Method for resource adaptive cleaning control of a cleaning base station, cleaning base station and cleaning system

Abstract

The application provides a resource self-adaptive cleaning control method for a cleaning base station, a cleaning base station and a cleaning system, and relates to the technical field of cleaning base station control. The method comprises the following steps: obtaining a dirt parameter of a component to be cleaned; monitoring the remaining cleaning resources of the cleaning base station; determining a continuous cleaning mode according to the dirt parameter and the remaining cleaning resources; and controlling the cleaning base station to clean the component to be cleaned in the continuous cleaning mode. According to the application, the risk of cleaning task interruption can be reduced in the case of insufficient remaining cleaning resources, the continuity of the cleaning task is ensured, and the success rate of the overall cleaning task is improved.

Description

Technical Field

[0001] This invention relates to the field of clean base station control technology, and in particular to a resource adaptive cleaning control method for a clean base station, a clean base station, and a cleaning system. Background Technology

[0002] With the increasing popularity of cleaning robots, cleaning base stations, as supporting equipment, can automatically clean the cleaning components on the cleaning equipment. However, the continuous consumption of cleaning resources such as clean water and cleaning agents during the cleaning process often leads to a shortage of remaining cleaning resources for the cleaning base stations.

[0003] When remaining cleaning resources are insufficient, cleaning base stations typically take one of the following approaches: 1. Directly interrupt the cleaning task; 2. Switch to save mode in advance when resources are about to run out.

[0004] However, the first approach can prevent the overall cleaning task from being completed. A common implementation of the second approach is to reduce resource consumption individually based on the type of resource lacking, such as switching to water-saving mode when water is scarce and liquid-saving mode when detergent is scarce. This fixed degradation method based on a single, fixed threshold can lead to the unreasonable activation of the saving mode. For example, when a cleaning component is stained with dirt requiring detergent removal, the minimal detergent provided by the liquid-saving mode may not be sufficient to effectively emulsify the dirt, thus affecting the subsequent cleaning effect. Furthermore, in cleaning scenarios with multiple cleaning components, the first cleaning component may consume most of the cleaning resources, resulting in a severe shortage of resources for subsequent cleaning tasks, thereby interrupting the cleaning process.

[0005] Therefore, with insufficient remaining cleaning resources, the current cleaning base stations cannot guarantee the continuity of cleaning tasks, nor can they guarantee the cleaning effect of cleaning components, and may even further reduce the subsequent cleaning effect of cleaning equipment. Summary of the Invention

[0006] To address the shortcomings of existing technologies, this invention provides a resource adaptive cleaning control method for cleaning base stations, a cleaning base station, and a cleaning system. It solves the problem that existing cleaning base stations are prone to interrupting cleaning tasks and making it difficult to guarantee cleaning results when there are insufficient remaining cleaning resources.

[0007] According to an embodiment of the present invention, a first aspect provides a resource adaptive cleaning control method for a clean base station, comprising: Obtain the dirt parameters of the component to be cleaned; Monitor the remaining cleaning resources at the clean base station; Based on the dirt parameters and the remaining cleaning resources, a continuous cleaning mode is determined; The cleaning base station is controlled to clean the components to be cleaned in the continuous cleaning mode.

[0008] The second aspect provides a clean base station, including: Base station main body; The resource monitoring module is used to monitor the remaining cleaning resources; A dirt detection device is used to obtain dirt parameters of the cleaning components; The controller is used to execute the resource adaptive cleaning control method for the clean base station described above.

[0009] The third aspect provides a cleaning system, including the aforementioned cleaning base station and at least one cleaning device; The cleaning equipment is equipped with at least one cleaning component. When the cleaning equipment is used in conjunction with the cleaning base station, the cleaning component serves as the component to be cleaned for the cleaning base station.

[0010] A fourth aspect provides a computer-readable storage medium storing instructions that, when executed by a processor, configure the processor to perform the resource adaptive cleaning control method for the clean base station described above.

[0011] Compared to existing technologies, this invention offers the following advantages: By determining the continuous cleaning mode based on the dirt parameters of the components to be cleaned and the remaining cleaning resources of the cleaning base station, the risk of cleaning task interruption can be reduced when remaining cleaning resources are insufficient, ensuring the continuity of the cleaning task and thus improving the overall success rate of the cleaning task. Furthermore, by using the dirt parameters of the components to be cleaned as the basis for determining the continuous cleaning mode, the utilization rate of remaining cleaning resources is maximized for the differentiated cleaning needs of each component, ensuring that each component receives appropriate cleaning treatment. This solves the problem in fixed degradation modes where excessive degradation of individual components leads to overall cleaning failure, or insufficient degradation of individual components causes premature resource depletion, thus interrupting the cleaning task. Attached Figure Description

[0012] Figure 1 This is a schematic diagram of the composition and structure of the cleaning system according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the composition structure of a clean base station according to an embodiment of the present invention; Figure 3 This is a schematic diagram illustrating the implementation process of the resource adaptive cleaning control method for a clean base station according to an embodiment of the present invention; Figure 4 for Figure 3 A detailed implementation flowchart of step S103 is shown below; Figure 5 for Figure 4 A detailed implementation flowchart of step S1032 is shown below. Detailed Implementation

[0013] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0014] The terms "first," "second," "third," "fourth," etc., used in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be used interchangeably where appropriate. For example, without departing from the scope of this document, first information can also be referred to as second information, and similarly, second information can also be referred to as first information.

[0015] Depending on the context, the word "if" as used here can be interpreted as "when," "when," or "in response to determination."

[0016] Furthermore, as used herein, the singular forms “a,” “one,” and “the” are intended to also include the plural forms, unless the context indicates otherwise.

[0017] It should be further understood that the terms “comprising” or “including” indicate the presence of features, steps, operations, elements, components, items, kinds, and / or groups, but do not exclude the presence, occurrence, or addition of one or more other features, steps, operations, elements, components, items, kinds, and / or groups.

[0018] The terms “or” and “and / or” as used herein are interpreted as inclusive, or mean any one or any combination thereof. Therefore, “A, B, or C” or “A, B, and / or C” means “any one of the following: A, B, C, A and B, A and C, B and C, A, B, and C”. Exceptions to this definition occur only when combinations of elements, functions, steps, or operations are inherently mutually exclusive in some way.

[0019] Currently, for cleaning equipment used in conjunction with cleaning base stations, the continuity of cleaning tasks within the cleaning base station is a crucial prerequisite for the successful completion of cleaning tasks within the cleaning equipment. However, cleaning base stations typically interrupt cleaning tasks when remaining cleaning resources are insufficient, leading to the failure of the overall cleaning task. Even though some cleaning base stations can switch to a resource-saving mode in advance when remaining cleaning resources are insufficient, the fixed degradation method based on a single fixed threshold still cannot solve the problem of easy interruption of cleaning tasks and difficulty in guaranteeing cleaning effectiveness. To address the above technical problems, this invention proposes a resource-adaptive cleaning control method for cleaning base stations, a cleaning base station, and a cleaning system.

[0020] The cleaning system provided in the embodiments of the present invention will be described in detail below.

[0021] Figure 1 This is a schematic diagram of the composition structure of the cleaning system provided in an embodiment of the present invention, such as... Figure 1 As shown, the cleaning system of this embodiment includes a cleaning base station 11 and at least one cleaning device 12.

[0022] In the cleaning system of this embodiment, the cleaning device 12 can be an automated cleaning terminal such as a floor scrubber, mop, or sweeping robot, and is not limited here.

[0023] Alternatively, the cleaning equipment described above can be equipped with a single cleaning component to achieve simple cleaning.

[0024] Optionally, the cleaning equipment is equipped with multiple cleaning components, or the cleaning equipment supports automatic replacement of cleaning components, with the cleaning base station equipped with multiple cleaning components to accommodate various cleaning needs.

[0025] Optionally, the aforementioned cleaning equipment can also be used in a multi-machine collaborative operation mode, that is, multiple cleaning devices can be used in conjunction with a cleaning base station to accommodate a wider range of more complex cleaning needs.

[0026] Therefore, when the cleaning device 12 of the present invention is used in conjunction with the cleaning base station 11, the cleaning component of the cleaning device is the component to be cleaned of the cleaning base station. On the cleaning base station side, the number of components to be cleaned may be 1, such as the current cleaning task only requires cleaning one component to be cleaned; the number of components to be cleaned may also be much greater than 1, such as the current cleaning task requires cleaning multiple components to be cleaned. In this case, the cleaning base station cleans multiple components to be cleaned at the same time or cleans each component to be cleaned in sequence.

[0027] In the cleaning system of this embodiment, the cleaning base station 11 employs a resource adaptive cleaning control method to address the issue of insufficient remaining cleaning resources, which is highly likely to occur during the cleaning process of a single or multiple components to be cleaned. According to this method, the cleaning system of this embodiment can rationally plan remaining cleaning resources and formulate a working mode that allows the cleaning base station to continue cleaning even when remaining cleaning resources are insufficient. This reduces the probability of cleaning task interruption, thereby ensuring the continuity of the cleaning task and ultimately improving the overall success rate of the cleaning task.

[0028] The clean base station provided in the embodiments of the present invention will be described in detail below.

[0029] Figure 2 This is a schematic diagram of the composition structure of a clean base station provided in an embodiment of the present invention. The embodiment of the present invention uses this clean base station for... Figure 1 The cleaning system shown is used as an example for illustration. Figure 2 As shown, the clean base station of this embodiment of the invention includes a base station body 21, a resource monitoring module 221, a dirt detection device 222, and a controller 22.

[0030] In this embodiment of the clean base station, the detailed structure of the base station body 21 is not limited here, but is designed to accommodate various actual cleaning resources, such as cleaning water, cleaning agents, disinfectants, and other cleaning and maintenance aids. The resource monitoring module 221 and the dirt detection device 222 can be logical functional units inside the controller 22, implemented in the form of software modules, firmware algorithms, or hardware logic circuits, and are not limited here. The controller is located in the base station body.

[0031] In this embodiment of the invention, the cleaning base station, in terms of internal resource monitoring, is equipped with physical sensors such as liquid level sensors and flow sensors within the base station body 21 to monitor the consumption or remaining status of the actual cleaning resources in real time, outputting the first part of the raw monitoring signal. For cleaning resources that the cleaning base station has unlimited ownership but limited access to, such as power consumption and cleaning time, the base station body 21 monitors them through power detection circuits and timing circuits, outputting the second part of the raw monitoring signal. The aforementioned physical sensors, power detection circuits, and timing circuits are connected to the controller 22 (mainly its internal resource monitoring module 221). Since the two parts of the raw monitoring signal may be in different forms such as analog signals, pulse signals, or bus data, the controller's interface circuit first digitally conditions these two parts of the raw monitoring signal, and then the resource monitoring module 221 logically integrates the two parts of the digitized data to obtain complete, unified digital format data of the remaining cleaning resources.

[0032] In this embodiment of the invention, the cleaning base station acquires the dirt parameters of the components to be cleaned through a dirt detection device 222 in the dimension of external object perception. The dirt detection device 222 may include hardware such as image sensors and photoelectric sensors, and runs corresponding dirt recognition and photoelectric analysis algorithms to obtain the dirt parameters of the components to be cleaned. For any component to be cleaned, its dirt parameters can be a multi-dimensional data set, including but not limited to data such as oil stain value, dust value, stain area, and water stain value.

[0033] The cleaning base station of this invention also includes a hardware actuator 23 for cleaning, including but not limited to functional components such as a cleaning roller brush, spray assembly, squeegee, lifting drive assembly, and rotation drive assembly. The selection, quantity, and arrangement of the specific components can be flexibly adapted according to the overall specifications of the cleaning system, the cleaning scenario, and the cleaning requirements, and are not limited here. The controller sends control signals to the aforementioned hardware actuators to coordinate and cooperate to complete different preset cleaning modes.

[0034] Based on this, the controller 22 obtains the complete remaining cleaning resource data integrated by the resource monitoring module 221 and the dirt parameters obtained by the dirt detection device 222, and determines the continuous cleaning mode based on the remaining cleaning resource data and dirt parameters, thereby controlling the cleaning base station to clean the components to be cleaned in the continuous cleaning mode.

[0035] Therefore, the cleaning base station of this invention, when cleaning one or more components to be cleaned, can maximize the utilization rate of the remaining cleaning resources by combining the dirt parameters and the continuous cleaning mode of the remaining cleaning resources, so that each component to be cleaned can receive reasonable cleaning treatment. This solves the problem that under the fixed degradation mode, excessive degradation of individual components to be cleaned leads to overall cleaning failure, or insufficient degradation of individual components to be cleaned causes resources to be exhausted prematurely, thereby interrupting the cleaning task.

[0036] The resource adaptive cleaning control method for clean base stations provided in the embodiments of the present invention will be described in detail below.

[0037] Figure 3 This is a flowchart of a resource adaptive cleaning control method for a clean base station according to an embodiment of the present invention. The present invention uses this method for... Figure 2 Taking the controller of the cleaning base station shown as an example, and illustrating with a single cleaning task of the cleaning base station. Figure 3 As shown, the resource adaptive cleaning control method for cleaning base stations according to embodiments of the present invention includes, but is not limited to, the following steps: S101. Obtain the dirt parameters of the component to be cleaned; S102. Monitor the remaining cleaning resources of the clean base station; S103. Determine the continuous cleaning mode based on the dirt parameters and the remaining cleaning resources; S104. Control the cleaning base station to clean the components to be cleaned in the continuous cleaning mode.

[0038] The component to be cleaned in step S101 above refers to one or more cleaning devices that the cleaning base station needs to clean in the current cleaning task. The dirt parameters of the component to be cleaned can be obtained from, for example... Figure 2 The dirt and grime values ​​obtained from the dirt and grime detection device shown include, but are not limited to, oil stain values, dust values, stain area, and water stain values.

[0039] The monitoring results shown in step S102 above can be obtained from, for example... Figure 2 The resource monitoring module shown reads data including, but not limited to, remaining cleaning water, remaining cleaning agent, remaining power, and remaining cleaning time.

[0040] It should be noted that remaining cleaning water and cleaning agent are the actual cleaning resources of the cleaning base station and can be replenished. Remaining power and remaining cleaning time are the operating cleaning resources of the cleaning base station and cannot be replenished. Taking remaining power as an example, it represents the logical power required by the cleaning base station to determine whether its remaining power can support the current cleaning mode. In practice, if the logical power required for the current cleaning mode exceeds the remaining power, the cleaning base station will typically report an error or degrade its operation. Similarly, taking cleaning time as an example, it represents the available working time required by the cleaning base station to determine whether it can support the expected execution time of the current cleaning mode. This working time is limited by user settings or the safe operating time limit of the device hardware. In practice, if the expected execution time required for the current cleaning mode exceeds the remaining cleaning time, the cleaning base station will typically report an error or degrade its operation.

[0041] The above step S103 determines the continuous cleaning mode based on the dirt parameters and remaining cleaning resources. The basic principle is: based on the supply and demand relationship between the dirt parameters and remaining cleaning resources, it determines whether the remaining cleaning resources are sufficient, and then, based on this supply and demand relationship, adaptively and dynamically adjusts the cleaning mode. Specifically, regardless of whether the remaining cleaning resources are sufficient, the cleaning base station uses the remaining cleaning resources as a boundary constraint to dynamically match the working mode that prioritizes continuous cleaning, i.e., the aforementioned continuous cleaning mode. Furthermore, the decision-making process based on this supply and demand relationship also allows the final continuous cleaning mode to take into account the differentiated cleaning needs of multiple components to be cleaned.

[0042] The above step S104 may be to control the hardware actuator of the cleaning base station to clean the components to be cleaned in the continuous cleaning mode, and according to step S103, in this mode the cleaning base station will control the resource consumption of each component to be cleaned.

[0043] Through steps S101 to S104 described above, this embodiment of the invention can dynamically match the working mode that prioritizes continuous cleaning when there are insufficient remaining cleaning resources, reducing the risk of cleaning task interruption, ensuring the continuity of cleaning tasks, and thus improving the overall success rate of cleaning tasks. Furthermore, by using the dirt parameters of the components to be cleaned as the basis for determining the continuous cleaning mode, the utilization rate of remaining cleaning resources is maximized for the differentiated cleaning needs of each component, ensuring that each component receives appropriate cleaning treatment. This solves the problem in a fixed degradation mode where excessive degradation of individual components leads to overall cleaning failure, or insufficient degradation of individual components causes premature resource depletion, thus interrupting the cleaning task.

[0044] As the cleaning process progresses, or if non-steady-state losses occur in cleaning resources even when a continuous cleaning mode has been established, the remaining cleaning resources will deviate from expectations, rendering the pre-determined continuous cleaning mode inapplicable. Therefore, even within a single cleaning task, there is a need for dynamic adjustment. Based on this, this embodiment of the invention introduces closed-loop monitoring of the real-time remaining cleaning resources and dynamic correction of the cleaning mode after step S104, including: Continuously monitor the real-time remaining cleaning resources of the clean base stations; Based on the dirt parameters and the real-time remaining cleaning resources, determine whether the continuous cleaning mode has changed; If a change occurs, the cleaning base station is controlled to clean the component to be cleaned in a standby cleaning mode determined based on the dirt parameters and the real-time remaining cleaning resources.

[0045] The continuous cleaning mode of this invention is applicable to both situations where there are sufficient remaining cleaning resources and situations where there are insufficient remaining cleaning resources. Therefore, the continuous cleaning mode includes at least two cleaning schemes. For example... Figure 4 As shown, in one embodiment, step S103 above determines a continuous cleaning mode based on the dirt parameters and the remaining cleaning resources, including: S1031. When the remaining cleaning resources are sufficient, the continuous cleaning mode is determined to be the standard cleaning mode. S1032. When the remaining cleaning resources are insufficient, the continuous cleaning mode is determined to be a save-cleaning mode. Based on the supply and demand relationship shown in the above embodiments, if there are sufficient remaining cleaning resources, the standard cleaning mode determined in step S1031 can achieve the expected cleaning effect. If there are insufficient remaining cleaning resources, it indicates that the total resource consumption needs to be limited. In this case, the energy-saving cleaning mode determined in step S1032 should be used to prioritize ensuring the continuity of the cleaning task.

[0046] In this embodiment of the invention, the conversion relationship from the standard cleaning mode to the energy-saving cleaning mode is as follows: the energy-saving cleaning mode is obtained by downgrading the standard cleaning mode within a preset range. Here, the switching relationship indicates that the necessary resources for the component to be cleaned in the standard cleaning mode are exactly the same as the necessary resources for the component to be cleaned in the energy-saving cleaning mode. Furthermore, the downgrading adjustment indicates that the total resource consumption of the energy-saving cleaning mode will be less than the total resource consumption of the standard cleaning mode.

[0047] In this embodiment of the invention, the remaining cleaning resources include at least one of remaining cleaning water, remaining cleaning agent, remaining electricity, and remaining cleaning time. Therefore, to ensure that the total resource consumption of the energy-saving cleaning mode is less than that of the standard cleaning mode, the downgrade adjustment may include at least one of reducing the consumption of cleaning water, reducing the consumption of cleaning agent, reducing the consumption of electricity, and reducing the cleaning time. Specifically, reducing electricity consumption can be achieved by reducing the power of the heating element to lower the cleaning water temperature, or by reducing the speed of the drive motor to reduce the intensity of mechanical scrubbing; reducing cleaning water consumption can be achieved by reducing the flow rate of the water pump or closing the water supply valve.

[0048] Considering that blindly adjusting the total resource consumption of the low-cost cleaning mode may easily lead to ineffective or excessive degradation, this embodiment of the invention also determines the necessary resources and their consumption of the component to be cleaned in the standard cleaning mode through dirt parameters, so as to obtain the preset range based on the necessary resources and their consumption.

[0049] It should be noted that since steps S101 to S104 correspond to a single cleaning task of the clean base station, the dirt parameters of the components to be cleaned are usually not exactly the same in any two cleaning tasks. This means that when the embodiment of the present invention downgrades the standard cleaning mode to obtain a save-cleaning mode, the necessary resources and their consumption under the standard cleaning mode determined by the dirt parameters are not static, fixed values, but rather a dynamic benchmark that changes in real time with the cleaning task, or the components to be cleaned. Based on this dynamic benchmark, a preset range for downgrade adjustment is determined, enabling the downgrade adjustment of the embodiment of the present invention to have adaptive dynamic adjustment capabilities. This effectively solves the problems of ineffective or excessive downgrades that exist when using a fixed downgrade method with a single fixed threshold.

[0050] Two examples are given here to illustrate the problems of ineffective or excessive downgrades in the above fixed downgrade method.

[0051] Taking the component to be cleaned - cloth 1, and the dirt parameter of cloth 1 - oil stain value of 60% as an example, the necessary resources and their consumption of cloth 1 in the standard cleaning mode are shown in Table 1.1 below: Table 1.1 - Required resources and consumption of cleaning cloth 1 under standard cleaning mode

[0052] Taking the component to be cleaned - cloth 2, and the dirt parameter of cloth 2 - a comprehensive dirt value of 85% as an example, the necessary resources and their consumption for cloth 2 in the standard cleaning mode are shown in Table 2.1 below: Table 2.1 - Required resources and consumption of cleaning cloth 2 under standard cleaning mode

[0053] It should be noted that, to facilitate the quantification of resource consumption and degradation levels in examples, this embodiment of the invention first provides a unified quantification method for each remaining cleaning resource to establish the proportional relationship between each cleaning resource and the baseline state. This facilitates the rapid calculation of the corresponding standard consumption based on the dirt parameters of the component to be cleaned. This includes: normalizing each remaining cleaning resource into a coefficient representation; where a coefficient of 1 indicates the baseline consumption of each remaining cleaning resource for a baseline cleaning component with a baseline dirt parameter. For example, the baseline dirt parameter can be 50%, and the baseline consumption of the cleaning agent is 1 part. Then, when the dirt parameter of the component to be cleaned is 60%, the standard consumption of the cleaning agent is 1.1. Furthermore, the standard power consumption under the standard cleaning mode is characterized by the theoretical maximum heating temperature rise of the object being cleaned. As shown in Table 1.1 above, a water temperature of 55°C means that when the standard power consumption is applied to the cleaning water, the theoretical maximum temperature rise of the cleaning water is 55°C.

[0054] According to Tables 1.1 and 2.1, the necessary resources and their consumption under the standard cleaning mode, determined by the dirt parameters, are dynamic benchmarks that change in real time depending on the cleaning task, or rather, the components to be cleaned. Furthermore, if a fixed degradation method is adopted, such as switching to a water-saving mode that adjusts the cleaning water to 50% when the remaining cleaning water is insufficient, for cloth 2, the cleaning water will decrease from 1.5L to 0.75L, which may not be enough to clean it properly, resulting in excessive degradation.

[0055] The degradation adjustment shown in step S1032 above obtains a preset range for degradation adjustment by determining the necessary resources and their consumption under the standard cleaning mode based on the dirt parameters. Adjustments are then made within this preset range to ensure the degradation adjustment result remains within the preset range. This solves the problems of ineffective or excessive degradation inherent in the aforementioned fixed degradation method. This embodiment of the invention provides a detailed explanation of this degradation adjustment through a detailed implementation.

[0056] First, the triggering of the downgrade adjustment in this embodiment of the invention is not only based on the judgment result of whether the remaining cleaning resources are sufficient. When the remaining cleaning resources are insufficient, the missing resources are compared with the necessary resources obtained according to the dirt parameters to confirm whether it is necessary to make a downgrade adjustment. After confirming that a downgrade adjustment is needed, the downgrade adjustment is then made within a preset range, thereby avoiding the unreasonable activation of the saving mode.

[0057] like Figure 5 As shown, in one embodiment, when the remaining cleaning resources shown in step S1032 are insufficient, the step of downgrading the standard cleaning mode within a preset range to obtain the energy-saving cleaning mode includes: S10321. Obtain one or more missing resources when the remaining cleaning resources are insufficient; S10322. For a target missing resource that is of the same type as any of the required resources, obtain the standard consumption of the target missing resource in the standard cleaning mode and the initial remaining total amount of the target missing resource. S10323. Calculate the deviation range based on the standard consumption of the target missing resource in the standard cleaning mode, calculate the safety range based on the initial remaining total amount of the target missing resource, and determine the preset range by combining the deviation range and the safety range. S10324. Based on the standard consumption of the target missing resource in the standard cleaning mode, a downgrade adjustment is performed to obtain the downgrade adjustment result within the preset range; S10325. Adjust the standard cleaning mode according to the downgrade adjustment result to obtain the cost-saving cleaning mode.

[0058] Regarding step S10321 above, as shown in Table 1.1, the components to be cleaned typically require more than one type of resource in the standard cleaning mode. Therefore, this embodiment of the invention also compares the types of missing resources with the types of required resources one by one, in order to determine whether the various missing resources affect the implementation of the standard cleaning mode based on the comparison results, and thus confirm whether it is necessary to perform a downgrade adjustment when the remaining cleaning resources are insufficient.

[0059] The comparison result can be the target missing resource shown in step S10322 above. The target missing resource is the missing resource that affects the implementation of the standard cleaning mode. Furthermore, step S10322 can directly obtain the standard consumption of the target missing resource in the standard cleaning mode based on the required resources of the same type as the target missing resource. The initial remaining total amount of the target missing resource is obtained from the monitoring results of the remaining cleaning resources shown in step S102 above.

[0060] In one embodiment, the comparison result may also be that there is no target missing resource that matches any of the required resources in terms of type. That is, all missing resources obtained in step S10321 above do not affect the implementation of the standard cleaning mode. In this case, no downgrade adjustment is performed to avoid unreasonable activation of the save cleaning mode. For example, if the missing resource is disinfectant not shown in Table 1.1 above, it is unnecessary to downgrade the standard cleaning mode of the cloth 1. In this case, the continuous cleaning mode of the cloth 1 is still the standard cleaning mode.

[0061] Step S10322 above identifies the object of the downgrade adjustment. Based on this, step S10323 above shows the preset range of the downgrade adjustment. The preset range is the adjustment range to be followed by the downgrade adjustment, which is jointly determined by the deviation range and the safety range. The deviation range is the lower limit range for adjustment based on the standard consumption, ensuring that the component to be cleaned can complete basic cleaning functions. The safety range is usually less than or equal to the initial remaining total amount of the target missing resource. Preferably, the intersection of the deviation range and the safety range is taken as the preset range.

[0062] The downgrade adjustment result of step S10324 is limited by steps S10322 and S10323, and is the amount of consumption saved by the target missing resource in the saving and cleaning mode. The downgrade adjustment result is within a preset range, and preferably, the preset range is: the amount of consumption saved is less than or equal to the initial remaining total amount, and is within the deviation range.

[0063] Through the above steps S10321 to 10325, this embodiment of the invention adjusts the standard cleaning mode to a saving cleaning mode within a preset range, which can minimize the consumption of target missing resources, ensure the continuity of the cleaning task, and ensure that the components to be cleaned obtain basic cleaning results. This effectively solves the problem of ineffective cleaning caused by excessively reducing the consumption of target missing resources.

[0064] Corresponding to the example shown in Table 1.1, the implementation process of steps S10321 to S10325 is as follows: Assume that when the remaining cleaning resources are insufficient, there are two missing resources: cleaning agent and disinfectant. The cleaning agent and disinfectant are compared and analyzed with the required resources shown in Table 1.1. The cleaning agent is determined to be the target missing resource affecting the standard cleaning mode, and its initial remaining total is assumed to be 0.5 units. The disinfectant is not considered a target missing resource. According to Table 1.1, the standard consumption of cleaning agent in the standard cleaning mode is 1 unit. The deviation range calculated based on this standard consumption is greater than or equal to 0.3 units, indicating that 0.3 units of cleaning agent can ensure that the components to be cleaned can complete the basic cleaning function. The safe range calculated based on the initial remaining total amount of cleaning agent is less than or equal to 0.5 units. Therefore, the preset range for cleaning agent consumption is [0.3, 0.5]. If the downgrade adjustment result, i.e., the saving amount of cleaning agent in the saving cleaning mode is 0.5 units, indicates that this downgrade adjustment result can be used to adjust the standard cleaning mode to obtain the saving cleaning mode. The adjustment process is as follows: While keeping all other necessary resources except cleaning agent and their standard consumption unchanged in Table 1.1, based on the above downgrade adjustment result: the saving amount of cleaning agent in the saving mode is 0.5 units, adjust the standard cleaning mode shown in Table 1.1 to obtain the saving cleaning mode shown in Table 1.2. Table 1.2 specifically shows the necessary resources for rag 1 in this mode and their corresponding consumption.

[0065] Table 1.2 - Required resources and consumption of cleaning cloth 1 in the energy-saving cleaning mode

[0066] As can be seen, in the above example, the object of the downgrade adjustment is the cleaning agent; the preset range for the downgrade adjustment is: the cleaning agent is greater than or equal to 0.3 parts and less than or equal to 0.5 parts. The downgrade adjustment result within this preset range is: the amount of the target missing resource (cleaning agent) saved in the save-cleaning mode (0.5 parts).

[0067] Corresponding to the example shown in Table 2.1, the implementation process of steps S10321 to S10325 is as follows: Assume that the remaining cleaning resources are insufficient, corresponding to the cleaning water. Compare and analyze the cleaning water with the necessary resources shown in Table 2.1 to determine that the cleaning water is the target missing resource affecting the standard cleaning mode, and assume that its initial remaining total amount is 1L. According to Table 2.1, the standard consumption of cleaning water in the standard cleaning mode is 1.5 units. The deviation range calculated based on this standard consumption is greater than or equal to 0.7L, indicating that 0.7L of cleaning water can ensure that the components to be cleaned can complete the basic cleaning function. The safe range calculated based on the initial remaining total amount of cleaning water is less than or equal to 1L. Therefore, the preset range is the cleaning water consumption interval [0.7, 1]. If the downgrade adjustment result, i.e., the water saving in the water-saving cleaning mode is 1L, indicates that this downgrade adjustment result can be used to adjust the standard cleaning mode to obtain the water-saving cleaning mode. The adjustment process is as follows: While keeping all other necessary resources (except for the water used for cleaning) and their standard consumption unchanged in Table 2.1, based on the downgrade adjustment result that the water saving in the water-saving mode is 1L, adjust the standard cleaning mode shown in Table 2.1 to obtain the water-saving cleaning mode shown in Table 2.2. Table 2.2 specifically shows the necessary resources for the cleaning cloth 2 in this mode and their corresponding consumption.

[0068] Table 2.2 - Required resources and consumption of cleaning cloth 2 in the energy-saving cleaning mode

[0069] As can be seen, in the above example, the target of the downgrade adjustment is the cleaning water; the preset range of the downgrade adjustment is: the cleaning water is greater than or equal to 0.7L and less than or equal to 1L. The downgrade adjustment result within this preset range is: the amount of water saved in the target missing resource (cleaning water) in the save-cleaning mode (1L).

[0070] It should be noted that the degradation adjustment method shown in steps S10321 to S10325 above is a general method for degradation adjustment for multiple missing resources. For ease of intuitive understanding, the simplified scenario of "one missing resource" and "one component to be cleaned" shown in Tables 1.1 and 2.1 is used as an example. When facing multiple missing resources, the degradation adjustment result is the amount of consumption saved for each target missing resource in the save cleaning mode, such as the amount of consumption saved for target missing resource 1 - cleaning water in the save cleaning mode X1, and the amount of consumption saved for target missing resource 2 - cleaning agent in the save cleaning mode X2.

[0071] According to such Figure 1 The cleaning system shown and such Figure 2The clean base station shown in this embodiment of the invention, and the resource adaptive cleaning control method for the clean base station, also needs to consider scenarios with multiple components to be cleaned. While the basic processing principle described in the aforementioned degradation adjustment method is also applicable to scenarios with multiple components to be cleaned, considering the complex realities involving various missing resources and / or multiple components to be cleaned, this embodiment of the invention also provides several implementation methods for obtaining degradation adjustment results under different resource missing conditions and different numbers of components to be cleaned. These implementation methods exemplarily provide multiple conversion paths for calculating the saved consumption of the target missing resource in the saved cleaning mode from the standard consumption of the target missing resource in the standard cleaning mode under different resource missing conditions and different numbers of components to be cleaned.

[0072] In the first conversion path, for cases where the target missing resource is of a single type or includes multiple types, and the number of components to be cleaned is 1, the downgrade adjustment result is obtained as follows: the initial remaining total amount of each target missing resource is taken as the consumption saving amount of each target missing resource in the save-cleaning mode. Tables 1.1 and 1.2, and Tables 2.1 and 2.2 show the downgrade adjustments for cloth 1 and cloth 2, illustrating this method that maximizes the cleaning effect.

[0073] Here, we will further illustrate the situation with the cleaning cloth 1 shown in Table 1.1, assuming that the insufficient remaining cleaning resources correspond to two types of missing resources: cleaning agent and cleaning water. Both of these missing resources are target missing resources. The initial remaining total amount of cleaning agent is 0.5 units, and the initial remaining total amount of cleaning water is 0.7L. Then, within the preset range, the downgrade adjustment result is that the consumption saving of cleaning agent in the save-cleaning mode is 0.5 units, and the consumption saving of cleaning water in the save-cleaning mode is 0.7L. Using this downgrade adjustment result to adjust the standard cleaning mode yields the save-cleaning mode shown in Table 1.3. Table 1.3 specifically shows the necessary resources for cleaning cloth 1 in this mode and their corresponding consumption.

[0074] Table 1.3 - Required resources and consumption of cleaning cloth 1 in energy-saving cleaning mode

[0075] The first conversion path described above maximizes the cleaning potential based on existing remaining cleaning resources, thereby achieving relatively good cleaning results even in the energy-saving cleaning mode.

[0076] In the second conversion path, for cases where the target missing resource is of a single type and the number of components to be cleaned is greater than 1, the downgrade adjustment result is obtained according to the first graded downgrade scheme based on the priority of each component to be cleaned.

[0077] In this embodiment of the invention, the first graded degradation scheme adopts a single-dimensional adaptive control strategy, performing differentiated degradation adjustments based on the priority of each component to be cleaned. This scheme aims to: prioritize ensuring the cleaning needs of high-priority components, and then further allocate resources to meet the cleaning needs of lower-priority components. Through this asymmetric allocation mechanism based on the priority of the components to be cleaned, the cleaning effect of core components can be guaranteed as much as possible even when remaining cleaning resources are insufficient, ensuring the subsequent cleaning effect of the cleaning equipment. This avoids the problems of excessive degradation of core components and ineffective degradation of non-core components that are prone to occur in traditional fixed degradation methods.

[0078] For example, according to the first graded downgrade scheme, the downgrade adjustment is performed based on the standard consumption of the target missing resource in the standard cleaning mode to obtain the consumption saving amount of the target missing resource in the economical cleaning mode, including: SA, based on the priority of each of the components to be cleaned, performs the downgrade adjustment.

[0079] The detailed implementation steps of SA include: SA1. For the components to be cleaned with high priority, the standard cleaning mode shall be adopted; SA2. Based on the standard consumption of the target missing resource in the standard cleaning mode, calculate the first remaining total amount of the target missing resource after the standard cleaning mode ends. SA3. For the components to be cleaned with low priority, the energy-saving cleaning mode or delayed cleaning is adopted; wherein, the energy-saving consumption of the target missing resource in the energy-saving cleaning mode is obtained by downgrading the standard consumption, and the energy-saving consumption is capped at the difference between the initial remaining total and the first remaining total.

[0080] Here, we take three cleaning components, rag 1, rag 3 and rag 4, in a cleaning device as an example to illustrate the downgrading adjustment based on the priority of each component to be cleaned, as shown in step SA above.

[0081] First, during the cleaning process, the three components (cloth 1, cloth 3, and cloth 4) are assigned tasks according to the cleaning sequence for the same area to be cleaned: Cloth 1 is used for rough cleaning, such as removing large particles and heavy oil stains; Cloth 3 is used for fine cleaning, such as further removing residual stains; and Cloth 4 is used for polishing / drying, such as removing watermarks and improving smoothness. Based on this, on the cleaning base station side, Cloth 1 is considered component 1 to be cleaned, and its dirt parameter is 60% oil stain; Cloth 3 is considered component 2 to be cleaned, and its dirt parameter is 30% oil stain; and Cloth 4 is considered component 3 to be cleaned, and its dirt parameter is 10% oil stain. The necessary resources and their consumption for Cloth 1 in the standard cleaning mode are shown in Table 1.1, the necessary resources and their consumption for Cloth 3 in the standard cleaning mode are shown in Table 3.1 below, and the necessary resources and their consumption for Cloth 4 in the standard cleaning mode are shown in Table 4.1 below.

[0082] Table 1.1 - Required resources and consumption of cleaning cloth 1 under standard cleaning mode

[0083] Table 3.1 - Required resources and consumption of cleaning cloth 3 under standard cleaning mode

[0084] Table 4.1 - Required resources and consumption of cleaning cloth 4 under standard cleaning mode

[0085] The priority of each component to be cleaned can be determined based on its dirt level, urgency, or a combination of dirt level, urgency, and other factors, such as component replacement cost and its weight in the overall cleaning effect. Considering that dirt level directly and objectively reflects the actual cleaning needs of each component and is easy to obtain and quantify, this embodiment of the invention determines the priority of each component to be cleaned based on its dirt level. Here, we will use the determination of priority based on dirt level as an example. Therefore, the priorities of the above-mentioned cloths 1, 3, and 4 are: Cloth 1 (60% oil stain value) > Cloth 3 (30% oil stain value) > Cloth 4 (10% oil stain value).

[0086] Assuming the remaining cleaning resources represent 1.5 parts of cleaning agent, which is less than the 1.9 parts required for rags 1, 3, and 4, then the remaining cleaning resources are insufficient for the corresponding cleaning agent, and the cleaning agent is the target missing resource. Therefore, the standard consumption of cleaning agent for each component to be cleaned in the standard cleaning mode can be obtained from Tables 1.1, 3.1, and 4.1.

[0087] Before performing step SA above, resource matching is performed on each component to be cleaned with priority based on the initial remaining amount of the target missing resource—the cleaning agent—and a preset range, to identify at least one high-priority component and at least one low-priority component to be cleaned. Specifically, if both rag 1 and rag 3 are high-priority components to be cleaned, according to the standard consumption of cleaning agent in the standard cleaning mode shown in Tables 1.1 and 3.1, the initial remaining amount of cleaning agent is insufficient to support both rag 1 and rag 3 being high-priority components to be cleaned. Therefore, only rag 1 is designated as a high-priority component to be cleaned.

[0088] According to step SA1, the standard cleaning mode is adopted for cloth 1. The downgrade adjustment result for cloth 1 is the standard consumption of cleaning agent in the standard cleaning mode. Therefore, it is not necessary to adjust the standard cleaning mode according to the downgrade adjustment result.

[0089] According to step SA2, the first remaining amount of cleaning agent after the standard cleaning mode is 1.5-1=0.5L.

[0090] According to step SA3, rags 3 and rag 4 are considered low-priority components to be cleaned. For rag 3, the amount of cleaning agent saved in the save-cleaning mode is adjusted downgraded based on the standard consumption of 0.6; for rag 4, the amount of cleaning agent saved in the save-cleaning mode is adjusted downgraded based on the standard consumption of 0.3. Considering that the lower limit of the deviation range in the preset range corresponding to rag 4 is 0, meaning that rag 4 can maintain basic cleaning function with just water, the downgraded adjustment result for rag 3 is that the amount of cleaning agent saved in the save-cleaning mode is the first remaining total amount of cleaning agent, 0.5L; for rag 4, the downgraded adjustment result is that the amount of cleaning agent saved in the save-cleaning mode is 0L; and for rag 1, the downgraded adjustment result is that the standard consumption of cleaning agent in the standard cleaning mode is 1L.

[0091] The aforementioned rags 1, rag 3, and rag 4 conform to the second conversion path, which targets a single type of missing resource and has a quantity greater than 1 for the components to be cleaned. The above text shows the first graded degradation scheme based on the priority of each component to be cleaned, resulting in three degradation adjustment results. Based on these three degradation adjustment results, the standard cleaning mode is adjusted to obtain the cost-saving cleaning mode, as shown in Table 1.4 and Tables 3.2 and 4.2 below.

[0092] Table 1.4 - Required resources and consumption of cleaning cloth 1 in the energy-saving cleaning mode

[0093] Table 3.2 Required resources and consumption of cleaning cloth 3 in the energy-saving cleaning mode

[0094] Table 4.2 - Required resources and consumption of cleaning cloth 4 in the energy-saving cleaning mode

[0095] In the third conversion path, for cases where the target missing resources include multiple types and the number of components to be cleaned is greater than 1, the downgrade adjustment result is obtained based on the second graded downgrade scheme based on the priority of each component to be cleaned and the priority of each target missing resource.

[0096] In this embodiment of the invention, the second graded degradation scheme adopts a two-dimensional coupled adaptive control strategy, performing differentiated degradation adjustments based on the priority of each component to be cleaned and the priority of the target missing resources. This scheme aims to: firstly, clarify the order of degradation adjustments to achieve item-by-item configuration of multiple target missing resources; and then, during the allocation process for each specific target missing resource, nest the control logic of the first graded degradation scheme, i.e., prioritize ensuring the cleaning needs of high-priority components to be cleaned. Thus, when facing complex situations involving multiple missing resources and multiple components to be cleaned, the dual mechanism of first allocating resources by priority and then ensuring priority by component coordinates the coupling relationship between each missing resource and each component to be cleaned. This maximizes the cleaning effect of the core components to be cleaned while avoiding interruptions to the cleaning task due to limited resources from multiple sources, significantly improving the ability of the cleaning base station to ensure the continuity of the cleaning task under complex and changing resource constraints, as well as the subsequent cleaning effect of the cleaning equipment.

[0097] For example, according to the second graded degradation scheme, the degradation adjustment is performed based on the standard consumption of the target missing resource in the standard cleaning mode to obtain the consumption saving amount of the target missing resource in the economical cleaning mode, including: SB performs the downgrade adjustment based on the priority of each component to be cleaned and the priority of each target missing resource.

[0098] The detailed implementation steps of SB include: SB1. Select the component to be cleaned with the highest priority, sort the dirt parameters of the component to be cleaned from high to low, and obtain the priority of the target missing resource based on the sorting result; SB2. Allocate each of the target missing resources in sequence according to the priority shown by the target missing resources, and each allocation is based on the priority of each component to be cleaned.

[0099] The implementation of step SB2 above is the same as the downgrade adjustment of the first hierarchical downgrade scheme. Therefore, the second hierarchical downgrade scheme adopted by the third conversion path in this embodiment of the invention can be downgraded by directly nesting the first hierarchical downgrade scheme, thereby reusing existing algorithm modules in logical implementation and reducing computational overhead.

[0100] For example, the priority of the target missing resources obtained by SB1 is represented by a sequence of missing resources from the first target missing resource to the Nth target missing resource. Based on this, the detailed implementation of SB2 is as follows: according to the order shown by the priority of the target missing resources, that is, according to the sequence of missing resources from the first target missing resource to the Nth target missing resource, the resources are allocated sequentially in the order from the first target missing resource to the Nth target missing resource.

[0101] The allocation nests the control logic for executing the first-level degradation scheme, that is, for the nth target missing resource currently being processed, the first-level degradation scheme is adopted; SB21. For the high-priority components to be cleaned, the standard cleaning mode is adopted, and the nth target missing resource is the standard consumption amount in the standard cleaning mode; SB22. After cleaning the high-priority components to be cleaned, calculate the first remaining total amount of the nth target missing resource; SB23. For the components to be cleaned with low priority, the saving cleaning mode is adopted. The saving consumption of the nth target missing resource in the saving cleaning mode is obtained by downgrading the standard consumption. The saving consumption is capped at the difference between the initial remaining total and the first remaining total.

[0102] Taking rag 1, rag 2, and rag 3 as examples, according to the above example, the dirt parameter of rag 1 is 60% oil stain, the dirt parameter of rag 2 is 85% overall dirt, assuming its composition is 50% oil stain and 35% dust, and the dirt parameter of rag 3 is 30% oil stain. The necessary resources and their consumption for each component to be cleaned in standard mode are still shown in Tables 1.1, 2.1, and 3.1.

[0103] Based on the dirt parameters, the priority of each component to be cleaned is determined as: rag 2 > rag 1 > rag 3. The missing resources corresponding to insufficient remaining cleaning resources are cleaning agent and cleaning water, both of which are target missing resources. According to step B1, rag 2 is selected, and its dirt parameters are sorted from high to low as: oil value > dust value. Based on this sorting result, the priority of target missing resource 1 – cleaning agent – ​​is higher than that of target missing resource 2 – cleaning water. According to step SB2, cleaning agent is allocated first to rags 1, rag 2, and rag 3. The initial remaining total amount of cleaning agent is 3 units. During allocation, the control logic of the first-level degradation scheme is executed: Table 1.1 - Required resources and consumption of cleaning cloth 1 under standard cleaning mode

[0104] Table 2.1 - Required resources and consumption of cleaning cloth 2 under standard cleaning mode

[0105] Table 3.1 - Required resources and consumption of cleaning cloth 3 under standard cleaning mode

[0106] First, the initial remaining amount of cleaning agent is 3 units. Both rag 2 and rag 1 can be classified as high-priority cleaning components. However, according to the preset range of rag 3, it is obviously not the same as rag 4. The amount of cleaning agent saved in the energy-saving cleaning mode can be limited to 0. Assuming that the preset range for downgrading rag 3 limits the amount of cleaning agent saved in the energy-saving cleaning mode to no less than 0.2 units, then according to the initial remaining amount of cleaning agent and the preset range of each cleaning component, it can be seen that only rag 2 can be classified as a high-priority cleaning component, and rag 1 and rag 3 can be classified as low-priority cleaning components.

[0107] According to step SB21 above, for the high-priority rag 2, the standard cleaning mode is adopted, and the downgrade adjustment result is the standard consumption of cleaning agent in the standard cleaning mode, which is 2 parts.

[0108] According to step SB22 above, the first remaining amount of cleaning agent after the completion of the standard cleaning mode is 1 part.

[0109] According to step SB23 above, for the low-priority rags 1 and rag 3, based on the example above, the preset range for downgrading rag 3 is limited to a minimum cleaning agent consumption saving of 0.2 units in the energy-saving cleaning mode, and the maximum saving consumption for both rag 3 and rag 1 is 1 unit. Therefore, for rag 1, the downgrading adjustment result is a cleaning agent consumption saving of 0.8 units in the energy-saving cleaning mode, and for rag 3, the downgrading adjustment result is a cleaning agent consumption saving of 0.2 units in the energy-saving cleaning mode.

[0110] Then, with an initial remaining total of 3L of cleaning water, based on the same logic, both cloth 2 and cloth 1 are classified as high-priority components to be cleaned, while cloth 3 is classified as a low-priority component to be cleaned. Therefore, for cloth 2, the downgraded adjustment result is that the standard consumption of cleaning water in the standard cleaning mode is 1.5L; for cloth 1, the downgraded adjustment result is that the standard consumption of cleaning water in the standard cleaning mode is 1L; and for cloth 3, the downgraded adjustment result is that the standard consumption of cleaning water in the standard cleaning mode is 0.5L.

[0111] The aforementioned rags 1, rag 2, and rag 3 conform to the third conversion path, which targets multiple types of missing resources and has a greater than 1 number of components to be cleaned. The above shows the second graded degradation scheme based on the priority of each component to be cleaned and the priority of each target missing resource, resulting in three degradation adjustment results. Based on these three degradation adjustment results, the standard cleaning mode is adjusted to obtain the cost-saving cleaning mode, as shown in Tables 1.5, 2.3, and 3.3 below.

[0112] Table 1.5 - Required resources and consumption of cleaning cloth 1 in energy-saving cleaning mode

[0113] Table 2.3 - Required resources and consumption of cleaning cloth 2 in the energy-saving cleaning mode

[0114] Table 3.3 - Required resources and consumption of cleaning cloth 3 in the energy-saving cleaning mode

[0115] On the other hand, based on the above embodiments ensuring the continuity of cleaning tasks and taking into account the differentiated cleaning needs of each component to be cleaned, the adaptive cleaning control method for cleaning base station resources provided in this embodiment of the invention also optimizes the saving cleaning mode based on resource complementarity to obtain a compensating cleaning mode, thereby alleviating the problem of decreased cleaning effect that may be caused by ensuring the continuity of cleaning tasks.

[0116] The above optimization is performed after step S1032 determines that the remaining cleaning resources are insufficient, and after the downgrade adjustment is completed as described in steps S10321 to S10325 to obtain a save-cleaning mode, including: Based on the amount of consumption saved by the target missing resource in the energy-saving cleaning mode, construct a resource coupling matrix; According to the resource coupling matrix, if the remaining cleaning resources meet the compensation conditions, then the compensation cleaning resources corresponding to the compensation conditions and the additional consumption of each compensation cleaning resource are obtained. A compensated cleaning mode is obtained by compensating the saved cleaning mode. The compensation adjustment includes adding the additional consumption to the saved cleaning resources in the saved cleaning mode.

[0117] In the above steps, the resource coupling matrix establishes the substitution and compensation logic between different cleaning resources, serving as the basis for cross-dimensional parameter collaborative adjustment and quantitative compensation calculation when some resources are scarce. For example, when the target missing resource is cleaning water, compensation can be made by extending the cleaning time, based on the reduction of cleaning water using the water-saving cleaning mode determined according to the above embodiments; or, when the target missing resource is cleaning agent, compensation can be made by extending the cleaning time and / or cleaning water, based on the reduction of cleaning agent using the water-saving cleaning mode determined according to the above embodiments.

[0118] The detailed implementation of the above steps is illustrated here using a typical resource coupling matrix shown in Table 5 below.

[0119] Table 5 - Resource Coupling Matrix

[0120] According to Table 5 above, the target missing resource is cleaning water, the compensated cleaning resource is cleaning time, and the additional consumption is 0.6. Following the steps above, determine if the compensation condition is met: that is, whether the remaining amount of the compensated cleaning resource minus the cleaning time after executing the save-time cleaning mode is greater than 0.6. If it is greater, then the compensation condition is met. If the compensation condition is met, perform the compensation operation: add the saved consumption amount (here, 1) of the compensated cleaning resource in the save-time cleaning mode to the additional consumption amount (0.6), resulting in a compensated cleaning time consumption of 1.6. Correspondingly, the consumption of the target missing resource (cleaning water) remains unchanged, still 0.6 in the save-time cleaning mode.

[0121] This allows us to compare the consumption under the two modes: Water-saving cleaning mode: Water consumption is 0.6, and cleaning time consumption is 1. Compensated cleaning mode: Water consumption for cleaning remains at 0.6, while cleaning time consumption increases to 1.6.

[0122] It should be noted that the types of cleaning resources are not limited to those shown here, and the resource coupling matrix in reality may be more complex. Within the overall framework of the aforementioned degradation adjustment, this embodiment of the invention aims to utilize remaining cleaning resources for compensation to mitigate the decline in cleaning effectiveness caused by degradation. Therefore, the aforementioned compensation cleaning mode can employ a single resource for simple compensation to adapt to lightweight scenarios with limited computing power; or it can employ multiple resources for joint compensation to suit complex application environments with sufficient resources, higher requirements for cleaning effectiveness, or more flexible compensation strategies.

[0123] In order to directly obtain the judgment result of whether the remaining cleaning resources are sufficient when performing downgrade adjustment in the above embodiments, thereby improving decision-making efficiency, the embodiments of the present invention perform a pre-verification of the remaining cleaning resources of the cleaning base station based on sufficiency by using a preset prediction function.

[0124] This step can be performed before step S103 above, which determines the continuous cleaning mode based on the dirt parameters and the remaining cleaning resources, and includes: The remaining cleaning resources are input into a preset prediction function, and the preset prediction function is used to obtain a judgment result of whether the remaining cleaning resources are sufficient or insufficient.

[0125] The preset prediction function provided in this embodiment of the invention divides the remaining cleaning resources into rigid resources and flexible resources. The preset prediction function includes a first intermediate variable and a second intermediate variable, and the resource percentage is obtained by multiplying the first intermediate variable and the second intermediate variable. The first intermediate variable is obtained by calculating the minimum value based on rigid resources, and the second intermediate variable is obtained by calculating the preset piecewise function based on flexible resources. When the resource percentage is greater than or equal to a preset threshold, the remaining cleaning resources are sufficient; when the resource percentage is less than the preset threshold and is not 0, the remaining cleaning resources are insufficient.

[0126] It should be noted that rigid resources are cleaning resources that, once exhausted, will directly cause the output of the preset prediction function to be 0; elastic resources are cleaning resources that, even if exhausted, can still ensure that the output of the preset prediction function is not 0.

[0127] Based on this preset prediction function, on the one hand, the embodiments of the present invention can also determine whether the current remaining cleaning resources are sufficient to execute the above-mentioned resource adaptive cleaning control method. For example, when the rigid resources are less than the lower limit, the judgment result of the preset prediction function will definitely be that the remaining cleaning resources are exhausted, and cleaning cannot be performed if there is no remaining cleaning time or no remaining power. On the other hand, through the second intermediate variable, namely the preset piecewise function based on the elastic resources, the nonlinear relationship between the remaining status of the elastic resources and whether the remaining cleaning resources are sufficient can be quantified. Thus, the resource percentage output by the preset prediction function is a refined judgment result that can quantify the severity of resource scarcity.

[0128] Taking flexible resources as the cleaning agent and rigid resources as electricity as an example, when the remaining cleaning agent is 0 and the remaining electricity is at its maximum value, the second intermediate variable will be a relatively small value. Although this will not cause the resource percentage output by the preset prediction function to be 0, it will usually lead to a judgment that the remaining cleaning resources are slightly insufficient. When the remaining cleaning agent is at its maximum value and the remaining electricity is a relatively small value but not lower than the lower limit, the resource percentage output by the preset prediction function will correspond to a judgment that the remaining cleaning resources are severely insufficient.

[0129] For example, the formula for calculating the predictive function is: R=min(R X1 ,R X2 ,...,R XN )*f(R Y1 ,R Y2 ,...,R YM ); Among them, X1~XN are rigid resources, such as remaining water volume, remaining electricity volume, and remaining available cleaning time, while Y1~YM are flexible resources, such as remaining cleaning dosage.

[0130] When the cleaning base station is unable to obtain the dirt parameters of the component to be cleaned due to sensor failure, communication anomalies, or special operating modes, this embodiment of the invention can also adaptively enable a multi-level degradation strategy based on the aforementioned preset prediction function. For example, when the calculated resource percentage is less than the preset threshold, the method for determining the continuous cleaning mode includes: If the percentage of resources is within a preset first threshold range, then the remaining cleaning resources are slightly insufficient, and the continuous cleaning mode adopts an adaptive control method to shorten the cleaning time. If the resource percentage is within the preset second threshold range, then the remaining cleaning resources are moderately insufficient, and the continuous cleaning mode is a control method that uses adaptive control to reduce the cleaning water temperature and shorten the cleaning time. If the resource percentage is within the preset third threshold range, then the remaining cleaning resources are severely insufficient, and the continuous cleaning mode is a control method that cancels the use of cleaning agent and switches the operation mode to the rapid rinsing mode for cleaning operations. If the resource percentage is 0, pause the current cleaning task and enter a waiting state for replenishment until a resource replenishment instruction is received.

[0131] The above embodiments also show that the remaining cleaning water and remaining cleaning agent are the actual cleaning resources for the cleaning base station and can be replenished; the remaining power and remaining cleaning time are the operational cleaning resources for the cleaning base station and cannot be replenished. Other unmentioned remaining cleaning resources can also be categorized according to whether they can be replenished. Based on this, to reflect the difference between replenishable and non-replenishable resources in subsequent resource insufficiency judgments, thereby improving the targeting of downgrade or compensation decisions, in one embodiment, before obtaining the judgment result of insufficient remaining cleaning resources through the preset prediction function, if the resource percentage is less than a preset threshold and not 0, the method further includes: Issue additional prompts; Monitor whether supplementary instructions are received within a preset time; If not, output the judgment result that the remaining cleaning resources are insufficient; If so, update the remaining cleaning resources and rerun the preset prediction function based on the updated remaining cleaning resources.

[0132] It should be noted that before issuing a supplementary prompt, if the resource percentage output by the preset prediction function is less than a preset threshold, it indicates insufficient remaining cleaning resources. Depending on the different settings in the above embodiments, this percentage may also indicate a severe shortage of remaining cleaning resources. After issuing a supplementary prompt, if a supplementary instruction is received within a preset time, the preset prediction function is re-run, and the recalculated resource percentage may be greater than the preset threshold. In this case, the remaining cleaning resources are sufficient, and the standard cleaning mode can be adopted. Alternatively, according to the above embodiments, the recalculated resource percentage only indicates a slight shortage. Compared to the severe shortage state before supplementation, the cleaning mode can be upgraded from a lower level to a correspondingly higher level.

[0133] It is understandable that when the preset prediction function determines that the remaining cleaning resources are insufficient, this result may be dynamically adjusted. For example, the initial remaining cleaning resources of the cleaning base station may be sufficient or insufficient, and a defined continuous cleaning mode may exist. However, as the cleaning process progresses, the remaining cleaning resources may become insufficient to support the defined continuous cleaning mode. In this case, the aforementioned supplementary prompt can be issued before further downgrade adjustments. If a supplementary instruction is received within a preset time, the defined continuous cleaning mode can be restored.

[0134] This invention also provides a computer-readable storage medium storing instructions that, when executed by a processor, configure the processor to perform the resource adaptive cleaning control method for a clean base station as described in the above embodiments.

[0135] Computer-readable media, as defined herein, includes both permanent and non-permanent, removable and non-removable media, which can store information using any method or technology. Information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0136] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A resource adaptive cleaning control method for a clean base station, characterized in that, include: Obtain the dirt parameters of the component to be cleaned; Monitor the remaining cleaning resources at the clean base station; Based on the dirt parameters and the remaining cleaning resources, a continuous cleaning mode is determined; The cleaning base station is controlled to clean the components to be cleaned in the continuous cleaning mode.

2. The resource adaptive cleaning control method for clean base stations according to claim 1, characterized in that, The step of determining the continuous cleaning mode based on the dirt parameters and the remaining cleaning resources includes: When there are sufficient remaining cleaning resources, the continuous cleaning mode is determined to be the standard cleaning mode. When the remaining cleaning resources are insufficient, the continuous cleaning mode is determined to be a save-cleaning mode. The energy-saving cleaning mode is obtained by downgrading the standard cleaning mode within a preset range. The dirt parameters are used to determine the necessary resources and their consumption for the component to be cleaned in the standard cleaning mode, so as to obtain the preset range based on the necessary resources and their consumption.

3. The resource adaptive cleaning control method for a clean base station according to claim 2, characterized in that, The step of downgrading the standard cleaning mode within a preset range to obtain the energy-saving cleaning mode includes: When the remaining cleaning resources are insufficient, obtain one or more missing resources; For a target missing resource that is of the same type as any of the required resources, obtain the standard consumption of the target missing resource in the standard cleaning mode and the initial remaining total amount of the target missing resource. The deviation range is calculated based on the standard consumption of the target missing resource in the standard cleaning mode, and the safety range is calculated based on the initial remaining total amount of the target missing resource. The preset range is determined by the deviation range and the safety range. The target missing resource is downgraded based on its standard consumption in the standard cleaning mode to obtain a downgraded adjustment result within the preset range; the downgraded adjustment result is the reduced consumption of the target missing resource in the save cleaning mode. The standard cleaning mode is adjusted based on the downgrade adjustment results to obtain the cost-saving cleaning mode.

4. The resource adaptive cleaning control method for a clean base station according to claim 3, characterized in that, If there is no target missing resource that matches any of the required resources in type, then the downgrade adjustment will not be performed.

5. The resource adaptive cleaning control method for a clean base station according to claim 3 or 4, characterized in that, When the number of components to be cleaned is 1, the degradation adjustment result is obtained as follows: The initial remaining total amount of each of the target missing resources is used as the amount of consumption saved for each of the target missing resources in the save-cleaning mode.

6. The resource adaptive cleaning control method for a clean base station according to claim 3 or 4, characterized in that, When the target missing resource is of a single type and the number of components to be cleaned is greater than 1, the degradation adjustment result is obtained according to the first-level degradation scheme based on the priority of each component to be cleaned.

7. The resource adaptive cleaning control method for a clean base station according to claim 6, characterized in that, The method further includes: determining the priority of each component to be cleaned based on the dirt parameters of each component to be cleaned.

8. The resource adaptive cleaning control method for a clean base station according to claim 6, characterized in that, The downgrade adjustment of the first tiered downgrade scheme includes: For the high-priority components to be cleaned, the standard cleaning mode is used; Based on the standard consumption of the target missing resource in the standard cleaning mode, calculate the first remaining total amount of the target missing resource after the standard cleaning mode ends; For the components to be cleaned with low priority, the save-cleaning mode or the cleaning is delayed. When the save-cleaning mode is used, the save consumption of the target missing resource in the save-cleaning mode is obtained by downgrading the standard consumption, and the save consumption is capped at the difference between the initial remaining total and the first remaining total.

9. The resource adaptive cleaning control method for a clean base station according to claim 8, characterized in that, Also includes: Based on the initial remaining total amount of the target missing resources and the preset range of each of the components to be cleaned, at least one component to be cleaned with a high priority is identified based on the priority of each component to be cleaned.

10. The resource adaptive cleaning control method for a clean base station according to claim 3 or 4, characterized in that, The target missing resources include multiple types, and when the number of components to be cleaned is greater than 1, the degradation adjustment result is obtained according to a second-level degradation scheme based on the priority of each component to be cleaned and the priority of each target missing resource.

11. The resource adaptive cleaning control method for a clean base station according to claim 10, characterized in that, The downgrade adjustments in the second tiered downgrade scheme include: Select the component with the highest priority to be cleaned, sort the dirt parameters of the component to be cleaned from high to low, and obtain the priority of the target missing resource based on the sorting result; The target missing resources are allocated sequentially according to the priority order shown by the target missing resources, and the allocation is based on the priority of each component to be cleaned.

12. The resource adaptive cleaning control method for a clean base station according to claim 3 or 4, characterized in that, After performing a downgrade adjustment based on the standard consumption to obtain the reduced consumption of the target missing resource in the save-cleaning mode, the method further includes: Based on the amount of consumption saved by the target missing resource in the energy-saving cleaning mode, construct a resource coupling matrix; According to the resource coupling matrix, if the remaining cleaning resources meet the compensation conditions, then the compensation cleaning resources corresponding to the compensation conditions and the additional consumption of each compensation cleaning resource are obtained. A compensated cleaning mode is obtained by compensating the saved cleaning mode. The compensation adjustment includes adding the additional consumption to the saved cleaning resources in the saved cleaning mode.

13. The resource adaptive cleaning control method for a clean base station according to claim 1, characterized in that, Before determining the continuous cleaning mode based on the dirt parameters and the remaining cleaning resources, the method further includes: The remaining cleaning resources are input into a preset prediction function, and the preset prediction function is used to obtain a judgment result of whether the remaining cleaning resources are sufficient or insufficient.

14. The resource adaptive cleaning control method for a clean base station according to claim 13, characterized in that, The preset prediction function includes a first intermediate variable and a second intermediate variable, and the resource percentage is obtained by multiplying the first intermediate variable and the second intermediate variable. The first intermediate variable is obtained by calculating the minimum value based on rigid resources, and the second intermediate variable is obtained by calculating the preset piecewise function based on elastic resources; the remaining cleaning resources include rigid resources and elastic resources. When the resource percentage is greater than or equal to a preset threshold, the remaining cleaning resources are sufficient; When the percentage of resources is less than a preset threshold and is not 0, the remaining cleaning resources are insufficient.

15. The resource adaptive cleaning control method for a clean base station according to claim 13, characterized in that, Before obtaining the judgment result of insufficient remaining cleaning resources through the preset prediction function, the method further includes: Issue additional prompts; Monitor whether supplementary instructions are received within a preset time; If not, output the judgment result that the remaining cleaning resources are insufficient; If so, update the remaining cleaning resources and rerun the preset prediction function based on the updated remaining cleaning resources.

16. The resource adaptive cleaning control method for a clean base station according to claim 1, characterized in that, After the control cleaning base station cleans the components to be cleaned in the continuous cleaning mode, it further includes: Continuously monitor the real-time remaining cleaning resources of the clean base stations; Based on the dirt parameters and the real-time remaining cleaning resources, determine whether the continuous cleaning mode has changed; If a change occurs, the cleaning base station is controlled to clean the component to be cleaned in a standby cleaning mode determined based on the dirt parameters and the real-time remaining cleaning resources.

17. The resource adaptive cleaning control method for a clean base station according to claim 1, characterized in that, The remaining cleaning resources include at least one of the following: Remaining cleaning water, remaining cleaning agent, remaining electricity, and remaining cleaning time.

18. A clean base station, characterized in that, include: Base station main body; The resource monitoring module is used to monitor the remaining cleaning resources; A dirt detection device is used to obtain dirt parameters of the cleaning components; A controller for executing the resource adaptive cleaning control method for a clean base station as described in any one of claims 1 to 17.

19. A cleaning system comprising a cleaning base station as described in claim 18 and at least one cleaning device; The cleaning equipment is equipped with at least one cleaning component. When the cleaning equipment is used in conjunction with the cleaning base station, the cleaning component serves as the component to be cleaned for the cleaning base station.

20. A computer-readable storage medium storing instructions thereon, characterized in that, When the instructions are executed by the processor, the processor is configured to perform the resource adaptive cleaning control method for the cleaning base station as described in any one of claims 1 to 17.

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