Multi-method combination avionics system fault diagnosis method

Abstract

The invention discloses an avionics system fault diagnosis method based on combination of three methods which are FTA (fault tree analysis), a BAM (bidirectional associative memory) neural network and a BP (back-propagation) neural network. According to the invention, a fault diagnosis model integrating FTA and the BAM neural network and a fault diagnosis model combining the BP neural network are established respectively. When a fault phenomenon is obvious, the fault diagnosis model integrating FTA and the BAM neural network is adopted. Firstly, a fault mode of the system is acquired by using FTA, a training sample of BAM is analyzed and summarized, and finally, BAM carries out parallel association through an associative memory matrix so as to acquire a diagnosis result. When a fault phenomenon is not obvious or a fault example base does not have such a fault, the fault diagnosis model combining the BP neural network is adopted. Learning is carried out on a training sample, that is, data such as voltage, temperature and the like, acquired by the BP neural network, and fault diagnosis is carried out by using the trained network in the end. The two fault diagnosis models have complementary advantages, and make up deficiencies of each other, thereby effectively solving problems existing in avionics system fault diagnosis, and improving the accuracy and the efficiency of fault diagnosis.

Description

technical field [0001] The invention relates to the field of fault diagnosis methods for avionics systems, in particular to a fault diagnosis method for avionics systems based on the combination of three methods: FTA, BAM and BP. Background technique [0002] As aircraft equipment becomes more and more intelligent and informatized, more and more tasks need to be handled with the assistance of electronic systems, which will also lead to an increasing number of failures caused by electronic systems. In addition, as the electronic system continues to integrate into the core mission system of the weapon system, the more informatized and intelligent weapons and equipment will require the assistance of the electronic system to complete more tasks, and the failure of the electronic system will also greatly increase its maintenance support problems. At present, for the fault diagnosis of avionics systems in China, the frequent faults of avionics equipment are checked and repaired ba...

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Problems solved by technology

[0004] Aiming at the problems of difficult fault location, low accuracy and efficiency in fault diagnosis of avionics systems and the limitations of a single fault diagnosis method, the present invention provides a multi-method combined fault diagnosis method for avionics systems, using FTA (Fault Tree Analysis, fault tree analysis), BAM neural network (Bidirectional Associative Memory, two-way associative memory), BP neural network (Back-Propagation, reverse propagation) three methods combined

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