發(fā)布時(shí)間：2019-03-03 20:40

【摘要】：近年來(lái),機(jī)械故障智能診斷系統(tǒng)的研究成為機(jī)械故障診斷領(lǐng)域的研究熱點(diǎn),而系統(tǒng)的智能化程度和診斷準(zhǔn)確度依賴于系統(tǒng)知識(shí)庫(kù)中知識(shí)的數(shù)量與質(zhì)量以及知識(shí)的組織、分類以及更進(jìn)一步的知識(shí)共享和推理。本體作為一種能在語(yǔ)義和知識(shí)層次上描述知識(shí)模型的建模工具,可以提供對(duì)某一領(lǐng)域的概念以及相互關(guān)系的概念化描述,為知識(shí)共享奠定基礎(chǔ),本體支持對(duì)知識(shí)信息的區(qū)分,可以實(shí)現(xiàn)對(duì)領(lǐng)域知識(shí)的層次化表示,本體中包含的類公理以及約束公理可以用于知識(shí)的推理,且現(xiàn)有的本體推理機(jī)可以對(duì)本體提供直接的推理服務(wù)。 本文主要研究如何應(yīng)用本體構(gòu)建機(jī)械故障智能診斷系統(tǒng)的知識(shí)庫(kù),使用本體推理保證知識(shí)庫(kù)知識(shí)的正確性以及通過(guò)本體推理實(shí)現(xiàn)故障診斷的方法。具體對(duì)以下內(nèi)容進(jìn)行了分析和研究: (1)針對(duì)機(jī)械故障診斷需求,在現(xiàn)有的領(lǐng)域本體建模方法的基礎(chǔ)上提出了一套適用于機(jī)械故障診斷領(lǐng)域的本體構(gòu)建方法,通過(guò)對(duì)故障領(lǐng)域知識(shí)的分析,提出了縱向建模方案,對(duì)故障診斷領(lǐng)域知識(shí)根據(jù)故障類型、故障征兆、故障原因以及故障處理方法進(jìn)行分類。通過(guò)定義屬性來(lái)表達(dá)故障類型、故障征兆、故障原因以及故障處理方法之間存在的復(fù)雜的對(duì)應(yīng)關(guān)系,從而將故障診斷領(lǐng)域知識(shí)組織為具備語(yǔ)義關(guān)系的本體知識(shí)庫(kù)。 (2)依據(jù)提出的機(jī)械故障診斷領(lǐng)域的本體構(gòu)建方法以及縱向建模方案,以一類交流電動(dòng)機(jī)故障為例,使用本體建模工具Protégé4.0構(gòu)建了交流電動(dòng)機(jī)故障診斷本體,驗(yàn)證了本文提出的方法的可行性。 (3)本文提出通過(guò)定義復(fù)合類的方法實(shí)現(xiàn)故障診斷,即使用OWL中的構(gòu)造子對(duì)故障類型做復(fù)合類定義并將其聲明為等價(jià)類,本體推理機(jī)通過(guò)對(duì)等價(jià)類的推理實(shí)現(xiàn)故障診斷。 (4)使用本體推理機(jī)對(duì)故障診斷本體進(jìn)行了推理,對(duì)于推理檢測(cè)出的邏輯錯(cuò)誤提出了相應(yīng)的解決方案,并通過(guò)對(duì)等價(jià)類的推理,實(shí)現(xiàn)了對(duì)起動(dòng)故障、過(guò)熱故障以及電刷等故障的診斷,其診斷結(jié)果的準(zhǔn)確性和合理性較高。 結(jié)果表明,本文提出的機(jī)械故障診斷領(lǐng)域的本體構(gòu)建及推理的方法具有可行性,為機(jī)械故障智能診斷領(lǐng)域的本體建模及推理的理論與方法研究提供了一條值得探索的途徑。
[Abstract]:In recent years, the research of mechanical fault intelligent diagnosis system has become a hot topic in the field of mechanical fault diagnosis, and the degree of intelligence and diagnostic accuracy of the system depends on the quantity and quality of knowledge and the organization of knowledge in the knowledge base of the system. Classification and further knowledge sharing and reasoning. Ontology, as a modeling tool that can describe the knowledge model at the semantic and knowledge level, can provide a conceptual description of the concepts and relationships in a certain domain, lay the foundation for knowledge sharing, and ontology supports the distinction of knowledge information. The hierarchical representation of domain knowledge can be realized. The class axiom and constraint axiom contained in ontology can be used for reasoning of knowledge, and the existing ontology inference machine can provide direct reasoning services to ontology. This paper mainly studies how to use ontology to construct the knowledge base of mechanical fault intelligent diagnosis system, and how to use ontology reasoning to ensure the correctness of knowledge base and the method of realizing fault diagnosis through ontology reasoning. The following contents are analyzed and studied in detail: (1) according to the requirements of mechanical fault diagnosis, a set of ontology construction methods suitable for mechanical fault diagnosis is proposed on the basis of existing domain ontology modeling methods. Based on the analysis of fault domain knowledge, a vertical modeling scheme is proposed. The fault diagnosis domain knowledge is classified according to the fault type, fault symptom, fault cause and fault handling method. By defining attributes to express the complicated correspondence among fault type, fault symptom, fault cause and fault handling method, the knowledge of fault diagnosis field is organized into ontology knowledge base with semantic relationship. (2) according to the ontology construction method and longitudinal modeling scheme in the field of mechanical fault diagnosis, the fault diagnosis ontology of AC motor is constructed by using the ontology modeling tool Prot 茅 g 茅 4.0, taking a class of AC motor faults as an example. The feasibility of the proposed method is verified. (3) this paper proposes a method to realize fault diagnosis by defining composite class. Even if the composite class is defined by the constructors in OWL and declared as equivalent class, the ontology inference machine realizes fault diagnosis by reasoning the equivalent class. (4) the ontology inference machine is used to reason the fault diagnosis ontology, and the corresponding solution to the logic error detected by reasoning is put forward, and the starting fault is realized by reasoning the equivalent class. The diagnosis of overheating fault and brush fault has high accuracy and rationality. The results show that the method of ontology construction and reasoning in the field of mechanical fault diagnosis proposed in this paper is feasible, which provides a valuable way to study the theory and method of ontology modeling and reasoning in the field of intelligent mechanical fault diagnosis.
【學(xué)位授予單位】：湖南科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2011
【分類號(hào)】：TP391.1;TH165.3

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