Automatic cleaning system based on radar of patrol robot in complex dust environment

Abstract

The present invention relates to the field of robot technology, and in particular to an automatic cleaning system for a patrol robot radar based on a complex dust environment, comprising: based on the dust concentration of each sub-area, analyzing the dust complexity of an environmental space waiting to be cleaned, identifying the dust concentration distribution state of the environmental space waiting to be cleaned, setting an analysis period, performing stability analysis on the dust concentration of each sub-area within the analysis period, obtaining a dust dispersion stability value, judging whether the patrol robot needs to clean the environmental space based on the dust dispersion stability value, obtaining the dust concentration of the sub-area that is first in order, and generating a negative pressure power control value when the patrol robot is cleaning with reference to the dust concentration variability. The present invention continuously monitors and analyzes the dust concentration from the spatial and temporal dimensions, determines the changing law of the dust concentration, promptly discovers abnormal fluctuations in the dust concentration, and adjusts the negative pressure power of the patrol robot according to the dust concentration change relationship.

Description

Technical Field

[0001] The present invention relates to the field of robot technology, and in particular to an automatic cleaning system for a patrol robot radar in a complex dust environment. Background Art

[0002] With the continuous development of science and technology, traditional manual inspection methods have problems such as low efficiency, high labor intensity, and many safety hazards. The existing traditional manual inspection methods are increasingly unable to meet the needs of complex industrial systems. The emergence of inspection robots can replace manual inspections of specific areas or equipment, detect potential faults in a timely manner, avoid production accidents and reduce downtime. In complex dusty environments, inspection robots, as important monitoring and maintenance equipment, are playing an increasingly important role in production and life by replacing manual inspections.

[0003] However, when faced with a complex dust environment, the existing technology, on the one hand, lacks analysis of the fluctuations in the ambient dust concentration in the spatial and temporal dimensions, and starts the cleaning operation when the dust concentration is unstable, resulting in poor cleaning effects and wasting resources. It does not ensure that the cleaning operation is performed when the dust concentration is relatively stable. On the other hand, it lacks a method to adjust the power according to the dust concentration in different areas. Either the negative pressure power is set too high, resulting in energy waste, or the cleaning is incomplete due to too low a negative pressure power, and efficient and energy-saving cleaning operations cannot be achieved.

[0004] To this end, we proposed an automatic cleaning system based on a patrol robot radar in complex dust environments. Summary of the invention

[0005] The object of the present invention is to provide an automatic cleaning system for a patrol robot radar in a complex dust environment to solve at least one of the above-mentioned problems of the prior art.

[0006] The present invention provides an automatic cleaning system for a patrol robot radar in a complex dust environment, which specifically includes:

[0007] Data acquisition module: obtains the dust concentration of the sub-area of ​​the dust environment in the spatial dimension;

[0008] Environmental complexity assessment module: Based on the dust concentration in each sub-area, the dust complexity of the environmental space to be cleaned is analyzed, and then the dust concentration distribution state of the environmental space to be cleaned is identified based on the analysis results;

[0009] Cleaning determination module: When a low dust complexity signal is obtained, an analysis period is set, and the dust concentration in each sub-area within the analysis period is analyzed for stability to obtain a dust dispersion stability value. Based on the dust dispersion stability value, it is determined whether the inspection robot needs to clean the environment space;

[0010] Cleaning control module: When a cleaning control instruction is received, the dust concentration of the first sub-area in the order and the reference dust concentration variation rate are obtained, and the negative pressure power control value of the inspection robot during cleaning is generated based on this.

[0011] Beneficial effects of the present invention:

[0012] 1. The present invention obtains the dust concentration of the sub-area of ​​the dust environment in the spatial dimension, analyzes the dust complexity of the environmental space to be cleaned based on the dust concentration of each sub-area, and then identifies the dust concentration distribution state of the environmental space to be cleaned according to the analysis result. The present invention divides the cleaning environment space of the inspection robot into multiple sub-areas, evenly sets dust collection points, and then processes the dust concentration of the collection points at the mean value to obtain the dust concentration of the sub-area. The distribution of dust concentration in the environment can be comprehensively and accurately obtained, providing a reliable data basis for subsequent complexity judgment. Fluctuation analysis based on the dust concentration of the sub-area can clearly distinguish whether the distribution of environmental dust concentration is consistent, help judge the complexity of the environment, and help to plan the operation mode of the inspection robot in a more targeted manner.

[0013] 2. When the present invention obtains a signal of low dust complexity, an analysis period is set, and a stability analysis is performed on the dust concentration in each sub-area within the analysis period to obtain a dust dispersion stability value. Based on the dust dispersion stability value, it is judged whether the inspection robot needs to clean the environmental space; when a cleaning control instruction is obtained, the dust concentration of the sub-area that is first in the order is obtained, and the dust concentration variability is referred to, and the negative pressure power control value of the inspection robot during cleaning is generated accordingly; the present invention avoids starting cleaning too early when the dust concentration fluctuates greatly by judging the stability of the dust concentration in the environmental space in the time dimension, and ensures that the cleaning operation is carried out when the dust concentration is relatively stable. When the cleaning control instruction is obtained, the first sub-area in the order is obtained. The sub-area dust concentration and the reference dust concentration variability can generate a reasonable negative pressure power control value for the inspection robot during cleaning, which is beneficial to adjust the negative pressure power of the inspection robot during cleaning according to the dust concentration in different areas. It not only ensures the cleaning effect, enables the robot to effectively absorb dust according to the actual dust concentration, but also avoids energy waste due to excessive load power, and prevents incomplete cleaning due to too small negative pressure power, thereby realizing efficient and energy-saving cleaning operations, greatly enhancing the intelligence of the inspection robot's cleaning operations and its adaptability to different environments, reducing manual intervention, and improving the level of automation of work, so that the inspection robot can better cope with complex and changeable dust cleaning environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0015] Figure 1 This is a block diagram of an automatic cleaning system for a patrol robot radar in a complex dust environment according to an embodiment of the present invention;

[0016] Figure 2 This is a flow chart of an automatic cleaning method for a patrol robot radar in a complex dust environment according to an embodiment of the present invention;

[0017] Figure 3 It is a schematic diagram of the structure of an automatic cleaning device for a patrol robot radar in a complex dust environment according to an embodiment of the present invention;

[0018] Figure numbers: 3, computer device; 301, processor; 302, memory; 303, computer program. DETAILED DESCRIPTION

[0019] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0020] Embodiment 1

[0021] Figure 1 The block diagram of the automatic cleaning system of the patrol robot radar based on a complex dust environment provided by the embodiment of the present invention is applicable to the situation where the dust concentration changes linearly in the spatial dimension and is stable in the time dimension. The automatic cleaning system of the patrol robot radar based on a complex dust environment can be implemented by software and / or hardware. The automatic cleaning system of the patrol robot radar based on a complex dust environment can be configured in the automatic cleaning device of the patrol robot radar based on a complex dust environment. Optionally, the automatic cleaning device of the patrol robot radar based on a complex dust environment can be an electronic device, which can be a notebook, a desktop computer, a smart tablet, etc., and the embodiment of the present invention does not limit this.

[0022] like Figure 1 As shown, the automatic cleaning system of the patrol robot radar based on complex dust environment provided by the embodiment of the present invention specifically includes the following modules:

[0023] Data acquisition module: obtains the dust concentration of the sub-area of ​​the dust environment in the spatial dimension;

[0024] In some embodiments, the initial position of the inspection robot is taken as the origin, and the environment space where the inspection robot is waiting to be cleaned is divided according to the robot's travel mode to obtain multiple parallel sub-areas, wherein the spatial volume of each sub-area is the same;

[0025] Dust collection points are evenly arranged in the space of each sub-area, and each dust collection point is equipped with a dust sensor to obtain the dust concentration of each collection point, and the dust concentration of all collection points in the sub-area is averaged to obtain the dust concentration of each sub-area;

[0026] Environmental complexity assessment module: Based on the dust concentration in each sub-area, the dust complexity of the environmental space to be cleaned is analyzed, and then the dust concentration distribution state of the environmental space to be cleaned is identified based on the analysis results;

[0027] In some embodiments, based on the concentration of each sub-area, a fluctuation analysis is performed to output an environmental dust complexity judgment value, and then the dust complexity of the space waiting to be cleaned by the inspection robot is evaluated according to the environmental dust complexity judgment value;

[0028] If the environmental dust complexity judgment value is greater than or equal to the environmental dust complexity judgment threshold, it means that the dust concentrations of the various sub-areas are inconsistent, and the dust concentration distribution of the environmental space to be cleaned is inconsistent, generating a dust environment complexity signal;

[0029] If the environmental dust complexity judgment value is less than the environmental dust complexity judgment threshold, it means that the dust concentrations of each sub-area are relatively consistent, and the dust concentration distribution of the environmental space to be cleaned is relatively consistent, generating a simple dust environment signal;

[0030] It should be noted that the environmental dust complexity judgment value is used to characterize the consistency of dust concentration in each sub-area of ​​the environment space waiting to be cleaned. Generating a complex dust environment signal indicates that the dust concentration in each sub-area is inconsistent; generating a simple dust environment signal indicates that the dust concentration in each sub-area is relatively consistent;

[0031] When a complex signal of the dust environment is obtained, a sequence of dust concentrations in different sub-areas is constructed according to the spatial position to obtain a sub-area dust concentration spatial sequence. The spatial concentration linear distribution value is obtained by performing a linear distribution analysis on the sub-area dust concentration spatial sequence; wherein the spatial position is the distance between the center point of the sub-area and the inspection robot;

[0032] If the spatial concentration linear distribution value is less than the spatial concentration linear distribution threshold, the concentration of each sub-area to be cleaned changes linearly with the distance to a high degree, generating a signal with low dust complexity;

[0033] If the spatial concentration linear distribution value is greater than or equal to the spatial concentration linear distribution threshold, the concentration of each sub-area to be cleaned changes linearly with the distance at a low degree, generating a dust complexity high signal;

[0034] First, specifically, based on the concentration of each sub-region, the specific process of outputting the complex judgment value of the environmental dust through fluctuation analysis is:

[0035] Obtain the concentration of each sub-area, and calculate the environmental dust complexity judgment value by using the variance processing formula for the concentration of each sub-area;

[0036] Second, specifically, by performing linear distribution analysis on the dust concentration spatial sequence of the sub-region, the specific process of obtaining the linear distribution value of the spatial concentration is as follows:

[0037] Obtain the dust concentration of the first sub-region and the dust concentration of the first sub-region in the reverse order in the sub-region dust concentration empty sequence; perform difference calculation on the dust concentration of the first sub-region and the dust concentration of the first sub-region in the reverse order to obtain the end dust concentration change value, obtain the distance between the first sub-region and the first sub-region in the reverse order to obtain the end distance difference; perform ratio calculation on the end dust concentration change value and the end distance difference to obtain the reference dust concentration variation rate;

[0038] Obtain the dust concentration of the sub-region located in the previous sequence and the dust concentration of the sub-region located in the next sequence in the sub-region dust concentration empty sequence; perform difference calculation on the dust concentration of the sub-region in the previous sequence and the dust concentration of the sub-region in the next sequence to obtain the adjacent dust concentration change value, obtain the distance of the sub-region between the previous sequence and the next sequence to obtain the adjacent distance difference; perform ratio calculation on the adjacent dust concentration change value and the adjacent distance difference to obtain the dust concentration variability;

[0039] All the analyzed dust concentration variability rates are subjected to difference processing with the reference dust concentration variability rate, and the absolute value of the difference is taken to obtain the analyzed concentration variability deviation value;

[0040] Compare the analytical concentration variability deviation value to the analytical concentration variability deviation threshold:

[0041] If the analysis concentration variability deviation value is greater than or equal to the analysis concentration variability deviation threshold, it means that the dust concentration change trend in the adjacent area is significantly different from the dust concentration change trend in the front and rear end areas, and the analysis dust concentration variability is marked as asynchronous dust concentration variability;

[0042] If the analysis concentration variability deviation value is less than the analysis concentration variability deviation threshold, it means that the dust concentration change trend in the adjacent area is slightly different from the dust concentration change trend in the front and rear end areas, and the analysis dust concentration variability is marked as the synchronous dust concentration variability;

[0043] Count the number of asynchronous dust concentration variability rates, calculate the number ratio of asynchronous dust concentration variability rates, and at the same time, perform difference processing on all asynchronous dust concentration variability rates and reference dust concentration variability rates, and take the absolute value of the difference to obtain the analysis concentration variability deviation value, obtain the asynchronous dust concentration variability deviation value, and calculate the mean of all asynchronous dust concentration variability deviation values ​​to obtain the asynchronous dust concentration variability deviation mean;

[0044] Then, the linear distribution value of spatial concentration is obtained by multiplying the mean value of asynchronous dust concentration variability deviation and the number proportion of asynchronous dust concentration variability.

[0045] It should be noted that the spatial concentration linear distribution value is obtained by processing the data of the asynchronous dust concentration variability mean deviation and the number ratio of asynchronous dust concentration variability. The larger the asynchronous dust concentration variability mean deviation, the greater the difference between the dust concentration change trend in the adjacent area and the dust concentration change trend in the front and rear end areas, and the concentration of each sub-area waiting to be cleaned changes linearly with the change of distance to a lower degree. The larger the number ratio of asynchronous dust concentration variability, the greater the difference between the dust concentration change trend in the adjacent area and the dust concentration change trend in the front and rear end areas, and the concentration of each sub-area waiting to be cleaned changes linearly with the change of distance to a lower degree.

[0046] The technical solution of this embodiment is: obtaining the dust concentration of the sub-area of ​​the dust environment in the spatial dimension, analyzing the dust complexity of the environmental space to be cleaned based on the dust concentration of each sub-area, and then identifying the dust concentration distribution state of the environmental space to be cleaned according to the analysis result. The present invention divides the cleaning environmental space of the inspection robot into multiple sub-areas, evenly sets dust collection points, and then processes the dust concentration of the collection points at the mean value to obtain the dust concentration of the sub-area. It can comprehensively and accurately obtain the distribution of dust concentration in the environment, provide a reliable data basis for subsequent complexity judgment, and perform fluctuation analysis based on the dust concentration of the sub-area. It can clearly distinguish whether the distribution of environmental dust concentration is consistent, help judge the complexity of the environment, and help to plan the operation mode of the inspection robot in a more targeted manner.

[0047] Embodiment 2

[0048] like Figure 1 As shown, the radar automatic cleaning system for patrol robots in complex dusty environments provided by the embodiment of the present invention specifically includes the following modules:

[0049] Cleaning determination module: When a low dust complexity signal is obtained, an analysis period is set, and the dust concentration in each sub-area within the analysis period is analyzed for stability to obtain a dust dispersion stability value. Based on the dust dispersion stability value, it is determined whether the inspection robot needs to clean the environment space;

[0050] In some embodiments, when a dust complexity low signal is obtained, an analysis period is set, the duration of the analysis period is T, the value of T is preset by a person skilled in the art, the end time of the analysis period is the current time, recorded as TD, so the start time of the analysis period is (TD-T);

[0051] Obtain the dust concentration of each sub-area during the analysis period, calculate the variance of all dust concentrations during the analysis period, and obtain the current dust concentration variance of each sub-area;

[0052] Then the current dust concentration variance of all sub-areas is averaged to obtain the dust dispersion stability value;

[0053] comparing the dust dispersion stability value to a dust dispersion stability threshold;

[0054] If the dust dispersion stability value is greater than or equal to the dust dispersion stability threshold, it means that the dust concentration of the environment space waiting to be cleaned still fluctuates in the time dimension during the current time period, and the cleanup execution continues;

[0055] If the dust dispersion stability value is less than the dust dispersion stability threshold, it means that the dust concentration of the environment space to be cleaned tends to be stable in the time dimension during the current time period, and a cleaning control instruction is generated;

[0056] It should be noted that the dust dispersion stability value is used to characterize the fluctuation of dust concentration in the environment space waiting to be cleaned in the time dimension when the dust complexity is low, so as to assist in determining whether to issue a cleaning control instruction;

[0057] Cleaning control module: when receiving the cleaning control instruction, obtain the dust concentration of the first sub-area and the reference dust concentration variation rate, and generate the negative pressure power control value of the inspection robot during cleaning;

[0058] In some embodiments, when a cleaning control instruction is obtained, the dust concentration of the first sub-area is first obtained, and the dust concentration of the first sub-area is substituted into the dust concentration and power curve obtained by fitting, so as to obtain the initial setting value of the negative pressure power when the inspection robot is cleaning;

[0059] By formula , calculate the negative pressure power control value PT of the inspection robot during cleaning;

[0060] The negative pressure power control value is sent to the cleaning device of the inspection robot to control the negative pressure power of the inspection robot during cleaning;

[0061] Among them, P1 represents the initial setting value of the negative pressure power when the inspection robot is cleaning, K represents the reference dust concentration variation rate, and L represents the distance between the sub-area to be regulated by the negative pressure and the sub-area located first in the order;

[0062] The technical solution of this embodiment is as follows: when a signal of low dust complexity is obtained, an analysis period is set, and a stability analysis is performed on the dust concentration in each sub-area within the analysis period to obtain a dust dispersion stability value, and based on the dust dispersion stability value, a judgment is made as to whether the inspection robot needs to clean the environmental space; when a cleaning control instruction is obtained, the dust concentration of the sub-area that is first in the order is obtained, and the reference dust concentration variability is used to generate a negative pressure power control value for the inspection robot during cleaning; the present invention avoids starting cleaning too early when the dust concentration fluctuates greatly by judging the stability of the dust concentration in the environmental space in the time dimension, and ensures that the cleaning operation is carried out when the dust concentration is relatively stable. When a cleaning control instruction is obtained, the order is obtained, and the negative pressure power control value is generated accordingly. The dust concentration in the first sub-area and the reference dust concentration variability can generate a reasonable negative pressure power control value for the inspection robot during cleaning, which is beneficial to adjust the negative pressure power of the inspection robot during cleaning according to the dust concentration in different areas. It not only ensures the cleaning effect, but also enables the robot to effectively absorb dust according to the actual dust concentration. It can also avoid energy waste due to excessive load power, and prevent incomplete cleaning due to too small negative pressure power, thereby realizing efficient and energy-saving cleaning operations, greatly enhancing the intelligence of the inspection robot's cleaning operations and its adaptability to different environments, reducing manual intervention, and improving the level of automation of work, so that the inspection robot can better cope with complex and changeable dust cleaning environments.

[0063] Embodiment three:

[0064] like Figure 2 As shown, the automatic cleaning method of the radar of the inspection robot based on a complex dust environment provided by the embodiment of the present invention specifically includes:

[0065] Step 1: Obtain the dust concentration of the sub-area of ​​the dust environment in the spatial dimension;

[0066] Step 2: Based on the dust concentration of each sub-area, analyze the dust complexity of the environment space to be cleaned, and then identify the dust concentration distribution state of the environment space to be cleaned according to the analysis results;

[0067] Step 3: When a signal indicating a low dust complexity is obtained, an analysis period is set, and a stability analysis is performed on the dust concentration in each sub-area during the analysis period to obtain a dust dispersion stability value. Based on the dust dispersion stability value, a judgment is made as to whether the inspection robot needs to clean the environment space.

[0068] Step 4: When a cleaning control instruction is received, the dust concentration of the first sub-area and the reference dust concentration variation rate are obtained, and the negative pressure power control value of the inspection robot during cleaning is generated accordingly.

[0069] Embodiment 4

[0070] Reference Figure 3 The embodiment of the present invention further provides a computer device 3, comprising: a memory 302 and a processor 301 and a computer program 303 stored in the memory 302. When the computer program 303 is executed on the processor 301, an automatic cleaning system for a patrol robot radar in a complex dust environment as described in any one of the above systems is implemented.

[0071] The computer device 3 may be a computing device such as a desktop computer, a notebook, a PDA, or a cloud server. The computer device 3 may include, but is not limited to, a processor 301 and a memory 302. Those skilled in the art will appreciate that Figure 3 It is only an example of computer device 3 and does not constitute a limitation on computer device 3. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components, for example, it may also include input and output devices, network access devices, etc.

[0072] The processor 301 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0073] In some embodiments, the memory 302 may be an internal storage unit of the computer device 3, such as a hard disk or memory of the computer device 3. In other embodiments, the memory 302 may also be an external storage device of the computer device 3, such as a plug-in hard disk, a smart memory card (SmartMediaCard, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on the computer device 3. Further, the memory 302 may also include both an internal storage unit of the computer device 3 and an external storage device. The memory 302 is used to store an operating system, an application program, a boot loader (BootLoader), data, and other programs, such as the program code of the computer program, etc. The memory 302 may also be used to temporarily store data that has been output or is to be output.

[0074] Embodiment 5

[0075] An embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the automatic cleaning system based on a patrol robot radar in a complex dust environment as described in any of the above-mentioned systems is implemented.

[0076] In this embodiment, if the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application implements all or part of the processes in the above-mentioned embodiment method, which can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, the steps of the above-mentioned various method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium can at least include: any entity or device that can carry the computer program code to the camera / terminal device, recording medium, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, RandomAccess Memory), electric carrier signal, telecommunication signal and software distribution medium. For example, USB flash drive, mobile hard disk, disk or optical disk. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electric carrier signals and telecommunication signals.

[0077] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0078] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0079] In the embodiments disclosed in the present application, it should be understood that the disclosed devices / terminal equipment and methods can be implemented in other ways. For example, the device / terminal equipment embodiments described above are only schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0080] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0081] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0082] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. Based on the complex dust environment inspection robot radar automatic cleaning system, it is characterized by: include: Data acquisition module: obtains the dust concentration of the sub-area of ​​the dust environment in the spatial dimension; Environmental complexity assessment module: Based on the dust concentration in each sub-area, the dust complexity of the environmental space to be cleaned is analyzed, and then the dust concentration distribution state of the environmental space to be cleaned is identified based on the analysis results; The specific process of identifying the dust concentration distribution state of the environmental space to be cleaned is: When a complex signal of the dust environment is obtained, a sequence of dust concentrations in different sub-areas is constructed according to the spatial position to obtain a sub-area dust concentration spatial sequence. The spatial concentration linear distribution value is obtained by performing a linear distribution analysis on the sub-area dust concentration spatial sequence; wherein the spatial position is the distance between the center point of the sub-area and the inspection robot; If the spatial concentration linear distribution value is less than the spatial concentration linear distribution threshold, the concentration of each sub-area to be cleaned changes linearly with the distance to a high degree, generating a signal with low dust complexity; The specific process of obtaining the linear distribution value of the spatial concentration by performing linear distribution analysis on the dust concentration space sequence of the sub-region is as follows: Obtaining the sub-region dust concentration in the sub-region dust concentration empty sequence, determining the reference dust concentration variability and analyzing the dust concentration variability; Based on the reference dust concentration variability and the analytical dust concentration variability, the mean deviation of the asynchronous dust concentration variability and the proportion of the number of asynchronous dust concentration variability are analyzed; The linear distribution value of spatial concentration is obtained by multiplying the mean value of asynchronous dust concentration variability deviation and the number proportion of asynchronous dust concentration variability. Cleaning determination module: When a low dust complexity signal is obtained, an analysis period is set, and the dust concentration in each sub-area within the analysis period is analyzed for stability to obtain a dust dispersion stability value. Based on the dust dispersion stability value, it is determined whether the inspection robot needs to clean the environment space; Cleaning control module: When a cleaning control instruction is received, the dust concentration of the first sub-area in the order and the reference dust concentration variation rate are obtained, and the negative pressure power control value of the inspection robot during cleaning is generated based on this.

2. The automatic cleaning system of the patrol robot radar based on complex dust environment according to claim 1 is characterized in that: The dust concentration of the sub-area is obtained as follows: Taking the initial position of the inspection robot as the origin, the environment space where the inspection robot is waiting to be cleaned is divided according to the robot's movement mode to obtain multiple parallel sub-areas, wherein the spatial volume of each sub-area is the same; Dust collection points are evenly arranged in the space of each sub-area, and each dust collection point is equipped with a dust sensor to obtain the dust concentration of each collection point. The dust concentrations of all collection points in the sub-area are averaged to obtain the dust concentration of each sub-area.

3. The automatic cleaning system of the patrol robot radar in a complex dust environment according to claim 2 is characterized in that: The specific process of analyzing the dust complexity of the environment space to be cleaned is as follows: Based on the concentration of each sub-area, the environmental dust complexity judgment value is output through fluctuation analysis, and then the dust complexity of the space waiting to be cleaned by the inspection robot is evaluated according to the environmental dust complexity judgment value; If the environmental dust complexity judgment value is greater than or equal to the environmental dust complexity judgment threshold, it means that the dust concentrations of various sub-areas are inconsistent, and the dust concentration distribution of the environmental space to be cleaned is inconsistent, generating a dust environment complexity signal.

4. The automatic cleaning system of the patrol robot radar in a complex dust environment according to claim 3 is characterized in that: The specific process of the environmental dust complex judgment value is as follows: The concentration of each sub-area is obtained, and the concentration of each sub-area is processed through the variance processing formula to calculate the environmental dust complexity judgment value.

5. The automatic cleaning system of the patrol robot radar based on complex dust environment according to claim 4 is characterized in that: The specific process of determining the reference dust concentration variability and analyzing the dust concentration variability is as follows: Obtain the dust concentration of the first sub-region and the dust concentration of the first sub-region in the reverse order in the sub-region dust concentration empty sequence; perform difference calculation on the dust concentration of the first sub-region and the dust concentration of the first sub-region in the reverse order to obtain the end dust concentration change value, obtain the distance between the first sub-region and the first sub-region in the reverse order to obtain the end distance difference; perform ratio calculation on the end dust concentration change value and the end distance difference to obtain the reference dust concentration variation rate; Obtain the dust concentration of the sub-region located in the previous sequence and the dust concentration of the sub-region located in the next sequence in the sub-region dust concentration empty sequence; perform difference calculation on the dust concentration of the sub-region in the previous sequence and the dust concentration of the sub-region in the next sequence to obtain the adjacent dust concentration change value, obtain the distance of the sub-region between the previous sequence and the next sequence to obtain the adjacent distance difference; perform ratio calculation on the adjacent dust concentration change value and the adjacent distance difference to obtain the dust concentration variability.

6. The automatic cleaning system of the patrol robot radar in a complex dust environment according to claim 5 is characterized in that: The method for obtaining the asynchronous dust concentration variability mean deviation and the number ratio of the asynchronous dust concentration variability is as follows: All the analyzed dust concentration variability rates are respectively subjected to difference processing with the reference dust concentration variability rate, and the absolute value of the difference is taken to obtain the analyzed concentration variability deviation value; If the analysis concentration variability deviation value is greater than or equal to the analysis concentration variability deviation threshold, it means that the dust concentration change trend in the adjacent area is significantly different from the dust concentration change trend in the front and rear end areas, and the analysis dust concentration variability is marked as asynchronous dust concentration variability; Count the number of asynchronous dust concentration variability rates and calculate the proportion of the number of asynchronous dust concentration variability rates. At the same time, perform difference processing on all asynchronous dust concentration variability rates and the reference dust concentration variability rate, and take the absolute value of the difference to obtain the analysis concentration variability deviation value, obtain the asynchronous dust concentration variability deviation value, and calculate the mean of all asynchronous dust concentration variability deviation values ​​to obtain the asynchronous dust concentration variability deviation mean.

7. The automatic cleaning system of the patrol robot radar in a complex dust environment according to claim 1 is characterized in that: The dust dispersion stability value is obtained as follows: Obtain the dust concentration of each sub-area during the analysis period, calculate the variance of all dust concentrations during the analysis period, and obtain the current dust concentration variance of each sub-area; Then the current dust concentration variance of all sub-areas is averaged to obtain the dust dispersion stability value; If the dust dispersion stability value is less than the dust dispersion stability threshold, it means that the dust concentration of the environment space to be cleaned tends to be stable in the time dimension during the current time period, and a cleaning control instruction is generated.

8. The automatic cleaning system of the patrol robot radar in a complex dust environment according to claim 7 is characterized in that: The process of obtaining the negative pressure power control value is as follows: When a cleaning control instruction is obtained, the dust concentration of the first sub-area is obtained, and the dust concentration of the first sub-area is substituted into the dust concentration and power curve obtained by fitting to obtain the initial setting value of the negative pressure power when the inspection robot is cleaning; The negative pressure power control value PT of the inspection robot during cleaning is calculated by the formula, where P1 represents the initial setting value of the negative pressure power during cleaning of the inspection robot, K represents the reference dust concentration variation rate, and L represents the distance between the sub-area to be regulated by the negative pressure and the sub-area located first in the order.

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