Highway Slope Stability IoT Monitoring System Based on Laser Datum
In order to meet the high precision,real-time and long-distance requirements of stability monitoring for in-service high-risk highway slope,a photoelectric image-based deformation monitoring method based on FPGA to solve high-precision laser datum is proposed.The laser network monitoring system is divided into laser transmitting unit and intelligent target receiving unit.According to the function of the target FPGA module,the COM interface for wireless communication is designed.In order to improve the precision of the system,the target obscura structure is designed,which makes the incident laser transmitted from the longitudinal crack to the light screen and avoids the environmental light interference.In order to obtain a constant power laser source,a three-loop feedback structure of constant power laser emitting device is designed.In order to obtain a stable spot,the algorithm of fusion and connection is used to realize the accurate location of the spot.The transformation matrix from the world coordinate system to the pixel coordinate system is established,the internal and external parameter matrices of the monitoring system are solved by Zhang's calibration method,and the three-dimensional calibration of the monitoring system is realized.In order to complete the remote data transmission of slope settlement,WEB technology is used to develop remote interface for slope monitoring system,and a data storage and processing system based on MySQL database is established and installed at Zhangtan-Bahe section in Hanbin District,Ankang.The result shows that(1)the maximum monitoring error of slope stability monitoring system is 0.25 mm,and the error percentage is less than 2.99%;(2)the developed WEB remote interface system based on cloud network has perfect function and friendly interface,which can meet the needs of slope stability monitoring;(3)compared with the current 1 a monitoring,the test result of the study is better than that of the LM-optimized BP neural network algorithm,showing that the accuracy of the study can meet the needs of slope settlement accuracy.
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