A fault diagnosis scheme for planetary gearboxes using adaptive multi-scale morphology filter and modified hierarchical permutation entropy. (15th May 2018)

• Record Type: Journal Article
• Authors: Li, Yongbo; Li, Guoyan; Yang, Yuantao; Liang, Xihui; Xu, Minqiang
• Is Part Of: Mechanical systems and signal processing. Volume 105(2018)
• Page Start: 319
• Page End: 337
• Publication Date: 2018-05-15
• Subjects: Modified hierarchical permutation entropy (MHPE) -- Adaptive multi-scale morphological filter (AMMF) -- Laplacian score (LS) -- Fault diagnosis; Structural dynamics -- Periodicals; Vibration -- Periodicals; Constructions -- Dynamique -- Périodiques; Vibration -- Périodiques; Structural dynamics; Vibration; Periodicals; 621
• DOI: 10.1016/j.ymssp.2017.12.008
• Languages: English
• ISSNs: 0888-3270

Abstract

Highlights: MHPE is proposed to extract the fault features. MHPE can overcome the problems of MPE. A fault diagnosis strategy based on AMMF and MHPE is developed. The proposed method is validated using simulated and experimental signals. Abstract: The fault diagnosis of planetary gearboxes is crucial to reduce the maintenance costs and economic losses. This paper proposes a novel fault diagnosis method based on adaptive multi-scale morphological filter (AMMF) and modified hierarchical permutation entropy (MHPE) to identify the different health conditions of planetary gearboxes. In this method, AMMF is firstly adopted to remove the fault-unrelated components and enhance the fault characteristics. Second, MHPE is utilized to extract the fault features from the denoised vibration signals. Third, Laplacian score (LS) approach is employed to refine the fault features. In the end, the obtained features are fed into the binary tree support vector machine (BT-SVM) to accomplish the fault pattern identification. The proposed method is numerically and experimentally demonstrated to be able to recognize the different fault categories of planetary gearboxes.