摘要详情

ID / 提交时间

227 / 2021-04-09 10:16:31

标题

Application of CYCBD for the planetary gearbox fault diagnosis based on encoder information

关键字

Encoder signal, Planetary gearbox, Feature enhancement, Maximum second-order cyclostationarity blind deconvolution (CYCBD)

主题及专题

Machine Condition Monitoring and Fault Diagnosis

状态

终稿

作者

Boyao Zhang / Beihang University；School of Reliability and Systems Engineering

Yonghao Miao / School of Reliability and Systems Engineering, Beihang University, Beijing, China

Jing Lin / School of Reliability and Systems Engineering, Beihang University, Beijing, China

Chenhui Li / School of Reliability and Systems Engineering, Beihang University, Beijing, China

摘要

With more dynamic condition information, the built-in encoder signal is more superior and convenient than the traditional vibration signal in the mechanical system fault diagnosis. However, the early incipient fault features are apt to be submerged in the raw encoder signal due to the predominant feature of increasing. In this paper, the raw encoder signal is derived firstly to obtain the instantaneous angular speed. Then, IAS as the input series of the algorithm of maximum second-order cyclostationarity blind deconvolution (CYCBD), is used to enhance the fault features and identify the condition of the planetary gearbox. Through the simulation and experiment case, the feasibility of CYCBD in IAS signal can be verified.