Research on Instantaneous Angular Speed Signal Separation Method for Planetary Gear Fault Diagnosis
- 1 Hunan Provincial Key Laboratory of Health Maintenance for Mechanical Equipment, Hunan University of Science and Technology, Xiangtan, China
- 2 Hunan Provincial Key Laboratory of Health Maintenance for Mechanical Equipment, Hunan University of Science and Technology, Xiangtan, China
- 3 Hunan Provincial Key Laboratory of Health Maintenance for Mechanical Equipment, Hunan University of Science and Technology, Xiangtan, China
Abstract
Planetary gear train is a critical transmission component in large equipment such as helicopters and wind turbines. Conducting damage perception of planetary gear trains is of great significance for the safe operation of equipment. Existing methods for damage perception of planetary gear trains mainly rely on linear vibration analysis. However, these methods based on linear vibration signal analysis face challenges such as rich vibration sources, complex signal coupling and modulation mechanisms, significant influence of transmission paths, and difficulties in separating damage information. This paper proposes a method for separating instantaneous angular speed (IAS) signals for planetary gear fault diagnosis. Firstly, this method obtains encoder pulse signals through a built-in encoder. Based on this, it calculates the IAS signals using the Hilbert transform, and obtains the time-domain synchronous average signal of the IAS of the planetary gear through time-domain synchronous averaging technology, thus realizing the fault diagnosis of the planetary gear train. Experimental results validate the effectiveness of the calculated IAS signals, demonstrating that the time-domain synchronous averaging technology can highlight impact characteristics, effectively separate and extract fault impacts, greatly reduce the testing cost of experiments, and provide an effective tool for the fault diagnosis of planetary gear trains.
- Lei, Y., Kong, D., Li, N. and Lin, J. (2014) Adaptive Ensemble Empirical Mode Decomposition and Its Application to Fault Detection of Planetary Gearboxes. Journal of Mechanical Engineering , 50, 64. https://doi.org/10.3901/JME.2014.03.064
- Feng, Z.P. and Qin, S.F. (2016) Planetary Gearbox Fault Diagnosis Based on Hilbert Vibration Decomposition and Higher Order Differential Energy Operator. Journal of Vibration and Shock , 35, 47-54.
- Zhu, W. and Feng, Z. (2016) Fault Diagnosis of Planetary Gearbox Based on Improved Empirical Wavelet Transform. Chinese Journal of Scientific Instrument , 37, 2193-2201.
- Feng, Z. and Liang, M. (2016) Complex Signal Analysis for Planetary Gearbox Fault Diagnosis via Shift Invariant Dictionary Learning. Measurement , 90, 382-395. https://doi.org/10.1016/j.measurement.2016.04.078
- Bourdon, A., Chesné, S., André, H. and Rémond, D. (2019) Reconstruction of Angular Speed Variations in the Angular Domain to Diagnose and Quantify Taper Roller Bearing Outer Race Fault. Mechanical Systems and Signal Processing , 120, 1-15. https://doi.org/10.1016/j.ymssp.2018.09.040
- Liu, Z., Kong, D., Zhao, M. and Ma, Z. (2020) Encoder Signal Response Characteristics of Planetary Gear Sets with Cracks. Journal of Xi ’ an Jiaotong University , No. 2, 43-50.
- Feng, Z., Gao, A., Li, K. and Ma, H. (2021) Planetary Gearbox Fault Diagnosis via Rotary Encoder Signal Analysis. Mechanical Systems and Signal Processing , 149, 107325. https://doi.org/10.1016/j.ymssp.2020.107325
- Li, Z., Guo, Y., Yin, X. And Hua, J. (2023) Encoder Signal Feature Extraction of Sun Gear Fault at Low Speed Using Relative Ratio of Fault Feature lndex. Mechanical Science and Technology for Aerospace Engineering , No. 7, 1044-1049.
- Mcfadden, P.D. (1991) A Technique for Calculating the Time Domain Averages of the Vibration of the Individual Planet Gears and the Sun Gear in an Epicyclic Gearbox. Journal of Sound & Vibration , 144, 163-172. https://doi.org/10.1016/0022-460X(91)90739-7
- Smidt, M.R.D. (2010) Internal Vibration Monitoring of a Planetary Gearbox. Ring Gear.
- Yip, L. (2011) Analysis and Modeling of Planetary Gearbox Vibration Data for Early Fault Detection. Doctoral Dissertation, University of Toronto, Canada.
- Abboud, D., Antoni, J., Sieg-Zieba, S. and Eltabach, M. (2016) Deterministic-Random Separation in Nonstationary Regime. Journal of Sound & Vibration , 362, 305-326. https://doi.org/10.1016/j.jsv.2015.09.029