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Appl. Sci. 2018, 8(4), 619; https://doi.org/10.3390/app8040619

Fault Diagnosis of Rotating Machinery Based on the Multiscale Local Projection Method and Diagonal Slice Spectrum

1,2
,
1,2,* and 3
1
Key Laboratory of Metallurgical Equipment and Control Technology, Wuhan University of Science and Technology, Ministry of Education, Wuhan 430081, China
2
Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering, Wuhan University of Science and Technology, Wuhan 430081, China
3
Wuhan Ship Development & Design Institute, Wuhan 430064, China
*
Author to whom correspondence should be addressed.
Received: 1 March 2018 / Revised: 10 April 2018 / Accepted: 10 April 2018 / Published: 16 April 2018

Abstract

The vibration signals of bearings and gears measured from rotating machinery usually have nonlinear, nonstationary characteristics. The local projection algorithm cannot only reduce the noise of the nonlinear system, but can also preserve the nonlinear deterministic structure of the signal. The influence of centroid selection on the performance of noise reduction methods is analyzed, and the multiscale local projection method of centroid was proposed in this paper. This method considers both the geometrical shape and statistical error of the signal in high dimensional phase space, which can effectively eliminate the noise and preserve the complete geometric structure of the attractors. The diagonal slice spectrum can identify the frequency components of quadratic phase coupling and enlarge the coupled frequency component in the nonlinear signal. Therefore, the proposed method based on the above two algorithms can achieve more accurate results of fault diagnosis of gears and rolling bearings. The simulated signal is used to verify its effectiveness in a numerical simulation. Then, the proposed method is conducted for fault diagnosis of gears and rolling bearings in application researches. The fault characteristics of faulty bearings and gears can be extracted successfully in the researches. The experimental results indicate the effectiveness of the novel proposed method. View Full-Text
Keywords: centroid selection; noise reduction; multiscale local projection; diagonal slice spectrum; fault diagnosis centroid selection; noise reduction; multiscale local projection; diagonal slice spectrum; fault diagnosis
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Lv, Y.; Yuan, R.; Shi, W. Fault Diagnosis of Rotating Machinery Based on the Multiscale Local Projection Method and Diagonal Slice Spectrum. Appl. Sci. 2018, 8, 619.

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