Unmanned aerial vehicle cleaning method and system for building glass curtain wall

Abstract

The invention discloses an unmanned aerial vehicle cleaning method and system for a building glass curtain wall, and relates to the technical field of glass curtain wall cleaning.The method comprises the steps that firstly, according to the stain condition of the glass curtain wall, a cleaning brush, a cleaning agent, a sewage recycling device and related control parameters which have a good cleaning effect on the glass curtain wall are selected; the control and cleaning effect of subsequent stain cleaning is improved, the probability that sewage causes secondary pollution to the glass curtain wall is reduced, the cleaning difficulty is reduced, meanwhile, the safety of the glass curtain wall is effectively guaranteed, operation of the cleaning brush, the water spraying device and the sewage recycling device is monitored and analyzed in the cleaning process, and the cleaning effect is improved. The abnormal states of the cleaning brush, the water spraying device and the sewage recovery device can be found in time, so that adjustment is conducted in time, the curtain wall cleaning progress and effect are guaranteed, and the cleaning efficiency of the glass curtain wall is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of glass curtain wall cleaning, and in particular to a drone cleaning method and system for building glass curtain walls. Background Art

[0002] If glass curtain walls are not cleaned promptly, they may pose safety risks such as glass breakage. Drones can conduct comprehensive and detailed inspections and cleaning of glass curtain walls. Their high cleaning efficiency and maneuverability allow for more frequent cleaning of glass curtain walls, improving the overall image of the building.

[0003] In the existing technology, most of the parameters of the cleaning device in the drone are manually set, and then the drone is equipped with the cleaning device for cleaning. However, this method has at least the following shortcomings: 1. The cleaning device includes a cleaning brush, a water spray device and a sewage recovery device. At the same time, the water spray device is mixed with a detergent. The addition of the detergent can accelerate the cleaning speed of the stains in the glass curtain wall, but different types of detergents are suitable for different stains. For example, acidic detergents can effectively remove stubborn stains such as oil and water stains on the glass. Therefore, choosing the right type of detergent can improve the stain removal efficiency. However, in the existing technology, most of the detergents are selected manually based on experience, and are not selected based on the situation of the stains in the glass curtain wall, which cannot improve the subsequent cleaning efficiency.

[0004] 2. The brush heads of cleaning brushes are of various types, such as soft and hard. Different types of cleaning brushes have different cleaning effects on stains in curtain walls. However, the existing technology lacks the ability to select the appropriate type of cleaning brush according to the conditions of the stains in the curtain wall, which cannot improve the effect of subsequent stain cleaning and cannot effectively ensure the safety of the glass curtain wall.

[0005] 3. The sewage recovery device can recycle the cleaned sewage to prevent the sewage from flowing onto the glass curtain wall and causing secondary pollution. However, the recovery effects of different sewage recovery devices are different. The existing technology lacks the ability to select a suitable sewage recovery device based on the recovery effect of the sewage recovery device, thereby failing to ensure the timeliness of sewage recovery, increasing the probability of sewage causing secondary pollution to the glass curtain wall and reducing the curtain wall cleaning efficiency.

[0006] 4. The normal operation of the cleaning brush, water spray device and sewage recovery device during cleaning is a prerequisite for the complete cleaning of the curtain wall. However, the existing technology lacks monitoring and analysis of the operation of the cleaning brush, water spray device and sewage recovery device, and cannot timely detect the abnormal status of the cleaning brush, water spray device and sewage recovery device, so it is impossible to make timely adjustments, which affects the progress and effect of curtain wall cleaning. Summary of the Invention

[0007] In view of the above-mentioned technical deficiencies, the object of the present invention is to provide a drone cleaning method and system for building glass curtain walls.

[0008] In order to solve the above technical problems, the present invention adopts the following technical solutions: In the first aspect, the present invention provides a drone cleaning method for building glass curtain walls, comprising the following steps: S1. Cleaning device selection: model the building glass curtain wall and select the cleaning device solution corresponding to the drone.

[0009] S2. Cleaning control: Obtain the cleaning order of each cleaning area in the building's glass curtain wall. When the drone starts cleaning each cleaning area, use the 3D model of each cleaning area to control the operation of the drone's cleaning brush, water spray device, and sewage recovery device.

[0010] S3. Cleaning control adjustment: When the drone is cleaning each cleaning area, monitor the operation of the cleaning brush, water spray device and sewage recovery device in each cleaning area, analyze the operating status of the cleaning brush, water spray device and sewage recovery device, and then make corresponding adjustments.

[0011] In a second aspect, the present invention provides a drone cleaning system for building glass curtain walls, comprising: a cleaning device selection module for modeling the building glass curtain wall and selecting a cleaning device solution corresponding to the drone.

[0012] The cleaning control module is used to obtain the cleaning order of each cleaning area in the building's glass curtain wall. When the drone starts cleaning each cleaning area, the three-dimensional model of each cleaning area is used to control the operation of the drone's cleaning brush, water spray device and sewage recovery device.

[0013] The cleaning control adjustment module is used to monitor the operation of the cleaning brushes, water spray devices and sewage recovery devices in each cleaning area when the drone is cleaning each cleaning area, analyze the operating status of the cleaning brushes, water spray devices and sewage recovery devices, and then make corresponding adjustments.

[0014] The beneficial effects of the present invention are as follows: the present invention provides a drone cleaning method and system for building glass curtain walls, which improves the control and cleaning effect of subsequent stain cleaning by selecting a cleaning brush, a cleaning agent, a sewage recovery device and related control parameters according to the stain condition of the glass curtain wall, reduces the probability of secondary pollution of the glass curtain wall by sewage, and effectively ensures the safety of the glass curtain wall. During the cleaning process, the operation of the cleaning brush, the water spray device and the sewage recovery device is monitored and analyzed, and abnormal conditions of the cleaning brush, the water spray device and the sewage recovery device can be discovered in time, so that timely adjustments can be made to ensure the progress and effect of curtain wall cleaning. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0016] Figure 1 The figure is a schematic flow chart of the steps for implementing the method of the present invention.

[0017] Figure 2 This is a schematic diagram of the system structure connection of the present invention. DETAILED DESCRIPTION

[0018] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0019] Example 1:

[0020] See also Figure 1 As shown, a drone cleaning method for a building glass curtain wall comprises the following steps: S1, selecting a cleaning device: modeling the building glass curtain wall, and selecting a cleaning device solution corresponding to the drone.

[0021] In the above, the image of the glass curtain wall of the building is collected by the camera carried by the drone, and then three-dimensional modeling is performed to obtain a three-dimensional model of the glass curtain wall of the building.

[0022] In a specific embodiment, the specific process of selecting the cleaning device scheme corresponding to the drone is as follows: based on the three-dimensional model of the glass curtain wall of the building, the curtain wall is divided into a grid to obtain each cleaning area, and the stain data of each cleaning area is obtained. The stain data, cleaning brush type and a type of cleaning characteristic value of the historical cleaning area corresponding to each cleaning are obtained from the cleaning records. The stain data and a type of cleaning characteristic value of each cleaning brush type for each cleaning are counted, and then the cleaning priority value of each cleaning brush type is calculated, and the cleaning brush type with the largest cleaning priority value is selected as the cleaning brush type for the curtain wall.

[0023] It should be noted that the stain data includes the size, type, and location of the stain. The stain data of each cleaning area is obtained from the three-dimensional model of the building's glass curtain wall. Cleaning records are obtained from the database.

[0024] The stain types include cement stains, lime stains, oil stains, etc. An image of the stain can be obtained from a 3D model of the glass curtain wall of the building and compared with standard images of each stain type stored in a database to obtain the stain type.

[0025] Cleaning brush types include fiber flat brushes and crevice brushes.

[0026] Preferably, the cleaning priority value of each cleaning brush type is calculated as follows: the stain data and a type of cleaning characteristic value of each cleaning brush type are recorded as WZ xf and κ1 xf , where x represents the number of each cleaning brush type, f represents the number of each cleaning, x and f are positive integers, and the stain data of each cleaning area is recorded as WZ y , y represents the number of each cleaning area, and y is a positive integer.

[0027] Using the calculation formula: Get the cleaning priority value α1 of the x-th cleaning brush type x , where F and Y represent the total number of cleaning times and the number of cleaning areas, respectively, and e represents a natural constant.

[0028] Obtain the stain data, detergent type, and Class II cleaning characteristic values ​​for the historical cleaning area corresponding to each cleaning session from the cleaning records. Then, count the stain data and Class II cleaning characteristic values ​​for each detergent type for each cleaning session, calculate the cleaning priority value for each detergent type, and select the detergent type with the largest cleaning priority value as the curtain wall detergent type.

[0029] It should be noted that the types of cleaning agents include glass water, white vinegar solution and citric acid solution.

[0030] It should also be noted that the calculation method of the cleaning priority value of each cleaning agent type is the same as the calculation method of the cleaning priority value of each cleaning brush type, which will not be repeated here.

[0031] The cleaning agent type, wastewater recovery device, and three types of cleaning characteristic values ​​for the historical cleaning area corresponding to each cleaning are obtained from the cleaning records. Then, the cleaning agent type and three types of cleaning characteristic values ​​of each wastewater recovery device for each cleaning are counted, and the cleaning priority value of each wastewater recovery device is calculated. The wastewater recovery device with the largest cleaning priority value is selected as the wastewater recovery device for the curtain wall.

[0032] It should be noted that the sewage recovery device includes a combination device of suction cup adsorption and water pump recovery and a combination device of scraper bar and sewage collection tank recovery.

[0033] It should also be noted that the calculation method of the cleaning priority value of each sewage recovery device is the same as the calculation method of the cleaning priority value of each cleaning brush type, which will not be repeated here.

[0034] The curtain wall cleaning brush type, cleaning agent type and sewage recovery device are used as the corresponding cleaning device plan for the drone.

[0035] S2. Cleaning control: Obtain the cleaning order of each cleaning area in the building's glass curtain wall. When the drone starts cleaning each cleaning area, use the 3D model of each cleaning area to control the operation of the drone's cleaning brush, water spray device, and sewage recovery device.

[0036] In a specific embodiment, the operation of the cleaning brush in the drone is controlled, and the specific control process is as follows: the stain data, cleaning control data, cleaning time, post-cleaning stain data and post-cleaning damage data of the historical cleaning area of ​​the curtain wall cleaning brush type in each historical cleaning are obtained from the cleaning record, as the stain data, cleaning control data, cleaning time, post-cleaning stain data and post-cleaning damage data of the historical cleaning area of ​​the cleaning brush in each historical cleaning, the stain data of the historical cleaning area of ​​the cleaning brush in each historical cleaning is compared with the stain data of each cleaning area, if the stain data of a cleaning area is the same as the stain data of the historical cleaning area of ​​the cleaning brush in a certain historical cleaning, then the historical cleaning is used as the reference cleaning of the cleaning area, thereby obtaining each reference cleaning of each cleaning area, obtaining the cleaning control data, cleaning time, post-cleaning stain data and post-cleaning damage data of each cleaning area corresponding to each reference cleaning, and counting the average cleaning time, average post-cleaning stain data and average post-cleaning damage data of each cleaning area corresponding to each cleaning control data, and then normalizing them, and recording the processed values ​​as a1 respectively. yd 、a2 yd and a3 yd , d represents the number of each gear, and d is a positive integer.

[0037] Using the calculation formula: Get the cleaning effect value of the dth cleaning control data in the yth cleaning area The cleaning control data with the largest cleaning effect value is selected as the cleaning control data when the cleaning brush cleans each cleaning area, and corresponding control is performed when cleaning each cleaning area.

[0038] It should be noted that cleaning control data includes the speed and rotation duration of the cleaning brush, post-cleaning stain data, and post-cleaning damage data, such as scratch size and depth. A drone-mounted camera can capture images of the cleaned glass curtain wall to obtain post-cleaning stain and damage data. The drone records the cleaning control data of the cleaning brush during cleaning.

[0039] In another specific embodiment, the operation of the water spray device in the drone is controlled, and the specific process is as follows: the stain data, injection control data, liquid excess area and sewage collection angle change times of the curtain wall detergent type in each historical cleaning area in each historical cleaning are obtained from the cleaning record; if the stain data of a cleaning area is the same as the stain data of the detergent type in the historical cleaning area in a certain historical cleaning, then the historical cleaning is used as the reference cleaning of the cleaning area, thereby obtaining each reference cleaning of each cleaning area, obtaining the injection control data, liquid excess area and sewage collection angle change times corresponding to each reference cleaning of each cleaning area, and calculating the injection effect value of each injection control data in each cleaning area; selecting the injection control data with the largest injection effect value as the injection control data when the water spray device cleans each cleaning area, and performing corresponding control.

[0040] It should be noted that the injection control data includes the spray pressure and the distance between the nozzle and the curtain wall. When the drone is cleaning, it records the cleaning control data of the water spray device; the liquid excess area is the area where the liquid exceeds the cleaning area after the water spray device sprays the liquid. The drone can use the camera equipped with it to collect the image of the cleaning area after the water spray device sprays the liquid, and obtain the liquid excess area from the image of the cleaning area; the number of changes in the sewage collection angle refers to the number of times the sewage recovery device recovers the sewage in the cleaning area after the water spray device sprays liquid into the cleaning area and completes the cleaning. The drone can use the camera equipped with it to collect the video of the cleaning area during cleaning, and obtain the number of changes in the sewage collection angle from the video.

[0041] In the above description, the calculation method of the spraying effect value of each spraying control data in each cleaning area is the same as the calculation method of the cleaning effect value of the d-th cleaning control data in the y-th cleaning area, which will not be repeated here.

[0042] In another specific embodiment, the operation of the sewage recovery device in the described control drone is specifically controlled as follows: the sewage shape of the historical cleaning area, the collection port control data, the sewage diffusion area during suction, and the sewage residual area after suction of the sewage recovery device of the curtain wall in each historical cleaning are obtained from the cleaning records, thereby calculating the recovery effect value of each collection port control data when the sewage recovery device absorbs each sewage shape, and selecting the collection port control data with the largest recovery effect value as the collection port control data when the sewage recovery device absorbs each sewage shape. When each cleaning area needs to collect sewage, the sewage shape of each cleaning area is collected, and then compared with the collection port control data when the sewage recovery device absorbs each sewage shape, the collection port control data when the sewage recovery device absorbs sewage in each cleaning area is obtained, and corresponding control is performed.

[0043] It should be noted that the drone's onboard camera captures images of the cleaned area before cleaning, and the shape of the sewage is derived from these images. The collection port control data includes data on the size and shape of the collection port. During cleaning, the drone records the collection port control data of the sewage recovery device.

[0044] The diffusion area of ​​sewage during suction is the diffusion area of ​​sewage in the clean area when the sewage recovery device is recycling sewage in the clean area; the camera carried by the drone is used to collect a video of the sewage recovery device recycling sewage in the clean area, and the sewage area in each frame of the video is obtained from the video, and compared with the sewage area in the initial frame, and the area in each frame that does not overlap with the sewage area in the initial frame is obtained, recorded as each diffusion area, and the image recognition technology is used to obtain the area of ​​each diffusion area, and the accumulation is performed to obtain the diffusion area of ​​sewage during suction; the residual sewage area after suction represents the remaining sewage area after the sewage recovery device completes sewage recycling in the clean area, and the camera carried by the drone is used to collect an image of the clean area after the sewage recovery device completes sewage recycling in the clean area, and the remaining sewage area is obtained from the image.

[0045] Preferably, the calculation process of the recovery effect value of each collection port control data when the sewage recovery device absorbs various sewage shapes is as follows: using the sewage shape of the historical cleaning area, the collection port control data, the sewage diffusion area during suction and the sewage residual area after suction of the sewage recovery device in each historical cleaning, the collection port control data, the sewage diffusion area during suction and the sewage residual area after suction when the sewage recovery device absorbs various sewage shapes are counted, and then the mean is calculated, and the calculation result is used as the collection port control data, the average sewage diffusion area during suction and the average sewage residual area after suction when the sewage recovery device absorbs various sewage shapes; the average sewage diffusion area during suction and the average sewage residual area after suction when the sewage recovery device absorbs various sewage shapes are normalized, and then the mean is calculated to obtain the recovery effect value of each collection port control data when the sewage recovery device absorbs various sewage shapes.

[0046] S3. Cleaning control adjustment: When the drone is cleaning each cleaning area, monitor the operation of the cleaning brush, water spray device and sewage recovery device in each cleaning area, analyze the operating status of the cleaning brush, water spray device and sewage recovery device, and then make corresponding adjustments.

[0047] In a specific embodiment, the operating status of the cleaning brush is analyzed, and the specific process is as follows: when the drone cleans each cleaning area, the camera carried by the drone is used to collect the operating video of the cleaning brush in each cleaning area, and the stain cleaning coverage area of ​​the cleaning brush in each cleaning area is obtained from the operating video of the cleaning brush in each cleaning area. Using the three-dimensional model of the curtain wall, each cleaning area is divided into a primary area, a secondary area and a tertiary area, and the number of times the cleaning brush cleans the primary area, the secondary area and the tertiary area in each cleaning area is obtained from the operating video of the cleaning brush in each cleaning area. Then, the stain cleaning coverage area of ​​the cleaning brush in each cleaning area and the average number of times the cleaning brush cleans the primary area, the secondary area and the tertiary area are cleaned are used to calculate the operating status value of the cleaning brush.

[0048] It should be noted that the stain cleaning coverage area refers to the area where the area cleaned by the cleaning brush overlaps with the stain.

[0049] Several collection points are evenly distributed in each cleaning area, and the stain data of each collection point is obtained. The stain data of each collection point is compared with the preset stain data interval corresponding to each area level to obtain the area level corresponding to each collection point. All collection points of each area level are gathered and divided into each area level. Each area level includes first-level area, second-level area and third-level area.

[0050] The first-level area is the area with fewer stains, the second-level area is the area with more stains, and the third-level area is the area with very many stains. The stain data interval corresponding to each area level is set by the staff according to needs.

[0051] The average number of times the cleaning brush cleans the stain coverage area, cleans the primary area, the secondary area, and the tertiary area in each cleaning area is recorded as SS1 y 、a1 y 、a2 y and a3 y The total area of ​​stains in each clean area is obtained from the 3D model of the curtain wall, which is recorded as SS2 y , obtain the average number of times the cleaning brush cleans the primary, secondary, and tertiary areas in each historical cleaning from the cleaning records, and then calculate the mean, which is used as the reference cleaning number of the primary, secondary, and tertiary areas, respectively, and recorded as a1, a2, and a3; then use the analytical formula:

[0052] The running state value ω of the cleaning brush is obtained, where Y represents the number of cleaning areas.

[0053] Where, The calculation result is a class of clean eigenvalues.

[0054] The running status value of the cleaning brush includes values ​​of 1 and -1. When the running status value of the cleaning brush is 1, it indicates that the cleaning brush is running normally. When the running status value of the cleaning brush is -1, it indicates that the cleaning brush is running abnormally.

[0055] In another specific embodiment, the operating status of the water spray device is analyzed, and the specific process is as follows: when the drone cleans each cleaning area, the camera carried by the drone is used to collect the operating data of the water spray device in each cleaning area, and the spray stain coverage area of ​​the water spray device in each cleaning area, as well as the residual stain area of ​​the primary area, the secondary area and the tertiary area in each cleaning area after cleaning are obtained from the operating data of the water spray device in each cleaning area, and then the operating status value of the water spray device is calculated.

[0056] The operating status value of the water spray device includes values ​​of 1 and -1. When the operating status value of the water spray device is 1, it indicates that the water spray device is operating normally. When the operating status value of the water spray device is -1, it indicates that the water spray device is operating abnormally.

[0057] It should be noted that the spray stain coverage area refers to the area where the area where the liquid is sprayed by the water spraying device overlaps with the stain area.

[0058] The calculation methods of the operating state value and the second-class cleaning characteristic value of the water spray device are the same as those of the operating state value and the first-class cleaning characteristic value of the cleaning brush, and will not be repeated here.

[0059] In a specific embodiment, the operation status analysis process of the sewage recovery device is as follows: when the drone cleans each cleaning area, the camera carried by the drone is used to collect the operation video of the sewage recovery device in each cleaning area, and the sewage area before suction, sewage diffusion area and sewage residual area after suction of the sewage recovery device in each cleaning area are obtained from the operation video of the sewage recovery device in each cleaning area, and the operation status value of the sewage recovery device is calculated.

[0060] The operating status value of the sewage recovery device includes values ​​of 1 and -1. When the operating status value of the sewage recovery device is 1, it indicates that the sewage recovery device is operating normally. When the operating status value of the sewage recovery device is -1, it indicates that the sewage recovery device is operating abnormally.

[0061] It should be noted that the sewage diffusion area refers to the area where the sewage diffuses during the sewage recovery process of the sewage recovery device, and the sewage residual area after suction refers to the area remaining after the sewage recovery device recovers the sewage.

[0062] Obtain the sewage area before suction, sewage diffusion area and sewage residual area after suction corresponding to each historical sewage recovery of the sewage recovery device from the cleaning records, select each historical sewage recovery with the same sewage area before suction as the sewage area before suction of each cleaning area as each reference recovery of each cleaning area, obtain the sewage diffusion area and sewage residual area after suction corresponding to each reference recovery of each cleaning area, select the mode as the allowable sewage diffusion area and allowable sewage residual area after suction of each cleaning area, respectively, and record them as SS3 y and SS4 y The sewage diffusion area and the residual area of ​​sewage after suction of the sewage recovery device in each clean area are recorded as SS3′ y and SS4′ y , using the calculation formula:

[0063] Get the operating state value ξ of the sewage recovery device, where The calculation results are three types of cleaning characteristic values.

[0064] Example 2:

[0065] See also Figure 2 As shown, a drone cleaning system for building glass curtain walls includes: a cleaning device selection module, a cleaning control module, a cleaning control adjustment module and a database.

[0066] The cleaning device selection module is used to model the glass curtain wall of the building and select the corresponding cleaning device solution carried by the drone.

[0067] The cleaning control module is used to obtain the cleaning order of each cleaning area in the building's glass curtain wall. When the drone starts cleaning each cleaning area, the three-dimensional model of each cleaning area is used to control the operation of the drone's cleaning brush, water spray device and sewage recovery device.

[0068] The cleaning control adjustment module is used to monitor the operation of the cleaning brushes, water spray devices and sewage recovery devices in each cleaning area when the drone is cleaning each cleaning area, analyze the operating status of the cleaning brushes, water spray devices and sewage recovery devices, and then make corresponding adjustments.

[0069] A database for storing cleaning records and standard images of each stain type.

[0070] The present invention selects a cleaning brush, a cleaning agent, a sewage recovery device and related control parameters that have a good cleaning effect on the glass curtain wall according to the stain condition of the glass curtain wall, thereby improving the control and cleaning effect of subsequent stain cleaning, reducing the probability of sewage causing secondary pollution to the glass curtain wall, and effectively ensuring the safety of the glass curtain wall. During the cleaning process, the operation of the cleaning brush, the water spray device and the sewage recovery device is monitored and analyzed, and abnormal conditions of the cleaning brush, the water spray device and the sewage recovery device can be discovered in time, so that timely adjustments can be made to ensure the progress and effect of curtain wall cleaning. The above content is only an example and explanation of the concept of the present invention. Technicians in this technical field can make various modifications or supplements to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined in this specification, they should all fall within the scope of protection of the present invention.

Claims

1. A drone cleaning method for a building glass curtain wall, characterized in that: The steps include: S1. Cleaning device selection: Model the glass curtain wall of the building and select the cleaning device solution that can be carried by the drone; S2. Cleaning control: Obtain the cleaning order of each cleaning area in the building's glass curtain wall. When the drone starts cleaning each cleaning area, use the 3D model of each cleaning area to control the operation of the drone's cleaning brush, water spray device, and wastewater recovery device. S3. Cleaning control adjustment: When the drone is cleaning each cleaning area, monitor the operation of the cleaning brush, water spray device and sewage recovery device in each cleaning area, analyze the operating status of the cleaning brush, water spray device and sewage recovery device, and then make corresponding adjustments.

2. A drone cleaning method for a building glass curtain wall according to claim 1, characterized in that: The specific process of selecting the cleaning device solution corresponding to the drone is as follows: Based on the 3D model of the building's glass curtain wall, the curtain wall is divided into a grid to obtain various cleaning areas. The stain data of each cleaning area is obtained. The stain data, cleaning brush type, and a type of cleaning characteristic value corresponding to each cleaning session are obtained from the cleaning records. The stain data and a type of cleaning characteristic value of each cleaning brush type are counted. The cleaning priority value of each cleaning brush type is then calculated, and the cleaning brush type with the largest cleaning priority value is selected as the cleaning brush type for the curtain wall. Obtain the stain data, cleaning agent type, and Class II cleaning characteristic value of each cleaning area from the cleaning records. Then, calculate the stain data and Class II cleaning characteristic value of each cleaning agent type, calculate the cleaning priority value of each cleaning agent type, and select the cleaning agent type with the largest cleaning priority value as the curtain wall cleaning agent type. Obtain the cleaning agent type, wastewater recovery device, and three types of cleaning characteristic values ​​for each historical cleaning area from the cleaning records. Then, count the cleaning agent type and three types of cleaning characteristic values ​​for each wastewater recovery device during each cleaning. Calculate the cleaning priority value for each wastewater recovery device, and select the wastewater recovery device with the largest cleaning priority value as the wastewater recovery device for the curtain wall. The curtain wall cleaning brush type, cleaning agent type and sewage recovery device are used as the corresponding cleaning device plan for the drone.

3. A drone cleaning method for a building glass curtain wall according to claim 2, characterized in that: The specific process of calculating the cleaning priority value of each cleaning brush type is as follows: The stain data and cleaning characteristic values ​​of each cleaning brush type are recorded as WZ xf and κ1 xf , where x represents the number of each cleaning brush type, f represents the number of each cleaning, x and f are positive integers, and the stain data of each cleaning area is recorded as WZ y , y represents the number of each cleaning area, y is a positive integer; Using the calculation formula: Get the cleaning priority value α1 of the x-th cleaning brush type x , where F and Y represent the total number of cleaning times and the number of cleaning areas, respectively, and e represents a natural constant.

4. A drone cleaning method for a building glass curtain wall according to claim 2, characterized in that: Control the operation of the cleaning brush in the drone. The specific control process is as follows: The stain data, cleaning control data, cleaning time, post-cleaning stain data and post-cleaning damage data of the historical cleaning area of ​​the curtain wall cleaning brush type in each historical cleaning are obtained from the cleaning records, and the stain data, cleaning control data, cleaning time, post-cleaning stain data and post-cleaning damage data of the historical cleaning area of ​​the cleaning brush in each historical cleaning are used as the stain data, cleaning control data, cleaning time, post-cleaning stain data and post-cleaning damage data of the historical cleaning area of ​​the cleaning brush in each historical cleaning are compared with the stain data of each cleaning area. If the stain data of a cleaning area is the same as the stain data of the historical cleaning area of ​​the cleaning brush in a certain historical cleaning, then this historical cleaning is used as the reference cleaning of the cleaning area, so as to obtain each reference cleaning of each cleaning area, obtain the cleaning control data, cleaning time, post-cleaning stain data and post-cleaning damage data of each cleaning area corresponding to each reference cleaning, and calculate the average cleaning time, average post-cleaning stain data and average post-cleaning damage data of each cleaning area corresponding to each cleaning control data, and then perform normalization processing, and record the processed values ​​as a1 respectively yd 、a2 yd and a3 yd , d represents the number of each gear, d is a positive integer; Using the calculation formula: Get the cleaning effect value of the dth cleaning control data in the yth cleaning area The cleaning control data with the largest cleaning effect value is selected as the cleaning control data when the cleaning brush cleans each cleaning area, and corresponding control is performed when cleaning each cleaning area.

5. A drone cleaning method for a building glass curtain wall according to claim 4, characterized in that: Control the operation of the water spray device in the drone. The specific process is as follows: Obtain from the cleaning records the stain data of the cleaning agent type of the curtain wall, the historical cleaning area, the spray control data, the liquid overflow area, and the number of times the sewage collection angle changes during each historical cleaning; If the stain data of a certain cleaning area is the same as the stain data of the historical cleaning area in a certain historical cleaning of the detergent type, then the historical cleaning is used as the reference cleaning of the cleaning area, so as to obtain the reference cleaning of each cleaning area, obtain the injection control data, liquid excess area and sewage collection change angle number of each cleaning area corresponding to each reference cleaning, calculate the injection effect value of each injection control data in each cleaning area; select the injection control data with the largest injection effect value as the injection control data when the water spray device cleans each cleaning area, and perform corresponding control.

6. The method for cleaning a glass curtain wall of a building by using a drone according to claim 4, wherein: The specific process of controlling the operation of the sewage recovery device in the drone is as follows: The sewage shape, collection port control data, sewage diffusion area during suction and sewage residual area after suction of the curtain wall sewage recovery device in each historical cleaning are obtained from the cleaning records. The recovery effect value of each collection port control data when the sewage recovery device absorbs each sewage shape is calculated, and the collection port control data with the largest recovery effect value is selected as the collection port control data when the sewage recovery device absorbs each sewage shape. When each cleaning area needs to collect sewage, the sewage shape of each cleaning area is collected, and then compared with the collection port control data when the sewage recovery device absorbs each sewage shape, the collection port control data when the sewage recovery device absorbs sewage in each cleaning area is obtained, and corresponding control is performed.

7. The method for cleaning a glass curtain wall of a building by using a drone according to claim 1, wherein: Analyze the operating status of the cleaning brush. The specific process is as follows: When the drone cleans each cleaning area, the camera carried by the drone is used to collect the operation video of the cleaning brush in each cleaning area, and the stain cleaning coverage area of ​​the cleaning brush in each cleaning area is obtained from the operation video of the cleaning brush in each cleaning area. Using the three-dimensional model of the curtain wall, each cleaning area is divided into a primary area, a secondary area, and a tertiary area. The number of times the cleaning brush cleans the primary area, the secondary area, and the tertiary area in each cleaning area is obtained from the operation video of the cleaning brush in each cleaning area. Then, the operation status value of the cleaning brush is calculated using the stain cleaning coverage area and the average number of times the cleaning brush cleans the primary area, the secondary area, and the tertiary area in each cleaning area. The running status value of the cleaning brush includes values ​​of 1 and -1. When the running status value of the cleaning brush is 1, it indicates that the cleaning brush is running normally. When the running status value of the cleaning brush is -1, it indicates that the cleaning brush is running abnormally.

8. The method for cleaning a building glass curtain wall with a drone according to claim 7, wherein: Analyze the operating status of the water spray device. The specific process is as follows: When the drone cleans each cleaning area, the camera carried by the drone is used to collect the operating data of the water spray device in each cleaning area. The water spray device's spray stain coverage area in each cleaning area, as well as the residual stain area in the primary area, secondary area, and tertiary area of ​​each cleaning area after cleaning, are obtained from the operating data of the water spray device in each cleaning area. Then, the operating status value of the water spray device is calculated; The operating status value of the water spray device includes values ​​of 1 and -1. When the operating status value of the water spray device is 1, it indicates that the water spray device is operating normally. When the operating status value of the water spray device is -1, it indicates that the water spray device is operating abnormally.

9. The method for cleaning a glass curtain wall of a building by using a drone according to claim 7, wherein: The operating status analysis process of the sewage recovery device is as follows: When the drone is cleaning each cleaning area, the camera on board the drone is used to collect operation videos of the sewage recovery device in each cleaning area. From the operation videos of the sewage recovery device in each cleaning area, the sewage area before suction, the sewage diffusion area, and the sewage residual area after suction are obtained, and the operation status value of the sewage recovery device is calculated; The operating status value of the sewage recovery device includes values ​​of 1 and -1. When the operating status value of the sewage recovery device is 1, it indicates that the sewage recovery device is operating normally. When the operating status value of the sewage recovery device is -1, it indicates that the sewage recovery device is operating abnormally.

10. A drone cleaning system using the drone cleaning method for building glass curtain walls according to any one of claims 1 to 9, characterized in that: include: The cleaning device selection module is used to model the glass curtain wall of the building and select the cleaning device solution corresponding to the drone; The cleaning control module is used to obtain the cleaning order of each cleaning area in the building's glass curtain wall. When the drone starts cleaning each cleaning area, it uses the three-dimensional model of each cleaning area to control the operation of the drone's cleaning brush, water spray device, and wastewater recovery device; The cleaning control adjustment module is used to monitor the operation of the cleaning brushes, water spray devices and sewage recovery devices in each cleaning area when the drone is cleaning each cleaning area, analyze the operating status of the cleaning brushes, water spray devices and sewage recovery devices, and then make corresponding adjustments.

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