Prof Brett Kirk, University of Western Australia
Industry Advisor: Peter Crosby, ASC Pty Ltd
Participants: ANSTO, ASC Pty Ltd, DSTO, Monash, QR, QUT, Rio Tinto Aluminium, Sunwater, UniNewcastle, UniSA, UWA, Curtin.
Programme Overview
Intelligent Diagnostics and Remnant Life Prediction is developing technologies to streamline and automate fault diagnosis and prognosis in intelligent maintenance systems. Intelligent diagnosis and prognosis are central to accurate maintenance planning and scheduling. These tasks currently call for expert human intervention and interpretation; actions that need to be automated.
The research programme is developing algorithms and techniques to provide the necessary basics linking condition monitoring technology with asset management systems. The reliance on human intervention to make diagnostics/prognostics will decrease as these activities are quantified with accuracy and reliability.
New technologies are being developed to determine the safe life of equipment and drive the intelligent maintenance system by concentrating in the following areas:
- Data processing and data fusion/mining,
- Intelligent diagnosis, and
- Residual/service life prediction.
