Fault Diagnosis of Bearings with Adjusted Vibration Spectrum Images. (2nd December 2018)

• Record Type: Journal Article
• Authors: Qiu, Mingquan; Li, Wei; Zhu, Zhencai; Jiang, Fan; Zhou, Gongbo
• Other Names: Zappino Enrico Academic Editor.
• Is Part Of: Shock and vibration. Volume 2018(2018)
• Publication Date: 2018-12-02
• Subjects: Shock (Mechanics) -- Periodicals; Vibration -- Periodicals; 534.5
• DOI: 10.1155/2018/6981760
• Languages: English
• ISSNs: 1070-9622

Abstract

Abstract : In order to diagnose bearing faults under different operating state and limited sample condition, a fault diagnosis method based on adjusted spectrum image of vibration signal is proposed in this paper. Firstly, the Davies–Bouldin index (DBI) is employed to select a proper capture focus (CF) and image size, and the spectrum of vibration signal is computed via fast Fourier transformation (FFT) and adjusted according to the average rotating speed. Then, the spectrum is plotted and captured as a two-dimensional (2D) image with the optimized CF and image size. Two-dimensional principal component analysis (2DPCA) is used to reduce the dimension of images, and finally a nearest neighbour method is applied to classify the faults of bearings. Two experiments are carried out to validate the effectiveness of the proposed method. Besides, a further investigation on the effect of spectrum frequency resolution is conducted and a recommended selection method of frequency resolution is given based on the experimental performances. In our method, the training samples could be from only one operating condition, while the testing samples are from all possible operation conditions. All experiment results have demonstrated that the proposed method could achieve high classification accuracy even with very limited training samples.