Water supply optimization scheduling method and system for waterworks

Abstract

The invention provides a waterworks water supply optimization scheduling method and system, and relates to the technical field of resource scheduling, and the waterworks water supply optimization scheduling method comprises the steps: obtaining real-time water supply data of a water supply route; monitoring real-time water supply data of the water supply route to obtain real-time fault nodes and real-time fault information of the water supply route; according to the real-time fault nodes and the real-time fault information, scheduling demand query is carried out through a constructed emergency scheduling model based on a water supply route, so that scheduling demand data corresponding to the real-time fault nodes are obtained; obtaining an optimal first-aid repair scheduling plan according to the scheduling demand data; and executing a corresponding scheduling task according to the optimal first-aid repair scheduling plan. According to the optimal scheduling method and system provided by the invention, the matching between the scheduled manpower and material resources and the fault site can be improved, and the emergency repair efficiency is effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of resource scheduling, and particularly to a method and system for optimizing the water supply scheduling of a waterworks. Background Art

[0002] When a water supply failure occurs in an existing waterworks, relevant water service personnel will locate the failure point and then conduct relevant valve control to prevent water resource waste and secondary disasters (such as road surface collapse). At the same time, relevant emergency personnel are notified to conduct emergency repair at the failure site.

[0003] However, since the water service personnel cannot arrive at the water supply failure site in the first place, and since the conditions of each point on the water supply route are different and relatively complex, through a unified emergency scheduling plan, it is easy to lead to unreasonable arrangements of human and material resources, and it cannot accurately match the current water supply failure, thus greatly reducing the efficiency of emergency repair. Summary of the Invention

[0004] In view of the above-mentioned disadvantages of the prior art, the purpose of the present invention is to provide a method and system for optimizing the water supply scheduling of a waterworks, which is used to solve the problem that when conducting emergency scheduling of the water supply of a waterworks in the prior art, it is difficult for the scheduled human and material resources to match the failure situation, resulting in a lag in emergency scheduling.

[0005] To achieve the above purpose and other related purposes, the present invention provides a method for optimizing the water supply scheduling of a waterworks, including: obtaining real-time water supply data of a water supply route; monitoring the real-time water supply data of the water supply route to obtain real-time failure nodes and real-time failure information of the water supply route; according to the real-time failure nodes and real-time failure information, querying scheduling requirements through an emergency scheduling model constructed based on the water supply route to obtain scheduling requirement data corresponding to the real-time failure nodes; obtaining an optimal emergency repair scheduling plan according to the scheduling requirement data; and executing corresponding scheduling tasks according to the optimal emergency repair scheduling plan.

[0006] In an embodiment of the present invention, the emergency scheduling model is constructed in the following manner: obtaining historical water supply data, historical failure nodes and historical repair data of the water supply route; updating the initial emergency scheduling model of the water supply route according to the historical water supply data; and optimizing the updated initial emergency scheduling model according to the historical failure nodes and historical repair data to obtain the emergency scheduling model.

[0007] In an embodiment of the present invention, according to historical water supply data, the initial emergency scheduling model of the water supply route is updated, including: obtaining the initial laying data of the water supply route; according to the initial laying data, obtaining scheduling features and initial parameters of the scheduling features; according to the initial laying data, scheduling features and initial parameters of the scheduling features, constructing an initial emergency scheduling model, wherein the initial emergency scheduling model includes a plurality of network nodes; according to historical water supply data, increasing or decreasing the scheduling features and initial parameters to obtain updated scheduling features and updated parameters; and updating the initial emergency scheduling model of the water supply route through the updated scheduling features and updated parameters.

[0008] In an embodiment of the present invention, according to historical water supply data, increasing or decreasing the scheduling features and initial parameters to obtain updated scheduling features and updated parameters includes: performing feature search on historical water supply data to obtain historical scheduling features and historical parameters corresponding to the historical scheduling features; comparing the historical scheduling features and historical parameters with the scheduling features and initial parameters respectively; if the scheduling features and the historical scheduling features are different, adding the historical scheduling features different from the scheduling features and their corresponding historical parameters to the scheduling features to obtain updated scheduling features; if the scheduling features and the historical scheduling features are the same, replacing the initial parameters with the historical parameters corresponding to the historical scheduling features whose difference from the initial parameters corresponding to the scheduling features is greater than a set value to obtain updated parameters.

[0009] In an embodiment of the present invention, according to historical fault nodes and historical repair data, the updated initial emergency scheduling model is optimized to obtain an emergency scheduling model, including: finding the first part of network nodes in the updated initial emergency scheduling model corresponding to the historical fault nodes; obtaining differential scheduling features and parameter differences according to the historical repair data corresponding to the historical fault nodes and the updated scheduling features and updated parameters of the first part of network nodes; adjusting the updated scheduling features and updated parameters of the first part of network nodes according to the differential scheduling features and parameter differences to obtain first corrected scheduling features and first corrected parameters; determining the unit length comprehensive influence attenuation degree of each second part of network nodes around the first part of network nodes according to the differential scheduling features and parameter differences; adjusting the updated scheduling features and updated parameters of the second part of network nodes according to the differential scheduling features, parameter differences and unit length comprehensive influence attenuation degree to obtain second corrected scheduling features and second corrected parameters; and optimizing the updated initial emergency scheduling model according to the first corrected scheduling features, first corrected parameters, second corrected scheduling features and second corrected parameters to obtain an emergency scheduling model.

[0010] In an embodiment of the present invention, determining the unit length comprehensive influence attenuation degree of each second part of network nodes around the first part of network nodes according to the differential scheduling feature and the parameter difference includes: obtaining the first unit length influence attenuation degree according to the differential scheduling feature; obtaining the second unit length influence attenuation degree according to the parameter difference under the differential scheduling feature; and determining the unit length comprehensive influence attenuation degree of each second part of network nodes around the first part of network nodes according to the first unit length influence attenuation degree and the second unit length influence attenuation degree.

[0011] In an embodiment of the present invention, according to the real-time fault nodes and real-time fault information, querying the scheduling requirements through the constructed emergency scheduling model based on the water supply route to obtain the scheduling requirement data corresponding to the real-time fault nodes includes: searching for target network nodes in the emergency scheduling model according to the real-time fault nodes to obtain the target scheduling features and target parameters of the target network nodes; obtaining the feature adjustment factor and the parameter adjustment factor according to the real-time fault information; and adjusting the target scheduling features and target parameters according to the feature adjustment factor and the parameter adjustment factor to obtain the real-time scheduling features and real-time parameters as the scheduling requirement data corresponding to the real-time fault nodes.

[0012] In an embodiment of the present invention, the scheduling requirement data includes real-time scheduling features and real-time parameters; obtaining the optimal emergency repair scheduling plan according to the scheduling requirement data includes: searching for the nearest location of the real-time fault nodes according to the real-time scheduling features to obtain relevant sites with corresponding emergency resource items; querying the resource reserves of the relevant sites according to the real-time parameters to determine the final site combination and resource scheduling and allocation information; and obtaining the optimal emergency repair scheduling plan according to the site combination and resource scheduling and allocation information.

[0013] In an embodiment of the present invention, it further includes: after the scheduling task is completed, optimizing the emergency scheduling model with the real-time fault nodes and the real-time emergency repair data corresponding to the real-time fault nodes.

[0014] To achieve the above and other related purposes, the present invention also provides a water supply optimization scheduling system for a waterworks, including: an acquisition unit for acquiring the real-time water supply data of the water supply route; a monitoring unit for monitoring the real-time water supply data of the water supply route to obtain the real-time fault nodes and real-time fault information of the water supply route; a query unit for querying the scheduling requirements through the constructed emergency scheduling model based on the water supply route according to the real-time fault nodes and real-time fault information to obtain the scheduling requirement data corresponding to the real-time fault nodes; a retrieval unit for obtaining the optimal emergency repair scheduling plan according to the scheduling requirement data; and an execution unit for performing the corresponding scheduling task according to the optimal emergency repair scheduling plan.

[0015] As described above, a method and system for optimizing the water supply scheduling of a waterworks according to the present invention have the following beneficial effects: when a water supply failure occurs, by using the real-time failure nodes and real-time failure information, it is possible to quickly query the scheduling demand data required for emergency failures through the emergency scheduling model of the water supply route, and then arrange the corresponding optimal emergency repair scheduling plan based on the scheduling resources to complete the emergency command and dispatch. This can effectively improve the timely personnel arrangement and emergency repair efficiency when the water supply is abnormal, and reduce the scheduling difficulty of resources and personnel during emergency command. Moreover, during the construction of the emergency scheduling model, by using historical water supply data, historical failure nodes, and historical emergency repair data, the continuous update and optimization of the initial emergency scheduling model can effectively ensure the query accuracy of the emergency scheduling model for scheduling demand data including real-time scheduling characteristics and real-time parameters. While improving the efficiency during emergency scheduling, it also ensures the accuracy of the corresponding scheduling resources, thereby improving the solution efficiency for real-time failures that occur. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a schematic flow chart of the method for optimizing the water supply scheduling of a waterworks provided by an embodiment of the present invention.

[0017] Figure 2 It is shown as a structural block diagram of the system for optimizing the water supply scheduling of a waterworks provided by an embodiment of the present invention.

[0018] Figure 3 It is shown as a schematic structural diagram of an electronic device according to an embodiment of the present invention.

[0019] Description of Component Labels Electronic device 1; System for optimizing the water supply scheduling of a waterworks 11; Memory 12; Processor 13; Acquisition unit 111; Monitoring unit 112; Query unit 113; Retrieval unit 114; Execution unit 115. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0020] The following specific examples illustrate the embodiments of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that, without conflict, the following embodiments and the features in the embodiments can be combined with each other.

[0021] It should be noted that the illustrations provided in the following embodiments only schematically illustrate the basic concept of the present invention. Therefore, only the components related to the present invention are shown in the drawings, rather than being drawn according to the number, shape, and size of the components in actual implementation. The type, quantity, and proportion of each component in actual implementation can be arbitrarily changed, and the component layout type may also be more complex.

[0022] In the following description, a large number of details are explored to provide a more thorough explanation of the embodiments of the present invention. However, it is obvious to those skilled in the art that the embodiments of the present invention can be implemented without these specific details. In other embodiments, well-known structures and devices are shown in the form of block diagrams rather than in detail to avoid making the embodiments of the present invention difficult to understand.

[0023] The present invention provides a method for optimizing the water supply scheduling of a waterworks. By monitoring real-time water supply data, relevant water supply faults can be quickly responded to; and when responding to a fault, the real-time fault nodes and corresponding real-time fault information obtained through monitoring can be used to query the scheduling requirements corresponding to the current fault for the corresponding real-time fault nodes. Furthermore, the actual situation corresponding to nodes at different positions on the water supply route can be used to query the required scheduling resources, and then based on this scheduling resource, an appropriate optimal emergency repair scheduling plan can be arranged to complete the emergency command and dispatch, which can effectively improve the timely personnel arrangement and repair efficiency during water supply anomalies and reduce the scheduling difficulty of human and material resources during emergency command.

[0024] Figure 1 The flowchart of the method for optimizing the water supply scheduling of a waterworks in an exemplary embodiment of the present application is shown, which is applied to the waterworks water supply optimization scheduling system and includes steps S10 - step S50. The following will be combined with Figure 1 to elaborate on the technical solution of the present application in detail.

[0025] First, step S10 is executed to obtain the real-time water supply data of the water supply route.

[0026] The real-time water supply data can be collected by installing various sensor devices on the water supply line and then uploaded to the waterworks water supply optimization scheduling system to achieve the collection of the real-time water supply data of the water supply line by the waterworks water supply optimization scheduling system. Among them, the sensor devices can include sensors such as pressure, flow rate, water quality, water level, temperature, vibration, and leakage detection. Each sensor has a different function and obtains different data. For example, a pressure sensor monitors the pipe network pressure, a flow rate sensor monitors the flow velocity and flow rate, and a water quality sensor monitors residual chlorine, turbidity, etc.

[0027] Next, step S20 is executed: Monitor the real-time water supply data of the water supply route to obtain the real-time fault nodes and real-time fault information of the water supply route.

[0028] After the real-time water supply data is obtained by the water supply optimization and dispatching system of the waterworks, the real-time water supply data can be monitored. When a fault is detected in the real-time water supply data of the water supply route, the corresponding real-time fault nodes and real-time fault information are generated. For example, when a water supply fault such as a pipe burst occurs, the pipe network pressure drops suddenly, and a pressure gradient difference is formed upstream and downstream of the leak point. By analyzing the time-series data of the pressure sensor network and combining with the hydraulic model inversion, the current real-time fault nodes can be quickly and accurately located, and the fault type such as pipe burst and the length range affected by the fault can be used as real-time fault information.

[0029] Next, step S30 is executed. According to the real-time fault nodes and real-time fault information, a dispatching requirement query is performed through the constructed emergency dispatching model based on the water supply route to obtain the dispatching requirement data corresponding to the real-time fault nodes.

[0030] After the water supply optimization and dispatching system of the waterworks obtains the real-time fault nodes and real-time fault information of the water supply route, the real-time fault nodes and real-time fault information are input into the emergency dispatching model based on the water supply route to query the dispatching requirements corresponding to this fault, so as to obtain the dispatching requirement data corresponding to the real-time fault nodes. The dispatching requirement data may include resources such as manpower and material resources required for dispatching. For example, the human resources may be what skills the repair workers need and how many repair workers are needed. Of course, it may also be other human resources that need to be dispatched according to needs; the material resources may be what mechanical equipment and instruments are needed, how many mechanical equipment are needed, how many instruments are needed, etc. Of course, it may also be other possible material resources required.

[0031] Among them, the emergency dispatching model can be further constructed in the following way: Obtain the historical water supply data, historical fault nodes and historical emergency repair data of the water supply route; Update the initial emergency dispatching model of the water supply route according to the historical water supply data; Optimize the updated initial emergency dispatching model according to the historical fault nodes and historical emergency repair data to obtain the emergency dispatching model.

[0032] In the process of constructing the emergency dispatching model, it can be seen that the emergency dispatching model is obtained through continuous update and optimization. It can update the model based on the historical water supply data collected each time, and can further optimize the model based on the historical fault nodes and historical emergency repair data corresponding to each historical fault to ensure the accuracy of the emergency dispatching model when predicting the dispatching requirement data corresponding to the real-time fault nodes, to ensure the emergency repair efficiency when dealing with each fault, and at the same time ensure the efficiency of water supply fault recovery.

[0033] When updating the initial emergency dispatch model, according to historical water supply data, updating the initial emergency dispatch model of the water supply route may further include: Obtain the initial laying data of the water supply route; According to the initial laying data, obtain the dispatch characteristics and the initial parameters of the dispatch characteristics; According to the initial laying data, the dispatch characteristics and the initial parameters of the dispatch characteristics, construct an initial emergency dispatch model, where the initial emergency dispatch model includes multiple network nodes; According to historical water supply data, increase or decrease the dispatch characteristics and the initial parameters to obtain updated dispatch characteristics and updated parameters; Update the initial emergency dispatch model of the water supply route through the updated dispatch characteristics and the updated parameters.

[0034] Before updating the initial emergency dispatch model using historical water supply data, it is necessary to first construct the initial emergency dispatch model. When constructing the initial emergency dispatch model, during the process of laying water supply pipelines, the initial laying data during the pipeline laying process can be recorded, and then according to the requirements of the initial emergency dispatch model, the relevant dispatch features and the initial parameters of the dispatch features in the initial laying data can be extracted. The dispatch features can be the replacement water pipes corresponding to the pipeline connection structure required for emergency excavation, the instruments required for water pipe installation, the personnel required for water pipe installation, the personnel required for emergency excavation, etc.; the initial features can be the quantities of replacement water pipes, the instruments required for water pipe installation, the personnel required for water pipe installation, the personnel required for emergency excavation, etc. Then, according to the actual laying route, laying depth, laying soil layer and other information of the initial laying data, and combined with the extracted dispatch features and the initial parameters of the dispatch features, the initial emergency dispatch model can be realized. In this initial emergency dispatch model, each network node is configured with corresponding information such as initial laying data, dispatch features and the initial parameters of the dispatch features. After obtaining the initial emergency dispatch model, in order to ensure the emergency dispatch accuracy of the initial emergency dispatch model, it is also possible to increase or decrease and adjust the dispatch features and initial parameters according to the historical water supply data collected historically. After the adjustment is completed, the updated dispatch features and updated parameters are obtained accordingly, and then the initial emergency dispatch model of the water supply route is updated using the updated dispatch features and updated parameters. The historical water supply data obtained includes sensor data collected by sensors such as pressure, flow rate, water quality, water level, temperature, vibration, and leakage detection, and can also include soil humidity sensors, leak conductance sensors, gas sensors, etc. For example, in the initial laying data, it may be affected by soil humidity. The soil humidity at the time of initial laying completion can facilitate excavation due to weather scenarios such as rain. As time changes, the soil humidity at that location will change further, so it is necessary to further adjust the dispatch features and initial parameters based on historical water supply data to ensure that the basic parameters of the initial emergency dispatch model can accurately respond to emergency dispatch requirements.

[0035] Adjusting the dispatch features and initial parameters up or down according to historical water supply data to obtain updated dispatch features and updated parameters may further include: Performing feature search on historical water supply data to obtain historical dispatch features and the historical parameters corresponding to the historical dispatch features; Comparing the historical dispatch features and historical parameters with the dispatch features and initial parameters respectively; If the dispatch features and the historical dispatch features are different, then add the historical dispatch features that are different from the dispatch features and their corresponding historical parameters to the dispatch features to obtain updated dispatch features; If the scheduling feature is the same as the historical scheduling feature, then replace the initial parameter corresponding to the historical scheduling feature whose difference from the initial parameter corresponding to the scheduling feature is greater than the set value with the historical parameter to obtain the updated parameter.

[0036] When adjusting the scheduling feature and the initial parameter using the historical water supply data, the historical water supply data can be first subjected to feature search to find the historical scheduling feature and the corresponding historical parameter existing in the historical water supply data. Then, compare the historical scheduling feature with the corresponding scheduling feature in the initial emergency scheduling model and compare the historical parameter with the corresponding initial parameter in the initial emergency scheduling model, so as to realize the increase or decrease adjustment of the scheduling feature and the initial parameter. Specifically, when the scheduling feature is different from the historical scheduling feature, then add the historical scheduling feature different from the scheduling feature and its corresponding historical parameter to the scheduling feature to obtain the updated scheduling feature. Of course, the difference between the scheduling feature and the historical scheduling feature may also be that the historical water supply data shows that the corresponding influence has been eliminated, and the corresponding scheduling feature and initial parameter can be deleted and adjusted, which can also be understood as adding the historical scheduling feature different from the scheduling feature and its corresponding historical parameter to the scheduling feature. For example, when the historical scheduling feature includes , and the corresponding scheduling feature in the initial emergency scheduling model includes , if there is a historical scheduling feature that is the same as the corresponding scheduling feature in the initial emergency scheduling model, then the remaining in is different from in and . If does not exist a certain feature in when comparing with , then this feature can be added to ; if has an extra feature when comparing with , then in

[0037] In addition, there will be cases where the scheduling features and historical scheduling features are the same. When the scheduling features and historical scheduling features are the same, it is necessary to further compare the historical parameters with the corresponding initial parameters in the initial emergency scheduling model. If the difference between the historical parameters and the initial parameters is greater than the set value, the historical parameters can be used to replace the corresponding initial parameters, so as to obtain updated parameters. The updated parameters can be obtained by adding or subtracting the difference from the initial parameters. For example, when the historical scheduling features include , and the corresponding scheduling features in the initial emergency scheduling model include , if there is a historical scheduling feature that is the same as the corresponding scheduling feature in the initial emergency scheduling model, then the remaining in is different from in and . For and , each historical parameter corresponding to is compared with each initial parameter corresponding to . And when the two are the same, it includes the scheduling features and initial parameters in the corresponding initial emergency scheduling model. However, when the two are different and the difference between them exceeds the set value, the corresponding initial parameters are adjusted.

[0038] It should be noted that the acquisition of historical water supply data can be periodic. Therefore, the initial emergency scheduling model can be updated periodically according to the number of times of obtaining historical water supply data. Each update can use the scheduling features and parameters of the previous initial emergency scheduling model as the initial scheduling features and initial parameters to update the initial emergency scheduling model based on the historical water supply data of the next cycle.

[0039] When optimizing the initial emergency scheduling model, according to the historical fault nodes and historical repair data, optimizing the updated initial emergency scheduling model to obtain the emergency scheduling model may further include: Finding the first part of network nodes in the updated initial emergency scheduling model corresponding to the historical fault nodes; Obtaining the differential scheduling features and parameter differences according to the historical repair data corresponding to the historical fault nodes and the updated scheduling features and updated parameters of the first part of network nodes; Adjusting the updated scheduling features and updated parameters of the first part of network nodes according to the differential scheduling features and parameter differences to obtain the first corrected scheduling features and the first corrected parameters; Determine the comprehensive influence attenuation degree per unit length of each second - part network node around the first - part network node according to the differential scheduling feature and the parameter difference; Adjust the updated scheduling feature and updated parameter of the second - part network node according to the differential scheduling feature, parameter difference and comprehensive influence attenuation degree per unit length to obtain the second - corrected scheduling feature and second - corrected parameter; Optimize the updated initial emergency scheduling model according to the first - corrected scheduling feature, first - corrected parameter, second - corrected scheduling feature and second - corrected parameter to obtain the emergency scheduling model.

[0040] The historical fault nodes and historical repair data are the actual data corresponding to historical repairs, which can accurately correct and optimize the initial emergency scheduling model. Specifically, the initial emergency scheduling model includes at least two parts of network nodes. The first - part network nodes are updated through historical fault nodes, and the second - part network nodes are predicted and updated based on historical fault nodes.

[0041] When selecting the first - part network nodes, according to the specific positions of the historical fault nodes in the corresponding water supply routes, select the corresponding network nodes in the updated initial emergency scheduling model as the first - part network nodes. Then, obtain the differential scheduling feature and parameter difference by using the historical repair data corresponding to the historical fault nodes and the updated scheduling feature and updated parameter of the first - part network nodes. Specifically, extract the repair scheduling features and repair parameters in the actual repair process according to the historical repair data corresponding to the historical fault nodes, and then calculate the differences between them and the updated scheduling feature and updated parameter, so as to obtain the differential scheduling feature (that is, there will be additional features or reduced features compared with the updated scheduling feature) and parameter difference (that is, the difference between the repair parameter and the updated parameter). Based on the differential scheduling feature and parameter difference, the updated scheduling feature and updated parameter of the first - part network nodes and each second - part network node around the first - part network node can be corrected and adjusted respectively. Specifically, first directly correct and adjust the updated scheduling feature and updated parameter of the first - part network nodes according to the differential scheduling feature and parameter difference to obtain the first - corrected scheduling feature and first - corrected parameter; then generate the comprehensive influence attenuation degree per unit length of each second - part network node around the first - part network node according to the differential scheduling feature and parameter difference, and then use the comprehensive influence attenuation degree per unit length to adjust the updated scheduling feature and updated parameter of each second - part network node in turn to obtain the second - corrected scheduling feature and second - corrected parameter. Further, use the first - corrected scheduling feature, first - corrected parameter, second - corrected scheduling feature and second - corrected parameter to optimize the updated initial emergency scheduling model to obtain the emergency scheduling model.

[0042] Specifically, according to the differential scheduling feature and the parameter difference, determine the comprehensive influence attenuation degree per unit length of each second part of network nodes around the first part of network nodes, including: According to the differential scheduling feature, obtain the first influence attenuation degree per unit length; According to the parameter difference under the differential scheduling feature, obtain the second influence attenuation degree per unit length; According to the first influence attenuation degree per unit length and the second influence attenuation degree per unit length, determine the comprehensive influence attenuation degree per unit length of each second part of network nodes around the first part of network nodes.

[0043] When using the differential scheduling feature and the parameter difference to determine the comprehensive influence attenuation degree per unit length of each second part of network nodes around the first part of network nodes, first determine the corresponding first influence attenuation degree per unit length according to the differential scheduling feature. For example, if some differential scheduling features have a strong influence persistence on the water supply route, then the first influence attenuation degree per unit length at this time is lower, and the influence distance of this differential scheduling feature on the water supply route is longer; for example, during emergency repair, it is found that due to the accumulation of scale and the like on the water pipes over a long time, it is difficult to disassemble the water pipes, and such situations may be reflected in the surrounding water pipes. Therefore, the first influence attenuation degree per unit length corresponding to such differential scheduling features is small. Of course, there are also some differential scheduling features with weak influence persistence on the water supply route. In this case, the first influence attenuation degree per unit length is shorter, and the influence distance of this differential scheduling feature on the water supply route is shorter; for example, during emergency repair, it is found that due to accidental construction near the historical fault node recently, the soil humidity in this area has changed, and the diffusion degree of this change to the surrounding area is small. At this time, the comprehensive influence attenuation degree per unit length is large, and the influence length on the nearby water supply route is short.

[0044] Then, for the parameter difference under the differential scheduling feature, the corresponding second influence attenuation degree per unit length can be selected according to the different parameter difference ranges corresponding to each differential scheduling feature, so as to determine the comprehensive influence attenuation degree per unit length of each second part of network nodes around the first part of network nodes in combination with the first influence attenuation degree per unit length and the second influence attenuation degree per unit length.

[0045] Specifically, after obtaining the differential scheduling feature and the corresponding parameter difference utilize the corresponding differential scheduling feature and the corresponding parameter difference to directly adjust the updated scheduling feature and updated parameters of the first part of network nodes. If the updated scheduling feature of the first part of network nodes lacks the differential scheduling feature , then add this differential scheduling feature to the update scheduling feature of the first part of network nodes , if the update scheduling feature of the first part of network nodes has an extra differential scheduling feature , then delete this differential scheduling feature from the update scheduling feature of the first part of network nodes . Similarly, if the parameter difference is a positive value, then add this parameter difference to the update parameter , and if the parameter difference is a negative value, then subtract this parameter difference from the update parameter .

[0046] In addition, for each second part of network nodes around the first part of network nodes, first according to the influence persistence of the differential scheduling feature , for example, the influence attenuation degree per unit length of the first unit length can be obtained by looking up a table , and then according to the corresponding parameter difference within the range of parameter differences, look up the table to obtain the corresponding influence attenuation degree per unit length of the second unit length . Then add the influence attenuation degree per unit length of the first unit length and the influence attenuation degree per unit length of the second unit length for superposition calculation to obtain the comprehensive influence attenuation degree per unit length on each second part of network nodes around the first part of network nodes , where, according to the comprehensive influence attenuation degree per unit length , the differential scheduling feature and the corresponding parameter difference with respect to the first part of network nodes have an influence distance of , and then according to this influence distance allocate corresponding attenuation parameters to each second part of network nodes. For example, when the distance between the second part of network nodes and the first part of network nodes is , then the attenuation parameter , where the attenuation parameter is the quantity of parameters directly adjusting the update scheduling feature and update parameter of the second part of network nodes, and the comprehensive influence attenuation degree per unit length is the adjustment amount for the attenuation parameter .

[0047] In step S30, according to the real-time fault nodes and real-time fault information, query the scheduling requirements through the constructed emergency scheduling model based on the water supply route to obtain the scheduling requirement data corresponding to the real-time fault nodes, including: Based on the real-time fault node, search for the target network node in the emergency scheduling model to obtain the target scheduling characteristics and target parameters of the target network node; Based on the real-time fault information, obtain the feature adjustment factor and the parameter adjustment factor; Based on the feature adjustment factor and the parameter adjustment factor, adjust the target scheduling characteristics and target parameters to obtain the real-time scheduling characteristics and real-time parameters as the scheduling demand data corresponding to the real-time fault node.

[0048] After obtaining the emergency scheduling model based on the historical water supply data, historical fault nodes, and historical emergency repair data of the water supply route, when the water supply optimization scheduling system of the waterworks monitors the real-time fault node and real-time fault information, the corresponding scheduling demand data can be retrieved according to the real-time fault node and real-time fault information. Specifically, first search for the target network node corresponding to the real-time fault node in the emergency scheduling model, then retrieve the corresponding target scheduling characteristics and target parameters in the emergency scheduling model, and then obtain the feature adjustment factor and the parameter adjustment factor for adjusting the target scheduling characteristics and target parameters according to the real-time fault information. For example, when the real-time fault information of the current real-time fault node shows that the current fault type is relatively urgent and the necessity of some target scheduling characteristics is relatively large, the feature adjustment factor is relatively larger, and the necessity of the target scheduling characteristics obtained according to the feature adjustment factor is stronger and cannot be replaced by other similar scheduling characteristics; while if the feature adjustment factor is medium, when some target scheduling characteristics are relatively scarce, they can be replaced by other scheduling characteristics; furthermore, if the feature adjustment factor is small, when some target scheduling characteristics are relatively scarce, they can be replaced by other scheduling characteristics or directly ignored to quickly obtain the real-time scheduling characteristics and timely respond to the corresponding scheduling demands. For the parameter adjustment factor, the corresponding parameter adjustment factor can be obtained according to the situation of the fault intensity in the fault intensity range of the real-time fault information to adjust the target parameters corresponding to the scheduling characteristics. Further, the real-time scheduling characteristics and real-time parameters can be used as the scheduling demand data corresponding to the real-time fault node.

[0049] Next, execute step S40 to obtain the optimal emergency repair scheduling plan according to the scheduling demand data. Among them, the scheduling demand data includes real-time scheduling characteristics and real-time parameters.

[0050] After the water supply optimization scheduling system of the waterworks determines the scheduling demand data, it can further generate the corresponding optimal emergency repair scheduling plan according to the real-time scheduling characteristics and real-time parameters in the scheduling demand data, combined with the relevant nearby sites responsible for scheduling and the resource reserves of each relevant site, to quickly respond to the scheduling tasks of the real-time fault node.

[0051] In step S40, according to the dispatching demand data, an optimal emergency repair dispatching plan is obtained, including: According to the real-time dispatching characteristics, the real-time fault nodes are searched nearby to obtain relevant stations with corresponding emergency resource items; According to the real-time parameters, the resource reserves of relevant stations are queried to determine the final station combination and resource dispatching allocation information; According to the station combination and resource dispatching allocation information, an optimal emergency repair dispatching plan is obtained.

[0052] In the process of the waterworks water supply optimization dispatching system obtaining the optimal emergency repair dispatching plan according to the dispatching demand data, the real-time dispatching characteristics, that is, the required emergency resource items, can be first used to query each nearby station to find relevant stations with corresponding emergency resource items. The emergency resource items can include human resources, material resources, etc. Then, based on the real-time parameters, that is, the required resource quantity, the resource reserves of relevant stations are queried, and the emergency resource items and resource quantities that meet the relevant requirements are retrieved nearby in turn according to the distance from the real-time fault node, so as to generate the final station combination and resource dispatching allocation information, and according to the station combination and resource dispatching allocation information, an optimal emergency repair dispatching plan is generated to execute the dispatching task of the real-time fault node.

[0053] Next, step S50 is executed, and the corresponding dispatching task is executed according to the optimal emergency repair dispatching plan.

[0054] The optimal emergency repair dispatching plan can include the station combination and resource dispatching allocation information. The waterworks water supply optimization dispatching system can notify the corresponding stations to prepare the corresponding emergency resource items and resource quantities according to the station combination and resource dispatching allocation information of the real-time fault node, so as to realize the issuance of relevant dispatching tasks and improve the response efficiency of emergency dispatching.

[0055] After step S50, that is, after executing the corresponding dispatching task according to the optimal emergency repair dispatching plan, it also includes: After the dispatching task is completed, the real-time fault node and the real-time repair data corresponding to the real-time fault node are used to optimize the emergency dispatching model.

[0056] After the corresponding emergency dispatching task is completed according to the real-time fault node, by inputting the corresponding real-time fault node and the real-time repair data corresponding to the real-time fault node into the emergency dispatching model again, the continuous optimization of the emergency dispatching model is realized to ensure the emergency dispatching accuracy of the emergency dispatching model.

[0057] Please refer to Figure 2, the present invention also provides an optimized water supply scheduling system 11 for a waterworks, including: an acquisition unit 111 for acquiring real-time water supply data of a water supply route; a monitoring unit 112 for monitoring the real-time water supply data of the water supply route to obtain real-time fault nodes and real-time fault information of the water supply route; a query unit 113 for querying scheduling requirements through an emergency scheduling model based on the water supply route according to the real-time fault nodes and real-time fault information to obtain scheduling requirement data corresponding to the real-time fault nodes; a retrieval unit 114 for obtaining an optimal emergency repair scheduling plan according to the scheduling requirement data; and an execution unit 115 for executing corresponding scheduling tasks according to the optimal emergency repair scheduling plan.

[0058] It should be noted that the optimized water supply scheduling system 11 for a waterworks provided in the above embodiment belongs to the same concept as the optimized water supply scheduling method for a waterworks provided in the above embodiment. The specific manners in which each module and unit perform operations have been described in detail in the method embodiment and will not be elaborated here. In practical applications, the optimized water supply scheduling system 11 for a waterworks provided in the above embodiment can, as needed, allocate the above functions to different functional modules, that is, divide the internal structure of the device into different functional modules to complete all or part of the functions described above, and this is not limited here either.

[0059] Please refer to Figure 3 , the electronic device 1 may include a memory 12, a processor 13, and a bus, and may also include a computer program stored in the memory 12 and executable on the processor 13, such as an optimized water supply scheduling program for a waterworks.

[0060] Among them, the memory 12 includes at least one type of readable storage medium, and the readable storage medium includes flash memory, mobile hard disks, multimedia cards, card-type memories (such as SD or DX memories, etc.), magnetic memories, magnetic disks, optical disks, etc. The memory 12 may be an internal storage unit of the electronic device 1 in some embodiments, such as the mobile hard disk of the electronic device 1. The memory 12 may also be an external storage device of the electronic device 1 in other embodiments, such as a plug-in mobile hard disk, a Smart Media Card (SMC), a Secure Digital (SD) card, a Flash Card, etc. equipped on the electronic device 1. Further, the memory 12 may include both an internal storage unit and an external storage device of the electronic device 1. The memory 12 can be used not only to store application software installed on the electronic device 1 and various types of data, such as the code for optimizing water supply scheduling in a waterworks, but also to temporarily store data that has been output or will be output.

[0061] In some embodiments, the processor 13 may be composed of an integrated circuit. For example, it may be composed of a single packaged integrated circuit, or may be composed of multiple packaged integrated circuits with the same or different functions, including the combination of one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and various control chips. The processor 13 is the control core of the electronic device 1, connecting various components of the entire electronic device 1 through various interfaces and circuits. By running or executing programs or modules stored in the memory 12 (such as the water supply optimization scheduling program of a waterworks), and by calling the data stored in the memory 12, it executes various functions of the electronic device 1 and processes data.

[0062] The processor 13 executes the operating system of the electronic device 1 and various installed application programs. The processor 13 executes the application programs to implement the steps in the above-mentioned water supply optimization scheduling method for a waterworks.

[0063] Exemplarily, the computer program may be divided into one or more modules. The one or more modules are stored in the memory 12 and executed by the processor 13 to complete this application. The one or more modules may be a series of computer program instruction segments capable of completing specific functions, and these instruction segments are used to describe the execution process of the computer program in the electronic device 1. For example, the computer program may be divided into the various units in the water supply optimization scheduling system of a waterworks.

[0064] The above-mentioned integrated unit implemented in the form of a software functional module may be stored in a computer-readable storage medium. The computer-readable storage medium may be non-volatile or volatile. The above-mentioned software functional module is stored in a storage medium and includes several instructions to enable a computer device (which may be a personal computer, a computer device, or a network device, etc.) or a processor to execute some functions of the water supply optimization scheduling method described in various embodiments of this application.

[0065] In summary, for the water supply optimization scheduling method and system disclosed by the present invention, in the event of a water supply failure, based on the real-time failure node and real-time failure information, it is possible to quickly query the scheduling demand data required for emergency failures through the emergency scheduling model of the water supply route, and then arrange the corresponding optimal emergency repair scheduling plan based on the scheduling resources to complete the emergency command and dispatch. This can effectively improve the timely personnel arrangement and emergency repair efficiency during water supply anomalies, and reduce the scheduling difficulty of resources and personnel during emergency command. Moreover, during the construction of the emergency scheduling model, by using historical water supply data, historical failure nodes, and historical emergency repair data, the continuous update and optimization of the initial emergency scheduling model can effectively ensure the query accuracy of the emergency scheduling model for scheduling demand data including real-time scheduling characteristics and real-time parameters. While improving the efficiency during emergency scheduling, it also ensures the accuracy of the corresponding scheduling resources, thereby improving the solution efficiency for real-time failures that occur. Therefore, the present invention effectively overcomes various shortcomings in the prior art and has high industrial utilization value.

[0066] The above embodiments are only illustrative of the principles and effects of the present invention, and are not intended to limit the present invention. Any person familiar with this technology can modify or change the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or changes completed by those with ordinary knowledge in the technical field without departing from the spirit and technical ideas disclosed by the present invention should still be covered by the claims of the present invention.

Claims

1. A method for optimizing the water supply scheduling of a waterworks, characterized in that, Including: Obtain the real-time water supply data of the water supply route; Monitor the real-time water supply data of the water supply route to obtain the real-time fault nodes and real-time fault information of the water supply route; According to the real-time fault nodes and the real-time fault information, query the dispatching requirements through the constructed emergency dispatching model based on the water supply route to obtain the dispatching requirement data corresponding to the real-time fault nodes; According to the dispatching requirement data, obtain the optimal emergency repair dispatching plan; Execute the corresponding dispatching tasks according to the optimal emergency repair dispatching plan.

2. The optimized scheduling method for water supply in a waterworks according to claim 1, characterized in that: The emergency dispatching model is constructed in the following way: Obtain the historical water supply data, historical fault nodes and historical emergency repair data of the water supply route; Update the initial emergency dispatching model of the water supply route according to the historical water supply data; Optimize the updated initial emergency dispatching model according to the historical fault nodes and the historical emergency repair data to obtain the emergency dispatching model.

3. The optimized scheduling method for water supply in a waterworks according to claim 2, characterized in that: Updating the initial emergency dispatching model of the water supply route according to the historical water supply data includes: Obtain the initial laying data of the water supply route; According to the initial laying data, obtain the dispatching characteristics and the initial parameters of the dispatching characteristics; Construct the initial emergency dispatching model according to the initial laying data, dispatching characteristics and the initial parameters of the dispatching characteristics, wherein the initial emergency dispatching model includes a plurality of network nodes; Increase or decrease and adjust the dispatching characteristics and the initial parameters according to the historical water supply data to obtain updated dispatching characteristics and updated parameters; Update the initial emergency dispatching model of the water supply route through the updated dispatching characteristics and the updated parameters.

4. The water supply optimization scheduling method of a waterworks according to claim 3, characterized in that: Increasing or decreasing and adjusting the dispatching characteristics and the initial parameters according to the historical water supply data to obtain updated dispatching characteristics and updated parameters includes: Perform feature search on the historical water supply data to obtain historical dispatching characteristics and the historical parameters corresponding to the historical dispatching characteristics; Compare the historical dispatching characteristics and the historical parameters with the dispatching characteristics and the initial parameters respectively; If the dispatching characteristics and the historical dispatching characteristics are different, add the historical dispatching characteristics different from the dispatching characteristics and their corresponding historical parameters to the dispatching characteristics to obtain the updated dispatching characteristics; If the dispatching characteristics and the historical dispatching characteristics are the same, replace the initial parameters with the historical parameters corresponding to the historical dispatching characteristics whose difference from the initial parameters corresponding to the dispatching characteristics is greater than the set value to obtain the updated parameters.

5. The optimized scheduling method for water supply in a waterworks according to claim 3, characterized in that: Optimizing the updated initial emergency dispatching model according to the historical fault nodes and the historical emergency repair data to obtain the emergency dispatching model includes: Find the first part of network nodes in the updated initial emergency dispatching model corresponding to the historical fault nodes; Obtain the differential dispatching characteristics and parameter differences according to the historical emergency repair data corresponding to the historical fault nodes and the updated dispatching characteristics and the updated parameters of the first part of network nodes Adjusting the updated scheduling characteristics and the updated parameters of the first part of network nodes according to the differential scheduling characteristics and the parameter difference to obtain a first revised scheduling characteristic and a first revised parameter; Determining, based on the differential scheduling characteristics and the parameter difference, a comprehensive impact attenuation per unit length on each of the second portion of network nodes surrounding the first portion of network nodes; Adjusting the updated scheduling characteristics and the updated parameters of the second part of network nodes according to the differential scheduling characteristics, the parameter difference, and the unit length comprehensive impact attenuation to obtain second revised scheduling characteristics and second revised parameters; The updated emergency dispatch initial model is optimized according to the first revised dispatch feature, the first revised parameter, the second revised dispatch feature, and the second revised parameter to obtain the emergency dispatch model.

6. The optimized scheduling method for water supply in a waterworks according to claim 5, characterized in that: Determining, based on the differential scheduling characteristics and the parameter difference, a unit length comprehensive impact attenuation on each of the second portion of network nodes surrounding the first portion of network nodes, including: Obtaining a first unit length impact attenuation according to the differential scheduling characteristics; Obtaining a second unit length impact attenuation according to the parameter difference under the differential scheduling characteristics; The comprehensive unit length influence attenuation on each second portion of network nodes around the first portion of network nodes is determined based on the first unit length influence attenuation and the second unit length influence attenuation.

7. The optimized scheduling method for water supply in a waterworks according to claim 1, wherein: According to the real-time fault node and the real-time fault information, a scheduling demand query is performed through the emergency scheduling model based on the water supply route to obtain scheduling demand data corresponding to the real-time fault node, including: According to the real-time fault node, a target network node search is performed in the emergency scheduling model to obtain target scheduling characteristics and target parameters of the target network node; Obtaining a characteristic adjustment factor and a parameter adjustment factor according to the real-time fault information; The target scheduling feature and the target parameter are adjusted according to the feature adjustment factor and the parameter adjustment factor to obtain real-time scheduling feature and real-time parameter as scheduling demand data corresponding to the real-time fault node.

8. The water supply optimization scheduling method of a waterworks according to claim 1, characterized in that: The scheduling demand data includes real-time scheduling characteristics and real-time parameters; According to the dispatch demand data, an optimal emergency repair dispatch plan is obtained, including: According to the real-time scheduling characteristics, searching for the real-time fault node nearby to obtain relevant sites with corresponding emergency resource items; Performing a resource reserve query on the relevant sites based on the real-time parameters to determine a final site combination and resource scheduling allocation information; An optimal emergency repair scheduling plan is obtained according to the site combination and the resource scheduling allocation information.

9. The water supply optimization scheduling method of a waterworks according to claim 1, characterized in that: Also includes: After the scheduling task is completed, the emergency scheduling model is optimized using the real-time fault node and the real-time repair data corresponding to the real-time fault node.

10. A water supply optimization scheduling system for a waterworks, characterized in that: include: an acquisition unit, used for acquiring real-time water supply data of a water supply route; A monitoring unit, configured to monitor the real-time water supply data of the water supply route to obtain real-time fault nodes and real-time fault information of the water supply route; A query unit, configured to perform a scheduling demand query based on the real-time fault node and the real-time fault information through an emergency scheduling model constructed based on the water supply route, so as to obtain scheduling demand data corresponding to the real-time fault node; A retrieving unit, configured to obtain an optimal emergency repair scheduling plan based on the scheduling demand data; as well as An execution unit is used to execute corresponding scheduling tasks according to the optimal emergency repair scheduling plan.

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