Blind system fault detection and isolation method for real-time signal processing of spacecraft
A fault detection and real-time signal technology, applied in neural learning methods, electrical testing/monitoring, biological neural network models, etc., can solve problems such as insufficient intelligence and cumbersome manual creation of knowledge bases
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[0041] like figure 1 As shown, the present invention is divided into offline and online stages. Offline stage: the first step is to determine the basic structure of the two ELMAN neural networks, fault detection and fault isolation, according to the number of diagnostic basis signals available for reference in the target system (including two types of control input and measurement output) and the number of faults that need to be detected and isolated The second step is to collect the sample data of the target system in normal and fault modes and set the training target, and use the improved update gradient strategy for offline training to obtain the structure and weight parameters of the two networks respectively, and then obtain the optimal fault detection neural network. Network and fault isolation neural network module; the third step is to design a corresponding fault logic judgment module after the output of the two neural network modules. Online stage: Embed the two net...
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