Electromagnetic coupling between conductors is a fundamental concern in locomotive harnesses, where manual bundling introduces significant uncertainty and variability. Accurate and efficient crosstalk prediction under such conditions remains challenging. A rapid modeling and crosstalk prediction method for manually assembled harnesses is presented. The harness is first converted into uniform cascaded segments (UCS) using the cascade method. The arrangement characteristics of UCS are then utilized to transform random segment relationships into a graph search problem. An improved ant colony algorithm is employed to optimize the graph search, enabling efficient modeling of manually bundled harness structures. Based on the constructed model, crosstalk is computed using the chain parameter method with distributed parameter matrix transformations. Comparisons with existing method and measured result validate the accuracy and effectiveness of the proposed method. The results demonstrate that the proposed method offers significant advantages for modeling wiring harnesses with a large number of wires.
Yang et al. (Tue,) studied this question.
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