【作者】 梁伟； 尹康涌； 朱睿； 黄浩声； 周学华； 王益男； 周治国； 王凯莺；

【Author】 LIANG Wei;YIN Kangyong;ZHU Rui;HUANG Haosheng;ZHOU Xuehua;WANG Yinan;ZHOU Zhiguo;WANG Kaiying;Electric Power Research Institute,State Grid Jiangsu Electric Power Co.,Ltd.;School of Integrated Circuits and Electronics,Beijing Institute of Technology;China Electricity Council;

【机构】 国网江苏省电力有限公司电力科学研究院； 北京理工大学集成电路与电子学院； 中国电力企业联合会；

【摘要】 电力行业作为国民经济的基石,保障电力安全生产作业安全是重中之重。针对传统的电力作业现场安全性评估手段消耗大量的人力物力且依赖管理人员主观意识的问题,提出一种基于模糊综合评价法的电力生产作业安全性评价模型,模型根据深度学习算法检测为作业现场违章情况,采用层次分析法制定因素集并构建隶属度函数实现了对电力作业现场安全性的自动化评估。实验证明所提出模型能够有效地评估电力作业现场安全性并得到安全性量化结果。更多还原

【Abstract】 As the cornerstone of the national economy, the power industry is the top priority to ensure the safety of power production and operation. Aiming at the problem that the traditional safety assessment methods of electric power operation site consume a lot of human and material resources and rely on the subjective consciousness of managers. This paper proposes a power production operation safety evaluation model based on fuzzy comprehensive evaluation method, which uses the analytic hierarchy method to formulate the factor set and construct the membership function to realize the automatic assessment of the safety of the power operation site according to the deep learning algorithm detecting the violation of the work site. Experiments prove that the proposed model can effectively evaluate the safety of the power work site and obtain safety quantification results.更多还原