A new method for determining effective rank order of singularvalue decomposition denoising based on fitting error minimum principle
CUI Weicheng1,XU Aiqiang2,LI Wei1,MENG Fanlei1
1. Department of Aircraft Engineering, Naval Aeronautical and Astronautical University ,Yantai 264001, China;
2. Institute of Aircraft Detection and Application, Naval Aeronautical and Astronautical University, Yantai 264001, China
In order to maximize the signal-to-noise ratio of a rotating mechanical equipment's fault vibration signals, the singular value decomposition (SVD) de-noising method was studied, and a new method for determining its effective rank order was proposed. Firstly, a vibration signal was reconstructed in phase space, and the singular value decomposition of the attractor trajectory matrix was performed. Secondly, singular values were divided into a signal group and a noise group. For the results of each grouping, rank and singular value were taken as independent variable and dependent one, respectively. The feature singular value curve of signal and the feature singular value curve of noise were fitted, then the fitting errors were solved. At last, the singular value order corresponding to the minimum fitting error was taken as the effective rank order, and the SVD de-noising was performed. The results of numerical simulation and actual gear fault data analysis showed that the proposed method can effectively improve signal-to-noise ratios of signals, and create a beneficial condition for the subsequent fault feature extraction.
崔伟成1，许爱强2，李伟1，孟凡磊1. 基于拟合误差最小化原则的奇异值分解降噪有效秩阶次确定方法[J]. 振动与冲击, 2017, 36(3): 132-137.
CUI Weicheng1,XU Aiqiang2,LI Wei1,MENG Fanlei1. A new method for determining effective rank order of singularvalue decomposition denoising based on fitting error minimum principle. JOURNAL OF VIBRATION AND SHOCK, 2017, 36(3): 132-137.
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