Many manufacturing systems are controlled using discrete sensors and actuators. The changes in values of the corresponding control I/O signals are events. The timing and sequencing relationships of these events can be used to determine whether a system is operating as expected, or whether a fault may have occurred. In this paper, we present a method of learning interevent timing relationships using observations from a correctly operating system. The sample statistics of the observation characteristic of correct system operation are used to create a confidence space of possible timing relationships (acceptable delay intervals) of the underlying system. Any timing relationship used as a specification of correct observation for fault monitoring will result in some level of false alarms and missed detections among all the possible relationships in the confidence space. Given a relative cost of false alarms versus missed detections, the timing relationships can be chosen to minimize the worst case total of the false alarm and missed detection costs over the confidence space. Simulations are used to evaluate the performance of the chosen timing relationship over a range of perturbed systems.
|Number of pages||15|
|Journal||IEEE Transactions on Systems, Man, and Cybernetics Part A:Systems and Humans|
|State||Published - Jan 2000|
Bibliographical noteFunding Information:
Manuscript received December 3, 1996; revised January 22, 1999 and August 2, 1999. This work was supported in part by Eaton Corporation, Rockwell International, NSF Grants ECS-9807106 and CDA-9502645, and ARO Grant DAAH04-96-0339.
ASJC Scopus subject areas
- Control and Systems Engineering
- Human-Computer Interaction
- Computer Science Applications
- Electrical and Electronic Engineering