Automatic Color Inspection for Colored Wires in Electric Cables

Abstract

In this paper, an automatic optical inspection system for checking the sequence of colored wires in electric cable is presented. The system is able to inspect cables with flat connectors differing in the type and number of wires. This variability is managed in an automatic way by means of a self-learning subsystem and does not require manual input from the operator or loading new data to the machine. The system is coupled to a connector crimping machine and once the model of a correct cable is learned, it can automatically inspect each cable assembled by the machine. The main contributions of this paper are: (i) the self-learning system; (ii) a robust segmentation algorithm for extracting wires from images even if they are strongly bent and partially overlapped; (iii) a color recognition algorithm able to cope with highlights and different finishing of the wire insulation. We report the system evaluation over a period of several months during the actual production of large batches of different cables; tests demonstrated a high level of accuracy and the absence of false negatives, which is a key point in order to guarantee defect-free productions

Automatic Optical Inspection System for Wire Color Sequence Detection

“…In the existing methods, rule-based methods on feature extraction are widely used such as [ 16 , 17 , 18 ]. Although they are not more accurate than deep neural networks trained with large datasets, this technique is still needed due to its low complexity, low hardware requirements, and fast execution speed.…”

An Autonomous Operational Service System for Machine Vision-based Inspection towards Smart Factory of Manufacturing Multi-wire Harnesses

“…Among these methods, automatic inspection of wire harnesses has been studied along with methods of detecting the components by the pattern matching method, or measuring the length using the edge detection method [19]. Studies have also considered error detection [20] and systems for testing automatic connectors for testing flat connectors with different types and numbers of wires [21].…”

Diagnóstico de Degradação de Isolamento de Cabos Elétricos de Baixa Tensão por Análise de Imagem e Classificação por Rede Neural Artificial

“…Uma ferramenta computacional muito empregada em substituição à inspeção visual é a análise de cores, um campo amplamente explorado na visão computacional (Ghidoni, Finotto and Menegatti, 2015). Um recente trabalho técnico correlaciona a detecção do fim da vida útil de cabos elétricos de baixa tensão com, somente, o componente brilho do modelo computacional de representação de cor HSV (Vieira, Muniz and Rampinelli, 2018).…”