Risk mining and location analysis of coal mine equipment control failures based on the Apriori Algorithm

The underground operation environment of coal mines is complex, with diverse equipment and existing problems in personnel management, resulting in a high failure rate of equipment control, which restricts safe production and operation. This research focuses on the precise positioning of the failure links of coal mine equipment control, striving to identify the key risk factors leading to equipment control failures. This paper firstly analyzes each system underground in a certain coal mine, the corresponding equipment, and the corresponding scenarios. Then, 7 385 groups of equipment control failure data from Shendong Coal Mine from 2021 to 2024 are collected. After preprocessing such as data cleaning, the Apriori algorithm is used to mine association rules, and thresholds for support, confidence, and lift are set to screen out strong association rules. The research finds that the combined scenario of “Detailed Location_Fan Power Distribution Point” and “Equipment Name_Production Transformer” has a high risk. When some factors are superimposed, the failure probability is extremely high, indicating that there may be potential hazards in specific operation processes or authority settings. It is recommended to optimize the hardware linkage logic, standardize the operation process, and strengthen personnel training and supervision.