This article uses Pandas as the foundation to clean and analyze data from multiple monitoring platforms,including transmitters,power,and air-receive signals.It proposes a fault analysis and prediction model based on multi-platform data.Through the analysis of fault distribution and trend data in single and combined dimensions,an effective situational prediction model is constructed.This model can predict the probability of fault occurrence in the current environment,providing reliable decision support for improving station operation and maintenance.
关键词
Pandas/数据清洗/故障分析/预测模型/运维效率
Key words
Pandas/Data cleaning/Fault analysis/Predictive model/Operation and maintenance efficiency
维普
万方数据