摘要
应急柴油机(EDG)是保证核电厂安全可靠运行的一级安全设备,其应急启动成功率是衡量核电站安全等级的关键指标之一,因此对EDG启动过程进行有效监测评估具有重要价值。本文利用在线监测系统采集EDG启动过程数据,考虑瞬变启动数据的不确定性,提出了一种基于云重心模型的EDG启动状态评估方法。首先,充分结合EDG快速启动特点,选择能够反映EDG启动阶段缸内发火做功和高压空气做功状态的7个特征参数作为评估指标,为准确计算特征指标,提出了适用于快速启动过程的瞬时转速优化计算方法和振动信号角域精确重采样方法。然后,利用云模型在解决随机性和不确定性问题方面的优势,构建综合云评估模型,将云重心评判法引入到EDG启动状态评估中。最后,以实际核电现场多次测试数据为分析案例,利用本文提出的特征提取方法和综合云评估模型对测量状态进行评估,验证了所提方法的有效性,为EDG启动状态评估提供了有效途径。
The emergency diesel engine(EDG)is the first level safety equipment for ensuring the safe and reliable operation of the nuclear power plant.The success rate of the emergency start-up is one of the key indicators to measure the safety level of the nuclear power plant.Therefore,it is of great value to effectively monitor and evaluate the start-up process of EDG.In this paper,the on-line monitoring system is used to collect the data of the EDG startup process.Considering the uncertainty of transient start-up data,an EDG start-up state evaluation method based on the cloud gravity center model is proposed.Firstly,according to the characteristics of the rapid start-up of EDG,seven characteristic parameters that can reflect the working state of firing and high-pressure air in the start-up stage are selected as evaluation indexes.To accurately calculate the characteristic indexes,an instantaneous speed optimization calculation method and an accurate angle domain resampling method of vibration signal are proposed.Then,taking the advantages of the cloud model in solving the problems with randomness and uncertainty,a comprehensive cloud evaluation model is constructed,and the cloud barycenter evaluation method is introduced into the EDG start-up state evaluation.Finally,the proposed method is verified by using the actual nuclear power field test cases,indcating that it is an effective method for EDG start-up state evaluation.
作者
管玉峰
秦贯洲
周正平
魏琨竺
茆志伟
Guan Yufeng;Qin Guanzhou;Zhou Zhengping;Wei Kunzhu;Mao Zhiwei(Jiangsu Nuclear Power Corporation,Lianyungang 222042;Xi’an Institute of Modern Control Technology,Xi’an 710065;Key Laboratory of Ministry of Education on Engine Health Monitoring-Control and Networking,Beijing University of Chemical Technology,Beijing 100029)
出处
《高技术通讯》
CAS
2021年第5期549-558,共10页
Chinese High Technology Letters
基金
双一流建设专项经费(ZD1601)
压缩机技术国家重点实验室开放基金(SKL-YSJ201811)资助项目。
