基于IAGA-BP的复杂机电产品线缆故障定位方法研究

Research on Cable Fault Location Method for Complex Mechatronic Products Based on IAGA-BP

针对复杂机电产品线缆断路故障定位难的问题,本文提出一种改进的自适应遗传算法与误差逆向传播神经网络相结合的线缆断路故障定位方法。首先,采用改进的自适应遗传算法对误差逆向传播神经网络的权值阈值选取进行优化;然后,将预测的定位结果与同类型的算法进行比较,结果表明改进的自适应遗传算法与误差逆向传播神经网络相结合的方法对定位线缆故障距离效果更好。最后,结合某相控阵雷达机柜中的故障线缆实例,验证了本文提出的方法在复杂机电产品线缆断路故障定位方面的可行性。

Aimed at the problem of difficulty in locating the cable open-circuit fault in complex mechatronic products,a cable open-circuit fault location method which combines improved adaptive genetic algorithm with back propagation BP neural network is proposed in this paper.The weight threshold selection of back propagation BP neural network is opti⁃mized by the improved adaptive genetic algorithm,and the predicted location results are compared with those of the same type of algorithm.Results show that the improved adaptive genetic algorithm combined with back propagation BP neural network is more effective in locating the cable fault distance.Finally,a faulty cable in a phased array radar cabi⁃net is taken as an example,and the feasibility of the proposed method in cable open-circuit fault location for complex mechatronic products is verified.