人工智能驱动的数据分析技术在电力变压器状态检修中的应用综述
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摘要
状态检修为电力变压器的稳定运行与优质电力的正常供应提供了重要保障。随着智能电网建设的不断推进,包括状态监测、生产管理、运行调度、气象环境等在内的电力变压器运行状态相关信息已逐步呈现出体量大、种类多、增长快的典型大数据特征。因此,在电力大数据的时代背景下,开展结合人工智能技术的电力变压器状态数据综合挖掘与分析研究,对于进一步提升设备状态检修的全面性、高效性与准确性具有十分重要的意义。鉴于此,首先概述了面向数据分析的人工智能技术,涵盖专家系统、不确定性推理、机器学习及智能优化计算等研究内容;然后,结合电力变压器状态检修各阶段任务的智能化需求,论述了人工智能驱动的数据分析技术在数据清洗、文本挖掘、图像识别、状态评估、故障诊断、状态预测及检修决策优化等典型场景中的应用研究现状;最后,探讨了现阶段影响基于人工智能的数据分析技术在状态检修领域应用效果的关键问题,并对未来的主要研究方向进行了展望。
Condition-based maintenance is an important measure to ensure stable operation of power transformers and normal supply of electricity. With the development of smart grid, the transformer state data from condition monitoring system, power production management system, operation dispatching system and environmental meteorology system possess the typical characteristics of big data, such as volume, variety and velocity. Therefore, the comprehensive mining and analysis of transformer state data combined with artificial intelligence is of great significance for promoting comprehensiveness, efficiency and accuracy of state maintenance. We first outlined the artificial intelligence technology for data analysis, covering the content of expert system, uncertainty reasoning, machine learning and intelligent computing. Then, In combination with the intelligent demands of the tasks in each stage of condition maintenance, we discussed the application status of artificial intelligence driven data analysis in typical scenarios such as data cleaning, text mining, image recognition, condition assessment, fault diagnosis, condition prediction, and maintenance decision optimization. Finally, we discussed the key problems affecting the application of data analysis technology based on artificial intelligence in the field of condition based maintenance,and prospected the future research directions.
Condition-based maintenance is an important measure to ensure stable operation of power transformers and normal supply of electricity. With the development of smart grid, the transformer state data from condition monitoring system, power production management system, operation dispatching system and environmental meteorology system possess the typical characteristics of big data, such as volume, variety and velocity. Therefore, the comprehensive mining and analysis of transformer state data combined with artificial intelligence is of great significance for promoting comprehensiveness, efficiency and accuracy of state maintenance. We first outlined the artificial intelligence technology for data analysis, covering the content of expert system, uncertainty reasoning, machine learning and intelligent computing. Then, In combination with the intelligent demands of the tasks in each stage of condition maintenance, we discussed the application status of artificial intelligence driven data analysis in typical scenarios such as data cleaning, text mining, image recognition, condition assessment, fault diagnosis, condition prediction, and maintenance decision optimization. Finally, we discussed the key problems affecting the application of data analysis technology based on artificial intelligence in the field of condition based maintenance,and prospected the future research directions.
引文
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