Geotechnical Engineering Safety Monitoring Automation System

The safety monitoring of geotechnical engineering was progressed with the development of mining industry, architecture engineering ,road construction .To monitor the deformation of rock mass and soilmass is an important subject for traffic engineering, mining industry, architecture engineering, water conservancy,slope and so on. The safety monitoring technology has a great development in recent years,and we can find it has these characteristics,real-time, long-distance and non-contact.This thesis takes the application of safety monitoring in geotechnical engineering into account,takes the laboratory construction of resourses and safety school as the background of reseach.The author's summarises of main research are as follows:(1)From analysis the defects, such as bad expansibility, bad compatibility and non-realtime, this thesis describe technical indexes, hardware and software of the system, and how to building the safety monitoring of geotechnical engineering with these characteristics, real-time, long-distance and non-contact.(2)On the foundation of the system forms, have explained the realization of socket network communication in detail based on real-time communication, describe the transmission system of datum live separately from control layer and network transmit layer, adopt B/S (Browser / server, i.e. browser / server) and implement the operation of the monitoring system, gathers the data.(3) To analysis the principle and methods of data's curve regression, trend stacking and Kalman filtering, which was the foundation of fusion data.Take datum array monitored in a long-term course as an example, utilize MATLAB software to explain the realization of the multisensors data fusion in detail.(3)Curve fitting, trend superposing, Caiman who has analyzed data strains monitoring data preconditioning principle and method of the wave and merges the data on this basis. Take datum array monitored in a long-term course as an example, utilize MATLAB software to explain the realization that many transducers merged in detail.(4)Apply BP artificial neural networks to implement that predict the safe monitoring data of the geotechnical engineering.Meanwhile analyze the predicting result, which have explained (the count of implying layer) influence on defects of predicted result. And have chosen the minimum defects and optimum combination to predict by contrast.