Reliable multiple combined fault diagnosis of bearings using heterogeneous feature models and multiclass support vector Machines
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DOI: 10.1016/j.ress.2018.02.012
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Cited by:
- Miao, Mengqi & Yu, Jianbo & Zhao, Zhihong, 2022. "A sparse domain adaption network for remaining useful life prediction of rolling bearings under different working conditions," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
- Leoni, Leonardo & De Carlo, Filippo & Abaei, Mohammad Mahdi & BahooToroody, Ahmad & Tucci, Mario, 2023. "Failure diagnosis of a compressor subjected to surge events: A data-driven framework," Reliability Engineering and System Safety, Elsevier, vol. 233(C).
- Xu, Zhaoyi & Saleh, Joseph Homer, 2021. "Machine learning for reliability engineering and safety applications: Review of current status and future opportunities," Reliability Engineering and System Safety, Elsevier, vol. 211(C).
- Na, Kyumin & Yoon, Heonjun & Kim, Jaedong & Kim, Sungjong & Youn, Byeng D., 2023. "PERL: Probabilistic energy-ratio-based localization for boiler tube leaks using descriptors of acoustic emission signals," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
- Moradi, Ramin & Groth, Katrina M., 2020. "Modernizing risk assessment: A systematic integration of PRA and PHM techniques," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
- Zuo, Lin & Xu, Fengjie & Zhang, Changhua & Xiahou, Tangfan & Liu, Yu, 2022. "A multi-layer spiking neural network-based approach to bearing fault diagnosis," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
- Yiwei Wang & Jian Zhou & Lianyu Zheng & Christian Gogu, 2022. "An end-to-end fault diagnostics method based on convolutional neural network for rotating machinery with multiple case studies," Journal of Intelligent Manufacturing, Springer, vol. 33(3), pages 809-830, March.
- Wang, Xu & Shen, Changqing & Xia, Min & Wang, Dong & Zhu, Jun & Zhu, Zhongkui, 2020. "Multi-scale deep intra-class transfer learning for bearing fault diagnosis," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
- Li, Xin & Yang, Yu & Wu, Zhantao & Yan, Ke & Shao, Haidong & Cheng, Junsheng, 2022. "High-accuracy gearbox health state recognition based on graph sparse random vector functional link network," Reliability Engineering and System Safety, Elsevier, vol. 218(PB).
- Liu, Jie & Xu, Huoyao & Peng, Xiangyu & Wang, Junlang & He, Chaoming, 2023. "Reliable composite fault diagnosis of hydraulic systems based on linear discriminant analysis and multi-output hybrid kernel extreme learning machine," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
- Feng, Liuyang & Zhang, Limao, 2022. "Enhanced prediction intervals of tunnel-induced settlement using the genetic algorithm and neural network," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
- Zou, Xinyu & Tao, Laifa & Sun, Lulu & Wang, Chao & Ma, Jian & Lu, Chen, 2023. "A case-learning-based paradigm for quantitative recommendation of fault diagnosis algorithms: A case study of gearbox," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
- Guo, Jianchun & Si, Zetian & Liu, Yi & Li, Jiahao & Li, Yanting & Xiang, Jiawei, 2022. "Dynamic time warping using graph similarity guided symplectic geometry mode decomposition to detect bearing faults," Reliability Engineering and System Safety, Elsevier, vol. 224(C).
- Guan, Yang & Meng, Zong & Sun, Dengyun & Liu, Jingbo & Fan, Fengjie, 2021. "2MNet: Multi-sensor and multi-scale model toward accurate fault diagnosis of rolling bearing," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
- Li, Xin & Zhong, Xiang & Shao, Haidong & Han, Te & Shen, Changqing, 2021. "Multi-sensor gearbox fault diagnosis by using feature-fusion covariance matrix and multi-Riemannian kernel ridge regression," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
- Lee, Jinwook & Kim, Myungyon & Ko, Jin Uk & Jung, Joon Ha & Sun, Kyung Ho & Youn, Byeng D., 2022. "Asymmetric inter-intra domain alignments (AIIDA) method for intelligent fault diagnosis of rotating machinery," Reliability Engineering and System Safety, Elsevier, vol. 218(PB).
- Zio, Enrico, 2022. "Prognostics and Health Management (PHM): Where are we and where do we (need to) go in theory and practice," Reliability Engineering and System Safety, Elsevier, vol. 218(PA).
- Ding, Yifei & Jia, Minping & Zhuang, Jichao & Cao, Yudong & Zhao, Xiaoli & Lee, Chi-Guhn, 2023. "Deep imbalanced domain adaptation for transfer learning fault diagnosis of bearings under multiple working conditions," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
- Park, Chan Hee & Kim, Hyeongmin & Suh, Chaehyun & Chae, Minseok & Yoon, Heonjun & Youn, Byeng D., 2022. "A health image for deep learning-based fault diagnosis of a permanent magnet synchronous motor under variable operating conditions: Instantaneous current residual map," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
- Bai, Ruxue & Meng, Zong & Xu, Quansheng & Fan, Fengjie, 2023. "Fractional Fourier and time domain recurrence plot fusion combining convolutional neural network for bearing fault diagnosis under variable working conditions," Reliability Engineering and System Safety, Elsevier, vol. 232(C).
- Peters, Benjamin & Yildirim, Murat & Gebraeel, Nagi & Paynabar, Kamran, 2020. "Severity-based diagnosis for vehicular electric systems with multiple, interacting fault modes," Reliability Engineering and System Safety, Elsevier, vol. 195(C).
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Keywords
Bearings (mechanical); Envelope signal processing; Feature extraction; Support vector machines; Nearest neighborhood search; Fault detection and diagnosis; Data-driven diagnostic; Reliability;All these keywords.
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