Embedded high-efficiency computation platform oriented to onboard fault prediction and health management, and method
A fault prediction and health management technology, applied in the registration/indication of vehicle operation, instruments, registration/indication, etc., can solve the problems such as the inability of the aircraft PHM system to monitor and diagnose the status of the fault, and the failure of the aircraft to be discovered in time. Achieving the effect of rich extensible interfaces, strong expansion ability and strong expansibility
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specific Embodiment approach 1
[0032] Specific implementation mode one: refer to Figure 1 to Figure 10 Specifically, an embedded high-energy-efficiency computing platform oriented to airborne fault prediction and health management described in this embodiment includes: a data processing unit, a data cache and storage unit, and an onboard bus interface unit;
[0033] The onboard bus interface unit is used to collect flight parameters on the onboard bus in real time, and is also used to send the analysis results sent by the data processing unit to the onboard bus.
[0034] The data processing unit communicates with the on-board bus through the on-board bus interface unit, and is used to analyze the flight parameters on the on-board bus to obtain analysis results.
[0035] Among them, the ARMA model is embedded in the data processing unit, and the flight parameters on the airborne bus are used to fit the model using the RLS algorithm, and the fitting result is obtained as the analysis result of the data proce...
specific Embodiment approach 2
[0070] Specific implementation mode two: An embedded high-energy-efficiency computing method for airborne fault prediction and health management described in this implementation mode, the method is:
[0071] Collect and store flight parameters on the onboard bus,
[0072] Use standard parameters to initialize the ARMA model (Auto-Regressive and Moving Average Model, auto-regressive and moving average model),
[0073] Use the currently collected flight parameters to use the RLS algorithm to fit the ARMA model to obtain the fitting result. The fitting result is the predicted value of the flight parameters at the next moment, and the predicted value is used as the analysis result of the flight parameters.
[0074] send analysis results to the onboard bus,
[0075] Determine whether to end the analysis, if yes, end the analysis, otherwise re-acquire and store the flight parameters on the current on-board bus.
[0076] In actual operation of this embodiment, if Figure 11 as sho...
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