| CPC G05B 23/0275 (2013.01) [G05B 23/027 (2013.01); G06F 16/683 (2019.01)] | 18 Claims |

|
1. An audio-based device fault detection method, comprising:
obtaining initial audio data collected by a drone for a target device, wherein the target device is a reactor required for a spinning process, and the initial audio data for the reactor is collected by: controlling the drone to execute an operation plan to obtain the initial audio data, the operation plan comprising inspection time, location information of the reactor, and a requirement for the collected initial audio data;
preprocessing the initial audio data to obtain audio data to be detected;
performing feature extraction on the audio data to be detected to obtain an audio feature of the audio data to be detected;
constructing an information graph based on the audio feature;
obtaining a fault detection result for the target device based on the information graph and a graph neural network model;
obtaining, based on collection time of the initial audio data, an operating parameter of the reactor in a preset time range with the collection time as a benchmark, in a case of the fault detection result indicates that the reactor has a fault, wherein the operating parameter comprises at least one of: voltage, current, rotation speed or viscosity;
determining a fault condition of the reactor based on the operating parameter; and
issuing emergency alarm information after determining that the reactor is abnormal based on the operating parameter.
|