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CN120177001A - Calibration sampling method and system based on heliostat fields with different areas - Google Patents

Calibration sampling method and system based on heliostat fields with different areas Download PDF

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Publication number
CN120177001A
CN120177001A CN202510652397.0A CN202510652397A CN120177001A CN 120177001 A CN120177001 A CN 120177001A CN 202510652397 A CN202510652397 A CN 202510652397A CN 120177001 A CN120177001 A CN 120177001A
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heliostat
sampling
calibration
heliostats
camera
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徐谦
魏源
潘任伟
代增丽
赵仁卿
王桂亮
朱超
刘权武
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SEPCO3 Electric Power Construction Co Ltd
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SEPCO3 Electric Power Construction Co Ltd
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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D3/00—Control of position or direction
    • G05D3/12—Control of position or direction using feedback
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J1/00—Photometry, e.g. photographic exposure meter
    • G01J1/42—Photometry, e.g. photographic exposure meter using electric radiation detectors
    • G01J1/4204—Photometry, e.g. photographic exposure meter using electric radiation detectors with determination of ambient light
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
    • G01M11/00—Testing of optical apparatus; Testing structures by optical methods not otherwise provided for
    • G01M11/02—Testing optical properties

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Abstract

The application belongs to the technical field of heliostats, in particular to a calibration sampling method and a system based on heliostat fields with different areas, which provides a sampling expected queuing algorithm based on tracking accuracy, sampling time consumption estimation and mirror optical efficiency, and scheduling different heliostats for sampling based on a sampling optimization algorithm of multi-heliostat combined light intensity prediction and calibration camera temperature real-time monitoring so as to improve the sampling efficiency of heliostats in a heliostat field.

Description

Calibration sampling method and system based on heliostat fields with different areas
Technical Field
The application belongs to the technical field of heliostats, and particularly relates to a calibration sampling method and system based on heliostat fields with different areas.
Background
The tower type photo-thermal mirror field has high requirements on tracking accuracy of the heliostat reflected light spots. After a period of operation, the heliostat can have reduced reflection accuracy. In order to maintain high accuracy of heliostat tracking, the heliostat needs to be calibrated continuously. The heliostat field is usually calibrated by adopting methods such as heliostat daytime white target calibration, heliostat reflected sunlight to camera sampling calibration and the like.
In general, 30-40 m2 medium heliostats are calibrated by adopting a daytime white target method, the white target size is large, and a single white target can only calibrate one heliostat at a time, however, for the heliostat field with the same lighting area and using a small heliostat, the efficiency is very low when the small heliostat is calibrated by adopting the method, and the calibration period of the heliostat field can be greatly prolonged.
When the heliostat is used for reflecting sunlight to the camera for sampling and calibrating the field, a calibration tower and a camera are generally arranged around the light-gathering field, the distance between the heliostat and the calibration camera is different, and meanwhile, the heliostat is suitable for a small planar heliostat due to the fact that the curvature radius of the medium-sized heliostat is fixed and the reflection light spots are large, and the method for sampling and calibrating the heliostat for reflecting sunlight to the camera is not suitable for the medium-sized heliostat.
Conventional tower photo-thermal fields typically have only small heliostats or only medium heliostats. In the large-scale mirror field, the small heliostat has the advantages of accurate condensation control in the area close to the heat absorption tower, and the medium heliostat with a certain curvature has the advantages of light spots in the area far from the heat absorption tower. For the field where the small heliostat and the medium heliostat are installed at the same time, the above two common calibration methods cannot be applied at the same time.
Disclosure of Invention
Based on the problems, the application provides a sampling expected queuing algorithm based on tracking accuracy, sampling time consumption estimation and mirror optical efficiency, and a sampling optimization algorithm based on multi-heliostat integrated light intensity prediction and calibration camera temperature real-time monitoring, which are used for scheduling different heliostats for sampling so as to improve the sampling efficiency of heliostats in a heliostat field. The technical proposal is as follows:
A calibration sampling method based on heliostat fields with different areas comprises the following steps:
S1, calculating tracking accuracy of a heliostat;
s2, calculating priority ordering;
S3, heliostat sampling scheduling based on sampling expected priority;
S4, periodic training;
s5, scheduling optimization is carried out based on multi-heliostat combined light intensity prediction and camera temperature real-time monitoring, whether the maximum combined light intensity reaches an upper limit is calculated, if yes, the step S3 is returned to, if not, the heliostat starts sampling, and after the sampling is completed, the sample is put in storage;
s6, judging whether the condition of incapability of sampling is met, if so, ending the sampling, and otherwise, returning to the step S2.
Preferably, the method further comprises the step S0. of preparing the calibration sampling environment in advance:
The heliostat parameter setting comprises a small heliostat, a medium heliostat and a medium heliostat, wherein the small heliostat refers to a planar heliostat with the area of 2-3 m < 2 >, and the medium heliostat refers to a curved heliostat with the area of 30-40 m < 2 >, and is a concave mirror with a certain curvature, which is formed by assembling a plurality of planar mirrors according to m rows and n columns;
The total number of the calibration cameras needed by the mirror field is based on the visual range of all cameras, all heliostats of the mirror field can be covered, each calibration camera can be matched and combined with heliostats in different areas, and each heliostat can also be matched and combined with a plurality of calibration cameras;
Daytime sampling, wherein heliostat reflection light spots in a sampling camera picture are brighter, and other areas are dark;
The sampling combination comprises three parts of heliostats, calibration cameras and solar light sources, wherein each calibration camera can form N sampling combinations according to the actual small-sized and medium-sized heliostats in the visual field of the calibration cameras, the sampling combination is represented by [ C i, Hi, Li ], the calibration cameras are represented by C, the heliostats are represented by H, and the solar light sources are represented by L;
Calibrating a camera:
Through camera calibration, determining the mapping relation between heliostat ID and camera pixel coordinates:
;
And (3) calibrating the region of interest, namely determining a light spot detection boundary for each heliostat in the field of view of the camera when the camera is calibrated so as to eliminate noise interference of light spot detection during sampling, wherein after one heliostat starts to sample, other heliostats in the light spot detection boundary of the heliostat cannot sample by using the camera, and the region is called a camera region of interest.
Preferably, the tracking accuracy of the heliostat is calculated as follows:
the heliostat is provided with two driving motors which respectively control the heliostat in azimuth angle And pitch angleRotating in the direction;
Each sampling combination successfully acquires a sample with the actual angle of the sample being While the theoretical angle of the sample isThen, the angle difference between the two driving motors in the sample is respectively:
;
;
The final tracking accuracy is calculated by the heliostat based on samples of different angles acquired by different sampling combinations, and is as follows:
;
Wherein:
r, tracking accuracy of heliostat;
the number of samples per heliostat;
the calibration sampling preparation stage calculates the tracking accuracy of all heliostats, and when a new sample is acquired, recalculates the tracking accuracy of the heliostats, and updates the tracking accuracy ordering of all heliostats.
Preferably, the area of the medium heliostat is larger, the single sampling time consumption is longer than that of the small heliostat, and the solar altitude angle of the same heliostat at different times every day is different, so that the sampling time consumption is different, the sampling time consumption average value of effective samples of the heliostat with the same hour time period and the same type is calculated as the time consumption estimated value of the current sampling by taking the hour time period of the same hour time period as a dividing unit, and the solar altitude angle of the heliostat with the same hour time period in different seasons is larger, so that the sampling time consumption average value is calculated, and the samples with the set number are arranged in the inverted order of the sample acquisition time in the hour time period.
Preferably, the time consumption ratio of the medium heliostat to the small heliostat in the current hour period is calculated as follows:
;
;
Wherein:
ρ tM sampling time consumption ratio of the medium heliostat;
ρ tS sampling time-consuming ratio of small heliostat;
T j time consuming the sample of the medium heliostat;
J, the number of sampling samples of the medium heliostat;
t k time consuming sampling of the sample by the small heliostat;
K, the number of sampling samples of the small heliostat;
The sampling expected calculation formula for integrating the heliostat tracking accuracy, the heliostat sampling time consumption ratio and the heliostat optical efficiency value is as follows:
;
The heliostat optical efficiency parameter formula is:
;
Wherein:
E, sampling expected values of heliostats;
R, heliostat tracking accuracy;
ρ, heliostat sampling time consumption ratio;
η is the value of the optical efficiency of the heliostat;
k 1、k2 dynamic adjustment coefficients;
the optical efficiency value of the heliostat;
Heliostat reflectivity;
Heliostat curvature;
cosine efficiency of heliostat;
Shadow shielding efficiency of heliostats;
Atmospheric transmittance;
before the heliostat of the heliostat field starts sampling, a sampling expected value of each heliostat is calculated, and the larger the expected value is, the higher the sampling priority is.
Preferably, in step S5, the photosynthetic intensity is predicted to be different in illumination intensity of reflection light spots of heliostats with different surface types, one medium heliostat is composed of m rows and n columns of mirror surfaces, and the maximum value of illumination intensity generated by the reflection light spots on a calibrated and sampled camera is approximately the same as that of a small heliostatWhen M medium heliostats and N small heliostats are sampled by using one calibration camera at the same time, multi-facula overlapping occurs, and the maximum total light intensity on the calibration camera is as follows:
;
Wherein:
m, the number of medium heliostats;
the number of small heliostats;
m, lens row number of the medium heliostat;
n, lens columns forming the medium heliostat;
r is specular reflectivity;
I i, the illumination intensity of a single lens of the medium heliostat;
And I j, the illumination intensity of the small heliostat lens.
Preferably, when the heliostat of the heliostat field is sampled, a plurality of heliostats simultaneously use the same calibration camera for sampling, and as the number of the heliostat light spots increases, the temperature of the calibration camera gradually increases, and the upper temperature resistance limit of the calibration camera and the upper energy of the heliostat reflection light spots determine the upper number limit of the heliostats simultaneously sampled;
The temperature is divided into a normal temperature region, a warning temperature region and an over Wen Wenou when the camera is calibrated and sampled, the calibration control system can schedule a plurality of heliostats in a standby state to enter a sampling state when the camera temperature is in the normal temperature region, the calibration control system maintains the current heliostat sampling and does not increase the heliostat in the new standby state to enter the sampling state when the camera temperature is gradually increased to the warning temperature region along with the increase of the simultaneous sampling quantity, and the temperature of the camera in the warning temperature region can be continuously increased to the over temperature region due to the influence of DNI increase, the increase of the simultaneous sampling heliostat quantity or other factors, at the moment, all heliostats stop sampling immediately.
Preferably, for the same calibration camera, when a heliostat enters a sampling pre-queuing waiting state, the maximum total light intensity of the heliostat after entering the sampling needs to be estimated; if the maximum photosynthetic intensity which can be born by the calibration camera is exceeded, the heliostat cannot start sampling, the maximum total light intensity needs to be estimated again after the sampling of any heliostat which is being sampled is ended, the judging process is repeated, and the heliostat can formally start sampling until the estimated total light intensity is within the allowable range;
Because the total light intensity of the medium-sized heliostat is X times that of the small-sized heliostat, when the medium-sized heliostat enters a sampling pre-queuing waiting state, the sampling can be formally started after the sampling of a plurality of small-sized heliostats is completed.
A calibration sampling system based on heliostat fields with different areas comprises a signal acquisition unit, a processing unit and an output unit;
the signal acquisition unit is used for acquiring a processing signal;
the processing unit is used for calculating tracking accuracy of heliostats, calculating expected priority, and carrying out heliostat sampling scheduling based on the expected priority;
And the output unit is used for visually outputting the result.
Compared with the prior art, the application has the following beneficial effects:
The method uses sunlight and a calibration camera to calibrate and sample in the daytime.
The method calibrates the region of interest of the calibration camera, can avoid mutual interference between reflected light spots generated during sampling of heliostats with similar distances, and eliminates noise interference during light spot extraction and recognition during sampling, thereby improving sampling efficiency.
The method sorts the heliostats according to tracking accuracy, and the lower the tracking accuracy is, the higher the calibration sampling priority is.
The method considers that the area of the medium heliostat is larger, the single sampling time is longer than that of the small heliostat, and meanwhile, the influence of the optical efficiency of the mirror surface is considered. Thus, the desired prioritization algorithm is optimized based on tracking accuracy, sampling time-consuming estimation, and specular optical efficiency.
According to the method, the maximum synthetic light intensity on a single calibration camera is pre-calculated when different quantities of medium-sized and small-sized heliostats are simultaneously sampled, so that the quantity of heliostats simultaneously sampled by the single calibration camera is controlled, and the over-temperature damage of the calibration camera caused by excessive energy is prevented.
The method provides a sampling temperature interval, an alarm temperature interval and a stop sampling temperature interval of the calibration camera, can improve the concurrency and efficiency of the calibration sampling, and simultaneously protects the hardware of the calibration camera from being damaged.
According to the method, the rotation of the heliostat is controlled by the two stepping motors in the horizontal direction and the vertical direction, and the movement path of the reflecting light spots of the heliostat is controlled to avoid the calibration camera, so that the generation of sampling light spots and the temperature interference of the camera can be avoided.
Drawings
FIG. 1 is a schematic illustration of region of interest calibration in calibrating camera view;
FIG. 2 is a heliostat sampling schedule flow chart;
FIG. 3 is a schematic diagram of a field calibration sampling;
In the figure:
11-region of interest of small heliostat, 12-small heliostat, 13-region of interest of medium heliostat of small and medium heliostat adjacent region, 14-region of interest of medium heliostat of small and medium heliostat adjacent region, 15-region of interest of medium heliostat, 16-region of interest of medium heliostat, 17-region of interest of small heliostat of small and medium heliostat adjacent region, 18-region of small heliostat of small and medium heliostat adjacent region;
21-heat absorber, 22-heat absorbing tower, 23-calibration camera, 24-small heliostat, 25-medium heliostat.
Detailed Description
The following detailed description of the technical solutions of the present application will be made by specific embodiments and accompanying drawings, and it should be understood that the embodiments of the present application and specific features in the embodiments are detailed descriptions of the technical solutions of the present application, and not limiting the technical solutions of the present application, and that the specific technical features may be combined with each other.
The method uses sunlight and a calibration camera to calibrate and sample in the daytime.
As shown in fig. 1, the method calibrates the interested region of the calibration camera, and can avoid mutual interference between reflected light spots when heliostats with similar distances are sampled, so as to eliminate noise interference when light spots are extracted and identified in the sampling process, thereby improving the sampling efficiency.
The method sorts the heliostats according to tracking accuracy, and the lower the tracking accuracy is, the higher the calibration sampling priority is.
The method considers that the area of the medium heliostat is larger, the single sampling time is longer than that of the small heliostat, and meanwhile, the influence of the optical efficiency of the mirror surface is considered. Thus, the desired prioritization algorithm is optimized based on tracking accuracy, sampling time-consuming estimation, and specular optical efficiency.
According to the method, the maximum synthetic light intensity on a single calibration camera is pre-calculated when different quantities of medium-sized and small-sized heliostats are simultaneously sampled, so that the quantity of heliostats simultaneously sampled by the single calibration camera is controlled, and the over-temperature damage of the calibration camera caused by excessive energy is prevented.
The method provides a sampling temperature interval, an alarm temperature interval and a stop sampling temperature interval of the calibration camera, can improve the concurrency and efficiency of the calibration sampling, and simultaneously protects the hardware of the calibration camera from being damaged.
According to the method, the rotation of the heliostat is controlled by the two stepping motors in the horizontal direction and the vertical direction, and the movement path of the reflecting light spots of the heliostat is controlled to avoid the calibration camera, so that the generation of sampling light spots and the temperature interference of the camera can be avoided.
In order to achieve the above purpose, the technical scheme of the invention is as follows:
2-3, a calibration sampling method based on heliostat fields of different areas includes the following steps:
s1, starting a sampling program, and calculating tracking accuracy of a heliostat;
s2, calculating priority ordering;
s3, heliostat sampling scheduling based on sampling expected priority, and heliostat with highest priority waits;
S4, periodic training;
s5, scheduling optimization is carried out based on multi-heliostat combined light intensity prediction and camera temperature real-time monitoring, whether the maximum combined light intensity reaches an upper limit is calculated, if yes, the step S3 is returned, and if not, after the heliostat begins to sample, the sample is put in storage;
s6, judging whether a condition that cannot be sampled (such as sunset cannot be sampled) is reached, if so, ending the sampling, and otherwise, returning to the step S2.
Calibration sampling environment and early preparation:
1. Heliostat:
1) Small heliostat:
The small heliostat refers to a planar heliostat with an area of 2-3 m 2.
2) Medium heliostat:
The medium heliostat refers to a curved heliostat with the area of 30-40 m < 2 >, and is a concave mirror with a certain curvature, which is formed by assembling a plurality of plane mirrors according to m rows and n columns.
2. Calibrating the camera:
The calibration camera is arranged on the outer wall support of the cylindrical heat absorption tower in the center of the lens field, and the larger the lens field is, the higher the height of the heat absorption tower is. In general, the mounting height of the camera in the large lens field can reach more than hundred meters. Meanwhile, a plurality of calibration cameras can be installed on different horizontal planes of the heat absorption tower in multiple layers, so that the requirements of more heliostat sampling in a mirror field, higher calibration sampling efficiency and the like are met.
The total number of calibration cameras needed for the field of mirrors is such that the field of mirrors can be covered by all heliostats for all cameras' viewable range. Meanwhile, each calibration camera can be paired with heliostats of different areas, and each heliostat can also be paired with a plurality of calibration cameras.
During daytime sampling, special mode, shutter, gain and other parameters need to be configured to reduce the brightness of the picture. Heliostat reflection light spots in the image of the sampling camera are brighter, and other areas appear dark.
3. Sampling combination:
The sampling combination consists of heliostat, calibration cameras and sunlight sources, and each calibration camera can form N sampling combinations according to the actual small and medium heliostat in the field of view. Sample combination is denoted by [ C 1, H1, L1 ] (where the calibration camera is denoted by C, the heliostat is denoted by H, the solar source is denoted by L):
4. calibrating a camera:
The calibration camera in the invention is calibrated in daytime, all heliostats are rotated to a horizontal posture before the calibration of the camera, and Azimuth angle (Az) and pitch angle (El) of all heliostats are kept the same. And when the camera is calibrated, selecting a mirror surface center point of the horizontal posture of the heliostat in the view angle of the camera as a three-dimensional coordinate point of the heliostat space, and calibrating the heliostats in all calibration cameras by using a camera calibration algorithm.
The camera calibration aims at establishing a mapping relation between a three-dimensional world coordinate system and a two-dimensional image pixel coordinate system. The world coordinates of the calibration camera are the camera lens center, and the world coordinates of the heliostat are the mirror surface center when in a horizontal posture, and the coordinate conversion calculation process is as follows:
1) Converting the world coordinates into calibrated camera coordinates;
2) Converting the calibration camera coordinates into image plane coordinates;
3) Converting the image plane coordinates into image pixel coordinates;
and (3) determining the mapping relation between the heliostat ID (the heliostat is represented by H) and the pixel coordinates of the camera through camera calibration:
。
5. and (5) calibrating a region of interest:
When each camera performs calibration sampling on heliostats in a visual field, mutually-interfered heliostat reflection light spots with similar distances can be generated, and the mutually-interfered heliostat light spots during sampling are called sampling conflicts. Thus, when a camera is calibrated, a spot detection boundary is determined for each heliostat in the field of view of the camera to eliminate noise interference of spot detection during sampling, after one heliostat begins to sample, other heliostats within the spot detection boundary of the heliostat cannot sample using the camera, which is referred to as a camera region of interest (Region of Interest, abbreviated as ROI).
(II) a calibration sampling method:
first, tracking accuracy calculation:
The heliostat can calculate the root mean square error (RMS), i.e., tracking accuracy, of the heliostat angle through a plurality of different sampled samples.
The heliostat is provided with two driving motors which respectively control the heliostat in azimuth angleAnd pitch angleAnd rotates in the direction. Each sampling combination successfully acquires a sample with the actual angle of the sample beingWhile the theoretical angle of the sample is. Then, the angle difference between the two driving motors in the sample is respectively:
;
;
The final tracking accuracy is calculated by the heliostat based on samples of different angles acquired by different sampling combinations, and is as follows:
;
Wherein,
R, tracking accuracy of heliostat;
Number of samples per heliostat.
The calibration sample preparation phase will calculate the tracking accuracy of all heliostats. And after a new sample is acquired, recalculating the tracking accuracy of the heliostats, and updating the tracking accuracy sequences of all the heliostats.
Second, heliostat sampling pre-queuing:
Sample expectation queuing algorithms based on heliostat tracking accuracy, sample time-consuming estimation, and specular optical efficiency.
1) The tracking accuracy of the heliostat is calculated based on the collected effective samples, and when the number of the samples is larger and the angular distribution of the heliostat is wider, the tracking accuracy is higher, namely the tracking error is lower.
2) The medium heliostat has a larger area and takes longer time for a single sampling than a small heliostat. For the same heliostat, the solar altitude angle at different times every day is different, so that the sampling time consumption is different. Therefore, taking the hours as a division unit, calculating the sampling time-consuming average value of the effective samples of heliostats of the same type in the same hour period through the hour period in which the sampling time is located, and taking the sampling time-consuming average value as the time-consuming estimated value of the current sampling. The solar altitude angle in the same hour period in different seasons has larger difference, so when the sampling time-consuming mean value is calculated, a certain number of samples are arranged in the reverse order of the sample collecting time in the hour period.
The time consumption ratio of the medium heliostat and the small heliostat in the current hour period is calculated as follows:
;
;
Wherein:
ρ tM sampling time consumption ratio of the medium heliostat;
ρ tS sampling time-consuming ratio of small heliostat;
T j time consuming the sample of the medium heliostat;
J, the number of sampling samples of the medium heliostat;
t k time consuming sampling of the sample by the small heliostat;
K, the number of samples sampled by the small heliostat.
3) The higher the heliostat mirror optical efficiency, the higher the thermal power output at the field of the mirror on a day-by-day basis. Thus, the higher the heliostat mirror optical efficiency, the higher its sampling priority, with the other factors being equal. The optical efficiency of the mirror surface is influenced by factors such as heliostat reflectivity, curvature, cosine efficiency, shadow shielding efficiency, atmospheric transmissivity and the like, and when the sampling priority is expected to be calculated, expected values are comprehensively considered.
The heliostat optical efficiency parameter formula is:
Wherein:
the optical efficiency value of the heliostat;
Heliostat reflectivity;
Heliostat curvature;
cosine efficiency of heliostat;
Shadow shielding efficiency of heliostats;
Atmospheric transmittance;
Finally, the sampling expected calculation formula integrating the heliostat tracking accuracy, the heliostat sampling time consumption ratio and the heliostat optical efficiency value is as follows:
;
Wherein:
E, sampling expected values of heliostats;
R, heliostat tracking accuracy;
ρ, heliostat sampling time consumption ratio;
η is the value of the optical efficiency of the heliostat;
k 1、k2 dynamic adjustment coefficients;
before the heliostat of the heliostat field starts sampling, a sampling expected value of each heliostat is calculated, and the larger the expected value is, the higher the sampling priority is.
Third, heliostat sampling scheduling algorithm
The sampling scheduling algorithm provided by the invention performs scheduling optimization based on multi-heliostat synthetic light intensity prediction and calibration camera temperature real-time monitoring.
Because meteorological factors such as DNI, field temperature, wind speed and the like can change in real time, the temperature of the calibration camera can also change in real time during sampling, and the number of heliostats which can be sampled by the calibration camera at the same time is different. Therefore, the calibration sampling system pre-queues based on the sampling expected priority, and performs real-time scheduling optimization on heliostat sampling according to multi-heliostat photosynthetic intensity prediction and real-time temperature feedback of a calibration camera.
1) Photosynthetic intensity prediction:
The illumination intensities of the reflecting light spots of the heliostats with different planes are different, one medium-sized heliostat consists of m rows and n columns of mirror surfaces, and the maximum value of the illumination intensity of the reflecting light spots generated by the camera for calibration sampling is approximately equal to that of the small heliostat Multiple times. When the M medium heliostats and the N small heliostats are sampled by using one calibration camera at the same time, multi-light-spot overlapping occurs, and the maximum total light intensity on the calibration camera is as follows:
;
Wherein:
m, the number of medium heliostats;
the number of small heliostats;
m, lens row number of the medium heliostat;
n, lens columns forming the medium heliostat;
r is specular reflectivity;
I i, the illumination intensity of a single lens of the medium heliostat;
I j the illumination intensity of the small heliostat lens;
the sum maximum of illumination intensities of M medium heliostats and N small heliostats;
Meanwhile, DNI is time-of-day, and DNI may generate a surge or dip situation with the appearance and drift of cloud. Resulting in a maximum total light intensity on a single calibration camera In order to ensure that the calibration camera is not damaged by high temperature, the number of heliostats sampled using the calibration camera needs to be automatically adjusted.
For the same calibration camera, when a heliostat enters a sampling pre-queuing waiting state, the maximum total light intensity of the heliostat after the heliostat enters the sampling needs to be estimated. If the maximum photosynthetic intensity which can be born by the calibration camera is exceeded, the heliostat cannot start sampling, the maximum total light intensity needs to be estimated again after the sampling of any heliostat which is being sampled is ended, and the judging process is repeated until the estimated total light intensity is within the allowable range, the heliostat can formally start sampling.
Because the total light intensity of the medium-sized heliostat is X times that of the small-sized heliostat, when the medium-sized heliostat enters a sampling pre-queuing waiting state, the sampling can be formally started after the sampling of a plurality of small-sized heliostats is completed.
In the following, two typical heliostat sampling priorities are taken as an example, and heliostat groups sampled simultaneously by the same calibration camera are scheduled. Taking 3m2 small heliostats (denoted by a) and 30m2 medium heliostats (denoted by B) as examples, it is assumed that the total light intensity of the medium heliostats is 10 times that of the small heliostats, and the upper limit of the number of heliostats in which the calibration camera simultaneously samples is 12 small heliostats.
Examples:
Assume that the sampling is desired prioritized as A1 a 2..a 14 a 15B 1a 16 a 17..a 29 a 30.
The heliostat groups (marked by underline) sampled at the same time are sequentially:
[A1 A2 A3 A4 A5 A6 A7 A8 A9 A10 A11 A12 A13 A14 A15 B1 A16 A17 A18 A19 ...]
[A1 A2 A3 A4 A5 A6 A7 A8 A9 A10 A11 A12 A13 A14 A15 B1 A16 A17 A18 A19 ...]
[A1 A2 A3 A4 A5 A6 A7 A8 A9 A10 A11 A12 A13 A14 A15 B1 A16 A17 A18 A19 ...]
[A1 A2 A3 A4 A5 A6 A7 A8 A9 A10 A11 A12 A13 A14 A15 B1 A16 A17 A18 A19 ...]
[A1 A2 A3 A4 A5 A6 A7 A8 A9 A10 A11 A12 A13 A14 A15 B1 A16 A17 A18 A19 ...]
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[A1 A2 A3 A4 A5 A6 A7 A8 A9 A10 A11 A12 A13 A14 A15 B1 A16 A17 A18 A19 ...]
[A1 A2 A3 A4 A5 A6 A7 A8 A9 A10 A11 A12 A13 A14 A15 B1 A16 A17 A18 A19 ...]
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[... A15 B1 A16 A17 A18 A19 A20 A21 A22 A23 A24 A25 A26 A27 A28 A29 A30...]
[... A15 B1 A16 A17 A18 A19 A20 A21 A22 A23 A24 A25 A26 A27 A28 A29 A30...]
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2) Monitoring the temperature of a camera in real time:
When heliostat field heliostat is sampled, a plurality of heliostats can be simultaneously sampled by using the same calibration camera, and the temperature of the calibration camera is gradually increased along with the increase of the number of heliostat spots. The upper temperature tolerance limit of the calibration camera and the energy of the heliostat reflected light spots determine the upper limit of the number of heliostats that are sampled simultaneously. From the perspective of full-field calibration, the more heliostats are sampled simultaneously, the higher the field calibration efficiency and the shorter the calibration period. Therefore, in order to sample more heliostats simultaneously on the premise of ensuring the safety of the calibration camera, a temperature sensor is arranged in the calibration camera to feed back the temperature to a calibration control system in real time, so that the scheduling of the heliostats can be flexibly adjusted.
The temperature is divided into a normal temperature region, a warning temperature region and a super Wen Wenou when the camera is calibrated for sampling. The calibration control system may schedule a plurality of heliostats in a "standby" state to enter a "sampling" state when the camera temperature is at a normal temperature zone. As the number of simultaneous samples increases, the camera temperature gradually increases and exceeds the lower limit of the warning temperature zone, and the calibration control system maintains the current heliostat sample and no longer adds a new "standby" state heliostat to enter the "sampling" state. Due to the effects of increased DNI, increased number of simultaneously sampled heliostats, or other factors, the temperature of the camera in the warning temperature zone may continue to rise and exceed the lower limit of Wen Wenou, at which point, to protect the safety of the camera hardware, the calibration control system must control all heliostats to immediately stop sampling until the camera temperature falls to the normal temperature zone, and reschedule the heliostats to begin sampling.
Fourth, a facula motion trail prediction algorithm:
The sampling scheduling algorithm provided by the invention is used for controlling and optimizing based on the heliostat reflected light spot movement track prediction algorithm.
In order to prevent the calibration camera from being irradiated by the reflection light spots of the heliostat rotating randomly in the mirror field, the invention provides a prediction algorithm based on the movement track of the reflection light spots, and the algorithm can control the rotation distance of the heliostat in the horizontal and vertical directions by calculating the intersection point of rays and objects in a space coordinate system so as to prevent the calibration camera from being damaged due to temperature shock when the reflection light spots of a plurality of heliostats are irradiated simultaneously.
The ray reflected by the heliostat to the sunlight, i.e., the ray in space, can be expressed by a parametric equation. Let the ray start point beThe direction vector isThen any point on the rayCan be expressed asWherein t is greater than or equal to 0.t is a parameter that determines the position of a point on a ray. When t=0, the number of times of the process is,With increasing, the point moves in the direction of the ray.
Establishing a spatial cuboid model for calibrating a camera, the axis-aligned cuboid can be represented by six plane equations, respectively,,,,,. To determine whether the ray intersects the cuboid, it is necessary to determine the intersection of the ray and the six planes, respectively. For each plane, substituting the ray parameter equation into the plane equation according to the calculation method of intersecting the ray and the plane(Wherein,Is a planar normal vectorCoordinates of (c) and a t value is obtained. If the value of t for all planes does not satisfy t≥0, or the determined intersection point coordinates are not within the range of a cuboid (e.g., for planesFinding that the coordinates of the intersection point are greater thanOr is smaller than) Then the ray does not intersect the cuboid.
And determining to perform horizontal axis rotation or vertical axis rotation by utilizing the pre-calculation of the reflected ray position of the solar facula of the heliostat at the next moment, thereby completing the safe path of the reflected facula so as to avoid all calibration cameras and other devices of the mirror field, and finally moving to the sampling waiting position near the calibration camera of the current sampling combination of the heliostat.
Fifth, image processing and flare recognition:
1) Background diagram interception:
before starting sampling of a pre-queuing heliostat, capturing a screenshot region of interest image as a background image frame to be sampled of the heliostat according to the image coordinate position of the heliostat and the region of interest of the heliostat 。
2) Background difference and binarization processing:
After the heliostat enters a sampling starting stage from a pre-queuing state, a calibration camera starts to capture the light spots of the interested region of the heliostat in real time, and the sizes and pixel values of expected light spots are different for heliostats with different sizes. Collecting a flare image identified in a camera as a foreground image frame Taking the pixel difference value of the foreground image and the background image and taking the absolute value as the difference image of the sampling light spot:
;
After obtaining the light spot differential image, performing binarization processing on pixel points in the differential image, wherein different threshold values are required to be set as the light spot sizes and the intensities of heliostats with different sizes are different, and finally obtaining the binarization image of the light spot of the heliostat。
3) Spot identification:
Firstly, the light spot identification process utilizes a contour detection algorithm to extract the contour in the binarized image. And adopting a Canny edge detection algorithm, firstly carrying out Gaussian filtering on a binarized image to smooth noise, then calculating the gradient amplitude and direction of the image, determining edge pixels through non-maximum suppression and double-threshold detection, and finally obtaining a contour through edge connection.
And secondly, analyzing contour features. For the extracted contour, the length, closure, convexity and other characteristics of the contour can be analyzed. For heliostat reflected spots, the profile is typically closed, and the spot profile is typically approximately circular. For a spot of approximately circular shape, there is a relationship between the contour length and the area, and this feature is used to determine whether it is a spot, and discarding the image that fails to be identified.
And thirdly, calculating pixel coordinates corresponding to the central point of the light spot by using a centroid algorithm, and converting the pixel coordinates into angles of heliostats Az and El. Meanwhile, the angle of Az and El can be converted into the number of steps of the heliostat stepper motor.
Fourth, in the sampling process, the heliostat continuously rotates, the calibration camera continuously acquires the reflection light spot, and simultaneously, the angles of the heliostat Az and El and the stepping number of the heliostat stepping motor are continuously converted.
And finally, carrying out averaging treatment on the step number set obtained by sampling to obtain Az and El step numbers of heliostats under the sampling combination and related sampling information, namely, obtaining complete sample data.
Conventional tower photo-thermal fields typically have only small heliostats or only medium heliostats. In the large-scale mirror field, the small heliostat has the advantages of accurate condensation control in the area close to the heat absorption tower, and the medium heliostat with a certain curvature has the advantages of light spots in the area far from the heat absorption tower. At present, the commonly used daytime calibration method cannot be simultaneously applied to the fields of small heliostats and medium heliostats, and the daytime calibration method mainly solves the problem of sampling the fields of the small heliostats and the medium heliostats.
According to the calibration method for the region of interest of the calibration camera, mutual interference between reflected light spots during sampling of heliostats with similar distances can be avoided, so that noise interference during light spot extraction and recognition in the sampling process is eliminated, and the sampling efficiency is improved.
The invention provides a sampling expected queuing algorithm based on tracking accuracy, sampling time consumption estimation and mirror optical efficiency, so that high-efficiency sampling queuing control can be provided for small and medium heliostats at the same time.
The sampling scheduling algorithm provided by the invention performs scheduling optimization based on multi-heliostat synthetic light intensity prediction and calibration camera temperature real-time monitoring, so that the efficiency of sampling scheduling can be improved, and meanwhile, the safe and reliable operation of the calibration camera in the sampling process can be ensured.
The sampling scheduling algorithm provided by the invention is controlled and optimized based on the heliostat reflected light spot movement track prediction algorithm, so that mutual conflict and noise interference in the sampling process can be reduced, and damage to the mirror field equipment caused by irradiation of excessive reflected light spots can be avoided.

Claims (9)

1.一种基于不同面积定日镜镜场的校准采样方法，其特征在于，包括以下步骤：1. A calibration sampling method based on heliostat fields of different areas, characterized in that it comprises the following steps: S1.计算定日镜的跟踪准确度;S1. Calculate the tracking accuracy of the heliostat; S2.计算优先级排序；S2. Calculate the priority ranking; S3.基于采样期望优先级的定日镜采样调度;S3. Heliostat sampling scheduling based on sampling expectation priority; S4.定期轮训；S4. Regular rotation training; S5.基于多定日镜合光强度预测与校准相机温度实时监控进行调度优化，计算最大合光强度是否已达上限，若是返回步骤S3；若否，定日镜开始采样，采样完成后，样本入库；S5. Based on the prediction of the combined light intensity of multiple heliostats and the real-time monitoring of the temperature of the calibration camera, the scheduling optimization is performed to calculate whether the maximum combined light intensity has reached the upper limit. If so, the process returns to step S3; if not, the heliostat starts sampling, and after the sampling is completed, the samples are stored in the warehouse; S6.判断是否达到无法采样条件，若是，结束本次采样；若否返回步骤S2。S6. Determine whether the sampling condition is reached. If so, end the sampling; if not, return to step S2. 2.根据权利要求1所述的基于不同面积定日镜镜场的校准采样方法，其特征在于，还包括步骤S0.校准采样环境的前期准备：2. The calibration sampling method based on heliostat fields of different areas according to claim 1 is characterized in that it also includes step S0. Preliminary preparation of the calibration sampling environment: 定日镜参数设定：小型定日镜指面积为2~3㎡的平面定日镜；中型定日镜指面积为30~40㎡的曲面定日镜，是由多个平面镜按m行n列拼装成的具有一定曲率的凹面镜；Heliostat parameter setting: Small heliostat refers to a flat heliostat with an area of 2~3㎡; medium heliostat refers to a curved heliostat with an area of 30~40㎡, which is a concave mirror with a certain curvature assembled from multiple flat mirrors in m rows and n columns; 校准相机：镜场所需要的校准相机总数量以所有相机的可视范围能将镜场全部定日镜覆盖为准，每个校准相机可以与不同区域的定日镜配对组合，每个定日镜也能够与多个校准相机进行配对组合；Calibration cameras: The total number of calibration cameras required for the mirror field is based on the visual range of all cameras covering all heliostats in the mirror field. Each calibration camera can be paired with heliostats in different areas, and each heliostat can also be paired with multiple calibration cameras. 日间采样，采样时相机画面中定日镜反射光斑较亮，而其他区域呈现为暗黑色；During daytime sampling, the light spot reflected by the heliostat in the camera image is brighter, while other areas appear dark; 采样组合：由定日镜、校准相机、太阳光源三部分组成，每个校准相机根据其视野中的实际小型、中型定日镜会组成N多个采样组合；采样组合用[Ci, Hi, Li]表示；其中，校准相机用C表示，定日镜用H表示，太阳光源用L表示；Sampling combination: It consists of three parts: heliostat, calibration camera, and solar light source. Each calibration camera will form N sampling combinations according to the actual small and medium heliostats in its field of view. The sampling combination is represented by [C i , H i , L i ], where the calibration camera is represented by C, the heliostat is represented by H, and the solar light source is represented by L. 相机标定：Camera calibration: 通过相机标定，确定定日镜ID与相机像素坐标的映射关系：Through camera calibration, determine the mapping relationship between the heliostat ID and the camera pixel coordinates: ； ; 感兴趣区域标定：在相机标定时，为相机视野中的每个定日镜确定光斑检测边界，以消除采样时光斑检测的噪声干扰，在一个定日镜开始采样后，该定日镜的光斑检测边界内的其他定日镜无法使用该相机进行采样，该区域称为相机感兴趣区域。Region of Interest calibration: During camera calibration, the spot detection boundary is determined for each heliostat in the camera field of view to eliminate noise interference in spot detection during sampling. After a heliostat starts sampling, other heliostats within the spot detection boundary of the heliostat cannot use the camera for sampling. This area is called the camera region of interest. 3.根据权利要求1所述的基于不同面积定日镜镜场的校准采样方法，其特征在于，计算该定日镜的跟踪准确度，步骤如下：3. The calibration sampling method based on heliostat fields of different areas according to claim 1, characterized in that the tracking accuracy of the heliostat is calculated by the following steps: 定日镜有两个驱动电机，分别控制定日镜在方位角和俯仰角方向上转动；The heliostat has two drive motors, which control the heliostat in azimuth and and pitch angle Rotate in direction; 每个采样组合经过采样过程成功采集到一个样本，该样本的实际角度为，而该样本的理论角度为，那么，该样本中两个驱动电机的角度差分别为：Each sampling combination successfully collects a sample after the sampling process, and the actual angle of the sample is , and the theoretical perspective of this sample is , then the angle differences between the two drive motors in this sample are: ； ; ； ; 通过该定日镜基于不同采样组合采集到的多个不同角度的样本，计算最终跟踪准确度为：The final tracking accuracy is calculated by using multiple samples at different angles collected by the heliostat based on different sampling combinations: ； ; 其中：in: R：定日镜的跟踪准确度；R: tracking accuracy of the heliostat; ：每个定日镜的样本数量； : The number of samples for each heliostat; 校准采样准备阶段会计算所有定日镜的跟踪准确度，当采集到新的样本后，重新计算定日镜的跟踪准确度，并更新所有定日镜的跟踪准确度排序。The tracking accuracy of all heliostats is calculated during the calibration sampling preparation phase. When new samples are collected, the tracking accuracy of the heliostats is recalculated and the tracking accuracy ranking of all heliostats is updated. 4.根据权利要求1所述的基于不同面积定日镜镜场的校准采样方法，其特征在于，中型定日镜面积更大，其单次采样耗时比小型定日镜更长，对于同一个定日镜，每天不同时刻的太阳高度角不同，导致采样耗时长短不同，因此，以小时为划分单位，通过采样时所处的小时时段，计算相同小时时段、相同类型定日镜的有效样本的采样耗时均值，作为当前采样的耗时估计值；不同季节相同小时时段的太阳高度角存在差异，因此，计算采样耗时均值时，使用该小时时段内按样本采集时间倒序排列获取的设定数量样本。4. The calibration sampling method based on heliostat fields of different areas according to claim 1 is characterized in that a medium-sized heliostat has a larger area and its single sampling time is longer than that of a small heliostat. For the same heliostat, the solar altitude angle at different times of the day is different, resulting in different sampling times. Therefore, taking hours as the division unit, the sampling time average of valid samples of the same type of heliostats in the same hourly period is calculated according to the hourly period when sampling is performed, as the estimated time of the current sampling; the solar altitude angle of the same hourly period in different seasons is different, therefore, when calculating the sampling time average, a set number of samples obtained in the hourly period in reverse order of sample collection time are used. 5.根据权利要求4所述的基于不同面积定日镜镜场的校准采样方法，其特征在于，计算当前小时时段中型定日镜和小型定日镜的耗时比分别为：5. The calibration sampling method based on heliostat fields of different areas according to claim 4 is characterized in that the time consumption ratios of the medium-sized heliostat and the small-sized heliostat in the current hour period are calculated as follows: ； ; ； ; 其中：in: ρtM：中型定日镜的采样耗时比；ρ tM : sampling time ratio of medium-sized heliostat; ρtS：小型定日镜的采样耗时比；ρ tS : sampling time ratio of small heliostat; Tj：中型定日镜采样样本的耗时；T j : time taken by the medium-sized heliostat to collect samples; J：中型定日镜采样样本的数量；J: number of samples collected by medium-sized heliostats; Tk：小型定日镜采样样本的耗时；T k : time taken by a small heliostat to collect samples; K：小型定日镜采样样本的数量；K: the number of samples collected by small heliostats; 综合定日镜跟踪准确度、定日镜采样耗时比和定日镜的光学效率值的采样期望计算公式为：The sampling expectation calculation formula of the comprehensive heliostat tracking accuracy, heliostat sampling time ratio and heliostat optical efficiency value is: ； ; 定日镜光学效率参数公式为：The formula for the optical efficiency parameter of the heliostat is: ； ; 其中：in: E：定日镜采样的期望值；E: expected value of heliostat sampling; R：定日镜跟踪准确度；R: heliostat tracking accuracy; ρ：定日镜采样耗时比；ρ: heliostat sampling time ratio; η：定日镜的光学效率值；η: optical efficiency value of heliostat; k1、k2：动态调节系数；k 1 , k 2 : dynamic adjustment coefficients; ：定日镜的光学效率值； : optical efficiency value of heliostat; ：定日镜反射率； : heliostat reflectivity; ：定日镜曲率； : heliostat curvature; ：定日镜的余弦效率； : cosine efficiency of the heliostat; ：定日镜的阴影遮挡效率； : Shadow blocking efficiency of heliostat; ：大气透射率； : atmospheric transmittance; 镜场定日镜开始采样前，计算每个定日镜的采样期望值，期望值越大，则采样优先级越高。Before the heliostats in the mirror field start sampling, the sampling expected value of each heliostat is calculated. The larger the expected value, the higher the sampling priority. 6.根据权利要求1所述的基于不同面积定日镜镜场的校准采样方法，其特征在于，步骤S5中光合强度预测：不同面型定日镜反射光斑的光照强度不同，一个中型定日镜由m行n列镜面组成，其反射光斑对校准采样的相机产生的光照强度最大值近似为小型定日镜的倍；当M个中型定日镜与N个小型定日镜同时使用一个校准相机进行采样时，会出现多光斑重叠，则该校准相机上的最大合光强度为：6. The calibration sampling method based on heliostat fields of different areas according to claim 1 is characterized in that in step S5, the photosynthetic intensity prediction is as follows: the illumination intensities of the reflected light spots of heliostats of different surface types are different, and a medium-sized heliostat is composed of m rows and n columns of mirrors, and the maximum illumination intensity generated by its reflected light spot to the calibration sampling camera is approximately equal to that of a small heliostat. times; when M medium-sized heliostats and N small heliostats use one calibration camera for sampling at the same time, multiple spots will overlap, and the maximum combined light intensity on the calibration camera is: ； ; 其中：in: M：中型定日镜的数量；M: number of medium-sized heliostats; N：小型定日镜的数量；N: number of small heliostats; m：组成中型定日镜的镜片行数；m: the number of rows of mirrors that make up a medium-sized heliostat; n：组成中型定日镜的镜片列数；n: the number of mirror columns that make up the medium-sized heliostat; R：镜面反射率；R: specular reflectivity; Ii：中型定日镜单镜片的光照强度；I i : illumination intensity of a single lens of a medium-sized heliostat; Ij：小型定日镜镜片的光照强度。I j : Light intensity of small heliostat lens. 7.根据权利要求1所述的基于不同面积定日镜镜场的校准采样方法，其特征在于，镜场定日镜采样时，多个定日镜会同时使用同一个校准相机进行采样，随着定日镜光斑数量的增加，该校准相机温度逐步升高，校准相机的耐温上限和定日镜反射光斑的能量决定了同时进行采样的定日镜数量上限；7. The calibration sampling method based on heliostat fields of different areas according to claim 1 is characterized in that when sampling heliostats in the field, multiple heliostats will use the same calibration camera for sampling at the same time, and as the number of heliostat spots increases, the temperature of the calibration camera gradually increases, and the upper temperature limit of the calibration camera and the energy of the heliostat reflected spot determine the upper limit of the number of heliostats that can sample at the same time; 校准相机采样时将温度划分为常温温区、警告温区、超温温区：相机温度处于常温温区时，校准控制系统可以调度多个“待命”状态的定日镜进入“正在采样”状态；随着同时采样数量的增大，相机温度逐步升高至警告温区时，校准控制系统维持当前的定日镜采样并不再增加新的“待命”状态的定日镜进入“正在采样”状态；由于DNI增大、同时采样定日镜数量增加或其他因素的影响，处于警告温区的相机的温度可能会继续升高至超温温区，此时，所有定日镜立即停止采样。When the calibration camera samples, the temperature is divided into normal temperature zone, warning temperature zone, and over-temperature zone: when the camera temperature is in the normal temperature zone, the calibration control system can dispatch multiple heliostats in the "standby" state to enter the "sampling" state; as the number of simultaneous sampling increases, when the camera temperature gradually rises to the warning temperature zone, the calibration control system maintains the current heliostat sampling and no longer adds new heliostats in the "standby" state to enter the "sampling" state; due to the increase of DNI, the increase in the number of simultaneous sampling heliostats or other factors, the temperature of the camera in the warning temperature zone may continue to rise to the over-temperature zone. At this time, all heliostats immediately stop sampling. 8.根据权利要求1所述的基于不同面积定日镜镜场的校准采样方法，其特征在于，对于同一个校准相机，当一个定日镜已进入采样预排队等待状态时，需要预估该定日镜进入采样后的最大合光强度；如果超过校准相机能承受的最大光合强度，则该定日镜无法开始采样，需要等待正在采样的任一定日镜采样结束后再重新预估最大合光强度，重复这个判断过程，直到预估合光强度在容许范围之内时，该定日镜才可以正式开始采样；8. The calibration sampling method based on heliostat fields of different areas according to claim 1 is characterized in that, for the same calibration camera, when a heliostat has entered the sampling pre-queue waiting state, it is necessary to estimate the maximum combined light intensity of the heliostat after entering the sampling state; if it exceeds the maximum photosynthetic intensity that the calibration camera can withstand, the heliostat cannot start sampling, and it is necessary to wait for any heliostat that is sampling to finish sampling before re-estimating the maximum combined light intensity, and repeat this judgment process until the estimated combined light intensity is within the allowable range, and the heliostat can officially start sampling; 由于中型定日镜的合光强度是小型定日镜的X倍，中型定日镜已进入采样预排队等待状态时，需要等待多个小型定日镜完成采样后才能正式开始采样。Since the combined light intensity of a medium-sized heliostat is X times that of a small-sized heliostat, when a medium-sized heliostat has entered the sampling pre-queue waiting state, it is necessary to wait for multiple small-sized heliostats to complete sampling before officially starting sampling. 9.一种基于不同面积定日镜镜场的校准采样系统，采用如权利要求1-8任一所述基于不同面积定日镜镜场的校准采样方法，其特征在于，包括信号采集单元、处理单元和输出单元；9. A calibration sampling system based on heliostat fields of different areas, using the calibration sampling method based on heliostat fields of different areas as claimed in any one of claims 1 to 8, characterized in that it comprises a signal acquisition unit, a processing unit and an output unit; 信号采集单元：获取处理信号；Signal acquisition unit: obtains and processes signals; 处理单元：计算定日镜的跟踪准确度；计算期望优先级，基于采样期望优先级的定日镜采样调度；基于多定日镜合光强度预测与校准相机温度实时监控进行调度优化；Processing unit: calculates the tracking accuracy of the heliostat; calculates the expected priority and schedules the heliostat sampling based on the expected sampling priority; performs scheduling optimization based on the prediction of the combined light intensity of multiple heliostats and the real-time monitoring of the temperature of the calibration camera; 输出单元：对结果进行可视化输出。Output unit: Visualize the results.
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