Modeling of Laser Cladding High Entropy Alloys Friction and Wear Monitoring

Yanjun Jia

School of Mechanical Engineering Tianjin Polytechnic University, Tianjin, 300387, China

Abstract: Aiming at the problem of low precision of traditional wear monitoring model, a friction and wear monitoring model of laser cladding high entropy alloys is constructed. After decomposition of the input wear signal by wavelet packet decomposition, FFT is used to extract the characteristic parameters in the decompo-sition sequence. Taking the characteristic parameters as the parameters of the neural network, the training sample set is used to train the neural network. Wear data were analyzed by using neural network after training. Combining d-s theory to determine the relevant parameters of the model and improve the monitoring accuracy, the construction of the monitoring model is completed. Compared with the traditional monitoring model, the monitoring precision of the established monitoring model is about 3 times that of the traditional monitoring model, which is more suitable for monitoring the friction and wear of laser cladding high entropy alloys.

Keywords: Laser cladding; High entropy alloys; Friction wear; Monitoring and modeling