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Research programs

Condition monitoring

UTS researchers have applied research expertise in Condition Monitoring and Condition Based Maintenance systems for critical infrastructure/assets. These include:
  • Large scale data analysis including high-dimensional data correlation, frequent pattern mining, anomaly detection and data feature selection and extraction
  • Sensing, perception and control of intelligent machines in unstructured environments
  • New optimisation techniques in the field of combinatorial optimisation 
  • Practical applications (planning & scheduling) of large scale mixed integer linear programming 

UTS is one of eight Australian universities participating in the Rail Manufacturing Cooperative Research Centre (RMCRC) and currently has three active research and innovation projects in the area of Condition Based Monitoring with industry partner Downer Rail.

The three research teams within UTS currently making contributions in this area are:

  • Centre for Autonomous Systems (CAS) — multi sensor fusion, mapping and control will be leveraged to provide robotic platforms capable of automating the capturing, extraction and enacting on sensor information for improved condition assessment and maintenance of rolling stock
  • Global Big Data Technologies Centre (GBDTC) — existing large scale data records will be leveraged through advanced analytics skills to provide enhanced information on fault detection and prediction impacts for maintenance procedures of fault alerts
  • Optimisation Group (OG) — will develop efficient optimisation procedures for planning and scheduling in the maintenance centre, integrated with mobile maintenance services.

All research and innovation projects are being undertaken in collaboration with commercial service providers engaged in active maintenance programs. All research includes on-site testing and iterative improvement methods.

UTS welcomes post-graduate research students and internships wishing to be embedded within these programs where feasible.