CAD-Assisted 3D Assembly of Automobile Electrical Switch considering PSO-BP Neural Network Algorithm

• Published in: Journal of Electrical and Computer Engineering Vol. 2022; pp. 1 - 11
• Main Author: Zhang, Hanting
• Format: Journal Article
• Language: English
• Published: New York Hindawi 05.05.2022; John Wiley & Sons, Inc; Wiley
• Subjects: Algorithms; Assembly; Back propagation networks; Coordinate transformations; Efficiency; Neural networks; Process planning; Product design; Software; Switches; User interface
• ISSN: 2090-0147; 2090-0155; 2090-0155
• DOI: 10.1155/2022/6454942

The installation of automotive electrical switches is a complex three-dimensional space assembly project which has high requirements for installation accuracy. In order to improve the installation effect of automotive electrical switches, this paper applies the PSO-BP neural network algorithm to automotive electrical switches and integrates PSO and ELM algorithms. The training speed of the ELM model is fast, the model generalizes the data well, and the noise data have little effect on the model. Moreover, this article combines simulation research to evaluate the effect of this algorithm. After confirming the performance of the effect, this paper uses a case study to study the effect of the application of the PSO-BP neural network algorithm to the automotive electrical switch. The research results show that the CAD-assisted 3D assembly system of automobile electrical switch considering PSO-BP neural network algorithm has a good effect.