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Model-Based Intelligent Fault Detection and Diagnosis for Mating Electric Connectors in Robotic Wiring Harness Assembly Systems

机译:机器人线束组装系统中基于模型的智能故障检测与诊断

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摘要

Mating a pair of electric connectors is one of the most important steps in a robotic wiring harness assembly system. A class of piecewise linear force models is proposed to describe both the successful and the faulty mating processes of connectors via an elaborate analysis of forces during different phases. The corresponding parameter estimation method of this model is also presented by adapting regular least-square estimation methods. A hierarchical fuzzy pattern matching multidensity classifier is proposed to realize fault detection and diagnosis for the mating process. This classifier shows good performance in diagnosis. A typical type of connectors is investigated in this paper. The results can easily be extended to other types. The effectiveness of proposed methods is finally confirmed through experiments.
机译:配对一对电连接器是机器人线束组装系统中最重要的步骤之一。提出了一类分段线性力模型,通过对不同阶段的力进行详尽的分析来描述连接器的成功和错误配合过程。通过采用规则的最小二乘估计方法,也提出了该模型的相应参数估计方法。提出了一种分层模糊模式匹配多密度分类器,以实现对接过程的故障检测与诊断。该分类器显示出良好的诊断性能。本文研究了一种典型的连接器类型。结果可以轻松扩展到其他类型。最后通过实验证实了所提出方法的有效性。

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