PHM system with comprehensive data analytics to provide localized reasoning for a failure prediction
2022-26-1230
05/26/2022
- Event
- Content
- Aircraft system contains components to perform system core functionality, monitor system health and record the health status. The recorded health status data provides useful information that leads to the root cause of a failure. The maintenance activities are performed based on the routine procedure and manual approach to identify failure. Most system maintenance are ignored due to the failure to identify system health deterioration. The failure in aircraft systems is monitored periodically from various types of data in the aircraft such as Flight Data recorder (FDR), Aircraft Condition Monitoring System (ACMS), Weather, Maintenance and Pilot Report (PIREP) data. The fault data is embedded in these collections of data however the actual reasoning of the system failure is very difficult and cumbersome to identify and end up in the replacement of the failed component without understanding the cause of the failure. This is because the typical field failure analysis is performed in isolation to analyze the failure in a particular system and only in case of major failure the detailed analysis of the entire aircraft is performed. In all practical scenarios it is understood that one of the main reasons for a failure in a system is due to the operational impact of other aircraft systems and vis-a-vie. Today data analytics are effectively used for predictive health management. With the large amount of data collected in the avionics systems it is difficult to identify the root cause of the failure or health deterioration. This synopsis provide insight into prognostic health of the system using the critical parameters based on data analytics and provide the localized reasoning for the predicted failure.
- Citation
- Sundaramurthy, A., "PHM system with comprehensive data analytics to provide localized reasoning for a failure prediction," SAE Technical Paper 2022-26-1230, 2022, .