
Shocking fault component of abnormal sound signal in the fault engine extract method based on linear superposition method and cross-correlation analysis
Author(s) -
Dayong Ning,
Yongjun Gong
Publication year - 2015
Publication title -
advances in mechanical engineering/advances in mechanical engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.318
H-Index - 40
eISSN - 1687-8140
pISSN - 1687-8132
DOI - 10.1177/1687814015599107
Subject(s) - superposition principle , fault (geology) , component (thermodynamics) , signal (programming language) , noise (video) , independent component analysis , waveform , computer science , background noise , pattern recognition (psychology) , signal processing , component analysis , artificial intelligence , mathematics , telecommunications , physics , geology , mathematical analysis , radar , seismology , image (mathematics) , thermodynamics , programming language
An extracted fault component of an abnormal sound is useful for faulty diagnosis. The existing fault component extracting approaches based on time–frequency analysis should filter the original signal to eliminate the background noise. However, these approaches will significantly change the fault component. In this article, a method for extracting the fault component of an abnormal sound signal is presented. This method is based on the linear superposition method and cross-correlation analysis. The method can eliminate the background noise and acquire the waveform of fault component. According to the feature of the shocking fault component, the acquired signal was intercepted into several segments, and the cross-correlation analysis was adopted to remove the wrong segment without the fault shocking component. The correct components were then linearly superposed together to eliminate the background noise. Finally, two experiments were performed to evaluate the effectiveness of the proposed fault component extracting method. The results show that the approach satisfactorily extracts the fault shocking component. The precise faulty component can be extracted by this method, which judges the engine condition precisely. The fault type can be diagnosed easily by this method. This method can be used in other fields to extract a particular component from a complicated signal