Use of parameter estimation for the detection and diagnosis of faults on electric train door systems

H Dassanayake; Clive Roberts; Colin Goodman; Andrew Tobias

doi:10.1243/1748006XJRR265

Use of parameter estimation for the detection and diagnosis of faults on electric train door systems

H Dassanayake, Clive Roberts, Colin Goodman, Andrew Tobias

Research output: Contribution to journal › Article

11 Citations (Scopus)

Abstract

The results of tests on a new class of closed-loop electric train door were used to construct a mathematical model that could form the basis of a fast-response condition monitoring system. Faults are detected by identifying variations in selected mechanical and electrical hardware characteristics, these being evaluated through parameter estimation. The main obstacle is signal noise, but this can be overcome with linear integral pre-filtering.

Original language	English
Pages (from-to)	271-278
Number of pages	8
Journal	Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability
Volume	223
Issue number	4
DOIs	https://doi.org/10.1243/1748006XJRR265
Publication status	Published - 1 Dec 2009

Keywords

fault diagnosis
parameter estimation
condition monitoring
predictive maintenance
fault detection

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10.1243/1748006XJRR265

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abstract = "The results of tests on a new class of closed-loop electric train door were used to construct a mathematical model that could form the basis of a fast-response condition monitoring system. Faults are detected by identifying variations in selected mechanical and electrical hardware characteristics, these being evaluated through parameter estimation. The main obstacle is signal noise, but this can be overcome with linear integral pre-filtering.",

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AU - Roberts, Clive

AU - Goodman, Colin

AU - Tobias, Andrew

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AB - The results of tests on a new class of closed-loop electric train door were used to construct a mathematical model that could form the basis of a fast-response condition monitoring system. Faults are detected by identifying variations in selected mechanical and electrical hardware characteristics, these being evaluated through parameter estimation. The main obstacle is signal noise, but this can be overcome with linear integral pre-filtering.

KW - fault diagnosis

KW - parameter estimation

KW - condition monitoring

KW - predictive maintenance

KW - fault detection

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DO - 10.1243/1748006XJRR265

M3 - Article

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JO - Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability

JF - Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability

IS - 4

ER -

Use of parameter estimation for the detection and diagnosis of faults on electric train door systems

Abstract

Keywords

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