基于物联网的瓦斯发电厂设备状态监测与预测维护
Monitoring and Predictive Maintenance of Gas Power Plant Equipment Status Based on the Internet of Things
范晓雷1
作者信息
- 1. 沁水寺河瓦斯发电有限公司,山西晋城 048200
- 折叠
摘要
设计了一种基于物联网的瓦斯发电厂设备状态监测与预测维护系统.该系统通过在关键设备上部署物联网传感器,实时采集设备运行参数,结合大数据分析和机器学习算法,实现设备状态评估、故障预测与智能维护决策.主要创新点包括面向电厂的混合组网架构,以及建立自适应的故障预测模型以支持决策优化.该系统推动了瓦斯发电厂设备状态感知能力的提升,使运维决策更加智能化.
Abstract
This paper designs a gas power plant equipment status monitoring and predictive maintenance system based on the Internet of Things(IoT).The system deploys IoT sensors on key equipment to collect real-time operating parameters,and combines big data analysis and machine learning algorithms to achieve equipment status evaluation,fault prediction,and intelligent maintenance decision-making.The main innovations include a hybrid networking architecture for power plants and the establishment of an adaptive fault prediction model to support decision optimization.This system has promoted the improvement of equipment status perception ability in gas power plants,making operation and maintenance decisions more intelligent.
关键词
物联网/瓦斯发电厂/智能维护Key words
IoT/gas power plant/intelligent maintenance引用本文复制引用
出版年
2024
NETL
NSTL
万方数据