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The traditional spacecraft fault detection system has poor attitude positioning ability, which makes it impossible to break through the threshold and accurately realize the detection, and the traditional system does not have the ability to reconstruct. In order to solve the above problems, based on the self-diagnosis and reconstruction technology, a new method of fault detection is proposed, which integrates hardware devices such as fault detectors, data collectors, filters and so on. Constructing wavelet neural network, combining the advantages of spacecraft fault detection principle and reconstruction problem set neural network algorithm and wavelet function, constructing wavelet neural network, introducing fault detection algorithm to realize autonomous diagnosis and reconstruction of spacecraft fault detection system. The experimental results show that the designed spacecraft fault detection system based on the self-diagnostic reconstruction technology can detect from the three axes of X, Y, and Z to determine the spacecraft faults in different azimuths. After setting the threshold, the proposed the detection system can analyze the threshold well, realize the breakthrough of the residual error, and has the ability of route reconstruction.