Abstract
For the fault diagnosis of intershaft bearings, the fusion information exergy distance method (FIEDM) is proposed by fusing four information exergies, such as singular spectrum exergy, power spectrum exergy, wavelet energy spectrum exergy, and wavelet space spectrum exergy, which are extracted from acoustic emission (AE) signals under multiple rotational speeds and multimeasuring points. The theory of FIEDM is investigated based on four information exergy distances under multirotational speeds. As for rolling bearings, four faults and one normal condition are simulated on a birotor test rig to collect the AE signals, in which the four faults are inner ring fault, outer ring fault, rolling element fault, and inner race‐rolling element coupling fault. The faults of the intershaft bearings are analyzed and diagnosed by using the FIEDM. From the investigation, it is demonstrated that the faults of the intershaft bearings are accurately diagnosed and identified, and the FIEDM is effective for the analysis and diagnosis of intershaft bearing faults. Furthermore, the fault diagnosis precision of intershaft bearings becomes higher with increasing rotational speed.
Highlights
In the birotor system of an aeroengine, the intershaft bearing is widely used to connect high- and low-pressure rotors in a rotor supporting system. e outer and inner rings of intershaft bearing rotate with the high- and low-pressure rotor, respectively
In line with the process information of an acoustic emission (AE) signal in the time domain [t1, t2], the information exergy is gained by integrating information entropy S of the measuring point in
If the four information exergies are fused to reflect the fault features from different analytical domains, the information features of the intershaft bearing faults can be fully described synthetically, so that it is promising to improve the accuracy of the fault analysis and recognition
Summary
In the birotor system of an aeroengine, the intershaft bearing is widely used to connect high- and low-pressure rotors in a rotor supporting system. e outer and inner rings of intershaft bearing rotate with the high- and low-pressure rotor, respectively. Zhao et al [13] combined approximate entropy and empirical mode decomposition to discuss the defect sizes of the rolling elements in bearings He and Zhang [14] utilized the approximate entropy and wavelet analysis method to manage the AE signals in rolling bearing fault diagnosis. The objective of this study is to develop the fusion information exergy distance method (FIEDM) for intershaft bearing fault diagnosis by the AE signals of five condition (rolling element fault, inner ring fault, outer ring fault, inner ringrolling element coupling fault, and normal) and four information exergies (singular spectrum exergy (SSE), power spectrum exergy (PSE), wavelet energy spectrum exergy (WESE), and wavelet space spectrum exergy (WSSE)) from different analytical domains (time, frequency, and timefrequency domains).
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