Research and application of fault diagnostics method for new energy power plant equipment based on big data mining

Abstract

In view of the diversity, complexity and magnanimity of information data in the operation status of new energy power plant, the data mining technology is applied to fault diagnostics. On this basis, the overall process of fault diagnostics methods including clustering analysis, fault rule mining, fault modeling and other mathematical statistical theories is designed. The logical relationship between massive data is redefined at a deeper level. And the most effective fault characterization is extracted. The correctness and validity of the method are proved by comparing the curve of the fault characteristic parameter prediction results with the field measurement results. This method has high data processing efficiency, effectively improves the reliability and accuracy of fault diagnostics and early warning. And it provides a strong guarantee for the safe operation of the new energy grid-connected.