Automatic cleaning and detecting method and equipment for elevated sound insulation wall

Abstract

The invention provides an automatic cleaning and detecting method and device for elevated sound insulation walls, and belongs to the technical field of cleaning equipment. The method specifically comprises the steps that cleaning treatment is conducted on the elevated sound insulation walls of different groups with similar smudginess states according to preset flow; and determining cleaning flows of different groups with similar dirty states by using the cleaning states of the elevated sound insulation walls with the cleaning state detection lengths until the cleaning states of the elevated sound insulation walls with the cleaning state detection lengths of the groups with similar dirty states are obtained. Cleaning the elevated sound insulation walls of different groups with similar dirty states on the basis of the cleaning flow of the groups with similar dirty states, and dynamically adjusting the cleaning flow of the groups with similar dirty states according to the detection result of the cleaning states of the cleaned elevated sound insulation walls. And the cleaning treatment efficiency of the elevated sound insulation wall is ensured.

Description

Technical Field

[0001] The invention belongs to the technical field of cleaning equipment, and in particular relates to an automatic cleaning detection method and equipment for an elevated sound insulation wall. Background Art

[0002] In order to reduce the impact of elevated vehicle noise on residents, the installation of elevated sound insulation walls can greatly achieve sound insulation and noise reduction of noise sources, but at the same time, how to clean the sound insulation walls has become a technical problem that needs to be solved urgently.

[0003] Specifically, in the invention patent application CN202210387639.4 "A sound insulation board cleaning device", before brushing and cleaning the cleaning board, the sound insulation board is firstly scraped and the dust is collected so that it can be moved on a longer sound insulation board. However, it is not difficult to find the following technical problems through analysis: When cleaning elevated sound insulation walls, since the water carrying capacity of the cleaning equipment is limited, if the same cleaning flow rate is used for elevated sound insulation walls in different cleaning states, the cleaning efficiency of the elevated sound insulation walls will inevitably be slowed down.

[0004] In view of the above technical problems, the present invention provides an automatic cleaning detection method and equipment for an elevated sound insulation wall. Summary of the invention

[0005] To achieve the purpose of the present invention, the present invention adopts the following technical solutions: According to one aspect of the present invention, a method for automatically cleaning and detecting an elevated sound insulation wall is provided.

[0006] An automatic cleaning and detection method for an elevated sound insulation wall, specifically comprising: S1 divides the elevated sound insulation wall into multiple groups with similar dirtiness status based on the historical traffic volume of the elevated lane corresponding to the elevated sound insulation wall; S2 obtains the distribution data and length of elevated sound insulation walls of different similar groups of dirty states, and determines the clean state detection length of different similar groups of dirty states in combination with the historical traffic flow of elevated lanes corresponding to the different similar groups of dirty states; S3 performs cleaning processing of elevated sound insulation walls of different similar groups of dirty states according to preset flow rates until the cleaning state of the elevated sound insulation walls of the similar groups of dirty states of the cleaning state detection length is obtained, and the cleaning flow rates of different similar groups of dirty states of the cleaning state are determined by using the cleaning state of the elevated sound insulation walls of the cleaning state detection length; S4 performs cleaning treatment of elevated sound insulation walls of different similar dirty state groups based on the cleaning flow rates of the similar dirty state groups, and dynamically adjusts the cleaning flow rates of the similar dirty state groups according to the detection results of the cleaning state of the elevated sound insulation walls after the cleaning treatment.

[0007] A further technical solution is that the historical vehicle flow is determined based on the analysis results of the monitoring data of the monitoring device of the elevated lane.

[0008] A further technical solution is to divide the elevated sound insulation walls into multiple groups with similar dirtiness, including: Based on the historical traffic volume, determine the deviation of the historical traffic volume between different elevated noise barriers on different dates; Determine the deviation date of traffic flow between different elevated noise insulation walls according to the deviation of historical traffic flow on different dates; The traffic flow similarity coefficients between different elevated sound insulation walls are determined based on the number of traffic flow deviation dates, and the elevated sound insulation walls are divided into a plurality of similar dirtiness status groups according to the traffic flow similarity coefficients.

[0009] A further technical solution is to divide the elevated sound insulation wall into a plurality of similar dirty status groups according to the vehicle flow similarity coefficient, specifically including: Elevated sound insulation walls whose traffic flow similarity coefficients are greater than a preset similarity coefficient are classified into the same similarity group of dirtiness.

[0010] A further technical solution is that the preset flow rate is determined according to the clean length of the elevated sound insulation wall, wherein the longer the clean length of the elevated sound insulation wall is, the smaller the preset flow rate is.

[0011] A further technical solution is that the method for determining the cleaning flow rate of the group with similar dirtiness status is: Determining the length of the elevated sound insulation wall in different cleaning state intervals based on the detection result of the cleaning state of the elevated sound insulation wall of the cleaning state detection length; Determine the matching cleaning flow rates corresponding to different cleaning state intervals, and determine the weight values ​​of the matching cleaning flow rates in different cleaning state intervals according to the length ratios of the elevated sound insulation walls in different cleaning state intervals; The cleaning flow of the group with similar dirty states is determined based on the matching cleaning flow of the elevated sound insulation wall in different cleaning state intervals and the weight value of the matching cleaning flow.

[0012] A further technical solution is that the cleaning status of the elevated sound insulation wall is determined based on the analysis results of the monitoring image of the cleaning equipment of the elevated sound insulation wall.

[0013] On the other hand, the present application provides an elevated sound insulation wall automatic cleaning detection device, which adopts the above-mentioned elevated sound insulation wall automatic cleaning detection method, specifically comprising: Group division module, detection length determination module, cleaning flow determination module, flow adjustment module; The group division module is responsible for dividing the elevated sound insulation wall into a plurality of groups with similar dirtiness status based on the historical traffic volume of the elevated lane corresponding to the elevated sound insulation wall; The detection length determination module is responsible for obtaining the distribution data and lengths of elevated sound insulation walls with similar different dirty states, and determining the clean state detection lengths of different dirty state similar groups in combination with the historical traffic flow of elevated lanes corresponding to different dirty state similar groups; The cleaning flow determination module is responsible for performing cleaning processing on elevated sound insulation walls of different similar groups of dirty states according to preset flow rates until the cleaning state of the elevated sound insulation walls of the similar groups of dirty states of the cleaning state detection length is obtained, and the cleaning flow rates of different similar groups of dirty states of the cleaning state are determined by using the cleaning state of the elevated sound insulation walls of the cleaning state detection length; The flow adjustment module is responsible for cleaning the elevated sound insulation walls of different groups with similar dirty states based on the cleaning flow of the groups with similar dirty states, and dynamically adjusting the cleaning flow of the groups with similar dirty states according to the detection results of the cleaning state of the elevated sound insulation walls after the cleaning treatment.

[0014] The beneficial effects of the present invention are: 1. In the present invention, the cleaning state of the elevated sound insulation wall is used to determine the cleaning flow of similar groups with different dirty states, thereby realizing dynamic adjustment of the cleaning flow of similar groups with different dirty states from the perspective of the cleaning state of the elevated sound insulation wall, avoiding the technical problem of excessive water consumption and slow cleaning efficiency due to the use of the same cleaning flow, while also ensuring the cleaning effect of the elevated sound insulation wall.

[0015] 2. In the present invention, the cleaning flow rate of the group with similar dirtiness is dynamically adjusted according to the detection result of the cleaning state of the elevated sound insulation wall after cleaning treatment, thereby avoiding the technical problem that the cleaning result of the elevated sound insulation wall cannot meet the requirements due to the use of a fixed cleaning flow rate. By dynamically adjusting the cleaning flow rate according to the detection result of the cleaning state, the reliability of the cleaning effect of the elevated sound insulation wall is further improved on the basis of avoiding excessive use of water.

[0016] Other features and advantages will be described in the following description. The objects and other advantages of the present invention are realized and obtained by the structures particularly pointed out in the description and drawings.

[0017] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The above and other features and advantages of the present invention will become more apparent by describing in detail exemplary embodiments thereof with reference to the accompanying drawings; Figure 1 It is a flow chart of an automatic cleaning and detection method for an elevated sound insulation wall; Figure 2 is a flow chart of a method for determining a clean state detection length for a dirty state similar group; Figure 3 is a flow chart of a method for determining a cleaning flow rate for a group with similar dirtiness status; Figure 4 It is a framework diagram of an automatic cleaning and testing device for an elevated sound insulation wall. DETAILED DESCRIPTION

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

[0020] When cleaning elevated sound insulation walls, since the water carrying capacity of the cleaning equipment is limited, different cleaning flow rates need to be adopted according to the elevated sound insulation walls in different cleaning states, so as to improve the efficiency of the cleaning process while ensuring the cleaning reliability of the elevated sound insulation walls.

[0021] Dirt status similar group: determined by the sum of historical vehicle flows within a preset time period, and elevated sound insulation walls with a deviation of the sum of historical vehicle flows within 100 vehicles are divided into the same dirt status similar group.

[0022] Clean state detection length of groups with similar dirty states: The detection ratio of different elevated sound insulation walls is determined by using the historical traffic volume, and the clean state detection length of groups with similar dirty states is determined by multiplying the detection ratio by the length.

[0023] Cleaning flow rate: the cleaning flow rate is determined according to the proportion of the deviation in the cleaning state of the elevated sound insulation wall within the cleaning state detection length. Specifically, when the proportion of the deviation in the cleaning state is 10%, the cleaning flow rate is the preset flow rate multiplied by 1.1.

[0024] Dynamically adjust the cleaning flow of groups with similar dirty states: Determine the proportion of deviation in the cleaning state based on the detection results of the cleaning state of the elevated sound insulation wall after cleaning. When the proportion of deviation in the cleaning state is greater than 5%, it is determined that dynamic adjustment of the cleaning flow of groups with similar dirty states is required.

[0025] Embodiment 1 To solve the above-mentioned problem, according to one aspect of the present invention, Figure 1 As shown, a method for automatic cleaning and detection of elevated sound insulation walls is provided, which specifically includes: S1 divides the elevated sound insulation wall into multiple groups with similar dirtiness status based on the historical traffic volume of the elevated lane corresponding to the elevated sound insulation wall; S2 obtains the distribution data and length of elevated sound insulation walls of different similar groups of dirty states, and determines the clean state detection length of different similar groups of dirty states in combination with the historical traffic flow of elevated lanes corresponding to the different similar groups of dirty states; S3 performs cleaning processing of elevated sound insulation walls of different similar groups of dirty states according to preset flow rates until the cleaning state of the elevated sound insulation walls of the similar groups of dirty states of the cleaning state detection length is obtained, and the cleaning flow rates of different similar groups of dirty states of the cleaning state are determined by using the cleaning state of the elevated sound insulation walls of the cleaning state detection length; S4 performs cleaning treatment of elevated sound insulation walls of different similar dirty state groups based on the cleaning flow rates of the similar dirty state groups, and dynamically adjusts the cleaning flow rates of the similar dirty state groups according to the detection results of the cleaning state of the elevated sound insulation walls after the cleaning treatment.

[0026] Furthermore, the historical vehicle flow is determined based on the analysis results of the monitoring data of the monitoring device of the elevated lane.

[0027] Specifically, the elevated sound insulation walls are divided into multiple groups with similar dirtiness, including: Based on the historical traffic volume, determine the deviation of the historical traffic volume between different elevated noise barriers on different dates; Determine the deviation date of traffic flow between different elevated noise insulation walls according to the deviation of historical traffic flow on different dates; The traffic flow similarity coefficients between different elevated sound insulation walls are determined based on the number of traffic flow deviation dates, and the elevated sound insulation walls are divided into a plurality of similar dirtiness status groups according to the traffic flow similarity coefficients.

[0028] It can be understood that the elevated sound insulation wall is divided into a plurality of similar dirty status groups according to the vehicle flow similarity coefficient, specifically including: Elevated sound insulation walls whose traffic flow similarity coefficients are greater than a preset similarity coefficient are classified into the same similarity group of dirtiness.

[0029] It should also be noted that the elevated sound insulation walls are divided into several groups with similar dirtiness, including: Based on the historical traffic volume, the deviation of the historical traffic volume between different elevated sound insulation walls on different dates is determined, and the deviation of the traffic volume between different elevated sound insulation walls on different dates is determined by using the deviation; Determine the date similarity coefficients between different elevated sound insulation walls on different dates according to the vehicle flow deviation, and determine the vehicle flow similarity coefficients between different elevated sound insulation walls by averaging the date similarity coefficients on different dates; The elevated sound insulation wall is divided into a plurality of groups with similar dirtiness states according to the vehicle flow similarity coefficient.

[0030] It should also be noted that the elevated sound insulation walls are divided into several groups with similar dirtiness, including: S11 determines the deviation of the average daily traffic volume between different elevated sound insulation walls based on the historical traffic volume, and judges whether the deviation of the average daily traffic volume between the elevated sound insulation walls meets the requirement. If so, proceed to the next step; if not, determine that the elevated sound insulation walls do not belong to the same dirty state similar group; S12 determines the deviation of historical vehicle flow between different elevated sound insulation walls on different dates, and uses the deviation to determine the deviation of vehicle flow between different elevated sound insulation walls on different dates, and determines whether there are similar vehicle flow dates between the elevated sound insulation walls by using the vehicle flow deviation. If yes, proceed to the next step, if not, proceed to step S15; S13 determines whether the number of similar traffic flow dates is greater than the preset number of dates. If so, it is determined that the elevated sound insulation wall belongs to the same similar dirty state group. If not, proceed to the next step. S14 obtains the number and proportion of the traffic flow similar dates, and determines the similarity coefficient evaluation amount between the elevated sound insulation walls in combination with the traffic flow deviation amount of different traffic flow similar dates, and judges whether the similarity coefficient evaluation amount meets the requirements. If so, it is determined that the elevated sound insulation walls belong to the same dirty state similar group, if not, proceeds to the next step; S15 determines the date similarity coefficients between different elevated sound insulation walls on different dates according to the vehicle flow deviation, and judges whether the number of dates with date similarity coefficients less than a preset coefficient threshold meets the requirement. If so, it is determined that the elevated sound insulation walls belong to the same dirty state similarity group. If not, proceed to the next step. S16 determines the traffic flow similarity coefficients between different elevated sound insulation walls by using the average values ​​of the date similarity coefficients on different dates and the similarity coefficient evaluation values ​​between the elevated sound insulation walls, and divides the elevated sound insulation walls into a plurality of similar dirtiness status groups by using the traffic flow similarity coefficients.

[0031] Furthermore, the historical traffic volume of the elevated lane corresponding to the similar dirty state group is determined according to the average value of the historical traffic volume of the elevated sound insulation wall in the similar dirty state group.

[0032] Specifically, Figure 2 As shown, the method for determining the cleaning state detection length of the dirty state similar group is: Determine a benchmark detection ratio of the dirty state similar group by using the historical vehicle flow of the elevated lane corresponding to the dirty state similar group; Divide the elevated sound insulation walls whose distances are within a preset distance interval into the same clean area, and determine the dirtiness state discrete coefficient of the elevated sound insulation walls by using the lengths of the elevated sound insulation walls in different clean areas and the distances between different adjacent clean areas; The clean state detection ratio of the dirty state similar group is determined by using the dirty state discrete coefficient and the reference detection ratio, and the clean state detection length of the dirty state similar group is determined according to the clean state detection ratio and the length of the elevated sound insulation wall in the dirty state similar group.

[0033] Further, the cleaning state detection ratio of the dirty state similar group is determined by using the dirt state discrete coefficient and the reference detection ratio, specifically including: The preset compensation detection ratio corresponding to the dirt state discrete coefficient is determined according to the dirt state discrete coefficient, and the cleaning state detection ratio of the dirt state similar group is determined by using the sum of the preset compensation detection ratio and the reference detection ratio.

[0034] It should also be noted that the method for determining the cleaning state detection length of the dirty state similar group is: Determine the traffic busy coefficient of the dirty state similar group by using the historical traffic flow of the elevated lane corresponding to the dirty state similar group; Determine the average spacing distance between adjacent elevated sound insulation walls according to the distribution of the elevated sound insulation walls, and determine the distribution dispersion coefficient between the elevated sound insulation walls using the average spacing distance; The clean state detection ratio of the dirty state similar group is determined by the product of the distribution dispersion coefficient and the traffic flow busy coefficient, and the clean state detection length of the dirty state similar group is determined according to the clean state detection ratio and the length of the elevated sound insulation wall in the dirty state similar group.

[0035] It should also be noted that the method for determining the cleaning state detection length of the dirty state similar group is: S21 determines the traffic busy coefficient of the dirty state similar group using the historical traffic flow of the elevated lane corresponding to the dirty state similar group, and judges whether the traffic busy coefficient of the dirty state similar group is greater than the preset busy coefficient. If so, determines the clean state detection length of the dirty state similar group according to the preset detection ratio and the length of the elevated sound insulation wall in the dirty state similar group. If not, proceeds to the next step. S22 divides the elevated sound insulation walls whose distances are within a preset distance interval into the same cleaning area, and determines whether the number of the cleaning areas is greater than the preset number of cleaning areas. If so, proceed to the next step; if not, proceed to step S25; S23 determines whether the average distance between different adjacent cleaning areas is greater than a preset distance threshold, if so, proceeds to the next step, if not, proceeds to step S25; S24: The cleaning areas whose distance from the elevated sound insulation wall is greater than the preset distance are used as the screening cleaning areas, and it is determined whether the number of the screening cleaning areas is greater than the preset number of areas. If so, the cleaning state detection length of the dirty state similar group is determined according to the preset detection ratio and the length of the elevated sound insulation wall in the dirty state similar group. If not, proceed to the next step. S25 determines the dirtiness state discrete coefficient of the elevated sound insulation wall by utilizing the length of the elevated sound insulation wall in different cleaning areas and the distance between different adjacent cleaning areas, determines the cleaning state detection ratio of the dirty state similar group by multiplying the dirty state discrete coefficient by the traffic busy coefficient, and determines the cleaning state detection length of the dirty state similar group according to the cleaning state detection ratio and the length of the elevated sound insulation wall in the dirty state similar group.

[0036] Furthermore, the preset flow rate is determined according to the clean length of the elevated sound insulation wall, wherein the longer the clean length of the elevated sound insulation wall is, the smaller the preset flow rate is.

[0037] Specifically, Figure 3 As shown, the method for determining the cleaning flow rate of the group with similar dirtiness status is: Determining the length of the elevated sound insulation wall in different cleaning state intervals based on the detection result of the cleaning state of the elevated sound insulation wall of the cleaning state detection length; Determine the matching cleaning flow rates corresponding to different cleaning state intervals, and determine the weight values ​​of the matching cleaning flow rates in different cleaning state intervals according to the length ratios of the elevated sound insulation walls in different cleaning state intervals; The cleaning flow of the group with similar dirty states is determined based on the matching cleaning flow of the elevated sound insulation wall in different cleaning state intervals and the weight value of the matching cleaning flow.

[0038] It should be further explained that the method for determining the cleaning flow rate of the group with similar dirtiness status is: Determining the length of the elevated sound insulation wall in different cleaning state intervals based on the detection result of the cleaning state of the elevated sound insulation wall of the cleaning state detection length; Determine the matching cleaning flow rates corresponding to different cleaning state intervals, and determine the weight values ​​of the matching cleaning flow rates in different cleaning state intervals according to the length ratios of the elevated sound insulation walls in different cleaning state intervals; The cleaning flow of the group with similar dirty states is determined based on the matching cleaning flow of the elevated sound insulation wall in different cleaning state intervals and the weight value of the matching cleaning flow.

[0039] Furthermore, the cleaning status of the elevated sound insulation wall is determined based on the analysis results of the monitoring images of the cleaning equipment of the elevated sound insulation wall.

[0040] It should be further explained that the method for determining the cleaning flow rate of the group with similar dirtiness status is: S31 determines whether there is an elevated sound insulation wall whose cleaning state does not meet the requirements based on the detection result of the cleaning state of the elevated sound insulation wall of the cleaning state detection length, if yes, proceed to the next step, if not, proceed to step S35; S32 regards the elevated sound insulation wall whose cleaning state does not meet the requirements as the sound insulation wall with abnormal cleaning state, and determines whether the length of the sound insulation wall with abnormal cleaning state of the similar dirty state group meets the requirements. If so, proceed to the next step; if not, determine the cleaning flow rate of the similar dirty state group using the preset cleaning flow rate; S33 determines the interval distance between adjacent sound insulation walls with abnormal cleaning status based on the distribution data of the sound insulation walls with abnormal cleaning status, and determines the interval discrete coefficient of the sound insulation walls with abnormal cleaning status based on the interval distance between adjacent sound insulation walls with abnormal cleaning status, and judges whether the interval discrete coefficient of the sound insulation walls with abnormal cleaning status meets the requirements, if so, proceeds to the next step, if not, determines the cleaning flow rate of the group with similar dirty status based on the preset cleaning flow rate; S34 determines the length of the elevated sound insulation wall in different cleaning state intervals based on the detection result of the cleaning state of the elevated sound insulation wall of the cleaning state detection length, and judges whether there is a cleaning state interval in which the length ratio of the elevated sound insulation wall is greater than the preset length ratio. If so, the cleaning flow rate of the dirty state similar group is determined by using the matching cleaning flow rate corresponding to the cleaning state interval in which the length ratio is greater than the preset length ratio. If not, proceed to the next step. S35 determines the matching cleaning flow corresponding to different cleaning status intervals, and determines the weight value of the matching cleaning flow in different cleaning status intervals according to the length ratio of the elevated sound insulation wall in different cleaning status intervals, and determines the cleaning flow of the group with similar dirty status based on the matching cleaning flow of the elevated sound insulation wall in different cleaning status intervals and the weight value of the matching cleaning flow.

[0041] Furthermore, the cleaning flow rate of the groups with similar dirtiness is dynamically adjusted, specifically including: Using the cleaning status detection result of the elevated sound insulation wall after cleaning, it is determined whether there is an elevated sound insulation wall with abnormal cleaning status, if so, proceed to the next step, if not, it is determined that there is no need to dynamically adjust the cleaning flow rate of the group with similar dirty status; Determine the elevated sound insulation wall with abnormal cleaning status in different detection time periods, and use it as the abnormal cleaning sound insulation wall, and judge whether the length of the abnormal cleaning sound insulation wall meets the requirements. If so, proceed to the next step. If not, dynamically adjust the cleaning flow of the group with similar dirt status by using the preset cleaning flow compensation amount; Obtain the number of detection periods for the cleaning abnormal sound insulation wall, determine whether the number of detection periods for the cleaning abnormal sound insulation wall meets the requirement, if so, proceed to the next step, if not, dynamically adjust the cleaning flow of the group with similar dirtiness status by using a preset cleaning flow compensation amount; Based on the length of the cleaning abnormal sound insulation wall in different detection periods, the detection period in which the length of the cleaning abnormal sound insulation wall is greater than the preset length threshold is determined, and it is judged whether the number of detection periods in which the length of the cleaning abnormal sound insulation wall is greater than the preset length threshold meets the requirement. If so, proceed to the next step; if not, dynamically adjust the cleaning flow of the group with similar dirtiness status by using the preset cleaning flow compensation amount; Based on the length of the cleaning process abnormal sound insulation wall in different detection periods, the cleaning effect abnormality coefficient is determined, and according to the cleaning effect abnormality coefficient, it is determined whether it is necessary to dynamically adjust the cleaning flow rate of the group with similar dirtiness status.

[0042] Embodiment 2 On the other hand, as Figure 4As shown, the present application provides an elevated sound insulation wall automatic cleaning detection device, which adopts the above-mentioned elevated sound insulation wall automatic cleaning detection method, specifically including: Group division module, detection length determination module, cleaning flow determination module, flow adjustment module; The group division module is responsible for dividing the elevated sound insulation wall into a plurality of groups with similar dirtiness status based on the historical traffic volume of the elevated lane corresponding to the elevated sound insulation wall; The detection length determination module is responsible for obtaining the distribution data and lengths of elevated sound insulation walls with similar different dirty states, and determining the clean state detection lengths of different dirty state similar groups in combination with the historical traffic flow of elevated lanes corresponding to different dirty state similar groups; The cleaning flow determination module is responsible for performing cleaning processing on elevated sound insulation walls of different similar groups of dirty states according to preset flow rates until the cleaning state of the elevated sound insulation walls of the similar groups of dirty states of the cleaning state detection length is obtained, and the cleaning flow rates of different similar groups of dirty states of the cleaning state are determined by using the cleaning state of the elevated sound insulation walls of the cleaning state detection length; The flow adjustment module is responsible for cleaning the elevated sound insulation walls of different groups with similar dirty states based on the cleaning flow of the groups with similar dirty states, and dynamically adjusting the cleaning flow of the groups with similar dirty states according to the detection results of the cleaning state of the elevated sound insulation walls after the cleaning treatment.

[0043] Based on the above embodiments, the present invention achieves the following beneficial effects: 1. In the present invention, the cleaning state of the elevated sound insulation wall is used to determine the cleaning flow of similar groups with different dirty states, thereby realizing dynamic adjustment of the cleaning flow of similar groups with different dirty states from the perspective of the cleaning state of the elevated sound insulation wall, avoiding the technical problem of excessive water consumption and slow cleaning efficiency due to the use of the same cleaning flow, while also ensuring the cleaning effect of the elevated sound insulation wall.

[0044] 2. In the present invention, the cleaning flow rate of the group with similar dirtiness is dynamically adjusted according to the detection result of the cleaning state of the elevated sound insulation wall after cleaning treatment, thereby avoiding the technical problem that the cleaning result of the elevated sound insulation wall cannot meet the requirements due to the use of a fixed cleaning flow rate. By dynamically adjusting the cleaning flow rate according to the detection result of the cleaning state, the reliability of the cleaning effect of the elevated sound insulation wall is further improved on the basis of avoiding excessive use of water.

[0045] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device, equipment, and non-volatile computer storage medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0046] The above is a description of a specific embodiment of the specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0047] The above description is only one or more embodiments of this specification and is not intended to limit this specification. For those skilled in the art, one or more embodiments of this specification may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of one or more embodiments of this specification shall be included in the scope of the claims of this specification.

Claims

1. An automatic cleaning detection method for elevated sound insulation walls, characterized in that: Specifically include: Based on the historical traffic volume of the elevated lanes corresponding to the elevated sound insulation walls, the elevated sound insulation walls are divided into multiple groups with similar dirtiness status; Obtain the distribution data and length of elevated sound insulation walls of different similar groups of dirty states, and determine the clean state detection length of different similar groups of dirty states in combination with the historical traffic flow of elevated lanes corresponding to the different similar groups of dirty states; Cleaning the elevated sound insulation walls of different similar groups of dirty states according to preset flow rates until the cleaning state of the elevated sound insulation walls of the similar groups of dirty states of the cleaning state detection length is obtained, and the cleaning flow rates of different similar groups of dirty states of the cleaning state are determined by using the cleaning state of the elevated sound insulation walls of the cleaning state detection length; The cleaning flow rates of the groups with similar dirty states are used as the basis for cleaning treatment of elevated sound insulation walls of different groups with similar dirty states, and the cleaning flow rates of the groups with similar dirty states are dynamically adjusted according to the detection results of the cleaning states of the elevated sound insulation walls after the cleaning treatment.

2. The automatic cleaning detection method for elevated sound insulation wall according to claim 1, characterized in that: The historical vehicle flow is determined based on the analysis results of the monitoring data of the monitoring device of the elevated lane.

3. The automatic cleaning detection method for elevated sound insulation wall according to claim 1, characterized in that: Divide the elevated sound insulation walls into several groups with similar soiling conditions, including: Based on the historical traffic volume, determine the deviation of the historical traffic volume between different elevated noise barriers on different dates; Determine the deviation date of traffic flow between different elevated noise insulation walls according to the deviation of historical traffic flow on different dates; The traffic flow similarity coefficients between different elevated sound insulation walls are determined based on the number of traffic flow deviation dates, and the elevated sound insulation walls are divided into a plurality of similar dirtiness status groups according to the traffic flow similarity coefficients.

4. The automatic cleaning detection method for elevated sound insulation wall according to claim 3, characterized in that: The elevated sound insulation wall is divided into a plurality of similar dirty status groups according to the vehicle flow similarity coefficient, including: Elevated sound insulation walls whose traffic flow similarity coefficients are greater than a preset similarity coefficient are classified into the same similarity group of dirtiness.

5. The automatic cleaning detection method for elevated sound insulation wall according to claim 1, characterized in that: The historical traffic volume of the elevated lane corresponding to the similar group in terms of dirtiness is determined according to the average value of the historical traffic volume of the elevated sound insulation wall in the similar group in terms of dirtiness.

6. The automatic cleaning detection method for elevated sound insulation wall according to claim 1, characterized in that: The method for determining the cleaning state detection length of the dirty state similar group is: Determine the benchmark detection ratio of the dirty state similar group by using the historical vehicle flow of the elevated lane corresponding to the dirty state similar group; Divide the elevated sound insulation walls whose distances are within a preset distance interval into the same clean area, and determine the dirtiness state discrete coefficient of the elevated sound insulation walls by using the lengths of the elevated sound insulation walls in different clean areas and the distances between different adjacent clean areas; The clean state detection ratio of the dirty state similar group is determined by using the dirty state discrete coefficient and the reference detection ratio, and the clean state detection length of the dirty state similar group is determined according to the clean state detection ratio and the length of the elevated sound insulation wall in the dirty state similar group.

7. The automatic cleaning detection method for elevated sound insulation wall according to claim 6, characterized in that: Determining the cleaning state detection ratio of the group with similar dirty states by using the dirty state discrete coefficient and the reference detection ratio specifically includes: The preset compensation detection ratio corresponding to the dirt state discrete coefficient is determined according to the dirt state discrete coefficient, and the cleaning state detection ratio of the dirt state similar group is determined by using the sum of the preset compensation detection ratio and the reference detection ratio.

8. The automatic cleaning detection method for elevated sound insulation wall according to claim 1, characterized in that: The method for determining the cleaning state detection length of the dirty state similar group is: S21 determines the traffic busy coefficient of the dirty state similar group using the historical traffic flow of the elevated lane corresponding to the dirty state similar group, and judges whether the traffic busy coefficient of the dirty state similar group is greater than the preset busy coefficient. If so, determines the clean state detection length of the dirty state similar group according to the preset detection ratio and the length of the elevated sound insulation wall in the dirty state similar group. If not, proceeds to the next step. S22 divides the elevated sound insulation walls whose distances are within a preset distance interval into the same cleaning area, and determines whether the number of the cleaning areas is greater than the preset number of cleaning areas. If so, proceed to the next step; if not, proceed to step S25; S23 determines whether the average distance between different adjacent cleaning areas is greater than a preset distance threshold, if so, proceeds to the next step, if not, proceeds to step S25; S24: The cleaning areas whose distance from the elevated sound insulation wall is greater than the preset distance are used as the screening cleaning areas, and it is determined whether the number of the screening cleaning areas is greater than the preset number of areas. If so, the cleaning state detection length of the dirty state similar group is determined according to the preset detection ratio and the length of the elevated sound insulation wall in the dirty state similar group. If not, proceed to the next step. S25 determines the dirtiness state discrete coefficient of the elevated sound insulation wall by utilizing the length of the elevated sound insulation wall in different cleaning areas and the distance between different adjacent cleaning areas, determines the cleaning state detection ratio of the dirty state similar group by multiplying the dirty state discrete coefficient by the traffic busy coefficient, and determines the cleaning state detection length of the dirty state similar group according to the cleaning state detection ratio and the length of the elevated sound insulation wall in the dirty state similar group.

9. The automatic cleaning detection method for elevated sound insulation wall according to claim 1, characterized in that: The preset flow rate is determined according to the clean length of the elevated sound insulation wall, wherein the longer the clean length of the elevated sound insulation wall is, the smaller the preset flow rate is.

10. An automatic cleaning and detection device for elevated sound insulation walls, using an automatic cleaning and detection method for elevated sound insulation walls according to any one of claims 1 to 9, characterized in that: Specifically include: Group division module, detection length determination module, cleaning flow determination module, flow adjustment module; The group division module is responsible for dividing the elevated sound insulation wall into a plurality of groups with similar dirtiness status based on the historical traffic volume of the elevated lane corresponding to the elevated sound insulation wall; The detection length determination module is responsible for obtaining the distribution data and lengths of elevated sound insulation walls with similar different dirty states, and determining the clean state detection lengths of different dirty state similar groups in combination with the historical traffic flow of elevated lanes corresponding to different dirty state similar groups; The cleaning flow determination module is responsible for performing cleaning processing on elevated sound insulation walls of different similar groups of dirty states according to preset flow rates until the cleaning state of the elevated sound insulation walls of the similar groups of dirty states of the cleaning state detection length is obtained, and the cleaning flow rates of different similar groups of dirty states of the cleaning state are determined by using the cleaning state of the elevated sound insulation walls of the cleaning state detection length; The flow adjustment module is responsible for cleaning the elevated sound insulation walls of different groups with similar dirty states based on the cleaning flow of the groups with similar dirty states, and dynamically adjusting the cleaning flow of the groups with similar dirty states according to the detection results of the cleaning state of the elevated sound insulation walls after the cleaning treatment.

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