System fault diagnostics using fault tree analysis
online resourceposted on 19.09.2008, 10:30 by Emma E. Hurdle, Lisa JacksonLisa Jackson, J.D. Andrews
Over the last 50 years advances in technology have led to an increase in the complexity and sophistication of systems. More complex systems can be harder to maintain and the root cause of a fault more difficult to isolate. Down-time resulting from a system failure can be dangerous or expensive depending on the type of system. In aircraft systems the ability to quickly diagnose the causes of a fault can have a significant impact on the time taken to rectify the problem and return the aircraft to service. In chemical process plants the need to diagnose causes of a safety critical failure in a system can be vital and a diagnosis may be required within minutes. Speed of fault isolation can save time, reduce costs and increase company productivity and therefore profits. System fault diagnosis is the process of identifying the cause of a malfunction by observing its effect at various test points. Fault tree analysis (FTA) is a method that describes all possible causes of a specified system state in terms of the state of the components within the system. A system model is used to identify the states the system should be in at any point in time. This paper presents a method for diagnosing faults in systems using FTA to explain the deviations from normal operation observed in sensor outputs. The causes of a system's failure modes will be described in terms of the component states. This will be achieved with the use of coherent and non-coherent fault trees. A coherent fault tree is constructed from AND and OR logic, therefore only considers component failed states. The non-coherent method expands this allowing the use of NOT logic which implies that the existence of component failed states and working states are both taken into account. This paper illustrates the concepts of this method by applying the technique to a simplified water tank level control system.
- Aeronautical, Automotive, Chemical and Materials Engineering
- Aeronautical and Automotive Engineering