Capacity Detection Method of Uninterrupted Special Transformer Based on Big Data and Pattern Recognition

In order to ensure the normal operation of uninterruptible special transformers and reduce the heavy losses caused by faults, a capacity detection method of uninterruptible special transformers based on big data and pattern recognition is proposed. Under the big data and pattern recognition, the optimal membership degree of capacity detection of uninterruptible special transformer is obtained, and the characteristic parameters of transformer operation state are extracted according to the results. Thus the load model of uninterruptible special transformer is constructed, and the capacity detection of uninterruptible special transformer is realized. The experimental results show that the proposed method can directly reflect the internal operation of the special transformer and detect the capacity problem of the special transformer without power outage.