A tower automatic cleaning method and system

Abstract

The present invention discloses an automatic tower cleaning method and system, comprising: collecting pollution information of a first object; performing regional positioning on the first object according to the pollution information to obtain a first pollution area; performing a first characteristic analysis on the first pollution area to obtain an evaluation result for each of the first pollution areas; and performing pollution treatment on each of the first characteristic areas according to the evaluation result. Through accurate pollution assessment and regional positioning, combined with dynamic adjustment of different cleaning difficulties, areas with different pollution levels can be treated in a targeted manner, thus avoiding waste of resources and improving cleaning efficiency. At the same time, the method can effectively protect equipment, extend service life, reduce manual intervention, and improve the degree of automation of cleaning, and has high innovation and application value.

Description

Technical Field

[0001] The present invention relates to the technical field of automatic cleaning, and in particular to an automatic tower cleaning method and system. Background Art

[0002] With the widespread application of renewable energy, the frequency of use of tower equipment such as wind power generation and solar power generation has greatly increased. As a high-altitude facility, the tower is prone to accumulate dust, pollutants and wind and sand, resulting in a layer of dirt covering the surface of the tower, which not only affects the appearance of the equipment, but also may reduce the power generation efficiency of the equipment. In wind power generation, the dirt on the surface of the tower will affect the air flow of the wind turbine, reduce the wind energy conversion efficiency, and cause the loss of the wind turbine. In solar power generation, the dirt on the tower will affect the light reception of the photovoltaic panel, resulting in a decrease in power generation. The traditional tower cleaning method mainly relies on manual operation, which is not only inefficient, but also poses a threat to the safety of the equipment. Therefore, the development of an efficient, automated and intelligent tower cleaning method is a technical problem that needs to be solved urgently. Summary of the invention

[0003] In view of the above-mentioned problems, the present invention is proposed.

[0004] Therefore, the technical problem solved by the present invention is that the existing methods have the problems of large power consumption, low efficiency, high cost, etc.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: a tower automatic cleaning method, comprising:

[0006] collecting pollution information of the first object;

[0007] According to the pollution information, performing regional positioning on the first object to obtain a first pollution area;

[0008] Performing a first characteristic analysis on the first polluted areas to obtain an evaluation result for each of the first polluted areas;

[0009] Contamination processing is performed on each of the first characteristic regions according to the evaluation result.

[0010] As a preferred solution of the tower automatic cleaning method described in the present invention, the pollution information includes information of the part to be cleaned collected by a multi-sensor device before cleaning the first object.

[0011] As a preferred solution of the tower automatic cleaning method described in the present invention, the area positioning includes gridding the first object to obtain pollution information of each area.

[0012] As a preferred solution of the tower automatic cleaning method described in the present invention, the first contaminated area includes, in the grid, an area marked with contamination.

[0013] As a preferred solution of the tower automatic cleaning method described in the present invention, the first feature analysis includes determining the difficulty of cleaning each area.

[0014] As a preferred solution of the tower automatic cleaning method described in the present invention, the pollution treatment includes performing cleaning treatments of different modes on different areas according to the cleaning difficulty of each area.

[0015] As a preferred solution of the tower automatic cleaning method of the present invention, the first feature analysis also includes dynamically adjusting the pollution assessment in combination with multi-dimensional data:

[0016]

[0017] Among them, S i A represents the pollution level score of the ith area; ij represents the area of ​​the jth pollutant in the ith region; L ik Adhesion force of the kth pollutant in the ith region (N); C i represents the difficulty coefficient of contamination cleaning in the i-th area; T i represents the time period of the ith region; P l represents the interaction factor of the lth region; D l represents the pollution distribution density of the lth area (α j ,β k ,γ are the weight coefficients of pollutant area, adhesion and cleaning difficulty respectively;δ j represents the dynamic impact coefficient of the jth pollutant on the area; k represents the attenuation factor of the kth pollutant in different time periods;

[0018] By dividing the pollution levels into different levels, setting the upper and lower thresholds for each level, and comparing the S i The level it is in, so as to obtain the pollution degree of each area;

[0019] During the execution phase, cleaning modes of different intensities are used for areas with different levels of contamination.

[0020] An automatic tower cleaning system using the method of the present invention is characterized by:

[0021] A collection module, collecting pollution information of the first object;

[0022] A positioning module, performing regional positioning on the first object according to the pollution information to obtain a first pollution area;

[0023] An analysis module, performing a first characteristic analysis on the first polluted areas to obtain an evaluation result for each of the first polluted areas;

[0024] A processing module performs pollution processing on each of the first characteristic regions according to the evaluation result.

[0025] A computer device comprises: a memory and a processor; the memory stores a computer program, wherein: the processor implements the steps of any one of the methods of the present invention when executing the computer program.

[0026] A computer-readable storage medium stores a computer program, wherein: when the computer program is executed by a processor, the steps of any one of the methods of the present invention are implemented.

[0027] Beneficial effects of the invention: The tower automatic cleaning method provided by the invention can treat areas with different pollution levels in a targeted manner through accurate pollution assessment and regional positioning, combined with dynamic adjustment of different cleaning difficulties, to avoid waste of resources and improve cleaning efficiency. At the same time, the method can effectively protect equipment, extend service life, reduce manual intervention, and improve the degree of automation of cleaning, and has high innovation and application value. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0029] Figure 1 An overall flow chart of an automatic tower cleaning method provided for the first embodiment of the present invention. DETAILED DESCRIPTION

[0030] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0031] Example 1, reference Figure 1 , as an embodiment of the present invention, provides a tower automatic cleaning method, comprising:

[0032] S1: Collect pollution information of a first object.

[0033] The contamination information includes information of a portion that needs to be cleaned, collected by a multi-sensor device before cleaning the first object.

[0034] In this embodiment, the first object is a tower, and the pollution information includes detecting and monitoring the tower surface through various sensing devices (such as sensors, cameras, laser radars, etc.), and collecting relevant data of the parts that need to be cleaned. These sensing devices can monitor the pollution of the tower surface in real time and obtain relevant physical quantity data, such as the dust accumulation on the tower surface, the distribution of stains, the degree of wind and sand erosion, the types of pollutants (such as dust, oil, bird droppings, etc.), and the degree of adhesion of pollutants.

[0035] S2: According to the pollution information, perform region positioning on the first object to obtain a first pollution region.

[0036] In this embodiment, regional positioning is achieved by gridding the tower surface. Specifically, the tower surface is divided into multiple small areas according to a predetermined rule (such as uniform division or division by pollution severity), and each small area is called a "grid unit". Each grid unit contains the pollution information of the area, including characteristic data such as the type, area, and adhesion of the pollutant.

[0037] According to the size and shape of the tower and the area that actually needs to be cleaned, the tower surface is divided into several regular grids (such as rectangular grids, hexagonal grids, etc.). The size of each grid can be set according to the accuracy of the sensor, the distribution characteristics of the pollutants, and the cleaning range of the cleaning equipment. In general, the size of the grid should be small enough to accurately capture the distribution of pollutants, but not too small to cause excessive computational complexity. For example, assuming that the tower surface is cylindrical, it can be divided into annular layers (along the height direction) and radial grids (along the radius direction). Each annular layer and each radial area forms a grid unit.

[0038] After the grid division is completed, the sensor scans each grid unit and collects pollution information in real time. This pollution information includes: the area of ​​pollutants in each grid, the adhesion of pollutants, the type of pollutants (such as dust, oil stains, bird droppings, etc.), the difficulty of cleaning pollutants, etc. Pollution information may also include environmental factors in the area, such as temperature, humidity, wind speed, etc., because these factors will also affect the accumulation of pollution and the difficulty of cleaning. The pollution information of each grid unit will be stored in the data processing system for further analysis. Each grid unit will be assigned a unique identifier to ensure effective tracking of pollution information in different areas. The pollution information will be transmitted to the central processing system via wireless network or wired communication. The system will determine which areas are more seriously polluted and need to be cleaned first based on the feedback data from the sensors.

[0039] The first contaminated area includes, in the grid, an area marked with contamination.

[0040] In an optional embodiment, the area positioning is for the grid division of the plane or uneven operating surface. For the plane surface (such as the horizontal platform of the tower, the bottom plane of the tower body, the maintenance platform, etc.), the grid division method is relatively direct. The plane operating surface is usually of regular geometric shape and relatively uniform surface, so the traditional regular grid division method can be used: the plane operating surface is evenly divided into multiple rectangular or square grid units according to fixed horizontal and vertical coordinate axes. The size of each grid unit can be set according to actual needs. Generally speaking, the smaller the size of the grid unit, the more accurate the cleaning effect, but the complexity of calculation and processing will also increase. The sensor in each grid unit will collect the pollution information of the area. The system analyzes each grid area based on this information to determine which areas need to be cleaned. The analysis results will be fed back to the cleaning equipment, instructing the cleaning equipment to give priority to areas with severe pollution.

[0041] For uneven tower surfaces or other similar irregular surfaces (such as cylindrical surfaces, curved surfaces, inclined surfaces, etc. of towers), the meshing process will be more complicated, and the geometric characteristics and actual shapes of the surfaces need to be considered. The following are the detailed steps for meshing uneven operating surfaces: First, obtain the three-dimensional point cloud data of the tower surface through technologies such as three-dimensional laser scanning or photogrammetry. By processing the point cloud data, a digital three-dimensional model of the tower surface (such as a mesh model, a surface model, etc.) can be established, which will provide a basis for subsequent meshing. After obtaining the three-dimensional model, the uneven surface can be divided using methods based on triangular meshes (such as Delaunay triangulation) or quadrilateral meshes (such as meshed surface technology). In this case, the mesh unit is no longer a fixed-shape rectangle or square, but a polygonal or triangular unit that is adaptively adjusted according to factors such as surface curvature and concave-convex shapes.

[0042] The meshing of uneven surfaces must not only consider the shape changes on the horizontal plane, but also the changes at different heights of the surface (such as the upper part, lower part, inclined part, etc. of the tower). Therefore, when meshing, it is also necessary to divide the meshes for different height layers according to the height changes of the surface. For example, the tower surface can be divided into multiple longitudinal ring layers, and each ring layer is further divided according to its local shape. For uneven surfaces, it may be necessary to adjust the density of the meshing according to the inclination and curvature of different areas. For areas with larger inclinations or larger changes in curvature, the meshing is more detailed to capture the pollution more accurately. Conversely, for flat areas, the density of the mesh can be appropriately reduced.

[0043] S3: Performing a first characteristic analysis on the first polluted areas to obtain an evaluation result for each of the first polluted areas.

[0044] The first feature analysis includes determining the difficulty of cleaning each area.

[0045] Incorporating multi-dimensional data to dynamically adjust pollution assessments:

[0046]

[0047] Among them, S i A represents the pollution level score of the ith area; ij represents the area of ​​the jth pollutant in the ith region; L ik Adhesion force of the kth pollutant in the ith region (N); C i represents the difficulty coefficient of contamination cleaning in the i-th area; T i represents the time period of the ith region; P l represents the interaction factor of the lth region; D l represents the pollution distribution density of the lth area (α j ,β k ,γ are the weight coefficients of pollutant area, adhesion and cleaning difficulty respectively;δ j represents the dynamic impact coefficient of the jth pollutant on the area; k Represents the attenuation factor of the kth pollutant in different time periods.

[0048] In this embodiment, the first characteristic analysis is only performed on the properties of pollutants on the plane. By comprehensively evaluating the pollution level score of each area, the cleaning mode and priority can be dynamically adjusted. For areas with higher pollution level scores, the cleaning equipment can select a stronger cleaning mode for cleaning to improve efficiency and ensure the cleaning effect. For areas with lower pollution levels, the equipment can select an appropriate cleaning method to save cleaning resources. In this way, the cleaning process can be more intelligent and refined, achieving the purpose of improving efficiency and reducing energy consumption.

[0049] In an optional embodiment, the first feature analysis may also consider the flatness of the cleaning surface of the first object. The flatness of the cleaning surface is crucial to the assessment of cleaning difficulty, because a flat surface is easier to clean, while an uneven surface may make it difficult to remove contaminants, or may even accumulate more contaminants due to the uneven surface. Therefore, the analysis of the flatness can be used as part of the cleaning difficulty assessment to help the system more accurately determine the cleaning difficulty of each area and adjust the cleaning strategy.

[0050] By dividing the pollution levels into different levels, setting the upper and lower thresholds for each level, and comparing the S i The level at which it is located can be used to obtain the degree of pollution in each area.

[0051] During the execution phase, cleaning modes of different intensities are used for areas with different levels of contamination.

[0052] S4: Performing pollution processing on each of the first characteristic regions according to the evaluation result.

[0053] Specifically, different cleaning modes are applied to different areas according to the cleaning difficulty of each area.

[0054] For areas with different cleaning difficulties, the system should select different cleaning modes. The specific cleaning mode can be dynamically adjusted according to the characteristics of the area (such as flatness, type of pollutants, cleaning difficulty, etc.). The main cleaning modes are as follows:

[0055] Lightly contaminated area cleaning mode:

[0056] For lightly contaminated areas, where there are fewer pollutants and weaker adhesion, conventional cleaning methods can be used. Common cleaning methods include:

[0057] Low-pressure spray cleaning: Low-pressure jet cleaning using water or cleaning fluid, suitable for areas with less contaminants and easy to remove;

[0058] Cleaning agent spraying: Use a specific cleaning agent to spray the contaminated area, which is suitable for dirt with weak adhesion.

[0059] Moderately polluted area cleaning mode:

[0060] For moderately polluted areas, the degree of pollution is more obvious and the adhesion of pollutants is moderate. At this time, more efficient cleaning methods are required, including:

[0061] High-pressure jet cleaning: Use a high-pressure water gun for jet cleaning to help wash away firmly attached contaminants;

[0062] Mechanical scrubbing combined with spray cleaning: Use a scrubbing tool to physically wipe the surface, combined with spray cleaning, especially suitable for areas with a certain degree of surface roughness.

[0063] Heavily polluted area cleaning mode:

[0064] For heavily polluted areas, the pollutants have strong adhesion and a large pollution range, making cleaning more difficult. In this case, more powerful and professional cleaning methods are required, including:

[0065] High-pressure water gun + strong cleaning agent: High-pressure water gun can remove the outer layer of pollutants, and strong cleaning agent can destroy pollutants with strong adhesion;

[0066] Ultrasonic cleaning: In some areas where it is difficult to remove pollutants, ultrasonic cleaning equipment can be used to remove pollutants by using the bubbles generated by high-frequency vibrations;

[0067] Mechanical brush cleaning: For areas where contaminants are very firmly attached, special rotating brushes can be used for physical cleaning, combined with high-pressure water flow to remove stubborn contaminants.

[0068] Embodiment 2 is an embodiment of the present invention. This embodiment also provides an automatic tower cleaning system, which includes:

[0069] The collection module collects pollution information of the first object.

[0070] A positioning module performs regional positioning on the first object according to the pollution information to obtain a first pollution area.

[0071] The analysis module performs a first characteristic analysis on the first polluted areas to obtain an evaluation result for each of the first polluted areas.

[0072] A processing module performs pollution processing on each of the first characteristic regions according to the evaluation result.

[0073] If the above functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0074] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0075] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0076] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0077] Example 3 is an embodiment of the present invention, which provides an automatic tower cleaning method. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments.

[0078] The test object was an actual wind turbine tower, and the pollutants were mainly dust, bird droppings and contaminated oil stains.

[0079] Test environment and equipment

[0080] The test was conducted on the tower surface of a wind farm. The following equipment and sensors were used:

[0081] High-precision sensors: used to collect pollution information, including pollution area, pollutant type, adhesion, etc.

[0082] Intelligent grid positioning system: divide the tower surface into grids and identify contaminated areas.

[0083] Multi-dimensional data analysis platform: Analyzes the collected data, including pollutant adhesion, area, cleaning difficulty, etc., and outputs pollution assessment results.

[0084] Cleaning equipment: including low-pressure spray system, high-pressure water gun, ultrasonic cleaning system, mechanical brushing equipment, etc.

[0085] Implementation process

[0086] Pollution information collection: Use high-precision sensors to collect pollution data at different heights and in different areas on the tower surface. The data includes the adhesion of pollutants (unit: N), the area of ​​pollutants (unit: m 2 ), pollution type, pollution cleaning difficulty coefficient, etc.

[0087] Regional positioning: The tower surface is divided into 10 grid areas through the intelligent grid positioning system. The pollution data of each area is collected through sensors to establish a corresponding pollution information database.

[0088] First feature analysis: Combined with the multi-dimensional data analysis platform, the cleaning difficulty of each area is analyzed. Factors considered include the adhesion of pollutants, the area of ​​contamination, the difficulty of cleaning, the flatness of the cleaning surface, etc.

[0089] Pollution treatment assessment: Based on the assessment results, determine the cleaning difficulty level (mild, medium, severe) for each area, and select the appropriate cleaning mode according to the different levels, such as low-pressure spray, high-pressure water gun, mechanical brushing, etc.

[0090] Cleaning mode execution: According to the evaluation results of each area, the cleaning mode is selected and executed. Low-pressure spray is used for lightly polluted areas, and high-pressure water gun combined with ultrasonic cleaning is used for highly polluted areas.

[0091] Table 1 Data record table

[0092]

[0093]

[0094] Through the analysis of the above data tables, we can draw the following conclusions:

[0095] According to experimental data, high-pressure water guns or ultrasonic cleaning are usually selected for areas with large contamination areas and strong adhesion (such as areas 5 and 6). These areas have a higher cleaning difficulty coefficient (above 3.0) and require stronger cleaning methods.

[0096] Areas with smaller contamination areas and weaker adhesion (such as area 1 and area 2) are suitable for low-pressure spray cleaning, which has a shorter cleaning time and better effect, and the cleaning effect can reach more than 90%.

[0097] The data shows that the cleaning effect of high-pressure water gun combined with ultrasonic cleaning in heavily polluted areas (areas 4 and 5) is more than 95%, even close to 100%. This shows that for areas with high pollution levels, the use of a composite cleaning mode (such as the combination of high-pressure water gun and ultrasonic) can significantly improve the cleaning effect.

[0098] On the contrary, when low-pressure spray is used in lightly polluted areas, the cleaning effect is stable between 85% and 92%, and the cleaning time is short, indicating that the low-pressure spray cleaning method is effective for lightly polluted areas and can save time and resources.

[0099] Compared with the prior art, the advantage of the present invention is that it intelligently selects the appropriate cleaning mode according to the degree of contamination, adhesion and cleaning difficulty coefficient of each area. In this way, it is possible to save energy, reduce cleaning time and perform refined cleaning on different types of contamination while ensuring the cleaning effect. For example, the combination of high-pressure water gun and ultrasonic cleaning can efficiently clean stubborn contaminants (such as area 5) with less damage to the surface of the tower.

[0100] At present, tower cleaning methods on the market usually use a single mode (such as high-pressure water guns or mechanical brushing), which cannot be dynamically adjusted for different polluted areas, which easily leads to energy waste and poor cleaning effect. The method of the present invention can perform personalized cleaning for each polluted area, thereby significantly improving the cleaning efficiency and effect.

[0101] From the data, we can see that the areas using targeted cleaning modes have a good balance between cleaning time and effect. For example, although the cleaning time of area 5 is longer (30 minutes), the cleaning effect reaches 98%, showing efficient cleaning performance, while the traditional cleaning method may lead to ineffective cleaning for a longer time due to the inappropriate cleaning mode.

[0102] This embodiment demonstrates the effectiveness of the tower automatic cleaning method, and verifies the innovation and advantages of the method in terms of cleaning mode selection, cleaning time optimization and cleaning effect improvement through experimental data. By dynamically selecting the appropriate cleaning mode based on the analysis of factors such as the degree of contamination, adhesion, and type of pollutants, not only the cleaning efficiency is improved, but also the energy consumption and cleaning cost can be effectively reduced. Compared with the prior art, the present invention has obvious advantages in many aspects, especially in terms of cleaning effect optimization and time management, reflecting the great potential of the intelligent cleaning system.

[0103] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A tower automatic cleaning method, characterized in that: include: collecting pollution information of the first object; According to the pollution information, performing regional positioning on the first object to obtain a first pollution area; Performing a first characteristic analysis on the first polluted areas to obtain an evaluation result for each of the first polluted areas; Contamination processing is performed on each of the first characteristic regions according to the evaluation result.

2. The automatic tower cleaning method according to claim 1, characterized in that: The contamination information includes information of a portion that needs to be cleaned, collected by a multi-sensor device before cleaning the first object.

3. The automatic tower cleaning method according to claim 2, characterized in that: The area positioning includes gridding the first object to obtain pollution information of each area.

4. The automatic tower cleaning method according to claim 3, characterized in that: The first contaminated area includes, in the grid, an area marked with contamination.

5. The automatic tower cleaning method according to claim 4, characterized in that: The first feature analysis includes determining the difficulty of cleaning each area.

6. The automatic tower cleaning method according to claim 5, characterized in that: The pollution treatment includes performing cleaning treatments of different modes on different areas according to the cleaning difficulty of each area.

7. The automatic tower cleaning method according to claim 5, characterized in that: The first feature analysis also includes dynamically adjusting the pollution assessment by combining multi-dimensional data: Among them, S i A represents the pollution level score of the ith area; ij represents the area of ​​the jth pollutant in the ith region; L ik Adhesion force of the kth pollutant in the ith region (N); C i represents the difficulty coefficient of contamination cleaning in the i-th area; T i represents the time period of the ith region; P l represents the interaction factor of the lth region; D l represents the pollution distribution density of the lth area (α j , β k , γ are the weight coefficients of pollutant area, adhesion and cleaning difficulty respectively; δ j represents the dynamic impact coefficient of the jth pollutant on the area; k represents the attenuation factor of the kth pollutant in different time periods; By dividing the pollution levels into different levels, setting the upper and lower thresholds for each level, and comparing the S i The level it is in, so as to obtain the pollution degree of each area; During the execution phase, cleaning modes of different intensities are used for areas with different levels of contamination.

8. An automatic tower cleaning system using the method according to any one of claims 1 to 7, characterized in that: A collection module, collecting pollution information of the first object; A positioning module, performing regional positioning on the first object according to the pollution information to obtain a first pollution area; An analysis module performs a first characteristic analysis on the first polluted areas to obtain an evaluation result for each of the first polluted areas; A processing module performs pollution processing on each of the first characteristic regions according to the evaluation result.

9. A computer device comprising: A memory and a processor; the memory stores a computer program, wherein the processor implements the steps of any method as claimed in claim 1 when executing the computer program.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

Images