Diesel engine fault simulation and automated diagnostics

Funding or Partner Organisation: Australian Research Council (ARC SPIRT Grant)

Start year: 2001

Summary: This project will develop a number of techniques for the diagnostics of diesel engines, by developing a dynamic model on which a range of faults can be simulated. In this way, neural networks can be trained to recognise the symptoms of these faults without having to experience them in practice, which would not be economically feasible. Signal processing techniques will be developed to extract features from torsional vibration signals, and signals from accelerometers mounted externally on the engine. The main beneficiary of these techniques will be the mining industry, the economic backbone of many regional parts of Australia.

Acknowledgement of Country

UTS acknowledges the Gadigal people of the Eora Nation, the Boorooberongal people of the Dharug Nation, the Bidiagal people and the Gamaygal people, upon whose ancestral lands our university stands. We would also like to pay respect to the Elders both past and present, acknowledging them as the traditional custodians of knowledge for these lands.