Mode Identification Based on Fuzzy Clustering and Grey System Theory and its Applichation

Abstract:

The helath condition of rotor has been greatly concerned in rotating machinery. But for the lack of information, it is very difficult to judge the actual conditon. Based on the fuzzy and grey characteristics between faults and symptoms, a new method integrated with fuzzy clustering and grey relation analysis was put forward to identify the condition of rotor system. Firstly, eight features, such as average value, peak-peak value, variance value, virtual value and etc., were extracted from the vibration signal of rotor system. Then, fuzzy C-means algorithm was used to cluster forty samples into 4 clusters, meanwhile, the clustering center was acquired and regarded as standard pattern matrix. Finally, the grey relation degree was calculated between pattern to be inspected and the standard pattern matrix. Using this method, the unbalanced conditions of rotor system was precisely identified, which shows that the integrated method is valid and practicable.

• Periodical: Advanced Materials Research (Volumes 171-172)
• Pages: 144-149
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.171-172.144
• Online since: December 2010
• Authors: Li Xiang Duan, Lai Bin Zhang, Yang Meng
• Keywords: Fuzzy Clustering, Grey Relative Analysis, Mode Identification, Rotor System

References

[1] Dong Ju Han. Vibration analysis of periodically time-varying rotor system with transverse crack. Mechanical Systems and Signal Processing 21 (2007), p.2857–2879.

DOI: 10.1016/j.ymssp.2007.02.006

[2] TejasH. Patel, AshishK. Darpe. Experimental investigations on vibration response of misaligned rotors. Mechanical Systems and Signal Processing 23 (2009), pp.2236-2252.

DOI: 10.1016/j.ymssp.2009.04.004

[3] Duan Lixiang, Zhang Laibin, Wang Zhaohui. De-noising of Diesel Vibration Signal Using Wavelet Packet and Singular Value Decomposition. Front. Mech. Eng. China(2006)4, pp.375-380.

DOI: 10.1007/s11465-006-0055-6

[4] Deng Julong. A Course in Grey Systems Theory. Huazhong University of Science and Technology Press, (1990).

[5] Yuan Xing, Duan Zhishan, Sun Yinghong. Roller Bearing Fault Diagnosis Based on EMD-AR Model and Grey Incidence. Bearing, 2008, (1), pp.30-32.

[6] Dong Yabin, Zhang Xiaolong. Determination Method for Identification Coefficient of Grey Relational Grade and Applying in Mechanical Faults Diagnosis. Equipment Manufacturing Technology, 2008, (3), pp.121-125.

[7] Shi Xudong, Fu Yili, Dai Yong, Ma Yulin. Machines grouping base on fuzzy clustering. Journal of Harbin Institute of Technology. 2001, 33(3), pp.287-290.

[8] Duan Lixiang, Zhang Laibin, Wang Zhaohui. Study on the Condition Monitoring for Diesel Engine Based on Fluctuation Method and Fuzzy Clustering. Journal of Mechanical Strength, 2005, 27(5), pp.567-570.

[9] Francisco de A.T. de Carvalho. Fuzzy c-means clustering methods for symbolic interval data. Pattern Recognition Letters 28 (2007), pp.423-437.

DOI: 10.1016/j.patrec.2006.08.014

[10] Yong-Huang Lin, Pin-Chan Lee, Ta-Peng Chang. Practical expert diagnosis model based on the grey relational analysis technique. Expert Systems with Applications 36 (2009), pp.1523-1528.

DOI: 10.1016/j.eswa.2007.11.046