David Antory

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This paper presents a case study of the application of a data-driven monitoring technique to diagnose air leaks in an automotive diesel engine. Using measurement signals taken from the sensors/actuators which are present in a modern automotive vehicle, a data-driven diagnostic model is built for condition monitoring purposes. Detailed investigations have(More)
This paper presents an innovative diagnostic method tailored for automotive electronic system diagnostic tools. By incorporating a Bayesian Belief Network (BBN) technique, the proposed method is capable of guiding vehicle diagnostics in a probabilistic manner. In addition, the method features a multiple-DTC-orientated troubleshooting strategy, and is(More)
This paper presents simple and practical methodologies for early engine misfire detection. Two diagnostics models, one based on standard linear system identification approaches and a second using a novel nonlinear extension of the linear approaches, involving a multilayer perceptron neural network, were investigated. The models were validated using(More)
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