Fault decision-making method for effective load

Abstract

The invention discloses a fault decision-making method for a payload, and relates to the field of spacecrafts. The method comprises the steps that operation parameters of a payload are acquired; Establishing a decision-making model, and training the decision-making model according to the operation parameters and the Markov model, the decision-making model being a deep enhanced network model; And making a decision on the fault of the effective load according to the trained decision model. The invention provides a fault decision-making method, the depth enhancement network model is trained through the operation parameters and the Markov model; and fault diagnosis, Inference and decision are combined, According to the method, the complete cycle process from fault discovery to fault decision making of the spacecraft effective load is achieved, the problem that under the influence of multiple factors, the complex jump parameter relevance and the false detection rate are high is solved, probability fuzzy diagnosis and dynamic updating of the context logic relation are achieved, and the accuracy and timeliness of fault diagnosis and decision making are improved.

Description

technical field [0001] The invention relates to the field of spacecraft, in particular to a payload failure decision method. Background technique [0002] At present, the spacecraft payload fault diagnosis methods are mainly divided into: fault diagnosis method based on expert system, diagnosis method based on support vector machine, diagnosis method based on artificial neural network, diagnosis method based on fault tree analysis, etc. [0003] Spacecraft is a device that effectively explores, develops, and rationally utilizes space resources. Real-time and efficient fault diagnosis and decision-making technology are of great significance to the reliable and stable operation of spacecraft. However, due to the complexity of the system, the particularity of the operating environment, and uncertainties, the traditional fault diagnosis method only diagnoses the cause and lacks decision-making assistance, and has a high false detection rate for complex jump parameters under the ...

AI Technical Summary

Problems solved by technology

However, due to the complexity of the system, the particularity of the operating environment, and uncertainties, the traditional fault diagnosis method only diagnoses the cause and lacks decision-making assistance, and has a high false detection rate for complex jump parameters under the influence of multiple factors. , unable to meet the requirements of intelligence, accuracy and timeliness

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