基于传感器的山体滑坡实时监测系统的实验室实现
摘要
中国是个多山的国家,山地约占全国面积的2/3,是世界上山体滑坡较多的国家之一。除了自然因素引起的山体滑坡外,随着国民经济的蓬勃发展,各项工程活动也对山体地质环境往往起着破坏性的作用。在铁路、公路、水利、航运、采矿、建筑以及国防建设中经常遇到斜(边)的稳定性问题。在中国,每年由山体滑坡引起的损失超过3亿美元,而在全世界却高达10亿美元之多。这些使山体滑坡成为除地震外最大的自然灾害。由于山体滑坡引起如此多的财产损失、人员伤亡,早期预警系统的建立就显得十分必要了。
随着科学的发展一些新的监测技术进入人们视野,用传感器作为监测仪器来研究山体滑坡监测的研究变得非常重要。这些研究及时捕捉崩滑灾害的特征信息,为崩塌、山体滑坡的正确分析评价、预测预报及治理工程等提供可靠资料和科学依据。
论文的目标就是研究如何在实验室实现传感器监测模拟。我们主要以美国基康公司的5种不同传感器为研究对象(如表面位移计、埋入式位移计、多点位移计、土压力计、测斜仪),分别研究如何设计机械工装来帮助传感器实现山体滑坡模拟及如何调试、测试整个监测控制系统的可靠性与稳定性。为从山体滑坡体内部、相关因素、诱发因素去更好地分析了解山体滑坡的稳定性提供了信息,多角度多方位地扩大了思路。此外还编写程序软件,建立山体滑坡监测预警系统,为危险数据的管理和预警、为以后的进一步实验室研究打下坚实基础。本文的主要研究工作及其研究成果:(1)首先分析了山体滑坡的类型、影响因素,并对斜坡的结构、变形破坏原理及其他地质模型进行了总结。找到了实施山体滑坡监测的切入点,并对当前的边坡监测方法进行了总结,为进一步研究打下了基础;(2)分析了不同传感器的工作原理、优缺点的基础上,同时阐述了多种用于判断山体滑坡是否处于稳定状态的监测预警指标(如稳定性系数、可靠概率、位移速率、位移加速度、塑性应变率、蠕变曲线切线角、位移矢量角、声发射参数、分维值等),给传感器预警系统的建立打下了坚实的基础;(3)根据表面位移计、埋入式位移计、多点位移计、土压力计、测斜仪的工作原理,分别设计了不同的机械工装来带动其运动模拟山体滑坡发生现场,并用数据测试装置来检测机械工装模拟山体滑坡的模拟效果,通过多次测试得出测试位移与给定位移相似度达到96%以上,以证明该装置确实能有效的模拟山体滑坡现场;(4)为方便于对监测数据的管理与实时分析,以便及时发现预警情况,采用VC++程序进行编程,分别针对表面位移计、埋入式位移计、多点位移计、土压力计、测斜仪的不同监测指标设计不同的管理子软件,并与临界安全值比较,当其监测数据接近临界安全值时,该软件会自动发出警告,最后用Delphi设计出一套软件可以同时管理这5个子软件,使该预警系统成为一个整体。
China is one of countries full of landslides mostly in the world and the mountain area accounts for about 2 / 3. Besides the natural factors leading to landslides, with the vigorous development of the national economy, the engineering activities on mountain zoon also play a destructive role in the environment. In railway, highway, water conservancy, shipping, mining, construction and national defense we have to face the slope stability problems. Damage caused by landslides exceeds $ 3 billion annually in China and more than $ 10 billion each year worldwide, making losses attributed to landslides greater than any other natural disaster except earthquake. Along with massive property loss, thousands people are killed and injured every year as the result of landslides. Potentially, much of this property damage and many of the injuries and deaths can be avoided with an operational landslide warning system. As the development of new monitoring technology, using sensors for monitoring landslide has become very important. These studies can make contributions to capturing the characteristics of landslides in time, which provide reliable information and scientific basis for correct landslides analysis, evaluation, prediction and control.
The paper's goal is to study simulation of landslide and using sensors to monitor the landslide in the laboratory. Five different kinds of sensors are from Geokon Company, United States (surface displacement meter, embedded displacement meter, multi-point displacement meter, earth pressure cell, and inclinometer). Our jobs are to design the auxiliary tooling which can help to achieve simulation of landslide and how to debug and test the identification part of whole monitoring system. They are helpful for multi-angle and multi-faceted expansion of the ideas such as internal results, related factors, predisposing factors. In addition, programming software is used to establish landslide warning system for risk data management and early warning in the future. Some practical significance and scientific research achievements of value are got. To sum up, in the following aspects:
Firstly the types of landslide, impact factors, slope of the structure, deformation theory and other geological model are the focus points. The next step is finding the key points for the landslide monitoring and then we summarized the current monitoring methods.
Different sensors working principle, advantages and disadvantages are analyzed in detail. Monitoring and early warning indicators which determine whether a slope is in safe state are introduced (stability factor, reliable probability, displacement rate, displacement acceleration, strain rate, creep curve tangent angle, displacement vector angle, acoustic emission parameters, fractal dimension, etc.). All of these make the early warning indicators, sensors monitoring and early warning form an organic whole logically.
According to different working principles of the five sensors (surface displacement meter, embedded displacement meter, multi-point displacement meter, earth pressure cell, and inclinometer) five different auxiliary tooling which can help to achieve simulation of landslide are designed. By analyzing data testing device is used to detect the similarity between simulated landslide brought by machine tooling and the real one. Test displacement and given displacement show that there are more than 96% similarity. It can really prove that the device can simulate landslide effectively.
In order to facilitate the management of monitoring data and find suddenly changed data, with considering the different monitoring indicators we use VC + + to make programs for the surface displacement transducer, embedded displacement meter, multi-point displacement meter, earth pressure, and inclinometer respectively. Compared to safety value when there is danger, the software will automatically issue a warning. Finally, Delphi is used to design software which can manage the five programs. So the warning system becomes a whole.
随着科学的发展一些新的监测技术进入人们视野,用传感器作为监测仪器来研究山体滑坡监测的研究变得非常重要。这些研究及时捕捉崩滑灾害的特征信息,为崩塌、山体滑坡的正确分析评价、预测预报及治理工程等提供可靠资料和科学依据。
论文的目标就是研究如何在实验室实现传感器监测模拟。我们主要以美国基康公司的5种不同传感器为研究对象(如表面位移计、埋入式位移计、多点位移计、土压力计、测斜仪),分别研究如何设计机械工装来帮助传感器实现山体滑坡模拟及如何调试、测试整个监测控制系统的可靠性与稳定性。为从山体滑坡体内部、相关因素、诱发因素去更好地分析了解山体滑坡的稳定性提供了信息,多角度多方位地扩大了思路。此外还编写程序软件,建立山体滑坡监测预警系统,为危险数据的管理和预警、为以后的进一步实验室研究打下坚实基础。本文的主要研究工作及其研究成果:(1)首先分析了山体滑坡的类型、影响因素,并对斜坡的结构、变形破坏原理及其他地质模型进行了总结。找到了实施山体滑坡监测的切入点,并对当前的边坡监测方法进行了总结,为进一步研究打下了基础;(2)分析了不同传感器的工作原理、优缺点的基础上,同时阐述了多种用于判断山体滑坡是否处于稳定状态的监测预警指标(如稳定性系数、可靠概率、位移速率、位移加速度、塑性应变率、蠕变曲线切线角、位移矢量角、声发射参数、分维值等),给传感器预警系统的建立打下了坚实的基础;(3)根据表面位移计、埋入式位移计、多点位移计、土压力计、测斜仪的工作原理,分别设计了不同的机械工装来带动其运动模拟山体滑坡发生现场,并用数据测试装置来检测机械工装模拟山体滑坡的模拟效果,通过多次测试得出测试位移与给定位移相似度达到96%以上,以证明该装置确实能有效的模拟山体滑坡现场;(4)为方便于对监测数据的管理与实时分析,以便及时发现预警情况,采用VC++程序进行编程,分别针对表面位移计、埋入式位移计、多点位移计、土压力计、测斜仪的不同监测指标设计不同的管理子软件,并与临界安全值比较,当其监测数据接近临界安全值时,该软件会自动发出警告,最后用Delphi设计出一套软件可以同时管理这5个子软件,使该预警系统成为一个整体。
China is one of countries full of landslides mostly in the world and the mountain area accounts for about 2 / 3. Besides the natural factors leading to landslides, with the vigorous development of the national economy, the engineering activities on mountain zoon also play a destructive role in the environment. In railway, highway, water conservancy, shipping, mining, construction and national defense we have to face the slope stability problems. Damage caused by landslides exceeds $ 3 billion annually in China and more than $ 10 billion each year worldwide, making losses attributed to landslides greater than any other natural disaster except earthquake. Along with massive property loss, thousands people are killed and injured every year as the result of landslides. Potentially, much of this property damage and many of the injuries and deaths can be avoided with an operational landslide warning system. As the development of new monitoring technology, using sensors for monitoring landslide has become very important. These studies can make contributions to capturing the characteristics of landslides in time, which provide reliable information and scientific basis for correct landslides analysis, evaluation, prediction and control.
The paper's goal is to study simulation of landslide and using sensors to monitor the landslide in the laboratory. Five different kinds of sensors are from Geokon Company, United States (surface displacement meter, embedded displacement meter, multi-point displacement meter, earth pressure cell, and inclinometer). Our jobs are to design the auxiliary tooling which can help to achieve simulation of landslide and how to debug and test the identification part of whole monitoring system. They are helpful for multi-angle and multi-faceted expansion of the ideas such as internal results, related factors, predisposing factors. In addition, programming software is used to establish landslide warning system for risk data management and early warning in the future. Some practical significance and scientific research achievements of value are got. To sum up, in the following aspects:
Firstly the types of landslide, impact factors, slope of the structure, deformation theory and other geological model are the focus points. The next step is finding the key points for the landslide monitoring and then we summarized the current monitoring methods.
Different sensors working principle, advantages and disadvantages are analyzed in detail. Monitoring and early warning indicators which determine whether a slope is in safe state are introduced (stability factor, reliable probability, displacement rate, displacement acceleration, strain rate, creep curve tangent angle, displacement vector angle, acoustic emission parameters, fractal dimension, etc.). All of these make the early warning indicators, sensors monitoring and early warning form an organic whole logically.
According to different working principles of the five sensors (surface displacement meter, embedded displacement meter, multi-point displacement meter, earth pressure cell, and inclinometer) five different auxiliary tooling which can help to achieve simulation of landslide are designed. By analyzing data testing device is used to detect the similarity between simulated landslide brought by machine tooling and the real one. Test displacement and given displacement show that there are more than 96% similarity. It can really prove that the device can simulate landslide effectively.
In order to facilitate the management of monitoring data and find suddenly changed data, with considering the different monitoring indicators we use VC + + to make programs for the surface displacement transducer, embedded displacement meter, multi-point displacement meter, earth pressure, and inclinometer respectively. Compared to safety value when there is danger, the software will automatically issue a warning. Finally, Delphi is used to design software which can manage the five programs. So the warning system becomes a whole.
引文
[1]黄润秋,许强.地质灾害过程模拟和过程控制研究[M].北京:科学出版社,2002.
[2]文海家,张永兴等.滑坡预报国内外研究动态及发展趋势[J].中国地质灾害与防治学报,2004,15(1):1-4.
[3]孟辉,胡海涛.我国主要人类工程活动引起的滑坡崩塌与泥石流灾害[J].工程地质学报, 1996, 12(4): 69-74.
[4]张平之等.滑坡监测研究及其新进展[J].传感器世界,2005:10-14.
[5]国外降雨滑坡灾害预测预报动态研究现状发展趋势.[EB/OL]. http://tech.163.com /04/1105/06/14 DFSEGR0009rt.html.
[6] Highland, L. and Schuster, R. (2000).“Significant Landslide Events in the United States,”USGS, Retrieved from http://landslide.usgs.gov/docs/faq/significantls_508.pdf.
[7]李天文,吴琳等. GPS技术在滑坡监测中的应用[J].山地学报, 2004,22(6):713-718.
[8]张洁,胡光道等. INSAR技术在滑坡监测中的应用研究[J].工程地球物理学报, 2001, 1(2):147-152.
[9] M.G.Angeli.罗小杰译.意大利泰西纳复杂滑坡的监测与预警系统[J].滑坡消息,1994,8:16-17.
[10] Mantovani et al., 1996 F. Mantovani, R. Soeters and C.J. Van Westen, Remote sensing techniques for landslide studies and hazard zonation in Europe, Geomorphology 15 (1996): 213–225.
[11] Sheth, A. N., Tejaswi, Metha, P., Parekh, C. Bansal, R. Merchant, S. Singh T. N. Desai, U.B., Thekkath, C. A., and Toyama, K. (2005). Poster Abstract“A Sensor Network Based Landslide Prediction System,”Proceedings of Sensys 2005.
[12] U.S. Geological Survey (2007), Landslide Hazards, Monitoring retrieved from http://landslides.usgs.gov/hwy50.
[13] U. S. Geological Survey (2006),“The U.S. Geological Survey Landslide Hazards Program 5-Year Plan,”retrieved from http://landslides.usgs.gov/nlic/LHP_2006_Plan.pdf.
[14] Reid, M., LaHusen, R. (2008).“Highway 50, California, Current landslide status,”retrieved form http://landslides.usgs.gov/monitoring/hwy50/status.php.
[15] Schulz, W. H., Coe, J. A., Ellis, W. L., and Kibler, J. D. (2006).“Preliminary Assessment of Landslides Along the Florida River Downstream from Lemon Reservoir, La Plata County, Colorado,”USGS open file report 2006-1343.
[16] Terzis et al. (2006) Terzis, A., Anandarajah, A., Moore, K. and Wang, I. (2006).“Slip SurfaceLocalization162in Wireless Sensor Networks for Landslide Prediction,”IPSN 06.
[17] Sheth et al. (2005) Sheth, A. N., Tejaswi, Metha, P., Parekh, C. Bansal, R. Merchant, S. Singh T. N. Desai, U.
[18] Mehta et al. (2005) Mehta, P. Jagyash, B., Tejaswi, K., Bansal, R. Parekh, C., Sheth, A., Merchant, S. N.,Singh, T. N. Thekkath C. A. and Desai, U. B. (2005).“Distributed Detection Strategies for Landslide Prediction using Wireless Sensor Networks,”Retrieved from http://www.ee.iitb.ac.in/~prakshep/dds_lp.pdf.
[19]李兴举,孙增生.滑坡监测系统的设计[J].路基工程,1999,(5)期:1-5.
[20]周平根.滑坡监测的指标体系与技术方法[J].地质力学学报,2004,10(1):19-25.
[21]李喻理.滑坡监测与变形预报分析[J].山西建筑,2008,34(20):117.
[22]杜建军.基于GPS技术的滑坡自动监测系统[D].重庆大学,2005:19-33.
[23]邬晓岚,涂亚英.滑坡监测方法及新进展[J].中国仪器仪表,2001,(3):10-13.
[24] Angeli et al., 2000 M.G. Angeli, A. Pasuto and S. Silvano, A critical review of landslide monitoring experiences, Engineering Geology 55 (2000):133–147.
[25] Konak, G.;Onur, A.H.; Karakus, D.; K?se, H.; Koca, Y.; Yenice, H.Slope stability analysis and slide monitoring by inclinometer readings[JA].ManeyPublishing,2004,113(3):171-180.
[26] Turner, J. P. Time Domaine Reflectometry for Monitoring Slope Movements[J]. Wyoming Dept. of Transportation, Cheyenne., 64p, Aug 2006 .
[27] Tarantino, C.; Blonda, P.; Pasquariello, G.Application of change detection techniques for monitoring man-induced landslide causal factors[J]. International Geoscience and Remote Sensing Symposium (IGARSS), v 2: 1103-1106.
[28] Rosser, N.J.; Petley, D.N.; Lim, M.; Dunning, S.A.; Allison, R.J. Terrestrial laser scanning for monitoring the process of hard rock coastal cliff erosion[J].Quarterly Journal of Engineering Geology and Hydrogeology, v 38, n 4, p 363-375, November 2005.
[29]肖云,周春梅,虞珏,李沛.大冶铁矿滑坡预测模型研究[J].武汉工程大学学报,2010,32(1):9-11
[30]喻根, B. H. P. Maathuis, C. J. van Westen.基于GIS的滑坡预测模型的预测率及其作用[J].岩石力学与工程学报,2007,26(2):285-287.
[31] Crozier, M.J., 1999. Prediction of rainfall-triggered landslides: a test of the antecedent water status model. Earth Surface Processes and Landforms 24: 825–833.
[32] Reichenbach, P., Cardinali, M., De Vita, P., Guzzetti, F., 1998. Regional hydrological thresholds for landslides and floods in the Tiber River Basin (central Italy). Environmental Geology 35 (2–3): 146–159.
[33] Watson, A.D.; Moore, D.P.; Stewart, T.W.; Psutka, J.F. Investigations and monitoring of rockslopes at Checkerboard Creek and Little Chief Slide[R]. 1st Canada-US Rock Mechanics Symposium - Rock Mechanics Meeting Society's Challenges and Demands, May 27, 2007 - May 31, 2007.
[34]杜良法,黄壮远,孙瑞举.地质灾害监测中环境地球物理方法综述[J].西部探矿工程,2008,(2):68-88.
[35]谢全敏,曲守宁.滑坡灾害监测与预测时序分析[J].自然灾害学报,1993,2(4):67-73.
[36]王俊杰.检测技术与仪表[M]武汉理工大学出版社.2002:1-228.
[37]孟继红,何秀珍.滑坡监测中测量工作的几个问题[J].中国地质灾害与防治学报,2005,16(1):119-120.
[38]刘东.浅谈滑坡监测系统的建立[J].化工矿物与加工,2008,(4):36-38.
[39]张华伟,王世梅,霍志涛,张业明.三峡库区滑坡监测的新方法[J].科学技术与工程,2006,6(13):1898-1900.
[40]王君.传感器原理及检测技术[M].吉林大学出版社,2003:19-44.
[41]徐科军.传感器与检测技术[M].中国电子出版社,2008:24-56.
[42]姜德义,朱合华,杜云贵.边坡稳定性分析与滑坡防治[M].重庆大学出版社,2005:1-101.
[43]张振华,冯夏庭,周辉,张传庆,催强.基于设计安全系数及破坏模式的边坡开挖过程动态变形监测预警方法研究[J].岩土力学,2009,30(3):603-612.
[44]林鸿州,于玉贞,李广信,彭建兵.降雨特性对土质边坡失稳的影响[J].岩石力学与工程学报,2009,28(1):198-204.
[45]冉启发,江智明.滑坡传感器和倾斜计在小龙潭煤矿边坡监测中的应用[J].露天采矿技术,1990,(4):22-25.
[46]李厚芝.三峡库区地质灾害监测中几种常用方法之比较[J].探矿工程(岩土钻掘工程). 2008,(7):81-84.
[47]马祖长,乔晖,孙怡宁.一种无线传感器网络的设计[J].研究与开发,2003,(11):49.
[48]张海飞.利用Delphi实现数据库的备份与恢复[J].长春师范学院学报, 2005,(05):23-27
[49]鱼明.浅析Delphi数据录入与维护的三种方式[J].太原教育学院学报, 2005,(02):77-78
[50]叶菁. Delphi 7.0数据库的架构[J].中山大学学报论丛, 2004,(01):329-331
[51]孙以义,杜鹃.快速应用程序开发工具Delphi[J].电脑技术, 1996,(11) :16-18
[52]司晓萍.新一代开发工具——Delphi 2.0[J].软件世界, 1996,(11):80-81
[2]文海家,张永兴等.滑坡预报国内外研究动态及发展趋势[J].中国地质灾害与防治学报,2004,15(1):1-4.
[3]孟辉,胡海涛.我国主要人类工程活动引起的滑坡崩塌与泥石流灾害[J].工程地质学报, 1996, 12(4): 69-74.
[4]张平之等.滑坡监测研究及其新进展[J].传感器世界,2005:10-14.
[5]国外降雨滑坡灾害预测预报动态研究现状发展趋势.[EB/OL]. http://tech.163.com /04/1105/06/14 DFSEGR0009rt.html.
[6] Highland, L. and Schuster, R. (2000).“Significant Landslide Events in the United States,”USGS, Retrieved from http://landslide.usgs.gov/docs/faq/significantls_508.pdf.
[7]李天文,吴琳等. GPS技术在滑坡监测中的应用[J].山地学报, 2004,22(6):713-718.
[8]张洁,胡光道等. INSAR技术在滑坡监测中的应用研究[J].工程地球物理学报, 2001, 1(2):147-152.
[9] M.G.Angeli.罗小杰译.意大利泰西纳复杂滑坡的监测与预警系统[J].滑坡消息,1994,8:16-17.
[10] Mantovani et al., 1996 F. Mantovani, R. Soeters and C.J. Van Westen, Remote sensing techniques for landslide studies and hazard zonation in Europe, Geomorphology 15 (1996): 213–225.
[11] Sheth, A. N., Tejaswi, Metha, P., Parekh, C. Bansal, R. Merchant, S. Singh T. N. Desai, U.B., Thekkath, C. A., and Toyama, K. (2005). Poster Abstract“A Sensor Network Based Landslide Prediction System,”Proceedings of Sensys 2005.
[12] U.S. Geological Survey (2007), Landslide Hazards, Monitoring retrieved from http://landslides.usgs.gov/hwy50.
[13] U. S. Geological Survey (2006),“The U.S. Geological Survey Landslide Hazards Program 5-Year Plan,”retrieved from http://landslides.usgs.gov/nlic/LHP_2006_Plan.pdf.
[14] Reid, M., LaHusen, R. (2008).“Highway 50, California, Current landslide status,”retrieved form http://landslides.usgs.gov/monitoring/hwy50/status.php.
[15] Schulz, W. H., Coe, J. A., Ellis, W. L., and Kibler, J. D. (2006).“Preliminary Assessment of Landslides Along the Florida River Downstream from Lemon Reservoir, La Plata County, Colorado,”USGS open file report 2006-1343.
[16] Terzis et al. (2006) Terzis, A., Anandarajah, A., Moore, K. and Wang, I. (2006).“Slip SurfaceLocalization162in Wireless Sensor Networks for Landslide Prediction,”IPSN 06.
[17] Sheth et al. (2005) Sheth, A. N., Tejaswi, Metha, P., Parekh, C. Bansal, R. Merchant, S. Singh T. N. Desai, U.
[18] Mehta et al. (2005) Mehta, P. Jagyash, B., Tejaswi, K., Bansal, R. Parekh, C., Sheth, A., Merchant, S. N.,Singh, T. N. Thekkath C. A. and Desai, U. B. (2005).“Distributed Detection Strategies for Landslide Prediction using Wireless Sensor Networks,”Retrieved from http://www.ee.iitb.ac.in/~prakshep/dds_lp.pdf.
[19]李兴举,孙增生.滑坡监测系统的设计[J].路基工程,1999,(5)期:1-5.
[20]周平根.滑坡监测的指标体系与技术方法[J].地质力学学报,2004,10(1):19-25.
[21]李喻理.滑坡监测与变形预报分析[J].山西建筑,2008,34(20):117.
[22]杜建军.基于GPS技术的滑坡自动监测系统[D].重庆大学,2005:19-33.
[23]邬晓岚,涂亚英.滑坡监测方法及新进展[J].中国仪器仪表,2001,(3):10-13.
[24] Angeli et al., 2000 M.G. Angeli, A. Pasuto and S. Silvano, A critical review of landslide monitoring experiences, Engineering Geology 55 (2000):133–147.
[25] Konak, G.;Onur, A.H.; Karakus, D.; K?se, H.; Koca, Y.; Yenice, H.Slope stability analysis and slide monitoring by inclinometer readings[JA].ManeyPublishing,2004,113(3):171-180.
[26] Turner, J. P. Time Domaine Reflectometry for Monitoring Slope Movements[J]. Wyoming Dept. of Transportation, Cheyenne., 64p, Aug 2006 .
[27] Tarantino, C.; Blonda, P.; Pasquariello, G.Application of change detection techniques for monitoring man-induced landslide causal factors[J]. International Geoscience and Remote Sensing Symposium (IGARSS), v 2: 1103-1106.
[28] Rosser, N.J.; Petley, D.N.; Lim, M.; Dunning, S.A.; Allison, R.J. Terrestrial laser scanning for monitoring the process of hard rock coastal cliff erosion[J].Quarterly Journal of Engineering Geology and Hydrogeology, v 38, n 4, p 363-375, November 2005.
[29]肖云,周春梅,虞珏,李沛.大冶铁矿滑坡预测模型研究[J].武汉工程大学学报,2010,32(1):9-11
[30]喻根, B. H. P. Maathuis, C. J. van Westen.基于GIS的滑坡预测模型的预测率及其作用[J].岩石力学与工程学报,2007,26(2):285-287.
[31] Crozier, M.J., 1999. Prediction of rainfall-triggered landslides: a test of the antecedent water status model. Earth Surface Processes and Landforms 24: 825–833.
[32] Reichenbach, P., Cardinali, M., De Vita, P., Guzzetti, F., 1998. Regional hydrological thresholds for landslides and floods in the Tiber River Basin (central Italy). Environmental Geology 35 (2–3): 146–159.
[33] Watson, A.D.; Moore, D.P.; Stewart, T.W.; Psutka, J.F. Investigations and monitoring of rockslopes at Checkerboard Creek and Little Chief Slide[R]. 1st Canada-US Rock Mechanics Symposium - Rock Mechanics Meeting Society's Challenges and Demands, May 27, 2007 - May 31, 2007.
[34]杜良法,黄壮远,孙瑞举.地质灾害监测中环境地球物理方法综述[J].西部探矿工程,2008,(2):68-88.
[35]谢全敏,曲守宁.滑坡灾害监测与预测时序分析[J].自然灾害学报,1993,2(4):67-73.
[36]王俊杰.检测技术与仪表[M]武汉理工大学出版社.2002:1-228.
[37]孟继红,何秀珍.滑坡监测中测量工作的几个问题[J].中国地质灾害与防治学报,2005,16(1):119-120.
[38]刘东.浅谈滑坡监测系统的建立[J].化工矿物与加工,2008,(4):36-38.
[39]张华伟,王世梅,霍志涛,张业明.三峡库区滑坡监测的新方法[J].科学技术与工程,2006,6(13):1898-1900.
[40]王君.传感器原理及检测技术[M].吉林大学出版社,2003:19-44.
[41]徐科军.传感器与检测技术[M].中国电子出版社,2008:24-56.
[42]姜德义,朱合华,杜云贵.边坡稳定性分析与滑坡防治[M].重庆大学出版社,2005:1-101.
[43]张振华,冯夏庭,周辉,张传庆,催强.基于设计安全系数及破坏模式的边坡开挖过程动态变形监测预警方法研究[J].岩土力学,2009,30(3):603-612.
[44]林鸿州,于玉贞,李广信,彭建兵.降雨特性对土质边坡失稳的影响[J].岩石力学与工程学报,2009,28(1):198-204.
[45]冉启发,江智明.滑坡传感器和倾斜计在小龙潭煤矿边坡监测中的应用[J].露天采矿技术,1990,(4):22-25.
[46]李厚芝.三峡库区地质灾害监测中几种常用方法之比较[J].探矿工程(岩土钻掘工程). 2008,(7):81-84.
[47]马祖长,乔晖,孙怡宁.一种无线传感器网络的设计[J].研究与开发,2003,(11):49.
[48]张海飞.利用Delphi实现数据库的备份与恢复[J].长春师范学院学报, 2005,(05):23-27
[49]鱼明.浅析Delphi数据录入与维护的三种方式[J].太原教育学院学报, 2005,(02):77-78
[50]叶菁. Delphi 7.0数据库的架构[J].中山大学学报论丛, 2004,(01):329-331
[51]孙以义,杜鹃.快速应用程序开发工具Delphi[J].电脑技术, 1996,(11) :16-18
[52]司晓萍.新一代开发工具——Delphi 2.0[J].软件世界, 1996,(11):80-81