The invention relates to the technical field of charging
pile monitoring management, and discloses a charging operation management platform based on
data analysis, and the platform comprises a data collection module which obtains and uploads the multi-
source data of a corresponding charging
pile in real time; the data preprocessing module is used for carrying out normalization
processing on the multi-
source data and filling missing values; the
feature extraction and analysis module is used for extracting and acquiring statistical features of the multi-
source data according to a
time sequence based on a sliding window
algorithm; the AI analysis module is used for outputting a
fault probability and a residual life prediction value according to statistical characteristics by adopting a multi-task
deep learning model optimized by transfer learning; the early warning analysis module is used for triggering graded early warning according to the
fault probability, and is linked with the digital twin platform to generate a
processing plan; and the
log management module is used for recording an alarm event, a
processing state and an equipment historical health degree curve, multi-dimensional data is subjected to
cross validation through a multi-task
deep learning model, potential faults of the charging
pile can be recognized in real time, active early warning can be performed, and the operation and maintenance efficiency and safety are improved.