A Fault Detection and Diagnosis Method for Aircraft Actuators Based on Deep Random Forest Algorithm

Abstract

The invention discloses an aircraft actuator fault detection and diagnosis method based on a depth random forest algorithm. The method includes: firstly, summarizing the fault mode of an aircraft actuator; establishing an RBF neural network, and collecting the input and output data of the aircraft actuator under the normal working condition to serve as training data, and training the parameters inthe neural network model to obtain analysis redundancy of the monitored actuator; analyzing the residual data of the output signals by collecting the output of the actual actuator and the neural network model, and after the feature extraction, inputting the feature data set into a trained depth random forest multi-classifier for fault mode recognition. According to the invention, the complex nonlinear input and output relation of the aircraft actuator can be accurately simulated by the neural network, the fault mode is accurately recognized by a depth random forest strong classifier, and moreover, the method has the advantages of parallel calculation and high running speed, can be integrated into a flight management computer of an aircraft, realizes the online real-time monitoring, and the accuracy and the efficiency of fault diagnosis of the aircraft actuator are improved.

Description

technical field [0001] The invention relates to a fault diagnosis method for an aircraft actuator, in particular to a fault detection and diagnosis method for an aircraft actuator based on a deep random forest algorithm. Background technique [0002] Aircraft, as the most important means of delivery in today's society, plays an important role in both civil and national defense fields. With the development of science and technology and the growth of social needs, the structure and functions of aircraft systems are becoming more and more complex. Higher and higher requirements are placed on the reliability of aircraft. Moreover, due to the special operating environment of the aircraft, the safety of the aircraft flight is very important. Once a certain system of the aircraft fails, it may lead to serious safety accidents. Therefore, real-time fault detection and diagnosis for each system of the aircraft is a necessary measure to ensure the safe flight of the aircraft. For ex...

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Problems solved by technology

Therefore, once the actuator fails, it may cause a major safety accident. With the improvement of aircraft maneuverability, the aircraft actuator needs to be under various complex aerodynamic loads, which increases the probability of its failure.

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