大数据分析在预测石化设备失效与预防性维修中的应用研究
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高用莲
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天津保泰安全技术服务有限公司，天津，300000
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摘要：石油化工行业设备工况复杂、运行环境恶劣，设备失效易引发安全事故与巨额经济损失。传统维修模式难以满足现代石化产业高质量发展需求，而大数据分析技术为设备失效预测与预防性维修提供了全新解决方案。本文首先阐述石化设备失效特征与传统维修模式局限性，进而构建大数据驱动的设备失效预测与预防性维修体系，包括数据采集、预处理、特征提取、预测模型构建等核心环节。结合实际案例验证该体系应用效果，最后分析当前技术应用面临的挑战并展望未来发展方向。研究表明，大数据分析技术可有效提升石化设备失效预测准确率，优化预防性维修策略，降低维修成本与停机损失，为石化行业安全生产提供技术支撑。
关健词：大数据分析；石化设备；失效预测；预防性维修；机器学习
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Application Research of Big Data Analysis in Predicting Petrochemical Equipment Failure and Preventive Maintenance
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Yonglian Gao
Tianjin Baota Security Technology Service Co., Ltd. Tianjin, 30000 , China
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Abstract：The petrochemical industry is characterized by complex equipment operating conditions and harsh operating envi-ronments, where equipment failure is prone to cause safety accidents and huge economic losses. Traditional maintenance models can hardly meet the high-quality development needs of the modern petrochemical industry, while big data analysis technology provides a new solution for equipment failure prediction and preventive maintenance. This paper first elaborates on the failure characteristics of petrochemical equipment and the limitations of traditional maintenance models, then constructs a big data-driv-en equipment failure prediction and preventive maintenance system, including core links such as data collection, preprocessing, feature extraction, and prediction model construction. Combined with practical cases, the application effect of the system is verified, and finally the challenges faced by the current technical application and the future development direction are analyzed. The research shows that big data analysis technology can effectively improve the accuracy of petrochemical equipment failure prediction, optimize preventive maintenance strategies, reduce maintenance costs and downtime losses, and provide technical support for the safe production of the petrochemical industry.
Keywords : Big Data Analysis; Petrochemical Equipment; Failure Prediction; Preventive Maintenance; Machine Learning
参考文献
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