Helicopter main reduction planetary gear fault diagnosis method based on SVDD

Issue title: Selected papers from the International Symposium on Applied Electromagnetics and Mechanics - ISEM 2019

Guest editors: Jinhao Qiu, Ke Xiong and Hongli Ji

Article type: Research Article

Authors: Xia, Yubin^{a; b} | Liang, Dakai^a; | Zheng, Guo^b | Wang, Jingling^b | Zeng, Jie^a

Affiliations: [a] State Key Laboratory of Mechanics and Control of Mechanical Structures, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu Province, China | [b] Aviation Key Laboratory of Science and Technology on Fault Diagnosis and Health Management, AVIC Shanghai Aero Measurement-Controlling Research Institute, Shanghai, China

Correspondence: [*] Corresponding author: Dakai Liang, No. 29 Yudao Street, Qinhuai District, Nanjing, Jiangsu 210016, China. E-mail: liangdk@nuaa.edu.cn

Abstract: Aiming at the irregularity of the fault characteristics of the helicopter main reducer planetary gear, a fault diagnosis method based on support vector data description (SVDD) is proposed. The working condition of the helicopter is complex and changeable, and the fault characteristics of the planetary gear also show irregularity with the change of working conditions. It is impossible to diagnose the fault by the regularity of a single fault feature; so a method of SVDD based on Gaussian kernel function is used. By connecting the energy characteristics and fault characteristics of the helicopter main reducer running state signal and performing vector quantization, the planetary gear of the helicopter main reducer is characterized, and simultaneously couple the multi-channel information, which can accurately characterize the operational state of the planetary gear’s state.

Keywords: Helicopter main reduction, kernel function, SVDD, fault diagnosis

DOI: 10.3233/JAE-209316

Journal: International Journal of Applied Electromagnetics and Mechanics, vol. 64, no. 1-4, pp. 137-145, 2020