基于热力镜像建模技术的电厂关键设备状态智慧识别

为了制定合理的电厂关键设备运维策略，解决电厂关键设备状态智慧识别的非线性难题，研究基于热力镜像建模技术的电厂关键设备状态智慧识别方法。采集电厂关键设备的日常运行数据作为样本数据，选取最小二乘支持向量机算法建立输入变量为中间点温度的热力镜像模型，最小二乘支持向量机通过获取模型样本、确定编码形式、采集数据、热力镜像建模以及模型验证建立热力镜像模型，利用热力镜像模型输出电厂关键设备状态智慧识别结果。实验结果表明，该方法可以智慧识别电厂关键设备状态，具有识别速度快、识别精度高的优势，并验证了该热力镜像建模技术可以为电厂关键设备的运维策略提供依据。

Intelligent recognition of power plant key equipment status based on thermal mirroring modeling technology

In order to formulate a reasonable operation and maintenance strategy for key equipment in power plants and solve the nonlinear problem of intelligent identification of key equipment states in power plants，the intelligent identification method of key equipment states in power plants based on thermal mirroring modeling technology was studied.Collect the daily operating data of key equipment of the power plant as sample data，select the least squares support vector machine algorithm to establish a thermal mirror model with the input variable as the intermediate point temperature.Through obtaining model samples，determines the encoding form，collects data，thermal mirroring modeling and model verification,the thermal mirroring model was established by using the least squares support vector machine.And the thermal mirroring model was used to output the intelligent recognition results of the key equipment status of the power plant.The experimental results showed that,the method can intelligently identify the state of key equipment in the power plant，and has the advantages of fast recognition speed and high recognition accuracy.It was verified that the thermal mirroring modeling technology can provide a basis for the operation and maintenance strategy of the key equipment of the power plant.