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INTELLIGENT CONDITION BASED MAINTENANCE - A SOFT COMPUTING APPROACH TO SYSTEM DIAGNOSIS AND PROGNOSIS

KOTHAMASU, RANGANATH
http://rave.ohiolink.edu/etdc/view?acc_num=ucin1141339344

Abstract Details

2006, PhD, University of Cincinnati, Engineering : Industrial Engineering.
Maintenance is the set of activities performed on a system to sustain it in operable condition while Condition Based Maintenance (CBM) refers to the practice of triggering these activities as necessitated by the condition of the target system. CBM thus entails the process of diagnosis (of the target system) and timely identification of incipient or existing failures popularly known as Failure Detection and Identification (FDI). FDI has been given due research focus; however there is a dearth of autonomous yet interactive decision making tools that would perform diagnosis and prognosis under the precepts of CBM in a guided environment. The development of such an architecture along with the tools necessary for decision making in the realm of condition based maintenance constitute the focus of this research. The architecture and the tools developed in this research encompass the model based approach to FDI. These tools are built on Neuro-Fuzzy (NF) paradigms as they offer many advantages in the form of accuracy, adaptability and lucidity compared to other parametric and non-parametric approaches. Along with the development of a NF algorithm, suitable evaluation criteria are also explored and developed to gauge the applicability and efficiency of the developed models. Intelligent Condition Based Maintenance (ICBM) thus refers to the creation of adaptive and robust FDI models based on a model based architecture and their subsequent validation using suitable evaluation criteria. The efficiency and robustness of these ICBM tools are demonstrated by applying them in several scenarios – Simulated as well as real world.
Dr. Samuel Huang (Advisor)
109 p.
Condition Based Maintenance; Model based maintenance; Neuro-Fuzzy; Backpropagation; Information Entropy; Model selection

Recommended Citations

Citations

  • KOTHAMASU, R. (2006). INTELLIGENT CONDITION BASED MAINTENANCE - A SOFT COMPUTING APPROACH TO SYSTEM DIAGNOSIS AND PROGNOSIS [Doctoral dissertation, University of Cincinnati]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1141339344

    APA Style (7th edition)

  • KOTHAMASU, RANGANATH. INTELLIGENT CONDITION BASED MAINTENANCE - A SOFT COMPUTING APPROACH TO SYSTEM DIAGNOSIS AND PROGNOSIS. 2006. University of Cincinnati, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ucin1141339344.

    MLA Style (8th edition)

  • KOTHAMASU, RANGANATH. "INTELLIGENT CONDITION BASED MAINTENANCE - A SOFT COMPUTING APPROACH TO SYSTEM DIAGNOSIS AND PROGNOSIS." Doctoral dissertation, University of Cincinnati, 2006. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1141339344

    Chicago Manual of Style (17th edition)

ucin1141339344
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© 2006, all rights reserved.
This open access ETD is published by University of Cincinnati and OhioLINK.