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Minor-Fault Diagnosis Based on Reduced-Dimensional Zonotopic Filtering and Its Application to Inductor Current Analysis of Converter
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王
DOI：10.1109/tie.2026.3679714.png)
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Abstract
En 中文
This work proposes a novel method for minor-fault diagnosis based on reduced-dimensional zonotopic filtering (RDZF). First, the zonotope space that contains the fault-state prediction is constructed using zero missed alarm rate (MAR) of fault diagnosis as the design index of the minor-fault amplifier to achieve optimal amplification. Subsequently, the zonotope order is reduced without increasing the conservative properties of the algorithm. The Euclidean distance is used to achieve the lowest dimension of the zonotope, and the upper and lower bounds of the fault state are obtained from the box space. Then, the estimation interval of the minimal fault is solved in reverse. Finally, an experimental platform based on the buck–boost circuit is constructed to verify the effectiveness and practicability of the proposed algorithm in a practical scenario.
Keywords:
Filter design
minor-fault diagnosis
signal amplification
zonotope
Journal
IF:
7.2
Papers:
1.8W
Citations:
9.8W
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Cited Papers