To improve the diagnosis accuracy and self-adaptability of fatigue crack in ulterior place of the supporting shaft, time series and neural network are attempted to be applied in research on diag-nosing the fatigue cr...To improve the diagnosis accuracy and self-adaptability of fatigue crack in ulterior place of the supporting shaft, time series and neural network are attempted to be applied in research on diag-nosing the fatigue crack’s degree based on analyzing the vibration characteristics of the supporting shaft. By analyzing the characteristic parameter which is easy to be detected from the supporting shaft’s exterior, the time series model parameter which is hypersensitive to the situation of fatigue crack in ulterior place of the supporting shaft is the target input of neural network, and the fatigue crack’s degree value of supporting shaft is the output. The BP network model can be built and net-work can be trained after the structural parameters of network are selected. Furthermore, choosing the other two different group data can test the network. The test result will verify the validity of the BP network model. The result of experiment shows that the method of time series and neural network are effective to diagnose the occurrence and the development of the fatigue crack’s degree in ulterior place of the supporting shaft.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
Rotary bending fatigue tests were carried out with two kinds of materials, S43C and S50C, using the front engine and front drive shaft （FF shaft） of vehicle. The specimens were induction hardened about 1.0mm depth f...Rotary bending fatigue tests were carried out with two kinds of materials, S43C and S50C, using the front engine and front drive shaft （FF shaft） of vehicle. The specimens were induction hardened about 1.0mm depth from the specimen surface, and the hardness value on the surface was about HRC56-60. The tested environment temperatures were -30, 25 and 80℃ in order to look over effect of the induction hardening and the environmental temperatures on the fatigue characteristics. The fatigue limit of induction hardened specimens increased more about 45% than non-hardened specimens showing that the endurances of S43C and S50C were 98.1 and 107.9MPa in non-hardened samples, 147.1 and 156.9MPa in hardened samplesrespectably. The maximum tensile and compressive stress on the small circular defect was about ＋250 and -450MPa respectively when circular defect is situated on top and bottom. The fatigue life increased 80, 25 and -30℃ in order regardless of hardening. In comparison of the fatigue lives on the basis of tested result at 25℃, the fatigue lives of non-hardened specimens decreased about 35%, but that of hardened specimens decreased about only 5% at 80℃ more than at 25℃. And fatigue life of non-hardened and hardened specimens were about 110% and 120% higher at -30℃ than that of 25℃. Based on the result of stress distribution near the defect, the tensile and compressive stress repeatedly generated by load direction were the largest on the small circular defect due to the stress concentration.展开更多
基金This project is supported by National Natural Science Fundation of China (No. 50675066)Provincial Key Technologies R&D of Hunan, China (No. 05FJ2001)China Postdoctoral Science Foundation (No. 2005038006).
文摘To improve the diagnosis accuracy and self-adaptability of fatigue crack in ulterior place of the supporting shaft, time series and neural network are attempted to be applied in research on diag-nosing the fatigue crack’s degree based on analyzing the vibration characteristics of the supporting shaft. By analyzing the characteristic parameter which is easy to be detected from the supporting shaft’s exterior, the time series model parameter which is hypersensitive to the situation of fatigue crack in ulterior place of the supporting shaft is the target input of neural network, and the fatigue crack’s degree value of supporting shaft is the output. The BP network model can be built and net-work can be trained after the structural parameters of network are selected. Furthermore, choosing the other two different group data can test the network. The test result will verify the validity of the BP network model. The result of experiment shows that the method of time series and neural network are effective to diagnose the occurrence and the development of the fatigue crack’s degree in ulterior place of the supporting shaft.
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.
文摘Rotary bending fatigue tests were carried out with two kinds of materials, S43C and S50C, using the front engine and front drive shaft （FF shaft） of vehicle. The specimens were induction hardened about 1.0mm depth from the specimen surface, and the hardness value on the surface was about HRC56-60. The tested environment temperatures were -30, 25 and 80℃ in order to look over effect of the induction hardening and the environmental temperatures on the fatigue characteristics. The fatigue limit of induction hardened specimens increased more about 45% than non-hardened specimens showing that the endurances of S43C and S50C were 98.1 and 107.9MPa in non-hardened samples, 147.1 and 156.9MPa in hardened samplesrespectably. The maximum tensile and compressive stress on the small circular defect was about ＋250 and -450MPa respectively when circular defect is situated on top and bottom. The fatigue life increased 80, 25 and -30℃ in order regardless of hardening. In comparison of the fatigue lives on the basis of tested result at 25℃, the fatigue lives of non-hardened specimens decreased about 35%, but that of hardened specimens decreased about only 5% at 80℃ more than at 25℃. And fatigue life of non-hardened and hardened specimens were about 110% and 120% higher at -30℃ than that of 25℃. Based on the result of stress distribution near the defect, the tensile and compressive stress repeatedly generated by load direction were the largest on the small circular defect due to the stress concentration.
