本文選題：制造物聯(lián) + 關鍵事件　； 參考：《貴州大學》2016年博士論文

【摘要】：互聯(lián)網、物聯(lián)網、云計算、大數據等技術在制造業(yè)的滲透,推動了制造業(yè)信息化的發(fā)展,形成了制造業(yè)的新技術。其中,電子技術、信息技術、計算智能、物聯(lián)網與先進制造技術的融合,形成了制造物聯(lián)技術,增強了制造智能化能力,形成了新型制造服務模式。制造物聯(lián)通過感知、處理及利用制造數據,提供生產過程智能管控的決策支持,以促進生產過程精確控制的實現。面對“互聯(lián)網+”環(huán)境下先進制造服務模式的需求,制造與服務過程中信息綜合感知及智能處理等難題亟待解決。本文在分析制造物聯(lián)及復雜事件處理等領域相關研究進展的基礎上,研討了生產過程制造物聯(lián)關鍵事件主動感知與處理架構及方法,并建立了所提技術方法應用實現的相關制造過程物聯(lián)管控系統(tǒng)。論文的具體研究工作如下:首先,在制造物聯(lián)事件感知的基礎理論方面,主要進行制造物聯(lián)內涵及其技術特征分析,構建了面向車間生產的制造物聯(lián)技術架構;研究了制造物聯(lián)感知數據的來源及其特性,并分析了制造數據采集及異構系統(tǒng)數據集成方式,建立了制造數據管理體系模型。其次,針對制造物聯(lián)事件主動感知方面,結合制造物聯(lián)網特點、制造物聯(lián)事件主動感知模型以及物聯(lián)感知系統(tǒng)設計,建立基于物聯(lián)網技術的事件主動感知技術架構,并設計了基于“傳感網+嵌入式+Web Service”的生產過程事件感知方法,以提供精確生產和智能決策需要的重要支撐。基于智能制造模式構建了制造大數據的應用規(guī)劃,并結合制造數據感知處理及應用實例,說明所提理論框架的可行性與有效性。然后,針對制造過程事件的結構化統(tǒng)一表達需求,采用EXPRESS語言建立了制造物聯(lián)車間事件模型,并制定了EXPRESS轉換為XML模式制造數據的映射規(guī)則。面向制造過程事件組織和關聯(lián)方面的統(tǒng)一語義描述,通過生產過程事件類型及關聯(lián)關系分析,建立了復雜事件結構模型;結合復雜事件操作符和可擴展標記語言語法語義,建立了基于XML的制造過程事件描述語言(XEDL),并依據生產過程事件描述實例,說明XEDL語言在事件模型描述方面的優(yōu)勢。基于XEDL的復雜事件表達方法,有利于解決制造過程事件關聯(lián)的推理求解和統(tǒng)一組織問題。最后,在制造過程事件處理方面,針對制造物聯(lián)系統(tǒng)的分布式特點,提出了基于“EDA+SOA”的復雜事件處理架構,并進行復雜事件處理模塊和規(guī)則引擎的闡析。針對復雜事件模式匹配方面,建立了基于CEP的匹配式事件關聯(lián)方案,運用Apriori算法對制造過程事務集進行關聯(lián)規(guī)則挖掘并生成關聯(lián)模板;以事件處理引擎工作原理為基礎,結合關鍵事件和事件匹配模板的特點,提出基于有向圖的啟發(fā)式Esper算法,實現了基于關聯(lián)模板的生產過程關鍵事件實時處理。應用實現方面,基于Windows7操作系統(tǒng)和.NET 4.0架構,借助Microsoft Visual Studio 2010和My Eclipse開發(fā)平臺,以C#和Java作為開發(fā)語言,以Microsoft SQL Server2008 R2作為數據庫,研發(fā)面向離散型生產過程的制造物聯(lián)管控平臺,以實現制造物聯(lián)事件感知與處理技術研究成果的應用�；谥圃煳锫�(lián)管控平臺的業(yè)務邏輯和體系結構,結合制造物聯(lián)智能感知以及信息技術,建立了一套面向油辣椒生產的物聯(lián)管控系統(tǒng),實現了生產過程關鍵監(jiān)控環(huán)節(jié)信息的感知及查詢、事件關聯(lián)分析等。綜上所述,論文對制造物聯(lián)關鍵事件主動感知與處理涉及的關鍵技術問題進行了探討,通過理論研究及應用實現結果,驗證了所提技術方法的可行性。生產過程制造物聯(lián)關鍵事件主動感知的理論方法與處理技術的研究成果,將為制造業(yè)生產過程智能管控和決策優(yōu)化提供理論支撐。
[Abstract]:The infiltration of Internet, Internet of things, cloud computing, large data and other technologies in the manufacturing industry has promoted the development of manufacturing information and formed a new technology in manufacturing industry. The integration of electronic technology, information technology, computational intelligence, the Internet of things and advanced manufacturing technology formed the technology of manufacturing material union, enhanced the ability of manufacturing intelligence and formed a new type of technology. Manufacturing service modes. Product is perception, processing and utilization of manufacturing data, provide the production process control intelligent decision support, to promote the realization of accurate control of the production process. In the face of "Internet plus" under the environment of advanced manufacturing mode service demand, manufacturing and service of information in the process of comprehensive perception and intelligent processing problems urgently On the basis of the related research progress in the field of manufacturing and complex event processing, this paper discusses the framework and methods of the active perception and processing of the key events in the manufacturing process, and establishes a related manufacturing process control system related to the implementation of the proposed technology and method. The specific research work of this paper is as follows: first of all, the research work is as follows: On the basis of the basic theory of event perception, this paper mainly carries out the connotation and technical characteristics analysis of the manufacture, constructs the technology framework of manufacturing material Association for the workshop production, studies the source and characteristics of the perceived data, and analyzes the manufacturing data collection and the data integration method of the heterogeneous system, and establishes the manufacturing number. According to the model of management system, secondly, in view of the active perception of the event, combined with the features of the Internet of things, the active perception model of the event and the design of the physical association perception system is designed, the event active perception technology architecture based on the Internet of things technology is established, and the production process based on the "sensor network + embedded +Web Service" is designed. Event perception method to provide important support for precise production and intelligent decision-making. Based on the intelligent manufacturing model, the application planning of large data is built, and the feasibility and effectiveness of the proposed theoretical framework are illustrated with the manufacturing data perception processing and application examples. Then, the structural unified expression of the manufacturing process needs to be expressed. The event model of manufacturing joint workshop is established in EXPRESS language, and the mapping rules of EXPRESS conversion into XML model are formulated. A unified semantic description of the event organization and association of the manufacturing process is described. The complex event structure model is established through the analysis of the event type and association relationship in the production process, and the complex event is combined with the complex event. The syntax semantics of the operator and extensible markup language, the XML based manufacturing process event description language (XEDL) is established, and the advantages of the XEDL language in the event model description are described according to the production process events. The XEDL based complex event expression method is favorable for solving and unifying the reasoning of the event Association of the manufacturing process. In the end, in the manufacturing process event processing, the complex event processing architecture based on "EDA+SOA" is proposed for the distributed characteristics of the manufacturing association system, and the complex event processing module and the rule engine are explained. A matching event association scheme based on CEP is established for the complex event pattern matching. Apriori algorithm is used to mining association rules for manufacturing process transactions and generating association templates. Based on the working principle of event processing engine and combining the characteristics of key events and event matching templates, a heuristic Esper algorithm based on directed graph is proposed to implement the real-time processing of key events in the production process based on the Association template. In the aspect of implementation, based on Windows7 operating system and.NET 4 architecture, with the aid of Microsoft Visual Studio 2010 and My Eclipse development platform, C# and Java are developed as the development language and Microsoft SQL Server2008 is used as the database to develop a manufacturing joint management platform for discrete production process, in order to realize the event perception and processing of the manufacturing material union. The application of the technical research results. Based on the business logic and architecture of the joint management and control platform of the manufacturing material, combined with the intelligent perception of the manufacture and the information technology, a set of joint management and control system for the production of oil pepper is established, which realizes the sense and inquiry of the key monitoring link information of the production process, the event association analysis and so on. In this paper, the key technical problems involved in the active perception and processing of the key events of the manufacturing association are discussed. The feasibility of the proposed technical method is verified through theoretical research and application implementation. The theoretical method of the active perception of the key events in the production process and the research results of the processing technology will be the production process intelligence of the manufacturing industry. It provides theoretical support for control and decision optimization.

【學位授予單位】：貴州大學
【學位級別】：博士
【學位授予年份】：2016
【分類號】：TP391.44;TN929.5;TP311.52

【相似文獻】

相關期刊論文 前7條

1 ;“制造物聯(lián)與RFID技術”專欄征稿通知[J];計算機集成制造系統(tǒng);2012年09期

2 ;“制造物聯(lián)與RFID技術”專欄征文通知[J];計算機集成制造系統(tǒng);2012年10期

3 ;“制造物聯(lián)與RFID技術”專欄征文通知[J];計算機集成制造系統(tǒng);2012年11期

4 ;“制造物聯(lián)與RFID技術”專欄征文通知[J];計算機集成制造系統(tǒng);2013年01期

5 ;“制造物聯(lián)與RFID技術”專欄征文通知[J];計算機集成制造系統(tǒng);2012年12期

6 ;“制造物聯(lián)與RFID技術”專欄征文通知[J];計算機集成制造系統(tǒng);2013年02期

7 ;[J];;年期

相關重要報紙文章 前1條

1 一民;找出地球最早生命的證據[N];北京科技報;2001年

相關博士學位論文 前2條

1 陳偉興;生產過程制造物聯(lián)關鍵事件主動感知與處理技術研究[D];貴州大學;2016年

2 王建華;制造物聯(lián)海量數據流處理方法研究[D];廣東工業(yè)大學;2015年

相關碩士學位論文 前2條

1 曹珠英;韓國制造物責任法研究[D];華東政法大學;2008年

2 王錦煜;制造物聯(lián)中車間底層數控設備監(jiān)控管理系統(tǒng)的研究[D];江南大學;2014年

，

本文編號：1825674