| 引用本文: | 陈勇,李胜男,张丽,鲁浩,戴志辉.基于改进Apriori算法的智能变电站二次设备缺陷关联性分析[J].电力系统保护与控制,2019,47(20):135-141.[点击复制] |
| CHEN Yong,LI Shengnan,ZHANG Li,LU Hao,DAI Zhihui.Association analysis for defect data of secondary device in smart substations based on improved Apriori algorithm[J].Power System Protection and Control,2019,47(20):135-141[点击复制] |
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| 摘要: |
| 智能变电站的出现为大数据的收集、管理提供了技术支持，也为二次设备缺陷数据的关联性分析提供了丰富的数据样本。首先，在此基础上建立了智能变电站二次设备缺陷数据模型。其次，根据智能变电站缺陷数据模型特点对Apriori算法进行了改进，降低了算法的时间复杂度和内存占用量。最后，以某市一年的智能变电站二次设备缺陷数据为例，通过改进的Apriori算法挖掘缺陷数据各个属性之间的关联性并对关联规则进行了分析。研究表明，该方法能够分析缺陷情况，寻找二次设备薄弱环节，为缺陷巡检方式的制定和检修策略的制定提供支持。与传统Apriori算法相比，改进算法的时间复杂度较低。 |
| 关键词: Apriori算法 智能变电站 二次设备 缺陷 关联性分析 |
| DOI：10.19783/j.cnki.pspc.181390 |
| 投稿时间：2018-11-06修订日期：2019-01-03 |
| 基金项目:国家自然科学基金项目资助(51877084);河北省自然科学基金项目资助(E2018502063);中央高校基本科研业务费项目资助(2017MS096) |
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| Association analysis for defect data of secondary device in smart substations based on improved Apriori algorithm |
| CHEN Yong,LI Shengnan,ZHANG Li,LU Hao,DAI Zhihui |
| (Electric Power Research Institute of Yunnan Power Grid Co., Ltd., Kunming 650500, China;North China Electric Power University Baoding, Baoding 071003, China) |
| Abstract: |
| The development of smart substations provide technical support for collection and management of big data, and abundant defect data for related analysis about the secondary device. In view of this, this paper establishes the defect data model of the secondary device in smart substations firstly. Secondly, according to characteristics of the defect data model, the Apriori algorithm is improved to reduce the time complexity and memory occupation. Finally, taking defect data of the secondary device of a city in one year as an example, the association rules of the defect data are acquired and analyzed by the improved Apriori algorithm. The result shows that the proposed method can analyze the device defect, search for the weakness of the secondary device, and provide the support for the formulation of defect inspection modes. Besides, compared with the traditional Apriori algorithm, the improved Apriori algorithm reduces the time complexity. This work is supported by National Natural Science Foundation of China (No. 51877084), Natural Science Foundation of Hebei Province (No. E2018502063), and Fundamental Research Funds for the Central Universities (No. 2017MS096). |
| Key words: Apriori algorithm smart substation secondary device defect association analysis |
