DocumentCode :
6896
Title :
Automatic Color Inspection for Colored Wires in Electric Cables
Author :
Ghidoni, Stefano ; Finotto, Matteo ; Menegatti, Emanuele
Author_Institution :
Dept. of Inf. Eng., Univ. of Padova, Padua, Italy
Volume :
12
Issue :
2
fYear :
2015
fDate :
Apr-15
Firstpage :
596
Lastpage :
607
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; and (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.
Keywords :
automatic optical inspection; cables (electric); image recognition; image segmentation; production engineering computing; quality control; unsupervised learning; automatic optical color inspection; cable production; color measurements; color recognition; colored wires; connector crimping machine; defect-free productions; electric cables; quality control; self-learning subsystem; Connectors; Crimping; Image color analysis; Inspection; Visualization; Wires; Cable crimping; visual inspection; wire color measurement; wire color sequence; wire detection;
fLanguage :
English
Journal_Title :
Automation Science and Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
1545-5955
Type :
jour
DOI :
10.1109/TASE.2014.2360233
Filename :
6932505
Link To Document :
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