Power battery voltage time sequence anomaly detection method, electronic equipment and storage medium

The invention relates to a power battery voltage time sequence anomaly detection method, electronic equipment and a storage medium. A formation process and a capacity grading process are necessary processes in a power battery production rear section, and safety accidents of battery swelling, battery cell temperature suddenly rising, fire and explosion can be possibly caused if abnormity is not found in time in the production process; the research on the discovery of the battery causing the accident is basically caused by the violent change of the battery voltage or the probe voltage in the charging and discharging process. According to the invention, a time sequence anomaly detection algorithm based on deep learning is combined with the charging and discharging voltage data of the power battery to train the model, real-time anomaly detection is carried out on the charging and discharging process of battery production after the model is available, abnormal voltage data is found in time and an alarm is given, t