Crankshaft is regarded as an important component of engines, and it is an important application of remanufacturing because of its high added value. However, the fatigue failure research of remanufactured crankshaft is...Crankshaft is regarded as an important component of engines, and it is an important application of remanufacturing because of its high added value. However, the fatigue failure research of remanufactured crankshaft is still in its primary stage. Thus, monitoring and investigating the fatigue failure of the remanufacturing crankshaft is crucial. In this paper, acoustic emission （AE） technology and machine vision are used to monitor the four-point bending fatigue of 42CrMo, which is the material of crankshaft. The specimens are divided into two categories, namely, pre-existing crack and non-pre- existing crack, which simulate the crankshaft and crank- shaft blank, respectively. The analysis methods of para- meter-based AE techniques, wavelet transform （WT） and SEM analysis are combined to identify the stage of fatigue failure. The stage of fatigue failure is the basis of using AE technology in the field of remanufacturing crankshafts. The experiment results show that the fatigue crack propagation style is a transgranular fracture and the fracture is a brittle fracture. The difference mainly depends on the form of crack initiation. Various AE signals are detected by parameter analysis method. Wavelet threshold denoising and WT are combined to extract the spectral features of AE signals at different fatigue failure stages.展开更多
基金This research was supported by the National Natural Science Foundation of China （Grant Nos. 51535011 and 51275151）.
文摘Crankshaft is regarded as an important component of engines, and it is an important application of remanufacturing because of its high added value. However, the fatigue failure research of remanufactured crankshaft is still in its primary stage. Thus, monitoring and investigating the fatigue failure of the remanufacturing crankshaft is crucial. In this paper, acoustic emission （AE） technology and machine vision are used to monitor the four-point bending fatigue of 42CrMo, which is the material of crankshaft. The specimens are divided into two categories, namely, pre-existing crack and non-pre- existing crack, which simulate the crankshaft and crank- shaft blank, respectively. The analysis methods of para- meter-based AE techniques, wavelet transform （WT） and SEM analysis are combined to identify the stage of fatigue failure. The stage of fatigue failure is the basis of using AE technology in the field of remanufacturing crankshafts. The experiment results show that the fatigue crack propagation style is a transgranular fracture and the fracture is a brittle fracture. The difference mainly depends on the form of crack initiation. Various AE signals are detected by parameter analysis method. Wavelet threshold denoising and WT are combined to extract the spectral features of AE signals at different fatigue failure stages.
