Shaft Crack Identification Based on Vibration and AE Signals
Author(s) -
Wenxiu Lu,
Fulei Chu
Publication year - 2011
Publication title -
shock and vibration
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.418
H-Index - 45
eISSN - 1875-9203
pISSN - 1070-9622
DOI - 10.1155/2011/460178
Subject(s) - vibration , signal (programming language) , structural engineering , acoustics , acoustic emission , wavelet , rotor (electric) , finite element method , frequency domain , time domain , engineering , computer science , mechanical engineering , physics , artificial intelligence , computer vision , programming language
The shaft crack is one of the main serious malfunctions that often occur in rotating machinery. However, it is difficult to locate the crack and determine the depth of the crack. In this paper, the acoustic emission (AE) signal and vibration response are used to diagnose the crack. The wavelet transform is applied to AE signal to decompose into a series of time-domain signals, each of which covers a specific octave frequency band. Then an improved union method based on threshold and cross-correlation method is applied to detect the location of the shaft crack. The finite element method is used to build the model of the cracked rotor, and the crack depth is identified by comparing the vibration response of experiment and simulation. The experimental results show that the AE signal is effective and convenient to locate the shaft crack, and the vibration signal is feasible to determine the depth of shaft crack.
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