大数据技术在高压加氢换热器运行状态评估中的应用

高压加氢换热器是炼油厂的重要装置，但高压加氢换热器面临着铵盐腐蚀导致泄露的问题，因此对加氢换热器的运行状态评估十分重要。针对使用传统方法进行加氢换热器运行状态评估的不足的问题，本文提出了一种基于大数据的高压加氢换热器运行状态评估的方法。对于工业界常见的噪声数据，本文提出了自动化的噪声区间检测算法。对于传感器参数维度高、存在不相关维度的问题，本文提出了基于皮尔森系数的关健参数检测算法。最后，本文提出了一种基于主成份的系统健康打分算法，辅助现场施工员评估高压加氢换热器健康状况。基于大数据技术的高压加氢换热装置的运行状态评估，有助于帮助施工人员更准确掌握工业系统状况，对于故障的预警有积极指导意义。

Application of Big Data Technology in Evaluation of Operating State of High-pressure Hydrogenation Heat Exchanger

The high-pressure hydrogenation heat exchanger is an important device of the refinery, but the high-pressure hydrogenation heat exchanger is exposed to the problem of leakage caused by ammonium salt corrosion. Therefore, it is very important to evaluate the operating status of the hydrogenation heat exchanger. To improve the method of using the traditional method to evaluate the operating status of hydrogenation heat exchangers, this paper proposes a method for evaluating the operating status of hydrogenation heat exchangers based on big data. For noisy data common in the industry, this paper proposes an automated noisy interval detection algorithm. For the problem that the sensor parameters have high dimensions and there are unrelated dimensions, this paper proposes a key parameter detection algorithm based on Pearson correlation coefficient. Finally, this paper presents a system-based health scoring algorithm based on PCA (Principal Component Analysis) to assist site operators in assessing the health of hydrogenation heat exchangers. The evaluation of the operating status of the hydrorefining heat exchange device based on big data technology will help the technicist to more accurately grasp the status of the industrial system and have positive guiding significance for the early warning of the failure.