危化品槽罐车运输安全监测信息处理技术研究
|
摘要
以分布式车载多传感器数据采集网络系统和危险化学品泄漏气体传感器标定系统的研发为基础,系统研究了危险化学品运输槽罐车安全状态分析模型、传感器信号的预处理方法、传感器信号间的相关性以及多传感器数据融合的安全状态评估方法。
首先,研制了用于采集槽罐车运行状态和槽罐中危险化学品安全状态参数的数据采集网络系统。该网络系统由车载数据采集终端和远程中央控制中心组成。其中,数据采集终端采集来自安装于槽罐车不同部位的多只传感器的检测信号,其中包括检测槽罐车运行参数的速度、加速度和倾角传感器信号；检测槽罐中危险化学品压力、液位和泄漏气体的传感器信号；检测槽罐车周围环境温、湿度的传感器信号；以及检测非法打开槽罐车进出料口舱门的门开关传感器信号。远程中央控制中心接收并处理由数据采集终端通过无线方式发送而来的车载传感器信号以及通过GPS发送而来的槽罐车位置和速度信号,并综合评估危险化学品运输槽罐车的安全状态及在必要时给出预、报警信息。在远程中央控制中心,根据各传感器特征值的特点,给出了适用于不同传感器的数据预处理方法,并通过线性相关性分析,获得了不同传感器信号与同一特定安全状态之间的线性相关系数,进而提出了利用多传感器信号相关性判断运输危险化学品槽罐车安全状态的方法。
其次,为了掌握危险化学品泄漏气体的性质以及使监测危险化学品是否泄漏的气体传感器的数据准确可靠,设计并组建了一个温湿度可调的、高精度、小批量、动态闭环自动标定系统。该系统由四级杆质谱仪、质量流量计、温湿度控制单元和计算机程控系统等部分组成。其中,温湿度控制单元可根据要求控制测试腔的环境温度为0～100℃、湿度为0～100%RH；计算机程控单元将四级杆质谱仪采集到的数据经最小二乘法处理后控制质量流量计的输出,保证配气精度的同时实现配气过程的闭环控制。采用该系统,对目前工业领域使用量最大的12种危化品气体进行了不同浓度配制试验,利用Agilent6890气相色谱仪对4批共132个气体样本进行了浓度检测,系统的最小相对误差为0.01%,最大相对误差为10.61%。讨论了气体种类、环境温湿度等条件对该系统配气精度的影响。
第三,为了准确的评估槽罐车运输危化品的安全状态,从集合论的角度,研究了不同集合域的安全状态评估算法。具体讨论了康托集下利用主传感器信号评估安全状态的阈值法、变化率阈值法和改进的C4.5决策树算法。其中,阈值法算法简单,但误报率较高；变化率阈值法因增加了变化趋势的判断,误报率显著降低；改进的C4.5决策树算法因具有较好的处理缺省数据和带有噪声数据的能力,误报率更低。为避免因主传感器故障而造成的误报漏报,又建立了基于系统方法论的多传感器数据融合分析模型,研究了基于信号相关函数的模糊综合评价算法和可拓工程算法。其中,模糊综合评价算法中设计了用于度量每个传感器信号与其它各个传感器信号之间相互支撑程度的误差函数和每个传感器信号与特定的危险化学品运输槽罐车安全状态之间隶属关系的模糊综合函数。利用该算法,对一组含有泄漏和正常安全行驶两个状态的数据进行了判断分析,与阈值法相比,危险状态判断准确率为100%。但该算法对各个传感器信号的稳定性要求较高,且对不同安全状态之间各传感器信号的差异性要求显著,所以又研究了可拓工程函数算法。提出了使用层次分析法计算不同传感器信号之间相互支撑程度,使用可拓函数计算每个传感器信号与特定安全状态之间隶属关系的新观点。利用该算法,进行了一级泄漏、二级泄漏和正常安全行驶三个安全状态的判断分析,危险状态判断准确率为100%,并正确给出了当前安全状态的趋势值,为险情预报提供了基础。
最后,为了验证算法的鲁棒性和可靠性,根据实际槽罐车的罐箱体状态,搭建了一个小型罐箱实验系统开展了大量车载实验研究,并参加了863课题合作单位开展的千公里级的陆路和海路考核。结果表明所研究的算法可以实用于危险化学品运输槽罐车的安全状态评估。
The paper focuses on how to evaluate the tank vehicle's safety state for hazardous chemicals transportation. A distributed and multi-sensor monitoring system is designed and a gas sensor calibration system is established, an analytical model for the tank vehicle's safety status is proposed, and muiti-sensor information algrithems are studied to evaluate the safety status.
First of all, a data acquisition network system is designed to collect the running status of the vehicle and the safety parameters of the hazardous chemicals. The network system includes a data acquisition terminal and a remote central control unit. The signals from eight kinds of sensors distributed in different positions are collected in the data acquisition terminal. These sensors can be divided into four sections. The first section is an acceleration sensor and an angle sensor for detecting the tank vehicles'running status. The second section is a gas sensor, a pressure sensor and a liquid level sensor for monitorting the safety status of the hazardous chemiclas in the tank. The third section is a temperature sensor and a humidity sensor for obtaining the ambient environment. The last section is a door switch sensor for an illegal operation. Remote central control unit is used to wirelessly receive data from the data acquisition terminals and evaluat the safety status of the vehicles comprehensively. If a danger occurred, the managers can receive a forecasting or an alarm message. According to the characteristics of the sensors, suitable pre-processing methods are approved for different sensors. And the correlation coefficient between different sensors and a safety status was gained by signals correlations. Furthmore, a new method based on the multi-sensor signal correlation was put forward to detect the vehicle's safety status.
Secondly, the gas sensor is the core element to assess the state of the leakage. In order to guarantee the accuracy of the gas sensor, a gas sensor calibration system is designed and established. This system can configure gas concentration in a closed loop automaticly and continuously with a high precision. And this system can calibrate fourty gas sensors one time. This system consists of a quadrupole mass spectrometer, multiple mass flow controllers, a tempreture and humidity regulator unit and a computer. It can regulate the tempreture range from0to100℃, and the humidity from0to100%RH. Meanwhile, it can control the outputs of the mass flow controllers by dealing with the data from the quadrupole mass spectrometer by the least squares. In order to validate the accuracy of the system,132samples of12kinds of hazardous chemicals gas with different concentrations are sampled. And all these samples were tested by the Agilent6890gas chromatograph.The minimum relative error of the system is0.01%, the maximum relative error was10.61%. According to the results, the relationship between the system accuracy and the ambient environmental temperature humidity conditions is studied.
Thirdly, from the respective of set theory, several evaluation algorithms are studied. A threshold method, a ratio threshold method and a revised C4.5decision tree algorithm are studied.The threshold method is simple with higher false rate. While, the ratio threshold method due to the increment trend judgment decreased the false rate rapidly.And the lowest false rate appeared on the revised C4.5decision tree algorithm with a high ability to deal with missing data and noise data. In order to eliminate the false rate, a novel distributed multi-sensor analysis model is put forward based on the system theory, and a fuzzy comprehensive evaluation algorithm and an extension engineering algorithm are studied. The fuzzy evaluation algorithm consists of a error function and a fuzzy evaluation function. The error function expresses the relation between a sensor and other sensors, and the fuzzy evaluation function displays the relation between a sensor and a safety status. A data set containing leakeage status and normal status is analyzed. Compared with the threshold method, the risk judgment accuracy rate of this algorithm is100%. Owing to the signals limited in strict boundary conditions, the fuzzy comprehensive algorithm only can predict two safety statuses. Extension engineering function algorithm is studied. It consists of an analytic hierarchy process and an extension function. The same data set used in the fuzzy function algorithm is analyzed, risk judgment accuracy rate is also100%. Meanwhile, a tendency of the safety status is given precisely in real time.
Finally, in order to validate the robustness and reliability of the algorithms, a small-scale tin box experiment system is carried out. And a large number of vehicle experimental researches are simulated and tested. Meanwhile, these algorithms are adopted in an exercises launched by the863project team.Research results show that the algorithms can be used to evaluate the safety status in hazardous chemicals transportation by tank vehicles.
首先,研制了用于采集槽罐车运行状态和槽罐中危险化学品安全状态参数的数据采集网络系统。该网络系统由车载数据采集终端和远程中央控制中心组成。其中,数据采集终端采集来自安装于槽罐车不同部位的多只传感器的检测信号,其中包括检测槽罐车运行参数的速度、加速度和倾角传感器信号；检测槽罐中危险化学品压力、液位和泄漏气体的传感器信号；检测槽罐车周围环境温、湿度的传感器信号；以及检测非法打开槽罐车进出料口舱门的门开关传感器信号。远程中央控制中心接收并处理由数据采集终端通过无线方式发送而来的车载传感器信号以及通过GPS发送而来的槽罐车位置和速度信号,并综合评估危险化学品运输槽罐车的安全状态及在必要时给出预、报警信息。在远程中央控制中心,根据各传感器特征值的特点,给出了适用于不同传感器的数据预处理方法,并通过线性相关性分析,获得了不同传感器信号与同一特定安全状态之间的线性相关系数,进而提出了利用多传感器信号相关性判断运输危险化学品槽罐车安全状态的方法。
其次,为了掌握危险化学品泄漏气体的性质以及使监测危险化学品是否泄漏的气体传感器的数据准确可靠,设计并组建了一个温湿度可调的、高精度、小批量、动态闭环自动标定系统。该系统由四级杆质谱仪、质量流量计、温湿度控制单元和计算机程控系统等部分组成。其中,温湿度控制单元可根据要求控制测试腔的环境温度为0～100℃、湿度为0～100%RH；计算机程控单元将四级杆质谱仪采集到的数据经最小二乘法处理后控制质量流量计的输出,保证配气精度的同时实现配气过程的闭环控制。采用该系统,对目前工业领域使用量最大的12种危化品气体进行了不同浓度配制试验,利用Agilent6890气相色谱仪对4批共132个气体样本进行了浓度检测,系统的最小相对误差为0.01%,最大相对误差为10.61%。讨论了气体种类、环境温湿度等条件对该系统配气精度的影响。
第三,为了准确的评估槽罐车运输危化品的安全状态,从集合论的角度,研究了不同集合域的安全状态评估算法。具体讨论了康托集下利用主传感器信号评估安全状态的阈值法、变化率阈值法和改进的C4.5决策树算法。其中,阈值法算法简单,但误报率较高；变化率阈值法因增加了变化趋势的判断,误报率显著降低；改进的C4.5决策树算法因具有较好的处理缺省数据和带有噪声数据的能力,误报率更低。为避免因主传感器故障而造成的误报漏报,又建立了基于系统方法论的多传感器数据融合分析模型,研究了基于信号相关函数的模糊综合评价算法和可拓工程算法。其中,模糊综合评价算法中设计了用于度量每个传感器信号与其它各个传感器信号之间相互支撑程度的误差函数和每个传感器信号与特定的危险化学品运输槽罐车安全状态之间隶属关系的模糊综合函数。利用该算法,对一组含有泄漏和正常安全行驶两个状态的数据进行了判断分析,与阈值法相比,危险状态判断准确率为100%。但该算法对各个传感器信号的稳定性要求较高,且对不同安全状态之间各传感器信号的差异性要求显著,所以又研究了可拓工程函数算法。提出了使用层次分析法计算不同传感器信号之间相互支撑程度,使用可拓函数计算每个传感器信号与特定安全状态之间隶属关系的新观点。利用该算法,进行了一级泄漏、二级泄漏和正常安全行驶三个安全状态的判断分析,危险状态判断准确率为100%,并正确给出了当前安全状态的趋势值,为险情预报提供了基础。
最后,为了验证算法的鲁棒性和可靠性,根据实际槽罐车的罐箱体状态,搭建了一个小型罐箱实验系统开展了大量车载实验研究,并参加了863课题合作单位开展的千公里级的陆路和海路考核。结果表明所研究的算法可以实用于危险化学品运输槽罐车的安全状态评估。
The paper focuses on how to evaluate the tank vehicle's safety state for hazardous chemicals transportation. A distributed and multi-sensor monitoring system is designed and a gas sensor calibration system is established, an analytical model for the tank vehicle's safety status is proposed, and muiti-sensor information algrithems are studied to evaluate the safety status.
First of all, a data acquisition network system is designed to collect the running status of the vehicle and the safety parameters of the hazardous chemicals. The network system includes a data acquisition terminal and a remote central control unit. The signals from eight kinds of sensors distributed in different positions are collected in the data acquisition terminal. These sensors can be divided into four sections. The first section is an acceleration sensor and an angle sensor for detecting the tank vehicles'running status. The second section is a gas sensor, a pressure sensor and a liquid level sensor for monitorting the safety status of the hazardous chemiclas in the tank. The third section is a temperature sensor and a humidity sensor for obtaining the ambient environment. The last section is a door switch sensor for an illegal operation. Remote central control unit is used to wirelessly receive data from the data acquisition terminals and evaluat the safety status of the vehicles comprehensively. If a danger occurred, the managers can receive a forecasting or an alarm message. According to the characteristics of the sensors, suitable pre-processing methods are approved for different sensors. And the correlation coefficient between different sensors and a safety status was gained by signals correlations. Furthmore, a new method based on the multi-sensor signal correlation was put forward to detect the vehicle's safety status.
Secondly, the gas sensor is the core element to assess the state of the leakage. In order to guarantee the accuracy of the gas sensor, a gas sensor calibration system is designed and established. This system can configure gas concentration in a closed loop automaticly and continuously with a high precision. And this system can calibrate fourty gas sensors one time. This system consists of a quadrupole mass spectrometer, multiple mass flow controllers, a tempreture and humidity regulator unit and a computer. It can regulate the tempreture range from0to100℃, and the humidity from0to100%RH. Meanwhile, it can control the outputs of the mass flow controllers by dealing with the data from the quadrupole mass spectrometer by the least squares. In order to validate the accuracy of the system,132samples of12kinds of hazardous chemicals gas with different concentrations are sampled. And all these samples were tested by the Agilent6890gas chromatograph.The minimum relative error of the system is0.01%, the maximum relative error was10.61%. According to the results, the relationship between the system accuracy and the ambient environmental temperature humidity conditions is studied.
Thirdly, from the respective of set theory, several evaluation algorithms are studied. A threshold method, a ratio threshold method and a revised C4.5decision tree algorithm are studied.The threshold method is simple with higher false rate. While, the ratio threshold method due to the increment trend judgment decreased the false rate rapidly.And the lowest false rate appeared on the revised C4.5decision tree algorithm with a high ability to deal with missing data and noise data. In order to eliminate the false rate, a novel distributed multi-sensor analysis model is put forward based on the system theory, and a fuzzy comprehensive evaluation algorithm and an extension engineering algorithm are studied. The fuzzy evaluation algorithm consists of a error function and a fuzzy evaluation function. The error function expresses the relation between a sensor and other sensors, and the fuzzy evaluation function displays the relation between a sensor and a safety status. A data set containing leakeage status and normal status is analyzed. Compared with the threshold method, the risk judgment accuracy rate of this algorithm is100%. Owing to the signals limited in strict boundary conditions, the fuzzy comprehensive algorithm only can predict two safety statuses. Extension engineering function algorithm is studied. It consists of an analytic hierarchy process and an extension function. The same data set used in the fuzzy function algorithm is analyzed, risk judgment accuracy rate is also100%. Meanwhile, a tendency of the safety status is given precisely in real time.
Finally, in order to validate the robustness and reliability of the algorithms, a small-scale tin box experiment system is carried out. And a large number of vehicle experimental researches are simulated and tested. Meanwhile, these algorithms are adopted in an exercises launched by the863project team.Research results show that the algorithms can be used to evaluate the safety status in hazardous chemicals transportation by tank vehicles.
引文
[1]Lin Wensheng, Zhang Na, Gu Anzhong. LNG (liquefied natural gas):A necessary part in China's future energy infrastructure [J]. Energy,2010,35(11):4383-4391.
[2]David A. Wood.A review and outlook for the global LNG trade [J].Journal of natural gas science and engineering,2012,9:16-27.
[3]高贫,刘大斌,倪欧琪.危险化学品管理现状及其分类的一般程序[J].爆破器材,2004,33(12)：116-120.
[4]张丽,柏萍.2006-2007年危险化学品运输事故研究[J].中国安全生产科学技,2008,4(6)：74-78.
[5]S. J Lee, M. H. Kim, D. H. Lee, et al. The effects of LNG-tank sloshing on the global motions of LNG carriers [J], Ocean engineering,2007:10-20.
[6]Perri Z Ruckart,Wendy A Wattigney,Wendy E Kaye. Risk factors for acute chemical releases with public health consequences:Hazardous substances emergency events surveillance in the U.S.,1996-2001 [J]. Environment health,2004,10:dok10.1186/1476-069X-3-10.
[7]Satish Kumar, Hyouk-Tae Kwon, Kwang-Ho Choi,et al. Current status and future projections of LNG demand and supplies:A global prospective [J]. Energy policy,2011,39(7):4097-4104.
[8]刘倩.孝感市危险化学品监管系统的设计研究[D].武汉：中国地质大学,2010.
[9]Phil Cleaver, Mike Johnson, Ben Hob. A summary of some experimental data on LNG safety [J]. Journal of hazardous materials,2007 (140):429-438.
[10]Ronald P. Koopman, Donald L. Ermak. Lessons learned from LNG safety research [J]. Journal of hazardous materials,2007 (140):412-428.
[11]Robin Pitblado, John Baik, Vijay Raghunathan. LNG decision making approaches compared [J]. Journal of hazardous materials,2006(130):148-154.
[12]Jerry Havens, James Venart. Fire performance of LNG carriers insulated with polystyrene foam [J]. Journal of hazardous materials,2008. doi:10.1016/j.jhazmat.2008.01.094.
[13]Arup Das, A.K. Gupta, T.N. Mazumder. A comprehensive risk assessment framework for offsite transportation of inflammable hazardous waste [J]. Journal of hazardous materials,2012,227-228:88-96.
[14]Susanna Dorigoni.Sergio Portatadino. LNG development across Europe:Infrastructural and regulatory analysis [J]. Energy policy,2008, doi:10.1016/j.enpol.2008.05.015.
[15]Niels Peter H(?)j, Wolfgang Kroger.Risk analyses of transportation on road and railway from a European perspective [J]. Safety science,2002,40,(1-4):337-357.
[16]Crainic dor Gabriel, Gilbert Laporte. Planning models for freight transportation[J]. European Journal of Operational Research,1997,97(3):409-438.
[17]江金华,弓燕舞.液化天然气罐式集装箱公路运输的分析[J].煤气与热力,2004,24(11)：644-646.
[18]孙代平.一种危险化学品罐箱/槽车的实时监测系统[D].大连：大连理工大学,2006.
[19]陈毅.危险化学品运输罐箱状态监测算法的研究[D].大连：大连理工大学,2009.
[20]彭建华.液化天然气罐式集装箱水路运输试验及分析[J].中国航海,2007年第2期：52-54.
[21]危险化学品汽车运输安全监控系统通用规范[S].中华人们共和国安全生产行业标准AQ2003-2005.国家安全生产监督管理总局.
[22]魏利军,多英全,吴宗之.城市重大危险源安全规划方法及程序研究[J].中国安全生产科学技术,2005,1(1)：15-20.
[23]Jerry Havens, Tom Spicer. United states regulations for sitting LNG terminals:problems and potential [J]. Journal of hazardous materials,2007 (140):439-443.
[24]钱新.世界各国危化品运输事故应急救援组织及特点[J].现代职业安全,第97期,2009年9月：70-71.
[25]Wang Jie. A study on technical development on LNG vessel [J]. system, man and cybernetic, 2009:4936-4939.
[26]Young Ho Yu, Bu Gi Kim, Dai Gil Lee.Cryogenic reliability of the sandwich insulation board for LNG ship [J].Composite Structures,2013,95:547-556.
[27]王冰,陈学东,王国平.大型低温LNG储罐设计与建造技术的新进展[J].天然气工业.第30卷第5期,2010年5月：1-5.
[28]Roberto Bubbico, Sergio Di Cave, Barbara Mazzarotta. Risk analysis for road and rail transport of hazardous materials:a GIS approach [J].Journal of loss prevention in the process industries, 2004,17(6):483-488.
[29]F. L. Pincinato, P.S. Riedel, J.C.C. Milanelli. Modelling an expert GIS system based on knowledge to evaluate oil spill environmental sensitivity [J]. Ocean & coastal management, 2009,52(9):479-486.
[30]Jiang Jiping, Wang Peng, Lung Wu-seng, et al. A GIS-based generic real-time risk assessment framework and decision tools for chemical spills in the river basin [J].Journal of hazardous materials,2012(227-228):280-291.
[31]辛春林,王金连.危险化学品运输事故历史数据研究综述[J].中国安全科学学报,2012,22(7)：89-94.
[32]He Gui-zhen,Zhang Lei.Lu Yong-long,et al. Managing major chemical accidents in China: towards effective risk information [J].Journal of hazardous materials,2011,187(1/3):171-181.
[33]M. Khalil, M.A. Abdou, M.S. Mansour, et al. A cascaded fuzzy-LOPA risk assessment model applied in natural gas industry [J]. Journal of loss prevention in the process industries,2012, 25(6):877-882.
[34]Mario Miana, Rafael del Hoyo a, Vega Rodrigalvarez, et al. Calculation models for prediction of liquefied natural gas (LNG) ageing during ship transportation [J]. Applied energy.2010,87(5): 1687-1700.
[35]Liu Li-ping, Li Shu-xia, Fan Ti-jun, et al. Transportation risk assessment of chemical industry supply chain based on A dual model [J]. Procedia environmental sciences,2011,11(A): 393-397.
[36]Ren Changing, Yuan Xiongjun. Study on emergency response rank mode of flammable and explosive hazardous materials road transportation [J]. Procedia engineering,2012,45:830-835.
[37]P.K. Marhavilas, D.E. Koulouriotis.Developing a new alternative risk assessment framework in the work sites by including a stochastic and a deterministic process:A case study for the Greek public electric power provider[J].Safety Science,2012,50(3):448-462.
[38]R.Ohba, A.Kouchi, T.Haara, et al. Validation of heavy and light gas dispersion models for the safety analysis of LNG tank [J]. Journal of loss prevention in the process industries. 2004:325-337.
[39]Chen Jie, Zeng shun-peng. Numerical Simulation Research for thermo-responsive behavior of LNG spherical tank under the fire environment [C]. Apperceiving computing and intelligence analysis,2010:221-224.
[40]Arun Parihar, Charles Vergara, J. Keith Clutter. Methodology for consequence analysis of LNG releases at deepwater port facilities [J]. Safety Science,2011,49(5):686-694.
[41]M. Siddiqui, S. Jayanti, T. Swaminathan. CFD analysis of dense gas dispersion in indoor environment for risk assessment and risk mitigation [J]. Journal of hazardous materials,2012, (209-210):177-185.
[42]Yacine Zellouf, Benoit Portannier. First step in optimizing LNG storages for offshore terminals [J].Journal of natural gas science and engineering,2011,3(5):582-590.
[43]Xie anchang, Lu wei, Luca Quadrifoglio,et al. A multimodal location and routing model for hazardous materials transportation [J].Journal of Hazardous Materials,2012, (227-228): 135-141.
[44]Arye Nehorai, Boaz Porat, Eytan Paldi. Detection and localization of vapor-emitting sources [J]. IEEE transactions on signal processing,1995,43(1):243-254.
[45]R. Andrew Russell, David Thiel. Reimundo Deveza, et al. A robotic system to locate hazardous chemical leaks [C]. IEEE International conference on robotics and automation,1995:556-561.
[46]E. Topuz, I. Talinli, E. Aydin. Integration of environmental and human health risk assessment for industries using hazardous materials:A quantitative multi criteria approach for environmental decision makers [J], Environment International,2011,37 (2):393-403.
[47]Han Z.Y, Weng W.G. Comparison study on qualitative and quantitative risk assessment methods for urban natural gas pipeline network [J]. Journal of hazardous materials,2011, 189(1-2):509-518
[48]翁帮华,银小兵,向启贵.SAFETY定量风险分析软件在石油天然气开发风险评估中的应用[J].石油与天然气化工,2007,36(6)：524-527.
[49]Unsihuay-Vila C, Marangon-Lima J.W, et al. A model to long-term, multiarea, multistage, and integrated expansion planning of electricity and natural gas systems [J]. Power system,2010. 25(2):1154-1168.
[50]Maryam Kalantarnia, Faisal Khan, Kelly Hawboldt. Dynamic risk assessment using failure assessment and Bayesian theory [J].Journal of loss prevention in the process industries.2009,22 (5):600-606.
[51]Hans J. Pasman, William J. Rogers. Risk assessment by means of Bayesian networks:A comparative study of compressed and liquefied H2 transportation and tank station risks [J].International journal of hydrogen energy,2012,37(22):17415-17425.
[52]刘凌燕,庞奇志,宋秀江.液氧储罐爆炸事故树分析[J].工业安全与环保,2005,31(1)：49-51.
[53]Luis Castillo, Carlos A. Dorao. Decision-making on liquefied natural gas (LNG) projects using game theory [C].Computational intelligence in multicriteria decision-making,2011:60-66.
[54]Zhao Rui, Gareth Neighbour, Jiaojie Han, et al.Using game theory to describe strategy selection for environmental risk and carbon emissions reduction in the green supply chain [J].Journal of loss prevention in the process industries,2012,25(6):927-936.
[55]Feng Shimin, Guan Qing, Xu Sheng,et al. Human tracking based on mean shift and Kalman Filter [C].2009 International conference on artificial intelligence and computational intelligence. 2009:518-2-522.
[56]Amir Babaeian, Saeed Rastegar, Mojtaba Bandarabadi, et al. Mean shift-Based object tracking with multiple features [C].41st Southeastern symposium on system theory.2009,3:68-72.
[57]马小明,吴晓曦.LNG储罐火灾后果分析[J].中山大学学报,2007,27(2)：105-108.
[58]朱小红,张慧明,陆愈实等.爆炸与中毒模型在液氨储罐安全评价中的应用[J].安全与环境工程,2007,14(3)：100-103.
[59]Adam S. Markowski, M. Sam Mannan. Fuzzy logic for piping risk assessment [J].Journal of loss prevention in the process industries,2009,22(6):921-927.
[60]Chee Beng Goh, Chi Bun Ching, Reginald Tan. Risk analysis for the road transportation of hazardous chemicals in Singapore - a methodology [J].Journal of loss prevention in the process industries,1995,8(1):35-39.
[61]Zhang Jiang-hua, Zhao Lai-jun. Risk analysis of dangerous chemicals transportation [J].Systems engineering-theory & practice,2007,27(12):117-122.
[62]Luciano Fabbri, Sergio Contini. Benchmarking on the evaluation of major accident-related risk assessment [J]. Journal of hazardous materials,2009,162 (2-3):1465-1476.
[63]张洪泉,乔英杰,范茂军.基于Y-A1203膜微加工煤油传感器研究[J].传感器与微系统,2012,31(3)：43-45,49.
[64]刘丛宁,施云波,修德斌,等.面向氯气安全监测的无线传感器网络系统[J].仪表技术与传感器,2012,1：46-48.
[65]V. Malyshev, A.V. Pislyakov. Investigation of gas-sensitivity of sensor structures to carbon monoxide in a wide range of temperature, concentration and humidity of gas medium [J]. Sensors and Actuators B,2007, B 123:71-81.
[66]Kurup, Pradeep U. An electronic nose for detecting hazardous chemicals and explosives [C]. technologies for homeland security,2008:144-149.
[67]Frank C. DeLucia, Jr., Alan C. Samuels, Russell S. Harmon, et al. Laser-induced breakdown spectroscopy (LIBS):A promising versatile chemical sensor technology for hazardous material detection [J]. IEEE sensors journal,2005,5(4):681-690.
[68]Anns-erik, Hildegard, Jander. A test system for gas sensors. Sensors and Actuators B [J].1995, B23:163-172.
[69]Malyshe V, Pislyakov. Investigation of gas-sensitivity of sensor structures to carbon monoxide in a wide range of temperature, concentration and humidity of gas medium [J]. Sensors and Actuators B.2007,B 123:71-81.
[70]方米华,刘骥,魏利军等.危险品运输车辆监控预警系统设计与开发[J].中国安全科学学报,2008,18(5)：109-115.
[71]王敏.危险品运输安全评价系统指标,中国物流与采购[J],2012(7)：68-69.
[72]周受钦,王浩铭.中集集团完成智能罐箱多式联运应用测试.集装箱化[J],2008,19(5)：24-25.
[73]张永生,段战归,周受钦,等.危化品运输设备状态实时监测系统开发[J].交通与计算机,2007,25(6)：106-108.
[74]孙代平,唐祯安,魏广芬,等.一种液化石油气罐箱/槽罐车的实时探测器[J].测控技术,2007,26(6)：15-39.
[75]Li M Q, Chen X, Liu J H. A practical testing system for gas sensor array [J]. Proceedings of the 2008 IEEE international conference on information and automation.2008:1812-1816.
[76]Sun guo, Song Rui, He Shiwei, et al. Mixed transportation network design based on immune clone annealing algorithm [J]. Journal of transportation systems engineering and information technology,2009,9(3):103-108.
[77]A. Batzias, C.G. Siontorou, P.-M.P. Spanidis. Designing a reliable leak bio-detection system for natural gas pipelines [J]. Journal of hazardous materials,2011,186(1):35-58.
[78]陈毅,唐祯安,余隽等.倾斜姿态下智能罐箱液体泄漏状态监测方法[J].仪表技术与传感器.2010(1)：98-100.
[79]陈毅,唐祯安,余隽等.一种危化品运输智能罐箱运行状态监测方法：中国,200910304657.6[P].2011,04.
[80]余隽,唐祯安,黄正兴等.一种用于可燃气体探测器的基线漂移自适应补偿探测方法：中国,200910010072.3[P].2010.10.
[81]Dasarathy B. Decision Fusion [M].Washington:IEEE Computer Society Press,1994.
[82]韩增奇,于俊杰,李宁霞等.信息融合技术综述[J].情报杂志,2010,29：110-114.
[83]蔡莉莉.基于数据融合的语音情感分析与识别[D].南京：东南大学,2005.
[84]杨秀雷.自主推进式猎雷声纳系统体系结构研究[D].哈尔滨：哈尔滨工程大学,2007.
[85]Kaeye Dastner, Thomas Kausch, Felix Opitz. An object oriented development suite for data fusion:design, generation, simulation and testing [C]. Information fusion,2007:1-8.
[86]沙春哲,施云波,修德斌,等.气体传感器长期稳定性智能检测系统[J].电子测量技术,第33卷第6期,2010：102-106.
[87]Tschuncky, Peter, Kiesele, et al.Gas-measuring system with gas sensor and gas generator [P]. American:20060230813.
[88]宋委远.基于传感器阵列的混合气体测试系统研究[D].武汉：华中科技大学,2006.
[89]赵建华,兰华永,陈滋健.基于质量流量控制器的多组分动态配气系统研究[J].自动化仪表,2008年第29卷第2期：44-48.
[90]张鑫，李冬梅,黄元庆.基于LabVIEW的阵列式传感器数据采集系统[J].仪器仪表学报,第27卷第6期增刊,2006.6：1439-1401.
[91]刘洪武,陈德桂,李志鹏.具有图形组态功能的传感器阵列测试系统[J].仪器仪表学报,第26卷第8期,2005：876-880.
[92]Bruce Eckel. Thinking in JAVA [M].出版社：机械工业出版社，2004.
[93]刘冲,吴成百,张文涛等.微小型燃料电池测试系统的气体流量控制[J],光学精密工程,2008年第14卷第5期：840-846.
[94]Liu C.H,Wu CH B,Zhang W T,et al. Gas flux control of testing system for micro/miniature fuel cell [J].Optics and precision engineering,2008,14(5):840-846.
[95]Buckley M.E. Process control in the semiconductor manufacturing environment using a high pressure quad rupole mass spectrometer [J]. Semiconductor processing quality through measurement.1994:211-217.
[96]李芳,张玉广,陆平等.四极质谱仪在空气中七种常量微量组分在线监测中的应用[J].分析仪器,2007年第2期：20-22.
[97]Savadkouhi J. Reliability considerations for gas delivery components [J].Advanced semiconductor manufacturing conference and workshop, USA:IEEE/SEMI,2003:255-261.
[98]刘小娟.复合分子筛催化热解生物质制生物油的研究[D].杭州：浙江工业大学,201].[99]宇传华SPSS与统计分析(含光盘)[M].出版社：电子工业出版社,2007.
[100]黄志坚.工程系统概论——系统论在工程技术中的应用[M].出版社：北京大学出版社,2010.
[101]中国石化集团上海工程有限公司等.化学化工物性数据手册—有机卷)[M],出版社：化学工业出版社,2009.
[102]Thomas Jech.集合论(英文版)[M],出版社：世界图书出版公司,2007.
[103]Explosive gases with electrical equipment part 14:the dangerous site classification [S]. GB3836.14-2000.
[104]Explosive gases with electrical equipment part 1:general requirements [S]. GB3836.1-2000.
[105]Indrek S. Wichman. Material flammability, combustion, toxicity and fire hazard in transportation [J]. Progress in energy and combustion science,2003,29(3):247-299.
[106]常用危险化学品的分类及标志[S].中华人们共和国国家标准GB13690-92,国家技术监督局,1992.
[107]Kanaskar, Nitin,Seker,et al. Dynamical system theory for the detection of anomalous behavior in computer programs [J]. Systems, man, and cybernetics, Part C:applications and reviews,2012, 42(6):1579-1589.
[108]Wei Liang, Jinqiu Hu, Laibin Zhang, Cunjie Guo, Weipeng Lin.Assessing and classifying risk of pipeline third-party interference based on fault tree and SOM [J]. Engineering applications of artificial intelligence,2012,25(3):594-608.
[109]Ruggieri, Salvatore. Efficient C4.5 [classification algorithm] [M], Knowledge and Data Engineering,2002,14(2):438-444.
[110]Jose M. Molina, Jes us Garca, Francisco J. Jimenez, et al. Surveillance multisensor management with fuzzy evaluation of sensor task priorities [J]. Engineering applications of artificial intelligence.2002 (15):511-527.
[111]Adam S. Markowski, M. Sam Mannan, Agata Kotynia, et al. Application of fuzzy logic to explosion risk assessment [J]. Journal of Loss Prevention in the Process Industries,2011,24(6): 780-790.
[112]A. Azadeh, M. Saberi, S.F. Ghaderi,et al. Improved estimation of electricity demand function by integration of fuzzy system and data mining approach [J]. Energy Conversion and Management.2008:2165-2177.
[113]Toms□ Kroupa. Filters in fuzzy class theory [J]. Fuzzy Sets and Systems.159 (2008):1773-1787.
[114]Jose M. Molina, Jesus Garcia, Francisco J. Jimenez,et al. Surveillance multisensor management with fuzzy evaluation of sensor task priorities[J].engineering applications of artificial intelligense,15(2002):511-527.
[115]潘东,金以慧.可拓控制的探索与研究[J].控制理论与应用.1996,13(3)：305-311.
[116]Liang-Teh Lee,Shin-Tsung Lee,Jui-Chih Chang. An extenics-based dynamic resource adjustment for the virtual machine in cloud computing environment [C]. Fourth international conference on ubi-media computing, DOI10.1109/U-MEDIA.2011.33.
[117]Lee Liang-Te, Tao De-Fu, Tseng Chia-Ying, et al. An extenics-based load balancing mechanism for distributed computing systems [C], Proceedings of/€€E TENCON02, 2011:371-374.
[118]Peng Shuai-ying, Li Guang-jie, Meng Fan-qi, et al. Application of extenics theory in hazard assessment of debris flow based on comprehensive weighting of subjective and objective methods [C]. Consumer electronics, communications and networks,2008:2966-2969.
[119]Shu Hong-chun, Peng Shi-xin, Zhao Xing-bing. Integration of multi-algorithm for single-phase fault detection in distribution system with Arc suppression coil grounding using extenics [C]. Electric utility deregulation and restructuring and power technologies. DRPT2008. (4): 2111-2114.
[120]Ju Yi-jing, Yu Yong-quan, Ju Guang-ming, et al. Extension set and restricting qualifications of matter-elements'extension [C]. Proceedings of the third international conference on information technology and applications (ICITA'05),2005:1-4.
[121]J.W Jin; L Rothrock, P.L McDermott et al. Using the analytic hierarchy process to examine judgment consistency in a complex multi-attribute task systems [J]. Man and cybernetics, Part A: systems and humans,2010:1105-1115.
[2]David A. Wood.A review and outlook for the global LNG trade [J].Journal of natural gas science and engineering,2012,9:16-27.
[3]高贫,刘大斌,倪欧琪.危险化学品管理现状及其分类的一般程序[J].爆破器材,2004,33(12)：116-120.
[4]张丽,柏萍.2006-2007年危险化学品运输事故研究[J].中国安全生产科学技,2008,4(6)：74-78.
[5]S. J Lee, M. H. Kim, D. H. Lee, et al. The effects of LNG-tank sloshing on the global motions of LNG carriers [J], Ocean engineering,2007:10-20.
[6]Perri Z Ruckart,Wendy A Wattigney,Wendy E Kaye. Risk factors for acute chemical releases with public health consequences:Hazardous substances emergency events surveillance in the U.S.,1996-2001 [J]. Environment health,2004,10:dok10.1186/1476-069X-3-10.
[7]Satish Kumar, Hyouk-Tae Kwon, Kwang-Ho Choi,et al. Current status and future projections of LNG demand and supplies:A global prospective [J]. Energy policy,2011,39(7):4097-4104.
[8]刘倩.孝感市危险化学品监管系统的设计研究[D].武汉：中国地质大学,2010.
[9]Phil Cleaver, Mike Johnson, Ben Hob. A summary of some experimental data on LNG safety [J]. Journal of hazardous materials,2007 (140):429-438.
[10]Ronald P. Koopman, Donald L. Ermak. Lessons learned from LNG safety research [J]. Journal of hazardous materials,2007 (140):412-428.
[11]Robin Pitblado, John Baik, Vijay Raghunathan. LNG decision making approaches compared [J]. Journal of hazardous materials,2006(130):148-154.
[12]Jerry Havens, James Venart. Fire performance of LNG carriers insulated with polystyrene foam [J]. Journal of hazardous materials,2008. doi:10.1016/j.jhazmat.2008.01.094.
[13]Arup Das, A.K. Gupta, T.N. Mazumder. A comprehensive risk assessment framework for offsite transportation of inflammable hazardous waste [J]. Journal of hazardous materials,2012,227-228:88-96.
[14]Susanna Dorigoni.Sergio Portatadino. LNG development across Europe:Infrastructural and regulatory analysis [J]. Energy policy,2008, doi:10.1016/j.enpol.2008.05.015.
[15]Niels Peter H(?)j, Wolfgang Kroger.Risk analyses of transportation on road and railway from a European perspective [J]. Safety science,2002,40,(1-4):337-357.
[16]Crainic dor Gabriel, Gilbert Laporte. Planning models for freight transportation[J]. European Journal of Operational Research,1997,97(3):409-438.
[17]江金华,弓燕舞.液化天然气罐式集装箱公路运输的分析[J].煤气与热力,2004,24(11)：644-646.
[18]孙代平.一种危险化学品罐箱/槽车的实时监测系统[D].大连：大连理工大学,2006.
[19]陈毅.危险化学品运输罐箱状态监测算法的研究[D].大连：大连理工大学,2009.
[20]彭建华.液化天然气罐式集装箱水路运输试验及分析[J].中国航海,2007年第2期：52-54.
[21]危险化学品汽车运输安全监控系统通用规范[S].中华人们共和国安全生产行业标准AQ2003-2005.国家安全生产监督管理总局.
[22]魏利军,多英全,吴宗之.城市重大危险源安全规划方法及程序研究[J].中国安全生产科学技术,2005,1(1)：15-20.
[23]Jerry Havens, Tom Spicer. United states regulations for sitting LNG terminals:problems and potential [J]. Journal of hazardous materials,2007 (140):439-443.
[24]钱新.世界各国危化品运输事故应急救援组织及特点[J].现代职业安全,第97期,2009年9月：70-71.
[25]Wang Jie. A study on technical development on LNG vessel [J]. system, man and cybernetic, 2009:4936-4939.
[26]Young Ho Yu, Bu Gi Kim, Dai Gil Lee.Cryogenic reliability of the sandwich insulation board for LNG ship [J].Composite Structures,2013,95:547-556.
[27]王冰,陈学东,王国平.大型低温LNG储罐设计与建造技术的新进展[J].天然气工业.第30卷第5期,2010年5月：1-5.
[28]Roberto Bubbico, Sergio Di Cave, Barbara Mazzarotta. Risk analysis for road and rail transport of hazardous materials:a GIS approach [J].Journal of loss prevention in the process industries, 2004,17(6):483-488.
[29]F. L. Pincinato, P.S. Riedel, J.C.C. Milanelli. Modelling an expert GIS system based on knowledge to evaluate oil spill environmental sensitivity [J]. Ocean & coastal management, 2009,52(9):479-486.
[30]Jiang Jiping, Wang Peng, Lung Wu-seng, et al. A GIS-based generic real-time risk assessment framework and decision tools for chemical spills in the river basin [J].Journal of hazardous materials,2012(227-228):280-291.
[31]辛春林,王金连.危险化学品运输事故历史数据研究综述[J].中国安全科学学报,2012,22(7)：89-94.
[32]He Gui-zhen,Zhang Lei.Lu Yong-long,et al. Managing major chemical accidents in China: towards effective risk information [J].Journal of hazardous materials,2011,187(1/3):171-181.
[33]M. Khalil, M.A. Abdou, M.S. Mansour, et al. A cascaded fuzzy-LOPA risk assessment model applied in natural gas industry [J]. Journal of loss prevention in the process industries,2012, 25(6):877-882.
[34]Mario Miana, Rafael del Hoyo a, Vega Rodrigalvarez, et al. Calculation models for prediction of liquefied natural gas (LNG) ageing during ship transportation [J]. Applied energy.2010,87(5): 1687-1700.
[35]Liu Li-ping, Li Shu-xia, Fan Ti-jun, et al. Transportation risk assessment of chemical industry supply chain based on A dual model [J]. Procedia environmental sciences,2011,11(A): 393-397.
[36]Ren Changing, Yuan Xiongjun. Study on emergency response rank mode of flammable and explosive hazardous materials road transportation [J]. Procedia engineering,2012,45:830-835.
[37]P.K. Marhavilas, D.E. Koulouriotis.Developing a new alternative risk assessment framework in the work sites by including a stochastic and a deterministic process:A case study for the Greek public electric power provider[J].Safety Science,2012,50(3):448-462.
[38]R.Ohba, A.Kouchi, T.Haara, et al. Validation of heavy and light gas dispersion models for the safety analysis of LNG tank [J]. Journal of loss prevention in the process industries. 2004:325-337.
[39]Chen Jie, Zeng shun-peng. Numerical Simulation Research for thermo-responsive behavior of LNG spherical tank under the fire environment [C]. Apperceiving computing and intelligence analysis,2010:221-224.
[40]Arun Parihar, Charles Vergara, J. Keith Clutter. Methodology for consequence analysis of LNG releases at deepwater port facilities [J]. Safety Science,2011,49(5):686-694.
[41]M. Siddiqui, S. Jayanti, T. Swaminathan. CFD analysis of dense gas dispersion in indoor environment for risk assessment and risk mitigation [J]. Journal of hazardous materials,2012, (209-210):177-185.
[42]Yacine Zellouf, Benoit Portannier. First step in optimizing LNG storages for offshore terminals [J].Journal of natural gas science and engineering,2011,3(5):582-590.
[43]Xie anchang, Lu wei, Luca Quadrifoglio,et al. A multimodal location and routing model for hazardous materials transportation [J].Journal of Hazardous Materials,2012, (227-228): 135-141.
[44]Arye Nehorai, Boaz Porat, Eytan Paldi. Detection and localization of vapor-emitting sources [J]. IEEE transactions on signal processing,1995,43(1):243-254.
[45]R. Andrew Russell, David Thiel. Reimundo Deveza, et al. A robotic system to locate hazardous chemical leaks [C]. IEEE International conference on robotics and automation,1995:556-561.
[46]E. Topuz, I. Talinli, E. Aydin. Integration of environmental and human health risk assessment for industries using hazardous materials:A quantitative multi criteria approach for environmental decision makers [J], Environment International,2011,37 (2):393-403.
[47]Han Z.Y, Weng W.G. Comparison study on qualitative and quantitative risk assessment methods for urban natural gas pipeline network [J]. Journal of hazardous materials,2011, 189(1-2):509-518
[48]翁帮华,银小兵,向启贵.SAFETY定量风险分析软件在石油天然气开发风险评估中的应用[J].石油与天然气化工,2007,36(6)：524-527.
[49]Unsihuay-Vila C, Marangon-Lima J.W, et al. A model to long-term, multiarea, multistage, and integrated expansion planning of electricity and natural gas systems [J]. Power system,2010. 25(2):1154-1168.
[50]Maryam Kalantarnia, Faisal Khan, Kelly Hawboldt. Dynamic risk assessment using failure assessment and Bayesian theory [J].Journal of loss prevention in the process industries.2009,22 (5):600-606.
[51]Hans J. Pasman, William J. Rogers. Risk assessment by means of Bayesian networks:A comparative study of compressed and liquefied H2 transportation and tank station risks [J].International journal of hydrogen energy,2012,37(22):17415-17425.
[52]刘凌燕,庞奇志,宋秀江.液氧储罐爆炸事故树分析[J].工业安全与环保,2005,31(1)：49-51.
[53]Luis Castillo, Carlos A. Dorao. Decision-making on liquefied natural gas (LNG) projects using game theory [C].Computational intelligence in multicriteria decision-making,2011:60-66.
[54]Zhao Rui, Gareth Neighbour, Jiaojie Han, et al.Using game theory to describe strategy selection for environmental risk and carbon emissions reduction in the green supply chain [J].Journal of loss prevention in the process industries,2012,25(6):927-936.
[55]Feng Shimin, Guan Qing, Xu Sheng,et al. Human tracking based on mean shift and Kalman Filter [C].2009 International conference on artificial intelligence and computational intelligence. 2009:518-2-522.
[56]Amir Babaeian, Saeed Rastegar, Mojtaba Bandarabadi, et al. Mean shift-Based object tracking with multiple features [C].41st Southeastern symposium on system theory.2009,3:68-72.
[57]马小明,吴晓曦.LNG储罐火灾后果分析[J].中山大学学报,2007,27(2)：105-108.
[58]朱小红,张慧明,陆愈实等.爆炸与中毒模型在液氨储罐安全评价中的应用[J].安全与环境工程,2007,14(3)：100-103.
[59]Adam S. Markowski, M. Sam Mannan. Fuzzy logic for piping risk assessment [J].Journal of loss prevention in the process industries,2009,22(6):921-927.
[60]Chee Beng Goh, Chi Bun Ching, Reginald Tan. Risk analysis for the road transportation of hazardous chemicals in Singapore - a methodology [J].Journal of loss prevention in the process industries,1995,8(1):35-39.
[61]Zhang Jiang-hua, Zhao Lai-jun. Risk analysis of dangerous chemicals transportation [J].Systems engineering-theory & practice,2007,27(12):117-122.
[62]Luciano Fabbri, Sergio Contini. Benchmarking on the evaluation of major accident-related risk assessment [J]. Journal of hazardous materials,2009,162 (2-3):1465-1476.
[63]张洪泉,乔英杰,范茂军.基于Y-A1203膜微加工煤油传感器研究[J].传感器与微系统,2012,31(3)：43-45,49.
[64]刘丛宁,施云波,修德斌,等.面向氯气安全监测的无线传感器网络系统[J].仪表技术与传感器,2012,1：46-48.
[65]V. Malyshev, A.V. Pislyakov. Investigation of gas-sensitivity of sensor structures to carbon monoxide in a wide range of temperature, concentration and humidity of gas medium [J]. Sensors and Actuators B,2007, B 123:71-81.
[66]Kurup, Pradeep U. An electronic nose for detecting hazardous chemicals and explosives [C]. technologies for homeland security,2008:144-149.
[67]Frank C. DeLucia, Jr., Alan C. Samuels, Russell S. Harmon, et al. Laser-induced breakdown spectroscopy (LIBS):A promising versatile chemical sensor technology for hazardous material detection [J]. IEEE sensors journal,2005,5(4):681-690.
[68]Anns-erik, Hildegard, Jander. A test system for gas sensors. Sensors and Actuators B [J].1995, B23:163-172.
[69]Malyshe V, Pislyakov. Investigation of gas-sensitivity of sensor structures to carbon monoxide in a wide range of temperature, concentration and humidity of gas medium [J]. Sensors and Actuators B.2007,B 123:71-81.
[70]方米华,刘骥,魏利军等.危险品运输车辆监控预警系统设计与开发[J].中国安全科学学报,2008,18(5)：109-115.
[71]王敏.危险品运输安全评价系统指标,中国物流与采购[J],2012(7)：68-69.
[72]周受钦,王浩铭.中集集团完成智能罐箱多式联运应用测试.集装箱化[J],2008,19(5)：24-25.
[73]张永生,段战归,周受钦,等.危化品运输设备状态实时监测系统开发[J].交通与计算机,2007,25(6)：106-108.
[74]孙代平,唐祯安,魏广芬,等.一种液化石油气罐箱/槽罐车的实时探测器[J].测控技术,2007,26(6)：15-39.
[75]Li M Q, Chen X, Liu J H. A practical testing system for gas sensor array [J]. Proceedings of the 2008 IEEE international conference on information and automation.2008:1812-1816.
[76]Sun guo, Song Rui, He Shiwei, et al. Mixed transportation network design based on immune clone annealing algorithm [J]. Journal of transportation systems engineering and information technology,2009,9(3):103-108.
[77]A. Batzias, C.G. Siontorou, P.-M.P. Spanidis. Designing a reliable leak bio-detection system for natural gas pipelines [J]. Journal of hazardous materials,2011,186(1):35-58.
[78]陈毅,唐祯安,余隽等.倾斜姿态下智能罐箱液体泄漏状态监测方法[J].仪表技术与传感器.2010(1)：98-100.
[79]陈毅,唐祯安,余隽等.一种危化品运输智能罐箱运行状态监测方法：中国,200910304657.6[P].2011,04.
[80]余隽,唐祯安,黄正兴等.一种用于可燃气体探测器的基线漂移自适应补偿探测方法：中国,200910010072.3[P].2010.10.
[81]Dasarathy B. Decision Fusion [M].Washington:IEEE Computer Society Press,1994.
[82]韩增奇,于俊杰,李宁霞等.信息融合技术综述[J].情报杂志,2010,29：110-114.
[83]蔡莉莉.基于数据融合的语音情感分析与识别[D].南京：东南大学,2005.
[84]杨秀雷.自主推进式猎雷声纳系统体系结构研究[D].哈尔滨：哈尔滨工程大学,2007.
[85]Kaeye Dastner, Thomas Kausch, Felix Opitz. An object oriented development suite for data fusion:design, generation, simulation and testing [C]. Information fusion,2007:1-8.
[86]沙春哲,施云波,修德斌,等.气体传感器长期稳定性智能检测系统[J].电子测量技术,第33卷第6期,2010：102-106.
[87]Tschuncky, Peter, Kiesele, et al.Gas-measuring system with gas sensor and gas generator [P]. American:20060230813.
[88]宋委远.基于传感器阵列的混合气体测试系统研究[D].武汉：华中科技大学,2006.
[89]赵建华,兰华永,陈滋健.基于质量流量控制器的多组分动态配气系统研究[J].自动化仪表,2008年第29卷第2期：44-48.
[90]张鑫，李冬梅,黄元庆.基于LabVIEW的阵列式传感器数据采集系统[J].仪器仪表学报,第27卷第6期增刊,2006.6：1439-1401.
[91]刘洪武,陈德桂,李志鹏.具有图形组态功能的传感器阵列测试系统[J].仪器仪表学报,第26卷第8期,2005：876-880.
[92]Bruce Eckel. Thinking in JAVA [M].出版社：机械工业出版社，2004.
[93]刘冲,吴成百,张文涛等.微小型燃料电池测试系统的气体流量控制[J],光学精密工程,2008年第14卷第5期：840-846.
[94]Liu C.H,Wu CH B,Zhang W T,et al. Gas flux control of testing system for micro/miniature fuel cell [J].Optics and precision engineering,2008,14(5):840-846.
[95]Buckley M.E. Process control in the semiconductor manufacturing environment using a high pressure quad rupole mass spectrometer [J]. Semiconductor processing quality through measurement.1994:211-217.
[96]李芳,张玉广,陆平等.四极质谱仪在空气中七种常量微量组分在线监测中的应用[J].分析仪器,2007年第2期：20-22.
[97]Savadkouhi J. Reliability considerations for gas delivery components [J].Advanced semiconductor manufacturing conference and workshop, USA:IEEE/SEMI,2003:255-261.
[98]刘小娟.复合分子筛催化热解生物质制生物油的研究[D].杭州：浙江工业大学,201].[99]宇传华SPSS与统计分析(含光盘)[M].出版社：电子工业出版社,2007.
[100]黄志坚.工程系统概论——系统论在工程技术中的应用[M].出版社：北京大学出版社,2010.
[101]中国石化集团上海工程有限公司等.化学化工物性数据手册—有机卷)[M],出版社：化学工业出版社,2009.
[102]Thomas Jech.集合论(英文版)[M],出版社：世界图书出版公司,2007.
[103]Explosive gases with electrical equipment part 14:the dangerous site classification [S]. GB3836.14-2000.
[104]Explosive gases with electrical equipment part 1:general requirements [S]. GB3836.1-2000.
[105]Indrek S. Wichman. Material flammability, combustion, toxicity and fire hazard in transportation [J]. Progress in energy and combustion science,2003,29(3):247-299.
[106]常用危险化学品的分类及标志[S].中华人们共和国国家标准GB13690-92,国家技术监督局,1992.
[107]Kanaskar, Nitin,Seker,et al. Dynamical system theory for the detection of anomalous behavior in computer programs [J]. Systems, man, and cybernetics, Part C:applications and reviews,2012, 42(6):1579-1589.
[108]Wei Liang, Jinqiu Hu, Laibin Zhang, Cunjie Guo, Weipeng Lin.Assessing and classifying risk of pipeline third-party interference based on fault tree and SOM [J]. Engineering applications of artificial intelligence,2012,25(3):594-608.
[109]Ruggieri, Salvatore. Efficient C4.5 [classification algorithm] [M], Knowledge and Data Engineering,2002,14(2):438-444.
[110]Jose M. Molina, Jes us Garca, Francisco J. Jimenez, et al. Surveillance multisensor management with fuzzy evaluation of sensor task priorities [J]. Engineering applications of artificial intelligence.2002 (15):511-527.
[111]Adam S. Markowski, M. Sam Mannan, Agata Kotynia, et al. Application of fuzzy logic to explosion risk assessment [J]. Journal of Loss Prevention in the Process Industries,2011,24(6): 780-790.
[112]A. Azadeh, M. Saberi, S.F. Ghaderi,et al. Improved estimation of electricity demand function by integration of fuzzy system and data mining approach [J]. Energy Conversion and Management.2008:2165-2177.
[113]Toms□ Kroupa. Filters in fuzzy class theory [J]. Fuzzy Sets and Systems.159 (2008):1773-1787.
[114]Jose M. Molina, Jesus Garcia, Francisco J. Jimenez,et al. Surveillance multisensor management with fuzzy evaluation of sensor task priorities[J].engineering applications of artificial intelligense,15(2002):511-527.
[115]潘东,金以慧.可拓控制的探索与研究[J].控制理论与应用.1996,13(3)：305-311.
[116]Liang-Teh Lee,Shin-Tsung Lee,Jui-Chih Chang. An extenics-based dynamic resource adjustment for the virtual machine in cloud computing environment [C]. Fourth international conference on ubi-media computing, DOI10.1109/U-MEDIA.2011.33.
[117]Lee Liang-Te, Tao De-Fu, Tseng Chia-Ying, et al. An extenics-based load balancing mechanism for distributed computing systems [C], Proceedings of/€€E TENCON02, 2011:371-374.
[118]Peng Shuai-ying, Li Guang-jie, Meng Fan-qi, et al. Application of extenics theory in hazard assessment of debris flow based on comprehensive weighting of subjective and objective methods [C]. Consumer electronics, communications and networks,2008:2966-2969.
[119]Shu Hong-chun, Peng Shi-xin, Zhao Xing-bing. Integration of multi-algorithm for single-phase fault detection in distribution system with Arc suppression coil grounding using extenics [C]. Electric utility deregulation and restructuring and power technologies. DRPT2008. (4): 2111-2114.
[120]Ju Yi-jing, Yu Yong-quan, Ju Guang-ming, et al. Extension set and restricting qualifications of matter-elements'extension [C]. Proceedings of the third international conference on information technology and applications (ICITA'05),2005:1-4.
[121]J.W Jin; L Rothrock, P.L McDermott et al. Using the analytic hierarchy process to examine judgment consistency in a complex multi-attribute task systems [J]. Man and cybernetics, Part A: systems and humans,2010:1105-1115.