Reservoir safety evaluation method and device, program product and electronic equipment

Abstract

The invention provides a reservoir safety evaluation method and device, a program product and electronic equipment, and relates to the technical field of computers. The method comprises the following steps: determining reservoir data of a reservoir to be evaluated; the reservoir data comprises feature data, actual measurement data and patrol data; determining a target building type of the reservoir to be evaluated according to the feature data, and constructing a safety evaluation index system according to the target building type and safety evaluation content specified by specifications; and inputting the safety evaluation index system, the measured data and the patrol data into a reservoir safety comprehensive evaluation model to obtain total evaluation information of the reservoir to be evaluated. According to the invention, the reservoir data is processed through the reservoir safety comprehensive evaluation model, the total evaluation information of the to-be-evaluated reservoir is output, and the evaluation precision is improved.

Description

Reservoir safety assessment methods, devices, procedures, products, and electronic equipment Technical Field

[0001] This disclosure relates to the field of computer technology, and in particular to a method, apparatus, program product and electronic equipment for reservoir safety assessment. Background Technology

[0002] As a core infrastructure for water resource regulation, flood control and disaster reduction, and energy supply, the safe and stable operation of reservoirs is directly related to the safety of people's lives and property and the sustainable development of society and economy within the basin.

[0003] Currently, reservoir safety assessment mainly relies on a simple superposition of single indicators or a few key indicators, while specific assessment schemes are generally based on manual inspections and expert judgment.

[0004] While the aforementioned reservoir safety assessment methods can provide a preliminary assessment of basic safety factors such as dam structure, seepage status, and hydrological conditions, and play a certain role in routine safety monitoring scenarios, evaluation models based on single or a few indicators are significantly one-sided. They struggle to comprehensively cover multi-dimensional safety factors such as dam structural integrity, seepage stability, and hydrological load adaptability, easily leading to the omission of key risk points. Furthermore, manual inspections and experience-based judgments rely heavily on expert subjective perception; differences in the knowledge and practical experience of different experts can lead to inconsistencies in evaluation conclusions, lacking objective and unified judgment standards. Therefore, the reservoir safety assessment methods provided by related technologies have low accuracy. Summary of the Invention

[0005] This disclosure provides a reservoir safety assessment method, a reservoir safety assessment device, an electronic device, and a computer program product, which improve the accuracy of reservoir safety assessment to a certain extent.

[0006] According to a first aspect of this disclosure, a method for reservoir safety evaluation is provided. The method includes: determining reservoir data for a reservoir to be evaluated; the reservoir data includes characteristic data, measured data, and inspection data; determining the target building type of the reservoir to be evaluated based on the characteristic data, and constructing a safety evaluation index system based on the target building type and the safety evaluation content specified in the standards; and inputting the safety evaluation index system, the measured data, and the inspection data into a comprehensive reservoir safety evaluation model to obtain the overall evaluation information of the reservoir to be evaluated.

[0007] In one possible implementation, the safety evaluation index system includes an evaluation hierarchy for the reservoir to be evaluated; the evaluation hierarchy includes a target layer, a sub-evaluation layer, and an evaluation index layer.

[0008] In one possible implementation, the safety evaluation index system, the measured data, and the inspection data are input into a comprehensive reservoir safety evaluation model to obtain the overall evaluation information of the reservoir to be evaluated. This includes: determining the performance evaluation matrix of the evaluation index layer based on the measured data, the inspection data, and the evaluation dimension information; determining a first evaluation result vector based on the performance evaluation matrix; determining a first weight value of the evaluation index layer; determining a second evaluation result vector of the sub-evaluation layer based on the first weight value of the evaluation index layer and the first evaluation result vector; determining a second weight value of the sub-evaluation layer; determining an evaluation result vector of the target layer based on the second weight value of the sub-evaluation layer and the second evaluation result vector; and determining the evaluation result vector of the target layer as the overall evaluation information of the reservoir to be evaluated.

[0009] In one possible implementation, determining the first weight value of the evaluation index layer includes: determining the single ranking weight of the evaluation index layer relative to the sub-item evaluation layer; determining the total ranking weight of the evaluation index layer relative to the target layer; and determining the first weight value of the evaluation index layer based on the single ranking weight and the total ranking weight.

[0010] In one possible implementation, determining the single ranking weight of the evaluation index layer relative to the sub-item evaluation layer includes: constructing a first judgment matrix based on the content of the sub-item evaluation layer and the evaluation index layer in the safety evaluation index system; performing hierarchical single ranking and consistency verification on the first judgment matrix to determine the eigenvector of the first judgment matrix; determining the maximum eigenvalue of the first judgment matrix based on the eigenvector of the first judgment matrix; and performing consistency verification on the first judgment matrix based on the maximum eigenvalue of the first judgment matrix to determine a target first judgment matrix that passes the consistency verification; and determining the single ranking weight of the evaluation index layer relative to the sub-item evaluation layer based on the target first judgment matrix.

[0011] In one possible implementation, the method further includes: determining the safety level of the reservoir to be evaluated based on the overall evaluation information and preset safety processing rules; and determining status information for indicating the operating status of the dam of the reservoir to be evaluated based on the safety level and the preset safety processing rules.

[0012] In one possible implementation, the method further includes: triggering preset alarm information when the status information indicates a status within a preset status set, wherein the preset alarm information is used to instruct business personnel to perform corresponding adjustment measures.

[0013] According to a second aspect of this disclosure, a reservoir safety evaluation device is provided. The device includes: a determining unit, configured to determine reservoir data of a reservoir to be evaluated; the reservoir data includes characteristic data, measured data, and inspection data; a constructing unit, configured to determine the target building type of the reservoir to be evaluated based on the characteristic data, and construct a safety evaluation index system based on the target building type and the safety evaluation content specified in the standards; and an evaluation unit, configured to input the safety evaluation index system, the measured data, and the inspection data into a comprehensive reservoir safety evaluation model to obtain the overall evaluation information of the reservoir to be evaluated.

[0014] In one possible implementation, the safety evaluation index system includes an evaluation hierarchy for the reservoir to be evaluated; the evaluation hierarchy includes a target layer, a sub-evaluation layer, and an evaluation index layer.

[0015] In one possible implementation, the evaluation unit is configured to: determine the performance evaluation matrix of the evaluation index layer based on the measured data, the inspection data, and the evaluation dimension information, and determine a first evaluation result vector based on the performance evaluation matrix; determine a first weight value of the evaluation index layer, and determine a second evaluation result vector of the sub-item evaluation layer based on the first weight value of the evaluation index layer and the first evaluation result vector; determine a second weight value of the sub-item evaluation layer, and determine an evaluation result vector of the target layer based on the second weight value of the sub-item evaluation layer and the second evaluation result vector; and determine the evaluation result vector of the target layer as the total evaluation information of the reservoir to be evaluated.

[0016] In one possible implementation, the evaluation unit is configured to: determine the single ranking weight of the evaluation index layer relative to the sub-evaluation layer; determine the total ranking weight of the evaluation index layer relative to the target layer; and determine a first weight value of the evaluation index layer based on the single ranking weight and the total ranking weight.

[0017] In one possible implementation, the evaluation unit is configured to: construct a first judgment matrix based on the content of the sub-evaluation layer and the evaluation index layer in the safety evaluation index system; perform hierarchical single sorting and consistency verification on the first judgment matrix to determine the eigenvector of the first judgment matrix; determine the maximum eigenvalue of the first judgment matrix based on the eigenvector of the first judgment matrix; and perform consistency verification on the first judgment matrix based on the maximum eigenvalue of the first judgment matrix to determine a target first judgment matrix that passes the consistency verification; and determine the single sorting weight of the evaluation index layer relative to the sub-evaluation layer based on the target first judgment matrix.

[0018] In one possible implementation, the device further includes a processing unit for: determining the safety level of the reservoir to be evaluated based on the overall evaluation information and preset safety processing rules; and determining status information for indicating the operating status of the dam of the reservoir to be evaluated based on the safety level and the preset safety processing rules.

[0019] In one possible implementation, the device further includes a processing unit for: triggering preset alarm information when the status information indicates a status within a preset status set, wherein the preset alarm information is used to instruct business personnel to perform corresponding adjustment measures.

[0020] According to a fourth aspect of this disclosure, a computer program product is provided, comprising a computer program that, when executed by a processor, implements the method of the first aspect described above and possible implementations thereof.

[0021] According to a fifth aspect of this disclosure, an electronic device is provided, comprising: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to perform the method of the first aspect and possible implementations thereof by executing the executable instructions.

[0022] The technical solution disclosed herein has the following beneficial effects: In this embodiment, the electronic device can determine the reservoir data of the reservoir to be evaluated; wherein, the reservoir data includes characteristic data, measured data, and inspection data; then, based on the characteristic data, the target structure type of the reservoir to be evaluated is determined, and a safety evaluation index system is constructed according to the target structure type and the safety evaluation content specified in the regulations; that is, a multi-level safety evaluation index system can be constructed according to the characteristics of the reservoir (e.g., according to the characteristics of different operation stages of the reservoir (construction period, initial storage period, operation period) or the characteristics of the target structure type, etc.), which covers multiple aspects of safety evaluation indicators such as design rationality, defect status, structural safety verification, and measured performance. Furthermore, the safety evaluation index system, measured data, and inspection data are input into the comprehensive safety evaluation model of the reservoir to be evaluated to obtain the overall evaluation information of the reservoir to be evaluated. In other words, by combining measured data and inspection data and using multi-source data fusion technologies such as the analytic hierarchy process (AHP), the index system can be quantitatively evaluated, further improving the accuracy and scientific nature of the evaluation of the reservoir to be evaluated.

[0023] Other features and advantages of this disclosure will be set forth in the following description and will be apparent in part from the description or may be learned by practicing the disclosure. The objects and other advantages of this disclosure may be realized and obtained by means of the structures particularly pointed out in the written description, claims, and drawings. Attached Figure Description

[0024] To more clearly illustrate the technical solutions of the embodiments of this disclosure, the accompanying drawings used in the embodiments of this disclosure will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this disclosure. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0025] Figure 1 shows a schematic diagram of an application scenario in this exemplary embodiment.

[0026] Figure 2 shows a flowchart of a reservoir safety evaluation method in this exemplary embodiment.

[0027] Figure 3 shows a schematic diagram of a safety evaluation index system in this exemplary embodiment.

[0028] Figure 4 shows a schematic diagram of a reservoir safety evaluation device in this exemplary embodiment.

[0029] Figure 5 shows a schematic diagram of the structure of an electronic device according to this exemplary embodiment. Detailed Implementation

[0030] To make the objectives, technical solutions, and advantages of this disclosure clearer, the technical solutions in the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this disclosure, and not all of them. Based on the embodiments of this disclosure, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this disclosure. Unless otherwise specified, the embodiments and features in the embodiments of this disclosure can be arbitrarily combined with each other. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than that shown here.

[0031] The term "comprising" and any variations thereof in the specification and claims of this disclosure are intended to cover non-exclusive protection. For example, a process, method, system, product, or apparatus that comprises a series of steps or units is not limited to the steps or units listed, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to such process, method, product, or apparatus.

[0032] In this disclosure, there are one or more embodiments; "multiple" refers to two or more. "And / or" describes the relationship between the associated objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following associated objects are in an "or" relationship. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple.

[0033] It should be noted that the terms "first," "second," "third," etc., in the specification, claims, and accompanying drawings of this disclosure are used to distinguish similar objects and are not necessarily used to describe a specific order, sequence, size, or priority. For example, the first weight value and the second weight value in the embodiments of this disclosure are merely used to distinguish different weight values. It should be understood that such data can be interchanged where appropriate so that the embodiments of this disclosure described herein can be implemented in orders other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this disclosure. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this disclosure as detailed in the appended claims.

[0034] The exemplary embodiments of this disclosure are described below with reference to the accompanying drawings, which are schematic illustrations of this disclosure and are not necessarily drawn to scale. Some block diagrams shown in the drawings may be functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities may be implemented in software, in hardware modules or integrated circuits, or in networks, processors, or microcontrollers. Implementations can be carried out in various forms and should not be construed as limited to the examples set forth herein. The features, structures, or characteristics described in this disclosure can be combined in any suitable manner in one or more embodiments. Numerous specific details are provided in the following description to give a thorough description of embodiments of this disclosure. However, those skilled in the art will recognize that one or more specific details may be omitted when implementing the technical solutions of this disclosure, or other methods, components, apparatuses, steps, etc., may be used to replace one or more specific details.

[0035] It should be noted that certain software, components, models, and other existing industry solutions may be mentioned in the embodiments disclosed herein. These should be considered exemplary and intended only to illustrate the feasibility of implementing the technical solutions disclosed herein, but do not imply that the applicant has already used or necessarily used such solutions. The collection, dissemination, and use of data in the technical solutions disclosed herein all comply with relevant national laws and regulations.

[0036] While the reservoir safety assessment methods provided in related technologies can make preliminary judgments on basic safety elements such as dam structure, seepage status, and hydrological conditions, playing a certain role in routine safety monitoring scenarios, evaluation models based on single or a few indicators have significant limitations. They cannot comprehensively cover multi-dimensional safety elements such as dam structural integrity, seepage stability, and hydrological load adaptability, easily leading to the omission of key risk points. Furthermore, manual inspections and experience-based judgments rely heavily on expert subjective perception; differences in the knowledge and practical experience of different experts may lead to inconsistencies in evaluation conclusions, lacking objective and unified judgment standards. Therefore, the reservoir safety assessment methods provided in related technologies have low accuracy.

[0037] To address one or more of the aforementioned problems, this disclosure provides an exemplary embodiment of a reservoir safety evaluation method. This method allows electronic equipment to determine reservoir data, including characteristic data, measured data, and inspection data. Then, based on the characteristic data, the target structure type of the reservoir is determined, and a safety evaluation index system is constructed according to the target structure type and the safety evaluation content specified in regulations. Specifically, a multi-level safety evaluation index system can be constructed based on the characteristics of the reservoir (e.g., the characteristics of different operational stages (construction period, initial impoundment period, operational period) or the characteristics of the target structure type). This safety evaluation index system covers multiple aspects of safety evaluation, including design rationality, defect status, structural safety verification, and measured performance. Furthermore, the safety evaluation index system, measured data, and inspection data are input into a comprehensive reservoir safety evaluation model to obtain the overall evaluation information of the reservoir. In other words, by combining measured data and inspection data and employing multi-source data fusion techniques such as the analytic hierarchy process (AHP), the index system can be quantitatively evaluated, further improving the accuracy and scientific rigor of the evaluation of the reservoir.

[0038] To better understand the technical solutions provided in the embodiments of this disclosure, the following is a brief introduction to the application scenarios applicable to the technical solutions provided in the embodiments of this disclosure. It should be noted that the application scenarios described below are only for illustrating the embodiments of this disclosure and are not intended to limit the scope. In specific implementation, the technical solutions provided in the embodiments of this disclosure can be flexibly applied according to actual needs.

[0039] Please refer to FIG. 1, which shows an application scenario to which the technical solution of the present disclosure embodiment can be applied. In this scenario schematic diagram, it includes multiple acquisition devices 110 and an electronic device 120. Among them, the acquisition device 110 and the electronic device 120 can be directly or indirectly communicatively connected through one or more networks 130. Optionally, the application scenario may further include an execution device. For example, the execution device can perform linkage processing based on the output result of the electronic device 120, which is not limited in the present disclosure embodiment.

[0040] In the present disclosure embodiment, the acquisition device 110 can acquire reservoir data. Among them, the reservoir data at least includes characteristic data, measured data, and inspection data. The acquisition device can send the acquired reservoir data to the electronic device 120, and then the electronic device 120 can determine the reservoir data of the to-be-evaluated reservoir; then, according to the characteristic data, determine the target building type of the to-be-evaluated reservoir, and construct a safety evaluation index system according to the target building type and the safety evaluation content specified by the specification; further, input the safety evaluation index system, measured data, and inspection data into the reservoir safety comprehensive evaluation model to obtain the total evaluation information of the to-be-evaluated reservoir.

[0041] In the present disclosure embodiment, the electronic device 120 can be a server. The server can be a physical server or a physical server cluster, or can be a cloud server or a cloud server cluster that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery network (Content Delivery Network, CDN), as well as big data and artificial intelligence platforms, but is not limited thereto.

[0042] Of course, the method provided by the present disclosure embodiment is not limited to the application scenario shown in FIG. 1, and can also be used in other possible application scenarios, such as an application scenario where the reservoir safety evaluation method is only implemented by the electronic device 120, which is not limited in the present disclosure embodiment.

[0043] To further illustrate the technical solution provided by the present disclosure embodiment, the following will be described in detail with reference to the accompanying drawings and specific implementation manners. Although the present disclosure embodiment provides method operation steps as shown in the following embodiments or drawings, based on routine or non-creative labor, more or fewer operation steps may be included in the method. In steps where there is no necessary causal relationship logically, the execution order of these steps is not limited to the execution order provided by the present disclosure embodiment. When the method is actually processed or the device is executed, it can be executed in the order shown in the embodiments or drawings or executed in parallel.

[0044] The following describes the reservoir safety evaluation method in this embodiment of the present disclosure with reference to the method flowchart shown in Figure 2. The steps shown in Figure 3 can be executed by the electronic device 120 shown in Figure 1.

[0045] Step 201: Determine the reservoir data of the reservoir to be evaluated.

[0046] In this embodiment of the disclosure, the electronic device can obtain reservoir data of the reservoir to be evaluated, wherein the reservoir data includes at least characteristic data, measured data and patrol data.

[0047] In this embodiment, the feature data refers to static data describing the inherent structural design and pre-defined functional positioning of a reservoir, serving as the fundamental basis for analyzing its capacity and boundaries. The feature sub-data includes structural feature data and functional feature data. Structural feature data encompasses core construction parameters of the reservoir, such as dam type (gravity dam, arch dam, etc.), dam height / length / crown width, total reservoir capacity / beneficial reservoir capacity / dead reservoir capacity, spillway dimensions and designed flood discharge capacity, specifications of water release structures (tunnels / culverts), foundation type and treatment methods, etc. Functional feature data clarifies the core uses and supporting designs of the reservoir, such as main functions (flood control, irrigation, water supply, power generation, aquaculture, etc., with multiple uses coexisting), design flood standard (100-year / 1000-year return period), irrigation area / water supply range / water supply population, installed power generation capacity (if any), and basic rules for dispatching and operation (such as flood control level, water supply priority), etc. This embodiment does not limit these aspects.

[0048] In this embodiment, the measured data are dynamic data reflecting the current operating status of the reservoir, continuously collected through automated means such as sensors and monitoring equipment. The measured data includes hydrological data, structural safety data, water quality data, and auxiliary data. Hydrological data includes reservoir water level, inflow, outflow, downstream river level, precipitation (reservoir area and upstream basin), and evaporation. Structural safety data includes dam settlement / displacement (vertical and horizontal), dam seepage pressure / flow, dam foundation uplift pressure, stress and strain of concrete / masonry structures, and spillway gate opening and operating status. Water quality data includes key water quality indicators such as pH, dissolved oxygen, turbidity, ammonia nitrogen, and total phosphorus in the reservoir area (especially important for reservoirs with water supply / aquaculture functions). Auxiliary data includes meteorological data such as water temperature, air temperature, and wind speed, and unit operating parameters of power generation reservoirs (such as output, voltage, and current), which are not limited in this embodiment.

[0049] In this embodiment, the inspection data consists of qualitative and quantitative data from regular / irregular on-site inspections and verification records by management personnel. Inspection data serves as a crucial supplement to compensate for blind spots in automated monitoring and ensures data integrity. The inspection data includes structural appearance data, surrounding environment data, equipment operating condition data, and handling record data. Specifically, structural appearance data includes whether the dam surface has cracks, erosion, or signs of leakage (such as damp areas or piping); whether the spillway and water conveyance structures are damaged or blocked; and whether the gates and opening / closing equipment are rusted or jammed. Surrounding environment data includes whether the reservoir bank slopes are stable (whether there are landslide or collapse risks), whether there are any illegal encroachments on the reservoir area / management scope, and whether there are any pollution sources flowing into the upstream basin. Equipment operating condition data includes whether monitoring equipment (sensors, pressure gauges, etc.) is working properly, whether communication is unimpeded, and the condition of backup power supplies and emergency equipment. Handling record data includes the specific location, description, photographic evidence, and follow-up records of subsequent rectification measures and results found during the inspection.

[0050] Step 202: Based on the feature data, determine the target structure type of the reservoir to be evaluated, and construct a safety evaluation index system according to the target structure type and the safety evaluation content specified in the standards.

[0051] In this embodiment of the disclosure, after obtaining reservoir data, the electronic device can classify the monitored object (e.g., the reservoir to be evaluated) into different building types (e.g., concrete dams, earth-rock dams, etc.) based on the characteristic data in the reservoir data. Furthermore, for different types of buildings, a safety evaluation index system can be constructed according to the safety evaluation content specified in the regulations.

[0052] In one possible implementation, the safety evaluation index system includes an evaluation hierarchy for the reservoir to be evaluated; the evaluation hierarchy includes a target layer, a sub-evaluation layer, and an evaluation index layer.

[0053] For example, see Figure 3, which is a schematic diagram of a safety evaluation index system exemplarily shown in an embodiment of this disclosure.

[0054] In Figure 3, based on the characteristic data in the reservoir data of the reservoir to be evaluated, the target structure type can be determined to be a concrete dam. Then, according to the "Guidelines for Safety Evaluation of Reservoir Dams," the safety evaluation content of the concrete dam as specified in the code includes the following: 1) Dam layout, dam crest and wave wall crest elevations, dam concrete zoning, gallery layout, and the rationality of dam joints, water-stopping, and drainage structures. 2) Sliding stability of the dam body along the foundation surface and slope bends, deep sliding stability along weak structural surfaces or gently sloping structural surfaces of the dam foundation, and lateral stability of the bank slope dam section. 3) Upstream and downstream surface stresses at the foundation surface and slope bends. 4) Reliability of the dam body and foundation seepage control works. 5) Reliability of dam foundation treatment measures. 6) The impact of dam body and foundation defects on structural safety and operational performance. 7) Operational performance such as dam deformation and seepage.

[0055] Please refer to Figure 3. Furthermore, by comprehensively collecting, sorting out, and analyzing concrete dam design specifications, safety evaluation guidelines, and related literature, and based on the safety evaluation content stipulated in the aforementioned concrete dam specifications, a safety evaluation index system with three cost-effectiveness levels can be determined. The three evaluation levels are the target level, the sub-item evaluation level, and the evaluation index level.

[0056] Figure 3 shows a three-tiered system. Tier A represents the target level, which sets the overall safety value of the project. Tier B is the sub-item evaluation level, which includes three safety evaluation indicators: structural safety review, on-site safety inspection, and measured performance evaluation. Tier C is the evaluation indicator level, setting six safety evaluation indicators: a. anti-sliding stability; b. dam heel and dam site stress; c. internal stress of the dam body; d. defect status; e. dam body deformation; and f. dam foundation seepage.

[0057] Step 203: Input the safety evaluation index system, measured data and inspection data into the reservoir safety comprehensive evaluation model to obtain the overall evaluation information of the reservoir to be evaluated.

[0058] In this embodiment of the disclosure, after obtaining the safety evaluation index information, the following steps can be used, but not limited to, to determine the overall evaluation information of the reservoir to be evaluated: Step A: Based on the measured data, inspection data and evaluation dimension information, determine the performance evaluation matrix of the evaluation index layer, and determine the first evaluation result vector based on the performance evaluation matrix.

[0059] In this embodiment, six evaluation indicators at level C can be quantitatively evaluated. The data sources include measured data, calculated structural values, and inspection data. The quantitative standards for the indicators, i.e., the evaluation dimension information, include design allowable values ​​specified in regulations, anomaly inference rules, and manual assessments. This allows for the determination of the performance evaluation matrix for the evaluation indicator layer, and the determination of the first evaluation result vector based on the performance evaluation matrix. For example, transposing the performance evaluation matrix can determine the first evaluation result vector, which can also be called the indicator judgment matrix.

[0060] Step B: Determine the first weight value of the evaluation index layer, and determine the second evaluation result vector of the sub-evaluation layer based on the first weight value of the evaluation index layer and the first evaluation result vector.

[0061] In one possible implementation, the first weight value of the evaluation index layer may be determined by, but is not limited to, the following steps: determining the single ranking weight of the evaluation index layer relative to the sub-evaluation layer; determining the total ranking weight of the evaluation index layer relative to the target layer; and determining the first weight value of the evaluation index layer based on the single ranking weight and the total ranking weight.

[0062] Optionally, a first judgment matrix can be constructed based on the content of the sub-evaluation layer and the evaluation index layer in the safety evaluation index system. Hierarchical single sorting and consistency verification are performed on the first judgment matrix to determine the eigenvector of the first judgment matrix. Based on the eigenvector of the first judgment matrix, the largest eigenvalue of the first judgment matrix is ​​determined. Based on the largest eigenvalue of the first judgment matrix, a consistency verification is performed on the first judgment matrix to determine the target first judgment matrix that passes the consistency verification. Based on the target first judgment matrix, the single sorting weight of the evaluation index layer relative to the sub-evaluation layer is determined.

[0063] Optionally, the single ranking weights of the evaluation index layer relative to the sub-evaluation layer can be aggregated to obtain the total ranking weight of the evaluation index layer relative to the target layer.

[0064] In this exemplary embodiment, considering that when determining the weights between indicators at each level, it is not possible to compare all indicators together, but rather to compare them pairwise, this reduces the difficulty of comparing different indicators and improves the accuracy of the weights. Therefore, in this exemplary embodiment, a judgment matrix can be used to perform pairwise comparisons between different indicators.

[0065] In this exemplary embodiment, a judgment matrix can be constructed based on the safety evaluation index information. The judgment matrix A is shown in Formula 1 below.

[0066] Formula 1.

[0067] In the judgment matrix A, aij It indicates the relative importance of indicator i to the evaluation object or evaluation target relative to indicator j at a certain level.

[0068] In this exemplary embodiment, 10 experts with extensive experience can be invited to score each of the aforementioned safety evaluation indicators using a 1-9 scale. By collecting, summarizing, and analyzing the expert scores, a judgment matrix can be constructed.

[0069] For example, see Table 1, which is a table of the meanings of the scale values ​​of judgment matrices 1 to 9.

[0070]

[0071] Table 1

[0072] In this exemplary embodiment, after obtaining the judgment matrix A using the 1-9 scale method, a ranking of the importance of indicators at this level relative to a certain indicator at a higher level needs to be performed. This ranking can be determined using, but is not limited to, the following steps: ① Based on Formula 2, normalize each column of the judgment matrix, that is: Formula 2.

[0073] ② Based on Formula 3, sum the rows of the normalized matrix for each column, i.e.: Formula 3.

[0074] ③ Based on Formula 4, the vector is normalized, that is: Formula 4.

[0075] In this way, we can obtain the eigenvector W=[W1,W2,W3,…,Wn]T of the judgment matrix. Here, the index of W is the ranking weight of the relative importance of an index at the same level to a certain index at the next higher level. This process is called hierarchical single ranking.

[0076] ④ Based on Formula 5, calculate the maximum eigenvalue λmax of the judgment matrix, that is: Formula 5.

[0077] Among them, (A) W) i Let matrix A The i-th component of the vector obtained by multiplying the vector with vector W. Let be the i-th element of the feature vector W.

[0078] ⑤ Consistency check.

[0079] In this exemplary embodiment, the purpose of performing a consistency check on the judgment matrix is ​​to verify the consistency between the importance of each indicator. For example, there may be contradictory situations where indicator A is significantly more important than indicator B, indicator B is significantly more important than indicator C, but indicator C is more important than indicator A. Therefore, to make the results of the judgment matrix more scientific and consistent, a consistency check is needed.

[0080] In this exemplary embodiment, the consistency index CI of the judgment matrix can be calculated based on the following formula six: Formula 6.

[0081] If CI=0, the matrix has complete consistency; when CI is close to 0, the matrix has satisfactory consistency; the larger CI is, the more serious the inconsistency of the matrix is.

[0082] In this exemplary embodiment, the consistency ratio CR can be determined based on the following formula seven: Formula 7.

[0083] RI is the average random consistency index, which can be obtained by looking up Table 2 below.

[0084]

[0085] Table 2

[0086] In this exemplary embodiment, when the calculated CR < 0.1, it can be determined that the judgment matrix A has satisfactory consistency, or that the inconsistency of this matrix is ​​within an acceptable range, and the judgment matrix passes the consistency test. When the CR value > 0.1, it is necessary to adjust the values ​​in the judgment matrix A and repeat steps ① to ⑤ to re-perform the consistency test on the judgment matrix until the requirement of CR < 0.1 is met, thus satisfying the consistency test.

[0087] In this exemplary embodiment, the hierarchical overall ranking refers to the process of determining the relative importance of all indicators at a certain level to the evaluation object or evaluation target. This process is carried out in the order from the target level to the criterion level and then to the indicator level. For the target level, the result of its hierarchical single ranking is also the result of the overall ranking.

[0088] For example, when there are m indicators P1, P2, …, Pm in layer B with a weight ranking feature vector of p = a1, a2, …, am for the target layer A, and the initial layer C has n indicators with a ranking feature vector of q = b1j, b2j, …, bmj (j = 1, 2, …, m) for the indicator Pj in the upper layer (i.e., layer B), then the weight value of the i-th indicator for the target layer A in the overall ranking of the initial layer C can be determined based on the following formula: Formula 8.

[0089] If expressed in matrix budget form, the weight value of the i-th index in the overall ranking of the initial layer C to the target layer A can be determined based on the following formula (Equation 9): Formula Nine.

[0090] Where Q is the weight matrix of layer C to layer B, and P is the weight vector of layer B to layer A. This is the total weight vector of layer C to layer A.

[0091] As can be seen, in this embodiment of the present disclosure, the single ranking weight of the evaluation index layer relative to the sub-evaluation layer and the total ranking weight of the evaluation index layer relative to the target layer can be determined based on the aforementioned formulas one to eight. The judgment matrix in the aforementioned formulas one to eight is A. Furthermore, the first weight value of the evaluation index layer can be determined based on the single ranking weight and the total ranking weight.

[0092] In this exemplary embodiment, the constructed safety evaluation index system consists of three levels: a Level A target layer comprehensive dam safety evaluation, four Level B criterion layer indicators, and twelve Level C initial layer indicators. The evaluation value of the Level B indicators can be determined by the weights of the Level C initial layer indicators relative to the Level B criterion layer indicators. That is, the aforementioned first weight value, and the corresponding evaluation result vector of the C-level indicator. (That is, the first evaluation result vector mentioned above) are multiplied one by one, and then the sum of all the product results is obtained, as shown in Formula 10 below: Formula 10.

[0093] in, The second evaluation result vector used to characterize the sub-evaluation layer; Used to characterize the first weight value; Used to characterize the first evaluation result vector.

[0094] Step C: Determine the second weight value of the sub-item evaluation layer, and determine the evaluation result vector of the target layer based on the second weight value of the sub-item evaluation layer and the second evaluation result vector.

[0095] In one possible implementation, the second weight value of the sub-evaluation layer may be determined by, but is not limited to, the following steps: determining the single ranking weight of the sub-evaluation layer relative to the target layer; determining the total ranking weight of the sub-evaluation layer relative to the target layer; and determining the first weight value of the sub-evaluation layer based on the single ranking weight and the total ranking weight.

[0096] Optionally, a second judgment matrix can be constructed based on the content of the sub-evaluation layer and the target layer in the safety evaluation index system. Hierarchical single sorting and consistency verification are performed on the second judgment matrix to determine the eigenvector of the second judgment matrix. Based on the eigenvector of the second judgment matrix, the largest eigenvalue of the second judgment matrix is ​​determined. Based on the largest eigenvalue of the second judgment matrix, a consistency verification is performed on the second judgment matrix to determine the target second judgment matrix that passes the consistency verification. Based on the target second judgment matrix, the single sorting weight of the sub-evaluation layer relative to the target layer is determined.

[0097] Optionally, the single ranking weights of the sub-evaluation layers relative to the target layer can be aggregated to obtain the total ranking weight of the sub-evaluation layers relative to the target layer.

[0098] In this embodiment of the disclosure, the single ranking weight of the sub-evaluation layer relative to the target layer and the total ranking weight of the sub-evaluation layer relative to the target layer can be determined based on the aforementioned formulas one to eight. The judgment matrix in the aforementioned formulas one to eight is A. Furthermore, the second weight value of the sub-evaluation layer can be determined based on the single ranking weight and the total ranking weight.

[0099] In this embodiment of the disclosure, the evaluation result vector of the target layer can be calculated as the product of the weight values ​​of the four B-level criterion layer indicators relative to the A-level target layer and the corresponding indicator judgment matrix, for example, determined by the following formula eleven: Formula 11.

[0100] Here, j ranges from 1 to 4, corresponding to the four B-level indicators. Used to characterize the second weight value, Used to characterize the second evaluation result vector.

[0101] Step D: Determine the evaluation result vector of the target layer as the total evaluation information of the reservoir to be evaluated.

[0102] In this embodiment of the disclosure, after obtaining the evaluation result vector of the target layer, the evaluation result vector of the target layer can be determined as the total evaluation information of the reservoir to be evaluated.

[0103] Therefore, in order to obtain the overall safety level or safety margin of the engineering structure of the reservoir to be evaluated, the quantitative results of each evaluation indicator can be weighted according to the importance of each evaluation indicator to obtain the overall evaluation result.

[0104] In one possible implementation, the overall evaluation results can be divided into intervals to determine the safety level of the project.

[0105] In an exemplary embodiment, the safety level of the reservoir to be evaluated can be determined based on the overall evaluation information and preset safety processing rules. Then, based on the safety level and preset safety processing rules, status information indicating the operational status of the dam of the reservoir to be evaluated is determined. Further, when the status information indicates a status within a preset status set, preset alarm information is triggered. The preset alarm information is used to instruct operational personnel to implement corresponding adjustment measures. The preset status set includes, for example, a general status, a relatively dangerous status, and a dam facing a risk of collapse, with different statuses corresponding to different adjustment measures.

[0106] For example, common subcategories of concrete dams include: gravity dams, arch dams (which transfer loads through the thrust of the arch), buttress dams (composed of buttresses and panels), and gravity arch dams (combining the characteristics of gravity dams and arch dams). To more accurately describe the current safety status of concrete dams, this paper will use gravity dams as an example. Considering the needs of online dam monitoring, based on the "Guidelines for Safety Evaluation of Reservoir Dams" SL258-2017, dams can be classified into Class I, Class II, and Class III dams, and further subdivided into five levels: A, B, C, D, and E. Alternatively, the equal interval division method commonly used in systems engineering can be used to classify dam safety evaluation levels, determining the scoring interval corresponding to each safety level, as well as the dam's operating status and countermeasures.

[0107] Optionally, the aforementioned preset security processing rules are as shown in Table 3, for example.

[0108]

[0109] Table 3

[0110] For example, if the total evaluation information is 3 and the preset safety handling rules are shown in Table 3, the safety level of the reservoir to be evaluated can be determined to be level D. Then, based on the safety level and the preset safety handling rules, the status information used to indicate the operating status of the dam of the reservoir to be evaluated is determined to be a relatively dangerous state. Further, the status information can be determined to indicate a state within a preset status set, thereby triggering preset alarm information. This preset alarm information is used to instruct operational personnel to implement corresponding adjustment measures. These adjustment measures may be communicated to the reservoir management personnel via telephone, SMS, email, etc., and then the management personnel will determine to send an expert team to the site again for a safety inspection, identify potential hazards, and take immediate measures to mitigate and reinforce the hazard to prevent further deterioration.

[0111] As can be seen, the embodiments of this disclosure not only provide a multi-level safety evaluation index system based on the characteristics of the reservoir (e.g., the characteristics of different operational stages of the reservoir (construction period, initial impoundment period, operation period) or the characteristics of the target building type), but also encompass safety evaluation indicators from multiple aspects such as design rationality, defect status, structural safety verification, and measured performance. Furthermore, it combines measured data and inspection data, employing multi-source data fusion techniques such as the analytic hierarchy process (AHP) to quantitatively evaluate the index system. Moreover, it achieves a quantitative evaluation of the structural safety of the reservoir, further improving the accuracy and scientific rigor of the evaluation of the reservoir under evaluation.

[0112] An exemplary embodiment of this disclosure also provides a reservoir safety evaluation device. Referring to FIG4, the reservoir safety evaluation device 400 includes the following program units: a determination unit 401, used to determine the reservoir data of the reservoir to be evaluated; the reservoir data includes feature data, measured data, and inspection data; a construction unit 402, used to determine the target building type of the reservoir to be evaluated based on the feature data, and construct a safety evaluation index system based on the target building type and the safety evaluation content specified in the standards; and an evaluation unit 403, used to input the safety evaluation index system, the measured data, and the inspection data into a comprehensive reservoir safety evaluation model to obtain the overall evaluation information of the reservoir to be evaluated.

[0113] In one possible implementation, the safety evaluation index system includes an evaluation hierarchy for the reservoir to be evaluated; the evaluation hierarchy includes a target layer, a sub-evaluation layer, and an evaluation index layer.

[0114] In one possible implementation, the evaluation unit 403 is configured to: determine the performance evaluation matrix of the evaluation index layer based on the measured data, the inspection data, and the evaluation dimension information, and determine a first evaluation result vector based on the performance evaluation matrix; determine a first weight value of the evaluation index layer, and determine a second evaluation result vector of the sub-item evaluation layer based on the first weight value of the evaluation index layer and the first evaluation result vector; determine a second weight value of the sub-item evaluation layer, and determine an evaluation result vector of the target layer based on the second weight value of the sub-item evaluation layer and the second evaluation result vector; and determine the evaluation result vector of the target layer as the total evaluation information of the reservoir to be evaluated.

[0115] In one possible implementation, the evaluation unit 403 is configured to: determine the single ranking weight of the evaluation index layer relative to the sub-evaluation layer; determine the total ranking weight of the evaluation index layer relative to the target layer; and determine a first weight value of the evaluation index layer based on the single ranking weight and the total ranking weight.

[0116] In one possible implementation, the evaluation unit 403 is configured to: construct a first judgment matrix based on the content of the sub-evaluation layer and the evaluation index layer in the safety evaluation index system; perform hierarchical single sorting and consistency verification on the first judgment matrix to determine the feature vector of the first judgment matrix; determine the maximum eigenvalue of the first judgment matrix based on the feature vector of the first judgment matrix; and perform consistency verification on the first judgment matrix based on the maximum eigenvalue of the first judgment matrix to determine a target first judgment matrix that passes the consistency verification; and determine the single sorting weight of the evaluation index layer relative to the sub-evaluation layer based on the target first judgment matrix.

[0117] In one possible implementation, the device further includes a processing unit for: determining the safety level of the reservoir to be evaluated based on the overall evaluation information and preset safety processing rules; and determining status information for indicating the operating status of the dam of the reservoir to be evaluated based on the safety level and the preset safety processing rules.

[0118] In one possible implementation, the device further includes a processing unit for: triggering preset alarm information when the status information indicates a status within a preset status set, wherein the preset alarm information is used to instruct business personnel to perform corresponding adjustment measures.

[0119] The specific details of each part of the above-mentioned device have been described in detail in the method section of the implementation plan. For any undisclosed details, please refer to the implementation plan of the method section, and therefore will not be repeated here.

[0120] It should be noted that although several modules or units for the device used to perform actions have been mentioned in the detailed description above, this division is not mandatory. In fact, according to exemplary embodiments of this disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0121] An exemplary embodiment of this disclosure also provides a computer program product. The computer program product includes a computer program that, when executed by a processor, implements the aforementioned reservoir safety assessment method.

[0122] In one implementation, the computer program product can be a tangible product containing a computer program, such as a computer-readable storage medium storing the computer program. The readable storage medium can be a storage medium based on electrical, magnetic, optical, electromagnetic, infrared, or other signals, including but not limited to: random access memory (RAM), read-only memory (ROM), magnetic tape, floppy disk, flash memory, hard disk drive (HDD), solid-state drive (SSD), etc. For example, the computer program product can be implemented as a non-volatile storage medium storing a computer program, such as read-only memory, NAND flash memory, etc.

[0123] In one implementation, the computer program product can be an intangible product containing a computer program. For example, the computer program product can be implemented as a virtual digital product, such as an executable file, installation package, or other digital file storing the computer program.

[0124] Computer program code can be written in one or more programming languages. Examples of programming languages ​​include C, Java, and C++. Program code can execute entirely on the user's computing device, partially on the user's computing device, or as a standalone software package. It can also execute partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, such as a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via an internet connection provided by a mobile network operator).

[0125] Computer programs can be carried or transmitted via signals such as electricity, magnetism, light, electromagnetic fields, and infrared radiation. Electronic devices can convert signals carrying computer programs into digital signals, thereby running the computer programs. When a computer program runs on an electronic device, its code is used to cause the electronic device to execute (more specifically, the processor of the electronic device to execute) the method steps of various exemplary embodiments of this disclosure. For example, the above-described reservoir safety evaluation method can be executed, which includes the following steps: Step 201: Determine the reservoir data of the reservoir to be evaluated; the reservoir data includes characteristic data, measured data, and patrol data; Step 202: Based on the characteristic data, determine the target building type of the reservoir to be evaluated, and construct a safety evaluation index system based on the target building type and the safety evaluation content specified in the regulations; Step 203: Input the safety evaluation index system, measured data, and patrol data into the comprehensive safety evaluation model of the reservoir to be evaluated to obtain the overall evaluation information of the reservoir to be evaluated.

[0126] By implementing the above methods and steps through a computer program, the reservoir data of the reservoir to be evaluated can be determined. This data includes characteristic data, measured data, and inspection data. Then, based on the characteristic data, the target structure type of the reservoir to be evaluated is determined, and a safety evaluation index system is constructed according to the target structure type and the safety evaluation content stipulated in the regulations. That is, a multi-level safety evaluation index system can be constructed based on the characteristics of the reservoir (e.g., the characteristics of different operational stages of the reservoir (construction period, initial impoundment period, operation period) or the characteristics of the target structure type), covering multiple aspects of safety evaluation indicators such as design rationality, defect status, structural safety verification, and measured performance. Furthermore, the safety evaluation index system, measured data, and inspection data are input into the comprehensive reservoir safety evaluation model to obtain the overall evaluation information of the reservoir to be evaluated. In other words, by combining measured data and inspection data and using multi-source data fusion technologies such as the analytic hierarchy process (AHP), the index system can be quantitatively evaluated, further improving the accuracy and scientific rigor of the evaluation of the reservoir to be evaluated.

[0127] Exemplary embodiments of this disclosure also provide an electronic device, which may include a processor and a memory. The memory stores executable instructions for the processor, such as computer programs. The processor executes the executable instructions to perform the method steps of various exemplary embodiments of this disclosure.

[0128] The electronic device will now be described by way of example in the form of a general-purpose computing device with reference to FIG5. It should be understood that the electronic device 500 shown in FIG5 is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments of this disclosure.

[0129] As shown in Figure 5, the electronic device 500 may include: a processor 510, a memory 520, a bus 530, an I / O (input / output) interface 540, and a network adapter 550.

[0130] The memory 520 may include volatile memory, such as RAM 521 and cache unit 522, and may also include non-volatile memory, such as ROM 523. The memory 520 may also include one or more program modules 524, including but not limited to: an operating system, one or more application programs, other program modules, and program data. Each or some combination of these examples may include an implementation of a network environment. For example, program module 524 may include the units described above.

[0131] The processor 510 may include one or more processing units, such as an AP (Application Processor), a modem processor, a GPU (Graphics Processing Unit), an ISP (Image Signal Processor), a controller, an encoder, a decoder, a DSP (Digital Signal Processor), a baseband processor, and / or an NPU (Neural-Network Processing Unit).

[0132] The processor 510 can be used to execute executable instructions stored in the memory 520, such as the above-mentioned reservoir safety evaluation method, which includes the following steps: Step 201: Determine the reservoir data of the reservoir to be evaluated; the reservoir data includes characteristic data, measured data, and patrol data; Step 202: Based on the characteristic data, determine the target building type of the reservoir to be evaluated, and construct a safety evaluation index system based on the target building type and the safety evaluation content specified in the regulations; Step 203: Input the safety evaluation index system, measured data, and patrol data into the comprehensive safety evaluation model of the reservoir to be evaluated to obtain the overall evaluation information of the reservoir to be evaluated.

[0133] By executing the above method steps through processor 510, the reservoir data of the reservoir to be evaluated can be determined. This data includes characteristic data, measured data, and inspection data. Then, based on the characteristic data, the target structure type of the reservoir to be evaluated is determined, and a safety evaluation index system is constructed according to the target structure type and the safety evaluation content stipulated in the regulations. That is, a multi-level safety evaluation index system can be constructed based on the characteristics of the reservoir (e.g., the characteristics of different operational stages of the reservoir (construction period, initial impoundment period, operation period) or the characteristics of the target structure type), covering multiple aspects of safety evaluation indicators such as design rationality, defect status, structural safety verification, and measured performance. Furthermore, the safety evaluation index system, measured data, and inspection data are input into the reservoir safety comprehensive evaluation model to obtain the overall evaluation information of the reservoir to be evaluated. In other words, by combining measured data and inspection data and using multi-source data fusion technologies such as the analytic hierarchy process (AHP), the index system can be quantitatively evaluated, further improving the accuracy and scientific nature of the evaluation of the reservoir to be evaluated.

[0134] Bus 530 is used to connect different components of electronic device 500 and may include a data bus, an address bus and a control bus.

[0135] Electronic device 500 can communicate with one or more external devices 600 (such as keyboard, mouse, external controller, etc.) through I / O interface 540.

[0136] Electronic device 500 can communicate with one or more networks via network adapter 550. For example, network adapter 550 can provide mobile communication solutions such as 3G / 4G / 5G, or wireless communication solutions such as wireless LAN, Bluetooth, and near-field communication. Network adapter 550 can communicate with other modules of electronic device 500 via bus 530.

[0137] Although not shown in Figure 5, other hardware and / or software modules may be configured in the electronic device 500, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0138] As can be seen from the above, the technical solutions disclosed herein can be implemented as methods, apparatus, systems, computer program products, storage media, electronic devices, etc. Those skilled in the art will understand that various aspects of this disclosure can be specifically implemented in the following forms: a completely hardware implementation, a completely software implementation (including firmware, microcode, etc.), or an implementation combining hardware and software aspects, which may be referred to as "circuit," "module," or "system," respectively.

[0139] It should be understood that this disclosure is not limited to the specific methods, steps, or structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. Those skilled in the art will readily conceive of other embodiments based on the specific implementations provided in this disclosure. Therefore, the specific implementations provided in this disclosure are merely exemplary, and the scope and spirit of this disclosure are indicated by the claims, and should cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary technical means in the art not disclosed in this disclosure.

Claims

1. A method for evaluating the safety of a reservoir, characterized in that, The method includes: determining reservoir data for the reservoir to be evaluated; the reservoir data includes characteristic data, measured data, and inspection data; determining the target building type of the reservoir to be evaluated based on the characteristic data, and constructing a safety evaluation index system based on the target building type and the safety evaluation content specified in the standards; inputting the safety evaluation index system, the measured data, and the inspection data into a comprehensive reservoir safety evaluation model to obtain the overall evaluation information of the reservoir to be evaluated.

2. The method according to claim 1, characterized in that, The safety evaluation index system includes the evaluation levels of the reservoir to be evaluated; the evaluation levels include the target level, the sub-evaluation level, and the evaluation index level.

3. The method according to claim 2, characterized in that, The safety evaluation index system, the measured data, and the inspection data are input into the reservoir safety comprehensive evaluation model to obtain the overall evaluation information of the reservoir to be evaluated. This includes: determining the performance evaluation matrix of the evaluation index layer based on the measured data, the inspection data, and the evaluation dimension information, and determining the first evaluation result vector based on the performance evaluation matrix; determining the first weight value of the evaluation index layer, and determining the second evaluation result vector of the sub-item evaluation layer based on the first weight value of the evaluation index layer and the first evaluation result vector; determining the second weight value of the sub-item evaluation layer, and determining the evaluation result vector of the target layer based on the second weight value of the sub-item evaluation layer and the second evaluation result vector; and determining the evaluation result vector of the target layer as the overall evaluation information of the reservoir to be evaluated.

4. The method according to claim 3, characterized in that, Determining the first weight value of the evaluation index layer includes: determining the single ranking weight of the evaluation index layer relative to the sub-item evaluation layer; determining the total ranking weight of the evaluation index layer relative to the target layer; and determining the first weight value of the evaluation index layer based on the single ranking weight and the total ranking weight.

5. The method according to claim 4, characterized in that, Determining the single-ranking weight of the evaluation index layer relative to the sub-item evaluation layer includes: constructing a first judgment matrix based on the content of the sub-item evaluation layer and the evaluation index layer in the safety evaluation index system; performing hierarchical single-ranking and consistency verification on the first judgment matrix to determine the eigenvector of the first judgment matrix; determining the maximum eigenvalue of the first judgment matrix based on the eigenvector of the first judgment matrix; and performing consistency verification on the first judgment matrix based on the maximum eigenvalue of the first judgment matrix to determine a target first judgment matrix that passes the consistency verification; and determining the single-ranking weight of the evaluation index layer relative to the sub-item evaluation layer based on the target first judgment matrix.

6. The method according to any one of claims 1-5, characterized in that, The method further includes: determining the safety level of the reservoir to be evaluated based on the overall evaluation information and the preset safety processing rules; and determining status information for indicating the operating status of the dam of the reservoir to be evaluated based on the safety level and the preset safety processing rules.

7. The method according to claim 6, characterized in that, The method further includes: when the status information indicates a status within a preset status set, triggering a preset alarm message, the preset alarm message being used to instruct business personnel to perform corresponding adjustment measures.

8. A reservoir safety assessment device, characterized in that, The device includes: a first determining unit for determining reservoir data of the reservoir to be evaluated; a second determining unit for determining the target building type of the reservoir to be evaluated based on the reservoir data, and determining safety evaluation index information based on the target building type and the safety evaluation content specified in the standards; and an evaluation unit for inputting the safety evaluation index information and the reservoir data into a comprehensive reservoir safety evaluation model to obtain the overall evaluation information of the reservoir to be evaluated.

9. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the method described in any one of claims 1 to 7.

10. An electronic device, characterized in that, include: processor; A memory for storing executable instructions of the processor; wherein the processor is configured to perform the method of any one of claims 1 to 7 by executing the executable instructions.

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