MARC 主機 00000nam a2200457 a 4500 
001    978-3-319-44932-6 
003    DE-He213 
005    20160908161433.0 
006    m        d         
007    cr nn 008maaau 
008    160908s2017    gw      s         0 eng d 
020    9783319449326|q(electronic bk.) 
020    9783319449319|q(paper) 
024 7  10.1007/978-3-319-44932-6|2doi 
040    GP|cGP 
041 0  eng 
050  4 TS191.8 
082 04 629.892|223 
100 1  Jaber, Alaa Abdulhady 
245 10 Design of an intelligent embedded system for condition 
       monitoring of an industrial robot|h[electronic resource] /
       |cby Alaa Abdulhady Jaber 
260    Cham :|bSpringer International Publishing :|bImprint: 
300    xxxv, 279 p. :|bill. (some col.), digital ;|c24 cm 
490 1  Springer theses,|x2190-5053 
505 0  Chapter 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 
520    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 
650  0 Robots, Industrial 
650  0 Embedded computer systems 
650  0 Fault location (Engineering) 
650 14 Engineering 
650 24 Robotics and Automation 
650 24 Circuits and Systems 
650 24 Control Structures and Microprogramming 
710 2  SpringerLink (Online service) 
773 0  |tSpringer eBooks 
830  0 Springer theses 
856 40 |u