Data drive system state model online distinguishing method based on multi-combination classifiers

Abstract

The invention discloses a data drive system state model online distinguishing method based on multi-combination classifiers. The method is used for solving the technical problem that an existing data drive system state model online distinguishing method has modeling difficultly. According to the technical scheme, in combination with analysis of aircraft historical monitoring data and system operating characteristics, through design and training of the multi-combination classifiers, real-time measured data is analyzed and classified, and operating state models of all systems of an aircraft are obtained through distinguishing. The technical problem that due to the high complexity degree of the systems, physical models cannot be directly used for erecting mathematical models is solved. In the distinguishing process, due to the fact that the classifiers are designed and trained in advance, the distinguishing time of real-time models is short, online distinguishing of system state models can be achieved, the models reflect whether the operating aircrafts breaks down or not and the type and degree of the fault, and great significance is achieved for research such as system real-time state monitoring, fault-tolerant control system design and fault recovery.

Description

technical field [0001] The invention relates to an online identification method of a state model of a data-driven system, in particular to an online identification method of a state model of a data-driven system based on a multi-combination classifier. Background technique [0002] The literature "Research on Fault Modeling Method Based on Equivalent Replacement, Journal of Northwestern Polytechnical University, Volume 33, Issue 1, February 2015" discloses a fault modeling method based on equivalent model replacement, which can target component and system faults For the problem of modeling and fault simulation, on the premise of using expert experience and knowledge and avoiding the establishment of complex models, the effective simulation of faults can be realized, and the implementation steps of general fault equivalent model replacement can be formed, that is, based on the analysis of the working mechanism of the system, the establishment of The normal model is divided in...

AI Technical Summary

Problems solved by technology

[0003] In order to overcome the shortcomings of the existing data-driven system state model online identification method that is difficult to model, the present invention provides an online identification method for data-driven system state models based on multi-combination classifiers

It solves the technical problem that the physical model cannot be directly used to build a mathematical model due to the high complexity of the system, and the problem of inaccurate models caused by not considering the operating environment of the model when modeling according to the physical operating mechanism of the system improves the ability to establish a spacecraft in Feasibility and Accuracy of Rail Operation State Model

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