官术网_书友最值得收藏!

參考文獻

[1]顧燕.智能傳感器發(fā)展現(xiàn)狀探究[J].無線互聯(lián)科技,2017(21):12-13.

[2]羅林,胥玉萍,宋春華.傳感器的最新應用與發(fā)展[J].信息通信,2016(3),176-177.

[3]高偉.淺談智能壓力傳感器[J].科技領(lǐng)域,2014(2):413.

[4]張映鋒,郭振剛,錢成,等.基于過程感知的底層制造資源智能化建模及其自適應協(xié)同優(yōu)化方法研究[J].機械工程學報,2018,54(16):1-10.

[5]CHHIM P, CHINNAM R B, SADAWI N. Product design and manufacturing process based ontology for manufacturing knowledge reuse [J]. Journal of Intelligent Manufacturing, 2019, 30(2):905-916.

[6]劉航,杜江,白瑀.基于多維度本體的制造業(yè)領(lǐng)域知識語義建模研究[J].制造技術(shù)與機床,2019(9):140-146.

[7]BOCK C E, ZHA X F, SUH H, et al. Ontological product modeling for collaborative design [J]. Advanced Engineering Informatics, 2010, 24(4):510-524.

[8]SADIK A R, URBAN B. An ontology-based approach to enable knowledge representation and reasoning in worker-cobot agile manufacturing [J]. Future Internet, 2017, 9(4):90.

[9]OGUZ O S, RAMPELTSHAMMER W, PAILLAN S, et al. An ontology for hu-man-human interactions and learning interaction behavior policies [J]. ACM Transactions on Human-Robot Interaction, 2019, 8(3):1-26.

[10]仇永濤.離散智能車間擾動預測與高效運行管控方法研究[D].無錫:江南大學,2020.

[11]付敬奇.執(zhí)行器及其應用[M].北京:機械工業(yè)出版社,2009.

[12]張學凱.防錯技術(shù)在電子產(chǎn)品生產(chǎn)線的應用研究[D].上海:上海交通大學,2008.

[13]陶飛,程穎,程江峰,等.數(shù)字孿生車間信息物理融合理論與技術(shù)[J].計算機集成制造系統(tǒng),2017,23(8):1603-1611.

[14]LIU M, MA J, LIN L, et al. Intelligent assembly system for mechanical products and key technology based on internet of things [J]. J Intell Manuf, 2017, 28(2):271-299.

[15]GIUSTO D, MORABITO G, IERA A, et al. The Internet of things [M]. New York: Springer, 2010.

[16]張俊.基于RFID和電子看板的裝配生產(chǎn)監(jiān)控系統(tǒng)的研究[D].杭州:浙江大學,2007.

[17]孫志楠.汽車裝配線多層次、多信息融合的3D虛擬監(jiān)控關(guān)鍵技術(shù)[D].南京:南京航空航天大學,2016.

[18]劉明周,馬靖,趙志彪,等.物聯(lián)網(wǎng)環(huán)境下的機械產(chǎn)品管控一體智能裝配系統(tǒng)建模[J].計算機集成制造系統(tǒng),2015,21(3):669-679.

[19]劉明周,王強,凌琳.基于實時信息驅(qū)動的生產(chǎn)車間運行駕駛艙研究及實現(xiàn)[J].計算機集成制造系統(tǒng),2015,21(8):2052-2062.

[20]HOZDI C E, KOZJEK D, BUTALA P. A cyber-physical approach to the man-agement and control of manufacturing systems [J]. Strojniski Vestnik, 2020, 66(1).

[21]馮明濤.基于深度學習的機器人視覺三維感知與識別方法研究[D].長沙:湖南大學,2019.

[22]HORNUNG A, WURM K M, BENNEWITZ M, et al. OctoMap: an efficient probabilistic 3D mapping framework based on octrees [J]. Autonomous Robots, 2013, 34: 189-206.

[23]GUO Y, BENNAMOUN M, SOHEL F, et al. A comprehensive performance evaluation of 3D local feature descriptors [J]. International Journal of Computer Vision, 2016, 116(1):66-89.

[24]張昊若.面向機器人抓取的弱紋理物體六自由度位姿估計方法研究[D].上海:上海交通大學,2019.

[25]FU M, ZHOU W. DeepHMap++: combined projection grouping and correspon-dence learning for full of pose estimation [J]. Sensors, 2019, 19(5):1032-1050.

[26]ZHUANG C, WANG Z, ZHAO H, et al. Semantic part segmentation method based 3D object pose estimation with RGB-D images for bin-picking [J]. Robotics and Computer-Integrated Manufacturing, 2021, 68: 102086.

[27]MNIH V, K AVUKCUOGLLI K, SILVER D, et al. Human-level control through deep reinforcement learning [J]. Nature, 2019, 518(7540):529-533.

[28]LEVEN P, HUTCHINSON S. A framework for real-time path Planning in changing environments [J]. The International Journal of Robotics Re-search, 2001, 21(12):999-1030.

[29]GUTTA P R, CHINTHALA V S, MANCHO JU R V, et al. A review on facility layout design of an automated guided vehicle in flexible manufactur-ing system [J]. Materials Today: Proceedings, 2018, 5(2):3981-3986.

[30]BOZER Y A, SRINIVASAN M M Tandem configurations for automated guid-ed vehicle systems and the analysis of single vehicle loops [J]. IIE Transactions, 1988, 23(1):72-82.

[31]龔劬.圖論與網(wǎng)絡最優(yōu)化算法[M].重慶:重慶大學出版社,2009.

[32]GASKINS R J, TANCHOCO J M A. Flow path design for automated guided vehicle systems [J]. International Journal of Production Research, 1987, 25(5):667-676.

[33]KASPI M, TANCHOCO J M A Optimal flow path design of unidirectional AGV systems [J]. International Journal of Production Research, 1990, 28(6):1023-1030.

[34]KASPI M, KESSELMAN U, TANCHOCO J M A. Optimal solution for the flow path design problem of a balanced unidirectional AGV system [J]. Inter-national Journal of Production Research, 2002, 40(2):389-401.

[35]KOOPMANS J C, BECKMANN M. Assignment problems and the location of economic activities [J]. Econometrica, 1957, 25(1):53-76.

[36]CHIANG W C, CHI C. Intelligent local search strategies for solving fa-cility layout problems with the quadratic assignment problem formu-lation [J]. European Journal of Operational Research, 1998, 106(2-3):457-488.

[37]SCHOLZ D, PETRICK A, DOMSCHKE W. STaTS:A slicing tree and tabu search based heuristic for the unequal area facility layout problem [J]. Europe-an Journal of Operational Research, 2009, 197(1):166-178.

[38]馬慶吉.基于改進灰狼算法的柔性作業(yè)車間調(diào)度方法研究[D].武漢:華中科技大學,2019.

[39]雷鳴.基于進化計算的多目標柔性作業(yè)車間調(diào)度問題研究[D].蘭州:蘭州交通大學,2020.

[40]李黎.混合量子粒子群算法在柔性作業(yè)車間調(diào)度中的研究與應用[D].大連:大連交通大學,2019.

[41]KOUISS K, PIERREVAL H, MEBARKI N. Using multi-agent architecture in FMS for dynamic scheduling [J]. Journal of Intelligent Manufacturing, 1997, 8(1):41-47

[42]WANG J Q, FAN G Q, YAN F Y, et al. Research on initiative schedul-ing mode for a physical internet-based manufacturing system [J]. International Journal of Advanced Manufacturing Technology, 2016, 84 (1-4):47-58.

[43]ZHANG Y F, QIAN C, LYU Jingxiang, et al. Agent and cyber-physical system based self-organizing and self-adaptive intelligent shopfloor [J]. IEEE Transactions on Industrial Informatics, 2017, 13(2):737-747.

[44]ZHANG Y F, WANG J, LIU Y. Game theory based real-time multi-objec-tive flexible job shop scheduling considering environmental impact [J]. Journal of Cleaner Production, 2017, 167(11):665-679.

[45]陶飛,張萌,程江峰,等.數(shù)字孿生車間:一種未來車間運行新模式[J].計算機集成制造系統(tǒng),2017,23(1):1-9.

[46]TA0 F, CHENG J F, QI Q L, et a1.Digital twin driven product design, manufacturing and service with big data [J]. The Interactional Journal of Advanced Manufacturing Technology, 2018, 94: 3563-3576.

[47]FOURGEAU E, GOMEZ E, ADLI H, et a1.System engineering workbench for multi-views systems methodology with 3DEXPERIENCE Platform the aircraft radar use case [M]//Complex Systems Design & Management Asia. Berlin: Springer International Publishing, 2016.

[48]GRIEVES M, VICKERS J. Digital twin: mitigating unpredictable, undesirable emergent behavior in complex systems [M]//Transdisciplinary Perspectives on Complex Systems. Berlin:Springer International Publishing, 2017.

[49]TUEGEL E, INGRAFFEA A, EASON T, et a1.Reengineering aircraft structural life prediction using a digital twin [J]. International Jour-nal of Aerospace Engineering, 2011. DDI: 10.1155/2011/154798.

[50]莊存波,劉檢華,熊輝,等.產(chǎn)品數(shù)字孿生體的內(nèi)涵、體系結(jié)構(gòu)及其發(fā)展趨勢[J].計算機集成制造系統(tǒng),2017,23(4):753-768.

[51]于勇,范勝廷,彭關(guān)偉,等.數(shù)字孿生模型在產(chǎn)品構(gòu)型管理中應用探討[J].航空制造技術(shù),2017,526(7):41-45.

[52]ZHANG H, LIU Q, CHEN X, et a1.A digitaltwin-based approach for designing and multi—objective optimization of hollow glass production 1ine [J]. IEEE Access, 2017(5):26901-26911.

[53]WANG J Q, FAN G Q, YAN F Y, et a1.Research on initiative scheduling mode for a physical internet-based manufacturing system [J]. International Journal of Advanced Manufacturing Technology, 2016, 84(1):47-58.

[54]QU T, PAN Y H, LYU X, et al. IoT-based real-time production logistics synchronization mechanism and method toward customer order dynam-ics [J]. Transactions of the Institute of Measurement and Contral, 2017, 39(4):429-445.

[55]屈挺,張凱,羅浩,等.物聯(lián)網(wǎng)驅(qū)動的“生產(chǎn)-物流”動態(tài)聯(lián)動機制、系統(tǒng)及案例[J].機械工程學報,2015,51(20):36-44.

[56]KOREN Y.Reconfigurable manufacturing systems [J]. Journal of Manufac-turing Systems,1999,29(4):130-141.

[57]MEHRABI M G, KANNATEY-ASIBU E. Mapping theory: a new approach to design of multi-sensor monitoring of reconfigurable machining systems (RMS) [J]. Journal of Manufacturing Systems, 2001, 20(5):297-304.

[58]DING Y, SHI J J, CEGLAREK D. Diagnosability analysis of multi-station manufacturing processes [J]. Journal of Dynamic Systems Measurement and Control-Transactions of the ASME, 2002, 124(1):1-13.

[59]SCHOLZ-REITER B, LAPPE D, GRUNDSTEIN S. Capacity adjustment based on reconfigurable machine tools-harmonising throughput time in job-shop manufacturing [J]. CIRP Annals,2015,64(1):403-406.

[60]RENNA P. Decision-making method of reconfigurable manufacturing systems'reconfiguration by a Gale-Shapley model [J]. Journal of Manufacturing Systems,2017,45:149-158.

[61]羅振壁,朱耀祥.現(xiàn)代制造系統(tǒng)[M].北京:機械工業(yè)出版社,2000.

[62]王國慶,胡新平,劉欣,等.伺服艙鑄造單元在首都航天機械公司的實踐[J].航天制造技術(shù),2006(4): 1-3.

[63]王國慶,胡新平,劉欣,等.機械加工單元的實用工藝布局方法與工藝優(yōu)化[J]. 航天制造技術(shù),2006(2):1-5.

[64]李京生.面向多品種變批量生產(chǎn)的重構(gòu)調(diào)度方法[D].北京:北京理工大學,2014.

[65]徐雨.離散型生產(chǎn)線的制造單元重構(gòu)技術(shù)研究[D].貴陽:貴州大學,2019.

[66]XIA T, XI L, PAN E, et al. Reconfiguration-oriented opportunistic maintenance policy for reconfigurable manufacturing systems [J]. Re-liability Engineering & System Safety, 2017, 166: 87-98.

[67]李曄,王宇晗,胡俊.小型可重組數(shù)控機床的設計[J].制造技術(shù)與機床,2002,1(5):25-27.

[68]張根寶,王化培.可重構(gòu)機床及其關(guān)鍵技術(shù)[J].制造技術(shù)與機床,2002,1(5):22-24.

[69]蔡宗琰,嚴新民.可重構(gòu)制造系統(tǒng)重構(gòu)算法的實例研究[J].計算機輔助設計與圖形學報,2003,15(2):162-166.

[70]白俊杰,龔毅光,王寧生,等.面向訂單制造的可重構(gòu)制造系統(tǒng)中虛擬制造單元構(gòu)建技術(shù)[J].計算機集成制造系統(tǒng),2009,15(2):313-320.

[71]鄭華林. 面向大規(guī)模定制的生產(chǎn)管理模式及其產(chǎn)品族建模技術(shù)研究[D]. 重慶:重慶大學.

[72]范興柱. 基于知識的可重構(gòu)FAS系統(tǒng)及仿真軟件的研究與開發(fā)[D].南京:南京航空航天大學.

[73]龔東軍,陳淑玲,王文江,等. 論智能制造的發(fā)展與智能工廠的實踐[J].機械制造,2019,57(2):4.

[74]佚名.《工業(yè)云應用發(fā)展白皮書(2016)》正式發(fā)布[J]. 電信工程技術(shù)與標準化,2017,30(1):1.

[75]何珍.面向智能物料輸送系統(tǒng)的感知互聯(lián)互通技術(shù)研究與實現(xiàn)[D].南京:南京航空航天大學.

[76]孫曉梅.基于物聯(lián)網(wǎng)的軍械倉庫信息管理可視化技術(shù)研究[D].南京:南京理工大學.

[77]孟祥慶.光纖測溫自動報警技術(shù)在信息機房的應用[J].2021(2018-10):82-83.

[78]陳琢.混沌在小信號測量與系統(tǒng)參數(shù)估計中的應用[D].杭州:浙江大學,2003.

[79]崔淑琴.智能壓力傳感器的研究與設計[D].哈爾濱:哈爾濱理工大學.

[80]王茜,董學仁,馬玉貞,等.智能信息處理技術(shù)在石墨纖維熱電偶中的應用[J].儀器儀表用戶,2004,11(2):2.

[81]宮芃成. 淺析智能傳感器及其應用發(fā)展[J]. 通訊世界,2019,26(1):2.

[82]任智,王青明,郭曉金. 無線傳感器網(wǎng)絡中基于最小跳數(shù)路由的節(jié)點休眠算法[J]. 計算機應用,2011,31(1):5.

[83]胡國強,李茵,蔚繼承. 基于6LoWPAN和CoAP的農(nóng)業(yè)環(huán)境信息傳感系統(tǒng)的設計與實現(xiàn)[J]. 現(xiàn)代電子技術(shù),2016,39(23):5.

[84]劉鋒.基于ZigBee的人體生理參數(shù)采集和傳輸系統(tǒng)的設計與實現(xiàn)[D].武漢:華中科技大學,2012.

[85]陳輝皇.多源信息系統(tǒng)中的決策規(guī)則挖掘研究[D].漳州:閩南師范大學.

[86]郭志偉.通用智能人性化排課問題的研究[D].西安:西北大學.

[87]錢亞東.支持協(xié)同設計的知識管理系統(tǒng)研究與開發(fā)[D].杭州:浙江大學,2006.

[88]江濤.自動化技術(shù)在機械設計制造中的應用[J]. 現(xiàn)代制造技術(shù)與裝備,2016(9):168-168.

[89]劉強.基于RRT算法的機械臂運動規(guī)劃技術(shù)研究[D].桂林:桂林電子科技大學.

[90]張莉萍,高英敏,于鎖清. Pro/E和RP技術(shù)在卡板設計中的應用[J]. 機械工程師,2004(8):2.

[91]莊存波,劉檢華,熊輝. 分布式自主協(xié)同制造——一種智能車間運行新模式[J]. 計算機集成制造系統(tǒng),2019,25(8):10.

[92]陶飛,劉蔚然,劉檢華,et al. 數(shù)字孿生及其應用探索[J]. 計算機集成制造系統(tǒng),2018,24(1):18.

[93]Fei, Tao, Jiangfeng, et al. Digital twin-driven product design, manu-facturing and service with big data [J]. The International Journal of Advanced Manufacturing Technology, 2018, 94(9-12):3563-3576.

主站蜘蛛池模板: 个旧市| 长兴县| 揭阳市| 罗山县| 鹿泉市| 盖州市| 福鼎市| 永安市| 江山市| 石家庄市| 突泉县| 古浪县| 梅州市| 安图县| 安龙县| 平阴县| 长春市| 理塘县| 垣曲县| 灵川县| 永嘉县| 城固县| 桐乡市| 安龙县| 沿河| 肥西县| 西安市| 河曲县| 浦城县| 新和县| 准格尔旗| 宝山区| 光泽县| 潜山县| 越西县| 宜良县| 花莲市| 堆龙德庆县| 休宁县| 萝北县| 阿克陶县|