis Under Variable Operating Conditions](https://ieeexplore.ieee.org/document/9761922/)|IEEE Transactions on Instrumentation and Measurement|2022| `LR` |
| [A health image for deep learning-based fault diagnosis of a permanent magnet synchronous motor under variable operating conditions: Instantaneous current residual map](https://linkinghub.elsevier.com/retrieve/pii/S0951832022003398)|Reliability Engineering & System Safety|2022| `HF` |
| [Fault diagnosis of bearings in multiple working conditions based on adaptive time-varying parameters short-time Fourier synchronous squeeze transform](https://iopscience.iop.org/article/10.1088/1361-6501/ac8abf)|Measurement Science and Technology|2022| `HF` |
| [New Approach for Bearing Fault Diagnosis Based on Fractional Spatio-Temporal Sparse Low Rank Matrix Under Multichannel Time-Varying Speed Condition](https://ieeexplore.ieee.org/document/9693923/)|IEEE Transactions on Instrumentation and Measurement|2022| `HF` |
| [Parallel adversarial feature learning and enhancement of feature discriminability for fault diagnosis of a planetary gearbox under time-varying speed conditions](https://iopscience.iop.org/article/10.1088/1361-6501/ac8be9)|Measurement Science and Technology|2022| `LR` |
| [A class alignment method based on graph convolution neural network for bearing fault diagnosis in presence of missing data and changing working conditions](https://linkinghub.elsevier.com/retrieve/pii/S0263224122007552)|Measurement|2022| `LR` |
| [New transfer learning fault diagnosis method of rolling bearing based on ADC-CNN and LATL under variable conditions](https://linkinghub.elsevier.com/retrieve/pii/S0263224121014597)|Measurement|2022| `LR` |
| [Detection and Diagnosis of Bearing Faults Under Fixed and Time-Varying Speed Conditions Using Persistence Spectrum and Multi-Scale Structural Similarity Index](https://ieeexplore.ieee.org/document/9665766/)|IEEE Sensors Journal|2022| `HF` |
| [A Novel Transfer Learning Method Based on Conditional Variational Generative Adversarial Networks for Fault Diagnosis of Wind Turbine Gearboxes under Variable Working Conditions](https://www.mdpi.com/2071-1050/14/9/5441)|Sustainability|2022| `LR` |
| [Triplet metric driven multi-head GNN augmented with decoupling adversarial learning for intelligent fault diagnosis of machines under varying working condition](https://linkinghub.elsevier.com/retrieve/pii/S0278612521002211)|JOURNAL OF MANUFACTURING SYSTEMS|2022| `LR` |
| [L2-Norm Shapelet Dictionary Learning-Based Bearing-Fault Diagnosis in Uncertain Working Conditions](https://ieeexplore.ieee.org/document/9667367/)|IEEE Sensors Journal|2022| `LR` |
| [Graph Cardinality Preserved Attention Network for Fault Diagnosis of Induction Motor Under Varying Speed and Load Condition](https://ieeexplore.ieee.org/document/9540360/)|IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS|2022| `LR` |
| [A fault diagnosis method based on improved convolutional neural network for bearings under variable working conditions](https://linkinghub.elsevier.com/retrieve/pii/S0263224121007089)|Measurement|2021| `LR` |
| [A New Structured Domain Adversarial Neural Network for Transfer Fault Diagnosis of Rolling Bearings Under Different Working Conditions](https://ieeexplore.ieee.org/document/9309429/)|IEEE Transactions on Instrumentation and Measurement|2021| `LR` |
| [Domain Adversarial Graph Convolutional Network for Fault Diagnosis Under Variable Working Conditions](https://ieeexplore.ieee.org/document/9410617/)|IEEE Transactions on Instrumentation and Measurement|2021| `LR` | [Official](https://github.com/HazeDT/DAGCN) |
| [Domain Adaptation-Based Transfer Learning for Gear Fault Diagnosis Under Varying Working Conditions](https://ieeexplore.ieee.org/document/9146579/)|IEEE Transactions on Instrumentation and Measurement|2021| `LR` |
| [Dynamic Joint Distribution Alignment Network for Bearing Fault Diagnosis Under Variable Working Conditions](https://ieeexplore.ieee.org/document/9343309/)|IEEE Transactions on Instrumentation and Measurement|2021| `LR` |
| [Meta-learning for few-shot bearing fault diagnosis under complex working conditions](https://linkinghub.elsevier.com/retrieve/pii/S0925231221001818)|Neurocomputing|2021| `LR` |
| [IFDS: An Intelligent Fault Diagnosis System With Multisource Unsupervised Domain Adaptation for Different Working Conditions](https://ieeexplore.ieee.org/document/9599596/)|IEEE Transactions on Instrumentation and Measurement|2021| `LR` |
| [An Enhanced Multifeature Fusion Method for Rotating Component Fault Diagnosis in Different Working Conditions](https://ieeexplore.ieee.org/document/9601157/)|IEEE Transactions on Reliability|2021| `HF` |
| [Hybrid distance-guided adversarial network for intelligent fault diagnosis under different working conditions](https://linkinghub.elsevier.com/retrieve/pii/S0263224121002153)|Measurement|2021| `LR` |
| [A novel transfer learning method for bearing fault diagnosis under different working conditions](https://linkinghub.elsevier.com/retrieve/pii/S0263224120312677)|Measurement|2021| `LR` |
| [Intelligent Fault Diagnosis of Rotor-Bearing System Under Varying Working Conditions With Modified Transfer Convolutional Neural Network and Thermal Images](https://ieeexplore.ieee.org/document/9130129/)|IEEE Transactions on Industrial Informatics|2021| `LR` |
| [A Hybrid Generalization Network for Intelligent Fault Diagnosis of Rotating Machinery Under Unseen Working Conditions](https://ieeexplore.ieee.org/document/9452118/)|IEEE Transactions on Instrumentation and Measurement|2021| `LR` |
| [An Intelligent Fault Diagnosis Method Based on Domain Adaptation and Its Application for Bearings Under Polytropic Working Conditions](https://ieeexplore.ieee.org/document/9272995/)|IEEE Transactions on Instrumentation and Measurement|2021| `LR` |
| [Knowledge mapping-based adversarial domain adaptation: A novel fault diagnosis method with high generalizability under variable working conditions](https://linkinghub.elsevier.com/retrieve/pii/S0888327020304817)|Mechanical Systems and Signal Processing|2021| `LR` |
| [Intelligent fault diagnosis of planetary gearbox based on adaptive normalized CNN under complex variable working conditions and data imbalance](https://linkinghub.elsevier.com/retrieve/pii/S0263224121005406)|Measurement|2021| `LR` |
| [Discriminative feature-based adaptive distribution alignment (DFADA) for rotating machine fault diagnosis under variable working conditions](https://linkinghub.elsevier.com/retrieve/pii/S1568494620308243)|Applied Soft Computing|2021| `LR` |
| [A novel hybrid method based on KELM with SAPSO for fault diagnosis of rolling bearing under variable operating conditions](https://linkinghub.elsevier.com/retrieve/pii/S0263224121002827)|Measurement|2021| `LR` |
| [Fractional frequency band entropy for bearing fault diagnosis under varying speed conditions](https://linkinghub.elsevier.com/retrieve/pii/S0263224120312768)|Measurement|2021| `HF` |
| [An informative frequency band identification framework for gearbox fault diagnosis under time-varying operating conditions](https://linkinghub.elsevier.com/retrieve/pii/S0888327021001667)|Mechanical Systems and Signal Processing|2021| `HF` |
| [A deformable CNN-DLSTM based transfer learning method for fault diagnosis of rolling bearing under multiple working conditions](https://www.tandfonline.com/doi/full/10.1080/00207543.2020.1808261)|International Journal of Production Research|2021| `LR` |
| [Multiscale holospectrum convolutional neural network-based fault diagnosis of rolling bearings with variable operating conditions](https://iopscience.iop.org/article/10.1088/1361-6501/ac05f8)|Measurement Science and Technology|2021| `LR` |
| [Cumulative Distribution Sharpness Profiling Based Bearing Fault Diagnosis Framework Under Variable Speed Conditions](https://ieeexplore.ieee.org/document/9400423/)|IEEE Sensors Journal|2021| `LR` |
| [A new transferable bearing fault diagnosis method with adaptive manifold probability distribution under different working conditions](https://linkinghub.elsevier.com/retrieve/pii/S0263224120310885)|Measurement|2021| `LR` |
| [Order spectrum analysis enhanced by surrogate test and Vold-Kalman filtering for rotating machinery fault diagnosis under time-varying speed conditions](https://linkinghub.elsevier.com/retrieve/pii/S0888327020309717)|Mechanical Systems and Signal Processing|2021| `HF` |
| [Fault detection and diagnosis via standardized k nearest neighbor for multimode process](https://linkinghub.elsevier.com/retrieve/pii/S1876107019303736)|Journal of the Taiwan Institute of Chemical Engineers|2020| `FG` |
| [Fault detection and diagnosis based on transfer learning for multimode chemical processes](https://linkinghub.elsevier.com/retrieve/pii/S0098135419308762)|Computers & Chemical Engineering|2020| `LR` |
| [Intelligent fault diagnosis of rolling bearings based on normalized CNN considering data imbalance and variable working conditions](https://linkinghub.elsevier.com/retrieve/pii/S0950705120302884)|Knowledge-Based Systems|2020| `LR` |
| [Fault Diagnosis of Rotary Machine Bearings Under Inconsistent Working Conditions](https://ieeexplore.ieee.org/document/8799018/)|IEEE Transactions on Instrumentation and Measurement|2020| `HF` |
| [A novel bearing intelligent fault diagnosis framework under time-varying working conditions using recurrent neural network](https://linkinghub.elsevier.com/retrieve/pii/S0019057819304902)|ISA Transactions|2020| `LR` |
| [Fault diagnosis of rotating machinery components using a deep kernel extreme learning machine under different working conditions](https://iopscience.iop.org/article/10.1088/1361-6501/ab9037)|Measurement Science and Technology|2020| `LR` |
| [A novel geodesic flow kernel based domain adaptation approach for intelligent fault diagnosis under varying working condition](https://linkinghub.elsevier.com/retrieve/pii/S0925231219313554)|Neurocomputing|2020| `LR` |
| [A simple data augmentation algorithm and a self-adaptive convolutional architecture for few-shot fault diagnosis under different working conditions](https://linkinghub.elsevier.com/retrieve/pii/S0263224120300762)|Measurement|2020| `LR` |
| [A New Deep Transfer Learning Method for Bearing Fault Diagnosis Under Different Working Conditions](https://ieeexplore.ieee.org/document/8809786/)|IEEE Sensors Journal|2020| `LR` |
| [Intelligent fault diagnosis of mechanical equipment under varying working condition via iterative matching network augmented with selective Signal reuse strategy](https://linkinghub.elsevier.com/retrieve/pii/S027861252030176X)|Journal of Manufacturing Systems|2020| `LR` |
| [Ensemble transfer CNNs driven by multi-channel signals for fault diagnosis of rotating machinery cross working conditions](https://linkinghub.elsevier.com/retrieve/pii/S095070512030530X)|Knowledge-Based Systems|2020| `FG` |
| [A study on adaptation lightweight architecture based deep learning models for bearing fault diagnosis under varying working conditions](https://linkinghub.elsevier.com/retrieve/pii/S0957417420305340)|Expert Systems with Applications|2020| `LR` |
| [Probabilistic Latent Semantic Analysis-Based Gear Fault Diagnosis Under Variable Working Conditions](https://ieeexplore.ieee.org/document/8747421/)|IEEE Transactions on Instrumentation and Measurement|2020| `LR` |
| [A Fast Multi-tasking Solution: NMF-Theoretic Co-clustering for Gear Fault Diagnosis under Variable Working Conditions](https://cjme.springeropen.com/articles/10.1186/s10033-020-00437-3)|Chinese Journal of Mechanical Engineering|2020| `LR` |
| [Bearing fault diagnosis with varying conditions using angular domain resampling technology, SDP and DCNN](https://linkinghub.elsevier.com/retrieve/pii/S0263224120301536)|Measurement|2020| `HF` |
| [Multibranch and Multiscale CNN for Fault Diagnosis of Wheelset Bearings Under Strong Noise and Variable Load Condition](https://ieeexplore.ieee.org/document/8962243/)|IEEE Transactions on Industrial Informatics|2020| `LR` |
| [Bogie fault diagnosis under variable operating conditions based on fast kurtogram and deep residual learning towards imbalanced data](https://linkinghub.elsevier.com/retrieve/pii/S0263224120307296)|Measurement|2020| `LR` |
| [A renewable fusion fault diagnosis network for the variable speed conditions under unbalanced samples](https://linkinghub.elsevier.com/retrieve/pii/S0925231219315164)|Neurocomputing|2020| `LR` |
| [Deep learning-based cross-domain adaptation for gearbox fault diagnosis under variable speed conditions](https://iopscience.iop.org/article/10.1088/1361-6501/ab64aa)|Measurement Science and Technology|2020| `LR` |
| [Generalization of deep neural network for bearing fault diagnosis under different working conditions using multiple kernel method](https://linkinghub.elsevier.com/retrieve/pii/S0925231219305247)|Neurocomputing|2019| `LR` |
| [A novel transfer learning method for robust fault diagnosis of rotating machines under variable working conditions](https://linkinghub.elsevier.com/retrieve/pii/S0263224119301903)|Measurement|2019| `LR` |
| [An intelligent fault diagnosis framework dealing with arbitrary length inputs under different working conditions](https://iopscience.iop.org/article/10.1088/1361-6501/ab26a2)|Measurement Science and Technology|2019| `LR` |
| [Data-driven time-frequency analysis method based on variational mode decomposition and its application to gear fault diagnosis in variable working conditions](https://linkinghub.elsevier.com/retrieve/pii/S0888327018303935)|Mechanical Systems and Signal Processing|2019| `HF` |
| [Acoustic spectral imaging and transfer learning for reliable bearing fault diagnosis under variable speed conditions](https://linkinghub.elsevier.com/retrieve/pii/S0263224119301939)|Measurement|2019| `LR` |
| [Rolling bearing fault diagnosis and performance degradation assessment under variable operation conditions based on nuisance attribute projection](https://linkinghub.elsevier.com/retrieve/pii/S0888327018302553)|Mechanical Systems and Signal Processing|2019| `LR` |
| [A fault diagnosis method for planetary gearboxes under non-stationary working conditions using improved Vold-Kalman filter and multi-scale sample entropy](https://linkinghub.elsevier.com/retrieve/pii/S0022460X18306576)|Journal of Sound and Vibration|2019| `HF` |
| [Root cause diagnosis of quality-related faults in industrial multimode processes using robust Gaussian mixture model and transfer entropy](https://linkinghub.elsevier.com/retrieve/pii/S0925231218300468)|Neurocomputing|2018| `FG` |
| [Intelligent Fault Diagnosis Under Varying Working Conditions Based on Domain Adaptive Convolutional Neural Networks](https://ieeexplore.ieee.org/document/8513748/)|IEEE Access|2018| `LR` |
| [Bearing Fault Diagnosis Under Variable Working Conditions Based on Domain Adaptation Using Feature Transfer Learning](https://ieeexplore.ieee.org/document/8543590/)|IEEE Access|2018| `LR` |
| [An integrated method based on CEEMD-SampEn and the correlation analysis algorithm for the fault diagnosis of a gearbox under different working conditions](https://linkinghub.elsevier.com/retrieve/pii/S0888327017304363)|Mechanical Systems and Signal Processing|2018| `HF` |
| [Transfer Learning With Neural Networks for Bearing Fault Diagnosis in Changing Working Conditions](http://ieeexplore.ieee.org/document/7961149/)|IEEE Access|2017| `LR` |
| [The Harmonic Order Tracking Analysis Method for the Fault Diagnosis in Induction Motors Under Time-Varying Conditions](http://ieeexplore.ieee.org/document/7737045/)|IEEE Transactions on Energy Conversion|2017| `HF` |
| [Rolling bearing fault diagnosis under variable conditions using LMD-SVD and extreme learning machine](https://linkinghub.elsevier.com/retrieve/pii/S0094114X15000671)|Mechanism and Machine Theory|2015| `HF` |
| [A new fault diagnosis method of multimode processes using Bayesian inference based Gaussian mixture contribution decomposition](https://linkinghub.elsevier.com/retrieve/pii/S0952197612002199)|Engineering Applications of Artificial Intelligence|2013| `FG` |
| [Automatic diagnosis method for structural fault of rotating machinery based on distinctive frequency components and support vector machines under varied operating conditions](https://linkinghub.elsevier.com/retrieve/pii/S0925231212007217)|Neurocomputing|2013| `HF` |
| [Diagnosis of Induction Motor Faults in Time-Varying Conditions Using the Polynomial-Phase Transform of the Current](https://ieeexplore.ieee.org/document/5475252/)|IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS|2011| `HF` |

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