automatic assembly line fault diagnosis method and system based on deep learning discovery and measurement

The invention relates to the technical field of assembly line fault diagnosis, and discloses an automatic assembly line fault diagnosis method based on deep learning discovery and measurement, which comprises the following steps of: performing data acquisition, which is used for acquiring feedback data of intelligent equipment and a sensor group, log data of system operation and external data; performing data standardization: standardizing the data in the above steps, and sending the processed data to a Hive data warehouse through a kafka stream processing platform; Based on a Spark MLlib platform, carrying out feature extraction, fuzzy logic and label classification on the data in the above steps, and carrying out machine learning to obtain a fault diagnosis model; and carrying out real-time diagnosis on the automatic assembly line by using the fault diagnosis model in the above steps, and carrying out early warning on faults. According to the automatic assembly line fault diagnosis method based on deep lear