Civil aircraft air-conditioning system online health monitoring data acquisition and analysis method

Abstract

The invention discloses a civil aircraft air-conditioning system online health monitoring data acquisition and analysis method, and is applied to real-time monitoring and early monitoring and early warning of failure of a large civil aircraft air-conditioning system. As for online health monitoring of the modern large civil aircraft air-conditioning system, firstly the health baseline model of the air-conditioning system is established by using the air-conditioning system monitoring parameters under the failure-free condition and the baseline model mining technology; then the deviation value of the monitoring parameters of the key position is determined to act as the monitoring object, and the baseline value is subtracted from the actual observation value of the monitoring parameters of the air-conditioning system so that the deviation value sequence of the monitoring parameters is obtained; and then the deviation value sequence is monitored and early warning of the failure of the air-conditioning system is emitted according to the abnormal deviation value sequence. The problems that the direct monitoring performance parameters of the civil aircraft air-conditioning system have high discrete degree and the early failure characteristics are not obvious can be solved, and early warning can be timely emitted at the early stage of the system failure by monitoring the deviation value sequence so that the real-time monitoring requirement of the large civil aircraft air-conditioning system can be met.

Description

technical field [0001] The invention relates to the field of equipment health monitoring and fault diagnosis, in particular to an online health monitoring data collection and analysis method for an air-conditioning system of a civil aircraft. Background technique [0002] The modern civil aircraft status monitoring system records the environment, load, status and performance of the aircraft system during operation, and the data is stored in the Quick Access Recorder (QAR), which records a wealth of system health status related flight data The information can not only be used for flight quality monitoring and evaluation, but also provide a rich data source for system fault monitoring and diagnosis. From the perspective of data mining, the application of QAR data for fault diagnosis and prediction of civil aircraft systems, and the assistance of maintenance personnel to complete preventive maintenance work are of great significance for effectively ensuring the operational safe...

AI Technical Summary

Problems solved by technology

[0006] For civil aircraft air conditioning systems, the relevant parameters that have been recorded so far include the main pipeline pressure of the air conditioning system, outlet temperature, environmental load parameters, aeroengine N1 and N2 speeds, flight altitude, flight speed, on / off status of air conditioning components, and atmospheric temperature. However, using these parameters to describe the health status of the air conditioning system is not accurate, and the direct monitoring of these performance parameters has a large dispersion, resulting in the problem that the early characteristics of the fault are not obvious

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