The application provides a
coal mine equipment fault detection method, medium and
system based on PHM, belongs to the technical field of
coal mine equipment fault detection, and comprises the following steps: collecting operation data based on PHM, including vibration, current and other indexes; next, the data is pretreated, denoised and features are extracted. Based on the pretreated data, a
mathematical model covering dynamics, electrical characteristics and
wear and tear is established, and an optimized model is obtained through parameter identification and optimization. The optimized model is discretized, a multi-dimensional
state space is constructed, and
normal state and fault state are defined. Based on the A*
algorithm, the shortest path from the
normal state to each fault state is searched, the difficulty of
fault occurrence is calculated, and a fault weight vector is obtained. Real-
time data is input into the optimized model, the distance from the current state to each fault endpoint is calculated, the fault weight is combined, and the
fault probability distribution and early warning information are output, thereby solving the technical problem that the prior art cannot meet the requirements of fault diagnosis accuracy, reliability and explainability.