An intelligent spraying method and system applied to an unmanned sweeper and a storage medium

Abstract

The application relates to an intelligent spraying method and system applied to an unmanned sweeper and a storage medium, and the method comprises the following steps: T1. The unmanned sweeper drives on a road, real-time dust content data information in an environment is acquired based on a vehicle-mounted dust sensor, and real-time humidity data information in the environment is acquired based on a vehicle-mounted humidity sensor; T2. According to the dust content data information in the environment, a cubic polynomial is used to perform curve fitting on the relationship between the dust content and water spraying flow, first water spraying flow data information is output, according to the humidity data information in the environment, a parametric inverse ratio function is used to perform curve fitting on the relationship between the environmental humidity and the water spraying flow, and second water spraying flow data information is output; and T3. The first water spraying flow data information and the second water spraying flow data information are used as the basis. The application not only realizes the dust suppression purpose when the unmanned sweeper works, but also improves cleaning cleanliness and water utilization.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of unmanned cleaning vehicles, and in particular to an intelligent spraying method and system applied to an unmanned cleaning vehicle and a storage medium. BACKGROUND

[0002] Currently, a cleaning vehicle cannot automatically adjust a spraying mechanism according to an environment during cleaning operation, and optimal cleaning effect cannot be achieved under various environments.

[0003] A road spraying system capable of automatically removing dust (patent number: CN218911236U) provides a road spraying system capable of automatically removing dust, which comprises a plurality of spraying mechanisms, a water supply mechanism connected with the spraying mechanisms, a plurality of detection mechanisms corresponding to each spraying mechanism, an electric control box electrically connected with the detection mechanisms and used for controlling the water supply mechanism and the spraying mechanism, the spraying mechanism comprises two groups of nozzle assemblies and adjusting assemblies arranged on both sides of the road, the nozzle assembly comprises fixed nozzles and adjusting nozzles arranged alternately, the adjusting nozzles are adjusted in the spraying angle by the adjusting assemblies, the detection mechanism comprises a stand column fixedly arranged on one side of the road, a plurality of PM2.5 probes of different heights are arranged on the stand column, the PM2.5 probes are electrically connected with a controller used for processing data and transmitting signals, and the controller is electrically connected with the electric control box. However, the road spraying system described in the patent can only be fixedly used, and can only start or stop the spraying mechanism according to the dust content, and cannot automatically adjust the spraying caliber and spraying effect of the spraying mechanism according to the dust content. SUMMARY

[0004] In view of the above deficiencies of the prior art, the application provides an intelligent spraying method and system applied to an unmanned cleaning vehicle and a storage medium, which not only achieves the purpose of dust suppression during the operation of the unmanned cleaning vehicle, but also improves the cleaning cleanliness and the water usage rate.

[0005] In order to achieve the above-mentioned purpose and other related purposes, the technical scheme provided by the application is as follows:

[0006] An intelligent spraying method applied to an unmanned cleaning vehicle, the method comprising:

[0007] T1. The unmanned cleaning vehicle drives on the road, real-time dust content data information in the environment is obtained based on a vehicle-mounted dust sensor, and real-time environmental humidity data information is obtained based on a vehicle-mounted humidity sensor;

[0008] T2. According to the dust content data information in the environment, a cubic polynomial is used to perform curve fitting on the relationship between the dust content and the water spraying flow, and first water spraying flow data information is output; according to the environmental humidity data information, a parametric inverse ratio function is used to perform curve fitting on the relationship between the environmental humidity and the water spraying flow, and second water spraying flow data information is output;

[0009] T3. Based on the first water spraying flow data information and the second water spraying flow data information, a minimum value algorithm is adopted to output optimal water spraying flow data information.

[0010] Further, in step T3, the minimum value algorithm comprises:

[0011] T31. The unmanned sweeper travels to a road position requiring spraying, and real-time first water spraying flow data information and second water spraying flow data information are acquired;

[0012] T32. If the water spraying flow in the first water spraying flow data information is greater than the water spraying flow in the second water spraying flow data information, the second water spraying flow data information is selected;

[0013] T33. If the water spraying flow in the first water spraying flow data information is less than the water spraying flow in the second water spraying flow data information, the first water spraying flow data information is selected.

[0014] Further, if the water spraying flow in the first water spraying flow data information is equal to the water spraying flow in the second water spraying flow data information, the first water spraying flow data information is selected.

[0015] Further, in step T2, the curve fitting of the relationship between the dust content and the water spraying flow by using a monomial cubic polynomial is:

[0016] f(x) = ax 3 + bx 2 + cx + d, wherein a, b, c, and d are variable coefficients, x is the dust content, and f(x) is the first water spraying flow.

[0017] Further, in step T2, the curve fitting of the relationship between the environmental humidity and the water spraying flow by using a parametric inverse ratio function is:

[0018]

[0019] wherein a1, b1, c1, and d1 are constant parameters, x is the environmental humidity, and g(x) is the second water spraying flow.

[0020] Further, according to the dust content and the water spraying flow, a first preset threshold is set, and if the dust content is less than the first preset threshold, the water spraying flow is recorded; according to the environmental humidity and the water spraying flow, a second preset threshold is set, and if the environmental humidity is greater than the second preset threshold, the water spraying flow is recorded.

[0021] In order to achieve the above-mentioned and other related purposes, the application further provides an intelligent spraying system applied to an unmanned cleaning vehicle, the system comprising an unmanned cleaning vehicle, a dust sensor, a humidity sensor, a calculation module, a control module, an electrically-controlled adjusting spray head and a deep learning module,

[0022] The unmanned cleaning vehicle is a carrier of the intelligent spraying system and a tool for realizing cleaning operation;

[0023] The dust sensor is used for detecting the dust content in the environment during cleaning and transmitting data to the calculation module;

[0024] The humidity sensor is used for detecting the humidity in the environment during cleaning and transmitting data to the calculation module;

[0025] The calculation module receives the data transmitted by the dust sensor and the humidity sensor, calculates the water spraying amount through a set water spraying amount calculation formula, and transmits information to the control module;

[0026] The control module receives the water spraying amount data transmitted by the calculation module and drives the electrically-controlled adjusting spray head;

[0027] The electrically-controlled adjusting spray head is an execution module of the spraying system;

[0028] The deep learning module adjusts the influence factor coefficient in the water spraying amount calculation formula through deep learning.

[0029] Further, the dust sensor is connected with the calculation module, the humidity sensor is connected with the calculation module, and the calculation module is connected with the control module.

[0030] Further, the control module is connected with the electrically-controlled adjusting spray head, and the deep learning module is connected with the electrically-controlled adjusting spray head.

[0031] In order to achieve the above-mentioned and other related purposes, the application further provides a computer readable storage medium, which stores a computer program programmed or configured to execute any one of the intelligent spraying methods applied to the unmanned cleaning vehicle.

[0032] The application has the following positive effects:

[0033] 1. The application automatically adjusts the spray caliber of the electric spray head by detecting the dust content in the environment during cleaning through the dust sensor and detecting the humidity in the environment during cleaning through the humidity sensor, so as to achieve the dust suppression purpose.

[0034] 2. The application improves the cleaning cleanliness and the water utilization rate by curve fitting of the water spraying amount and obtaining the optimal water spraying amount. BRIEF DESCRIPTION OF DRAWINGS

[0035] Figure 1 A flowchart of the method of the present application;

[0036] Figure 2 A schematic diagram of the system framework of the present application;

[0037] Figure 3 A schematic diagram of the relationship between humidity / dust content and water spraying amount of the present application.

[0038] Explanation of the reference numerals in the figure: 1 - unmanned cleaning vehicle, 2 - deep learning module, 3 - dust sensor, 4 - humidity sensor, 5 - electrically controlled spray head, 6 - calculation module, 7 - control module. DETAILED DESCRIPTION

[0039] Exemplary embodiments of the present disclosure are described below with reference to the accompanying drawings, which include various details of the embodiments of the present disclosure to assist in understanding, which should be considered as merely exemplary. Therefore, those of ordinary skill in the art should recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Also, in order to be clear and concise, descriptions of well-known functions and structures are omitted in the following description.

[0040] Embodiment 1: As shown in a smart spraying method applied to an unmanned cleaning vehicle, the method comprises: Figure 1

[0041] T1. The unmanned cleaning vehicle drives on the road, real-time acquires dust content data information in the environment based on the vehicle-mounted dust sensor, and real-time acquires environmental humidity data information based on the vehicle-mounted humidity sensor;

[0042] T2. According to the dust content data information in the environment, a cubic polynomial is used to curve fit the relationship between dust content and water spraying flow, and the first water spraying flow data information is output, and according to the environmental humidity data information, a parametric inverse ratio function is used to curve fit the relationship between environmental humidity and water spraying flow, and the second water spraying flow data information is output;

[0043] T3. Based on the first water spraying flow data information and the second water spraying flow data information, a minimum value algorithm is used to output the best water spraying flow data information.

[0044] In this embodiment, in step T3, the minimum value algorithm comprises:

[0045] T31. The unmanned cleaning vehicle drives to the road spraying position, and real-time acquires the first water spraying flow data information and the second water spraying flow data information;

[0046] ​T32. If the water flow in the first water flow data information is greater than the water flow in the second water flow data information, the second water flow data information is selected;

[0047] T33. If the water flow in the first water flow data information is less than the water flow in the second water flow data information, the first water flow data information is selected.

[0048] In this embodiment, if the water flow in the first water flow data information is equal to the water flow in the second water flow data information, the first water flow data information is selected.

[0049] In this embodiment, as shown in Figure 3 The curve fitting of the relationship between the dust content and the water flow by using a cubic polynomial is:

[0050] f(x) = ax 3 + bx 2 + cx + d, where a, b, c, and d are variable coefficients, x is the dust content, and f(x) is the first water flow.

[0051] In this embodiment, as shown in Figure 3 The curve fitting of the relationship between the environmental humidity and the water flow by using a parametric inverse ratio function is:

[0052]

[0053] where a1, b1, c1, and d1 are constant parameters, x is the environmental humidity, and g(x) is the second water flow.

[0054] In this embodiment, according to the dust content and the water flow, a first preset threshold is set, and if the dust content is less than the first preset threshold, the water flow is recorded. According to the environmental humidity and the water flow, a second preset threshold is set, and if the environmental humidity is greater than the second preset threshold, the water flow is recorded.

[0055] Embodiment 2: Based on the intelligent spraying method for unmanned cleaning vehicles in embodiment 1, the present application is further described and explained.

[0056] As shown in Figure 2 To achieve the above-mentioned purposes and other related purposes, the present application provides an intelligent spraying system for unmanned cleaning vehicles, which comprises an unmanned cleaning vehicle 1, a dust sensor 3, a humidity sensor 4, a computing module 6, a control module 7, an electrically controlled adjustable spray head 5, and a deep learning module 2,

[0057] The unmanned sweeper 1 is the carrier of the cleaning intelligent spraying system and is a tool for achieving cleaning operations;

[0058] The dust sensor 3 is used to detect the dust content in the environment during cleaning and transmit the data to the calculation module 6;

[0059] The humidity sensor 4 is used to detect the humidity of the environment during cleaning and transmit the data to the calculation module 6;

[0060] The calculation module 6 receives the data transmitted by the dust sensor 3 and the humidity sensor 4, calculates the water spraying amount by using the set water spraying amount calculation formula, and transmits the information to the control module 7;

[0061] The control module 7 receives the water spraying amount data transmitted by the calculation module and drives the electronically controlled regulating nozzle 5;

[0062] The electronically controlled regulating nozzle 5 is the execution module of the spraying system;

[0063] The deep learning module 2 adjusts the influencing factor coefficient in the water spray volume calculation formula through deep learning.

[0064] In this embodiment, the dust sensor 3 is connected to the calculation module 6 , the humidity sensor 4 is connected to the calculation module 6 , and the calculation module 6 is connected to the control module 7 .

[0065] In this embodiment, the control module 7 is connected to the electrically controlled adjustable nozzle 5 , and the deep learning module 2 is connected to the electrically controlled adjustable nozzle 5 .

[0066] In order to achieve the above-mentioned and other related purposes, the present invention provides a computer-readable storage medium, which stores a computer program programmed or configured to execute any one of the intelligent spraying methods applied to unmanned sweepers.

[0067] Any reference to storage, memory, database or other medium herein can include non-volatile and / or volatile storage. Non-volatile storage can include read-only memory (ROM), programmable ROM (PROM), electronically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile storage can include random-access memory (RAM), or external cache memory. By way of illustration, and not limitation, RAM is available in many forms such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), Synchlink DRAM (SLDRAM), Rambus DRAM (RDRAM), direct Rambus dynamic RAM (DRDRAM), and Rambus dynamic RAM (RDRAM). The disclosure should make it manifestly clear that the scope of the disclosure is made not subject to the RAM types recited herein.

[0068] In summary, the present application not only achieves the purpose of dust suppression when the unmanned sweeper is working, but also improves the cleaning degree and the water usage rate.

[0069] The above detailed description does not constitute a limitation on the protection scope of the present disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent replacements, and improvements within the spirit and principles of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. An intelligent spraying method applied to an unmanned sweeper, characterized in that: The method comprises: T1. The unmanned road sweeper is driving on the road, using the onboard dust sensor to obtain real-time data on the dust content in the environment, and the onboard humidity sensor to obtain real-time data on the ambient humidity. T2. Based on the environmental dust content data, use a cubic polynomial to perform curve fitting on the relationship between dust content and water spray flow rate, and output first water spray flow rate data. Based on the environmental humidity data, use an inverse function with a reference to perform curve fitting on the relationship between environmental humidity and water spray flow rate, and output second water spray flow rate data. T3 based on the first water flow rate data information and the second water flow rate data information, using the minimum algorithm to output the optimal water flow rate data information; In step T2, the relationship between dust content and water spray flow rate is fitted using a cubic polynomial as follows: f(x1)=ax 3 1+bx 2 1+cx1+d, where a, b, c, d are variable coefficients, x1 is the dust content, and f(x1) is the first water spray flow rate; In step T2, the curve fitting of the ambient humidity and the water spray flow rate is performed using an inverse function with a reference: ， Among them, a1, b1, c1, and d1 are constant parameters, x2 is the ambient humidity, and g(x2) is the second water spray flow rate.

2. The intelligent spraying method applied to an unmanned sweeper according to claim 1 is characterized in that: In step T3, the minimum value algorithm includes: T31. The unmanned sweeper drives to the road where spraying is required and obtains the first and second water spray flow data in real time; T32. If the water flow rate in the first water flow rate data information is greater than the water flow rate in the second water flow rate data information, then the second water flow rate data information is selected; T33. If the water spraying flow rate in the first water spraying flow rate data information is smaller than the water spraying flow rate in the second water spraying flow rate data information, the first water spraying flow rate data information is selected.

3. The intelligent spraying method for an unmanned sweeper according to claim 2 is characterized in that: If the water spraying flow rate in the first water spraying flow rate data information is equal to the water spraying flow rate in the second water spraying flow rate data information, the first water spraying flow rate data information is selected.

4. The intelligent spraying method for an unmanned sweeper according to claim 1 is characterized in that: A first preset threshold is set according to the dust content and the water spray flow rate. If the dust content is less than the first preset threshold, the water spray flow rate is recorded. A second preset threshold is set according to the ambient humidity and the water spray flow rate. If the ambient humidity is greater than the second preset threshold, the water spray flow rate is recorded.

5. An intelligent spraying system for an unmanned sweeper, characterized in that: The system is used to implement the intelligent spraying method for an unmanned sweeper according to any one of claims 1 to 4, and includes an unmanned sweeper, a dust sensor, a humidity sensor, a computing module, a control module, an electronically controlled regulating nozzle, and a deep learning module. The unmanned sweeper is the carrier of the cleaning intelligent spraying system and is a tool for achieving cleaning operations; The dust sensor is used to detect the dust content in the environment during cleaning and transmit the data to the calculation module; the humidity sensor is used to detect the humidity of the environment during cleaning and transmit the data to the calculation module; The calculation module receives data transmitted by the dust sensor and the humidity sensor, calculates the water spraying amount according to the set water spraying amount calculation formula, and transmits the information to the control module; The control module receives the water spraying amount data transmitted by the calculation module and drives the electronically controlled regulating nozzle; The electronically controlled regulating nozzle is the execution module of the spraying system; The deep learning module adjusts the influencing factor coefficient in the water spray volume calculation formula through deep learning.

6. The intelligent spraying system for an unmanned sweeper according to claim 5 is characterized in that: The dust sensor is connected to the calculation module, the humidity sensor is connected to the calculation module, and the calculation module is connected to the control module.

7. The intelligent spraying system for an unmanned sweeper according to claim 5 is characterized in that: The control module is connected to the electrically controlled adjustable nozzle, and the deep learning module is connected to the electrically controlled adjustable nozzle.

8. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program that is programmed or configured to execute the intelligent spraying method applied to an unmanned sweeper as described in any one of claims 1 to 4.

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