Masters Theses

Keywords and Phrases

Condition Monitoring; Mahalanobis Distance

Abstract

"Classification and forecasting are useful concepts in the field of condition monitoring. Condition monitoring refers to the analysis and monitoring of system characteristics to understand and identify deviations from normal operating conditions. This can be performed for prediction, diagnosis, or prognosis or a combination of any these purposes. Fault identification and diagnosis are usually achieved through data classification, while forecasting methods are usually used to accomplish the prediction objective. Data gathered from monitoring systems often consists of multiple multivariate time series and is fed into a model for data analysis using various techniques. One of the data analysis techniques used is the Mahalanobis-Taguchi strategy (MTS) because of its suitability for multivariate data analysis. MTS provides a means of extracting information in a multidimensional system by integrating information from different variables into a single composite metric. MTS is used to conduct analysis on the measurement parameters and seeks a correlation with the result while also seeking to optimize the analysis by identifying variables of importance strongly correlated with a defect or fault occurrence. This research presents the application of a MTS based system for predicting faults in heavy duty vehicles and the application of MTS in a multiclass classification problem. The benefits and practicality of the methodology in industrial applications are demonstrated through the use of real world data and discussion of results."--Abstract, page iv.

Advisor(s)

Cudney, Elizabeth A.

Committee Member(s)

Corns, Steven
Smith, Brian Keith

Department(s)

Engineering Management and Systems Engineering

Degree Name

M.S. in Systems Engineering

Publisher

Missouri University of Science and Technology

Publication Date

Spring 2014

Journal article titles appearing in thesis/dissertation

  • A review of literature on Mahalanobis-Taguchi strategy in condition monitoring
  • Predicting faults in heavy duty vehicles using the Mahalanobis-Taguchi strategy
  • Mahalanobis-Taguchi system for multiclass classification of steel plates fault

Pagination

67 pages

Note about bibliography

Includes bibliographical references.

Rights

© 2014 Adebolaji A. Jobi-Taiwo, All rights reserved.

Document Type

Thesis - Open Access

File Type

text

Language

English

Library of Congress Subject Headings

Machinery -- Monitoring -- Data processing
Commercial vehicles -- Monitoring -- Data processing
Taguchi methods (Quality control)
Multivariate analysis

Thesis Number

T 10453

Electronic OCLC #

882478844

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