Capacity Detection Algorithm of Uninterrupted Special Transformer Based on Artificial Immunity and Multi-Object Optimization

Aiming at the problem that the capacity detection error of an uninterruptible special transformer is large, which affects the operation effect of the transformer, a capacity detection algorithm for an uninterruptible special transformer based on artificial immunity and multi-object optimization is proposed. The algorithm combines an artificial immune algorithm and a multi-object optimization algorithm to decompose the vibration signal of the uninterruptible special transformer. According to the decomposition results, the winding deformation detection model of the uninterruptible special transformer is constructed, and the possible problems in the operation of the transformer can be found in time, so that corresponding measures can be taken for maintenance and repair, thus realizing the research on the capacity detection algorithm of the uninterruptible special transformer. The experimental results show that the Euclidean distance value of this algorithm is higher, which shows that its detection results can better express the capacity state of the actual uninterrupted special transformer equipment.