An intelligent dredging robot and dredging management method for elevated bridge deck drainage system

Abstract

The present invention provides an intelligent dredging robot and a dredging management method for an elevated bridge deck drainage system, which belongs to the technical field of robots, and specifically comprises: based on the sequence of dredging treatment of drainage systems at different potential danger locations, a plurality of dredging treatment schemes are generated; the treatment time of different potential danger locations under different dredging treatment schemes is determined based on the distribution data of different potential danger locations; the treatment time effectiveness of different dredging treatment schemes and the available treatment schemes under the dredging treatment schemes are determined in combination with the water accumulation risks at different potential danger locations; based on the historical traffic flow data, the treatment time effectiveness and the treatment time effectiveness of the available treatment schemes at different potential danger locations, the dredging treatment schemes among the available treatment schemes are determined; and the dredging treatment schemes and the dredging robots are used to dredge the drainage system at the potential danger location, thereby avoiding the impact of water on the elevated bridge surface on traffic.

Description

Technical Field

[0001] The present invention belongs to the technical field of robots, and in particular relates to an intelligent dredging robot for an elevated bridge deck drainage system and a dredging management method. Background Art

[0002] In extreme weather conditions, water often accumulates on the elevated bridge deck, seriously affecting the normal driving of vehicles. In order to dredge the drainage system, a dredging robot is used in the invention patent application CN202410093399.6 "A Pipeline Dredging Robot" to dredge the drainage system of the elevated bridge deck, avoiding the impact of water accumulation on traffic. However, it is not difficult to find the following technical problems through analysis:

[0003] Due to differences in the construction quality of elevated bridge decks, once high-intensity precipitation occurs, there will be deviations in the probability of waterlogging on elevated bridge decks at different locations. Therefore, if the probability of waterlogging on the elevated bridge deck cannot be used to manage the dredging of the drainage system of the elevated bridge deck, the efficiency of the dredging of the drainage system cannot be improved.

[0004] In response to the above technical problems, the present invention provides an intelligent dredging robot and a dredging management method for an elevated bridge deck drainage system. Summary of the invention

[0005] To achieve the purpose of the present invention, the present invention adopts the following technical solutions:

[0006] According to one aspect of the present invention, a dredging management method is provided.

[0007] A dredging management method specifically comprises:

[0008] S1 uses the predicted precipitation data and the historical dredging data of the drainage system to determine the water accumulation data of the viaduct deck under different similar precipitation times, and predicts the water accumulation depth at different positions of the viaduct deck and determines the potential hidden danger position according to the water accumulation data;

[0009] S2 determines the historical dredging data of the drainage system at different potential hidden danger locations, and determines the water accumulation risk of the potential hidden danger locations and the hidden danger locations in the potential hidden danger locations in combination with the predicted water accumulation depth;

[0010] S3 generates multiple groups of dredging treatment plans based on the order of dredging treatment of drainage systems at different potential hazard locations, determines the treatment time of different potential hazard locations under different dredging treatment plans based on the distribution data of different potential hazard locations, and determines the treatment time of different dredging treatment plans and available treatment plans under the dredging treatment plans in combination with the water accumulation risks at different potential hazard locations;

[0011] S4 determines the dredging solution among the available treatment solutions based on the historical traffic flow data, processing time and treatment effectiveness of the available treatment solutions at different potential hazard locations, and uses the dredging solution and the dredging robot to dredge the drainage system at the potential hazard location.

[0012] A further technical solution is that the predicted precipitation data is determined based on data capture results of a weather forecast platform.

[0013] A further technical solution is that the similar precipitation number is determined based on the deviation between the historical rainfall and the preset precipitation and the historical dredging data, and specifically the historical precipitation period in which the deviation is within a preset range and the deviation between the dredging interval and the current dredging interval is within a preset range is taken as the similar precipitation number.

[0014] A further technical solution is that the current dredging interval duration is determined based on the most recent dredging times of the drainage system and the current interval duration.

[0015] A further technical solution is that when the water accumulation risk of the potential hidden danger location does not meet the requirements, the potential hidden danger location is determined to be a hidden danger location.

[0016] A further technical solution is that the method for determining the dredging treatment solution among the available treatment solutions is:

[0017] Determine the historical average traffic flow of different hidden danger locations using the historical traffic flow data of different hidden danger locations;

[0018] Determine the traffic impact coefficients of different hidden danger locations according to the historical average traffic flow and processing time of different hidden danger locations under the available processing solutions, and determine the comprehensive traffic impact coefficient of the available processing solutions through the traffic impact coefficients of different hidden danger locations;

[0019] The comprehensive matching coefficients of different available treatment solutions are determined by using the comprehensive traffic impact coefficient and the treatment time efficiency, and the dredging treatment solution among the available treatment solutions is determined using the comprehensive matching coefficient.

[0020] A further technical solution is to use the comprehensive matching coefficient to determine the dredging treatment solution among the available treatment solutions, specifically including:

[0021] The available treatment plan with the largest comprehensive matching coefficient is used as the dredging treatment plan.

[0022] On the other hand, the present application provides an intelligent dredging robot for an elevated bridge deck drainage system, which is applied to the above-mentioned dredging management method, specifically comprising:

[0023] Positioning module, dredging processing module, processing result identification module;

[0024] The positioning module is responsible for performing position identification processing on the drainage system to obtain a processing position;

[0025] The dredging processing module is responsible for dredging the drainage system using the processing position;

[0026] The processing result identification module is responsible for identifying the dredging processing result of the drainage system to obtain an identification result, and determining whether a secondary dredging processing is required based on the identification result.

[0027] The beneficial effects of the present invention are:

[0028] 1. In the present invention, the hidden danger positions among the potential hidden danger positions are determined based on the historical dredging data and predicted water accumulation depth of the drainage system at different potential hidden danger positions. This not only realizes the evaluation of the congestion situation of the drainage system at the potential hidden danger position from the perspective of historical dredging data, but also takes into account the predicted water accumulation depth of the potential position, thereby realizing the identification of the hidden danger position with a higher risk of water accumulation, and also lays a foundation for differentiated dredging treatment of the drainage system, thereby improving the efficiency of the dredging treatment.

[0029] 2. In the present invention, the dredging treatment plan among the available treatment plans is determined based on the historical traffic flow data, processing time and processing time effectiveness of the available treatment plans of different potential danger locations. This avoids the technical problem of a potential danger location with a large historical traffic flow having a large traffic impact due to a long processing time, and also avoids the technical problem of a potential danger location with a large water accumulation risk having a large traffic impact due to a long processing time. This realizes the determination of dredging treatment plans from multiple angles, ensures the smoothness of traffic, and avoids the impact of water accumulation on traffic.

[0030] 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.

[0031] 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

[0032] 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;

[0033] Figure 1 It is a flow chart of the dredge management method;

[0034] Figure 2is a flow chart of a method for determining predicted depths of water accumulation at different locations on an elevated bridge deck;

[0035] Figure 3 It is a flow chart of the method for determining the risk of water accumulation at potential hazard locations;

[0036] Figure 4 It is a flow chart of a method for determining the treatment time limit of a dredging treatment plan;

[0037] Figure 5 It is a framework diagram of an intelligent dredging robot for elevated bridge deck drainage system. DETAILED DESCRIPTION

[0038] 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.

[0039] Due to differences in the construction quality of elevated bridge decks, once high-intensity precipitation occurs, there will be deviations in the probability of waterlogging on elevated bridge decks at different locations. Therefore, it is necessary to use the probability of waterlogging on elevated bridge decks to dredge and manage the drainage system of the elevated bridge deck to avoid the occurrence of waterlogging.

[0040] Predicted water accumulation depth: The predicted water accumulation depth is determined based on the average value of the water accumulation depth on the elevated bridge deck under different similar precipitation times.

[0041] Potential hidden danger location: The location where the predicted water depth is greater than the preset water depth is regarded as the potential hidden danger location.

[0042] Water accumulation risk at potential hidden danger locations: The water accumulation risk is determined based on the time between the most recent dredging time and the current time and the predicted water accumulation depth. The water accumulation risk is specifically determined based on the product of the predicted water accumulation depth, the time between the most recent dredging time and the current time and the preset proportional factor, and the potential hidden danger locations with water accumulation risks greater than 0.3 are regarded as hidden danger locations.

[0043] The treatment time of the dredging treatment plan: The treatment time is determined by the sum of the ratios of the water accumulation risk and the treatment time at different potential hazard locations, and a preset number of dredging treatment plans with the largest treatment time are used as available treatment plans, where the preset number is 3.

[0044] Unblocking solution: The ratio of the average historical traffic volume to the processing time is used to determine the clearance delay risk of different hidden danger locations. The largest available solution based on the product of the clearance delay risk of different hidden danger locations and the processing time of the available solutions is used as the unblocking solution.

[0045] Embodiment 1 To solve the above-mentioned problem, according to one aspect of the present invention, Figure 1 As shown, a dredging management method is provided, which specifically includes:

[0046] S1 uses the predicted precipitation data and the historical dredging data of the drainage system to determine the water accumulation data of the viaduct deck under different similar precipitation times, and predicts the water accumulation depth at different positions of the viaduct deck and determines the potential hidden danger position according to the water accumulation data;

[0047] S2 determines the historical dredging data of the drainage system at different potential hidden danger locations, and determines the water accumulation risk of the potential hidden danger locations and the hidden danger locations in the potential hidden danger locations in combination with the predicted water accumulation depth;

[0048] S3 generates multiple groups of dredging treatment plans based on the order of dredging treatment of drainage systems at different potential hazard locations, determines the treatment time of different potential hazard locations under different dredging treatment plans based on the distribution data of different potential hazard locations, and determines the treatment time of different dredging treatment plans and available treatment plans under the dredging treatment plans in combination with the water accumulation risks at different potential hazard locations;

[0049] S4 determines the dredging solution among the available treatment solutions based on the historical traffic flow data, processing time and treatment effectiveness of the available treatment solutions at different potential hazard locations, and uses the dredging solution and the dredging robot to dredge the drainage system at the potential hazard location.

[0050] Furthermore, the predicted precipitation data is determined based on data capture results from a weather forecast platform.

[0051] Specifically, the similar precipitation times are determined based on the deviation between the historical rainfall and the preset precipitation and the historical dredging data. Specifically, the historical precipitation time period in which the deviation is within the preset range and the deviation between the dredging interval and the current dredging interval is within the preset range is taken as the similar precipitation times.

[0052] It can be understood that the current dredging interval duration is determined based on the number of dredging operations of the drainage system most recently and the current interval duration.

[0053] It should be noted that if Figure 2 As shown, the method for determining the predicted depth of water accumulation at different positions on the viaduct deck is:

[0054] Determine the water accumulation depth at a specific location under different similar precipitation times by using water accumulation data under different similar precipitation times, and divide the similar precipitation times into different water accumulation depth intervals by using the water accumulation depth;

[0055] The occurrence probability of different waterlogging depth intervals is determined by the proportion of similar precipitation times in different waterlogging depth intervals;

[0056] The predicted depth of water accumulation at the specific location is determined according to the water accumulation depth range and occurrence probability of different water accumulation depth intervals.

[0057] Further, the predicted depth of waterlogging at the specific location is determined according to the waterlogging depth range and occurrence probability of different waterlogging depth intervals, specifically including:

[0058] The corresponding water accumulation temperatures of different water accumulation depth intervals are determined using the middle value of the water accumulation depth range, and the predicted water accumulation depth of the specific location is determined using the product of the corresponding water accumulation depth of different water accumulation depth intervals and the occurrence probability.

[0059] In another embodiment, the method for determining the predicted depth of water accumulation at different positions on the viaduct deck is:

[0060] Determine the water accumulation depth at a specific location under different similar precipitation times by using water accumulation data under different similar precipitation times, and divide the similar precipitation times into different water accumulation depth intervals by using the water accumulation depth;

[0061] The occurrence probability of different waterlogging depth intervals is determined by the proportion of similar precipitation times in different waterlogging depth intervals;

[0062] The waterlogging depth interval with the highest probability of occurrence is used as the screening depth interval, and the predicted waterlogging depth at the specific location is determined using the middle value of the waterlogging depth range in the screening depth interval.

[0063] In another embodiment, the method for determining the predicted depth of water accumulation at different positions on the viaduct deck is:

[0064] S11 determines the water accumulation depth at a specific location under different similar precipitation times by using the water accumulation data under different similar precipitation times, and uses the average value of the water accumulation depth at the specific location under different similar precipitation times as the average water accumulation depth;

[0065] S12 determines whether the deviations of the water depth at a specific location under different similar precipitation times and the average water depth are within a preset range, if so, using the average water depth as the water depth at the specific location, if not, proceeding to the next step;

[0066] S13 determines the deviation precipitation times by using the deviation between the water accumulation depth at the specific location under different similar precipitation times and the average water accumulation depth, and judges whether the proportion of the deviation precipitation times to the similar precipitation times is less than the preset proportion, if so, proceeds to the next step, if not, proceeds to step S16;

[0067] S14 determines whether there is a deviation between the water depth and the average water depth that does not meet the required deviation precipitation times, if so, proceed to the next step, if not, use the average water depth as the water depth at the specific location;

[0068] S15 determines the water depth deviation based on the deviation between the water depth under different deviation precipitation times and the average water depth, and judges whether the water depth deviation meets the requirement. If so, proceeds to the next step; if not, uses the average water depth as the water depth at the specific location;

[0069] S16 divides the similar precipitation times into different water accumulation depth intervals by using the water accumulation depth, determines the occurrence probability of different water accumulation depth intervals by the proportion of similar precipitation times in different water accumulation depth intervals, and determines the predicted water accumulation depth at the specific location according to the water accumulation depth range and occurrence probability of different water accumulation depth intervals.

[0070] Furthermore, when the predicted water accumulation depth at the specific location is greater than the preset water accumulation depth, the specific location is determined to be a potential hidden danger location.

[0071] In another possible embodiment, the method for determining the predicted depth of water accumulation at different positions on the viaduct deck is:

[0072] S111 determines the water accumulation depth of a specific location under different similar precipitation times by using the water accumulation data under different similar precipitation times, and judges whether there are similar precipitation times with a water accumulation depth greater than a preset water accumulation depth. If so, proceed to the next step; if not, determine that the specific location is not a potential hazard location;

[0073] S112: taking the number of similar precipitations with a water accumulation depth greater than a preset water accumulation depth as the number of water accumulations, and judging whether the proportion of the number of water accumulations in the number of similar precipitations is less than the preset proportion of water accumulations, if so, proceeding to the next step, if not, proceeding to step 115;

[0074] S113 obtains the average water depth of the water accumulation times, and determines whether the average water depth of the water accumulation times is within a preset depth range. If so, it is determined that the specific location is not a potential hidden danger location. If not, proceed to the next step;

[0075] S114 determines the probability of waterlogging based on the proportion of the number of waterlogging times in the number of similar precipitation times and the depth of waterlogging at different waterlogging times, and judges whether the probability of waterlogging is less than a preset probability threshold. If so, it is determined that the specific location is not a potential hidden danger location. If not, proceed to the next step.

[0076] S115 utilizes the water accumulation depth to divide the similar precipitation times into different water accumulation depth intervals, determines the occurrence probability of different water accumulation depth intervals according to the proportion of similar precipitation times in different water accumulation depth intervals, and determines the predicted water accumulation depth at the specific location according to the water accumulation depth range and occurrence probability of different water accumulation depth intervals.

[0077] Specifically, Figure 3 As shown, the method for determining the water accumulation risk at the potential hidden danger location is:

[0078] Based on the historical dredging data of the drainage system at the potential hidden danger location, determine the most recent dredging time of the potential hidden danger location, and use it as the near dredging time, and determine the dredging time based on the interval between the near dredging time and the current time;

[0079] Determine the dredging interval duration and pipeline congestion ratio of the drainage system at different historical dredging times according to the historical dredging data, and determine the reference dredging times in the historical dredging times by using the time deviation between the dredging interval duration and the dredging time duration;

[0080] The pipeline congestion ratio of the potential hidden danger location is determined by using the average value of the pipeline congestion ratio of the reference dredging times, and the water accumulation risk of the potential hidden danger location is determined by using the pipeline congestion ratio of the potential hidden danger location and the predicted water accumulation depth.

[0081] Furthermore, the water accumulation risk at the potential hidden danger location is determined based on the pipeline congestion ratio at the potential hidden danger location and the predicted water accumulation depth, specifically including:

[0082] Determine the drainage influence coefficient of the potential hidden danger location based on the pipeline congestion ratio of the potential hidden danger location, and determine the water accumulation depth correction value of the potential hidden danger location based on the drainage influence coefficient and the predicted water accumulation depth;

[0083] The water accumulation risk at the potential hidden danger location is determined according to the preset water accumulation risk corresponding to the water accumulation depth correction value.

[0084] It can be understood that when the water accumulation risk of the potential hidden danger location does not meet the requirements, the potential hidden danger location is determined to be a hidden danger location.

[0085] In another embodiment, the method for determining the water accumulation risk at the potential hidden danger location is:

[0086] Based on the historical dredging data of the drainage system at the potential hidden danger location, determine the most recent dredging time of the potential hidden danger location, and use it as the near dredging time, and determine the dredging time based on the interval between the near dredging time and the current time;

[0087] Determine the dredging interval duration and pipeline congestion ratio of the drainage system at different historical dredging times according to the historical dredging data, and determine the reference dredging times in the historical dredging times by using the time deviation between the dredging interval duration and the dredging time duration;

[0088] Determine the proportion of congestion times using the pipeline congestion ratio of the reference dredging times, determine the congestion risk coefficient according to the proportion of congestion times, and determine the water accumulation depth risk coefficient of the potential hidden danger location according to the predicted water accumulation depth;

[0089] The water accumulation risk at the potential hidden danger location is determined by weighting the congestion risk coefficient and the water accumulation depth risk coefficient.

[0090] In another embodiment, the method for determining the water accumulation risk at the potential hidden danger location is:

[0091] S21 determines whether the predicted water depth of the potential hidden danger location is the maximum limit of the water depth. If so, it is determined that the potential hidden danger location is a hidden danger location. If not, proceed to the next step;

[0092] S22 determines the most recent dredging time of the potential hidden danger location based on the historical dredging data of the drainage system at the potential hidden danger location, and uses it as the near dredging time, and determines the dredging time based on the interval between the near dredging time and the current time;

[0093] S23 determines the dredging interval duration and pipeline congestion ratio of the drainage system at different historical dredging times according to the historical dredging data, and uses the time deviation between the dredging interval duration and the non-dredging time duration to determine the reference dredging times in the historical dredging times, and uses the pipeline congestion ratio to determine whether there is a reference dredging number whose pipeline congestion ratio cannot meet the requirements, if yes, proceed to the next step, if not, proceed to step S26;

[0094] S24 determines whether there is a reference dredging number with a pipeline congestion ratio greater than a preset ratio. If so, it is determined that the potential hidden danger position belongs to a hidden danger position. If not, proceed to the next step;

[0095] S25 determines whether the reference dredging times for which the pipeline congestion ratio cannot meet the requirement meet the requirement, if so, proceeds to the next step, if not, determines that the potential hidden danger position is a hidden danger position;

[0096] S26 determines the proportion of congestion times using the pipeline congestion ratio of the reference dredging times, and determines the congestion risk coefficient based on the proportion of congestion times; determines the water accumulation depth risk coefficient of the potential hidden danger location based on the predicted water accumulation depth, and determines the water accumulation risk of the potential hidden danger location by the weight sum of the congestion risk coefficient and the water accumulation depth risk coefficient.

[0097] Specifically, the method for determining the dredging treatment plan is:

[0098] The order of dredging treatment of the drainage system at the potential hazard location can be freely combined to form multiple sets of dredging treatment plans.

[0099] Furthermore, the processing time of the hidden danger location is determined according to the dredging order and position in the dredging treatment plan. Specifically, the processing time of the hidden danger location in the early stage of the hidden danger location is determined according to the dredging order, and the moving time is determined using the position of the hidden danger location. The processing time of the hidden danger location is determined according to the moving time, the processing time, and the dredging time of the hidden danger location.

[0100] It is understandable that if Figure 4 As shown, the method for determining the treatment time of the dredging treatment solution is:

[0101] Divide the hidden danger locations into multiple risk intervals according to the water accumulation risks of different hidden danger locations, and determine the processing efficiency of different risk intervals by using the average value of the processing time of different hidden danger locations in different risk intervals;

[0102] Determine the waterlogging risk ranges corresponding to different risk intervals, and determine the risk weight values ​​of different risk intervals according to the waterlogging risk ranges;

[0103] The processing timeliness of the dredging treatment plan is determined based on the processing efficiency of different risk intervals and the risk weight value.

[0104] Furthermore, the processing time of the dredging treatment solution has a value range of 0 to 1, wherein when the processing time of the dredging treatment solution is greater than a preset time threshold, the dredging treatment solution is determined to be an available treatment solution.

[0105] In another embodiment, the method for determining the treatment time of the dredging treatment solution is:

[0106] S31 utilizes the processing time of different hidden danger positions in the dredging treatment plan, and utilizes the processing time to determine the total processing time of the dredging treatment plan, and determines whether the total processing time of the dredging treatment plan meets the requirements, if so, proceeds to the next step, if not, determines that the dredging treatment plan does not belong to the available treatment plan;

[0107] S32 uses different hidden danger positions to process the hidden danger position with a processing time longer than the preset time, and uses it as a delayed processing position to determine whether there is a delayed processing position with a water accumulation risk greater than the preset risk threshold, and if so, proceeds to the next step, if not, proceeds to step S35;

[0108] S33: taking the delayed processing positions where the water accumulation risk is greater than the preset risk threshold as delayed processing risk positions, and judging whether the number of the delayed processing risk positions meets the requirement, if so, proceeding to the next step, if not, determining that the dredging treatment scheme does not belong to the available treatment scheme;

[0109] S34 determines whether the average value of the water accumulation risk at the delayed treatment location meets the requirement, if so, proceeds to the next step, if not, determines that the dredging treatment solution does not belong to the available treatment solution;

[0110] S35 divides the hidden danger locations into multiple risk intervals according to the waterlogging risks of different hidden danger locations, and determines the processing efficiency of different risk intervals by using the average value of the processing time of different hidden danger locations in different risk intervals, determines the waterlogging risk ranges corresponding to different risk intervals, and determines the risk weight values ​​of different risk intervals according to the waterlogging risk ranges;

[0111] S36 determines the processing timeliness of the dredging treatment plan based on the processing efficiency of different risk intervals and the risk weight value.

[0112] Specifically, the method for determining the dredging treatment solution among the available treatment solutions is:

[0113] Determine the historical average traffic flow of different hidden danger locations using the historical traffic flow data of different hidden danger locations;

[0114] Determine the traffic impact coefficients of different hidden danger locations according to the historical average traffic flow and processing time of different hidden danger locations under the available processing solutions, and determine the comprehensive traffic impact coefficient of the available processing solutions through the traffic impact coefficients of different hidden danger locations;

[0115] The comprehensive matching coefficients of different available treatment solutions are determined by using the comprehensive traffic impact coefficient and the treatment time efficiency, and the dredging treatment solution among the available treatment solutions is determined using the comprehensive matching coefficient.

[0116] Further, the comprehensive matching coefficient is used to determine the dredging treatment solution among the available treatment solutions, specifically including:

[0117] The available treatment plan with the largest comprehensive matching coefficient is used as the dredging treatment plan.

[0118] Embodiment 2 On the other hand, as Figure 5 As shown, the present application provides an intelligent dredging robot for an elevated bridge deck drainage system, which is applied to the above-mentioned dredging management method, specifically comprising:

[0119] Positioning module, dredging processing module, processing result identification module;

[0120] The positioning module is responsible for performing position identification processing on the drainage system to obtain a processing position;

[0121] The dredging processing module is responsible for dredging the drainage system using the processing position;

[0122] The processing result identification module is responsible for identifying the dredging processing result of the drainage system to obtain an identification result, and determining whether a secondary dredging processing is required based on the identification result.

[0123] Based on the above embodiments, the present invention achieves the following beneficial effects:

[0124] 1. In the present invention, the hidden danger positions among the potential hidden danger positions are determined based on the historical dredging data and predicted water accumulation depth of the drainage system at different potential hidden danger positions. This not only realizes the evaluation of the congestion situation of the drainage system at the potential hidden danger position from the perspective of historical dredging data, but also takes into account the predicted water accumulation depth of the potential position, thereby realizing the identification of the hidden danger position with a higher risk of water accumulation, and also lays a foundation for differentiated dredging treatment of the drainage system, thereby improving the efficiency of the dredging treatment.

[0125] 2. In the present invention, the dredging treatment plan among the available treatment plans is determined based on the historical traffic flow data, processing time and processing time effectiveness of the available treatment plans of different potential danger locations. This avoids the technical problem of a potential danger location with a large historical traffic flow having a large traffic impact due to a long processing time, and also avoids the technical problem of a potential danger location with a large water accumulation risk having a large traffic impact due to a long processing time. This realizes the determination of dredging treatment plans from multiple angles, ensures the smoothness of traffic, and avoids the impact of water accumulation on traffic.

[0126] 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.

[0127] 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.

[0128] 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. A dredging management method, characterized in that: Specifically include: Determine water accumulation data of the viaduct deck under different similar precipitation times by using predicted precipitation data and historical dredging data of the drainage system, and determine predicted water accumulation depths at different locations of the viaduct deck and potential hidden danger locations according to the water accumulation data; Determine the historical dredging data of the drainage system at different potential hidden danger locations, and determine the water accumulation risk of the potential hidden danger locations and the hidden danger locations in the potential hidden danger locations in combination with the predicted water accumulation depth; Based on the order of dredging treatment of drainage systems at different potential hazard locations, multiple groups of dredging treatment plans are generated, and the treatment time of different potential hazard locations under different dredging treatment plans is determined based on the distribution data of different potential hazard locations. In addition, the treatment time of different dredging treatment plans and the available treatment plans under the dredging treatment plans are determined in combination with the water accumulation risks at different potential hazard locations; Based on the historical traffic flow data, processing time and processing time efficiency of available processing solutions at different potential danger locations, a dredging processing solution among the available processing solutions is determined, and the dredging processing solution and the dredging robot are used to dredge the drainage system at the potential danger location; The method for determining the treatment time of the dredging treatment solution is: S31 utilizes the processing time of different hidden danger positions in the dredging treatment plan, and utilizes the processing time to determine the total processing time of the dredging treatment plan, and determines whether the total processing time of the dredging treatment plan meets the requirements, if so, proceeds to the next step, if not, determines that the dredging treatment plan does not belong to the available treatment plan; S32 uses different hidden danger positions to process the hidden danger position with a processing time longer than the preset time, and uses it as a delayed processing position to determine whether there is a delayed processing position with a water accumulation risk greater than the preset risk threshold, and if so, proceeds to the next step, if not, proceeds to step S35; S33: taking the delayed processing positions where the water accumulation risk is greater than the preset risk threshold as delayed processing risk positions, and judging whether the number of the delayed processing risk positions meets the requirement, if so, proceeding to the next step, if not, determining that the dredging treatment scheme does not belong to the available treatment scheme; S34 determines whether the average value of the water accumulation risk at the delayed treatment location meets the requirement, if so, proceeds to the next step, if not, determines that the dredging treatment solution does not belong to the available treatment solution; S35 divides the hidden danger locations into multiple risk intervals according to the waterlogging risks of different hidden danger locations, and determines the processing efficiency of different risk intervals by using the average value of the processing time of different hidden danger locations in different risk intervals, determines the waterlogging risk ranges corresponding to different risk intervals, and determines the risk weight values ​​of different risk intervals according to the waterlogging risk ranges; S36 determines the processing timeliness of the dredging treatment plan based on the processing efficiency of different risk intervals and the risk weight value; The method for determining the water accumulation risk at the potential hidden danger location is: S21 determines whether the predicted water depth of the potential hidden danger location is the maximum limit of the water depth. If so, it is determined that the potential hidden danger location is a hidden danger location. If not, proceed to the next step; S22 determines the most recent dredging time of the potential hidden danger location based on the historical dredging data of the drainage system at the potential hidden danger location, and uses it as the near dredging time, and determines the dredging time based on the interval between the near dredging time and the current time; S23 determines the dredging interval duration and pipeline congestion ratio of the drainage system at different historical dredging times according to the historical dredging data, and uses the time deviation between the dredging interval duration and the non-dredging time duration to determine the reference dredging times in the historical dredging times, and uses the pipeline congestion ratio to determine whether there is a reference dredging number whose pipeline congestion ratio cannot meet the requirements, if yes, proceed to the next step, if not, proceed to step S26; S24 determines whether there is a reference dredging number with a pipeline congestion ratio greater than a preset ratio. If so, it is determined that the potential hidden danger position belongs to a hidden danger position. If not, proceed to the next step; S25 determines whether the reference dredging times for which the pipeline congestion ratio cannot meet the requirement meet the requirement, if so, proceeds to the next step, if not, determines that the potential hidden danger position is a hidden danger position; S26 determines the proportion of congestion times using the pipeline congestion ratio of the reference dredging times, and determines the congestion risk coefficient based on the proportion of congestion times; determines the water accumulation depth risk coefficient of the potential hidden danger location based on the predicted water accumulation depth, and determines the water accumulation risk of the potential hidden danger location by the weight sum of the congestion risk coefficient and the water accumulation depth risk coefficient.

2. The dredging management method according to claim 1, characterized in that: The predicted precipitation data is determined based on the data capture results of the weather forecast platform.

3. The dredging management method according to claim 1, characterized in that: The similar precipitation times are determined based on the deviation between the historical rainfall and the preset precipitation and the historical dredging data. Specifically, the historical precipitation period in which the deviation is within a preset range and the deviation between the dredging interval and the current dredging interval is within a preset range is taken as the similar precipitation times.

4. The dredging management method according to claim 3, characterized in that: The current dredging interval duration is determined based on the number of dredging operations of the drainage system most recently and the current interval duration.

5. The dredging management method according to claim 1, characterized in that: The method for determining the predicted depth of water accumulation at different positions on the viaduct deck is as follows: Determine the water accumulation depth at a specific location under different similar precipitation times by using water accumulation data under different similar precipitation times, and divide the similar precipitation times into different water accumulation depth intervals by using the water accumulation depth; The occurrence probability of different waterlogging depth intervals is determined by the proportion of similar precipitation times in different waterlogging depth intervals; The predicted depth of water accumulation at the specific location is determined according to the water accumulation depth range and occurrence probability of different water accumulation depth intervals.

6. The dredging management method according to claim 5, characterized in that: Determining the predicted depth of waterlogging at the specific location according to the waterlogging depth range and occurrence probability of different waterlogging depth intervals specifically includes: The corresponding water accumulation temperatures of different water accumulation depth intervals are determined using the middle value of the water accumulation depth range, and the predicted water accumulation depth of the specific location is determined using the product of the corresponding water accumulation depth of different water accumulation depth intervals and the occurrence probability.

7. The dredging management method according to claim 1, characterized in that: The method for determining the predicted depth of water accumulation at different positions on the viaduct deck is as follows: S111 determines the water accumulation depth of a specific location under different similar precipitation times by using the water accumulation data under different similar precipitation times, and judges whether there are similar precipitation times with a water accumulation depth greater than a preset water accumulation depth. If so, proceed to the next step; if not, determine that the specific location is not a potential hazard location; S112: taking the number of similar precipitations with a water accumulation depth greater than a preset water accumulation depth as the number of water accumulations, and judging whether the proportion of the number of water accumulations in the number of similar precipitations is less than the preset proportion of water accumulations, if so, proceeding to the next step, if not, proceeding to step 115; S113 obtains the average water depth of the water accumulation times, and determines whether the average water depth of the water accumulation times is within a preset depth range. If so, it is determined that the specific location is not a potential hidden danger location. If not, proceed to the next step; S114 determines the probability of waterlogging based on the proportion of the number of waterlogging times in the number of similar precipitation times and the depth of waterlogging at different waterlogging times, and judges whether the probability of waterlogging is less than a preset probability threshold. If so, it is determined that the specific location is not a potential hidden danger location. If not, proceed to the next step. S115 utilizes the water accumulation depth to divide the similar precipitation times into different water accumulation depth intervals, determines the occurrence probability of different water accumulation depth intervals according to the proportion of similar precipitation times in different water accumulation depth intervals, and determines the predicted water accumulation depth at the specific location according to the water accumulation depth range and occurrence probability of different water accumulation depth intervals.

8. An intelligent dredging robot for an elevated bridge deck drainage system, applied to a dredging management method according to any one of claims 1 to 7, characterized in that: Specifically include: Positioning module, dredging processing module, processing result identification module; The positioning module is responsible for performing position identification processing on the drainage system to obtain a processing position; The dredging processing module is responsible for dredging the drainage system using the processing position; The processing result identification module is responsible for identifying the dredging processing result of the drainage system to obtain an identification result, and determining whether a secondary dredging processing is required based on the identification result.

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