As various faults are inevitable during a satellite’s on-orbit operation, a modified intermittent process performance monitoring method is proposed. This performance monitoring of a satellite is performed via attitude information. This method not only overcomes the defects of the traditional intermittent process methods of requiring a priori knowledge and the difficulty in handling points on adjacent edges but also reduces the defects, such as omissions and false positives caused by the process modeling. This method combines the multiphase auto regression principal component analysis monitoring method based on affine propagation clustering (APC) optimized, and at the meanwhile, the population diversity-based particle swarm optimization algorithm is considered in APC. Numerical simulations proved the effectiveness of the proposed approach.
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