基于工业物联与知识工程的高能耗企业异常预警方法

Exception Warning of Energy-intensive Manufacturing Enterprise Based on Industrial IoT and Knowledge Engineering

异常事件的精准预警是高能耗企业优化运行控制的基础。针对高能耗企业中云端数据集中分析时间长、异常事件影响要素众多、异常事件预警不准等带来的异常事件管控不及时、优化处理困难、能耗高昂等难题,提出一种基于工业物联与知识工程的高能耗企业异常预警方法。在设计高能耗企业异常预警体系架构的基础上,对其中基于工业物联的边云协同感知环境、基于知识工程的生产异常管理知识挖掘、基于综合重要度的异常事件预警机制3个关键技术进行了详细阐述。最后,开发了高能耗企业异常精准预警及管控平台,验证了所提方法的可行性与有效性。通过上述体系架构及关键技术的实施,可有效促进高能耗企业数据的边云协同高效分析,并构建一种异常的主动感知与优化管控机制,为高能耗企业的可靠稳定运行提供了参考模型。

The active warning of exceptions is essential to the optimal control of energy-intensive enterprise.Due to the long analysis time of central cloud data analysis mode and numerous influencing factors and inaccurate early warning of exceptions,the exception management of energy-intensive enterprises is not timely,the optimal control is difficult,and the energy consumption is difficult to reduce.An exception early warning method of energy-intensive enterprises based on industrial Internet of Things(IoT)and knowledge engineering is proposed.After designing the exception early warning system architecture of energy-intensive consumption enterprises,three key technologies are discussed in detail,i.e.,industrial IoT-based edge cloud collaborative sensing environment,knowledge mining of production anomaly management based on knowledge engineering,and exception early warning mechanism based on comprehensive importance are elaborated.Lastly,an exception warning and control platform of energy-intensive enterprise is developed to demonstrate the effectiveness and feasibility of the proposed method.Through the implementation of the above architecture and key technologies,the collaborative and efficient analysis of the edge cloud data of energy-intensive enterprises can be effectively promoted,and an active exception perception and optimization management and control mechanism is built,providing a reference model for the reliable and stable operation of energy-intensive enterprises.