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- Bearing Fault Feature Enhancement and Diagnosis Based on Statistical Filtering and 1.5-Dimensional Symmetric Difference Analytic Energy Spectrum
- IEEE SENSORS JOURNALLiao, Zhiqiang Song, Xuewei Jia, Baozhu Chen, Peng 出版年：2021
- Bearing fault impulses are easily submerged by background noise, resulting in the inconspicuous fault feature and affecting the accuracy of the fault diagnosis. This paper presents a novel method for bearing the fault fe...
- Rolling bearing fault diagnosis method using time-frequency information integration and multi-scale TransFusion network
- KNOWLEDGE-BASED SYSTEMSWang, Zekun Xu, Zifei Cai, Chang Wang, Xiaodong Xu, Jianzhong Shi, Kezhong Zhong, Xiaohui Liao, Zhiqiang Li, Qing 'an 出版年：2024
- Advances in deep learning methods have demonstrated remarkable development in diagnosing faults of rotating machinery. The currently popular deep neural networks suffer from design flaws in thEIr network structure, leadi...
- Incrementally accumulated holographic SDP characteristic fusion method in ship propulsion shaft bearing fault diagnosis
- MEASUREMENT SCIENCE AND TECHNOLOGYSong, Xuewei Liao, Zhiqiang Wang, Hongfeng Song, Weiwei Chen, Peng 出版年：2022
- To improve the accuracy of the fault diagnosis of a ship propulsion shaft bearing in a harsh working environment, a visual diagnosis method based on the incrementally accumulated holographic symmetrical dot pattern (SDP)...
- Rolling Bearing Fault Diagnosis Under Different Severity Based on Statistics Detection Index and Canonical Discriminant Analysis
- IEEE ACCESSSong, Xuewei Liao, Zhiqiang Jia, Baozhu Kong, Defeng Niu, Jinzhang 出版年：2023
- Bearing failures are the most frequent causes of breakdowns in rotating machinery. Different levels of severity in these failures exhibit distinct fault characteristics in the vibration signal. This paper presents a bear...
- Bearing Fault Diagnosis Using Reconstruction Adaptive Determinate Stationary Subspace Filtering and Enhanced Third-Order Spectrum
- IEEE SENSORS JOURNALLiao, Zhiqiang Song, Xuewei Wang, Hongfeng Song, Weiwei Jia, Baozhu Chen, Peng 出版年：2022
- Raw vibration signals poorly perform in industrial bearing fault diagnosis because impulse features are damped and masked by disturbances and noises. Fault diagnosis is more challenging due to weak features. This work pr...
- Novel Rotating Machinery Structural Faults Signal Adaptive Multiband Filtering and Automatic Diagnosis
- MATHEMATICAL PROBLEMS IN ENGINEERINGSong, Xuewei Liao, Zhiqiang Wang, Hongfeng Song, Weiwei Chen, Peng 出版年：2021
- To realize an automatic diagnosis of rotating machinery structure faults, this paper presents a novel fault diagnosis model based on adaptive multiband filter and stacked autoencoders (SAEs). First, to solve the problem ...
- A novel approach for adaptively separating and extracting compound fault features of the in-wheel motor bearing
- ISA TRANSACTIONSTao, Yukun Ge, Chun Feng, Han Xue, Hongtao Yao, Mingyu Tang, Haihong Liao, Zhiqiang Chen, Peng 出版年：2025
- For compound fault detection of in-wheel motor bearings, this paper proposes a novel approach to adaptively separate multi-source signals and extract compound fault features. Building upon blind source separation (BSS), ...
- Automatic Bearing Fault Feature Extraction Method via PFDIC and DBAS
- MATHEMATICAL PROBLEMS IN ENGINEERINGLiao, Zhiqiang Song, Xuewei Jia, Baozhu Chen, Peng 出版年：2021
- Determining the embedded dimension of a singular value decomposition Hankel matrix and selecting the singular values representing the intrinsic information of fault features are challenging tasks. Given these issues, thi...
- Optimal Time Frequency Fusion Symmetric Dot Pattern Bearing Fault Feature Enhancement and Diagnosis
- SENSORSLiang, Guanlong Song, Xuewei Liao, Zhiqiang Jia, Baozhu 出版年：2024
- Regarding the difficulty of extracting the acquired fault signal features of bearings from a strong background noise vibration signal, coupled with the fact that one-dimensional (1D) signals provide limited fault informa...
- Bearing Fault Feature Enhancement and Diagnosis Based on Savitzky-Golay Filtering Gramian Angular Field
- IEEE ACCESSHuang, Zhende Song, Xuewei Liao, Zhiqiang Jia, Baozhu 出版年：2024
- In actual engineering production, bearings typically operate in harsh environments. The fault features of bearing vibration signals are often submerged by background noise, making it difficult to extract the fault signal...
- Bearing-Fault-Feature Enhancement and Diagnosis Based on Coarse-Grained Lattice Features
- SENSORSLi, Xiaoyu Jia, Baozhu Liao, Zhiqiang Wang, Xin 出版年：2024
- In view of the frequent failures occurring in rolling bearings, the strong background noise present in signals, weak features, and difficulties associated with extracting fault characteristics, a method of enhancing and ...
- Rotating machinery structural faults feature enhancement and diagnosis base on low-pass Teager energy operator intrinsic time-scale decomposition
- MEASUREMENT SCIENCE AND TECHNOLOGYSong, Xuewei Huang, Zhende Liang, Guanlong Niu, Jinzhang Jia, Baozhu Liao, Zhiqiang 出版年：2025
- Aiming to address the issue of the complex and harsh working environment of rotating machinery, the features of vibration signals associated with structural faults are often obscured by noise, resulting in low accuracy i...
- AC Motor Fault Diagnosis Based on Multi-source Signal Fusion SDP
- 15th Global Reliability and Prognostics and Health Management Conference, PHM-Beijing 2024Liao, Zhiqiang Liang, Guanlong Song, Xuewei Li, Xiaoyu Huang, Zhende Jia, Baozhu 出版年：2024
- In order to solve the problem of the limited ability of a single signal to characterize the fault state of AC motors, this paper proposes an AC motor fault diagnosis method based on multi-source signal fusion SDP (Symmet...
- Bearing Remaining Useful Life Prediction Using FNN-based Feature Principal Component and GRNN
- 2022 International Conference on Sensing, Measurement and Data Analytics in the Era of Artificial Intelligence, ICSMD 2022 - ProceedingsLiao, Zhiqiang Jia, Baozhu Kong, Defeng Ji, Ran Li, Xiaoyu Hao, Kang 出版年：2022
- In the bearing remaining useful life (RUL) prediction, constructing a health indicator to reflect the running bearings health status is one of the most critical parts, because it determines the performance of the RUL pre...
- Shaft Misalignment Fault Feature Extraction and Diagnosis via MCSA Utilizing Empirical Principal Component Analysis
- ICSMD 2024 - 5th International Conference on Sensing, Measurement and Data Analytics in the Era of Artificial IntelligenceLiao, Zhiqiang Huang, Zhende Song, Xuewei Jia, Baozhu Liang, Guanlong Li, Xiaoyu 出版年：2024
- The fault features of shaft misalignment in stator currents are often suppressed and masked by interference and noise, leading to weak fault features and affecting the accuracy of fault diagnosis. This paper proposes a f...
- Marine Propulsion Shaft Bearing Fault Feature Extraction and Diagnosis Based on Strong Tracking State Principal Component
- 2021 Global Reliability and Prognostics and Health Management, PHM-Nanjing 2021Liao, Zhiqiang Song, Xuewei Jia, Baozhu Zuo, Dunwen Sheng, Yi Chen, Peng 出版年：2021
- The vibration signal with non-stationary, strong noise, and weak fault feature is inevitably acquired in practical marine propulsion shaft bearing fault diagnosis due to harsh environment. These obstacles lead to diagnos...
