Application of the CEMS on Fault Diagnosis for Rotary Machine

Abstract:

In order to monitor states of the rotary machine in time and ensure its performance, it is very important to analyze the evolution from the normal state to the fault state. In the paper, a new method is proposed to improve the precision of fault diagnosis. Firstly, the character extraction with mutative scales (CEMS) is applied to achieve the characteristic values. Secondly, the Hidden Semi-Markov model is built to identify the different running states. Thirdly, the new method is compared with the traditional one by the example of bushing abrasion of the connecting rod in diesel engine. According to the simulation and experiment researches, it indicates that the signal characters with more state information can be obtained pertinently by using the CEMS. And the accuracy of recognition is 97.33% in the 150 test samples, improved evidently than the traditional one. And the new character extraction method can be used in the technology domain widely.

• Periodical: Applied Mechanics and Materials (Volumes 380-384)
• Pages: 947-950
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.380-384.947
• Online since: August 2013
• Authors: Qiang Huang, Jun Li, Hai Wen Le
• Keywords: Character Extraction with Mutative Scales, Rotary Machine, State Recognition

References

[1] D. H. Pandya,S. H. Upadhyay,S. P. Harsha. Fault diagnosis of rolling element bearing by using multinomial logistic regression and wavelet packet transform. Soft Computing. No. 5(2013), pp.87-91.

DOI: 10.1007/s00500-013-1055-1

[2] Huang Qiang, Song Shihua, etc. Analysis of fault grades of diesel engines using vibration signals. Journal of Huazhong University of Science and Technology. No. 6(2007), pp.105-107.

[3] XiaoFei Zhang, NiaoQing Hu, Lei Hu, Zhe Cheng. Multi-scale bistable stochastic resonance array: A novel weak signal detection method and application in machine fault diagnosis. Science China Technological Sciences. No. 5(2013), pp.245-252.

DOI: 10.1007/s11431-013-5246-x

[4] Zhang Xiao, Huang Qiang. Recovery of 3D Human Posture based on Monocular Vision Technology. Proceedings of 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems. (2009), pp.5-8.

DOI: 10.1109/icicisys.2009.5357729

[5] Fei Xia, Hao Zhang, Daogang Peng, etc. Turine Fault Diagnosis Based on Fuzzy Theory and SVM. Lecture Notes in Computer Science. Heidelberg: Springer Berlin. (2009), pp.668-676.

DOI: 10.1007/978-3-642-05253-8_73

[6] Yaguo Lei, Zhengjia He, Yanyang Zi. Fault diagnosis of rotating machinery based on a new hybrid clustering algorithm. The International Journal of Advanced Manufacturing Technology. Vol. 35(2008) pp.968-977.

DOI: 10.1007/s00170-006-0780-3

[7] Junjie Gu, Jin Tian, Xuezhi Peng. Diagnosis method based on wavelet coefficient scale relativity correlation dimension for fault. Frontiers of Energy and Power Engineering. Vol. 2(2008) pp.74-79.

DOI: 10.1007/s11708-008-0031-4