WO2020218113A1 - Contamination inspection device, contamination inspection method, and solar power generation module management method - Google Patents

Abstract

In this invention, an imaging device is used to capture an image of a partial area of a surface under inspection that is covered by a housing and illuminated with light from an illumination device. The degree of contamination of the surface under inspection is calculated on the basis of the color coordinates in a color space of each pixel in a measurement image captured by the imaging device and reference color coordinates in the color space.

Description

Stain inspection device, stain inspection method, and management method of photovoltaic power generation module

The present invention relates to a dirt inspection device, a dirt inspection method, and a method for managing a photovoltaic power generation module.

In the photovoltaic power generation module, it is important that the incident light reaches the solar cell without being diffusely reflected on the light receiving surface. As a factor of diffused reflection on the light receiving surface, dirt on the light receiving surface due to adhesion of dust, salt, oil, air pollutants, vegetation species, etc. can be considered. Due to the dirt on the light receiving surface, the amount of light reaching the solar cell decreases, and the generated power of the photovoltaic power generation module decreases.

In this regard, Patent Document 1 forms an antifouling thin film having a coating surface in which a hydrophilic region and a hydrophobic region are mixed on the glass surface on the light receiving surface side of the solar cell module. Patent Document 1 makes it possible to efficiently remove dust and the like adhering to the light receiving surface with a small amount of rainfall or the like by forming an antifouling thin film.

However, even if the light receiving surface is provided with antifouling properties, it is very difficult to completely prevent the light receiving surface from becoming dirty, and in reality, the light receiving surface becomes dirty over time. Therefore, in order to recover the reduced generated power, it is necessary to clean the light receiving surface of the photovoltaic power generation module at a predetermined time.

Japanese Unexamined Patent Publication No. 2012-256755

However, a method for measuring and quantifying the degree of dirt on the light receiving surface has not yet been established. Therefore, at present, the cleaning time of the light receiving surface is determined by the practical experience or custom of the manager of the photovoltaic power generation module.

In view of the above situation, the first object of the present invention is to provide a stain inspection device and a stain inspection method capable of measuring the degree of stain on the surface to be inspected and quantifying it with high accuracy.

A second object of the present invention is to provide a method for managing a photovoltaic power generation module that can theoretically determine the cleaning time of the light receiving surface.

In order to achieve the above object, the stain inspection device according to one aspect of the present invention captures a housing that covers a part of the surface to be inspected, a lighting device that irradiates the part of the area with light, and the part of the area. The degree of contamination of the surface to be inspected is calculated based on the first color coordinates in the color space of each pixel of the image pickup device and the measurement image captured by the image pickup device, and the reference color coordinates in the color space. It is configured to include an image processing unit (first configuration).

The stain inspection device having the first configuration may have a configuration in which the color space is a three-dimensional color space (second configuration).

In the stain inspection device having the first or second configuration, the image processing unit has a reference in which the second color coordinates are within a reference color range of a predetermined size centered on the reference color coordinates in the color space. The configuration may be such that the reference color coordinates are determined (third configuration) so that the number of pixels of the image is maximized.

Alternatively, in the stain inspection device having the first or second configuration, the image processing unit has a reference color range having a predetermined size centered on the second color coordinates of each pixel of the reference image in the color space. A configuration (fourth configuration) may be used in which the region having the largest overlap is calculated and the reference color coordinates are determined based on the region.

In the stain inspection device having any of the first to fourth configurations, the image processing unit detects pixels of the measurement image having the first color coordinates within the reference color range in the color space. Then, the degree of contamination of the surface to be inspected may be calculated based on the detection result of the pixel (fifth configuration).

In the stain inspection device having any of the first to fifth configurations, the image processing unit further calculates the degree of stain based on the correction value for each color component corresponding to the first color coordinates. (Sixth configuration) may be used.

Further, in order to achieve the above object, the stain inspection method according to one aspect of the present invention is a step of imaging a part of the surface to be inspected covered with a housing and illuminated by a lighting device with an imaging device. A step of calculating the degree of contamination of the surface to be inspected based on the color coordinates in the color space of each pixel of the measurement image captured by the image pickup apparatus and the reference color coordinates in the color space. It is said to be a configuration (seventh configuration).

Further, in order to achieve the above object, the method of managing the photovoltaic power generation module according to one aspect of the present invention is to irradiate the housing covering a part of the light receiving surface of the photovoltaic power generation module and the part of the area with light. The illumination device, an image pickup device that images a part of the region, a first color coordinate in the color space of each pixel of the measurement image captured by the image pickup device, and a reference color coordinate in the color space. Using an image processing unit for calculating the degree of contamination of the light receiving surface, the degree of contamination of the light receiving surface of the photovoltaic power generation module is measured, and the generated power of the photovoltaic power generation module is measured. After a predetermined elapsed period from the time when the first measurement step and the first measurement step are performed, the stain degree is measured by using the stain inspection device, and the second measurement for measuring the generated power is performed. A step and a step of determining a cleaning time of the light receiving surface based on the degree of contamination and the generated power measured in the first measurement step and the second measurement step, respectively, and the elapsed period. It is a configuration to be provided (eighth configuration).

In the method of managing the photovoltaic power generation module having the eighth configuration, the correction measurement value of the degree of contamination is calculated in the first measurement step and the second measurement step, and the correction measurement value is the first measurement value. It is a configuration (ninth configuration) in which the measured value of the degree of stain based on the color coordinates and the reference color coordinates is corrected based on the correction value for each color component corresponding to the first color coordinates. May be good.

In the method of managing the photovoltaic power generation module having the eighth or ninth configuration, at least the first measurement step and the second measurement step are carried out at least one of the early morning and the evening of the day. (10th configuration) may be used.

According to the stain inspection device and the stain inspection method of the present invention, the degree of stain on the surface to be inspected can be measured and quantified with high accuracy. Further, according to the management method of the photovoltaic power generation module of the present invention, the cleaning time of the light receiving surface can be theoretically determined.

It is a schematic diagram which shows the structural example of the dirt inspection apparatus. It is a schematic diagram which shows an example of the dirt inspection method using the dirt inspection apparatus. It is a flowchart for demonstrating an example of the stain inspection method using a stain inspection apparatus. It is a flowchart for demonstrating the method of quantifying the degree of dirt in the Example of 1st Embodiment. This is an example of the color space of the reference image in the embodiment. This is an example of the color space of the measured image. It is a flowchart for demonstrating the method of quantifying the degree of dirt in the modification of 1st Embodiment. This is an example of the color space of the reference image in the modified example. It is a flowchart for demonstrating an example of the management method of a photovoltaic power generation module. It is a graph which shows the relationship of the power generation of a photovoltaic power generation module with respect to the solar radiation intensity. It is a schematic diagram which shows the change of the generated power before and after cleaning. It is a flowchart for demonstrating the method of quantifying the degree of dirt in the Example of 2nd Embodiment. It is a flowchart for demonstrating the method of quantifying the degree of dirt in the modification of 2nd Embodiment.

Hereinafter, embodiments of the present invention will be described with reference to the drawings.

<1. First Embodiment>
FIG. 1 is a schematic view showing a configuration example of the dirt inspection device 1. The dirt inspection device 1 according to the present embodiment is mounted on the light receiving surface 301 of the photovoltaic power generation module 300, and inspects the degree of dirt on the light receiving surface 301.

The photovoltaic power generation module 300 is a power generation device that converts light incident on the light receiving surface 301 into electrical energy. The photovoltaic power generation module 300 includes a translucent substrate 310, a sealing resin layer 320, a solar cell 330, and a back film 340. In FIG. 1, the light receiving surface 301 is the upper surface of the substrate 310. A sealing resin layer 320 is provided on the lower surface of the substrate 310. A back film 340 is provided on the lower surface of the sealing resin layer 320. The sealing resin layer 320 is a transparent filler that is filled between the substrate 310 and the back film 340. The solar cell 330 is provided between the substrate 310 and the back film 340, and is sealed by the sealing resin layer 320. Polycrystalline silicon is used for the solar cell 330 in this embodiment. However, the present invention is not limited to this example, and compound semiconductor solar cells using materials such as GaAs-based, Cu-In-Se-based (CIS) -based, Cu-In-Ga-Se-based (CIGS) -based, and CdTe-based materials. A dye-sensitized solar cell or the like may be used. Further, the photovoltaic power generation module 300 further includes a terminal box and a cable (not shown). The terminal box takes out the output of the solar cell 330 and outputs it to the outside of the photovoltaic power generation module 300 through a cable.

<1-1. Dirt inspection device>
As shown in FIG. 1, the stain inspection device 1 includes a housing 11, a lighting device 12, a lighting driving device 13, a camera 14, a memory 15, a control device 16, a display device 17, and an input device 18. , The communication device 19, the external power supply terminal 20, and the built-in power supply 21.

The housing 11 has a cylindrical shape with a covered cylinder. The housing 11 internally houses the lighting drive device 13, the camera 14, the memory 15, the control device 16, the communication device 19, and the built-in power supply 21. A display device 17 and an input device 18 are provided on the lid portion of the housing 11. An external power supply terminal 20 is provided on the tubular portion of the housing 11. Further, the housing 11 has an opening 111 at an end on the light receiving surface 301 side. A lighting device 12 is provided on the inner edge of the opening 111.

When the dirt inspection device 1 is placed on the light receiving surface 301, the housing 11 covers a part of the region Ap of the light receiving surface 301 of the photovoltaic power generation module 300. As a result, the dirt inspection device 1 can perform the measurement in a state where the partial region Ap is shielded from external light, so that the noise of the measurement result can be suppressed. Further, the housing 11 is made of resin in this embodiment. Therefore, even if the housing 11 hits the light receiving surface 301 during mounting, the light receiving surface 301 is less likely to be damaged.

The lighting device 12 irradiates a part of the region Ap of the light receiving surface 301 with light. The illuminating device 12 has a ring-shaped substrate 121 and an LED array 122. The LED array 122 is provided at the radial inner end of the substrate 121 and has a plurality of white LEDs (reference numerals omitted) arranged in the circumferential direction. Each white LED emits white light inward in the radial direction with a predetermined radiation angle, and irradiates at least a part of the white light on a part region Ap of the light receiving surface 301 covered with the housing 11. As will be described later, the partial region Ap is a region for the stain inspection device 1 to measure the degree of contamination of the light receiving surface 301, and in the present embodiment, it is a region having a diameter of φ50 [mm] to φ200 [mm]. is there.

The lighting drive device 13 drives the lighting device 12 based on the control signal output from the control device 16, and particularly controls the light emission of the LED array 122.

The camera 14 is an imaging device that images a partial region Ap of the light receiving surface 301. The number of pixels of the image captured by the camera 14 is about 60,000 to 100,000 in this embodiment. The camera 14 includes a lens 141 and an image sensor 142. The light incident on the light receiving surface 301 from the above-mentioned partial region Ap is incident on the image sensor 142 through the lens 141. A CCD (charge coupled device) image sensor, a CMOS (complementary metal-oxide-semiconductor) image sensor, or the like is used for the image sensor 142.

The memory 15 is a non-transient storage medium that maintains storage even when the power supply is stopped. The memory 15 stores, for example, a program, control information, data, and the like used in each component of the dirt inspection device 1. The memory 15 also stores, for example, image data captured by the camera 14.

The control device 16 controls each component of the dirt inspection device 1 by using the program, control information, data, and the like stored in the memory 15. The control device 16 quantifies the degree of contamination of a partial region Ap of the light receiving surface 301 based on the reference image and the measurement image described later. A stain inspection method for measuring the degree of stain and a method for quantifying the degree of stain will be described later.

The control device 16 has an image processing unit 161 that processes an image captured by the camera 14. The image processing unit 161 calculates the degree of contamination of the light receiving surface 301 based on, for example, the color coordinates of each pixel of the measurement image captured by the camera 14 and the reference color coordinates described later. As a result, the degree of contamination of the light receiving surface 301 of the photovoltaic power generation module 300 can be measured and quantified with high accuracy. The measurement image is an image obtained by the camera 14 of the light receiving surface 301 (a part of the region) for which the degree of stain is measured by the stain inspection device 1. The reference color coordinates are color coordinates that serve as a reference when measuring the degree of stain, and in the present embodiment, the reference color coordinates are based on a reference image obtained by imaging (a part of a region) of a clean light receiving surface 301 using the stain inspection device 1. Will be decided. The measurement image and the reference image are captured in a state where the imaging region of the light receiving surface 301 is covered by the housing 11 and the light is irradiated from the lighting device 12. In the present embodiment, the imaging regions of the light receiving surface 301 of the reference image and the measurement image may be the same or different.

The display device 17 displays a measured value of the degree of dirt on a display (not shown) provided on the upper surface of the housing 11.

The input device 18 receives the user's operation input. The input device 18 includes a power ON / OFF button (not shown) for operating the start / stop of the dirt inspection device 1, a teaching start button (not shown) for inputting the execution of teaching described later, and a dirt inspection. It includes a measurement start button (not shown) for inputting the measurement start of the device 1. These buttons are provided on the upper surface of the housing 11.

Although the display device 17 and the input device 18 are provided separately in the present embodiment, the present invention is not limited to this example, and an integrated device such as a touch panel may be used.

The communication device 19 can communicate with the external terminal OT wirelessly or by wire. In this embodiment, two-way wireless communication is possible by Bluetooth (registered trademark). The external terminal OT is, for example, a portable device such as a personal computer or a smartphone. The communication device 19 can transmit, for example, the measurement data of the dirt inspection device 1 (numerical value of the degree of dirt, etc.) to the external terminal OT. The external terminal OT can also operate the dirt inspection device 1 by communicating with the communication device 19.

The external power supply terminal 20 can be electrically connected to the external power supply AC, and the power output from the external power supply AC can be supplied to each component of the dirt inspection device 1.

The built-in power supply 21 is a battery built in the dirt inspection device 1, and can be discharged to supply electric power to each component of the dirt inspection device 1. Further, the built-in power supply 21 can be charged by the electric power supplied from the external power supply AC via the external power supply terminal 20.

<1-2. Dirt inspection method>
Next, a dirt inspection method for the light receiving surface 301 of the photovoltaic power generation module 300 using the dirt inspection device 1 will be described. FIG. 2 is a schematic view showing an example of a stain inspection method using the stain inspection device 1. FIG. 3 is a flowchart for explaining an example of a stain inspection method using the stain inspection device 1. Note that FIG. 2 shows the positional relationship between the photovoltaic power generation module 300 and the dirt inspection device 1 when measuring the degree of dirt. Further, the broken line in FIG. 2 represents the center of the light receiving surface 301 of the photovoltaic power generation module 300 in the direction of the vertical width a and the center in the direction of the horizontal width b.

In FIG. 2, the photovoltaic power generation module 300 is installed outdoors and is installed at an inclination angle θv vertically upward with respect to the horizontal ground Hp. The vertical width of the photovoltaic power generation module 300 is, for example, a = 1.0 [m], and the horizontal width is, for example, b = 1.7 [m]. The inclination angle θv is, for example, 0 ° to 30 °.

In the stain inspection method using the stain inspection device 1, as shown in FIG. 3, after teaching the stain inspection device 1, the degree of contamination of the light receiving surface 301 is actually measured. By this dirt inspection method, the degree of dirt on the light receiving surface 301 of the photovoltaic power generation module 300 can be measured and quantified with high accuracy. The teaching is a step of setting a standard for the degree of dirt on the dirt inspection device 1. Further, in the present embodiment, the degree of contamination of the light receiving surface 301 is quantified from 0 to 100. The measured value of the degree of contamination is 100 on the clean light receiving surface 301, and becomes smaller as the light receiving surface 301 becomes dirty. If dirt can be visually confirmed, the measured value is, for example, about 23 to 24.

First, the reference region L0 on the light receiving surface 301 and its vicinity are washed with pure or purified water to be cleaned (S101). Then, the stain inspection device 1 is placed on the reference region L0, and when the teaching start button is pressed, a clean RGB color reference image of the reference region L0 is imaged (S103). The image processing unit 161 performs teaching based on the reference image (S105). The specific content of teaching will be described later.

Next, the degree of dirt on the light receiving surface 301 is actually measured using the taught dirt inspection device 1. In this step, first, the stain inspection device 1 is placed on the measurement area L1 on the light receiving surface 301, and when the measurement start button is pressed, the RGB color measurement image of the measurement area L1 is imaged (S111). .. The imaging in the measurement area L1 may be performed once or a plurality of times. The image processing unit 161 digitizes the degree of contamination in the measurement area L1 based on the captured image in the measurement area L1 and calculates the measured value (S113). The display device 17 displays the calculated measured value on the display (S115). The user can look at the display and read the measured value in the measurement area L1. The dirt inspection device 1 can also transmit the measured value to the external terminal OT.

The same processing as in steps S111 to S115 is performed in the measurement areas L2 to L5 (NO in step S117). Although the number of measurement regions is five in the present embodiment, the number of measurement regions is not limited to this example, and may be one or a plurality of measurement regions other than five.

When the measurement in all the measurement areas is completed (YES in step S117), the degree of contamination of the light receiving surface 301 of the photovoltaic power generation module 300 is calculated based on the measured values in each measurement area L1 to L5 (S119). .. For example, the average value of the measured values in all the measurement areas L1 to L5 is calculated. At this time, for example, by inputting the number of measurement points into the dirt inspection device 1 in advance, the control device 16 may calculate the average value of all the measured values and display it on the display device 17. Alternatively, the average value of all the measured values may be calculated by the external terminal and displayed on the display (not shown) of the external terminal.

In the stain inspection method of FIG. 2, teaching is carried out using the photovoltaic power generation module 300 to be inspected for measuring the degree of stain. However, the teaching is not limited to this example, and the teaching may be performed using a photovoltaic power generation module different from the inspection target. In this case, the photovoltaic power generation module to which the teaching is performed preferably has the same or similar configuration as the photovoltaic power generation module 300 to be inspected for measuring the degree of contamination. Further, the teaching may be performed in advance at a place where the photovoltaic power generation module 300 to be inspected is different from the installation place before the actual measurement of the degree of dirt. Alternatively, the teaching does not have to be performed every time the actual measurement is performed, and the teaching settings used in the previous actual measurement may be used as they are.

Further, in FIGS. 2 and 3, an example of inspection at a small-scale solar power plant was explained. On the other hand, for example, in a large-scale photovoltaic power plant with a generated power of 1 [MW] or more, the photovoltaic power generation modules are installed in a plurality of places and the size of each photovoltaic power generation module is large. The degree of dirt on the light receiving surface tends to be uneven. In such a case, for example, identify a place that is relatively easily soiled due to the influence of the surrounding environment, perform measurement with the photovoltaic power generation module installed at each specified place, and average the measured values. Should be the degree of dirtiness of the photovoltaic power plant.

<1-3. Quantification of degree of dirt>
Next, an example of the method for quantifying the degree of dirt in the first embodiment and a modified example thereof will be described.

<1-3-1. Example>
FIG. 4 is a flowchart for explaining a method for quantifying the degree of contamination in the embodiment of the first embodiment. FIG. 5A is an example of the color space of the reference image in the embodiment. FIG. 5B is an example of the color space of the measured image. In FIG. 5A, the black circles are the pixels Pa of the reference image. In FIG. 5B, the circles are pixels Pb of the measurement image. Further, in FIGS. 5A and 5B, the number of pixels Pa and Pb shown is significantly smaller than the actual number in order to make the figure easier to see.

The color space is a three-dimensional virtual space in which the hue is represented by the size of the color component R (Red), the size of the color component G (Green), and the size of the color component B (Blue). Hereinafter, the magnitude of the color component R (Red) is referred to as an R component value. Further, the size of the color component G (Green) is called the G component value, and the size of the color component B (Blue) is called the B component value. The hue coordinates (R, G, B) in the color space are represented by the R component value, the G component value, and the B component value. In the present embodiment, each color component value is represented by 16 gradations (that is, 0 to 15) in consideration of the calculation load. However, the number of gradations of each color component value is not limited to this example. For example, the number of gradations may be 256.

First, during teaching in the reference region L0 (see FIG. 2), as shown in FIG. 5A, the image processing unit 161 calculates the R component value, the G component value, and the B component value of each pixel Pa of the reference image. Then, the pixel Pa having each color component value as the color coordinate (R, G, B) is drawn in the color space (S301). The color coordinates of the pixel Pa of the reference image are an example of the "second color coordinates" of the present invention. The image processing unit 161 draws a spherical region having a predetermined radius r in the color space of the reference image (S303). Hereinafter, this spherical region is referred to as a reference sphere Sa. The reference sphere Sa is an example of the "reference color range" of the present invention. The radius r of the reference sphere Sa is set to 4 gradations in this embodiment. However, the present invention is not limited to this example, and the radius r may be other than 4.

The image processing unit 161 moves the reference sphere Sa in each axial direction in the color space of the reference image. The image processing unit 161 determines the position of the reference sphere Sa so that the number of pixels Pa of the reference image having the color coordinates (R, G, B) in the reference sphere Sa is maximized, and in the reference sphere Sa. Pixels Pa of a reference image having color coordinates (R, G, B) are detected. Hereinafter, the pixel Pa in the reference sphere Sa is referred to as a reference pixel Pam, and the number of reference pixel Pam is referred to as a reference pixel number m. The reference pixel number m is a positive integer, greater than 1 and less than or equal to the total number of pixels constituting the reference image. More specifically, the image processing unit 161 detects the reference color coordinates (Ra, Ga, Ba) that are the center of the reference sphere Sa when the most reference pixels Pam are included inside the reference sphere Sa. .. That is, the reference color coordinates (Ra, Ga, Ba) are the color coordinates (R) in the reference sphere Sa having a predetermined size centered on the reference color coordinates (Ra, Ga, Ba) in the color space of the reference image. , G, B) are set so that a certain reference pixel number m is maximized. Further, the reference pixel number m is also detected (S305). The reference color coordinates (Ra, Ga, Ba) and the reference pixel number m are stored in the memory 15.

Next, for example, when actually measuring the degree of contamination of the light receiving surface 301 in the measurement areas L1 to L5 (see FIG. 2), as shown in FIG. 5B, the image processing unit 161 is used for each pixel Pb of the captured measurement image. The R component value, the G component value, and the B component value are calculated, and pixels Pb having each color component value as color coordinates (R, G, B) are drawn in the color space of the measurement image (S311). The color coordinates (R, G, B) of the pixels of the measured image are an example of the "first color coordinates" of the present invention. The image processing unit 161 further draws a reference sphere Sa having a radius r whose center is located at the reference color coordinates (Ra, Ga, Ba) in the color space of the measurement image (S313). The image processing unit 161 detects the pixels Pb of the measurement image having the color coordinates (R, G, B) in the reference sphere Sa, and detects the number of pixels Pb in the reference sphere Sa (S315). In the present embodiment, the count value of each pixel Pb in the reference sphere Sa is 1 for one pixel Pb. Hereinafter, the pixel Pb in the reference sphere Sa is referred to as a range pixel Pbn, and the number of the range pixel Pbn is referred to as a range pixel number n. The number of pixels n in the range is a positive integer, greater than 1 and less than or equal to the total number of pixels constituting the measurement image.

The image processing unit 161 calculates the degree of contamination of the light receiving surface 301 based on the pixel detection result in S315. For example, the image processing unit 161 calculates the degree of contamination based on the reference pixel number m and the number of pixels in the range n, and calculates the measured value of the degree of contamination by the ratio of the number of pixels in the range n to the reference pixel number m (S317). ). In the present embodiment, the image processing unit 161 calculates the percentage of the value obtained by dividing the number of pixels n in the range by the reference number of pixels m, and uses this as the measured value of the degree of contamination based on the measured image. For example, in the case of FIG. 5B, the measured value is 80. Since the measured value is quantified in the range of 0 to 100, when the number of pixels n in the range is larger than the reference pixel number m (that is, when the percentage exceeds 100), the measured value for the measured image is set to 100. To.

The image processing unit 161 performs the above-mentioned processing every time the camera 14 captures the measured image. When a plurality of measured images are captured when the measurement start button is pressed once, the average value of the measured values with respect to the measured images may be used as a representative measured value in one measurement.

According to the stain inspection method described above, even if the basic image and the measurement image are images of different parts of the light receiving surface 301, the degree of contamination of the light receiving surface 301 of the photovoltaic module 300 is measured. It can be quantified with high accuracy.

<1-3-2. Modification example>
In the above-described embodiment, during teaching, the image processing unit 161 moves the reference sphere Sa by one gradation in each axial direction in the color space of the reference image, and each time, the reference pixel in the reference sphere Sa is moved. Detect a few meters. However, in this method, for example, to become possible to perform the detection process of times (16 ³ in the present embodiment) cube of the number of gradation of each color component values, easy operation load increases. Further, as the number of gradations of each color component value increases, the calculation load increases significantly. In order to reduce such a calculation load, in the modified example, the measured value of the degree of contamination is calculated by the method described below.

FIG. 6 is a flowchart for explaining a method for quantifying the degree of contamination in the modified example of the first embodiment. FIG. 7 is an example of the color space of the reference image in the modified example. In FIG. 7, the black circles are the pixels Pa of the reference image. Further, in FIG. 7, in order to make the figure easier to see, the number of the illustrated pixel Pa and the measurement sphere Sb described later is significantly smaller than the actual number.

In the modified example, when teaching in the reference region L0 (see FIG. 2), as shown in FIG. 7, the image processing unit 161 sets the R component value, the G component value, and the B component value of each pixel Pa of the reference image. Is calculated, and pixels Pa having each color component value as color coordinates (R, G, B) are drawn in the color space (S501).

Then, steps S503 to S505 are performed in order to determine the reference sphere Sa so that the number of reference pixels m having color coordinates (R, G, B) in the reference sphere Sa of the reference image is maximized. First, the image processing unit 161 sets a spherical region (hereinafter, referred to as a measurement sphere Sb) centered on the color coordinates (R, G, B) of each pixel Pa of the reference image in the color space of the reference image. Draw (S503). The measuring ball Sb is an example of the "reference color range" of the present invention. Further, the radius of the measurement sphere Sb is the same as the radius r of the reference sphere Sa of the above-described embodiment. In the color space, the image processing unit 161 has the most overlapping region Ar (FIG. 7) in which the measurement spheres Sb having a predetermined size centered on the color coordinates (R, G, B) of each pixel of the reference image have the largest overlap. The area indicated by the diagonal line) is calculated, and the reference color coordinates (Rb, Bb, Gb) are determined based on the most multiplex area Ar (S505). The reference color coordinates (Ra, Ga, Ba) can be calculated by averaging the color coordinates (R, G, B) of the pixel Pa corresponding to the reference sphere Sa including the most multiplex region Ar, for example. Further, when calculating the reference color coordinates (Ra, Ga, Ba), when there are a plurality of most multiplex regions Ar, for example, the reference color coordinates of any of the most multiplex regions Ar are adopted as the center of the reference sphere Sa. You may. Alternatively, the color coordinates obtained by averaging the reference color coordinates of the plurality of most multiplex regions Ar may be adopted as the center of the reference sphere Sa.

Next, the image processing unit 161 draws a reference sphere Sa having a radius r centered on the reference color coordinates (Rb, Bb, Gb) in the color space of the reference image (S507). Then, the image processing unit 161 detects the reference pixel Pam in the reference sphere Sa from the reference image, and detects the number of reference pixels m included in the reference sphere Sa (S509).

Since the subsequent steps S511 to S517 are the same as steps S311 to S317 of the embodiment (FIG. 4), the description thereof will be omitted.

In the modified example method, when determining the reference color coordinates (Ra, Ga, Ba) during teaching, it is not necessary to move the reference sphere Sa in each axial direction in the color space of the reference image. Therefore, the calculation load can be significantly reduced as compared with the embodiment.

<1-4. Management method of photovoltaic power generation module applying dirt inspection method>
Next, an example of a management method of the photovoltaic power generation module 300 to which the stain inspection method using the stain inspection device 1 is applied will be described. Normally, the photovoltaic power generation module 300 installed outdoors is placed in a harsh environment such as wind and rain, temperature, polluted gas, scattered matter, snow cover, and biological pollution. Therefore, several years after the installation, opinions such as "cleaning time" and "it's almost time for cleaning" were given by the O & M (operation and maintenance) contractor of the photovoltaic power generation module 300 or the photovoltaic power plant. Issued by the administrator. Conventionally, since a method for measuring the degree of contamination of the light receiving surface 301 of the photovoltaic power generation module 300 has not been established, the cleaning time of the light receiving surface 301 has been determined by practical experience or custom. Then, manual cleaning, high-pressure water cleaning, cleaning by a self-propelled automatic cleaning device mounted on the light receiving surface 301, etc. are performed, and the amount of recovery of the generated power is evaluated based on the difference in the generated power before and after the cleaning. It was only a wash. That is, the degree of contamination of the light receiving surface 301 and the amount of recovery of the generated power by cleaning were not quantified, and the correlation between the two was not theoretically managed. The management method of the photovoltaic power generation module 300 described below is for newly improving these.

FIG. 8 is a flowchart for explaining an example of a management method of the photovoltaic power generation module 300.

First, the generated power Wb of the photovoltaic power generation module 300 and the degree of contamination Sb of the light receiving surface 301 are measured and recorded together with the measurement date and time (S701). The degree of dirt Sb of the light receiving surface 301 is measured by, for example, the above-mentioned dirt inspection device 1 (see FIG. 1) and the above-mentioned dirt inspection method (see FIG. 3).

Further, after a predetermined elapsed period T has elapsed from the time when S701 is executed (YES in step S703), the generated power Wa of the photovoltaic power generation module 300 and the degree of contamination Sa of the light receiving surface 301 are measured, and together with the measurement date and time. Record (S705). The elapsed period T may be daily, weekly, monthly, or yearly. Further, step S705 is preferably carried out at the same time of solar radiation conditions (solar radiation intensity, weather) as in step S701.

Then, the degree of contamination Sb of the light receiving surface 301 measured in step S701 and the generated power Wb of the photovoltaic power generation module 300, the degree of contamination Sa of the light receiving surface 301 measured in step 705, and the generated power Wa of the photovoltaic power generation module 300. The cleaning time of the light receiving surface 301 of the photovoltaic power generation module 300 is determined based on the elapsed period T from steps S701 to S705 (S707).

In step S707, for example, first, the difference (Sa-Sb) between the degree of dirt on the clean surface and the degree of dirt Sb before cleaning is divided by the elapsed period T, so that the dirt rate ΔS = {() of the light receiving surface 301. Calculate Sa-Sb) / T}.

Further, by dividing the difference in the degree of dirt (Sa-Sb) by the difference in the generated power before and after this cleaning (Wa-Wb), the rate of change of the generated power with respect to the degree of dirt ΔW = {(Sa-Sb) / (Wa-Wb)} is calculated.

Further, the threshold value Ws of the generated power when cleaning the light receiving surface 301 is set, and the time when the generated power reaches the threshold Ws is calculated as the cleaning time of the light receiving surface 301 by using the above-mentioned fouling speed ΔS and change rate ΔW. .. The threshold value Ws can be set based on, for example, the lower limit of the generated power required for the photovoltaic power generation module 300. Alternatively, the threshold Ws can be set in consideration of the cost-effectiveness of the selling price of the generated power of the photovoltaic power generation module 300 with respect to the cleaning cost of the photovoltaic power generation module 300. For example, the profit obtained when the generated power of the photovoltaic power generation module 300 is sold in the elapsed period T is compared between the case where the current cleaning is performed and the case where the current cleaning is not performed, and the difference between the two. The threshold Ws can be determined so that is greater than or equal to the cleaning cost. Further, the threshold value Ws can be determined so that the above-mentioned difference sufficiently exceeds the cleaning cost and a predetermined profit is obtained. In the present embodiment, in consideration of the above-mentioned cost-effectiveness, the threshold value Ws is set to a value of about 90 [%] of the generated power Wo at the installation start time of the photovoltaic power generation module 300.

If the generated powers Wb and Wa are less than the threshold value Ws at the time of step S701 or S705, the time or a date close to that time may be determined as the day when the photovoltaic power generation module 300 is washed. ..

Further, in the management method of FIG. 8, steps S701 to S705 are performed once. However, the present invention is not limited to the example of FIG. 8, and steps S701 to S705 may be performed a plurality of times before the step S707 is performed. In this case, in step S707, based on each elapsed period T and the degree of contamination Sb and Sa of the light receiving surface 301 at the start and end of each elapsed period T and the generated power Wb and Wa of the photovoltaic power generation module 300, The cleaning time of the light receiving surface 301 of the photovoltaic power generation module 300 is determined. By doing so, the cleaning time of the light receiving surface 301 can be calculated more accurately.

Further, when steps S701 to S705 are performed a plurality of times, it is preferable that a part of the elapsed period T in each time has a different time length from the other part. More preferably, the elapsed period T at each time is set to a different time length. By doing so, it can be confirmed that a more accurate change in the dirt rate ΔS of the light receiving surface 301 and the rate of change ΔW of the generated power with respect to the degree of dirt can be obtained. Therefore, even if the change in the rate of change ΔW of the generated power with respect to the dirt rate ΔS and / or the degree of dirt on the light receiving surface 301 is non-linear, the cleaning time of the light receiving surface 301 can be determined more accurately.

Also, in the management method described above, steps S701 and S705 are preferably performed at least one of the early morning and the evening of the day.

For example, the intensity ratio of light of each wavelength contained in sunlight does not change with time, but the solar radiation intensity of sunlight incident on the photovoltaic power generation module 300 changes mainly with the altitude and solar radiation angle of the sun. In the time zone of the day, the maximum is usually from 12:00 to 14:00. The relationship between the power generated by the photovoltaic power generation module 300 and the solar radiation intensity in one day is as shown in FIG. 9, for example. In FIG. 9, the solar radiation intensity is less than 0.20 [kW / m ² ] at dawn including sunrise and dusk including sunset, and is larger than 0.60 [kW / m ² ] at noon including noon. In the early morning and evening between these, it is 0.20 [kW / m ² ] or more and 0.60 [kW / m ² ] or less. In this way, the rate of change of generated power with respect to the intensity of solar radiation is greatest in the early morning and evening. This tendency does not change even if the ambient temperature of the photovoltaic power generation module 300 changes.

In addition, the generated power of the photovoltaic power generation module 300 is usually PCS (power) so that the reverse power flow power sold from a plurality of photovoltaic power plants does not suddenly increase in a time zone close to the peak time of the generated power. The control system) controls the suppression so as not to exceed the upper limit threshold Wc. Therefore, as shown in FIG. 10, even if the above-mentioned management methods, particularly steps S701 and S705, are carried out at noon including, for example, before 10:00 to after 15:00, the difference in the generated power of the photovoltaic power generation module 300 is evaluated. There are things you can't do. Further, for example, at dawn before 6 o'clock and dusk after 17:00 in FIG. 10, the amount of increase in the generated power of the photovoltaic power generation module 300 before and after cleaning is very small. Therefore, it is difficult to understand the difference in the generated power of the photovoltaic power generation module 300. On the other hand, for example, in the early morning before 6:00 to 10 and in the evening after 15:00 to 17:00, the output suppression control of the PCS is not implemented, and the amount of increase in the generated power of the photovoltaic power generation module 300 is relatively large.

Therefore, by performing the above-mentioned management methods, particularly steps S701 and S705 in the early morning and / or evening, it is possible to more accurately detect the tendency that the generated power decreases as the degree of contamination of the light receiving surface 301 progresses. Therefore, the cleaning time of the light receiving surface 301 of the photovoltaic power generation module 300 can be calculated more accurately.

Further, in the above-mentioned management method, the degree of dirt on the light receiving surface 301 was detected by using the dirt inspection device 1. However, the present invention is not limited to this example, and the degree of contamination of the light receiving surface 301 may be detected by using an apparatus other than the stain inspection apparatus 1. For example, by utilizing the fact that diffused reflection of light is likely to occur when the light receiving surface 301 is dirty, a gloss meter for measuring the glossiness of the surface of the object to be measured or measuring the brightness of the reflected light from the surface of the object to be measured. You may use a brightness meter or the like. By pinpointly measuring the glossiness or brightness of a plurality of points on the light receiving surface 301 and comparing each measured value on the dirty light receiving surface 301 with the reference measured value on the clean light receiving surface 301, the degree of contamination is obtained. Can also be evaluated. However, the size of the measurement area of the gloss meter and the luminance meter is very narrow as compared with the measurement area of the stain inspection device 1 of the present embodiment. Therefore, the accuracy tends to be lower than that of the dirt inspection device 1 of the present mobile phone. Therefore, in order to sufficiently accurately evaluate the degree of contamination of the light receiving surface 301, it is necessary to perform measurement at more measurement points as compared with the case where the contamination inspection device 1 is used.

<2. Second Embodiment>
In the first embodiment described above, the hue of the stain covering the light receiving surface 301 is not considered. However, in reality, the hue of dirt greatly affects the fluctuation of the generated power of the photovoltaic power generation module 300. For example, even if the degree of stain is the same without considering the hue, the closer the stain color is to black, the greater the decrease in generated power. On the other hand, the closer the stain color is to white, the less the decrease in generated power is reduced. Therefore, in the second embodiment, the corrected measured value obtained by correcting the measured value calculated in the first embodiment (see FIG. 4) or a modified example thereof (see FIG. 6) in consideration of the hue of stains is calculated. Other than this, it is the same as that of the first embodiment. Hereinafter, a configuration different from that of the first embodiment will be described. Further, the same components as those in the first embodiment are designated by the same reference numerals, and the description of the same configurations as in the first embodiment may be omitted.

<2-1. Dirt inspection device>
In the second embodiment, the image processing unit 161 of the stain inspection device 1 describes the color coordinates (R, G, B) of each pixel of the measurement image, the reference color coordinates (Ra, Ga, Ba), and the measurement image. The correction measurement value of the degree of contamination of the light receiving surface 301 is calculated based on the correction values Nr, Ng, and Nb for each color component corresponding to the color coordinates (R, G, B) of each pixel. The correction values Nr, Ng, and Nb for each color component are set corresponding to the color coordinates (R, G, B) of each pixel Pb of the measurement image, respectively. The setting information of the correction values Nr, Ng, and Nb for each color component is stored in, for example, the memory 15.

Specifically, the correction values Nr, Ng, and Nb for each color component are set to the color coordinates (R, G, B) of the pixels (that is, the within-range pixels Pbn) in the reference sphere Sa in the color space of the measured image, respectively. The correction values Nrn, Ngn, and Nbn for each corresponding color component are included. The image processing unit 161 corrects the count value of each pixel Pbn in the range by the correction values Nrn, Ngn, and Nbn for each color component, and calculates the correction measurement value of the degree of stain using the corrected count value. In the following, the corrected count value of each pixel Pbn in the range is referred to as a correction count value na.

For example, the correction value Nrn corresponding to the R component value of the within-range pixel Pbn is set smaller as the R component value approaches the maximum gradation value (for example, 15), and when the R component value is the maximum gradation value. Is set to the minimum value (for example, a value smaller than 1). On the other hand, the correction value Nrn is set larger as the R component value is closer to the minimum gradation value (for example, 0), and is the maximum value (for example, a value larger than 1) when the R component value is the minimum gradation value. Is set to.

The same applies to the correction values Ngn and Nbn for each of the other color components of the within-range pixels Pbn. For example, the correction value Ngn corresponding to the G component value of the within-range pixel Pbn is set smaller as the G component value approaches the maximum gradation value (for example, 15), and when the G component value is the maximum gradation value. Is set to the minimum value (for example, a value smaller than 1). On the other hand, the correction value Ngn is set larger as the G component value is closer to the minimum gradation value (for example, 0), and is the maximum value (for example, a value larger than 1) when the G component value is the minimum gradation value. Is set to.

Further, the correction value Nbn corresponding to the B component value of the within-range pixel Pbn is set smaller as the B component value is closer to the maximum gradation value (for example, 15), and when the B component value is the maximum gradation value. Is set to the minimum value (for example, a value smaller than 1). On the other hand, the correction value Nbn is set larger as the B component value is closer to the minimum gradation value (for example, 0), and is the maximum value (for example, a value larger than 1) when the B component value is the minimum gradation value. Is set to.

The correction values Nrn, Ngn, and Nbn for each of these color components can be set based on, for example, the band gap of the material of the solar cell 330, the light reflectance according to the hue of the light incident on the light receiving surface 301, and the like.

<2-2. Quantification of degree of dirt>
Next, an example of the method for quantifying the degree of dirt in the second embodiment and a modified example thereof will be described.

<2-2-1. Example>
FIG. 11 is a flowchart for explaining a method for quantifying the degree of contamination in the embodiment of the second embodiment. Note that steps S901 to S915 in FIG. 11 are the same as steps S301 to S315 in the embodiment (FIG. 4) of the first embodiment.

In step S915, n in-range pixels Pbn included in the reference sphere Sa are detected. The image processing unit 161 determines the correction values Nrn, Ngn, and Nbn for each color component of each within the range pixel Pbn with reference to the setting information stored in the memory 15 (S916). Then, the image processing unit 161 is based on the reference pixel number m detected in S905, the range pixel number n detected in S915, and the correction values Nrn, Ngn, Nbn for each color component of each range pixel Pbn. A correction measurement value of the degree of stain based on the measurement image is calculated (S917).

That is, in S917, the image processing unit 161 has the color coordinates (R, G, B) of each pixel Pb of the measurement image, the reference color coordinates (Ra, Ga, Ba), and each pixel Pb of the measurement image. The correction measurement value of the degree of contamination of the light receiving surface 301 is calculated based on the correction values Nr, Ng, and Nb for each color component corresponding to the color coordinates (R, G, B). In other words, the image processing unit 161 measures the degree of contamination of the light receiving surface 301 based on the color coordinates (R, G, B) of each pixel Pb of the measurement image and the reference color coordinates (Ra, Ga, Ba). Further, the correction measurement value corrected based on the correction values Nr, Ng, and Nb for each color component corresponding to the color coordinates (R, G, B) of each pixel Pb of the measurement image is calculated.

For example, in the present embodiment, first, the image processing unit 161 calculates the correction count value na = (Nrn × Ngn × Nbn) of the pixels Pbn in each range. As described above, the correction count value na is a value obtained by correcting the count value of the pixels Pbn in each range in consideration of the hue of the stain in the second embodiment. When the hue of stains is not taken into consideration as in the first embodiment, the count value of the pixels Pbn in each range is 1.

Further, the image processing unit 161 has the sum of the correction count values na in the n range pixels Pbn Σna = {(Nr1 × Ng1 × Nb1) + (Nr2 × Ng2 × Nb2) + ... + (Nrn × Ngn ×). Nbn)} is calculated.

Then, the image processing unit 161 calculates the degree of contamination by the ratio {(Σna) / m} of the total sum Σna of the correction count value na to the reference pixel number m. In the second embodiment, the image processing unit 161 sets the percentage {100 × (Σna) / m} as the measured value of the degree of contamination based on the measured image. When the percentage exceeds 100, the measured value of the degree of contamination of the measured image is 100.

The image processing unit 161 performs the processing shown in FIG. 11 every time the camera 14 captures the measured image. When a plurality of measurement images are captured when the measurement start button is pressed once, the average value of the measured values may be a representative measured value in one measurement.

As described above, in the second embodiment, the image processing unit 161 receives the light receiving surface based on the color coordinates (R, G, B) of each pixel Pb of the measurement image and the reference color coordinates (Ra, Ga, Ba). The measured value of the degree of contamination of 301 is further corrected based on the correction values Nr, Ng, and Nb for each color component corresponding to the color coordinates (R, G, B) of each pixel Pb of the measured image. In other words, the image processing unit 161 has color coordinates (R, G, B) of each pixel Pb of the measurement image, reference color coordinates (Ra, Ga, Ba), and color coordinates of each pixel Pb of the measurement image. Based on the correction values Nr, Ng, and Nb for each color component corresponding to (R, G, B), the correction measurement value of the degree of contamination of the light receiving surface 301 is calculated. As described above, by correcting the measured value of the degree of stain without considering the hue using the correction values Nrn, Ngn, and Nbn for each color component, the light receiving surface 301 for the fluctuation of the generated power of the photovoltaic power generation module 300 is covered. The effect of the hue of stains can be considered. Therefore, the stain inspection device 1 can be used to more accurately detect the tendency of the generated power of the photovoltaic power generation module 300 to decrease.

<2-2-2. Modification example>
In addition, in order to reduce the calculation load at the time of teaching, the same method as in FIG. 4 (that is, a modified example of the first embodiment) may be adopted. FIG. 12 is a flowchart for explaining a method for quantifying the degree of contamination in the modified example of the second embodiment. Steps S1101 to S1115 of FIG. 12 are the same as steps S501 to S515 of the modified example (FIG. 6) of the first embodiment. Further, steps S1116 to S1117 of FIG. 12 are the same as steps S916 to S917 of the second embodiment (FIG. 11). The image processing unit 161 performs the processing of FIG. 12 every time the camera 14 captures the measured image. When a plurality of measurement images are captured when the measurement start button is pressed once, the average value of the measured values may be a representative measured value in one measurement.

<2-3. Management method of photovoltaic power generation module applying dirt inspection method>
In the second embodiment, the above-mentioned corrected measurement value is used in the management method (see FIG. 8) of the photovoltaic power generation module 300 to which the stain inspection method using the stain inspection device 1 is applied. For example, in steps S701 and S705 of FIG. 8, the corrected measurement values of the degree of dirt Sb and Sa of the light receiving surface 301 are the above-mentioned dirt inspection method (see FIG. 1) using, for example, the above-mentioned dirt inspection device 1 (see FIG. 1). 11. Measured according to FIG. 12). That is, the measured values Sb and Sa of the degree of contamination based on the color coordinates (R, G, B) in the color space of each pixel Pb of the measurement image and the reference color coordinates (Ra, Ga, Ba) in the color space are obtained. The correction measurement value of the degree of stain corrected based on the correction values Nr, Ng, and Nb for each color component corresponding to the color coordinates (R, G, B) is calculated. Then, the cleaning time of the light receiving surface 301 is determined based on the respective correction measurement values of the degree of contamination described above, the respective generated powers Wb and Wa measured in steps S701 and S705 of FIG. 8, and the elapsed period T. Will be done. By using the corrected measurement value of the degree of contamination in consideration of the hue, it is possible to more accurately detect the tendency of the generated power of the photovoltaic power generation module 300 to decrease. Therefore, the cleaning time of the light receiving surface 301 can be calculated more accurately.

<3. Remarks>
The embodiment of the present invention has been described above. It should be noted that the above-described embodiment is an example, and various modifications can be made to the combination of each component and each process, and it is understood by those skilled in the art that it is within the scope of the present invention.

For example, in the above-described embodiment, at least a part or all of the functional components of the control device 16 may be realized by physical components (for example, an electric circuit, an element, a device, etc.).

Further, in the above-described embodiment, the RBG color system space is exemplified as the color space representing the color coordinates. However, the present invention is not limited to this example. For example, the color space may be a color space of a CIE color system other than the RGB color system. As the color space of such a CIE color system, for example, an XYZ color system, an xyY color system, an L * u * v * color system, an L * a * b * color system, or the like can be adopted. .. Alternatively, the color space may be a CMY space, an HSV space, an HLS space, or the like. In the CMY space, the color coordinates (C, M, K) are represented by the C component value, the M component value, and the K component value. The C component value represents the magnitude of the color component C (cyan) of the pixels of the image. The M component value represents the size of the color component magenta of the pixels of the image. The K component value represents the size of the color component K (black) of the pixels of the image. Further, in the HSV space, the color coordinates (H, S, V) are represented by the hue value H, the saturation value S, and the brightness V of the pixels of the image. Further, in the HLS space, the color coordinates (H, L, S) are represented by the hue value H, the luminance value L, and the saturation value S of the pixels of the image.

Further, in the above-described embodiment, the present invention is applied to the measurement of the degree of contamination of the light receiving surface of the photovoltaic power generation module. However, the scope of application of the present invention is not limited to the above-mentioned examples. The present invention is also applicable to an apparatus for measuring the degree of contamination of the surface to be inspected other than the light receiving surface of the photovoltaic power generation module. The surface to be inspected is a surface on which dirt accumulates over time. For example, the surface to be inspected may be a display surface of a liquid crystal display device, a surface of a table or desk top plate, a glass surface of a vehicle, a surface of an outer wall of a building, or a floor surface.

100 Management system 1 Dirt inspection device 11 Housing 111 Opening 12 Lighting device 121 Base 122 LED array 13 Lighting drive device 14 Camera 141 Lens 142 Image sensor 15 Memory 16 Control device 161 Image processing unit 17 Display device 18 Input device 19 Communication device 20 External Power supply terminal 21 Built-in power supply 300 Solar power generation module 301 Light receiving surface 310 Translucent substrate 320 Encapsulating resin layer 330 Solar cell 340 Back film OT External terminal AC External power supply L0 Reference area L1 to L5 Measurement area Pa, Pb pixel Pam reference Pixel Pbn Range pixel Sa Reference sphere Sb Measurement sphere Ar Most multiplex region

Claims (10)

1. A housing that covers a part of the surface to be inspected,
   A lighting device that irradiates a part of the area with light,
   An image pickup device that images a part of the area and
   An image processing unit that calculates the degree of contamination of the surface to be inspected based on the first color coordinates in the color space of each pixel of the measurement image captured by the image pickup apparatus and the reference color coordinates in the color space.
   A stain inspection device equipped with.
2. The stain inspection device according to claim 1, wherein the color space is a three-dimensional color space.
3. The image processing unit uses the reference so that the number of pixels of the reference image having the second color coordinates within the reference color range of a predetermined size centered on the reference color coordinates is maximized in the color space. The stain inspection device according to claim 1 or 2, which determines the color coordinates.
4. The image processing unit calculates, in the color space, a region having the largest overlap of reference color ranges of a predetermined size centered on the second color coordinates of each pixel of the reference image, and the region is based on the region. The stain inspection device according to claim 1 or 2, which determines the reference color coordinates.
5. The image processing unit is in the color space.
   A pixel of the measurement image having the first color coordinates within the reference color range is detected.
   The stain inspection apparatus according to any one of claims 1 to 4, wherein the degree of contamination of the surface to be inspected is calculated based on the detection result of the pixel.
6. The stain inspection device according to any one of claims 1 to 5, wherein the image processing unit further corrects the degree of stain based on a correction value for each color component corresponding to the first color coordinates.
7. A step of imaging a part of the surface to be inspected covered by the housing and illuminated by the lighting device with the imaging device,
   A step of calculating the degree of contamination of the surface to be inspected based on the color coordinates in the color space of each pixel of the measurement image captured by the imaging device and the reference color coordinates in the color space.
   A stain inspection method.
8. A housing that covers a part of the light receiving surface of the photovoltaic power generation module, a lighting device that irradiates the part of the area with light, an image pickup device that images the part of the area, and a measurement image captured by the image pickup device. The photovoltaic power generation using a stain inspection device including a first color coordinate in the color space of each pixel and an image processing unit that calculates the degree of stain on the light receiving surface based on the reference color coordinate in the color space. The first measurement step of measuring the degree of dirt on the light receiving surface of the module and measuring the generated power of the photovoltaic power generation module, and
   After a predetermined elapsed period from the time when the first measurement step is performed, the stain inspection device is used to measure the degree of stain, and the second measurement step for measuring the generated power is
   A determination step for determining the cleaning time of the light receiving surface based on the degree of contamination, the generated power, and the elapsed period measured in the first measurement step and the second measurement step, respectively.
   How to manage a photovoltaic module, including.
9. In the first measurement step and the second measurement step, the correction measurement value of the degree of contamination is calculated.
   The correction measurement value is a value obtained by correcting the measurement value of the degree of stain based on the first color coordinates and the reference color coordinates based on the correction value for each color component corresponding to the first color coordinates. The method for managing a photovoltaic power generation module according to claim 8.
10. The management of the photovoltaic module according to claim 8 or 9, wherein at least the first measurement step and the second measurement step are performed at least one of the early morning and the evening of the day. Method.

Images