Greenhouse film dedusting method and system

Abstract

The invention relates to the technical field of greenhouses, in particular to a greenhouse film dedusting method and system for a greenhouse. The method comprises the following steps: acquiring target greenhouse film images of a plurality of greenhouses; for a first greenhouse film image without foreign matters in the target greenhouse film image, collecting illumination intensity, light transmittance and greenhouse film spectral data of the greenhouse corresponding to the first greenhouse film image; processing the greenhouse film spectrum data to obtain the greenhouse film thickness of the greenhouse corresponding to the first greenhouse film image; when the illumination intensity and the light transmittance are both smaller than the corresponding preset illumination intensity and preset light transmittance, dust removal is conducted on a greenhouse film of the greenhouse corresponding to the first greenhouse film image through a drip washing device and a brush device; or when the greenhouse film thickness is larger than the preset greenhouse film thickness, dust removal is conducted on the greenhouse film, corresponding to the first greenhouse film image, of the greenhouse through the drip washing device and the brush device. According to the method, the cleaning efficiency of the greenhouse film of the greenhouse is improved.

Description

Technical Field

[0001] The present application relates to the technical field of greenhouses, and further relates to a greenhouse film dust removal method and system. Background Art

[0002] Solar greenhouses are widely used in northern China as agricultural production facilities, designed to provide a suitable growing environment for crops. However, due to the region's characteristic dry climate and frequent sandstorms, the greenhouse films used in solar greenhouses are often exposed to contaminants. Currently, greenhouse film cleaning relies primarily on manual labor, which is not only inefficient but also labor-intensive and prone to film damage. Summary of the Invention

[0003] In order to solve the above technical problems, the present application provides a greenhouse film dust removal method and system, which improves the cleaning efficiency of the greenhouse film.

[0004] In a first aspect, the present application provides a method for removing dust from greenhouse film, comprising: collecting a plurality of target greenhouse film images of the greenhouse; for a first greenhouse film image in which no foreign matter exists in the target greenhouse film image, collecting light intensity, transmittance and greenhouse film spectrum data of the greenhouse corresponding to the first greenhouse film image; processing the greenhouse film spectrum data to obtain the greenhouse film thickness of the greenhouse corresponding to the first greenhouse film image; when the light intensity and the transmittance are both less than the corresponding preset light intensity and preset transmittance, dusting the greenhouse film of the greenhouse corresponding to the first greenhouse film image by means of a shower device and a brush device; or, when the greenhouse film thickness is greater than the preset greenhouse film thickness, dusting the greenhouse film of the greenhouse corresponding to the first greenhouse film image by means of a shower device and a brush device.

[0005] The above greenhouse film dust removal method acquires target film images from multiple greenhouses, providing basic data for subsequent analysis. Next, for the first foreign object-free film image, light intensity, transmittance, and film spectral data are collected. By processing this spectral data, the film thickness is accurately calculated. Finally, based on the comparison of light intensity, transmittance, and film thickness with preset values, a decision is made as to whether to activate the rinse and brush systems for dust removal, thereby ensuring that the greenhouse lighting conditions and crop growth environment are effectively maintained. This method not only improves greenhouse film cleaning efficiency but also avoids the labor-intensive nature of manual cleaning, thereby enhancing crop production efficiency and greenhouse environmental quality.

[0006] In one implementation, the method further includes: for a second greenhouse film image in which foreign matter exists in the target greenhouse film image, dust is removed from the greenhouse film corresponding to the second greenhouse film image by a high-pressure air pump device and a brush device.

[0007] In the above greenhouse film dust removal method, when there is a second greenhouse film image with foreign matter in the target greenhouse film image, there is no need to further collect the light intensity, transmittance and greenhouse film spectrum data corresponding to these second greenhouse film images. The drone can directly control the high-pressure air pump device and the brush device to remove dust from the greenhouse film corresponding to the second greenhouse film image, thereby improving the compatibility of this application and reducing the dust removal cost.

[0008] In one implementation, the processing of the greenhouse film spectral data to obtain the greenhouse film thickness of the greenhouse corresponding to the first greenhouse film image specifically includes: when there is no trapezoidal distortion in the greenhouse film spectral data, performing spectral analysis on the greenhouse film spectral data to obtain a corresponding spectral interference diagram; calculating the thickness of the greenhouse film at various positions corresponding to the first greenhouse film image based on the spectral position and distance between constructive interferences in the spectral interference diagram; calculating the average thickness of the greenhouse film corresponding to the first greenhouse film image based on the thickness of the greenhouse film at various positions corresponding to the first greenhouse film image, and using the average thickness as the greenhouse film thickness.

[0009] In one implementation, the method further includes: when there is trapezoidal distortion in the greenhouse film spectrum data, performing distortion correction on the greenhouse film spectrum data in the position dimension by using an interpolation algorithm to obtain the greenhouse film spectrum data without trapezoidal distortion.

[0010] The above greenhouse film dust removal method uses an interpolation algorithm to correct spectral data with trapezoidal distortion in the greenhouse film, resulting in distortion-free spectral data. This allows for more accurate spectral analysis and film thickness calculation, improving the quality of the spectral data and the accuracy of the analysis, thereby increasing the precision of film thickness measurement. By comparing the precise film thickness with the preset film thickness, dust removal is completed, further improving dust removal efficiency and avoiding errors in film thickness calculation that could lead to increased dust removal costs.

[0011] In a second aspect, the present application also provides a greenhouse film dust removal system, comprising: an acquisition module configured to acquire a plurality of target greenhouse film images of the greenhouse; a controller configured to identify foreign matter in the target greenhouse film images; for a first greenhouse film image in which no foreign matter exists in the target greenhouse film image, the acquisition module is configured to acquire light intensity, light transmittance and greenhouse film spectrum data of the greenhouse corresponding to the first greenhouse film image; the controller is configured to process the greenhouse film spectrum data to obtain the greenhouse film thickness ... The light intensity and the transmittance are compared with the preset light intensity and the preset transmittance, and the greenhouse film thickness is compared with the preset greenhouse film thickness; when the light intensity and the transmittance are both less than the corresponding preset light intensity and the preset transmittance, the controller is configured to generate a first dust removal instruction; when the greenhouse film thickness is greater than the preset greenhouse film thickness, the controller is configured to generate a second dust removal instruction; the drone is configured to remove dust from the greenhouse film corresponding to the first greenhouse film image through the shower device and the brush device based on the first dust removal instruction or the second dust removal instruction.

[0012] In one implementation, for the second greenhouse film image in which foreign matter exists in the target greenhouse film image, the controller is configured to generate a third dust removal instruction; the drone is configured to remove dust from the greenhouse film corresponding to the second greenhouse film image through a high-pressure air pump device and a brush device based on the third dust removal instruction.

[0013] In one implementation, when there is no trapezoidal distortion in the greenhouse film spectral data, the controller is configured to perform spectral analysis on the greenhouse film spectral data to obtain a corresponding spectral interference diagram; the controller is configured to calculate the thickness of the greenhouse film at various positions corresponding to the first greenhouse film image based on the spectral position and distance between the constructive interferences in the spectral interference diagram; the controller is configured to calculate the average thickness of the greenhouse film corresponding to the first greenhouse film image based on the thickness of the greenhouse film at various positions corresponding to the first greenhouse film image, and use the average thickness as the greenhouse film thickness.

[0014] In one implementation, the controller is configured to perform position dimension distortion correction on the greenhouse film spectral data by using an interpolation algorithm when there is trapezoidal distortion in the greenhouse film spectral data, so as to obtain the greenhouse film spectral data without trapezoidal distortion.

[0015] In one implementation, the high-pressure air pump device includes a micro high-pressure air pump and an air gun nozzle device, the rinsing device includes a water tank and a rinsing nozzle device, and the brush device includes a rotating brush and a telescopic rod.

[0016] In one implementation, the acquisition module includes an image acquisition module, a spectrum acquisition module and a sensor module; the image acquisition module is configured to acquire the target greenhouse film image; the spectrum acquisition module is configured to acquire the greenhouse film spectrum data; and the sensor module is configured to acquire the light intensity and the transmittance.

[0017] Compared with the prior art, the present invention has at least one of the following beneficial effects:

[0018] 1. Capturing target greenhouse film images from multiple greenhouses provides basic data for subsequent analysis. Next, for the first foreign body-free greenhouse film image, light intensity, transmittance, and film spectral data are collected. By processing this spectral data, the film thickness is accurately calculated. Finally, based on a comparison of light intensity, transmittance, and film thickness with preset values, a decision is made regarding whether to activate the rinse and brush systems for dust removal, thereby ensuring effective maintenance of greenhouse lighting conditions and the crop growth environment. This method not only improves greenhouse film cleaning efficiency but also avoids the labor-intensive and film-damaging effects of manual cleaning, thereby enhancing crop production efficiency and greenhouse environmental quality.

[0019] 2. When there is a second greenhouse film image with foreign matter in the target greenhouse film image, there is no need to further collect the light intensity, transmittance and greenhouse film spectrum data corresponding to these second greenhouse film images. The drone can directly control the high-pressure air pump device and the brush device to remove dust from the greenhouse film corresponding to the second greenhouse film image, thereby improving the compatibility of this application and reducing the dust removal cost.

[0020] 3. By using an interpolation algorithm to correct spectral data from greenhouse films with trapezoidal distortion, distortion-free spectral data can be obtained, enabling more accurate spectral analysis and film thickness calculation. This improves the quality of the spectral data and the accuracy of the analysis, thereby increasing the accuracy of film thickness measurement. By comparing the precise film thickness with the preset film thickness, dust removal can be completed, further improving dust removal efficiency and avoiding errors in film thickness calculation that could lead to increased dust removal costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The preferred embodiments will be described below in a clear and understandable manner with reference to the accompanying drawings to further illustrate the above-mentioned characteristics, technical features, advantages and implementation methods of the present invention.

[0022] Figure 1 The following is a structural block diagram of a greenhouse film dust removal system provided by an embodiment of the present application;

[0023] Figure 2A flow chart of a greenhouse film dust removal method provided in an embodiment of the present application is shown;

[0024] Figure 3 A flow chart for obtaining greenhouse film thickness provided in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0025] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the specific embodiments of the present invention will be described below with reference to the accompanying drawings. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings and other embodiments can be obtained based on these drawings without inventive work.

[0026] To simplify the drawings, only portions relevant to the invention are schematically depicted in each figure; they do not represent the actual structure of the product. Furthermore, to simplify the drawings and facilitate understanding, in some figures, only one component with the same structure or function is schematically depicted or labeled. In this document, "one" not only means "only one" but also "more than one."

[0027] It should be further understood that the term "and / or" used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.

[0028] It should be noted that, unless otherwise specified or limited, the terms "mounted," "connected," and "connected" should be understood broadly. For example, they can refer to fixed, detachable, or integral connections; mechanical or electrical connections; direct or indirect connections through an intermediary; and internal communication between two components. Those skilled in the art will understand the specific meanings of these terms in the present invention based on the specific circumstances.

[0029] In addition, in the description of the present application, the terms "first", "second", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0030] It should be noted that the above embodiments can be freely combined as needed. The above are only preferred embodiments of the present invention. It should be noted that those skilled in the art can make several improvements and modifications without departing from the principles of the present invention, and such improvements and modifications should also be considered within the scope of protection of the present invention.

[0031] Greenhouse film spectral data refers to data obtained using a spectrometer or other spectral measurement equipment on the transmission, reflection, and absorption characteristics of greenhouse films for different wavelengths of light. This data reflects the film's optical properties, including its transmittance, reflectance, and absorptivity for specific wavelengths. Film spectral data can be used to determine film thickness, as changes in film thickness affect the distribution of the spectrum. For example, thicker films reduce the transmission of specific wavelengths of light, which is reflected in the film's spectral data.

[0032] At present, the cleaning of greenhouse films mainly relies on manual operation, which is not only inefficient, but also labor-intensive and easily causes damage to the films. In addition, traditional cleaning methods cannot accurately judge the degree of contamination of the greenhouse films, and often require regular comprehensive cleaning, which increases operating costs. With the development of agricultural technology, some automated cleaning equipment has appeared on the market, but these equipment generally have problems such as poor cleaning effect and poor adaptability. Therefore, it is of great significance to develop an efficient and intelligent greenhouse film dust removal system. The present invention collects and analyzes the light intensity, light transmittance and greenhouse film spectral data of the greenhouse, and then determines whether the greenhouse film needs dust removal. It can achieve at least one of the following beneficial effects: improving the cleaning efficiency of the greenhouse film; or avoiding the problems of high labor intensity and easy damage to the greenhouse film caused by manual cleaning, thereby improving the production efficiency of crops and the environmental quality of the greenhouse.

[0033] The following is explained with reference to the accompanying drawings:

[0034] Reference Attachment Figure 1 , which shows a structural block diagram of a greenhouse film dust removal system provided by an embodiment of the present application. Figure 1 As shown, the system includes: a drone 100, a controller 200, and a sensor module 300. The drone 100 includes an image acquisition module 110, a spectrum acquisition module 120, a high-pressure air pump device 130, a washing device 140, a brush device 150, and a communication module 160.

[0035] Greenhouses include but are not limited to multi-span film greenhouses, multi-span glass greenhouses, solar greenhouses, etc. This application takes the solar greenhouse as an example.

[0036] The image acquisition module 110 includes, but is not limited to, high-definition cameras, webcams, and other devices for capturing images of the target greenhouse film. The spectrum acquisition module 120 includes, but is not limited to, other hyperspectral imaging devices such as hyperspectral cameras and spectrometers for collecting spectral data of the greenhouse film. The high-pressure air pump device 130 includes a miniature high-pressure air pump and an air gun nozzle device, the rinsing device 140 includes a water tank and a rinsing nozzle device, and the brush device 150 includes a rotating brush and a telescopic rod, all of which are used to remove dust from the greenhouse film. The drone 100 communicates with the controller 200 via the communication module 160, which includes, but is not limited to, radio communication equipment, Wi-Fi communication equipment, and cellular network communication equipment. The sensor module 300 includes, but is not limited to, a photodiode, a light intensity sensor, and a transmittance meter. The photodiode and light intensity sensor are used to collect light intensity, and the transmittance meter is used to collect transmittance. Further, the sensor modules 300 are distributed within each greenhouse.

[0037] The controller 200 analyzes and processes the data collected by the sensor module 300, the image acquisition module 110, and the spectrum acquisition module 120 to determine which greenhouse film requires dust removal. The controller 200 then sends the generated dust removal command to the drone 100 via the communication module 160, instructing the drone 100 to remove dust from the greenhouse film, thereby improving the greenhouse film cleaning efficiency.

[0038] Reference Attachment Figure 2 , which shows a flow chart of a greenhouse film dust removal method provided by an embodiment of the present application. Figure 2 As shown, the method includes:

[0039] S200, collecting target greenhouse film images of multiple greenhouses;

[0040] S210, for a first greenhouse film image without foreign matter in the target greenhouse film image, collecting light intensity, light transmittance, and greenhouse film spectrum data of the greenhouse corresponding to the first greenhouse film image;

[0041] S220, processing the greenhouse film spectral data to obtain the greenhouse film thickness of the greenhouse corresponding to the first greenhouse film image;

[0042] S230, when the light intensity and transmittance are both less than the corresponding preset light intensity and preset transmittance, the greenhouse film of the greenhouse corresponding to the first greenhouse film image is dusted by a shower device and a brush device; or, when the greenhouse film thickness is greater than the preset greenhouse film thickness, the greenhouse film of the greenhouse corresponding to the first greenhouse film image is dusted by a shower device and a brush device.

[0043] The image acquisition module captures target greenhouse film images of multiple greenhouses and transmits them to the controller via the communication module for identification. The identification module in the controller identifies which greenhouses within the target film images have foreign objects on their films. For first greenhouse film images without foreign objects in the target film images, the sensor module collects the corresponding light intensity and transmittance of the greenhouses corresponding to these first film images. The spectrum acquisition module on the drone collects spectral data of the greenhouse films corresponding to these first film images. The collected light intensity, transmittance, and spectral data are transmitted to the controller for processing. The analysis module in the controller analyzes the spectral data to determine the film thickness of the greenhouse corresponding to the first film image. The analysis module compares the film thickness with a preset film thickness. If the film thickness exceeds the preset thickness, the execution module in the controller generates a second dust removal command. Based on the second dust removal command, the drone controls the rinser and brush device to perform dust removal on the greenhouse films corresponding to the first film images.

[0044] Furthermore, the controller may also compare the collected light intensity and transmittance with the preset light intensity and preset transmittance. When the light intensity and transmittance are both less than the corresponding preset light intensity and preset transmittance, the execution module in the controller generates a first dust removal instruction. Based on the first dust removal instruction, the drone may also control the rinsing device and the brush device to complete the dust removal operation on the greenhouse film corresponding to the first greenhouse film image. The degree of depreciation of the greenhouse film will also affect the light intensity and transmittance. Therefore, the greenhouse film with a depreciation degree greater than the preset value can be cleaned, and the light intensity and transmittance of the cleaned greenhouse film can be collected and sent to the controller as reference data when performing the dust removal operation. At the same time, the greenhouse film dust removal method in the embodiment of the present application is not limited to dust removal for greenhouses, but can also be used to remove dust from glass, solar panels, etc.

[0045] In the embodiment of the present application, by acquiring target greenhouse film images of multiple greenhouses, basic data is provided for subsequent analysis. Next, for the first greenhouse film image without foreign matter, its light intensity, light transmittance and greenhouse film spectrum data are collected. By processing the spectral data, the thickness of the greenhouse film is further accurately calculated. Finally, based on the comparison results of the light intensity, light transmittance and greenhouse film thickness with the preset values, it is decided whether to start the rinsing device and the brush device for dust removal, thereby ensuring that the lighting conditions and crop growth environment in the greenhouse are effectively maintained. This method not only improves the greenhouse film cleaning efficiency of the greenhouse, but also avoids the problems of high work intensity and easy damage to the greenhouse film caused by manual cleaning, thereby improving the production efficiency of crops and the environmental quality of the greenhouse.

[0046] In one embodiment of the present application, it also includes: for a second greenhouse film image in which foreign matter exists in the target greenhouse film image, dust is removed from the greenhouse film corresponding to the second greenhouse film image by a high-pressure air pump device and a brush device.

[0047] When the controller's recognition module identifies foreign matter in the second greenhouse film image within the target greenhouse film image, the controller's execution module directly generates a third dust removal command. Based on this third dust removal command, the drone controls the high-pressure air pump and brush assembly to remove dust from the greenhouse film corresponding to the second greenhouse film image.

[0048] In an embodiment of the present application, when there is a second greenhouse film image with foreign matter in the target greenhouse film image, there is no need to further collect the light intensity, transmittance and greenhouse film spectrum data corresponding to these second greenhouse film images. The drone can directly control the high-pressure air pump device and the brush device to remove dust from the greenhouse film corresponding to the second greenhouse film image, thereby improving the compatibility of the present application and reducing the dust removal cost.

[0049] Reference Attachment Figure 3 , which shows a flow chart for obtaining the thickness of greenhouse film provided in an embodiment of the present application.

[0050] like Figure 3 As shown, including:

[0051] S300, when there is trapezoidal distortion in the greenhouse film spectral data, performing distortion correction on the greenhouse film spectral data in a position dimension by using an interpolation algorithm to obtain greenhouse film spectral data without trapezoidal distortion;

[0052] S310, when there is no trapezoidal distortion in the greenhouse film spectrum data, performing spectral analysis on the greenhouse film spectrum data to obtain a corresponding spectral interference pattern;

[0053] S320, calculating the thickness of the greenhouse film at each position corresponding to the first greenhouse film image based on the spectral position and distance between constructive interferences in the spectral interference pattern;

[0054] S330: Calculate the average thickness of the greenhouse film corresponding to the first greenhouse film image according to the thickness of each position of the greenhouse film corresponding to the first greenhouse film image, and use the average thickness as the greenhouse film thickness.

[0055] For a first greenhouse film image containing no foreign objects in the target greenhouse film image, the spectral acquisition module scans the greenhouse film corresponding to the first greenhouse film image to obtain greenhouse film spectral data. The greenhouse film spectral data includes the positional dimension and the spectral dimension of the greenhouse film. An analysis module in the controller determines whether there is trapezoidal distortion in the greenhouse film spectral data. If there is trapezoidal distortion in the greenhouse film spectral data, the analysis module in the controller uses an interpolation algorithm to correct the distortion in the positional dimension of the greenhouse film spectral data to obtain greenhouse film spectral data (or a two-dimensional spectral image) without trapezoidal distortion. The analysis module in the controller performs spectral analysis on the greenhouse film spectral data without trapezoidal distortion to obtain a corresponding spectral interference pattern. Using mirror geometry methods and the spectral position and distance between constructive interferences in the spectral interference pattern, the analysis module calculates the thickness of the greenhouse film at various locations on the greenhouse film corresponding to the first greenhouse film image. Furthermore, the analysis module in the controller calculates the average thickness of the greenhouse film corresponding to the first greenhouse film image based on the thickness of the greenhouse film at various locations on the greenhouse film corresponding to the first greenhouse film image, and uses the average thickness as the greenhouse film thickness. The calculated greenhouse film thickness is then compared with a preset film thickness (which can be 120 microns). If the film thickness exceeds the preset thickness, the execution module in the controller generates a second dust removal instruction. Based on the second dust removal instruction, the drone controls the rinser and brush device to remove dust from the greenhouse film corresponding to the first film image.

[0056] The present embodiment corrects greenhouse film spectral data for trapezoidal distortion using an interpolation algorithm, obtaining distortion-free spectral data. This allows for more accurate spectral analysis and greenhouse film thickness calculation, improving the quality of the spectral data and the accuracy of the analysis, thereby increasing the precision of greenhouse film thickness measurement. By comparing the precise film thickness with the preset film thickness, dust removal can be completed, further improving dust removal efficiency and avoiding errors in film thickness calculation that could lead to increased dust removal costs.

[0057] The embodiment of the present application also provides a greenhouse film dust removal system, comprising: an acquisition module configured to acquire target greenhouse film images of multiple greenhouses; a controller configured to identify foreign matter in the target greenhouse film images; for a first greenhouse film image in which no foreign matter exists in the target greenhouse film image, the acquisition module is configured to acquire light intensity, light transmittance and greenhouse film spectrum data of the greenhouse corresponding to the first greenhouse film image; the controller is configured to process the greenhouse film spectrum data to obtain the greenhouse film thickness of the greenhouse corresponding to the first greenhouse film image; the controller is configured to process the greenhouse film spectrum data to obtain the greenhouse film thickness of the greenhouse corresponding to the first greenhouse film image; The controller is configured to compare the light intensity and transmittance with the preset light intensity and transmittance, and to compare the greenhouse film thickness with the preset greenhouse film thickness; when the light intensity and transmittance are both less than the corresponding preset light intensity and preset transmittance, the controller is configured to generate a first dust removal instruction; when the greenhouse film thickness is greater than the preset greenhouse film thickness, the controller is configured to generate a second dust removal instruction; the drone is configured to remove dust from the greenhouse film of the greenhouse corresponding to the first greenhouse film image through a shower device and a brush device based on the first dust removal instruction or the second dust removal instruction.

[0058] The details of the embodiments of the present application have been described in the aforementioned embodiments and will not be repeated here.

[0059] In one embodiment of the present application, for a second greenhouse film image in which foreign matter exists in the target greenhouse film image, the controller is configured to generate a third dust removal instruction; the drone is configured to remove dust from the greenhouse film of the greenhouse corresponding to the second greenhouse film image through a high-pressure air pump device and a brush device based on the third dust removal instruction.

[0060] In one embodiment of the present application, when there is no trapezoidal distortion in the greenhouse film spectral data, the controller is configured to perform spectral analysis on the greenhouse film spectral data to obtain a corresponding spectral interference diagram; the controller is configured to calculate the thickness of the greenhouse film at various positions of the greenhouse corresponding to the first greenhouse film image based on the spectral position and distance between the constructive interferences in the spectral interference diagram; the controller is configured to calculate the average thickness of the greenhouse film of the greenhouse corresponding to the first greenhouse film image based on the thickness of the greenhouse film at various positions of the greenhouse corresponding to the first greenhouse film image, and use the average thickness as the greenhouse film thickness.

[0061] In one embodiment of the present application, the controller is configured to perform position dimension distortion correction on the greenhouse film spectral data by using an interpolation algorithm when there is trapezoidal distortion in the greenhouse film spectral data, so as to obtain greenhouse film spectral data without trapezoidal distortion.

[0062] In one embodiment of the present application, the high-pressure air pump device includes a micro high-pressure air pump and an air gun nozzle device, the rinsing device includes a water tank and a rinsing nozzle device, and the brush device includes a rotating brush and a telescopic rod.

[0063] In one embodiment of the present application, the acquisition module includes an image acquisition module, a spectrum acquisition module and a sensor module; the image acquisition module is configured to acquire the target greenhouse film image; the spectrum acquisition module is configured to acquire greenhouse film spectrum data; the sensor module is configured to acquire light intensity and transmittance.

[0064] It should be noted that the above embodiments can be freely combined as needed. The above are only preferred embodiments of the present invention. It should be pointed out that those skilled in the art can make several improvements and modifications without departing from the principles of the present invention, and such improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for removing dust from greenhouse film, characterized in that: include: Collecting a plurality of target greenhouse film images of the greenhouse; For a first greenhouse film image in which no foreign matter exists in the target greenhouse film image, collecting light intensity, light transmittance and greenhouse film spectrum data of the greenhouse corresponding to the first greenhouse film image; Processing the greenhouse film spectral data to obtain the greenhouse film thickness of the greenhouse corresponding to the first greenhouse film image; When the light intensity and the light transmittance are both less than the corresponding preset light intensity and preset light transmittance, dust is removed from the greenhouse film corresponding to the first greenhouse film image by using a shower device and a brush device; or, When the thickness of the greenhouse film is greater than a preset greenhouse film thickness, the greenhouse film of the greenhouse corresponding to the first greenhouse film image is dusted by the shower device and the brush device.

2. The greenhouse film dust removal method according to claim 1, characterized in that: Also includes: For the second greenhouse film image in which foreign matter exists in the target greenhouse film image, dust is removed from the greenhouse film corresponding to the second greenhouse film image by using a high-pressure air pump device and a brush device.

3. The greenhouse film dust removal method according to claim 1, characterized in that: The processing of the greenhouse film spectral data to obtain the greenhouse film thickness of the greenhouse corresponding to the first greenhouse film image specifically includes: When there is no trapezoidal distortion in the greenhouse film spectrum data, performing spectral analysis on the greenhouse film spectrum data to obtain a corresponding spectral interference diagram; Calculating the thickness of the greenhouse film at each position of the greenhouse corresponding to the first greenhouse film image according to the spectral position and distance between the constructive interferences in the spectral interference pattern; According to the thickness of each position of the greenhouse film of the greenhouse corresponding to the first greenhouse film image, the average thickness of the greenhouse film corresponding to the first greenhouse film image is calculated, and the average thickness is used as the greenhouse film thickness.

4. The greenhouse film dust removal method according to claim 3, characterized in that: Also includes: When there is trapezoidal distortion in the greenhouse film spectrum data, the greenhouse film spectrum data is corrected for distortion in the position dimension by using an interpolation algorithm to obtain the greenhouse film spectrum data without trapezoidal distortion.

5. A greenhouse film dust removal system, characterized in that: include: A collection module is configured to collect a plurality of target greenhouse film images of the greenhouse; A controller configured to identify foreign matter in the target greenhouse film image; For a first greenhouse film image in which no foreign matter exists in the target greenhouse film image, the acquisition module is configured to acquire light intensity, light transmittance and greenhouse film spectrum data of the greenhouse corresponding to the first greenhouse film image; The controller is configured to process the greenhouse film spectrum data to obtain the greenhouse film thickness of the greenhouse corresponding to the first greenhouse film image; The controller is configured to compare the light intensity and the light transmittance with a preset light intensity and a preset light transmittance, and to compare the greenhouse film thickness with a preset greenhouse film thickness; When the light intensity and the light transmittance are both less than the corresponding preset light intensity and preset light transmittance, the controller is configured to generate a first dust removal instruction; When the greenhouse film thickness is greater than a preset greenhouse film thickness, the controller is configured to generate a second dust removal instruction; The drone is configured to remove dust from the greenhouse film corresponding to the first greenhouse film image through a shower device and a brush device based on the first dust removal instruction or the second dust removal instruction.

6. The greenhouse film dust removal system according to claim 5, characterized in that: The controller is configured to generate a third dust removal instruction for a second greenhouse film image in which foreign matter exists in the target greenhouse film image; The drone is configured to remove dust from the greenhouse film corresponding to the second greenhouse film image by using a high-pressure air pump device and a brush device based on the third dust removal instruction.

7. The greenhouse film dust removal system according to claim 5, characterized in that: When there is no trapezoidal distortion in the greenhouse film spectrum data, the controller is configured to perform spectral analysis on the greenhouse film spectrum data to obtain a corresponding spectral interference diagram; The controller is configured to calculate the thickness of the greenhouse film at various positions corresponding to the first greenhouse film image according to the spectral position and distance between the constructive interferences in the spectral interference diagram; The controller is configured to calculate the average thickness of the greenhouse film corresponding to the first greenhouse film image according to the thickness of each position of the greenhouse film corresponding to the first greenhouse film image, and use the average thickness as the greenhouse film thickness.

8. The greenhouse film dust removal system according to claim 6, characterized in that: The controller is configured to perform distortion correction on the greenhouse film spectrum data in a position dimension by using an interpolation algorithm when there is trapezoidal distortion in the greenhouse film spectrum data, so as to obtain the greenhouse film spectrum data without trapezoidal distortion.

9. The greenhouse film dust removal system according to claim 8, characterized in that: The high-pressure air pump device comprises a micro high-pressure air pump and an air gun nozzle device, the rinsing device comprises a water tank and a rinsing nozzle device, and the brush device comprises a rotating brush and a telescopic rod.

10. The greenhouse film dust removal system according to any one of claims 6 to 9, characterized in that: The acquisition module includes an image acquisition module, a spectrum acquisition module and a sensor module; The image acquisition module is configured to acquire the target greenhouse film image; The spectrum acquisition module is configured to acquire the spectral data of the greenhouse film; The sensor module is configured to collect the light intensity and the light transmittance.

Images