| The tracking control of heliostats is a hot issue in the field of tower solar thermal power generation.In the tower solar thermal power generation project that has been put into commercial operation at home and abroad,the tracking control of heliostats adopts open-loop control.In order to ensure the tracking accuracy of the heliostat,high-precision mechanical devices and angle detecting devices must be installed,and error correction should be performed on the heliostats one by one,which increases the design cost and maintenance workload of the system.With the advancement of vision technology,more and more vision products have entered the field of industrial control.Therefore,in order to improve the defects of open-loop control,a vision-based heliostat tracking closed-loop control system is proposed.Firstly,the vision-based heliostat tracking closed-loop control strategy is studied.The camera mounted on the surface of the heliostat simultaneously takes photos of the sun and the collector,and derives the formula for calculating the target angle of the mirror surface of the heliostat according to the imaging principle of the camera.At the same time,the innovative splicing multiple cameras has been designed to solve the problem of insufficient vision of the vision platform.In this paper,Zhang camera calibration algorithm is used to complete the calibration of the camera.In order to extract the position coordinates of the sun and the collector in the image,weighted average method grayscale,bimodal threshold segmentation and morphological operation are used in image preprocessing.Effectively reduces the effects of image noise and enhances the detectability of the sun and collector profiles.For the target contour recognition problem,all the contours in the image and different target shape templates are matched according to the Hu moment feature.After verification,the method can accurately match the contours of the sun and the collector,and then calculate the contour centroid coordinates.For the tracking strategy,using the contour centroid coordinates of the collector to calculate the position of the collector will cause local overheating of the collector,this paper designs an improved scheme for the collector aiming point.Finally,based on functional requirements,the hardware platform is built on the embedded system,including the vision processing platform with the Raspberry Pi computing module as the core processor,the heliostat controller and weather station designed with Freescale microcontroller as the core,and the software design of each module is completed by writing a program.In order to verify the reliability of the tracking control system,a space model was built for the angle measurement experiment,and the experimental program was designed to test the system function.The experimental results show that the accuracy of the vision tracking system designed in this paper meets the requirements,and it has great application potential in the field of heliostat tracking control. |
