当前,国家电网处于数字化转型重要时期,“五E一中心”配合数据中台建设旨在打造新型大数据生态。本文首先针对当前“五E一中心”新环境下电力物资供应链数据特点及产生数据质量问题的原因,提出了物资供应链数据质量管理体系的技术需求。其次,从多个维度剖析了数据感知技术在电力物资供应链数据质量管理中的应用,主要分为基于时空相关性的多源感知数据清洗技术、基于隐藏规则挖掘的异构异常数据修复技术以及基于供应商信息系统标识的全息画像认知技术三大关键技术研究。最后,基于电力物资供应链生态圈全寿命周期管理发展需求,分析了数据感知技术延伸及拓展应用方向。

At present, the State Grid of China is in an important period of digital transformation. The "five E one center" cooperates with the construction of data center to create a new type of big data ecology. Firstly, according to the data characteristics of power material supply chain and the causes of data quality problems under the new environment of "five E one center", this paper puts forward the technical requirements of data quality management system of material supply chain. Secondly, the application of data sensing technology in data quality management of power material supply chain is analyzed from multiple dimensions. It is mainly divided into three modules: Multi-source perception data cleaning based on spatiotemporal correlation, heterogeneous abnormal data recovery technology based on hidden rule mining, and Holographic image recognition technology based on supplier information system identification. Finally, based on the development demand of life cycle management of power material supply chain ecosystem, the extension and application direction of data sensing technology are analyzed.

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国家自然科学基金项目（面上项目，重点项目，重大项目）