WO2018210072A1 - 一种基于多目图像识别的定日镜面形检测***及方法 - Google Patents
一种基于多目图像识别的定日镜面形检测***及方法 Download PDFInfo
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- WO2018210072A1 WO2018210072A1 PCT/CN2018/081856 CN2018081856W WO2018210072A1 WO 2018210072 A1 WO2018210072 A1 WO 2018210072A1 CN 2018081856 W CN2018081856 W CN 2018081856W WO 2018210072 A1 WO2018210072 A1 WO 2018210072A1
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- image
- heliostat
- image collector
- view image
- collector array
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/24—Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/24—Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures
- G01B11/245—Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures using a plurality of fixed, simultaneously operating transducers
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24S—SOLAR HEAT COLLECTORS; SOLAR HEAT SYSTEMS
- F24S20/00—Solar heat collectors specially adapted for particular uses or environments
- F24S20/20—Solar heat collectors for receiving concentrated solar energy, e.g. receivers for solar power plants
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24S—SOLAR HEAT COLLECTORS; SOLAR HEAT SYSTEMS
- F24S50/00—Arrangements for controlling solar heat collectors
- F24S50/20—Arrangements for controlling solar heat collectors for tracking
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B23/00—Testing or monitoring of control systems or parts thereof
- G05B23/02—Electric testing or monitoring
-
- 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
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0004—Industrial image inspection
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/50—Depth or shape recovery
- G06T7/55—Depth or shape recovery from multiple images
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/50—Depth or shape recovery
- G06T7/55—Depth or shape recovery from multiple images
- G06T7/571—Depth or shape recovery from multiple images from focus
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24S—SOLAR HEAT COLLECTORS; SOLAR HEAT SYSTEMS
- F24S23/00—Arrangements for concentrating solar-rays for solar heat collectors
- F24S23/70—Arrangements for concentrating solar-rays for solar heat collectors with reflectors
- F24S2023/83—Other shapes
- F24S2023/832—Other shapes curved
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24S—SOLAR HEAT COLLECTORS; SOLAR HEAT SYSTEMS
- F24S23/00—Arrangements for concentrating solar-rays for solar heat collectors
- F24S23/70—Arrangements for concentrating solar-rays for solar heat collectors with reflectors
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24S—SOLAR HEAT COLLECTORS; SOLAR HEAT SYSTEMS
- F24S80/00—Details, accessories or component parts of solar heat collectors not provided for in groups F24S10/00-F24S70/00
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E10/00—Energy generation through renewable energy sources
- Y02E10/40—Solar thermal energy, e.g. solar towers
- Y02E10/47—Mountings or tracking
Definitions
- the invention relates to a heliostat shape detection system and method based on multi-eye image recognition, and belongs to the technical field of heliostat surface shape detection.
- heliostats In a tower solar thermal power station, heliostats reflect and converge the sunlight that illuminates the surface to the heat sink, and then take the solar energy through the heat sink for power generation.
- the surface shape of each heliostat is a high-precision discrete surface with converging characteristics.
- errors In the actual manufacturing process of heliostats, there will be a variety of errors, which will reduce the accuracy of the surface shape, affect the convergence effect of sunlight, and ultimately affect the effective energy obtained by the heat absorber. Therefore, accurate measurement of the shape of the heliostat is required to ensure the power generation efficiency of the tower solar thermal power station.
- the current surface inspection technology is mainly divided into contact type and non-contact type.
- the contact type surface detection method is based on a displacement sensor or a probe, and is not suitable for a precise optical mirror surface, and generates a force on the mirror surface when detecting, which easily affects the detection accuracy.
- a non-contact detection technology solution is based on fringe projection, which directly projects a stripe onto the surface of the object to be measured, and solves the shape of the heliostat through the bending change of the stripe.
- the method is applicable to an object whose surface is a diffuse reflection surface, and when the surface reflectance of the object to be tested is high, it is difficult for the image collector to obtain an effective stripe image, and even the surface shape detection cannot be completed.
- Another non-contact detection technique is to project the fringes onto the screen, then adjust the relative position of the heliostats and the screen, and finally use the image collector to capture the fringe image of the surface of the heliostat to solve the heliostat shape.
- the method needs to adjust the relative position between the image collector, the heliostat and the screen according to the heliostat before each detection, so as to obtain a complete stripe image, and at the same time, the detection environment is required to be high, and the mirror surface to be measured is susceptible to miscellaneous The interference of astigmatism affects the contrast and correctness of the fringe image. Therefore, there is a need for a highly accurate, highly efficient detection method for detecting heliostat shapes having high reflection characteristics.
- the object of the present invention is to provide a non-contact heliostat surface detection system and method based on multi-view image recognition, which does not interact with the surface of the heliostat, and can ensure high precision at the same time. High efficiency heliostat surface inspection.
- a heliostat shape detection system based on multi-view image recognition comprising: a multi-view image collector array, a bracket and a computer, wherein the multi-view image collector array is mounted on a bracket, so that The main optical axes of each image collector are parallel to each other and point to the heliostats.
- the multi-view image collector array is connected to the computer through the data lines, and the collected image data is transmitted to the computer to complete the solution of the heliostat surface shape.
- the image collector of the multi-view image collector array is stably mounted on the bracket at equal intervals, and the number of image collectors in the multi-view image collector array is determined according to the outer shape of the measured heliostat, and It can be installed in the form of a module.
- the number of image collectors in the multi-view image collector array is at least two.
- the multi-view image collector array collects the heliostat images of the corresponding fields of view and transmits them to the computer respectively;
- the deviation of the real image of the same feature point in the plurality of image collectors from the center of the image in the image coordinate system is (X i , Y i ), where i represents the image collector number; and the multi-view image collector array
- the center point is the multi-objective measurement coordinate system (meeting the right-hand rule) origin, the Z-axis points to the heliostat; the center coordinates of each image collector are (x i , y i , 0), and the image collector spacing is L (unit: m); therefore, the multi-objective coordinate system coordinates of each real image point are (x i +X i ⁇ Size Pixel , y i +Y i ⁇ Size Pixel ,0);
- the focal length of the known multi-image image collector array is f
- the coordinates of the equivalent lens center of each image collector are (x i , y i , f); the equivalent lens center point and the corresponding real image are located in the three-dimensional linear equation for
- a single feature point of the heliostat can establish a plurality of three-dimensional line equations in the multi-image image collector array, and the above equation can be used to obtain the relative position of the line intersection in the multi-objective coordinate system.
- the coordinates (x j , y j , z j ) are the relative coordinates of a single feature point of the heliostat;
- the relative position information of the heliostat mirror in the multi-objective measurement coordinate system can be obtained, thereby solving the face shape of the heliostat.
- the system of the invention has simple structure and reasonable design, and can realize high-precision and high-efficiency heliostat surface shape detection by non-contact detection without interaction with the surface of the heliostat;
- the present invention calculates the relative position information of the measured surface by the original understanding of multi-track ranging, and is insensitive to the surface reflectivity characteristic of the measured object;
- the invention solves the shape of the heliostat according to the characteristic information of the surface, and can effectively detect the shape of the continuous type and the discrete heliostat, and has wide application range;
- the heliostats with similar external dimensions only need to be first calibrated to complete batches of various shapes.
- the detection is easy to operate and implement, and the detection efficiency is improved; the surface of the measured daylight is directly photographed by the multi-image image collector array, which is not easily affected by stray light and has good anti-interference performance.
- Figure 1 is a schematic view of a detection system of the present invention
- FIG. 2 is a schematic diagram of an array of multi-view image collectors in the present invention.
- Figure 3 is a schematic view of multi-eye imaging of the present invention.
- FIG. 4 is a schematic diagram showing deviations of a real image of a same feature point in a plurality of image collectors from an image center in an image coordinate system according to the present invention.
- Multi-view image collector array 2. Bracket; 3. Computer; 4. Heliostat; 5. Real image.
- a heliostat shape detection system based on multi-view image recognition includes a multi-view image collector array 1, a bracket 2 and a computer 3, and the multi-view image collector array 1 is installed in The bracket 2 is such that the main optical axes of each image collector are parallel to each other and directed to the heliostats 4, and the multi-view image collector array 1 is connected to the computer 3 through the data lines, and the collected image data is transmitted to the computer 3 to complete the date.
- the image collector of the multi-view image collector array 1 is stably mounted on the bracket 2 at equal intervals, and the number of image collectors in the multi-view image collector array 1 is determined according to the outer dimensions of the measured heliostat 4, and
- the module is installed in the form of a module; the number of image collectors in the multi-view image collector array 1 is at least two.
- a heliostat shape detection method based on multi-view image recognition which reconstructs the three-dimensional shape of the daylight to be measured by measuring the elevation angle and the roll angle of each sub-mirror, including the following steps:
- the distance of the heliostat 4 to the bracket 2 and the number of image collectors in the multi-view image collector array 1 are determined according to the outer dimensions of the heliostat 4;
- the multi-view image collector array 1 is stably mounted on the support 2, each image collector is adjusted such that their main optical axes are parallel to each other and aligned with the heliostat 4;
- multi-view image collector array 1 to collect the corresponding field of view of the heliostat image and then transmitted to the computer 3;
- the deviation of the real image 5 of the same feature point in the plurality of image collectors from the center of the image in the image coordinate system is (X i , Y i ), where i represents the image collector number;
- the center point of the multi-view image collector array 1 is the multi-objective measurement coordinate system (meeting the right-hand rule) origin, and the Z-axis points to the heliostat;
- the center coordinates of each image collector are (x i , y i , 0), and the image
- the collector spacing is L (unit: m); therefore, the multi-objective coordinate system coordinates of each real image point are (x i +X i ⁇ Size Pixel , y i +Y i ⁇ Size Pixel ,0);
- the focal length of the known multi-image image collector array 1 is f
- the coordinates of the equivalent lens center of each image collector are (x i , y i , f); the equivalent lens center point and the corresponding real image 5 are located in three dimensions
- the linear equation is
- a single feature point of the heliostat 4 can establish a plurality of three-dimensional line equations in the multi-image image collector array 1, and the above equation can be used to obtain a line intersection point in the multi-objective coordinate system.
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Abstract
Description
Claims (4)
- 一种基于多目图像识别的定日镜面形检测***,其特征在于:包括多目图像采集器阵列(1)、支架(2)和计算机(3),所述的多目图像采集器阵列(1)安装在支架(2),使得每个图像采集器的主光轴相互平行,并且指向定日镜(4),多目图像采集器阵列(1)通过数据线与计算机(3)相连,将采集的图像数据传输到计算机(3)完成定日镜面形的解算。
- 根据权利要求1所述一种基于多目图像识别的定日镜面形检测***,其特征在于:所述的多目图像采集器阵列(1)的图像采集器等间距稳定地安装在支架(2)上,多目图像采集器阵列(1)中图像采集器的数量根据被测定日镜(4)的外形尺寸确定,并可以模块的形式进行安装。
- 根据权利要求1所述的一种基于多目图像识别的定日镜面形检测***,其特征在于:所述多目图像采集器阵列(1)中图像采集器的个数为至少2个。
- 一种基于多目图像识别的定日镜面形检测方法其特征在于:通过测量每个子镜的俯仰角和滚转角重建待测定日镜的三维面形,包括如下步骤:(1)、根据定日镜(4)的外形尺寸确定定日镜(4)至支架(2)的距离和多目图像采集器阵列(1)中图像采集器的个数(至少2个);(2)、将多目图像采集器阵列(1)稳定地安装在支架(2)上,调节每个图像采集器,使得它们的主光轴相互平行并对准定日镜(4);(3)、多目图像采集器阵列(1)采集相应视场的定日镜图像后分别传输给计算机(3);(4)、通过图像识别技术中的特征识别技术对采集所得的图像数据进行特征匹配,确定多个图像采集器公共视场中的相应特征点;即定日镜(4)的一个 特征点在多目图像采集器阵列(1)对应的每个图像采集器上都会有一个实像(5);(5)、同一特征点在多个图像采集器中的实像(5)在图像坐标系中与图像中心的偏差为(X i,Y i),其中i表示图像采集器编号;以多目图像采集器阵列(1)的中心点为多目测量坐标系(满足右手定则)原点,Z轴指向定日镜;各个图像采集器中心坐标为(x i,y i,0),图像采集器间距为L(单位:m);所以,各个实像点的多目测量坐标系坐标为(x i+X i·Size Pixel,y i+Y i·Size Pixel,0);(6)、已知多目图像采集器阵列(1)的焦距为f,则各个图像采集器等效镜头中心的坐标为(x i,y i,f);等效镜头中心点与相应实像(5)所在三维直线方程为(7)、根据式(1),定日镜(4)的单个特征点可以多目图像采集器阵列(1)中建立多个三维直线方程,联列上述方程可求得直线交点在多目测量坐标系中的相对坐标(x j,y j,z j),即为定日镜(4)的单个特征点的相对坐标;(8)、重复上述过程,可获得定日镜(4)镜面在多目测量坐标系中的相对位置信息,从而解算定日镜(4)的面型。
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EP18788983.7A EP3627097A4 (en) | 2017-05-18 | 2018-04-04 | SYSTEM AND METHOD FOR MEASURING HELIOSTAT SURFACE SHAPE BASED ON MULTI-VIEW IMAGE RECOGNITION |
AU2018268608A AU2018268608B2 (en) | 2017-05-18 | 2018-04-04 | Heliostat surface shape detection system and method based on multi-view image recognition |
US16/194,292 US10697670B2 (en) | 2017-05-18 | 2018-11-17 | Heliostat surface shape detection system and method based on multi-view image recognition |
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CN201710353911.6A CN107167092B (zh) | 2017-05-18 | 2017-05-18 | 一种基于多目图像识别的定日镜面形检测***及方法 |
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US16/194,292 Continuation US10697670B2 (en) | 2017-05-18 | 2018-11-17 | Heliostat surface shape detection system and method based on multi-view image recognition |
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US20190086122A1 (en) * | 2017-05-18 | 2019-03-21 | Shanghai Parasol Renewable Energy Co., Ltd | Heliostat Surface Shape Detection System and Method Based on Multi-View Image Recognition |
CN110658858A (zh) * | 2019-10-19 | 2020-01-07 | 天合光能股份有限公司 | 一种基于智能光伏组件的不平坦地势逆跟踪方法 |
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CN108562245A (zh) * | 2018-03-28 | 2018-09-21 | 西安理工大学 | 一种定日镜三维测量方法 |
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CN107167092A (zh) | 2017-09-15 |
AU2018268608A1 (en) | 2018-12-13 |
CN107167092B (zh) | 2019-12-13 |
US10697670B2 (en) | 2020-06-30 |
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US20190086122A1 (en) | 2019-03-21 |
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