Condition Monitoring for Helicopter Main Gearbox Based on Wavelet Packet Transform and Wavelet Neural Network
This paper describes a conditon monitoring systems for helicopter main gearbox using wavelet packet transform (WPT) and wavelet neural network (WNN). According to the fault characteristics of main gearbox, a fault diagnosis method that combining WPT and WNN with threshold is proposed. Frist the noise is removed from vibration signals, then the denoising signals are decomposed by WPT, extract standard deviation coefficients of each level as the input of WNN, the learning rates and momentum factors are used to adjust the network, the method of batch training is applied and it can diagnose fault quickly, which can monitor the condition of main gearbox. Theoretical and practical application shows that this method is effective and feasible, its diagnostic speed is rapid and result is accuracy, which provides a new technical reference for the development of helicopter fault diagnostic systems.
wavelet packet transform (WPT) wavelet neural network (WNN) condition monitoring helicopter main gearbox fault diagnosis
Li-Sheng LIU Yu-Hang YANG Zong-Yuan LI Wei YU
College of automation Nanjing University of Science and Technology Nanjing, China Department of Reli Department of Reliability Army Aviation Research Institute Beijing, China
国际会议
西安
英文
467-471
2011-06-17（万方平台首次上网日期，不代表论文的发表时间）