摘要
提出一种基于改进PCA-SARMA的电厂除尘设备故障预警方法,首先对所有与除尘设备运行状态相关的特征参数采用改进主元分析法进行降维处理,然后在新主元特征参数的基础上采用SARMA算法对燃煤电厂除尘设备进行建模分析,最后对内蒙古某电厂600 MW燃煤机组LCM-D/G型袋式除尘设备进行实例验证。结果表明,该方法可以提前发现燃煤电厂除尘设备故障征兆,实现对燃煤电厂除尘设备的早期故障预警。
In this paper,a fault warning method for dust removal equipment in power plants based on improved PCA⁃SARMA is proposed.Firstly,the improved principal component analysis method is used to dimensionally reduce all characteristic parameters related to the operating state of the dust removal equipment.Then,on the basis of the new principal component characteristic parameters,SARMA algorithm is used to model and analyze the dust removal equipment of coal⁃fired power plant.Finally,an example of LCM⁃D/G bag dust removal equipment of a 600 MW coal⁃fired unit in a power plant in Inner Mongolia is verified.The results show that the method can detect the signs of dust removal equipment failures in coal⁃fired power plants in advance,and achieve early fault warning of dust removal equipment in coal⁃fired power plants.
作者
朱明皓
ZHU Minghao(Guoneng Inner Mongolia Hulunbuir Power Generation Co.,Ltd.,Hulunbuir 021025,China)
出处
《内蒙古电力技术》
2023年第3期86-90,共5页
Inner Mongolia Electric Power
基金
国家能源投资集团有限责任公司科技项目“辅助监盘系统研究与应用”(GNHB-22-1)。
关键词
改进主元分析
SARMA算法
燃煤电厂
除尘设备
故障预警
improved principal component analysis
SARMA algorithm
coal⁃fired power plant
dust removal equipment
fault warning
