面向电子故障诊断与维修的联合优化数学模型研究  

Research on Joint Optimization Mathematical Model for Electronic Fault Diagnosis and Maintenance

作　　者：樊葡萄 FAN Putao(Xingzhi College of Xi’an University of Finance and Economics,Xi’an 710038,China)

机构地区：[1]西安财经大学行知学院,西安710038

出　　处：《自动化与仪器仪表》2025年第3期76-80,共5页Automation & Instrumentation

摘　　要：为了提高汽车电子设备诊断与维修效率,保证汽车维修厂能够准时向客户交付维修完成后的车辆,提出了一种基于改进细菌觅食算法的汽车电子设备维修人员调度优化数学模型。首先针对细菌觅食算法的缺点进行改进,然后构建汽车电子设备维修人员调度优化数学模型,最后将改进后的细菌觅食算法应用于模型求解测试。测试结果表明:传统BFO算法和GA算法在求解时,若算例规模小,其寻优精度可以达到70%~80%,但随着算例规模变大,寻优精度只有50%左右。PSO算法对前两种算法相比稍微稳定一些,但面对大规模算例寻优精度也只有60%。改进的BFO算法随着维修任务数量的增加,收敛速度增加不明显,寻优精度一直维持90%以上,最高达到93%。综上,所构建模型具有可行性,改进的BFO算法收敛速度快、寻优能力强,具有良好的稳定性,十分适用于汽车电子设备维修人员调度优化的求解。In order to improve the efficiency of diagnosis and maintenance of automotive electronic equipment and ensure that car repair shops can deliver repaired vehicles to customers on time,this paper proposes a mathematical model for optimizing the scheduling of automotive electronic equipment maintenance personnel based on an improved bacterial foraging algorithm.Firstly,improvements were made to the shortcomings of the bacterial foraging algorithm.Then,a mathematical model for optimizing the scheduling of automotive electronic equipment maintenance personnel was constructed.Finally,the improved bacterial foraging algorithm was applied to model solving and testing.The test results show that the traditional BFO algorithm and GA algorithm can achieve optimization accuracy of 70% to 80% when solving problems with small case sizes.However,as the case size increases,the optimization accuracy is only about 50%.The PSO algorithm is slightly more stable compared to the first two algorithms,but its optimization accuracy for large-scale examples is only 60%.As the number of maintenance tasks increases,the convergence speed of the improved BFO algorithm in this article does not increase significantly,and the optimization accuracy remains above 90%,reaching a maximum of 93%.In summary,the model constructed in this article is feasible.The improved BFO algorithm has fast convergence speed,strong optimization ability,and good stability,making it very suitable for solving the scheduling optimization of automotive electronic equipment maintenance personnel.

关 键 词：电子设备 细菌觅食算法 数学模型 

分 类 号：TP39[自动化与计算机技术—计算机应用技术]