The crack fault is one of the most common faults in the rotor system,and researchers have paid close attention to its fault diagnosis.However,most studies focus on discussing the dynamic response characteristics cause...The crack fault is one of the most common faults in the rotor system,and researchers have paid close attention to its fault diagnosis.However,most studies focus on discussing the dynamic response characteristics caused by the crack rather than estimating the crack depth and position based on the obtained vibration signals.In this paper,a novel crack fault diagnosis and location method for a dual-disk hollow shaft rotor system based on the Radial basis function(RBF)network and Pattern recognition neural network(PRNN)is presented.Firstly,a rotor system model with a breathing crack suitable for a short-thick hollow shaft rotor is established based on the finite element method,where the crack's periodic opening and closing pattern and different degrees of crack depth are considered.Then,the dynamic response is obtained by the harmonic balance method.By adjusting the crack parameters,the dynamic characteristics related to the crack depth and position are analyzed through the amplitude-frequency responses and waterfall plots.The analysis results show that the first critical speed,first subcritical speed,first critical speed amplitude,and super-harmonic resonance peak at the first subcritical speed can be utilized for the crack fault diagnosis.Based on this,the RBF network and PRNN are adopted to determine the depth and approximate location of the crack respectively by taking the above dynamic characteristics as input.Test results show that the proposed method has high fault diagnosis accuracy.This research proposes a crack detection method adequate for the hollow shaft rotor system,where the crack depth and position are both unknown.展开更多
An investigation about the application of Acoustic Emission (AE) techniques to analyze the dynamic response of different cracked shafts rendered in bump tests is presented in this work. The experimental apparatus devi...An investigation about the application of Acoustic Emission (AE) techniques to analyze the dynamic response of different cracked shafts rendered in bump tests is presented in this work. The experimental apparatus devised for this work complies of six shafts with different transverse crack sizes and a high-frequency data acquisition system. The AE signals generated in the bump tests performed on the different cracked shafts are captured by a wideband AE transducer. Those signals are treated by using statistical moments, wavelet transforms, and frequency- and time-domain procedures. A transverse crack of predetermined depth is etched into each shaft. The experimental results show that the values of kurtosis and skewness estimated for the AE signals can be used to identify the crack size.展开更多
基金Supported by National Natural Science Foundation of China (Grant No.11972129)National Science and Technology Major Project of China (Grant No.2017-IV-0008-0045)+1 种基金Heilongjiang Provincial Natural Science Foundation (Grant No.YQ2022A008)the Fundamental Research Funds for the Central Universities。
文摘The crack fault is one of the most common faults in the rotor system,and researchers have paid close attention to its fault diagnosis.However,most studies focus on discussing the dynamic response characteristics caused by the crack rather than estimating the crack depth and position based on the obtained vibration signals.In this paper,a novel crack fault diagnosis and location method for a dual-disk hollow shaft rotor system based on the Radial basis function(RBF)network and Pattern recognition neural network(PRNN)is presented.Firstly,a rotor system model with a breathing crack suitable for a short-thick hollow shaft rotor is established based on the finite element method,where the crack's periodic opening and closing pattern and different degrees of crack depth are considered.Then,the dynamic response is obtained by the harmonic balance method.By adjusting the crack parameters,the dynamic characteristics related to the crack depth and position are analyzed through the amplitude-frequency responses and waterfall plots.The analysis results show that the first critical speed,first subcritical speed,first critical speed amplitude,and super-harmonic resonance peak at the first subcritical speed can be utilized for the crack fault diagnosis.Based on this,the RBF network and PRNN are adopted to determine the depth and approximate location of the crack respectively by taking the above dynamic characteristics as input.Test results show that the proposed method has high fault diagnosis accuracy.This research proposes a crack detection method adequate for the hollow shaft rotor system,where the crack depth and position are both unknown.
文摘An investigation about the application of Acoustic Emission (AE) techniques to analyze the dynamic response of different cracked shafts rendered in bump tests is presented in this work. The experimental apparatus devised for this work complies of six shafts with different transverse crack sizes and a high-frequency data acquisition system. The AE signals generated in the bump tests performed on the different cracked shafts are captured by a wideband AE transducer. Those signals are treated by using statistical moments, wavelet transforms, and frequency- and time-domain procedures. A transverse crack of predetermined depth is etched into each shaft. The experimental results show that the values of kurtosis and skewness estimated for the AE signals can be used to identify the crack size.
