基于边缘智能的复杂动态燃煤发电厂设备故障检测方法  

Edge Intelligence-Based Fault Detection Method for Complex Dynamic Coal-Fired Power Plant Equipment

作　　者：刘兰徽 Liu Lanhui(Chongqing Industrial Big Data Innovation Center Co.,Ltd.,Chongqing 400700,China)

机构地区：[1]重庆工业大数据创新中心有限公司,重庆400700

出　　处：《现代工业经济和信息化》2024年第11期109-112,共4页Modern Industrial Economy and Informationization

基　　金：国家重点研发计划资助(2022YFE0125400)。

摘　　要：边缘智能作为一种将数据处理和分析近似于数据源的技术,能有效减少延迟、优化带宽使用,并提高数据处理的安全性。边缘智能通过实时处理和分析传感器数据,可为设备故障预警提供技术支持。阐述了边缘智能在燃煤发电厂中的应用,详细分析了各种设备故障类型,展示了基于边缘智能的故障检测方法,包括数据采集、预处理、特征提取与故障检测。应用验证了所提方法的有效性和实用性。Edge intelligence,as a technology that approximates data processing and analysis to the data source,can effectively reduce latency,optimize bandwidth usage,and improve the security of data processing.Edge intelligence can provide technical support for equipment failure warning by processing and analyzing sensor data in real time.The application of edge intelligence in coal-fired power plants is described,various equipment fault types are analyzed in detail,and a fault detection method based on edge intelligence is demonstrated,including data acquisition,preprocessing,feature extraction and fault detection.The application verifies the effectiveness and practicality of the proposed method.

关 键 词：边缘智能 复杂动态燃煤 发电厂设备故障检测 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] X799.3[自动化与计算机技术—控制科学与工程] TM621[环境科学与工程—环境工程]