Nonlinear PCA With the Local Approach for Diesel Engine Fault Detection and Diagnosis.

Autor:	Xun Wang, Kruger, Uwe, Irwin, George W., McCullough, Geoff, McDowell, Neil
Předmět:	STATISTICAL process control FAULT location (Engineering) AUTOMOBILE engines DISTRIBUTION (Probability theory) MATHEMATICAL statistics GAUSSIAN distribution DIESEL motors VOLKSWAGEN automobiles MATHEMATICAL variables
Zdroj:	IEEE Transactions on Control Systems Technology; Jan2008, Vol. 16 Issue 1, p122-129, 8p, 4 Graphs
Abstrakt:	This brief examines the application of nonlinear statistical process control to the detection and diagnosis of faults in automotive engines. In this statistical framework, the computed score variables may have a complicated nonparametric distribution function, which hampers statistical inference, notably for fault detection and diagnosis. This brief shows that introducing the statistical local approach into nonlinear statistical process control produces statistics that follow a normal distribution, thereby enabling a simple statistical inference for fault detection. Further, for fault diagnosis, this brief introduces a compensation scheme that approximates the fault condition signature. Experimental results from a Volkswagen 1.9-L turbo-charged diesel engine are included. [ABSTRACT FROM AUTHOR]
Databáze:	Complementary Index
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