Intelligent evaluation system and method for regulation and storage tank based on fuzzy analytic hierarchy process and dynamic simulation

Abstract

The invention relates to the technical field of water environment treatment, in particular to a storage tank intelligent evaluation system and method based on fuzzy analytic hierarchy process and dynamic simulation. The system comprises a hydraulic data acquisition module, an FAHP dynamic evaluation engine, a multi-stage evaluation output module, a dynamic control execution unit and a feedback optimization module, the hydraulic data acquisition module is used for acquiring operation data of a pipe network and a regulation and storage tank in real time; the FAHP dynamic evaluation engine is used for generating a fuzzy judgment matrix based on the operation data of the pipe network and the regulation and storage pool and outputting an index weight; the multi-level evaluation output module is used for generating operation and maintenance suggestion data of different levels based on the index weight; the multi-stage evaluation output module is used for automatically adjusting the operation parameters of the regulation and storage tank equipment according to the evaluation result; and the feedback optimization module is used for reversely calibrating parameters of the hydraulic model according to the evaluation result.

Description

Technical Field

[0001] This invention relates to the field of water environment management technology, and in particular to an intelligent evaluation system and method for regulating reservoirs based on fuzzy hierarchical analysis and dynamic simulation. Background Technology

[0002] Rainwater storage tanks are artificially constructed, seepage-proof water storage facilities, and are important engineering facilities for rainwater storage. As a low-cost water-saving system, rainwater storage tanks effectively alleviate water shortages and solve urban flood control and drainage problems.

[0003] The existing technology is a stormwater storage tank overflow pollution control system (patent application number: 201310130601.X), which only relies on physical structure improvements (such as adding a sedimentation tank) and does not involve dynamic evaluation algorithms. It cannot optimize the operation strategy according to real-time operating conditions. In order to solve this technical problem, a stormwater storage tank intelligent evaluation system and method based on fuzzy hierarchical analysis and dynamic simulation is proposed. Summary of the Invention

[0004] To address the technical problems existing in the prior art, the present invention provides an intelligent evaluation system and method for water storage tanks based on fuzzy hierarchical analysis and dynamic simulation.

[0005] To achieve the above objectives, the embodiments of the present invention provide the following technical solutions:

[0006] In a first aspect, in one embodiment of the present invention, a smart evaluation system for regulating reservoirs based on fuzzy hierarchical analysis and dynamic simulation is provided. The system includes: a hydraulic data acquisition module, a FAHP dynamic evaluation engine, a multi-level evaluation output module, a dynamic control execution unit, and a feedback optimization module.

[0007] The hydraulic data acquisition module is used to collect real-time operating data of the pipeline network and the regulating reservoir;

[0008] The FAHP dynamic evaluation engine is used to generate a fuzzy judgment matrix based on pipeline and storage tank operation data, output index weights, and generate evaluation results based on index weights.

[0009] The multi-level evaluation output module is used to generate operation and maintenance suggestion data at different levels based on indicator weights;

[0010] The multi-level evaluation output module is used to automatically adjust the operating parameters of the storage tank equipment based on the evaluation results;

[0011] The feedback optimization module is used to reverse-calibrate the hydraulic model parameters in the FAHP dynamic evaluation engine using the evaluation results.

[0012] As a further aspect of the present invention, the hydraulic data acquisition module supports Modbus / TCP and OPC UA protocols for accessing the SCADA system.

[0013] As a further aspect of the present invention, the pipeline network and storage tank operation data include real-time rainfall intensity, pipeline network load rate, pipeline network flow rate, storage tank water level, suspended solids concentration, operation and maintenance management data, and historical operation and maintenance cost data.

[0014] As a further aspect of the present invention, the FAHP dynamic evaluation engine includes a weight matrix generator, a membership function library, and a fuzzy rule database.

[0015] As a further aspect of the present invention, the FAHP dynamic evaluation engine generates a weight matrix using a dynamic weight adjustment algorithm.

[0016] As a further aspect of the present invention, the multi-level evaluation output module is used to generate volume correction and dredging cycle data based on index weights.

[0017] As a further embodiment of the present invention, the multi-level evaluation output module is used to generate four-level operation and maintenance suggestion data (A / B / C / D) based on the indicator weights.

[0018] As a further embodiment of the present invention, the multi-level evaluation output module includes a valve control sub-module, pump start / stop logic, and a safety protection mechanism.

[0019] As a further aspect of the present invention, the hydraulic model parameters include the pipe network roughness coefficient and the pump efficiency curve.

[0020] Secondly, in another embodiment provided by the present invention, a smart evaluation method for water storage tanks based on fuzzy hierarchical analysis and dynamic simulation is provided, the method comprising:

[0021] Real-time acquisition of operational data from pipeline networks and storage tanks;

[0022] A fuzzy judgment matrix is ​​generated based on the operation data of the pipeline network and the regulating reservoir, the index weights are output, and the evaluation results are generated based on the index weights.

[0023] Based on the indicator weights, different levels of operation and maintenance suggestion data are generated;

[0024] The operating parameters of the water storage tank equipment are automatically adjusted based on the evaluation results.

[0025] The hydraulic model parameters are then calibrated using the evaluation results.

[0026] The technical solution provided by this invention has the following beneficial effects:

[0027] Through model linkage and dynamic weighting mechanisms, the accuracy of overflow event prediction is ≥90%, the dynamic dredging cycle and equipment maintenance strategy reduce the average annual cost by 15%-25%, and it supports adaptive adjustment of parameters for different climate zones in the north and south and combined / separate sewer systems.

[0028] These or other aspects of the invention will become more apparent from the following description of embodiments. It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only, and are not intended to limit the invention. Attached Figure Description

[0029] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other embodiments can be obtained based on these drawings without paying any creative work.

[0030] Figure 1 This is a structural block diagram of a smart evaluation system for water storage tanks based on fuzzy hierarchical analysis and dynamic simulation, according to an embodiment of the present invention.

[0031] Figure 2 This is a schematic diagram of the feedback optimization module in an intelligent evaluation system for water storage tanks based on fuzzy hierarchical analysis and dynamic simulation, according to an embodiment of the present invention.

[0032] Figure 3 This is a flowchart of a smart evaluation method for water storage tanks based on fuzzy hierarchical analysis and dynamic simulation, according to an embodiment of the present invention.

[0033] In the diagram: Hydraulic data acquisition module-100, FAHP dynamic evaluation engine-200, multi-level evaluation output module-300, dynamic control execution unit-400, feedback optimization module-500. Detailed Implementation

[0034] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0035] The flowchart shown in the attached diagram is for illustrative purposes only and does not necessarily include all content and operations / steps, nor does it necessarily have to be performed in the order described. For example, some operations / steps can be broken down, combined, or partially merged, so the actual execution order may change depending on the actual situation.

[0036] It should be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0037] Specifically, the embodiments of the present invention will be further described below with reference to the accompanying drawings.

[0038] In one embodiment, see Figure 3 As shown, an embodiment of the present invention also provides an intelligent evaluation system for water storage tanks based on fuzzy hierarchical analysis and dynamic simulation. This system includes a hydraulic data acquisition module 100, a FAHP dynamic evaluation engine 200, a multi-level evaluation output module 300, a dynamic control execution unit 400, and a feedback optimization module 500. The intelligent evaluation system for water storage tanks based on fuzzy hierarchical analysis and dynamic simulation is applied to a water storage tank control system, which includes a water conveyance network, a dredging system, a suspended solids monitoring module, and a water level control module, etc.

[0039] The hydraulic data acquisition module 100 is used to collect real-time operational data of the pipeline network and regulating reservoir.

[0040] In an embodiment of the present invention, the hydraulic data acquisition module 100 supports Modbus / TCP and OPC UA protocols for accessing the SCADA system.

[0041] In an embodiment of the present invention, the hydraulic data acquisition module 100 acquires data at a frequency of ≥1 time / minute during the rainy season and 1 time / hour during the dry season.

[0042] In embodiments of the present invention, the pipeline network and storage tank operation data include real-time rainfall intensity (0-50 mm / h), pipeline network load rate (0-100%), pipeline network flow rate (m³ / s), storage tank water level (m), suspended solids concentration (mg / L), operation and maintenance management data, and historical operation and maintenance cost data.

[0043] In embodiments of the present invention, the operation and maintenance management data includes dredging records, electricity consumption bills, and equipment maintenance logs.

[0044] The FAHP dynamic evaluation engine 200 is used to generate a fuzzy judgment matrix based on pipeline and storage tank operation data, output index weights, and generate evaluation results based on index weights.

[0045] In an embodiment of the present invention, the FAHP dynamic evaluation engine 200 uses a multi-level evaluation output module to generate evaluation results.

[0046] In an embodiment of the present invention, the FAHP dynamic evaluation engine 200 includes a weight matrix generator, a membership function library, and a fuzzy rule database.

[0047] The weight matrix generator includes a 9-level scaling method. The membership function library includes trapezoidal and Gaussian distributions.

[0048] In an embodiment of the present invention, the FAHP dynamic evaluation engine 200 uses a dynamic weight adjustment algorithm to generate a weight matrix.

[0049] In an embodiment of the present invention, the dynamic weight adjustment algorithm includes:

[0050] Equipment failure degradation mode: When the pump failure lasts for more than 2 hours, the weight of "operating energy consumption" will be automatically reduced to 0.1, and the weight of equipment reliability will be increased to 0.6.

[0051] Seasonal model: Based on meteorological data, the rainy season (May-September) and the dry season (October-April) are divided. The default overflow control weight is 0.6 for the rainy season and 0.3 for the dry season.

[0052] The calculation rule of the dynamic weight adjustment algorithm is as follows: when the rainfall intensity is >20mm / h, the overflow control weight is adjusted according to the formula. (R represents rainfall intensity) dynamically adjusted, and We represents overflow control weight.

[0053] The multi-level evaluation output module 300 is used to generate operation and maintenance suggestion data at different levels based on indicator weights.

[0054] In an embodiment of the present invention, the multi-level evaluation output module 300 is used to generate volume correction and dredging cycle data based on index weights.

[0055] The volume correction is adjusted based on the following formula:

[0056] ;

[0057] In the formula, This represents the regional rainfall intensity coefficient (values ​​range from 0.1 to 0.5). The value represents the correction factor for pipeline aging (range 1.2-1.5); V represents the design volume of the storage tank (m³); n represents the nonlinear correction index for rainfall intensity (range 1.2-1.8); and the formula for historical overflow events in the fitted area is meaningful.

[0058] By dynamically modifying the traditional volumetric calculation formula (V=Q), the problem of insufficient storage tank capacity caused by sudden changes in rainfall intensity and aging pipeline networks can be solved. For example:

[0059] When α = 0.3 (rainy region), the volume needs to be increased by 1.3 times;

[0060] When β=1.5 (severe aging of the pipeline network), the volume needs to be increased by an additional 50%.

[0061] The dredging cycle is adjusted based on the following formula:

[0062] ;

[0063] In the formula, This indicates the current concentration of suspended solids (mg / L). The design siltation threshold is represented (e.g., 200 mg / L). T represents the dynamic dredging cycle (months), K represents the siltation rate coefficient (0.5-1.2), and S represents the bottom area of ​​the storage tank (㎡); V represents the actual effective volume (m³).

[0064] Model logic:

[0065] When C SS If / C0>1 (i.e., the real-time concentration exceeds the threshold), the dredging cycle will be shortened to 50% of the original value.

[0066] When K=1.0 (medium siltation rate), for every 10% increase in bottom area S, the dredging cycle is shortened by 7%.

[0067] In an embodiment of the present invention, the multi-level evaluation output module 300 is used to generate four-level operation and maintenance suggestion data (A / B / C / D) based on indicator weights.

[0068] Specifically, Level A (≥85 points): No intervention required, continuous system monitoring; Level B (75-84 points): Warning pushed to mobile devices, manual review within 72 hours; Level C (60-74 points): Triggers dredging or equipment maintenance work orders; Level D (<60 points): Emergency response, on-site repair within 2 hours, activation of emergency plan.

[0069] The multi-level evaluation output module 400 is used to automatically adjust the operating parameters of the storage tank equipment based on the evaluation results.

[0070] In an embodiment of the present invention, the multi-level evaluation output module 400 includes a valve control submodule, pump start-stop logic, and a safety protection mechanism.

[0071] The valve control submodule is used to adjust the opening degree of the inlet valve (0-100%) according to the water level assessment level.

[0072] The pump start / stop logic is used to automatically start the standby pump when the evaluation result is C / D.

[0073] The aforementioned safety protection mechanism is used to forcibly open the overflow gate when the water level exceeds the limit (linked with the municipal pipe network).

[0074] like Figure 2 As shown, the feedback optimization module 500 is used to back-calibrate the hydraulic model parameters in the FAHP dynamic evaluation engine 200 by using the evaluation results.

[0075] Hydraulic models can serve as dynamic simulation components.

[0076] In embodiments of the present invention, the hydraulic model parameters include the pipe network roughness coefficient and the pump efficiency curve.

[0077] The feedback optimization module 500 is used to correct the pipeline roughness coefficient (triggered when the error > 5%) and update the pump efficiency curve (based on actual energy consumption data).

[0078] The invention also includes a VR operation and maintenance training module, which is used to develop a virtual scene of the water storage tank based on the Unity 3D engine to simulate emergency operation procedures under different working conditions (such as rainstorm overflow and equipment failure).

[0079] This invention also includes a VR operation and maintenance training module, which automatically sends SMS messages to operation and maintenance personnel and generates maintenance work orders when the evaluation result is C / D.

[0080] Example 1 uses this system to evaluate the Nanhu Reservoir in Wuhan. Specific data is as follows:

[0081] Data input:

[0082] Pipeline flow meter (accuracy ±2%), turbidity sensor (range 0-100NTU), weather station (10-minute rainfall resolution);

[0083] Historical data: There were 12 overflow events during the 2022 rainy season, with an average SS concentration of 180 mg / L.

[0084] Evaluation results:

[0085] The overflow control compliance rate during heavy rain season increased from 67% to 90%, and annual maintenance costs decreased by 18.6%.

[0086] The dredging cycle has been adjusted from a fixed 6 months to a dynamic 3-8 months, resulting in a 25% reduction in siltation.

[0087] Example 2 uses this system to evaluate a diversion-type water storage tank in Beijing. The specific data is as follows:

[0088] Scenario differences: Northern arid climate (average annual rainfall of 500mm), with an emphasis on dust prevention and equipment maintenance;

[0089] Weight adjustment effect:

[0090] During the dry season, "maintenance cost" has a weight of 0.4, and "dust control efficiency" has a weight of 0.3.

[0091] Equipment failure rate decreased by 40%, and maintenance manpower costs were reduced by 15%.

[0092] Comparative experiment:

[0093] Traditional AHP method: 28% misjudgment rate for overflow control during the rainy season, and 22% error rate for maintenance cost prediction during the dry season;

[0094] The method of this invention: The dynamic weight algorithm controls the misclassification rate to within 10% (P<0.05, t test).

[0095] Please see Figure 3 , Figure 3 This is a flowchart of a smart evaluation method for water storage tanks based on fuzzy hierarchical analysis and dynamic simulation provided by an embodiment of the present invention, such as... Figure 2 As shown, the intelligent evaluation method for water storage tanks based on fuzzy hierarchical analysis and dynamic simulation includes steps S10 to S50.

[0096] S10. Real-time acquisition of pipeline network and storage tank operation data;

[0097] S20. Generate a fuzzy judgment matrix based on the operation data of the pipeline network and the regulating reservoir, output the index weights, and generate the evaluation results based on the index weights.

[0098] S30. Based on indicator weights, generate operation and maintenance suggestion data at different levels.

[0099] S40. Automatically adjust the operating parameters of the storage tank equipment based on the evaluation results.

[0100] S50. Reverse-calibrate the hydraulic model parameters using the evaluation results.

[0101] It should be understood that although the above description follows a certain order, these steps are not necessarily executed in that order. Unless otherwise expressly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, some steps in this embodiment may include multiple steps or multiple stages, which are not necessarily completed at the same time, but may be executed at different times. The execution order of these steps or stages is not necessarily sequential, but may be performed alternately or in turn with other steps or at least a portion of the steps or stages in other steps.

[0102] It should be understood that, as used herein, the singular form "a" is intended to include the plural form as well, unless the context clearly supports an exception. It should also be understood that, as used herein, "and / or" refers to any and all possible combinations of one or more of the associatedly listed items. The embodiment numbers disclosed above are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0103] Those skilled in the art should understand that the discussion of any of the above embodiments is merely exemplary and is not intended to imply that the scope of the invention (including the claims) is limited to these examples. Within the framework of the invention, technical features of the above embodiments or different embodiments can be combined, and many other variations of different aspects of the invention exist, which are not provided in the details for the sake of brevity. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the invention should be included within the protection scope of the invention.

Claims

1. A smart evaluation system for water storage tanks based on fuzzy hierarchical analysis and dynamic simulation, characterized in that, The system includes: a hydraulic data acquisition module, a FAHP dynamic evaluation engine, a multi-level evaluation output module, a dynamic control execution unit, and a feedback optimization module; The hydraulic data acquisition module is used to collect real-time operating data of the pipeline network and the regulating reservoir; The FAHP dynamic evaluation engine is used to generate a fuzzy judgment matrix based on pipeline and storage tank operation data, output index weights, and generate evaluation results based on index weights. The multi-level evaluation output module is used to generate operation and maintenance suggestion data at different levels based on indicator weights; The dynamic control execution unit is used to automatically adjust the operating parameters of the storage tank equipment based on the evaluation results; The feedback optimization module is used to reverse-calibrate the hydraulic model parameters in the FAHP dynamic evaluation engine using the evaluation results.

2. The intelligent evaluation system for water storage tanks based on fuzzy hierarchical analysis and dynamic simulation as described in claim 1, characterized in that, The hydraulic data acquisition module supports Modbus / TCP and OPC UA protocols for accessing the SCADA system.

3. The intelligent evaluation system for water storage tanks based on fuzzy hierarchical analysis and dynamic simulation as described in claim 1, characterized in that, The pipeline network and storage tank operation data include real-time rainfall intensity, pipeline load rate, pipeline flow rate, storage tank water level, suspended solids concentration, operation and maintenance management data, and historical operation and maintenance cost data.

4. The intelligent evaluation system for water storage tanks based on fuzzy hierarchical analysis and dynamic simulation as described in claim 1, characterized in that, The FAHP dynamic evaluation engine includes a weight matrix generator, a membership function library, and a fuzzy rule database.

5. The intelligent evaluation system for water storage tanks based on fuzzy hierarchical analysis and dynamic simulation as described in claim 4, characterized in that, The FAHP dynamic evaluation engine uses a dynamic weight adjustment algorithm to generate a weight matrix.

6. The intelligent evaluation system for water storage tanks based on fuzzy hierarchical analysis and dynamic simulation as described in claim 1, characterized in that, The multi-level evaluation output module is used to generate volume correction and dredging cycle data based on indicator weights.

7. The intelligent evaluation system for water storage tanks based on fuzzy hierarchical analysis and dynamic simulation as described in claim 1, characterized in that, The multi-level evaluation output module is used to generate four levels of operation and maintenance suggestion data (A / B / C / D) based on the indicator weights.

8. The intelligent evaluation system for water storage tanks based on fuzzy hierarchical analysis and dynamic simulation as described in claim 1, characterized in that, The multi-level evaluation output module includes a valve control submodule, pump start / stop logic, and safety protection mechanism.

9. The intelligent evaluation system for water storage tanks based on fuzzy hierarchical analysis and dynamic simulation as described in claim 1, characterized in that, The hydraulic model parameters include the pipe network roughness coefficient and the pump efficiency curve.

10. A smart evaluation method for water storage tanks based on fuzzy hierarchical analysis and dynamic simulation, characterized in that, The method includes: Real-time acquisition of operational data from pipeline networks and storage tanks; A fuzzy judgment matrix is ​​generated based on the operation data of the pipeline network and the regulating reservoir, the index weights are output, and the evaluation results are generated based on the index weights. Based on the indicator weights, different levels of operation and maintenance suggestion data are generated; The operating parameters of the water storage tank equipment are automatically adjusted based on the evaluation results. The hydraulic model parameters are then calibrated using the evaluation results.

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