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Fault Detection and Diagnosis of Electro-Mechanical Systems Based on Real-time Data

CHAO, YUE
http://rave.ohiolink.edu/etdc/view?acc_num=ucin1215092937

Abstract Details

2008, MS, University of Cincinnati, Engineering : Computer Science.
The purpose of our research is to build a computer-based system that utilized real-timeoperating data to detect and diagnose malfunction in electro-mechanical systems. The methodology is to use assessment chart, which uses small number of data and control chart, to evaluate the performance of mechanical system. This method can be applied to a subsystem or be extended to the entire electro-mechanical systems. In order to achieve our research goal, our system is implemented in the following steps: 1) build a model which can characterize a mechanical system, 2) review the expert experience and control strategy of such a mechanical system to establish the assessment chart based FDD system, 3) monitor the actual status of the system in real time to assure the system is operating efficiently, and 4) make decision on the collected real-time data to detect any abnormality in the performance of the target system. This approach is applied to a real building HVAC system with genuine data. The result of our experiment shows that our strategy successfully detects most of faults introduced in the building system.
Chia-Yung Han, PhD (Committee Chair)
Raj Bhatnagar, PhD (Committee Member)
Qing-An Zeng, PhD (Committee Member)
96 p.
Computer Science

Recommended Citations

Citations

  • CHAO, Y. (2008). Fault Detection and Diagnosis of Electro-Mechanical Systems Based on Real-time Data [Master's thesis, University of Cincinnati]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1215092937

    APA Style (7th edition)

  • CHAO, YUE. Fault Detection and Diagnosis of Electro-Mechanical Systems Based on Real-time Data. 2008. University of Cincinnati, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ucin1215092937.

    MLA Style (8th edition)

  • CHAO, YUE. "Fault Detection and Diagnosis of Electro-Mechanical Systems Based on Real-time Data." Master's thesis, University of Cincinnati, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1215092937

    Chicago Manual of Style (17th edition)

ucin1215092937
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© 2008, all rights reserved.
This open access ETD is published by University of Cincinnati and OhioLINK.