摘要
燃气轮机广泛运用于电力、航空航天和城市热力供暖等领域,具有高效、清洁、灵活等特点。然而,燃气轮机存在结构复杂、启停频繁、工况多变等诸多影响因素,导致其健康程度劣化。因此,针对燃气轮机设备健康状况评估技术的研究愈发重要。随着传感器技术和新一代信息技术的进步,基于数据驱动的健康评估技术得到了长足发展。但目前的预测诊断模型存在复杂程度高、数据存储需求量大等问题,可能增加系统运行负担。因此,本文在深入分析相关理论的基础上,通过相关模型函数的运算、评估流程的搭建,开发了一种基于历史数据的燃气轮机健康状况实时评估系统,从而减轻智能预测诊断系统的运行压力,提升实时监测能力。最后,通过实例验证了所开发系统的可行性和稳定性,为燃气轮机设备健康评估技术提供新的发展思路。
Gas turbines are widely used in electric power,aerospace,urban heating and other fields,with the characteristics of high efficiency,clean,flexible and so on.However,the health degree of gas turbine equipment will deteriorate because of many influencing factors such as complex structure,frequent start and stop,and variable working conditions.Therefore,the research on the health assessment technology of gas turbine equipment has become increasingly important.With the progress of sensor technology and the new generation of information technology,the data-driven health assessment technology has been greatly developed.However,the current predictive diagnosis model has some problems,such as high complexity and large data storage demand,which increase the burden of system operation.Therefore,on the basis of in-depth analysis of relevant theories,this paper developed a real-time evaluation system of gas turbine health status based on historical data through the operation of relevant model functions and the establishment of evaluation processes,so as to reduce the operating pressure of the intelligent prediction and diagnosis system and improve the real-time monitoring capability.Finally,the stability and feasibility of the developed system are verified by an example,which provides a new development idea for gas turbine equipment health assessment technology.
作者
李红仁
张坤
王鑫
呼树尧
马吉伟
LI Hongren;ZHANG Kun;WANG Xin;HU Shuyao;MA Jiwei(HuaDian Electric Power Research Institute Company Limited,Hangzhou 310030,Zhejiang,China;North China Electric Power University,Beijing 102206,China)
出处
《电力大数据》
2024年第4期63-71,共9页
Power Systems and Big Data
关键词
燃气轮机
健康评估
聚类
S型隶属函数
数据评分
gas turbine
health assessment
clustering
S-shaped membership function
data scoring
作者简介
李红仁(1989),男,硕士,高级工程师,主要从事燃气发电机组智能运维技术研究等相关工作。
