Simultaneous-Fault Diagnosis of Satellite Power System Based on Fuzzy Neighborhood zeta-Decision-Theoretic Rough Set

Due to the increasing complexity of the entire satellite system and the deteriorating orbital environment, multiple independent single faults may occur simultaneously in the satellite power system. However, two stumbling blocks hinder the effective diagnosis of simultaneous-fault, namely, the difficulty of obtaining the simultaneous-fault data and the extremely complicated mapping of the simultaneous-fault modes to the sensor data. To tackle the challenges, a fault diagnosis strategy based on a novel rough set model is proposed. Specifically, a novel rough set model named FN zeta DTRS by introducing a concise loss function matrix and fuzzy neighborhood relationship is proposed to accurately mine and characterize the relationship between fault and data. Furthermore, an attribute rule-based fault matching strategy is designed without using simultaneous-fault data as training samples. The numerical experiments demonstrate the effectiveness of the FN zeta DTRS model, and the diagnosis experiments performed on a satellite power system illustrate the superiority of the proposed approach.