Denoised Improved Envelope Spectrum for Fault Diagnosis of Aero-Engine Inter-Shaft Bearing
Source abstract
Abstract
The inter-shaft bearing is an important component of aero-engine rotor systems. It works between a high-pressure rotor and a low-pressure rotor. Effective fault diagnosis of it is significant for an aero-engine. The casing vibration signals can promptly and intuitively reflect changes in the operational health status of an aero-engine’s support system. However, affected by a complex vibration transmission path and vibration of the dual-rotor, the intrinsic vibration information of the inter-shaft bearing is faced with strong noise and a dual-frequency excitation problem. This excitation is caused by the wide span of vibration source frequency distribution that results from the quite different rotational speeds of the high-pressure rotor and low-pressure rotor. Consequently, most existing fault diagnosis methods cannot effectively extract inter-shaft bearing characteristic frequency information from the casing signal. To solve this problem, this paper proposed the denoised improved envelope spectrum (DIES) method. First, an improved envelope spectrum generated by a spectrum subtraction method is proposed. This method is applied to solve the multi-source interference with wide-band distribution problem under dual-frequency excitation. Then, an improved adaptive-thresholding approach is subsequently applied to the resultant subtracted spectrum, so as to eliminate the influence of random noise in the spectrum. An experiment on a public run-to-failure bearing dataset validates that the proposed method can effectively extract an incipient bearing fault characteristic frequency (FCF) from strong background noise. Furthermore, the experiment on the inter-shaft bearing of an aero-engine test platform validates the effectiveness and superiority of the proposed DIES method. The experimental results demonstrate that this proposed method can clearly extract fault-related information from dual-frequency excitation interference. Even amid strong background noise, it precisely reveals the inter-shaft bearing’s fault-related spectral components.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Machine Fault Diagnosis Techniques · Gear and Bearing Dynamics Analysis · Engineering Diagnostics and Reliability
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
The State Key Laboratory of Precision Manufacturing for Extreme Service Performance, Central South University, Changsha 410017, China
The School of Traffic and Transportation Engineering, Central South University, Changsha 410017, China
Funding
National Natural Science Foundation of China
References (32)
Show source-provided references
1. Inter-Shaft Bearing Fault Diagnosis Based on Aero-Engine System: A Benchmarking Dataset Study
2. Bearings in Aerospace, Application, Distress, and Life: A Review10.1007/s11668-023-01658-z ↗
3. Nonlinear Response Analysis for a Dual-Rotor System Supported by Ball Bearing10.1016/j.ijnonlinmec.2020.103627 ↗
4. Research Status and Development Trend of Condition Monitoring on Main-Shaft Bearings Used in Aircraft Engines
5. Vibration Analysis of Peeling Fault of Intermediate Bearing Outer Ring Based on Whole Aero-Engine
6. Compound Faults Feature Extraction of Inter-Shaft Bearing Based on Vibration Signal of Whole Aero-Engine10.1177/10775463211041871 ↗
7. Fault Characteristics and Diagnosis Method of Intershaft Bearing in Aero-Engine
8. Frequency Band Optimization of Morlet Complex Wavelet and Its Application in Fault Diagnosis of Inter-Shaft Bearing
9. A Peak Energy Criterion (P. E.) for the Selection of Resonance Bands in Complex Shifted Morlet Wavelet (CSMW) Based Demodulation of Defective Rolling Element Bearings Vibration Response10.1142/S0219691309002982 ↗
10. Variational Mode Decomposition10.1109/TSP.2013.2288675 ↗
11. Wavelet Transform for Rotary Machine Fault Diagnosis:10 Years Revisited10.1016/j.ymssp.2023.110545 ↗
12. Adaptive Variational Mode Decomposition Based on Archimedes Optimization Algorithm and Its Application to Bearing Fault Diagnosis10.1016/j.measurement.2022.110798 ↗
13. A Study on the Diagnosis of Compound Faults in Rolling Bearings Based on ITD-SVD10.21595/jve.2020.21590 ↗
14. Intrinsic Time-Scale Decomposition: Time-Frequency-Energy Analysis and Real-Time Filtering of Non-Stationary Signals
15. Nonlinear Resonance Characteristics of a Dual-Rotor System with a Local Defect on the Inner Ring of the Inter-Shaft Bearing10.1016/j.cja.2020.11.014 ↗
16. Nonlinear Vibration and Stability Analysis of a Dual-Disk Rotor-Bearing System under Multiple Frequency Excitations10.1007/s11071-024-09731-4 ↗
17. The Relationship between Spectral Correlation and Envelope Analysis in the Diagnostics of Bearing Faults and Other Cyclostationary Machine Signals10.1006/mssp.2001.1415 ↗
18. Cyclic Spectral Analysis of Rolling-Element Bearing Signals: Facts and Fictions10.1016/j.jsv.2007.02.029 ↗
19. Fast Computation of the Spectral Correlation10.1016/j.ymssp.2017.01.011 ↗
20. Product Envelope Spectrum Optimization-Gram: An Enhanced Envelope Analysis for Rolling Bearing Fault Diagnosis10.1016/j.ymssp.2023.110270 ↗
21. Order-Frequency Analysis of Machine Signals10.1016/j.ymssp.2016.10.024 ↗
22. Advanced Bearing Diagnostics: A Comparative Study of Two Powerful Approaches10.1016/j.ymssp.2018.05.011 ↗
23. Improved Envelope Spectrum via Feature Optimisation-Gram (IESFOgram): A Novel Tool for Rolling Element Bearing Diagnostics under Non-Stationary Operating Conditions10.1016/j.ymssp.2020.106891 ↗
24. Optimal Frequency Band Selection Using Blind and Targeted Features for Spectral Coherence-Based Bearing Diagnostics: A Comparative Study10.1016/j.isatra.2021.08.025 ↗
25. Nonlinear Vibration Response Characteristics of a Dual-Rotor-Bearing System with Squeeze Film Damper10.1016/j.cja.2021.01.013 ↗
26. Noise Subtraction and Marginal Enhanced Square Envelope Spectrum (MESES) for the Identification of Bearing Defects in Centrifugal and Axial Pump10.1016/j.ymssp.2021.108366 ↗
27. Cyclostationarity by Examples10.1016/j.ymssp.2008.10.010 ↗
28. An Improved Envelope Spectrum via Candidate Fault Frequency Optimization-Gram for Bearing Fault Diagnosis10.1016/j.jsv.2022.116746 ↗
29. Optimal Noise Subtraction-Based Fault Components Extraction for Machinery Fault Diagnosis10.1109/TIM.2023.3277964 ↗
30. Lee, J., Qiu, H., Yu, G., Lin, J., and Rexnord Technical Services (2025, July 21). Bearing Data Set, IMS, University of Cincinnati, NASA Ames Prognostics Data Repository 2007. Available online: https://www.kaggle.com/datasets/vinayak123tyagi/bearing-dataset.
31. Wei, Y., Li, Y., Xu, M., and Huang, W. (2019). A Review of Early Fault Diagnosis Approaches and Their Applications in Rotating Machinery. Entropy, 21.10.3390/e21040409 ↗
32. Vibration Analysis on Turbofan Engine Intershaft Bearing with Outer Race Defect