| Because of the characteristics of agility, convenience and speediness of blasting technique, it is applied in most of tunnel construction in our country. The quality and velocity of the tunnel blasting design can directly influence the safety, quantity, cost and work period. How to change the current predicaments that the design determined, blasting parameters selected and calculated by the designer's experience, handwork drawing, adjusting and also those problems, such as, modifying difficulty, slow velocity on designing, deficiency on construction schedule authorized by people and construction quality control would be a very urgent problem to solve in the tunnel blasting and tunnel engineering. Therefore, to develop an intelligent tunnel blasting design system not only has important value in application function, but also will improve blasting design level, quality and velocity, even the theory of rock blasting and the combination between computer techniques and artificial intelligences.This thesis aims and argues at the scientific problems of the design determining, blasting parameters selecting, blast-hole layout, slow calculating, difficulty of data management and to utilize the former designs by using the existed blasting data, and continuing design as well. The target of replacing manual by the computer to complete the tunnel blasting design can be implemented by using tunnel blasting theories, computer database techniques, AI theories, ANN techniques, mathematics model theories and computer graphics theories. So, the intelligent process of the tunnel blasting design would be accelerated.According to the tunnel blasting design theories and methods, the parameters, data and expert experience knowledge related to the blasting design were obtained. The database structure and its datasheet structure suited to the tunnel blasting design were determined by adopting database techniques and methods. Selecting the software of Microsoft Access as the database system, the tunnel blasting database bps was set up. The all datasheet and their main keys, indexes and connections each other were established, so that the tunnel blasting design and construction management would be more security, consistency, integrality.According to the regular tunnel blasting design techniques, the composition of intelligent system for tunnel blasting design was determined by adopting the methods of both software engineering and artificial intelligence, which is consisted of knowledge base, database, reasoning system, computer interaction system, and explanation organization, on which a series of reasoning system and search policies based on the AI were given. The function modules including the system management, intelligent calculation of parameter, blasting data, primary design, construction design and construction information management are established on the basis of multi-factors with safety, practicality, quality and users' characteristic.The tunnel cross-section parameters were picked up according to the characteristics of the tunnel outline. The mathematical model, the tunnel outline could be drawn automatically and accurately by the method of input parameters of tunnel, the algorithm process and data flow given. Also the formulas and calculating steps of the tunnel cross-section area calculation could be drawn, which is also the foundation to self-adapting blast-hole disposal for the tunnel blasting.According to the computer techniques and tunnel design theories, together with mathematics modeling theories, the mathematics models were created, which can provide theory sustaining. The system can be self-adapting blast-hole disposal, in the aspects of the contour-hole, reliever-hole and excavated-hole by the tunnel geologic conditions and cross-section sizes. On the basis of above all, the blast-hole arrangement can be modified and adjusted.Using ANN theories and combining the practical requirement of tunnel blasting, a three-layer BP neural network model with 6 nodes in input layer, 7 nodes in output layer, 3 nodes in connotative layer is constructed, in which the Protodiakonov's hardness coefficient, tunnel cross-section area, practical advance per round, blast-hole diameter, etc. are considered as the input parameters of network, and the design advance per round, powder factor, contour-hole spacing, relief-hole spacing, excavated-hole spacing as the output parameters of network. The restrain conditions of network study, on the basis of the blasting prior knowledge according to the relation between the input and output parameters of the network, are proposed to accelerate calculating. The neural network model can implement the goal that the parameters of tunnel blasting are calculated accurately and quickly by using the existed blasting data quantitatively.Taking Visual C++ as the tool for the application system programming, it is available for the tunnel blasting design intelligent system to transfer the parameters, principle of layout blast-hole and relative mathematics models into system function, thus it could become an organic self-governed organization with all the functions operating well inside the system frame.The tunnel blasting design intelligent system(ZXTBS) was applied to Shang-lianxi and Le-shanting tunnel of Wuhan-Guangzhou passenger transport special railway. Considering the facts of the tunnel, the designs with 2.2m, 2.3m and 2.8m of the per ground were put forward separately, which achieved good blasting effect. It is shown that the design diagrams provided by the ZXTBS system can be used to engineering construction and it can achieve good implement on the goal that blasting parameters optimizing, computer drawing of self-adapting layout blast-hole, and self-studying. The designers can complete the tunnel blasting designs accurately and quickly by using ZXTBS system within 20 minutes. A series of problems such as the section was not smooth, the blast-hole efficiency was low, and detonator was fragile, etc., were solved; it can improve the construction quality, promote the schedule and reduce the construction cost. |
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