Defect correlation analysis of full-level collaborative power communication network based on FP-Growth algorithm

To guarantee the stable functioning of extensive comprehensive collaborative power communication network equipment linked to the power grid, this paper suggests a defect correlation analysis approach for comprehensive collaborative power communication network equipment, enhanced by the FP-Growth algorithm. Firstly, the fundamental framework and underlying principles of the comprehensive collaborative power communication network equipment are examined, and the malfunction data of the comprehensive collaborative power communication network equipment are gathered. Then, the original data is preprocessed, quantized and encoded into FP-Growth algorithm, and its support and confidence are calculated by constructing FP-Tree. Finally, the effectiveness of the method is verified by the simulation example of the actual full-level collaborative power communication network equipment defect data. This method can analyze and trace the information related to the core equipment defects of the fullness collaborative power communication network in an efficient and intelligent way, thus offering theoretical backing for operational and maintenance staff to devise maintenance strategies.