SUN Jianping, ZHAO Lihui, SUN Boyang, et al. Early warning of steam-driven induced draft fan based on data-driven and MSET[J]. Thermal power generation, 2020, 49(1): 78-84.
SUN Jianping, ZHAO Lihui, SUN Boyang, et al. Early warning of steam-driven induced draft fan based on data-driven and MSET[J]. Thermal power generation, 2020, 49(1): 78-84. DOI: 10.19666/j.rlfd.201907187.
基于数据驱动与多变量状态估计的汽动引风机故障预警
摘要
汽动引风机是新建电厂的重要设备之一
对其采用数据驱动的故障预警时
存在监测参数多、设备故障试验代价高、运行数据少的问题。为此
本文采用多变量状态估计(MSET)方法对汽动引风机相关测点进行状态监测
构造合理的记忆矩阵
使用奇异值分解法计算广义逆矩阵
从而提高计算效率;并以江苏某电厂为研究对象
提取现场包含喘振故障的数据
采用本文方案对实时数据进行状态预警。结果表明
该方案能够合理反映设备的运行状态
对喘振故障能够提前约5 h预警。
Abstract
Steam-driven induced draft fan is one of the important equipments for newly built power plants. There are many problems when applying data-driven fault warning scheme to the fans
such as various monitoring parameters
high cost of equipment failure test and few fault operation data. To solve these problems
this paper applies the multivariate state estimation technique(MSET) to monitor the status of the relevant points of the power plant fans. It analyzes a reasonable memory matrix scheme from the perspective of mathematical principle
and uses the singular value decomposition method to calculate the generalized inverse matrix
thus to improve the calculation efficiency. Taking a power plant in Jiangsu as the research object
the data of the surge fault is extracted from the site
and the scheme is applied to perform state alarm real time data warning. The results show that
the above scheme can reasonably reflect the operating state of the equipment
and the surge fault can be warned about 5 hours in advance.