Design Of An Intelligent Embedded System For Condition Monitoring Of An Industrial Robot

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Design of an Intelligent Embedded System for Condition Monitoring of an Industrial Robot

Design of an Intelligent Embedded System for Condition Monitoring of an Industrial Robot
Author :
Publisher : Springer
Total Pages : 279
Release :
ISBN-10 : 9783319449326
ISBN-13 : 331944932X
Rating : 4/5 (32X Downloads)

Book Synopsis Design of an Intelligent Embedded System for Condition Monitoring of an Industrial Robot by : Alaa Abdulhady Jaber

Download or read book Design of an Intelligent Embedded System for Condition Monitoring of an Industrial Robot written by Alaa Abdulhady Jaber and published by Springer. This book was released on 2016-09-08 with total page 279 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis introduces a successfully designed and commissioned intelligent health monitoring system, specifically for use on any industrial robot, which is able to predict the onset of faults in the joints of the geared transmissions. However the developed embedded wireless condition monitoring system leads itself very well for applications on any power transmission equipment in which the loads and speeds are not constant, and access is restricted. As such this provides significant scope for future development. Three significant achievements are presented in this thesis. First, the development of a condition monitoring algorithm based on vibration analysis of an industrial robot for fault detection and diagnosis. The combined use of a statistical control chart with time-domain signal analysis for detecting a fault via an arm-mounted wireless processor system represents the first stage of fault detection. Second, the design and development of a sophisticated embedded microprocessor base station for online implementation of the intelligent condition monitoring algorithm, and third, the implementation of a discrete wavelet transform, using an artificial neural network, with statistical feature extraction for robot fault diagnosis in which the vibration signals are first decomposed into eight levels of wavelet coefficients.


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