基于工业大数据的加氢装置高压换热器腐蚀预警系统开发
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摘要
针对加氢装置高压换热器因受原料影响而产生的铵盐垢下腐蚀、流动腐蚀等问题,利用大数据技术,基于企业的工业数据,构建了加氢装置高压换热器腐蚀预测模型,并开发了高压换热器腐蚀预警系统。该系统在某石化公司2~#柴油加氢装置实现了上线运行,并成功实现该高压换热器腐蚀的预警,提高了企业的生产运行能力,为企业平稳生产提供了保障。
Aimed at the problems of under-deposit corrosion and flow corrosion of the ammonium salt in the high pressure heat exchanger by effect of the crude material, the corrosion prediction model and warning system for the high pressure heat exchanger were built and developed basing on the industrial data of the enterprise and adopting big data technology. On-line operation of the warning system was realized on No.2 diesel oil hydrogenation unit in some petrochemical company, and the corrosion warning of the hydrogenation high pressure heat exchanger was realized successfully. Production running capacity of the enterprise was raised, safe and stable production of the enterprise was ensured.
Aimed at the problems of under-deposit corrosion and flow corrosion of the ammonium salt in the high pressure heat exchanger by effect of the crude material, the corrosion prediction model and warning system for the high pressure heat exchanger were built and developed basing on the industrial data of the enterprise and adopting big data technology. On-line operation of the warning system was realized on No.2 diesel oil hydrogenation unit in some petrochemical company, and the corrosion warning of the hydrogenation high pressure heat exchanger was realized successfully. Production running capacity of the enterprise was raised, safe and stable production of the enterprise was ensured.
引文
[1] 梁佳,刘金才.高压加氢裂化装置高压热交换器腐蚀分析及防护[J].石油化工设备, 2018(3):62-69.
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[2] 周晓康, 宋贤钧, 周立民. 石化设备实时故障分析和运行预警体系的构建[J]. 化工机械, 2011, 38(2):210-213.
[3] 郭丽杰, 赵明娟, 康建新. 基于PCA和RBF神经网络的石化装置故障监测与诊断[J]. 燕山大学学报, 2016, 40(5):456-461.
[4] 薛永飞. 基于改进T-PLS的化工过程故障诊断研究[D]. 甘肃兰州:兰州理工大学, 2014.
[5] Yuan M, Wu Y, Lin L. Fault diagnosis and remaining useful life estimation of aero engine using LSTM neural network[C]// International Conference on Aircraft Utility Systems. IEEE, 2016:135-140.
[6] Mao X, Wang L, Li C. SVM classifier for analog fault diagnosis using fractal features[C]//International Symposium on Intelligent Information Technology Application. IEEE, 2009:553-557.