A novel method based upon modified composite spectrum and relative entropy for degradation feature extraction of hydraulic pump. (1st January 2019)

• Record Type: Journal Article
• Authors: Li, Hongru; Sun, Jian; Ma, Hui; Tian, Zaike; Li, Yifan
• Is Part Of: Mechanical systems and signal processing. Volume 114(2019)
• Page Start: 399
• Page End: 412
• Publication Date: 2019-01-01
• Subjects: Composite spectrum -- Relative entropy -- Feature extraction -- Hydraulic pump; Structural dynamics -- Periodicals; Vibration -- Periodicals; Constructions -- Dynamique -- Périodiques; Vibration -- Périodiques; Structural dynamics; Vibration; Periodicals; 621
• DOI: 10.1016/j.ymssp.2018.04.040
• Languages: English
• ISSNs: 0888-3270

Abstract

Highlights: Propose a DCS algorithm to fuse the detail components for feature extraction. DCS power entropy and singular entropy are extracted as initial features. Present an algorithm based on Relative Entropy for the fusion of initial features. A hydraulic pump degradation experiment is conducted to verify the proposed method. Abstract: Feature extraction is a key step of Prognostics and Health Management (PHM). To improve the feature performance, a method based upon the modified composite spectrum and relative entropy is proposed. The DCS algorithm is firstly presented by the modification of earlier composite spectrum for making fusion of multi-channel vibration signals. Considering Shannon entropy and Tsallis entropy, the DCS power entropy and singular entropy are initially extracted. According to max relation entropy criterion and gradual fusion strategy, the relative entropy algorithm is built to fuse the initial features into a new one, which is considered to be the degradation feature. Result of the application in hydraulic pump degradation experiment demonstrates that the proposed algorithm is feasible and the fused feature is effective to measure the performance degradation of pump.