Abstract: Mine hoists are the core transportation equipment in coal mines. Under large-scale coal mining and complex working conditions, traditional monitoring methods can no longer meet the needs of timely fault detection and diagnosis. In order to solve the fault diagnosis problem during the operation of the hoist, this paper proposes a fault diagnosis system based on multi-sensor signal acquisition and feature analysis. In this paper, by summarizing the common fault types of the hoist, a scheme of installing sensors on the main equipment is proposed to realize data acquisition; the typical fault signals of the hoist are analyzed through experiments, the operating status of the bearings at different times is evaluated, and the early fault type is predicted by frequency doubling analysis; the experimental results verify the application value of the proposed fault diagnosis scheme in the evaluation of the hoist operation status and fault warning, and provide technical support for real-time monitoring, fault prediction and preventive maintenance of equipment.