Taking the gearbox in wind turbine as an example, this paper introduces a method about denoising the vibration signal of gearbox based on the vibration spectrum analysis and particle swarm optimization algorithm. The particle swarm optimization algorithm can reduce the search space by using one dimension search, and improve the optimization result by simultaneously optimizing the design parameters of Chebyshev band pass filter and Morlet wavelet filter, eventually filtering out the fault vibration signal of the gearbox. Experimental results show that this method can effectively eliminate the external noise in the vibration signal, and that the hybrid algorithm can effectively reduce the search range of particle swarm optimization and improve the optimization result for the relevant parameter optimization of Chebyshev band-pass filter and Morlet wavelet filter. It is applicable to the real-time gearbox fault diagnosis research. Therefore, it has certain value for theoretical research and practical applications. This hybrid algorithm has good optimized performance and the optimization process is fast. The fault features are obvious in the denoised signal, and can be applied to the real-time fault diagnosis of gearbox in the future research.
ZHANG Pengtao
,
LIU Jinhao
. Application of Particle Swarm Optimization Algorithm to Denoising Vibration Signal of Gearbox[J]. Science & Technology Review, 2014
, 32(13)
: 28
-32
.
DOI: 10.3981/j.issn.1000-7857.2014.13.004
[1] 曾兴祥, 樊新海. 综合传动装置齿轮故障诊断研究[J]. 机械传动, 2013, 35(1): 90-93. Zeng Xingxiang, Fan Xinhai. Fault diagnosis of the gear in the integrated transmission[J]. Mechanical Drive, 2013, 35(1): 90-93.
[2] 安婧, 伉大俪. 时频分析方法在齿轮故障诊断中的应用[J]. 信息技术, 2010, 23(3): 103-108. An Qian, Kang Dali. The application of time-frequency analysis method in gear fault diagnosis[J]. Information Technology, 2010, 23(3): 103-108.
[3] 康葳, 董田沼, 杨国振. 基于AHP的火控系统故障诊断策略研究[J]. 科技导报, 2012, 30(13): 53-56. Kang Wei, Dong Tianzhao, Yang Guozhen. Fault diagnosis strategy of the fire control system based on the AHP[J]. Science & Technology Review, 2012, 30(13): 53-56.
[4] 游张平, 胡小平, 张凯, 等. 基于自适应LS-SVM的柴油机进排气系统故障诊断[J]. 科技导报, 2010, 28(8): 77-80. You Zhangping, Hu Xiaoping, Zhang Kai, et al. The fault diagnosis for diesel engine inlet and exhaust system based on adaptive LS-SVM[J]. Science & Technology Review, 2010, 28(8): 77-80.
[5] 周平, 杨浩泉. 基于数据流动发动机动力不足故障诊断方法研究[J]. 科技导报, 2011, 29(3): 48-51. Zhou Ping, Yang Haoquan. Diagnosis method to power shortage fault in engine based on the data-stream[J]. Science & Technology Review, 2011, 29(3): 48-51.
[6] 王复兴. 黄金分割法在自控系统故障判断中的应用[J]. 自动化仪表, 2001, 22(6): 48-49. Wang Fuxing. Application of golden section method in fault diagnosis of automatic control system[J]. Automation Instrumentation, 2001, 22 (6): 48-49.
[7] 原菊梅, 潘宏侠. 粒子群优化齿轮箱振动信号周期分量提取方法[J]. 火力与指挥控制, 2013, 38(1): 30-33. Yuan Jumei, Pan Hongxia. Gearbox vibration signal periodic components extraction method based on advanced particle swarm optimization algorithm[J]. Fire Control & Command Control, 2013, 38 (1): 30-33.
[8] 毛鸿伟, 潘宏侠, 刘文礼. 基于粒子群优化的小波神经网络及其在齿轮箱故障诊断中的应用[J]. 振动与冲击, 2007, 26(5): 133-136. Mao Hongwei, Pan Hongxia, Liu Wenli. Application of fault diagnosis in gearbox based on wavelet neural network optimized by particle swarm optimization algorithm[J]. Journal of Vibration and Shock, 2007, 26(5): 133-136.
[9] Samanta B, Nataraj C. Use of particle swarm optimization for machinery fault detection[J]. Engineering Applications of Artificial Intelligence, 2009, 22(5): 308-316.
[10] Hussain S, Gabbar H A. A robust method for coupling detection among process variables[J]. Process Systems Engineering, 2012, 2(1): 93-110.
[11] Hussain S, Gabbar H A. Fault diagnosis in gearbox using adaptive wavelet filtering and shock response spectrum features extraction[J]. Structural Health Monitoring, 2013, 12(1): 1-12.
[12] Hussain S, Gabbar H A. A novel method for real time gear fault detection based on pulse shape analysis[J]. Mechanical Systems and Signal Processing, 2011, 25(4): 1287-1298.
