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Shock and Vibration
Volume 20 (2013), Issue 4, Pages 781-792
http://dx.doi.org/10.3233/SAV-130784

Fault Diagnosis of Plunger Pump in Truck Crane Based on Relevance Vector Machine with Particle Swarm Optimization Algorithm

Wenliao Du,1,2 Ansheng Li,2 Pengfei Ye,1 and Chengliang Liu1

1State Key Laboratory of Mechanical System and Vibration, Shanghai Jiao Tong University, Shanghai, China
2School of Mechanical and Electronic Engineering, Zhengzhou University of Light Industry, Zhengzhou, Henan, China

Received 14 February 2012; Revised 9 August 2012; Accepted 22 October 2012

Copyright © 2013 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [7 citations]

The following is the list of published articles that have cited the current article.

  • Bo Wang, Shu-Lin Liu, Chao Jiang, and Hong-Li Zhang, “Rolling bearings' intelligent fault diagnosis based on RVM optimized with Quantum genetic algorithm,” Zhendong yu Chongji/Journal of Vibration and Shock, vol. 34, no. 17, pp. 207–212, 2015. View at Publisher · View at Google Scholar
  • Bo Wang, Shu-Lin Liu, Hong-Li Zhang, and Chao Jiang, “Advances about relevance vector machine and its applications in machine fault diagnosis,” Zhendong yu Chongji/Journal of Vibration and Shock, vol. 34, no. 5, pp. 145–167, 2015. View at Publisher · View at Google Scholar
  • Chen Lu, Zhen-Ya Wang, Wei-Li Qin, and Jian Ma, “Fault diagnosis of rotary machinery components using a stacked denoising autoencoder-based health state identification,” Signal Processing, 2016. View at Publisher · View at Google Scholar
  • Huimin Zhao, Wu Deng, Guangyu Li, Lifeng Yin, and Bing Yang, “Research on a new fault diagnosis method based on WT, improved PSO and SVM for motor,” Recent Patents on Mechanical Engineering, vol. 9, no. 4, pp. 289–298, 2016. View at Publisher · View at Google Scholar
  • Shiwei Li, and Di Zhou, “Study on a new fault diagnosis method based on combining intelligent technologies,” International Journal of Multimedia and Ubiquitous Engineering, vol. 11, no. 6, pp. 61–72, 2016. View at Publisher · View at Google Scholar
  • Wu Deng, Rui Yao, Meng Sun, Huimin Zhao, Yinglian Luo, and Chang Dong, “Study on a novel fault diagnosis method based on integrating EMD, fuzzy entropy, improved PSO and SVM,” Journal of Vibroengineering, vol. 19, no. 4, pp. 2562–2577, 2017. View at Publisher · View at Google Scholar
  • Zhu Kedong, Mei Fei, and Zheng Jianyong, “Adaptive fault diagnosis of HVCBs based on P-SVDD and P-KFCM,” Neurocomputing, 2017. View at Publisher · View at Google Scholar