Tower type photo-thermal mirror field heliostat calibration sampling method and system

By monitoring wind speed in real time and calculating the real position of the artificial light source and camera, the problems of low calibration accuracy and low tracking accuracy in photothermal power generation projects are solved, and the tracking accuracy and operating efficiency of the mirror field are improved.

CN119618069AActive Publication Date: 2025-03-14SEPCOIII ELECTRIC POWER CONSTR CO LTD
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Patent Information

Application Number
CN202510167588.8
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-02-17
Publication Date
2025-03-14
Estimated Expiration
2045-02-17

AI Technical Summary

Technical Problem

In existing photothermal power generation projects, the calibration accuracy is low and the tracking accuracy is low. Traditional white target calibration cannot meet the high-precision requirements and the calibration rate is slow. Especially in strong wind environments, the camera position offset is large, which affects the tracking accuracy and operating efficiency of the mirror field.

Method used

Monitor wind speed through weather stations, calculate the real position of artificial light sources and cameras in real time, ensure the accuracy of machine vision sampling reflected light, and use real position coordinates for calibration in the calibration model to improve the accuracy of model parameters.

Benefits of technology

The calibration accuracy and tracking accuracy are improved, the impact of position coordinate deviation on the calibration model is reduced, and the tracking accuracy and operating efficiency of the mirror field are enhanced.

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Abstract

The invention belongs to the technical field of heliostats, and particularly relates to a tower type photo-thermal mirror field heliostat calibration sampling method and system. Coordinate calibration calculation is carried out on the position of a camera and the position of an artificial light source through the meteorological conditions of the wind direction and the wind speed in the calibration process; coordinates are calibrated according to the inclination angle of the support where the artificial light source and the camera are located caused by wind, so that calibration efficiency and calibration accuracy are guaranteed.
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Description

Technical Field

[0001] The present application belongs to the technical field of heliostats, and in particular relates to a calibration sampling method and system for heliostats in a tower-type solar thermal mirror field. Background Art

[0002] At present, the large-scale construction of solar thermal power generation projects has gradually shown the problems of low calibration accuracy and low tracking accuracy. Traditional white target calibration can no longer meet the calibration requirements of tracking accuracy, and the calibration rate is slow. At present, manual calibration uses the method of artificial light source-camera calibration, and the solution to achieve all-day calibration has gradually matured. During the day, solar light source calibration is used to reflect sunlight to the camera. At night, artificial light source is used to reflect light to the camera, and image processing and spot recognition are performed on the camera image. The calibration with higher accuracy is completed through model algorithm calculation. However, most camera brackets are steel frame structures and are often tens of meters high. Affected by the external environment, especially strong winds, the position offset is greatly affected by the wind. Due to the increasingly stringent requirements for tracking calibration accuracy, the precise position coordinates of each sampling device are particularly important at this time. The position coordinate deviation will cause large errors in the calibration model calculation and calibration accuracy correction, thereby affecting the tracking accuracy of the entire mirror field and affecting the operating efficiency of the mirror field.

[0003] In the current existing calibration schemes, most of them conduct a survey after the camera is installed to fix the position coordinates of the camera. During the calibration process, this fixed coordinate is used unchanged. The impact of the environment on the camera position coordinates is not considered, and there is no position offset correction method, which leads to a decrease in calibration accuracy and affects the tracking accuracy of the heliostat in the mirror field. Summary of the invention

[0004] Based on the above problems, this application provides a technical solution that can monitor the wind speed at the meteorological station and calculate the real position of the artificial light source and the camera in real time through wind speed and wind direction to ensure the accuracy of machine vision sampling reflected light. The technical content is: A method for calibrating and sampling a heliostat in a tower-type photothermal mirror field comprises the following steps: S1. Prioritize the calibration sampling of heliostats in the mirror field; S2. According to the current time, select artificial light source calibration or sunlight calibration; if it is daytime, select sunlight calibration, select a suitable camera, and set the heliostat to calibration mode; if it is nighttime, select artificial light source calibration, select a suitable artificial light source and camera, and set the heliostat to calibration mode; S3. Calculate the tilt angle of the camera according to the wind direction, and control the heliostat to reflect the sunlight or artificial light to the designated camera; S4. Determine the camera image to identify the light spot; if the light spot is identified, proceed to S5; if the light spot is not identified, return to S3; S5. Obtain camera images and heliostat position information; obtain camera and solar light source position information, or camera and artificial light source position information.

[0005] Preferably, the sorting method considers the number of valid samples of the current heliostat, the last sampling time of the current heliostat sample, and the current heliostat target test error. The priority sorting prerequisite is: According to the heliostat model, the maximum number of valid heliostat samples is set as M ,Exceed M The priority is lowered, and the heliostats with fewer samples are sampled first, and both reach M After the new sample is updated, the old sample is invalidated, and the valid sample can be kept for a maximum of M indivual, Or / and, if the heliostat has abnormal motion such as motor out of step, then the heliostat samples before the abnormal time are invalid; Or / and, the valid samples of the heliostat are sampled first according to the current longer time, and a heliostat cannot be continuously sampling; Or / and, the current heliostats with larger errors after target shooting are sampled first, and the default error of those without target shooting is 0.

[0006] Preferably, the number of effective heliostat samples is expressed by the following formula: ; n is the number of valid samples of the heliostat; Assume that the sampling cycle of the entire mirror field is D days, T is the time from the last sampling to the current time, It is the priority coefficient for converting the last sampling time to the current time interval. The formula is as follows: .

[0007] Preferably, the heliostats are sorted according to the size of S, and the heliostats with the highest priority are sampled first. The formula is as follows: ; is the target shooting error, which is 0 if no target shooting test is performed; Prioritize sampling calibration for special designated heliostats. If not specified, it is 0. If it is a designated heliostat, it has: ; , , is the weight coefficient.

[0008] Preferably, in step S3, according to the wind direction, a coordinate system is established with the center of the tower base as the origin, with due east as the positive direction of X, due north as the positive direction of Y, and upward as the positive direction of Z. , then the clockwise rotation angle of the tower relative to the Y axis is , the tower tilt angle , calculate the relative change value of the coordinates (x, y, z) of the artificial light source and camera above the tower: ; ; ; H is the height of the tower, the real coordinates of the artificial light source and the camera .

[0009] Preferably, in step S3, the wind moment on the tower is obtained according to the wind direction, as follows: Assuming that the windward area of ​​the tower changes linearly with height, the average windward area can be approximated as the base area and top area The average value of: ; W is the base width of the tower, is the width of the tower top; taking into account wind direction and tower angle , the frontal area becomes: ; Calculate wind force: ; Assuming that the wind moment acts at the center of the tower, the arm l=H / 2; The wind moment is: ; Wind speed v , air density , drag coefficient .

[0010] Preferably, the restoring moment is generated by the gravity of the iron tower and the cement foundation, and the iron tower gravity is: ; Cement foundation gravity: ; Total Gravity: ; Tower quality , cement foundation quality ; Soil anti-overturning moment: provided by passive earth pressure, passive earth pressure The calculation formula is as follows: ; ; ; Internal friction angle , soil density , the buried depth of the base is d; The point of action of passive earth pressure is located at 2 / 3 of the buried depth, that is: ; The overturning resistance moment provided by the soil is: ; Total restoring torque: ; When the restoring moment and wind moment are equal: ; You can find , and thus calculate the tower inclination angle , the cement base is width B.

[0011] A tower-type photothermal mirror field heliostat calibration sampling system, comprising a data acquisition module, a data processing module, a control module and a data output module; Data acquisition module: obtains physical parameters of towers, heliostats and cameras; Data processing module: calculates the tilt angle of the camera according to the wind direction; Control module: prioritizes the calibration samples of heliostats in the mirror field, obtains camera images and heliostat position information, or obtains camera and sunlight position information, or camera and artificial light source position information, controls the heliostat to reflect sunlight or artificial light to the specified camera; determines the camera image recognition spot; Data output module: Visually output the acquired data.

[0012] Compared with the prior art, the present invention has the following beneficial effects: In the calibration sampling process, the present invention calculates the real position of the artificial light source and the camera in real time through wind speed and wind direction according to the wind speed monitoring of the meteorological station to ensure the accuracy of the reflected light sampled by the machine vision, and calibrates the heliostat model according to the real position coordinates when solving the calibration model to improve the accuracy of the model parameters. The position obtained by this method is more accurate than that using fixed position coordinates, which has an important impact on the accuracy of the model calibration. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 This is the flow chart of this application. Figure 2 Establish a coordinate system diagram with the center of the tower base as the origin. Figure 3 This is a schematic diagram of the calibration of artificial light sources at night in the prior art. Figure 4 Calibrated for prior art daytime sunlight sources. DETAILED DESCRIPTION

[0014] The technical solution of the present application is described in detail below through specific embodiments and drawings. It should be understood that the embodiments of the present application and the specific features in the embodiments are detailed descriptions of the technical solution of the present application, rather than limitations on the technical solution of the present application, and the specific technical features may be combined with each other.

[0015] A method for calibrating and sampling a heliostat in a tower-type photothermal mirror field comprises the following steps: S0. The calibration service is started, and the abnormal motion of the heliostat is determined, and the sample validity is updated.

[0016] S1. Prioritize the calibration sampling of heliostats in the mirror field: The sorting method takes into account the number of valid samples of the current heliostat, the last sampling time of the current heliostat sample, and the current heliostat target test error. Prioritization prerequisites: According to the heliostat model, the maximum number of valid heliostat samples is set as M ,Exceed M The priority is lowered, and the heliostats with fewer samples are sampled first, and both reach M After the new sample is updated, the old sample is invalidated, and the valid sample can be kept for a maximum of M indivual, Or / and, if the heliostat has abnormal motion such as motor out of step, then the heliostat samples before the abnormal time are invalid; Or / and, the valid samples of the heliostat are sampled first according to the current longer time, and a heliostat cannot be continuously sampling; Or / and, the current heliostats with larger errors after target shooting are sampled first, and the default error of those without target shooting is 0.

[0017] Sorting process: The number of effective heliostat samples is expressed by the following formula: ; n is the number of valid samples of the heliostat.

[0018] Assume that the sampling cycle of the entire mirror field is D days, T is the time from the last sampling to the current time, It is the priority coefficient for converting the last sampling time to the current time interval. The formula is as follows: ; Sort the heliostats according to the size of S, and sample the heliostats with higher priority first. The formula is as follows: ; Target error , if no target shooting test is performed, it is 0; Prioritize sampling calibration for special designated heliostats. If not specified, it is 0. If it is a designated heliostat, it has: ; , , is the weight coefficient, The heliostats are sorted according to the size of S, and the heliostats with the highest priority are sampled first.

[0019] S2. According to the current time, select artificial light source calibration or sunlight calibration; if it is daytime, select sunlight calibration, select a suitable camera, and set the heliostat to calibration mode; if it is nighttime, select artificial light source calibration, select a suitable artificial light source and camera, and set the heliostat to calibration mode; Daytime calibration: Calibrate the camera position coordinates according to the current environmental wind speed and direction, reflect sunlight to the camera, obtain the camera image, and identify the light spot in the image through machine vision. If the recognition is successful, save the camera image, heliostat position information, camera position information, wind speed, and wind direction.

[0020] Night calibration: According to the current environmental wind speed and direction, calibrate the camera and artificial light source position coordinates, reflect the artificial light source to the camera, obtain the camera image, and identify the light spot in the image through machine vision. If the identification is successful, save the camera image, heliostat position information, camera position information, artificial light source position information, wind speed, and wind direction.

[0021] S3. Calculate the tilt angle of the camera according to the wind direction, and control the heliostat to reflect the sunlight or artificial light to the designated camera; The present invention takes the frame structure iron tower with buried cement foundation as an example for analysis and calculation: 1. Determine the parameters: Tower height H; tower base width W; tower top width ; Iron tower quality ; Quality of cement foundation ; Wind speed v; Air density ; Drag coefficient ; Wind direction and tower angle ; Cement base dimensions: length L, width B, height ; Base buried depth ; Soil properties: internal friction angle , soil density .

[0022] 2. Calculate the windward area: According to the tower structure, assuming that the windward area of ​​the tower changes linearly with height, the average windward area can be approximated as the average of the bottom area and the top area, and the formula is as follows: ; Consider wind direction and tower angle , the frontal area becomes: .

[0023] 3. Calculate wind force: .

[0024] 4. Calculate wind moment: The wind moment action point is at the center of the tower, and the arm l : ; Wind torque: .

[0025] 5. Calculate the restoring torque: The restoring moment is generated by the weight of the tower and the concrete base. The weight of the tower is: ; Cement foundation gravity: ; Total Gravity: ; Soil anti-overturning moment: provided by passive earth pressure, passive earth pressure The calculation formula is as follows: ; ; ; The point of action of passive earth pressure is located at 2 / 3 of the buried depth, that is: ; The overturning resistance moment provided by the soil is: ; Total restoring torque: .

[0026] Equilibrium conditions: When the restoring moment and wind moment are equal: ; You can find The tower inclination angle is calculated .

[0027] 7. According to the wind direction, a coordinate system is established with the center of the tower base as the origin (due east is the positive direction of X, due north is the positive direction of Y, and upward is the positive direction of Z) to calculate the relative displacement coordinates of X, Y, and Z.

[0028] Set wind direction to (North is 0 degrees), then the clockwise rotation angle of the tower relative to the Y axis is , from this, the relative change value of the coordinates (x, y, z) of the artificial light source and the camera above the tower can be calculated: ; ; ; Therefore, under the influence of ambient wind, the real coordinates of the artificial light source and the camera are .

[0029] S4. Determine whether the camera recognizes the light spot; if the light spot is recognized, proceed to S5; if the light spot is not recognized, return to S3; S5. Obtain camera images and heliostat position information; obtain camera and solar light source position information, or camera and artificial light source position information.

[0030] S6. The heliostat is set to normal mode and S1-S5 are repeated.

[0031] A tower-type photothermal mirror field heliostat calibration sampling system, comprising a data acquisition module, a data processing module, a control module and a data output module; Data acquisition module: obtains physical parameters of towers, heliostats and cameras; Data processing module: calculates the tilt angle of the camera according to the wind direction; Control module: prioritizes the calibration samples of heliostats in the mirror field, obtains camera images and heliostat position information, or obtains camera and sunlight position information, or camera and artificial light source position information, controls the heliostat to reflect sunlight or artificial light to the specified camera, and determines the camera recognition spot; Data output module: Visually output the acquired data.

[0032] The above is only a preferred implementation of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A method for calibrating and sampling heliostats in a tower-type solar thermal mirror field, characterized in that: The following steps are involved: S1. Prioritize the calibration sampling of heliostats in the mirror field; S2. According to the current time, select artificial light source calibration or sunlight calibration; if it is daytime, select sunlight calibration, select a suitable camera, and set the heliostat to calibration mode; if it is nighttime, select artificial light source calibration, select a suitable artificial light source and camera, and set the heliostat to calibration mode; S3. Calculate the tilt angle of the camera according to the wind direction, and control the heliostat to reflect the sunlight or artificial light to the designated camera; S4. Determine the camera image to identify the light spot; if the light spot is identified, proceed to S5; if the light spot is not identified, return to S3; S5. Obtain camera images and heliostat position information; obtain camera and solar light source position information, or camera and artificial light source position information.

2. The method for calibrating and sampling heliostats in a tower thermal mirror field according to claim 1, characterized in that: The sorting method takes into account the number of valid samples of the current heliostat, the last sampling time of the current heliostat sample, and the current heliostat target test error. The prerequisites for priority sorting are: According to the heliostat model, the maximum number of valid heliostat samples is set as M ,Exceed M The priority is lowered, and the heliostats with fewer samples are sampled first, and both reach M After the new sample is updated, the old sample is invalidated, and the valid sample can be kept for a maximum of M indivual, Or / and, if the heliostat has abnormal motion such as motor out of step, then the heliostat samples before the abnormal time are invalid; Or / and, the valid samples of the heliostat are sampled first according to the current longer time, and a heliostat cannot be continuously sampling; Or / and, the current heliostats with larger errors after target shooting are sampled first, and the default error of those without target shooting is 0.

3. The method for calibrating and sampling heliostats in a tower thermal mirror field according to claim 2, characterized in that: The number of effective heliostat samples is expressed by the following formula: ; n is the number of valid samples of the heliostat; is the target shooting error, which is 0 if no target shooting test is performed; Assume that the sampling cycle of the entire mirror field is D days, T is the time from the last sampling to the current time, It is the priority coefficient for converting the last sampling time to the current time interval. The formula is as follows: 。 4. The method for calibrating and sampling heliostats in a tower thermal mirror field according to claim 3, characterized in that: Sort the heliostats according to the size of S, and sample the heliostats with higher priority first. The formula is as follows: ; Prioritize sampling calibration for special designated heliostats. If not specified, it is 0. If it is a designated heliostat, it has: ; , , is the weight coefficient.

5. The method for calibrating and sampling heliostats in a tower thermal mirror field according to claim 3, characterized in that: In step S3, according to the wind direction, a coordinate system is established with the center of the tower base as the origin, with the east as the positive direction of X, the north as the positive direction of Y, and the upward direction as the positive direction of Z. , then the clockwise rotation angle of the tower relative to the Y axis is , the tower tilt angle , calculate the relative change value of the coordinates (x, y, z) of the artificial light source and the camera above the tower: ; ; ; H is the height of the tower, the real coordinates of the artificial light source and the camera .

6. The method for calibrating and sampling heliostats in a tower thermal mirror field according to claim 3, characterized in that: In step S3, the wind moment on the tower is obtained according to the wind direction, as follows: Assuming that the windward area of ​​the tower changes linearly with height, the average windward area can be approximated as the base area and top area The average value of: ; W is the base width of the tower, is the width of the tower top; taking into account wind direction and tower angle , the frontal area becomes: ; Calculate wind force: ; Assuming that the wind moment acts at the center of the tower, the arm l=H / 2; The wind moment is: ; Wind speed v , air density , drag coefficient .

7. The method for calibrating and sampling heliostats in a tower thermal mirror field according to claim 6, characterized in that: The restoring moment is generated by the weight of the tower and the concrete base. The weight of the tower is: ; Cement foundation gravity: ; Total Gravity: ; Tower quality , cement foundation quality ; Soil anti-overturning moment: provided by passive earth pressure, passive earth pressure The calculation formula is as follows: ; ; ; Internal friction angle , soil density , the buried depth of the base is d; The point of action of passive earth pressure is located at 2 / 3 of the buried depth, that is: ; The overturning resistance moment provided by the soil is: ; Total restoring torque: ; When the restoring moment and wind moment are equal: ; You can find , and thus calculate the tower inclination angle , the cement base is width B.

8. A heliostat calibration sampling system for a tower-type thermal mirror field, using the heliostat calibration sampling method for a tower-type thermal mirror field as claimed in any one of claims 1 to 7, characterized in that: It includes a data acquisition module, a data processing module, a control module and a data output module; Data acquisition module: obtains physical parameters of towers, heliostats and cameras; Data processing module: calculates the tilt angle of the camera according to the wind direction; Control module: prioritizes the calibration samples of heliostats in the mirror field, obtains camera images and heliostat position information, or obtains camera and sunlight position information, or camera and artificial light source position information, controls the heliostat to reflect sunlight or artificial light to the specified camera; determines the camera image recognition spot; Data output module: Visually output the acquired data.

Citation Information

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