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Power transformer condition monitoring and fault diagnosis with multi-agent system based on ontology reasoning

机译:基于本体推理的多智能体电力变压器状态监测与故障诊断

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Power transformer is one of the key important and most expensive equipments in electrical power system. Building systems to monitor their real time behaviours and diagnose their faults autonomously with comprehensive knowledge-base are the key issue. This paper provides a new framework for power transformer monitoring and fault diagnosis based on ontology reasoner. The Gaia methodology is applied to clarify, simplify and standardize the design of the multi-agent system. The real time data is gathered from power transformer, saved into database and it is also available to user on request. Reasoning techniques such as rule-based reasoning and ontology-based reasoning can reduce the user's works. The built ontology provides the comprehensive knowledge-base for deducing and diagnosing its faults. The applied ontology reasoner for fault detection is based on description logic.
机译:电力变压器是电力系统中最重要,最昂贵的设备之一。关键是要建立用于监视其实时行为并利用综合知识库自动诊断其故障的系统。本文为基于本体推理的电力变压器监测与故障诊断提供了一个新的框架。 Gaia方法论可用于澄清,简化和规范多主体系统的设计。实时数据是从电力变压器收集的,并保存到数据库中,也可应要求提供给用户。诸如基于规则的推理和基于本体的推理之类的推理技术可以减少用户的工作量。构建的本体为推断和诊断其故障提供了全面的知识库。用于故障检测的应用本体推理器基于描述逻辑。

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