A kind of inspection robot inspection dispatching management system and method based on Internet of Things

Abstract

The present invention relates to the technical field of water conservancy project inspection and scheduling, specifically to a detection robot inspection and scheduling management system and method based on the Internet of Things, in which a risk inspection monitoring point analysis module in the system combines the positions between different monitoring points in the corresponding water conservancy project and the collaborative relationship between the various monitoring points involved in the historical control process of the corresponding water conservancy project to generate indirect associated monitoring points corresponding to each element in the direct associated monitoring point set, and construct a risk inspection monitoring point set for the corresponding water conservancy project. In the inspection and scheduling process, the present invention not only realizes the dynamic construction of the risk inspection monitoring point set through the operating status data of the monitoring points, the impact of rainfall changes on the water level of the water conservancy project, and the collaborative relationship between the various monitoring points involved in the historical control process; it also takes into account the location of the detection robot to realize dynamic analysis and accurate screening of the inspection scheduling plan, and realizes effective management of the inspection and scheduling of the detection robot.

Description

Technical Field

[0001] The present invention relates to the technical field of water conservancy project inspection and dispatching, and in particular to an inspection and dispatching management system and method for a detection robot based on the Internet of Things. Background Art

[0002] Water conservancy projects are usually large-scale and require a lot of human resources for inspection and maintenance. The introduction of inspection robots can replace some manual inspection work and reduce labor costs. At the same time, since robots can conduct inspections 24 hours a day, they can further reduce manpower input and improve the continuity of inspection work.

[0003] In the existing inspection and dispatching management system based on the Internet of Things, fixed monitoring point objects to be inspected are often directly set or comprehensive inspections are carried out. This method has major defects. On the one hand, the existing sensor technology can monitor the status of water conservancy project monitoring points to a certain extent; on the other hand, the water level fluctuations in the area where the water conservancy project belongs will also require dynamic adjustment of the monitoring points to be inspected. If the fixed inspection objects belong to partial inspections, the inspection will be incomplete and there will be omissions in monitoring; and if the fixed inspection objects belong to comprehensive inspections, the inspection cycle will be longer, and the inspection efforts on key inspection objects will be insufficient, and it will be time-consuming and labor-intensive. Summary of the invention

[0004] The purpose of the present invention is to provide a detection robot inspection dispatch management system and method based on the Internet of Things to solve the problems raised in the above background technology.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: a method for patrol inspection and scheduling management of detection robots based on the Internet of Things, the method comprising the following steps:

[0006] S1. Obtain the operating status data corresponding to each monitoring point in the water conservancy project in real time through sensors, and lock the core monitoring points in the water conservancy project based on the acquired operating status data; obtain the rainfall forecast information in the subsequent preset time period based on the current time in the area to which the water conservancy project belongs, combine the historical rainfall forecast information of the area to which the corresponding water conservancy project belongs, predict the water level characteristics of the corresponding water conservancy project, and lock the risk monitoring points of the corresponding water conservancy project based on the rainfall forecast information;

[0007] S2. Extract the core monitoring points in the water conservancy project and the risk monitoring points based on rainfall forecast information, construct a directly associated monitoring point set, combine the positions of different monitoring points in the corresponding water conservancy project and the collaborative relationship between the various monitoring points involved in the historical control process of the corresponding water conservancy project, generate indirect associated monitoring points corresponding to each element in the directly associated monitoring point set, and construct a risk inspection monitoring point set for the corresponding water conservancy project;

[0008] S3, extract the fault risk characteristics of each element in the risk inspection monitoring point set of the corresponding water conservancy project, and construct a risk quantification inspection sequence;

[0009] S4. Obtain the inspection feature set of the corresponding detection robot of the corresponding water conservancy project in real time through the local area network of the area to which the corresponding water conservancy project belongs; generate various inspection scheduling planning schemes of the corresponding detection robot of the corresponding water conservancy project based on the risk quantification inspection sequence; analyze the inspection scheduling bias values ​​of different inspection scheduling planning schemes based on the risk quantification inspection sequence;

[0010] S5. Generate an inspection task instruction set based on the inspection scheduling planning scheme with the smallest inspection scheduling bias value, and transmit each inspection task instruction in the inspection task instruction set to the corresponding detection robot through the local area network of the area to which the corresponding water conservancy project belongs.

[0011] Further, the operation status data includes abnormal extraction information corresponding to the collected pictures at the corresponding monitoring points, and the abnormal extraction information is the ratio of the crack area to the area of ​​the collected pictures, the ratio of the spalling area to the area of ​​the collected pictures, and the ratio of the corrosion area to the area of ​​the collected pictures, which are extracted after image recognition of the corresponding collected pictures;

[0012] When locking the core monitoring points in the water conservancy project, obtain the preset fixed core monitoring points of the corresponding water conservancy project, and compare the various data in the abnormal extraction information in the operation status data corresponding to each monitoring point in the corresponding water conservancy project with the preset abnormal extraction threshold of the corresponding item of the corresponding monitoring point.

[0013] All monitoring points in the corresponding water conservancy project where the data in the corresponding abnormal extraction information is greater than or equal to the preset abnormal extraction threshold of the corresponding item of the corresponding monitoring point, as well as the fixed core monitoring points preset in the corresponding water conservancy project, are recorded as core monitoring points in the corresponding water conservancy project;

[0014] The following steps are involved in locking the risk monitoring points of the corresponding water conservancy projects based on rainfall forecast information:

[0015] S11, obtaining a data pair consisting of rainfall forecast information in a subsequent preset time period based on the current time in the area to which the water conservancy project belongs and the water level height in the monitoring area corresponding to the current water conservancy project as the water conservancy environment characteristics at the current time; the rainfall forecast information includes the duration corresponding to the corresponding time period and the corresponding precipitation depth prediction value in the corresponding time period;

[0016] S12, obtaining historical rainfall forecast information of the area to which the corresponding water conservancy project belongs, and constructing the water level change in the water conservancy project monitoring area respectively associated with different water conservancy environmental characteristics in the historical data; the water level change in the water conservancy project monitoring area associated with each water conservancy environmental characteristic is the maximum difference between the water level height in the monitoring area of ​​the corresponding water conservancy project in the corresponding time period in the corresponding water conservancy environmental characteristic and the water level height in the corresponding monitoring area in the corresponding water conservancy environmental characteristic;

[0017] S13, according to the different water conservancy environmental characteristics in the historical data, the water level changes in the water conservancy project monitoring area are respectively associated and mapped, and the water level changes in the water conservancy project monitoring area associated and mapped with the water conservancy environmental characteristics at the current time are matched, recorded as the water level associated mutation amount, and the data pair consisting of the water level height in the monitoring area corresponding to the current water conservancy project and the obtained water level associated mutation amount is used as the water level characteristic prediction result of the corresponding water conservancy project;

[0018] S14. Obtain a set of monitoring points whose water level in the monitoring area corresponding to the water conservancy project is covered in the interval [h, h+h1], which is recorded as a risk monitoring set. Any element in the risk monitoring set corresponds to a risk monitoring point of a corresponding water conservancy project based on rainfall forecast information; h represents the water level in the monitoring area corresponding to the current water conservancy project in the water level characteristic prediction result of the corresponding water conservancy project; h1 represents the water level correlation mutation amount in the water level characteristic prediction result of the corresponding water conservancy project.

[0019] The present invention analyzes the rainfall forecast information in the subsequent preset time period based on the current time in the area to which the corresponding water conservancy project belongs, taking into account that the rainfall forecast information in the area to which the corresponding water conservancy project belongs will affect the change of the water level height in the area to which the corresponding water conservancy project belongs. Combined with the current water level height in the area to which the corresponding water conservancy project belongs, it is possible to predict the water level height in the area to which the corresponding water conservancy project belongs, and then extract the monitoring point conditions in the water level change area, providing a data basis for the subsequent generation of a directly associated monitoring point set.

[0020] Furthermore, the directly associated monitoring point set includes all core monitoring points in the water conservancy project and all risk monitoring points based on rainfall forecast information;

[0021] The method for generating the indirect associated monitoring point corresponding to each element in the directly associated monitoring point set comprises the following steps:

[0022] S21, obtaining the positions between different monitoring points in the corresponding water conservancy project and the collaborative relationship between various monitoring points involved in the historical control process of the corresponding water conservancy project;

[0023] The collaborative relationship between the monitoring points represents the relationship between any different monitoring points in the set consisting of all monitoring points contained in the control area corresponding to each control process step in the same control process of the corresponding water conservancy project;

[0024] S22, obtaining historical fault data of each monitoring point in the corresponding water conservancy project, and obtaining the fault monitoring point association analysis set corresponding to each fault of each monitoring point; the number of fault monitoring point association analysis sets corresponding to each monitoring point is equal to the number of faults of the corresponding monitoring point, and the number of elements in the fault monitoring point association analysis set includes an empty set;

[0025] The fault monitoring point association analysis set includes all fault monitoring points whose interval between the corresponding fault time and the fault time of the corresponding monitoring point is less than the preset interval;

[0026] The union of the fault monitoring point association analysis sets corresponding to each fault of the same monitoring point is recorded as the association impact monitoring set of the corresponding monitoring point;

[0027] S23, marking the elements in the monitoring set that have a collaborative relationship with the corresponding monitoring point in the correlation impact monitoring point;

[0028] S24, obtaining the indirect associated monitoring points corresponding to each element in the directly associated monitoring point set, wherein the indirect associated monitoring point corresponding to any one element in the directly associated monitoring point set is the monitoring point corresponding to the marked element in the associated impact monitoring set corresponding to the corresponding element;

[0029] The risk inspection point set of the corresponding water conservancy project is a set consisting of each element in the corresponding directly associated monitoring point set and the indirect associated monitoring points corresponding to the corresponding elements.

[0030] Furthermore, when extracting the fault risk characteristics of each element in the risk inspection and monitoring point set of the corresponding water conservancy project, the fault risk characteristics include the self-failure risk probability and the coordinated failure risk probability, and the dth element in the risk inspection and monitoring point set of the corresponding water conservancy project is recorded as C d , the probability of self-failure risk in the fault risk characteristic corresponding to Cd is recorded as CZ d , the probability of collaborative failure risk in the failure risk feature corresponding to CD is recorded as CX d ,

[0031] The CZ d =P Cd ·P （Cd，[h，h+h1]） , where P Cd It indicates the proportion of the total number of failures corresponding to Cd in the historical data to the total number of failures of the corresponding water conservancy project; P （Cd，[h，h+h1]）It indicates the proportion of the number of faults in the interval [h, h+h1] corresponding to the water level height of Cd in the historical data based on the total number of faults corresponding to Cd;

[0032] Said , where C （d，k） Represents C d The kth element in the intersection of the set corresponding to each indirectly associated monitoring point and the risk inspection monitoring point set of the corresponding water conservancy project; kmax represents C d The total number of elements in the intersection of the set corresponding to each indirectly associated monitoring point and the risk inspection monitoring point set of the corresponding water conservancy project; P （d，k） Indicates that C in historical data （d，k） The corresponding total number of failures is based on the proportion of the total number of failures of the corresponding water conservancy project; Px （d，k） Represents C d The corresponding fault monitoring point association analysis set contains C （d，k） The number of sets based on C d The proportion of the total number of fault monitoring point association analysis sets;

[0033] CZ d +ω·CX d C d The corresponding risk quantification value, ω represents the preset risk quantification factor; the elements in the risk inspection and monitoring point set of the corresponding water conservancy project are sorted in descending order of the risk quantification value, and the sorting result is used as the constructed risk quantification inspection sequence.

[0034] Furthermore, the inspection feature set includes device binding information feature data pairs corresponding to each detection robot corresponding to the corresponding water conservancy project, the first element of each device binding information feature data pair is the corresponding detection robot number, and the second element is the position of the corresponding detection robot in the corresponding water conservancy project;

[0035] In the process of generating various inspection dispatching plans for the detection robots corresponding to the corresponding water conservancy projects, each inspection dispatching plan includes the inspection routes corresponding to each detection robot. The inspection route corresponding to each detection robot is the shortest planned route for the corresponding detection robot starting from the position of the corresponding detection robot in the corresponding water conservancy project and passing through each element of the risk inspection monitoring point set assigned in the corresponding inspection dispatching plan and belonging to the corresponding water conservancy project; the route of the detection robot passing through different monitoring points from its position is generated by Beidou navigation software;

[0036] The union of the corresponding sets of each element of the risk inspection monitoring point set of the corresponding water conservancy project assigned to each detection robot in each inspection scheduling planning scheme is the risk inspection monitoring point set of the corresponding water conservancy project, and the intersections between the corresponding sets of each element of the risk inspection monitoring point set of the corresponding water conservancy project assigned to different detection robots are all empty sets; the inspection scheduling bias value of the i-th inspection scheduling planning scheme based on the risk quantification inspection sequence is recorded as D i , the calculation formula is as follows:

[0037] ,

[0038] Among them, L i represents the sum of the distances of the inspection routes corresponding to each inspection robot in the i-th inspection scheduling plan; Lmax represents the maximum value of the sum of the distances of the inspection routes corresponding to each inspection robot in each inspection scheduling plan; μ represents the preset weight coefficient; Num （i，g，j） Indicates that the number of the jth monitoring point belonging to the risk inspection monitoring point set in the inspection route of the gth detection robot in the i-th inspection scheduling plan is greater than the number of monitoring points in the risk quantification inspection sequence of the j-1th monitoring point belonging to the risk inspection monitoring point set in the inspection route of each detection robot in the i-th inspection scheduling plan, and j>1; when j=1, Num （i，g，j） =0; gi represents the number of detection robots corresponding to the i-th inspection scheduling plan; jgi represents the number of monitoring points belonging to the risk inspection monitoring point set along the inspection route of the g-th detection robot in the i-th inspection scheduling plan; DV i It represents the difference between the maximum and minimum values ​​in the inspection routes corresponding to each inspection robot in the i-th inspection scheduling plan; DVmax represents the maximum value of each DVi corresponding to different values ​​of i.

[0039] Furthermore, the inspection route corresponding to the corresponding detection robot in the inspection scheduling planning scheme with the smallest inspection scheduling deviation value corresponding to the inspection task instruction of the detection robot, and all monitoring points along the corresponding inspection route;

[0040] The monitoring points along the corresponding inspection route include elements in the risk inspection monitoring point set of the corresponding water conservancy project, as well as monitoring points that do not belong to the risk inspection monitoring point set of the corresponding water conservancy project and whose corresponding operating status data are normal.

[0041] A detection robot inspection dispatching management system based on the Internet of Things, the system includes the following modules:

[0042] An operation status acquisition module, which acquires operation status data corresponding to each monitoring point in the water conservancy project in real time through sensors, and locks the core monitoring points in the water conservancy project based on the acquired operation status data;

[0043] A risk monitoring point locking module, wherein the risk monitoring point locking module obtains rainfall forecast information within a subsequent preset time period based on the current time in the area to which the water conservancy project belongs, combines the historical rainfall forecast information of the area to which the corresponding water conservancy project belongs, predicts the water level characteristics of the corresponding water conservancy project, and locks the risk monitoring point of the corresponding water conservancy project based on the rainfall forecast information;

[0044] A directly associated monitoring point acquisition module, which extracts core monitoring points in water conservancy projects and risk monitoring points based on rainfall forecast information to construct a directly associated monitoring point set;

[0045] A risk inspection monitoring point analysis module, which combines the positions of different monitoring points in the corresponding water conservancy project and the collaborative relationship between the various monitoring points involved in the historical control process of the corresponding water conservancy project to generate indirect related monitoring points corresponding to each element in the directly related monitoring point set, and construct a risk inspection monitoring point set for the corresponding water conservancy project;

[0046] A risk quantification inspection sequence construction module, which extracts the fault risk characteristics of each element in the risk inspection monitoring point set of the corresponding water conservancy project and constructs a risk quantification inspection sequence;

[0047] Inspection scheduling analysis module, the inspection scheduling analysis module obtains the inspection feature set of the corresponding detection robot of the corresponding water conservancy project in real time through the local area network of the area to which the corresponding water conservancy project belongs; generates various inspection scheduling planning schemes of the corresponding detection robot of the corresponding water conservancy project based on the risk quantification inspection sequence; analyzes the inspection scheduling bias values ​​of different inspection scheduling planning schemes based on the risk quantification inspection sequence;

[0048] The inspection scheduling instruction management module generates an inspection task instruction set based on the inspection scheduling planning scheme with the smallest inspection scheduling deviation value, and transmits each inspection task instruction in the inspection task instruction set to the corresponding detection robot through the local area network of the area to which the corresponding water conservancy project belongs.

[0049] Furthermore, the inspection scheduling analysis module includes an inspection feature set acquisition unit, an inspection scheduling scheme planning unit and an inspection scheduling bias value calculation unit.

[0050] The inspection feature set acquisition unit acquires the inspection feature set of the detection robot corresponding to the corresponding water conservancy project in real time through the local area network of the area to which the corresponding water conservancy project belongs;

[0051] The inspection scheduling plan planning unit generates various inspection scheduling plans for the corresponding detection robots of the corresponding water conservancy projects based on the risk quantification inspection sequence;

[0052] The inspection scheduling bias value calculation unit analyzes the inspection scheduling bias values ​​of different inspection scheduling planning schemes based on risk quantification inspection sequences.

[0053] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: during the inspection and scheduling process, the present invention not only realizes the dynamic construction of the risk inspection monitoring point set through the operating status data of the monitoring points, the impact of rainfall changes on the water level of the water conservancy project, and the collaborative relationship between the various monitoring points involved in the historical control process; it also takes into account the location of the detection robot to realize dynamic analysis and accurate screening of the inspection and scheduling scheme, and realizes effective management of the inspection and scheduling of the detection robot. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0055] Figure 1 It is a structural schematic diagram of a detection robot inspection dispatching management system based on the Internet of Things of the present invention;

[0056] Figure 2 It is a flow chart of a method for inspection and dispatching management of a detection robot based on the Internet of Things in the present invention. DETAILED DESCRIPTION

[0057] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0058] See also Figure 1 The present invention provides a technical solution: a detection robot inspection dispatching management system based on the Internet of Things, the system includes the following modules:

[0059] An operation status acquisition module, which acquires the operation status data corresponding to each monitoring point in the water conservancy project in real time through sensors, and locks the core monitoring points in the water conservancy project based on the acquired operation status data;

[0060] A risk monitoring point locking module, wherein the risk monitoring point locking module obtains rainfall forecast information within a subsequent preset time period based on the current time in the area to which the water conservancy project belongs, combines the historical rainfall forecast information of the area to which the corresponding water conservancy project belongs, predicts the water level characteristics of the corresponding water conservancy project, and locks the risk monitoring point of the corresponding water conservancy project based on the rainfall forecast information;

[0061] A directly associated monitoring point acquisition module, which extracts core monitoring points in water conservancy projects and risk monitoring points based on rainfall forecast information to construct a directly associated monitoring point set;

[0062] A risk inspection monitoring point analysis module, which combines the positions of different monitoring points in the corresponding water conservancy project and the collaborative relationship between the various monitoring points involved in the historical control process of the corresponding water conservancy project to generate indirect related monitoring points corresponding to each element in the directly related monitoring point set, and construct a risk inspection monitoring point set for the corresponding water conservancy project;

[0063] A risk quantification inspection sequence construction module, which extracts the fault risk characteristics of each element in the risk inspection monitoring point set of the corresponding water conservancy project and constructs a risk quantification inspection sequence;

[0064] The inspection scheduling analysis module includes an inspection feature set acquisition unit, an inspection scheduling scheme planning unit and an inspection scheduling bias value calculation unit.

[0065] The inspection feature set acquisition unit acquires the inspection feature set of the detection robot corresponding to the corresponding water conservancy project in real time through the local area network of the area to which the corresponding water conservancy project belongs;

[0066] The inspection scheduling plan planning unit generates various inspection scheduling plans for the corresponding detection robots of the corresponding water conservancy projects based on the risk quantification inspection sequence;

[0067] The inspection scheduling bias value calculation unit analyzes the inspection scheduling bias values ​​of different inspection scheduling planning schemes based on risk quantification inspection sequences;

[0068] The inspection scheduling instruction management module generates an inspection task instruction set based on the inspection scheduling planning scheme with the smallest inspection scheduling deviation value, and transmits each inspection task instruction in the inspection task instruction set to the corresponding detection robot through the local area network of the area to which the corresponding water conservancy project belongs.

[0069] like Figure 2 As shown, a method for inspection and scheduling management of detection robots based on the Internet of Things, the method comprises the following steps:

[0070] S1. Obtain the operating status data corresponding to each monitoring point in the water conservancy project in real time through sensors, and lock the core monitoring points in the water conservancy project based on the acquired operating status data; obtain the rainfall forecast information in the subsequent preset time period based on the current time in the area to which the water conservancy project belongs, combine the historical rainfall forecast information of the area to which the corresponding water conservancy project belongs, predict the water level characteristics of the corresponding water conservancy project, and lock the risk monitoring points of the corresponding water conservancy project based on the rainfall forecast information;

[0071] The operation status data includes abnormal extraction information corresponding to the collected pictures at the corresponding monitoring points, wherein the abnormal extraction information is the ratio of the crack area to the area of ​​the collected pictures, the ratio of the spalling area to the area of ​​the collected pictures, and the ratio of the corrosion area to the area of ​​the collected pictures, which are extracted after image recognition of the corresponding collected pictures;

[0072] When locking the core monitoring points in the water conservancy project, obtain the preset fixed core monitoring points of the corresponding water conservancy project, and compare the various data in the abnormal extraction information in the operation status data corresponding to each monitoring point in the corresponding water conservancy project with the preset abnormal extraction threshold of the corresponding item of the corresponding monitoring point.

[0073] All monitoring points in the corresponding water conservancy project where the data in the corresponding abnormal extraction information is greater than or equal to the preset abnormal extraction threshold of the corresponding item of the corresponding monitoring point, as well as the fixed core monitoring points preset in the corresponding water conservancy project, are recorded as core monitoring points in the corresponding water conservancy project;

[0074] The following steps are involved in locking the risk monitoring points of the corresponding water conservancy projects based on rainfall forecast information:

[0075] S11, obtaining a data pair consisting of rainfall forecast information in a subsequent preset time period based on the current time in the area to which the water conservancy project belongs and the water level height in the monitoring area corresponding to the current water conservancy project as the water conservancy environment characteristics at the current time; the rainfall forecast information includes the duration corresponding to the corresponding time period and the corresponding precipitation depth prediction value in the corresponding time period;

[0076] S12, obtaining historical rainfall forecast information of the area to which the corresponding water conservancy project belongs, and constructing the water level change in the water conservancy project monitoring area respectively associated with different water conservancy environmental characteristics in the historical data; the water level change in the water conservancy project monitoring area associated with each water conservancy environmental characteristic is the maximum difference between the water level height in the monitoring area of ​​the corresponding water conservancy project in the corresponding time period in the corresponding water conservancy environmental characteristic and the water level height in the corresponding monitoring area in the corresponding water conservancy environmental characteristic;

[0077] S13, according to the different water conservancy environmental characteristics in the historical data, the water level changes in the water conservancy project monitoring area are respectively associated and mapped, and the water level changes in the water conservancy project monitoring area associated and mapped with the water conservancy environmental characteristics at the current time are matched, recorded as the water level associated mutation amount, and the data pair consisting of the water level height in the monitoring area corresponding to the current water conservancy project and the obtained water level associated mutation amount is used as the water level characteristic prediction result of the corresponding water conservancy project;

[0078] S14. Obtain a set of monitoring points whose water level in the monitoring area corresponding to the water conservancy project is covered in the interval [h, h+h1], which is recorded as a risk monitoring set. Any element in the risk monitoring set corresponds to a risk monitoring point of a corresponding water conservancy project based on rainfall forecast information; h represents the water level in the monitoring area corresponding to the current water conservancy project in the water level characteristic prediction result of the corresponding water conservancy project; h1 represents the water level correlation mutation amount in the water level characteristic prediction result of the corresponding water conservancy project.

[0079] S2. Extract the core monitoring points in the water conservancy project and the risk monitoring points based on rainfall forecast information, construct a directly associated monitoring point set, combine the positions of different monitoring points in the corresponding water conservancy project and the collaborative relationship between the various monitoring points involved in the historical control process of the corresponding water conservancy project, generate indirect associated monitoring points corresponding to each element in the directly associated monitoring point set, and construct a risk inspection monitoring point set for the corresponding water conservancy project;

[0080] The directly associated monitoring point set includes all core monitoring points in the water conservancy project and all risk monitoring points based on rainfall forecast information;

[0081] The method for generating the indirect associated monitoring point corresponding to each element in the directly associated monitoring point set comprises the following steps:

[0082] S21, obtaining the positions between different monitoring points in the corresponding water conservancy project and the collaborative relationship between various monitoring points involved in the historical control process of the corresponding water conservancy project;

[0083] The collaborative relationship between the monitoring points represents the relationship between any different monitoring points in the set consisting of all monitoring points contained in the control area corresponding to each control process step in the same control process of the corresponding water conservancy project;

[0084] S22, obtaining historical fault data of each monitoring point in the corresponding water conservancy project, and obtaining the fault monitoring point association analysis set corresponding to each fault of each monitoring point; the number of fault monitoring point association analysis sets corresponding to each monitoring point is equal to the number of faults of the corresponding monitoring point, and the number of elements in the fault monitoring point association analysis set includes an empty set;

[0085] The fault monitoring point association analysis set includes all fault monitoring points whose interval between the corresponding fault time and the fault time of the corresponding monitoring point is less than the preset interval;

[0086] The union of the fault monitoring point association analysis sets corresponding to each fault of the same monitoring point is recorded as the association impact monitoring set of the corresponding monitoring point;

[0087] S23, marking the elements in the monitoring set that have a collaborative relationship with the corresponding monitoring point in the correlation impact monitoring point;

[0088] S24, obtaining the indirect associated monitoring points corresponding to each element in the directly associated monitoring point set, wherein the indirect associated monitoring point corresponding to any one element in the directly associated monitoring point set is the monitoring point corresponding to the marked element in the associated impact monitoring set corresponding to the corresponding element;

[0089] The risk inspection point set of the corresponding water conservancy project is a set consisting of each element in the corresponding directly associated monitoring point set and the indirect associated monitoring points corresponding to the corresponding elements.

[0090] S3, extract the fault risk characteristics of each element in the risk inspection monitoring point set of the corresponding water conservancy project, and construct a risk quantification inspection sequence;

[0091] When extracting the fault risk characteristics of each element in the risk inspection and monitoring point set of the corresponding water conservancy project, the fault risk characteristics include the self-failure risk probability and the coordinated failure risk probability. The dth element in the risk inspection and monitoring point set of the corresponding water conservancy project is recorded as C d , the probability of self-failure risk in the fault risk characteristic corresponding to Cd is recorded as CZ d , the probability of collaborative failure risk in the failure risk feature corresponding to CD is recorded as CX d ,

[0092] The CZ d =P Cd ·P （Cd，[h，h+h1]） , where P Cd It indicates the proportion of the total number of failures corresponding to Cd in the historical data to the total number of failures of the corresponding water conservancy project; P （Cd，[h，h+h1]） It indicates the proportion of the number of faults in the interval [h, h+h1] corresponding to the water level height of Cd in the historical data based on the total number of faults corresponding to Cd;

[0093] Said , where C （d，k） Represents C d The kth element in the intersection of the set corresponding to each indirectly associated monitoring point and the risk inspection monitoring point set of the corresponding water conservancy project; kmax represents C dThe total number of elements in the intersection of the set corresponding to each indirectly associated monitoring point and the risk inspection monitoring point set of the corresponding water conservancy project; P （d，k） Indicates that C in historical data （d，k） The corresponding total number of failures is based on the proportion of the total number of failures of the corresponding water conservancy project; Px （d，k） Represents C d The corresponding fault monitoring point association analysis set contains C （d，k） The number of sets based on C d The proportion of the total number of fault monitoring point association analysis sets;

[0094] CZ d +ω·CX d C d The corresponding risk quantification value, ω represents the preset risk quantification factor; the elements in the risk inspection and monitoring point set of the corresponding water conservancy project are sorted in descending order of the risk quantification value, and the sorting result is used as the constructed risk quantification inspection sequence.

[0095] S4. Obtain the inspection feature set of the corresponding detection robot of the corresponding water conservancy project in real time through the local area network of the area to which the corresponding water conservancy project belongs; generate various inspection scheduling planning schemes of the corresponding detection robot of the corresponding water conservancy project based on the risk quantification inspection sequence; analyze the inspection scheduling bias values ​​of different inspection scheduling planning schemes based on the risk quantification inspection sequence;

[0096] The inspection feature set includes device binding information feature data pairs corresponding to each detection robot corresponding to the corresponding water conservancy project, the first element of each device binding information feature data pair is the corresponding detection robot number, and the second element is the position of the corresponding detection robot in the corresponding water conservancy project;

[0097] In the process of generating various inspection dispatching plans for the detection robots corresponding to the corresponding water conservancy projects, each inspection dispatching plan includes the inspection routes corresponding to each detection robot. The inspection route corresponding to each detection robot is the shortest planned route for the corresponding detection robot starting from the position of the corresponding detection robot in the corresponding water conservancy project and passing through each element of the risk inspection monitoring point set assigned in the corresponding inspection dispatching plan and belonging to the corresponding water conservancy project; the route of the detection robot passing through different monitoring points from its position is generated by Beidou navigation software;

[0098] The union of the corresponding sets of each element of the risk inspection monitoring point set of the corresponding water conservancy project assigned to each detection robot in each inspection scheduling planning scheme is the risk inspection monitoring point set of the corresponding water conservancy project, and the intersections between the corresponding sets of each element of the risk inspection monitoring point set of the corresponding water conservancy project assigned to different detection robots are all empty sets; the inspection scheduling bias value of the i-th inspection scheduling planning scheme based on the risk quantification inspection sequence is recorded as D i , the calculation formula is as follows:

[0099] ,

[0100] Among them, L i represents the sum of the distances of the inspection routes corresponding to each inspection robot in the i-th inspection scheduling plan; Lmax represents the maximum value of the sum of the distances of the inspection routes corresponding to each inspection robot in each inspection scheduling plan; μ represents the preset weight coefficient; Num （i，g，j） Indicates that the number of the jth monitoring point belonging to the risk inspection monitoring point set in the inspection route of the gth detection robot in the i-th inspection scheduling plan is greater than the number of monitoring points in the risk quantification inspection sequence of the j-1th monitoring point belonging to the risk inspection monitoring point set in the inspection route of each detection robot in the i-th inspection scheduling plan, and j>1; when j=1, Num （i，g，j） =0; gi represents the number of detection robots corresponding to the i-th inspection scheduling plan; jgi represents the number of monitoring points belonging to the risk inspection monitoring point set along the inspection route of the g-th detection robot in the i-th inspection scheduling plan; DV i It represents the difference between the maximum and minimum values ​​in the inspection routes corresponding to each inspection robot in the i-th inspection scheduling plan; DVmax represents the maximum value of each DVi corresponding to different values ​​of i.

[0101] S5. Generate an inspection task instruction set based on the inspection scheduling planning scheme with the smallest inspection scheduling bias value, and transmit each inspection task instruction in the inspection task instruction set to the corresponding detection robot through the local area network of the area to which the corresponding water conservancy project belongs.

[0102] The inspection route corresponding to the corresponding detection robot in the inspection scheduling planning scheme with the smallest inspection scheduling deviation value corresponding to the inspection task instruction of the detection robot, and all monitoring points along the corresponding inspection route;

[0103] The monitoring points along the corresponding inspection route include elements in the risk inspection monitoring point set of the corresponding water conservancy project, as well as monitoring points that do not belong to the risk inspection monitoring point set of the corresponding water conservancy project and whose corresponding operating status data are normal.

[0104] In this embodiment, the inspection task instructions corresponding to the detection robot are updated once every preset time period, and before the inspection task instructions currently being executed by the detection robot are completed, the newly received inspection task instructions will be cached in the database. After all the inspection task instructions in the inspection task instruction set to which the original inspection task instructions belong are completed, the detection robot will execute the newly received inspection task instructions cached in the database; before the inspection task instructions currently being executed by the detection robot are completed, if the corresponding detection robot receives multiple inspection task instructions, the corresponding database caches the most recently received inspection task instructions, and the remaining inspection task instructions are deleted.

[0105] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0106] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for inspection and dispatch management of detection robots based on the Internet of Things, characterized in that: The method comprises the following steps: S1. Obtain the operating status data corresponding to each monitoring point in the water conservancy project in real time through sensors, and lock the core monitoring points in the water conservancy project based on the acquired operating status data; obtain the rainfall forecast information in the subsequent preset time period based on the current time in the area to which the water conservancy project belongs, combine the historical rainfall forecast information of the area to which the corresponding water conservancy project belongs, predict the water level characteristics of the corresponding water conservancy project, and lock the risk monitoring points of the corresponding water conservancy project based on the rainfall forecast information; S2. Extract the core monitoring points in the water conservancy project and the risk monitoring points based on rainfall forecast information, construct a directly associated monitoring point set, combine the positions of different monitoring points in the corresponding water conservancy project and the collaborative relationship between the various monitoring points involved in the historical control process of the corresponding water conservancy project, generate indirect associated monitoring points corresponding to each element in the directly associated monitoring point set, and construct a risk inspection monitoring point set for the corresponding water conservancy project; S3, extract the fault risk characteristics of each element in the risk inspection monitoring point set of the corresponding water conservancy project, and construct a risk quantification inspection sequence; S4. Obtain the inspection feature set of the corresponding detection robot of the corresponding water conservancy project in real time through the local area network of the area to which the corresponding water conservancy project belongs; generate various inspection scheduling planning schemes of the corresponding detection robot of the corresponding water conservancy project based on the risk quantification inspection sequence; analyze the inspection scheduling bias values ​​of different inspection scheduling planning schemes based on the risk quantification inspection sequence; S5. Generate an inspection task instruction set based on the inspection scheduling planning scheme with the smallest inspection scheduling bias value, and transmit each inspection task instruction in the inspection task instruction set to the corresponding detection robot through the local area network of the area to which the corresponding water conservancy project belongs; The operation status data includes abnormal extraction information corresponding to the collected pictures at the corresponding monitoring points, wherein the abnormal extraction information is the ratio of the crack area to the area of ​​the collected pictures, the ratio of the spalling area to the area of ​​the collected pictures, and the ratio of the corrosion area to the area of ​​the collected pictures, which are extracted after image recognition of the corresponding collected pictures; When locking the core monitoring points in the water conservancy project, obtain the fixed core monitoring points preset in the corresponding water conservancy project, and compare the data in the abnormal extraction information in the operation status data corresponding to each monitoring point in the corresponding water conservancy project with the preset abnormal extraction threshold of the corresponding item of the corresponding monitoring point; all monitoring points in the corresponding water conservancy project where the data in the corresponding abnormal extraction information is greater than or equal to the preset abnormal extraction threshold of the corresponding item of the corresponding monitoring point, as well as the fixed core monitoring points preset in the corresponding water conservancy project, are recorded as the core monitoring points in the corresponding water conservancy project; The following steps are involved in locking the risk monitoring points of the corresponding water conservancy projects based on rainfall forecast information: S11, obtaining a data pair consisting of rainfall forecast information in a subsequent preset time period based on the current time in the area to which the water conservancy project belongs and the water level height in the monitoring area corresponding to the current water conservancy project as the water conservancy environment characteristics at the current time; the rainfall forecast information includes the duration corresponding to the corresponding time period and the corresponding precipitation depth prediction value in the corresponding time period; S12, obtaining historical rainfall forecast information of the area to which the corresponding water conservancy project belongs, and constructing the water level change in the water conservancy project monitoring area respectively associated with different water conservancy environmental characteristics in the historical data; the water level change in the water conservancy project monitoring area associated with each water conservancy environmental characteristic is the maximum difference between the water level height in the monitoring area of ​​the corresponding water conservancy project in the corresponding time period in the corresponding water conservancy environmental characteristic and the water level height in the corresponding monitoring area in the corresponding water conservancy environmental characteristic; S13, according to the different water conservancy environmental characteristics in the historical data, the water level changes in the water conservancy project monitoring area are respectively associated and mapped, and the water level changes in the water conservancy project monitoring area associated and mapped with the water conservancy environmental characteristics at the current time are matched, recorded as the water level associated mutation amount, and the data pair consisting of the water level height in the monitoring area corresponding to the current water conservancy project and the obtained water level associated mutation amount is used as the water level characteristic prediction result of the corresponding water conservancy project; S14, obtaining a set of monitoring points consisting of the water level height in the monitoring area corresponding to the water conservancy project in the interval [h, h+h1], recorded as a risk monitoring set, wherein any element in the risk monitoring set corresponds to a risk monitoring point of the corresponding water conservancy project based on rainfall forecast information; the h represents the water level height in the monitoring area corresponding to the current water conservancy project in the water level characteristic prediction result of the corresponding water conservancy project; the h1 represents the water level correlation mutation amount in the water level characteristic prediction result of the corresponding water conservancy project; The directly associated monitoring point set includes all core monitoring points in the water conservancy project and all risk monitoring points based on rainfall forecast information; The method for generating the indirect associated monitoring point corresponding to each element in the directly associated monitoring point set comprises the following steps: S21, obtaining the positions between different monitoring points in the corresponding water conservancy project and the collaborative relationship between various monitoring points involved in the historical control process of the corresponding water conservancy project; The collaborative relationship between the monitoring points represents the relationship between any different monitoring points in the set consisting of all monitoring points contained in the control area corresponding to each control process step in the same control process of the corresponding water conservancy project; S22, obtaining historical fault data of each monitoring point in the corresponding water conservancy project, and obtaining the fault monitoring point association analysis set corresponding to each fault of each monitoring point; the number of fault monitoring point association analysis sets corresponding to each monitoring point is equal to the number of faults of the corresponding monitoring point, and the number of elements in the fault monitoring point association analysis set includes an empty set; The fault monitoring point association analysis set includes all fault monitoring points whose interval between the corresponding fault time and the fault time of the corresponding monitoring point is less than the preset interval; The union of the fault monitoring point association analysis sets corresponding to each fault of the same monitoring point is recorded as the association impact monitoring set of the corresponding monitoring point; S23, marking the elements in the monitoring set that have a collaborative relationship with the corresponding monitoring point in the correlation impact monitoring point; S24, obtaining the indirect associated monitoring points corresponding to each element in the directly associated monitoring point set, wherein the indirect associated monitoring point corresponding to any one element in the directly associated monitoring point set is the monitoring point corresponding to the marked element in the associated impact monitoring set corresponding to the corresponding element; The risk inspection point set of the corresponding water conservancy project is a set consisting of each element in the corresponding directly associated monitoring point set and the indirect associated monitoring points corresponding to the corresponding elements.

2. According to the inspection robot inspection scheduling management method based on the Internet of Things according to claim 1, it is characterized by: In step S3, the fault risk characteristics include the probability of self-failure risk and the probability of coordinated failure risk. The risk inspection monitoring points of the corresponding water conservancy project are concentrated in the first d The elements are recorded as C d , C d The corresponding fault risk probability in the fault risk characteristic is recorded as CZ d ,Will C d The probability of collaborative failure risk in the corresponding failure risk feature is recorded as CX d ; C d Corresponding to the fault risk probability in the fault risk characteristics CZ d The calculation formula is as follows: CZ d = P Cd · P （Cd，[h，h+h1] ） in, P Cd Indicates historical data C d The corresponding total number of failures is based on the proportion of the total number of failures of the corresponding water conservancy project; P （Cd，[h，h+h1]） Indicates historical data C d The number of faults corresponding to the water level in the interval [h, h+h1] is based on C d The corresponding proportion of the total number of failures; C d The probability of collaborative failure risk in the corresponding failure risk characteristics CX d The calculation formula is as follows: ， in, kmax express C d The total number of elements in the intersection of the set corresponding to each indirectly associated monitoring point and the risk inspection monitoring point set of the corresponding water conservancy project; P （d，k） Indicates historical data C （d，k） The corresponding total number of failures is based on the proportion of the total number of failures of the corresponding water conservancy project; Px （d，k） express C d The corresponding fault monitoring point correlation analysis set includes C （d，k） The number of sets is based on C d The proportion of the total number of fault monitoring point association analysis sets; C （d，k） express C d The first value in the intersection of the set corresponding to each indirect associated monitoring point and the risk inspection monitoring point set of the corresponding water conservancy project k elements; Will CZ d + ω · CX d Recorded as C d The corresponding risk quantification value is ω Represents a preset risk quantification factor; sorts the elements in the risk inspection monitoring point set of the corresponding water conservancy project in descending order of risk quantification value, and uses the sorting result as the constructed risk quantification inspection sequence.

3. The inspection and dispatching management method of a detection robot based on the Internet of Things according to claim 1 is characterized in that: The inspection feature set includes device binding information feature data pairs corresponding to each detection robot corresponding to the corresponding water conservancy project, the first element of each device binding information feature data pair is the corresponding detection robot number, and the second element is the position of the corresponding detection robot in the corresponding water conservancy project; In the process of generating each inspection dispatching plan for the detection robot corresponding to the corresponding water conservancy project, each inspection dispatching plan includes the inspection routes corresponding to each detection robot, and the inspection route corresponding to each detection robot is the shortest planned route of the corresponding detection robot starting from the position of the corresponding detection robot in the corresponding water conservancy project and passing through each element of the risk inspection monitoring point set assigned in the corresponding inspection dispatching plan and belonging to the corresponding water conservancy project; The route of the detection robot passing through different monitoring points from its current position is generated by Beidou navigation software; the union of the corresponding sets of each element of the risk inspection and monitoring point set of the corresponding water conservancy project assigned to each detection robot in each inspection scheduling planning scheme is the risk inspection and monitoring point set of the corresponding water conservancy project, and the intersections between the corresponding sets of each element of the risk inspection and monitoring point set of the corresponding water conservancy project assigned to different detection robots are all empty sets; The first i The inspection scheduling bias value of the inspection scheduling planning scheme based on the risk quantification inspection sequence is recorded as D i , the calculation formula is as follows: ， in, L i Indicates i The sum of the distances of the inspection routes corresponding to each inspection robot in the inspection scheduling plan; Lmax It represents the maximum value of the sum of the distances of the inspection routes corresponding to each inspection robot in each inspection scheduling plan; μ Indicates the preset weight coefficient; Num （i，g，j） Indicates i The inspection scheduling plan g The inspection route of the inspection robot j The number of the monitoring point belonging to the risk inspection monitoring point set in the risk quantification inspection sequence is greater than i The inspection routes of each inspection robot in the inspection scheduling plan are j -1 The number of monitoring points in the risk inspection monitoring point set that are in the risk quantification inspection sequence, and j >1; when j =1, Num （i，g，j） =0; gi Indicates i The number of detection robots corresponding to each inspection scheduling plan; Jj Indicates i The inspection scheduling plan g The number of monitoring points belonging to the risk inspection monitoring point set along the inspection route of each inspection robot; DV i Indicates i The difference between the maximum and minimum values ​​in the inspection routes corresponding to each inspection robot in the inspection scheduling plan; DVmax express i For different values, the corresponding DVi The maximum value in .

4. The inspection and dispatching management method of a detection robot based on the Internet of Things according to claim 3 is characterized in that: The inspection route corresponding to the corresponding inspection robot in the inspection scheduling planning scheme with the smallest inspection scheduling bias value corresponding to the inspection task instruction of the inspection robot, and all monitoring points along the corresponding inspection route; the monitoring points along the corresponding inspection route include elements in the risk inspection monitoring point set of the corresponding water conservancy project, and monitoring points that do not belong to the risk inspection monitoring point set of the corresponding water conservancy project and whose corresponding operating status data are normal.

5. A detection robot inspection dispatching management system based on the Internet of Things, applying a detection robot inspection dispatching management method based on the Internet of Things as described in any one of claims 1 to 4, characterized in that: The system includes the following modules: An operation status acquisition module, which acquires the operation status data corresponding to each monitoring point in the water conservancy project in real time through sensors, and locks the core monitoring points in the water conservancy project based on the acquired operation status data; A risk monitoring point locking module, wherein the risk monitoring point locking module obtains rainfall forecast information within a subsequent preset time period based on the current time in the area to which the water conservancy project belongs, combines the historical rainfall forecast information of the area to which the corresponding water conservancy project belongs, predicts the water level characteristics of the corresponding water conservancy project, and locks the risk monitoring point of the corresponding water conservancy project based on the rainfall forecast information; A directly associated monitoring point acquisition module, which extracts core monitoring points in water conservancy projects and risk monitoring points based on rainfall forecast information to construct a directly associated monitoring point set; A risk inspection monitoring point analysis module, which combines the positions of different monitoring points in the corresponding water conservancy project and the collaborative relationship between the various monitoring points involved in the historical control process of the corresponding water conservancy project to generate indirect associated monitoring points corresponding to each element in the directly associated monitoring point set, and construct a risk inspection monitoring point set for the corresponding water conservancy project; A risk quantification inspection sequence construction module, which extracts the fault risk characteristics of each element in the risk inspection monitoring point set of the corresponding water conservancy project and constructs a risk quantification inspection sequence; An inspection scheduling and analysis module, which obtains the inspection feature set of the inspection robot corresponding to the corresponding water conservancy project in real time through the local area network of the area to which the corresponding water conservancy project belongs; Based on the risk quantification inspection sequence, generate various inspection scheduling planning schemes for the corresponding detection robots of the corresponding water conservancy projects; Analyze the inspection scheduling bias values ​​of different inspection scheduling planning schemes based on risk quantification inspection sequences; The inspection and scheduling instruction management module generates an inspection task instruction set based on the inspection and scheduling planning scheme with the smallest inspection and scheduling deviation value, and transmits each inspection task instruction in the inspection task instruction set to the corresponding detection robot through the local area network of the area to which the corresponding water conservancy project belongs.

6. The inspection robot inspection dispatching management system based on the Internet of Things according to claim 5 is characterized by: The inspection scheduling analysis module includes an inspection feature set acquisition unit, an inspection scheduling scheme planning unit and an inspection scheduling bias value calculation unit. The inspection feature set acquisition unit acquires the inspection feature set of the detection robot corresponding to the corresponding water conservancy project in real time through the local area network of the area to which the corresponding water conservancy project belongs; The inspection scheduling plan planning unit generates various inspection scheduling plans for the corresponding detection robots of the corresponding water conservancy projects based on the risk quantification inspection sequence; The inspection scheduling bias value calculation unit analyzes the inspection scheduling bias values ​​of different inspection scheduling planning schemes based on risk quantification inspection sequences.

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