Carrier roller fault diagnosis method and system based on big data technology and storage medium

The invention discloses a carrier roller fault diagnosis method and system based on a big data technology and a storage medium. The carrier roller fault diagnosis method based on the big data technology comprises the following steps of S1, collecting audio data of a carrier roller; S2, extracting features of the audio data; wherein the features of the audio data specifically comprise one or any combination of sharpness, noise annoyance and speech interference level; S3, inputting the features of the audio data into a trained logistic regression model, which identifies the running state of the carrier roller; S4, executing warning, monitoring or control operation if the carrier roller runs abnormally, and executing the step S5 if the carrier roller runs normally to complete carrier roller fault diagnosis at the current moment; and S5, updating the moment, repeatedly executing the steps S1 to S4, and conducting carrier roller fault diagnosis at the next moment. According to the method, real-time diagnosis of a