Bayesian and Dempster–Shafer reasoning for knowledge-based fault diagnosis: A comparative study

Even though various frameworks exist for reasoning under uncertainty, a realistic fault diagnosis task does not fit into any of them in a straightforward way. For each framework, only part of the available data and knowledge is in the desired format. Moreover, additional criteria, like clarity of inference and computational efficiency,...

Timely condition-based maintenance planning for multi-component systems

Last-minute maintenance planning is often undesirable, as it may cause downtime during operational hours, may require rescheduling of other activities, and does not allow to optimize the management of spare parts, material, and personnel. In spite of the aforementioned drawbacks of last-minute planning, most existing methods plan maintenance...

Combining knowledge and historical data for system-level fault diagnosis of HVAC systems

Interdependencies among system components and the existence of multiple operating modes present a challenge for fault diagnosis of Heating, Ventilation, and Air Conditioning (HVAC) systems. Reliable and timely diagnosis can only be ensured when it is performed in all operating modes, and at the system level, rather than at the level of the...

Fault diagnosis using spatial and temporal information with application to railway track circuits

Adequate fault diagnosis requires actual system data to discriminate between healthy behavior and various types of faulty behavior. Especially in large networks, it is often impracticable to monitor a large number of variables for each subsystem. This results in a need for fault diagnosis methods that can work with a limited set of monitoring...