The high-pressure hydrogenation heat exchanger is an important equipment of the refinery, but it 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 for evaluating the operating status of hydrogenation heat exchangers by using the traditional method, this paper proposes a new method for evaluating the operation of hydrogenation heat exchangers based on big data. To address the noisy data common in the industry, this paper proposes an automated noisy interval detection algorithm. To deal with the problem that the sensor parameters have voluminous and unrelated dimensions, this paper proposes a key parameter detection algorithm based on the 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 operators to more accurately grasp the status of the industrial system and have positive guiding significance for the early warning of the failure.
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