Intelligent Fault Detection, Diagnosis and Health Evaluation for Industrial Robots
نویسندگان
چکیده
The focus of this study is development an intelligent fault detection, diagnosis and health evaluation system for real industrial robots. uses principal component analysis based statistical process control with Nelson rules online detection. Several suitable are chosen sensitive When a variation detected, the performs diagnostic operation to acquire features time domain frequency from motor encoder, current sensor external accelerometer multi-class support vector machine. Additionally, fuzzy logic robot index generator proposed evaluating robot, original design reflect status robot. Finally, several aging-related faults implemented on six-axis DRV90L7A6213N by Delta Electronics, validated effectively experimental results.
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ژورنال
عنوان ژورنال: Mechanika
سال: 2021
ISSN: ['2029-6983', '1392-1207']
DOI: https://doi.org/10.5755/j02.mech.24401