Testing an internal combustion engine.

摘要

Test measurements are collected from an engine. The test measurements are "pre-processed" by filtering and subsampling techniques so that Principle Component Analysis can be applied to condense the quantity of test measurements while still retaining a statistically accurate indication of a majority of the original measurements. The pre-processed test measurements are then passed through one or more classifiers including: a Neural Network classifier, a Fuzzy Logic classifier, a cluster-based classifier (or "Spherical" classifier) and a Genetic Program classifier. Results from these classifiers can be used to obtain a verdict about an engine (i.e., whether the engine is "normal" or "faulty").