基于广播电视多平台监控数据的故障分析和预测模型  

Fault Analysis and Prediction System Based on Multiple Monitoring Platform Data of Radio and Television

作　　者：郑晓夏 郑凯辉 Zheng Xiaoxia;Zheng Kaihui(Ningbo Radio and Television Transmitting Center,Zhejiang 315000,China)

机构地区：[1]宁波广播电视发射中心,浙江315000

出　　处：《广播与电视技术》2024年第11期96-99,共4页Radio & TV Broadcast Engineering

摘　　要：本文以Python数据分析库Pandas为基础,对发射机、电力、空收信号等多个监控平台数据进行清洗和分析,提出了一种基于多平台数据的故障分析和预测模型。通过单一维度和组合维度的故障分布和趋势数据分析,构建了一套有效的情境预测模型。该模型能够预测当前环境下故障发生的概率,为提高台站运维提供了可靠的决策支持。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 

分 类 号：TN94[电子电信—信号与信息处理]