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Power Transformer Condition Monitoring and Fault Diagnosis with Multi-agent System based on Ontology Reasoning

机译:基于本体推理的多助理系统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的重要和最昂贵的设备之一。构建系统要监控其实时行为并以全面的知识库自主诊断其故障是关键问题。本文为基于本体理发师的电力变压器监控和故障诊断提供了新的框架。盖亚方法应用于澄清,简化和标准化多助理系统的设计。实时数据从电源变压器收集,保存到数据库中,也可以根据要求提供给用户。推理技术如规则的推理和基于本体的推理,可以减少用户的作品。内置本体提供了综合知识库,用于推导和诊断其故障。用于故障检测的应用本体理发师基于描述逻辑。

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