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Integration of Fuzzy OWL Ontologies and Fuzzy Time Series in the Determination of Faulty Technical Units

机译:模糊OWL本体和模糊时间序列在故障技术单元确定中的集成

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The method of constructing fuzzy ontologies was investigated in the framework of this work. An ontological model for assessing the state of helicopter units has been developed. The article provides a formal description of fuzzy ontologies and features of the representation of elements of fuzzy axioms in FuzzyOWL notation. According to the proposed approach, the summarizing of the state of a complex technical system is carried out by means of an inference based on a fuzzy ontology. Objects, properties and axioms of fuzzy ontology determine the parameters of the membership functions and linguistic variables of the objects of analysis in the form of time series. A software product was developed to implement the proposed approach. As part of this work, experiments were conducted to search for anomalous situations and search for possible faulty helicopter units using the developed approach to the integration of fuzzy time series and fuzzy ontology. For the first time, the results of the inference of knowledge based on the integration of fuzzy time series and fuzzy ontologies in the tasks of analyzing the diagnosis of complex technical systems were obtained. The proposed approach of hybridization of fuzzy time series and fuzzy ontologies made it possible to reliably recognize anomalous situations with a certain degree of truth, and to find possible faulty aggregates corresponding to each anomalous situation.
机译:在这项工作的框架内,研究了构建模糊本体的方法。已经开发了用于评估直升机部队状态的本体模型。本文提供了模糊本体的正式描述,以及以FuzzyOWL表示法表示的模糊公理的元素表示的特征。根据所提出的方法,通过基于模糊本体的推理来对复杂技术系统的状态进行总结。模糊本体的对象,属性和公理以时间序列的形式确定分析对象的隶属函数的参数和语言变量。开发了一种软件产品来实现建议的方法。作为这项工作的一部分,进行了实验,以使用模糊时间序列和模糊本体的集成开发方法来搜索异常情况并搜索可能出现故障的直升机单元。首次获得了将模糊时间序列与模糊本体相结合的知识推理结果,用于复杂技术系统诊断分析任务中。提出的模糊时间序列和模糊本体混合的方法使得可以可靠地识别具有一定真实度的异常情况,并找到与每个异常情况相对应的可能的错误集合。

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