Optimization of laser cladding process parameters based on genetic algorithm and neural networks

Dongsheng Wang; Yichi Zhang; Yan Zhou; Lifeng Xu; Xinhua Zhou

doi:10.1117/12.2645922

30 August 2022 Optimization of laser cladding process parameters based on genetic algorithm and neural networks

Dongsheng Wang, Yichi Zhang, Yan Zhou, Lifeng Xu, Xinhua Zhou

Proceedings Volume 12309, International Conference on Advanced Manufacturing Technology and Manufacturing Systems (ICAMTMS 2022); 1230906 (2022) https://doi.org/10.1117/12.2645922
Event: International Conference on Advanced Manufacturing Technology and Manufacturing System (ICAMTMS 2022), 2022, Shijiazhuang, China

Abstract

This study optimized laser cladding process parameters by combining BP neural network (BPNN) and genetic algorithm (GA) based on the multi-layer cladding nano Al₂O₃-13 wt.%TiO₂ coating. The model structure was trained according to the orthogonal test results. The BPNN model of closed loop control temperature of the molten pool, ultrasonic vibration frequency and preheating temperature of the incubator with bonding strength and microhardness of the coating was constructed. Moreover, single-objective and multi-objective parameter optimizations were carried out to bonding strength and microhardness of the coating based on GA. Results demonstrated that the predicted values of models are very close to test values, indicating that the constructed model was accurate and reliable. The maximum bonding strength and the maximum microhardness of the coating after GA optimization are 70.7 MPa and 2025.5 HV, respectively. When weights of bonding strength and microhardness of the coating are the same, the coating achieved the optimal comprehensive performances under the 2472.0 ^oC of closed-loop control temperature of the molten pool, 31.9 kHZ of ultrasonic vibration frequency and 400 ^oC of preheating temperature of incubator. The corresponding bonding strength and microhardness are 69.1 MPa and 1835.5 HV, respectively.

Citation Download Citation

Dongsheng Wang, Yichi Zhang, Yan Zhou, Lifeng Xu, and Xinhua Zhou "Optimization of laser cladding process parameters based on genetic algorithm and neural networks", Proc. SPIE 12309, International Conference on Advanced Manufacturing Technology and Manufacturing Systems (ICAMTMS 2022), 1230906 (30 August 2022); https://doi.org/10.1117/12.2645922

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