摘要
利用大数据及人工智能技术全面分析加氢循环氢大机组异常原因,通过对大机组运行过程的相关工况参数变化趋势进行相关性分析,基于监督类机器学习算法的模型对大机组运行健康状况进行分析评估,提前获取可能发生的异常故障并及时采取应对措施。
It is used to comprehensively analyze the causes of abnormal in large Hydro-cracking Recycle units by Big data and artificial intelligence technology.Through the correlation analysis of the change trend of relevant operating condition parameters in the operation process of large units,the health status of large units is analyzed and evaluated based on the model of supervised machine learning algorithm,so as to obtain possible abnormal faults in advance and take corresponding measures in time.
出处
《工业控制计算机》
2021年第6期130-133,共4页
Industrial Control Computer
基金
宁波市科技创新2025重大专项资助,项目名称:基于工业物联网的面向流程工业的智能工厂全数据集成平台项目(2018B10049)。
关键词
大机组
预测性维护
大数据技术
large units
predictive maintenance
big data technology
