框架结构楼房拆除爆破专家系统研究与应用
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摘要
本文首先讨论了专家系统和人工神经网络在拆除爆破领域中的应用以及存在的问题，探讨了将专家系统和人工神经网络结合起来开发功能更为强大的混合拆除爆破专家系统的必要性和可能性。
本文研究的对象是框架结构楼房拆除爆破专家系统，该系统是武汉理工大学房泽法教授、叶海旺博士开发的拆除爆破专家系统四大模块：板(块)体拆除爆破、楼房框架拆除爆破、高耸建筑物拆除爆破(已开发)、薄壁容器类构筑物拆除爆破所组成的拆除爆破设计专家系统中楼房框架拆除爆破模块其中的一个子模块，楼房框架拆除爆破专家系统包含砖结构类楼房、砖混结构类楼房和框架结构类楼房三大类。
本文的研究内容有：以框架结构楼房拆除爆破领域的专业知识为基础制作专家系统知识库；设计一般面向对象的框架结构楼房爆破拆除设计的专家系统；搜集相关爆破工程实例制作用于爆堆效果预测神经网络训练的样本数据库；选取适当的输入输出因素，用MATLAV6.1构建爆破效果预测神经网络模型；用VB6.0编程开发出框架结构楼房拆除爆破专家系统，并实现爆破效果预测神经网络模型和专家系统的链接。该系统由初始参数输入、倒塌方法选取、倒塌方案确定、孔网参数设计、缺口形状及参数、爆破安全校核、倾倒安全校核、爆破网络、爆破效果预测、工程量计算、计算设计说明书等十一大功能模块组成。只需输入和拆除框架结构楼房的结构尺寸和环境条件相关的初始参数，该系统就可自动得出一套完整的框架结构楼房爆破设计参数，并根据这套爆破设计参数能对楼房倒塌后的爆破效果作出预测。
本文研究的意义：拆除爆破在国民经济建设中占有极其重要的地位。框架结构楼房是一种非常普遍的房屋结构，所以研究框架结构楼房爆破拆除设计专家系统是非常迫切和必要的；将人工神经网络应用到拆除爆破领域拆除爆破专家系统开发中；框架结构楼房爆破拆除设计专家系统吸收了大量成功的爆破工程实例，并在该基础上建立了爆破效果神经网络预测模型，进而可以对爆堆效果进行预测。
The application and the problems of expert system and neural network in blasting field has been discussed in this paper . The necessity and the possibility of developing the integrate Ann-Ex system has been discussed .
The objection studied in the paper is the expert system of explosive demolition of Frame building. The system is one module of the demolition blasting expert system developed by the professor Fangzefa and doctor Yehaiwang of Wuhan University of Technology . The demolition blasting expert system is made up of the following four modules: the plate demolition blasting , the building and frame building demolition blasting , the soaring structure demolition blasting , the thin-wall vessel demolition blasting. The building and frame building demolition blasting module is composed of the brick building and the brick-concrete building and the frame building demolition blasting.
In the paper , the following main factors are studied , such as developing the expert knowledge-base based on the special knowledge of the explosive demolition of Frame building , designing the object-oriented expert system of the explosive demolition of Frame building, developing the neural network training example base based on projects ,developing the forecasting mode of blast effects with Matlab 6.1, developing the expert system of explosive demolition of Frame building with Visual B 6.0, carrying out the connection of the expert system and forecast mode .The system consisted of eleven functional modules ,such as the input of initial parameters module ,the choice of the blasting method module, the choice of blast mode module, the design of blasting parameters module, the design of charge module , the verifying blasting safety module , the calculating safety of tumble module, the design of detonating net module , the blast effects forecasting module and the calculating volume module . The system can finish a complete design of Frame building explosive demolition as long as you input the structure parameters and surroundings parameters of the building.
The meaning of the paper is that demolition blasting have play an important role in the national economy , the frame building is very popular and the development of its demolition blasting is very urgent and necessary . The neural network is applied in the expert system of demolition blasting field . The system is absorbed a lot of project examples and establish the blast effects forecasting module based on the project examples base.
本文研究的对象是框架结构楼房拆除爆破专家系统，该系统是武汉理工大学房泽法教授、叶海旺博士开发的拆除爆破专家系统四大模块：板(块)体拆除爆破、楼房框架拆除爆破、高耸建筑物拆除爆破(已开发)、薄壁容器类构筑物拆除爆破所组成的拆除爆破设计专家系统中楼房框架拆除爆破模块其中的一个子模块，楼房框架拆除爆破专家系统包含砖结构类楼房、砖混结构类楼房和框架结构类楼房三大类。
本文的研究内容有：以框架结构楼房拆除爆破领域的专业知识为基础制作专家系统知识库；设计一般面向对象的框架结构楼房爆破拆除设计的专家系统；搜集相关爆破工程实例制作用于爆堆效果预测神经网络训练的样本数据库；选取适当的输入输出因素，用MATLAV6.1构建爆破效果预测神经网络模型；用VB6.0编程开发出框架结构楼房拆除爆破专家系统，并实现爆破效果预测神经网络模型和专家系统的链接。该系统由初始参数输入、倒塌方法选取、倒塌方案确定、孔网参数设计、缺口形状及参数、爆破安全校核、倾倒安全校核、爆破网络、爆破效果预测、工程量计算、计算设计说明书等十一大功能模块组成。只需输入和拆除框架结构楼房的结构尺寸和环境条件相关的初始参数，该系统就可自动得出一套完整的框架结构楼房爆破设计参数，并根据这套爆破设计参数能对楼房倒塌后的爆破效果作出预测。
本文研究的意义：拆除爆破在国民经济建设中占有极其重要的地位。框架结构楼房是一种非常普遍的房屋结构，所以研究框架结构楼房爆破拆除设计专家系统是非常迫切和必要的；将人工神经网络应用到拆除爆破领域拆除爆破专家系统开发中；框架结构楼房爆破拆除设计专家系统吸收了大量成功的爆破工程实例，并在该基础上建立了爆破效果神经网络预测模型，进而可以对爆堆效果进行预测。
The application and the problems of expert system and neural network in blasting field has been discussed in this paper . The necessity and the possibility of developing the integrate Ann-Ex system has been discussed .
The objection studied in the paper is the expert system of explosive demolition of Frame building. The system is one module of the demolition blasting expert system developed by the professor Fangzefa and doctor Yehaiwang of Wuhan University of Technology . The demolition blasting expert system is made up of the following four modules: the plate demolition blasting , the building and frame building demolition blasting , the soaring structure demolition blasting , the thin-wall vessel demolition blasting. The building and frame building demolition blasting module is composed of the brick building and the brick-concrete building and the frame building demolition blasting.
In the paper , the following main factors are studied , such as developing the expert knowledge-base based on the special knowledge of the explosive demolition of Frame building , designing the object-oriented expert system of the explosive demolition of Frame building, developing the neural network training example base based on projects ,developing the forecasting mode of blast effects with Matlab 6.1, developing the expert system of explosive demolition of Frame building with Visual B 6.0, carrying out the connection of the expert system and forecast mode .The system consisted of eleven functional modules ,such as the input of initial parameters module ,the choice of the blasting method module, the choice of blast mode module, the design of blasting parameters module, the design of charge module , the verifying blasting safety module , the calculating safety of tumble module, the design of detonating net module , the blast effects forecasting module and the calculating volume module . The system can finish a complete design of Frame building explosive demolition as long as you input the structure parameters and surroundings parameters of the building.
The meaning of the paper is that demolition blasting have play an important role in the national economy , the frame building is very popular and the development of its demolition blasting is very urgent and necessary . The neural network is applied in the expert system of demolition blasting field . The system is absorbed a lot of project examples and establish the blast effects forecasting module based on the project examples base.
引文
[1] 唐勇．专家系统在拆除爆破中的应用．工程爆破．1996．Vol 2，No．1：56～59．
[2] Little TN，Jiang J．模糊数学和专家系统在爆破中的应用．ICEB译文专辑．1991．
[3] Ghose AKetal．一个用于露天矿爆破设计新的专家系统软件．ICEB译文专辑，1991．
[4] Scheck DE. Expeanded expert system for blast design. Proc. Int. Symp. on Mine Planning and Equipment Selection. Blakema. , 1988.
[5] Smith ML, Hautala RL. A Coupled expert approach to optional blast design. Proc. Int. Symp. on Mine Planning and Equipment Selection. Blakema, 1990.
[6] 郭连军，范文忠．专家系统在露天矿爆破中的应用展望．辽宁冶金，1993．(1)：11～14．
[7] 叶海旺．高耸建筑物拆除爆破专家系统研究与应用：【硕士学位论文】．武汉：武汉理工大学资环学院，2000．
[8] 房泽法．高耸建筑物拆除爆破专家系统研究与应用．武汉理工大学学报，2002．Vol 24，No．5：75～78．
[9] 高岗．拆除爆破设计的智能系统研究与开发．工程爆破，1999．Vol 5，No．4：16～19．
[10] 舒思齐．高耸建筑物控制爆破拆除的可视化设计系统．武汉科技大学学报(自然科学版)，2000．Vol 24，No．1：63～65．
[11] 谭章禄．人工神经网络及其在矿业中应用前景．煤炭科学技术，1996．Vol24，No．4：44～47．
[12] 郭连军．爆破优化的神经网络模型．爆破工程，1996．Vol 2，No．：11～15．
[13] 段宝福．神经网络模型在台阶爆破块度预测中的应用．爆破工程，1999．Vol5，No4．：25～29．
[14] 陈德志．基于BP神经网络的路堑爆破对邻近民房安全预测的研究．岩石力学与工程学报，2002．Vol 21，No2．：2554～2559．
[15] 魏一呜．人工神经网络在矿业中的应用进展．中国锰业．，1996．Vol 14，No3．：7～11．
[16] 何广沂．拆除爆破新技术．北京：中国铁道出版社，1988．
[17] 管伯伦．爆破工程．北京：冶金工业出版社，1993．
[18] 董振华．特种爆破．北京：水利电力出版社，1994．
[19] 赵福兴．控制爆破工程学．西安：西安交通大学出版社，1988．
[20] 张志呈．爆破原理与设计．重庆：重庆大学出版社．1990
[21] 中国力学工程爆破工程专业委员会．工程爆破．冶金工业出版社，1992．
[22] 张建国．实用爆破技术．北京：冶金工业出版社，1997．
[23] 刘殿中．工程爆破实用手册．北京：冶金工业出版社，1999．
[24] 吴信东．专家系统设计．合肥：中国科学技术大学出版社，1990．
[25] 姚玉川．知识系统．大连：大连理工大学出版社，1988．
[26] 管纪文．知识工程原理．长春：吉林大学出版社，1988．
[27] 吴慧中．机械设计专家系统研究与实践．北京：中国铁道出版社，1994．
[28] Donald A. Waterman. A Guide to Expert Systems. The Rand Corporation, 1998.
[29] Richard Forsyth. Expert System Principles and Case Studties. Chapman and Hall Ltd, 1984.
[30] B. R. Yama G. T. Lineberry. Artificial neural network application for a predication task in mining, Mining Engineering, 1992.
[31] F. Meulenkamp M. Alvare Grima. Application of neural networks for the prediction of the unconfined compressive strength (UCS) from Equation hardness, International Journal of Rock Mechanics and Mining Sciences, 1999.
[32] Y. Yang, Q. Zhang. The Application of Neural Network to Rock Engineering Systems(RMS), Int. J. Rock Mech. Min. Sci. , 1998, 35(6).
[33] Sklavounos, P; Sakellariou, M. Intelligent classification of rock masses. Applications of Artificial Intelligence in Engineering X. Tenth International Conference on Applications of Artificial Intelligence in Engineering, 1995 (7):7340～7340.
[34] Yonghun Jong, Chungin Lee. Application of Neural Networks to Prediction of Powder Factor and Peak Particle Velocity in Tunnel Blasting.
[35] Dojcar, . Design methods for controlled blasting. Transactions of the Institution of Mining and Metallurgy. Section A. Mining Industry, 1996.
[36] Favreau. R. F. ; Favreau, P. How to design a blast with computer simulations. 28th Annual Conference on Expolsives and Blasting Technique, 2002, 475～483.
[37] Rybar. P. Simulation of blasting by computer program SIMTP. Metalurgija/Metallurgy, 1999, 103～107.
[38] Yamamoto, Masaaki; Kaneko, Katsuhiko; Hirata, Atsuo; Matsunaga, Hirofumi. Development of smooth blasting design support system based on computer simulation. Journal of the Japan Explosives Society, 1997: 100～109.
[39] 袁曾忍．人工神经元网络及其应用．北京：清华大学出版社，1999
[40] 王福寿．巷道稳定性分析及其支护设计的智能研究：【硕士学位论文】．武汉：武汉理工大学资环学院，2000
[41] 楼顺天 施阳．基于MATLAB的系统分析与设计——神经网络．西安：西安电子科技大学出版社，1998．
[42] 丛爽．面向MATLAB工具箱的神经网络理论与应用．合肥 中国科技大学出版社，1998．
[2] Little TN，Jiang J．模糊数学和专家系统在爆破中的应用．ICEB译文专辑．1991．
[3] Ghose AKetal．一个用于露天矿爆破设计新的专家系统软件．ICEB译文专辑，1991．
[4] Scheck DE. Expeanded expert system for blast design. Proc. Int. Symp. on Mine Planning and Equipment Selection. Blakema. , 1988.
[5] Smith ML, Hautala RL. A Coupled expert approach to optional blast design. Proc. Int. Symp. on Mine Planning and Equipment Selection. Blakema, 1990.
[6] 郭连军，范文忠．专家系统在露天矿爆破中的应用展望．辽宁冶金，1993．(1)：11～14．
[7] 叶海旺．高耸建筑物拆除爆破专家系统研究与应用：【硕士学位论文】．武汉：武汉理工大学资环学院，2000．
[8] 房泽法．高耸建筑物拆除爆破专家系统研究与应用．武汉理工大学学报，2002．Vol 24，No．5：75～78．
[9] 高岗．拆除爆破设计的智能系统研究与开发．工程爆破，1999．Vol 5，No．4：16～19．
[10] 舒思齐．高耸建筑物控制爆破拆除的可视化设计系统．武汉科技大学学报(自然科学版)，2000．Vol 24，No．1：63～65．
[11] 谭章禄．人工神经网络及其在矿业中应用前景．煤炭科学技术，1996．Vol24，No．4：44～47．
[12] 郭连军．爆破优化的神经网络模型．爆破工程，1996．Vol 2，No．：11～15．
[13] 段宝福．神经网络模型在台阶爆破块度预测中的应用．爆破工程，1999．Vol5，No4．：25～29．
[14] 陈德志．基于BP神经网络的路堑爆破对邻近民房安全预测的研究．岩石力学与工程学报，2002．Vol 21，No2．：2554～2559．
[15] 魏一呜．人工神经网络在矿业中的应用进展．中国锰业．，1996．Vol 14，No3．：7～11．
[16] 何广沂．拆除爆破新技术．北京：中国铁道出版社，1988．
[17] 管伯伦．爆破工程．北京：冶金工业出版社，1993．
[18] 董振华．特种爆破．北京：水利电力出版社，1994．
[19] 赵福兴．控制爆破工程学．西安：西安交通大学出版社，1988．
[20] 张志呈．爆破原理与设计．重庆：重庆大学出版社．1990
[21] 中国力学工程爆破工程专业委员会．工程爆破．冶金工业出版社，1992．
[22] 张建国．实用爆破技术．北京：冶金工业出版社，1997．
[23] 刘殿中．工程爆破实用手册．北京：冶金工业出版社，1999．
[24] 吴信东．专家系统设计．合肥：中国科学技术大学出版社，1990．
[25] 姚玉川．知识系统．大连：大连理工大学出版社，1988．
[26] 管纪文．知识工程原理．长春：吉林大学出版社，1988．
[27] 吴慧中．机械设计专家系统研究与实践．北京：中国铁道出版社，1994．
[28] Donald A. Waterman. A Guide to Expert Systems. The Rand Corporation, 1998.
[29] Richard Forsyth. Expert System Principles and Case Studties. Chapman and Hall Ltd, 1984.
[30] B. R. Yama G. T. Lineberry. Artificial neural network application for a predication task in mining, Mining Engineering, 1992.
[31] F. Meulenkamp M. Alvare Grima. Application of neural networks for the prediction of the unconfined compressive strength (UCS) from Equation hardness, International Journal of Rock Mechanics and Mining Sciences, 1999.
[32] Y. Yang, Q. Zhang. The Application of Neural Network to Rock Engineering Systems(RMS), Int. J. Rock Mech. Min. Sci. , 1998, 35(6).
[33] Sklavounos, P; Sakellariou, M. Intelligent classification of rock masses. Applications of Artificial Intelligence in Engineering X. Tenth International Conference on Applications of Artificial Intelligence in Engineering, 1995 (7):7340～7340.
[34] Yonghun Jong, Chungin Lee. Application of Neural Networks to Prediction of Powder Factor and Peak Particle Velocity in Tunnel Blasting.
[35] Dojcar, . Design methods for controlled blasting. Transactions of the Institution of Mining and Metallurgy. Section A. Mining Industry, 1996.
[36] Favreau. R. F. ; Favreau, P. How to design a blast with computer simulations. 28th Annual Conference on Expolsives and Blasting Technique, 2002, 475～483.
[37] Rybar. P. Simulation of blasting by computer program SIMTP. Metalurgija/Metallurgy, 1999, 103～107.
[38] Yamamoto, Masaaki; Kaneko, Katsuhiko; Hirata, Atsuo; Matsunaga, Hirofumi. Development of smooth blasting design support system based on computer simulation. Journal of the Japan Explosives Society, 1997: 100～109.
[39] 袁曾忍．人工神经元网络及其应用．北京：清华大学出版社，1999
[40] 王福寿．巷道稳定性分析及其支护设计的智能研究：【硕士学位论文】．武汉：武汉理工大学资环学院，2000
[41] 楼顺天 施阳．基于MATLAB的系统分析与设计——神经网络．西安：西安电子科技大学出版社，1998．
[42] 丛爽．面向MATLAB工具箱的神经网络理论与应用．合肥 中国科技大学出版社，1998．