Journal of Electronic Systems Run Ma 14 4 2024 https://doi.org/10.6025/jes/2024/14/4/124-131 https://www.dline.info/jes/fulltext/v14n4/jesv14n4_2.pdf detection based on multi-information integration. By integrating and analyzing information from multiple sources of electrical equipment, the accuracy and efficiency of equipment fault detection and diagnosis can be effectively improved. In detecting and diagnosing electrical equipment information, multiple sources of information are usually involved, including equipment operation data, sensor data, historical maintenance records, etc. This information has different forms and characteristics, so it needs to be integrated and comprehensively analyzed to fully explore the useful information within it. This article proposes a method for detecting, diagnosing and analyzing information on electrical equipment based on multi-information integration. This method first preprocesses and integrates information from different sources, then utilises machine learning and data mining techniques to analyze and mine the information. Among them, special attention is paid to the complementarity of information and fusion methods to extract valuable features and patterns from different information fully.