Multiple Fault Detection and Isolation Using the Haar Transform, Part 2: Application to the Stamping Process

[+] Author and Article Information
C. K. H. Koh

School of Mechanical and Production Engineering, Nanyang Technological University, Singapore

J. Shi

Industrial and Operations Engineering Department, University of Michigan, Ann Arbor, MI 48109

W. J. Williams

Electrical Engineering and Computer Science Department, University of Michigan, Ann Arbor, MI 48109

J. Ni

Mechanical Engineering and Applied Mechanics Department, University of Michigan, Ann Arbor, MI 48109

J. Manuf. Sci. Eng 121(2), 295-299 (May 01, 1999) (5 pages) doi:10.1115/1.2831219 History: Received October 01, 1996; Revised April 01, 1998; Online January 17, 2008


The sheet metal drawing operation is a complex manufacturing process involving more than forty process variables. The intricate interaction among these variables affect the forming tonnage which is measured by strain gages mounted on the press. A fault is said to occur when any of these process variables deviate beyond their specified limits. Current detection schemes based on thresholding do not fully exploit the information in the tonnage signals for the detection and isolation of multiple fault condition. It is thus an excellent case study for demonstrating the implementation of the detection methodology presented in Part 1. By partitioning the tonnage signature into disjoint segments, mutually exclusive sets of Haar coefficients can be used to isolate faults in each stage of the process.

Copyright © 1999 by The American Society of Mechanical Engineers
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