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in the process of engineering, the technology of 3d reconstruction for fabricating complex size and large-scale 3d model is of great significance to the development and production of large engineering projects. but the fabricating process of the model made by traditional technology in engineering is very tedious and laborious, and is lack of accurate. after reading the 3d microwave imaging technology made by different countries, this paper takes the microwave 3d imaging technology of chinese academy of sciences to build a 3d digital model, and built the airplane body model, put forward the application of the 3d digital model in engineering, discussed the problems caused by the application of the 3d digital model in the current technology of large engineering projects, and put forward the following solution for the large engineering projects: using the sensors, such as a-si, ccd camera, laser, and the like, shooting and obtaining the 3d digital model; using the software for 3d modeling, data processing, the visualization of the 3d model, and other functions; improving the 3d modeling software; analyzing the 3d model data processing, visualization, and data input, output and processing standard; strengthening the 3d model testing and verification functions; in a large engineering project, using 3d digital model to replace traditional 3d plastic model, virtual reality technology and other technologies to assist in the construction and operation of the large-scale engineering projects.
a fuzzy system has been widely used in recent years for its advantages of high precision, strong nonlinear, uncertain and non-stationary characteristics, and concise modeling, etc. considering the characteristics of the engineering production process, this paper investigates the fuzzy control based on the industrial digital neural network (idnn). through the analysis of the dynamic characteristics of the production process and process model, the characteristic of the fuzzy system and idnn are compared. in order to make the fuzzy system more sensitive to process disturbances, the amplitude of the control signal is transformed into the accumulated value of the difference between the actual and target signals. the simulation results demonstrate that the fuzzy system based on idnn not only has strong nonlinear adjustment ability, steady adjustment characteristics but also has high adaptation and stability, which has a good performance in controlling nonlinear industrial processes, and realizes real-time control of the system with high accuracy. it is believed that this study can provide a reference for fuzzy control based on idnn in the future.
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