LEADER 04249nam 22006255 450 001 9910254360503321 005 20200704162119.0 010 $a3-319-44932-X 024 7 $a10.1007/978-3-319-44932-6 035 $a(CKB)3710000000852439 035 $a(EBL)4676660 035 $a(DE-He213)978-3-319-44932-6 035 $a(MiAaPQ)EBC4676660 035 $a(PPN)195507347 035 $a(EXLCZ)993710000000852439 100 $a20160908d2017 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aDesign of an Intelligent Embedded System for Condition Monitoring of an Industrial Robot /$fby Alaa Abdulhady Jaber 205 $a1st ed. 2017. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2017. 215 $a1 online resource (302 p.) 225 1 $aSpringer Theses, Recognizing Outstanding Ph.D. Research,$x2190-5053 300 $aDescription based upon print version of record. 311 $a3-319-44931-1 320 $aIncludes bibliographical references at the end of each chapters. 327 $aChapter 1 Introduction -- Chapter 2 Literature Review -- Chapter 3 Signal Processing Techniques for Condition Monitoring -- Chapter 4 Puma 560 Robot and its Dynamic Characteristics -- Chapter 5 Robot Hardware, Transmission Faults and Data Acquisition -- Chapter 6 Robot Vibration Analysis and Feature Extraction -- Chapter 7 Intelligent Condition Monitoring System Design -- Chapter 8 Embedded System Design -- Chapter 9 Embedded Software Design, System Testing and Validation -- Chapter 10 Conclusions and Future Work -- References -- Appendices. 330 $aThis thesis introduces a successfully designed and commissioned intelligent health monitoring system, specifically for use on any industrial robot, which is able to predict the onset of faults in the joints of the geared transmissions. However the developed embedded wireless condition monitoring system leads itself very well for applications on any power transmission equipment in which the loads and speeds are not constant, and access is restricted. As such this provides significant scope for future development. Three significant achievements are presented in this thesis. First, the development of a condition monitoring algorithm based on vibration analysis of an industrial robot for fault detection and diagnosis. The combined use of a statistical control chart with time-domain signal analysis for detecting a fault via an arm-mounted wireless processor system represents the first stage of fault detection. Second, the design and development of a sophisticated embedded microprocessor base station for online implementation of the intelligent condition monitoring algorithm, and third, the implementation of a discrete wavelet transform, using an artificial neural network, with statistical feature extraction for robot fault diagnosis in which the vibration signals are first decomposed into eight levels of wavelet coefficients. 410 0$aSpringer Theses, Recognizing Outstanding Ph.D. Research,$x2190-5053 606 $aRobotics 606 $aAutomation 606 $aElectronic circuits 606 $aMicroprogramming  606 $aRobotics and Automation$3https://scigraph.springernature.com/ontologies/product-market-codes/T19020 606 $aCircuits and Systems$3https://scigraph.springernature.com/ontologies/product-market-codes/T24068 606 $aControl Structures and Microprogramming$3https://scigraph.springernature.com/ontologies/product-market-codes/I12018 615 0$aRobotics. 615 0$aAutomation. 615 0$aElectronic circuits. 615 0$aMicroprogramming . 615 14$aRobotics and Automation. 615 24$aCircuits and Systems. 615 24$aControl Structures and Microprogramming. 676 $a670.4272 700 $aJaber$b Alaa Abdulhady$4aut$4http://id.loc.gov/vocabulary/relators/aut$0933287 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910254360503321 996 $aDesign of an Intelligent Embedded System for Condition Monitoring of an Industrial Robot$92100667 997 $aUNINA