Title :
Load cell design and construct with fault detection by Probabilistic Neural Network
Author :
Moradkhani, A. ; Ahmadi, K. ; Mirmohammadhosseni, I. ; Sh, M. Aliyari ; Teshnehlab, M.
Author_Institution :
Sci. & Res. Branch, Mechatron. Dept, Islamic Azad Univ., Tehran
Abstract :
In this study a strain gage load cell as a S model has been designed which is used for measuring weight of elevator. Four methods of fixing and balancing Whetstone Bridge were considered and one way was achieved eventually which was given the best Whetstone Bridge´s output. For amplifying and measuring of changing resistance and voltage in Whetstone Bridge four current ways of amplifying and measuring were applied and with doing some modification in one of them construction of the main model was made. In this way microcontroller from the AVR family was applied for sampling of analog signal and also monitoring weight. Finally with using of Probabilistic Neural Network fault detection at zero level was carried out hence, safety of system was increased.
Keywords :
computerised instrumentation; electric resistance measurement; neural nets; probability; strain gauges; transducers; Whetstone Bridge; analog signal sampling; fault detection; microcontroller; probabilistic neural network; strain gage load cell; Bridge circuits; Current measurement; Electrical resistance measurement; Elevators; Fault detection; Microcontrollers; Neural networks; Strain measurement; Voltage; Weight measurement;
Conference_Titel :
Mechatronics and Automation, 2008. ICMA 2008. IEEE International Conference on
Conference_Location :
Takamatsu
Print_ISBN :
978-1-4244-2631-7
Electronic_ISBN :
978-1-4244-2632-4
DOI :
10.1109/ICMA.2008.4798725