Open AccessFault diagnosis of fracturing truck based on ITD and TET
Author(s) -
Xinrong Zhong,
Li Chai,
Haoyang Che,
ZhiChuan Zhao
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1894/1/012052
Subject(s) - truck , fault (geology) , transient (computer programming) , signal (programming language) , noise (video) , electric power system , power (physics) , engineering , automotive engineering , computer science , geology , artificial intelligence , seismology , physics , quantum mechanics , image (mathematics) , programming language , operating system
The power system is the core part of fracturing truck, and its running state will directly determine the operation efficiency of fracturing truck. Fracturing trucks often operate under heavy load and noisy conditions, so the power system is prone to faults and difficult to diagnose. In order to solve the difficult problem of fracturing vehicle power system diagnosis under noise and changing working conditions, one method based on intrinsic time-scale decomposition (ITD) and transient-extracting transform (TET) is proposed. Firstly, using the intrinsic time-scale decomposition to dealing the collected vibration signal of the fracturing vehicle power system, multiple related components have been obtained, and then perform transient-extracting transform to processing the components with larger correlations to the original signal. The local features of the signal are enhanced and the fault features are extracted to complete the fault diagnosis. The test results showing that the proposed fault diagnosis method can accurately identify the fault condition of the power system. the conclusions obtained can provide a certain reference for the research and development of the power system fault diagnosis method of fracturing truck.