Method and system for evaluating installation position of ammeter collector

Abstract

The invention discloses an ammeter collector installation position evaluation method and system, and relates to the technical field of electric power Internet of Things data acquisition management, and the method comprises the steps: collecting the multi-source environment data of an installation region, constructing a candidate installation position model, and screening installation conditions; for the candidate installation positions, calling a multi-factor inference rule to output candidate position suitability scores; and on the basis of the candidate position suitability score, according to the scene weight adjustment rule and the index weight, outputting a comprehensive evaluation score of the candidate position. According to the method, the multi-source environment data of the installation area is collected, the candidate installation position model is constructed, the multi-factor inference rule and scene weight dynamic optimization are combined, the comprehensive adaptability of the candidate positions is scientifically evaluated, the scientificity and fineness of installation position planning can be effectively improved, the communication performance is optimized, the electromagnetic interference risk is reduced, and the reliability of installation position planning is improved. And the maintenance convenience and controllability are enhanced, the capability of adapting to a complex environment is stronger, and the overall operation quality and reliability of an ammeter acquisition system are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of data collection and management of electric power Internet of Things, and in particular to a method and system for evaluating the installation position of an electric meter collector. Background Art

[0002] Amid the rapid development of smart grids and the power Internet of Things (IoT), meter collectors, as key information collection and transmission nodes, are responsible for the efficient aggregation and remote transmission of electricity metering data. In recent years, with the widespread adoption of wireless communication technologies such as low-power wide area networks (LPWANs), NB-IoT, and LoRa in power meter reading systems, the deployment density of meter collectors has continued to increase, placing higher demands on the rationality of their installation locations. Strategically planning the installation location of meter collectors not only directly impacts data communication quality but also affects system operational stability and maintenance costs. Consequently, research on optimizing meter collector installation locations has gradually garnered industry attention, with some existing solutions attempting to provide installation guidance based on communication signal coverage maps and building structure diagrams.

[0003] Existing technologies often focus on simple references to static parameters and lack comprehensive evaluation methods that are systematic, multi-dimensional, and dynamically optimized. Rough site selection often relies on manual experience combined with a single metric (such as communication signal strength). This fails to fully consider the complex coupling relationships between multiple factors, such as electromagnetic compatibility, structural stability, maintenance accessibility, and construction feasibility. This results in actual installation results being susceptible to fluctuations in the on-site environment, making it difficult to guarantee communication quality and subsequent maintenance reliability. Existing technologies generally fail to establish a complete candidate location model and lack dynamic screening and nonlinear inference optimization mechanisms. This makes it impossible to adaptively adjust indicator weights and target parameters for different installation scenarios (such as high-interference industrial areas and older building environments), resulting in insufficient intelligence and refinement in installation decisions. Summary of the Invention

[0004] In view of the above-mentioned problems, the present invention is proposed.

[0005] Therefore, the technical problems solved by the present invention are: the existing method for evaluating the installation location of meter collectors has a single evaluation indicator, lacks multi-dimensional comprehensive consideration, cannot realize dynamic screening and optimization of candidate locations, lacks adaptive optimization capabilities for complex scenarios, and how to achieve scientific planning and intelligent auxiliary decision-making of the installation location of meter collectors.

[0006] To solve the above technical problems, the present invention provides the following technical solutions: a method for evaluating the installation location of an electricity meter collector, comprising collecting multi-source environmental data of an installation area, constructing a candidate installation location model to screen installation conditions; the multi-source environmental data of the installation area includes the spatial layout of the building structure, the distribution density of electricity meters, information on obstructions, wall materials, power access conditions, wireless communication signal quality, and the distribution of electromagnetic interference sources; for the candidate installation location, calling a multi-factor inference rule to output a candidate location adaptability score; based on the candidate location adaptability score, outputting a comprehensive evaluation score of the candidate location according to the scenario weight adjustment rule and the indicator weight; constructing the candidate installation location model to screen installation conditions includes, based on the multi-source environmental data of the installation area, automatically constructing a candidate installation location model using preset spatial topology rules, dynamically screening a set of location nodes that meet the installation conditions, and constructing a candidate installation location set; calling the multi-factor inference rule to output the candidate location adaptability score includes, for the candidate location set, calling a predefined multi-factor inference rule library, scoring each candidate location based on communication signal quality, electromagnetic compatibility, post-maintenance convenience, structural stability, and construction feasibility indicators, and dynamically generating the candidate location adaptability score.

[0007] As a preferred solution of the method for evaluating the installation location of an electric meter collector described in the present invention, the method of outputting the comprehensive evaluation score of the candidate location based on the scenario weight adjustment rules and the indicator weights includes dynamically adjusting the indicator weights based on the scenario weight adjustment rules, outputting the comprehensive evaluation score of the candidate location, and generating a sorting optimization result.

[0008] As a preferred solution of the method for evaluating the installation location of an electric meter collector described in the present invention, the method of outputting the comprehensive evaluation score of the candidate location based on the scenario weight adjustment rules and indicator weights includes outputting the installation location based on the candidate location adaptability score and generating an auxiliary decision report.

[0009] As a preferred solution of the method for evaluating the installation location of an electric meter collector according to the present invention, the auxiliary decision report includes reasons for recommendation, location score details, and precautionary information.

[0010] Another object of the present invention is to provide an electricity meter collector installation location assessment system that can output a comprehensive assessment score for a candidate location based on the candidate location adaptability score, scenario weight adjustment rules, and indicator weights. This solves the problem that current electricity meter collector installation location assessment methods are unable to achieve dynamic screening and optimization of candidate locations and lack adaptive optimization capabilities for complex scenarios.

[0011] As a preferred solution of the meter collector installation position evaluation system described in the present invention, it includes: an installation area multi-source environmental data acquisition module, a candidate installation position model construction module, a candidate position adaptability score output module, a comprehensive evaluation module, and an installation position recommendation module; the installation area multi-source environmental data acquisition module is used to collect in real time the installation area multi-source environmental data including the building structure spatial layout, meter distribution density, obstruction information, wall material, power supply access conditions, wireless communication signal quality, and electromagnetic interference source distribution; the candidate installation position model construction module is used to construct a candidate installation position model using a preset spatial topology rule after the installation area multi-source environmental data acquisition module completes the collection, and screen the candidate installation position models that meet the installation requirements. A set of location nodes meeting the installation conditions is used to construct a set of candidate installation locations; the candidate location adaptability score output module is used to call a predefined multi-factor reasoning rule library after the candidate installation location model construction module outputs the candidate installation location set, and infer each candidate location based on communication signal quality, electromagnetic compatibility, post-maintenance convenience, structural stability, and construction feasibility indicators to output the candidate location adaptability score; the comprehensive evaluation module is used to output the comprehensive evaluation score of the candidate location based on the candidate location adaptability score and the scenario weight adjustment rule after the candidate location adaptability score output module outputs the candidate location adaptability score, and generate a ranking result; the installation location recommendation module is used to output the installation location through the ranking result of the comprehensive evaluation module.

[0012] A computer device includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement a method for evaluating an installation location of an electricity meter collector.

[0013] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of a method for evaluating the installation position of an electricity meter collector.

[0014] Beneficial effects of the present invention: The method for evaluating the installation location of an electric meter collector provided by the present invention collects multi-source environmental data of the installation area and constructs a candidate installation location model, thereby achieving comprehensive perception and structured expression of the installation environment of the electric meter collector and providing an accurate data basis for subsequent evaluation. By calling multi-factor inference rules to quantitatively score candidate locations based on multi-dimensional indicators such as communication signal quality, electromagnetic compatibility, convenience of later maintenance, structural stability and construction feasibility, a nonlinear evaluation of the comprehensive performance of each location is achieved, overcoming the limitations of traditional single-indicator, static evaluation methods. Furthermore, by dynamically adjusting the weights of each indicator according to the scenario weight adjustment rules, the comprehensive evaluation score can be adapted to different application environments, achieving intelligent optimization tailored to local conditions, and improving the adaptability of the method to complex and variable installation scenarios. Finally, by outputting a comprehensive ranking of the preferred installation locations and generating an auxiliary decision-making report containing recommendation reasons, location score details and precautions, the installation process is made more standardized and scientific, and the decision-making deviation caused by differences in human experience is reduced. Overall, the present invention effectively improves the scientific nature of the installation location planning of the meter collector, the reliability of communication, and the convenience of subsequent maintenance, and enhances the stability and controllability of the system operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0016] Figure 1 This is an overall flow chart of a method for evaluating the installation location of an electricity meter collector provided in Example 1 of the present invention. DETAILED DESCRIPTION

[0017] To make the above-mentioned objects, features, and advantages of the present invention more clearly understood, the following detailed description of the specific embodiments of the present invention is given in conjunction with the accompanying drawings. It is obvious that the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in this field without creative work should fall within the scope of protection of the present invention.

[0018] Example 1, reference Figure 1 , as one embodiment of the present invention, provides a method for evaluating the installation location of an electric meter collector, comprising: S1: Collect multi-source environmental data of the installation area, build a candidate installation location model and screen installation conditions.

[0019] Furthermore, mobile terminals or portable data collection devices are used to conduct on-site inspections of the planned installation area of ​​the meter collector, and real-time collection of multi-source environmental data including the spatial layout of the building structure, meter distribution density, obstruction information, wall material, power access conditions, wireless communication signal quality (such as NB-IoT / 4G / LoRa), and electromagnetic interference source distribution. Standardized coding processing is then performed to generate a scenario data set.

[0020] It should be noted that the collected scene dataset In , the following subset features are defined: Spatial topological feature set (installation space size, structural load-bearing capacity, obstacle avoidance, etc.), : Power supply access feature set, :Communication environment feature set, : Electromagnetic interference feature set, : Maintaining the reachability feature set and defining the candidate location space , its mathematical expression is: ; in, Represents the set of all optional physical locations in the installation area. represents the candidate location point, Indicates location Evaluation function on each feature dimension (value range normalized to ), Indicates the filtering threshold parameter of the corresponding feature dimension.

[0021] S2: For the candidate installation location, call the multi-factor inference rule to output the candidate location suitability score.

[0022] Furthermore, in the filtered candidate position set For each candidate position By calling the predefined multi-factor inference rule library, a nonlinear multi-dimensional coupling scoring model is constructed to Dynamic reasoning calculation is performed on the adaptability of the position to generate a preliminary score of the position adaptability .

[0023] Define five core indicator systems, including communication signal quality , electromagnetic compatibility , convenience of later maintenance , structural stability and constructibility For each indicator system, the collection location The engineering quantifiable parameters under the normalization or mapping function Converted into scoring input.

[0024] For candidate locations Calculating the position suitability score , expressed as: ; ; in, Candidate location The initial score of suitability, For the candidate locations, For the The smoothing adjustment constant of the indicator, For the The nonlinear stretching coefficient of the indicator, For the Position under the indicator The normalized score value of For location In the The original measurement value under each indicator, For the The minimum measurement value of an indicator among all candidate locations, For the The maximum measurement value of an indicator among all candidate positions, For the The power exponential adjustment parameter of the indicator score, is the error term suppression coefficient, For the Position under the indicator The error term function, For the The target reference value of each indicator, is the nonlinear weighting exponent of the error term.

[0025] The value range is usually ,like , indicating that the location is seriously unsuitable for installation, with multiple substandard or large errors; if At an intermediate level (e.g. ), indicating that the location has general adaptability and can be weighed according to project requirements; if Larger (e.g. ), indicating that the location is highly preferred, has excellent overall performance, and is recommended for installation.

[0026] S3: Based on the adaptability score of the candidate location, the scenario weight adjustment rules and indicator weights are used to output the comprehensive evaluation score of the candidate location.

[0027] Furthermore, in the generated positional fit preliminary score matrix Based on this, for different installation scenarios (such as high-interference industrial areas, old building environments, complex building intranet environments, etc.), the scenario weight adjustment rule library is dynamically called to adjust the weights and target reference values ​​in the indicator system, driving the comprehensive evaluation optimization model to calculate the final comprehensive evaluation score for each candidate location. .

[0028] Define the scenario The corresponding characteristic factor , and build a scene-adaptive weight adjustment function based on the engineering experience library or machine learning model training results , target reference value adjustment function For each candidate position , call the following nonlinear composite optimization model to calculate its comprehensive evaluation score : ; in, For the The comprehensive evaluation score of the candidate positions, is the candidate position index, is the total number of indicators, For the The basic weight of the indicator, For the The scene sensitivity coefficient of each indicator is For the scene The characteristic function of For the The candidate position is The preliminary scores under the indicators are For the The smoothing parameter of the indicator, For the The logarithmic stretch coefficient of the indicator, For the The power index of the indicator, is the denominator error suppression coefficient, For the The benchmark target value of each indicator, For the The scenario adjustment coefficient of each indicator, For the scene The impact factor, For the The power exponent of the error term of the indicator, is the total suppression power of the overall error term.

[0029] It should be noted that ,like Indicates that the candidate position is seriously unsuitable, the overall performance is low, or multiple deviations from the threshold are too large. Median level (e.g. ), indicates that the location is relatively general and can be considered as an alternative. , indicating that the overall adaptability is excellent and installation is recommended first.

[0030] It should also be noted that the candidate location comprehensive evaluation score matrix generated , according to the set sorting optimization strategy (such as sorting in descending order by comprehensive evaluation score, or combining thresholds to filter priority intervals), select a set of recommended installation locations . Perform scene consistency check on the sorting results, targeting specific scene labels Dynamically adjust the number of recommended candidates And the recommendation reason explanation strategy to ensure that the output results have scenario adaptability and engineering feasibility. Generate a decision-making support report, which includes the following structured information: Recommendation reason: Based on each location The contribution of key indicators and the adjustment process of scenario weights are automatically extracted to form the core recommendation basis, and the main technical reasons for the preferred location (such as high communication signal strength, low electromagnetic interference and good structural stability) are clearly stated; Location score details: The score results and relative rankings of all indicators (communication signal quality, electromagnetic compatibility, convenience of later maintenance, structural stability, and construction feasibility) of each recommended location are displayed in the form of tables or visual charts, which is convenient for engineers to understand intuitively; Precautions: Combined with on-site environmental data and scoring anomalies, potential risks or matters requiring attention are automatically prompted (such as the presence of a high-frequency interference source near the location, it is recommended to strengthen shielding or the maintenance channel at the location is limited, and the construction feasibility needs to be confirmed); Traceability information: Records metadata such as the scenario weight parameters, evaluation model version, and environmental data collection timestamp used in this round of evaluation to facilitate subsequent review and optimization tracking.

[0031] Example 2, an embodiment of the present invention provides an electricity meter collector installation location evaluation system, including an installation area multi-source environmental data acquisition module, a candidate installation location model construction module, a candidate location adaptability score output module, a comprehensive evaluation module, and an installation location recommendation module.

[0032] The installation area multi-source environmental data acquisition module is used to collect multi-source environmental data of the installation area in real time, including the spatial layout of the building structure, the distribution density of electricity meters, information on obstructions, wall materials, power access conditions, wireless communication signal quality, and the distribution of electromagnetic interference sources, and generate a scene data set after standardized coding processing.

[0033] It should also be noted that the installation area multi-source environmental data acquisition module completes the normalized encoding, timestamp labeling, and acquisition status verification of the above-mentioned multi-source environmental data, and uses the scene data set as the input prerequisite of the candidate installation location model construction module to start the candidate location modeling process.

[0034] The candidate installation location model construction module is used to automatically construct a candidate installation location model based on the scene data set provided by the installation area multi-source environment data acquisition module, using preset spatial topology rules, to screen the set of location nodes that meet the installation conditions to form a candidate installation location set.

[0035] It should also be noted that the candidate installation location model construction module completes spatial constraint verification, structural bearing capacity analysis, and obstacle avoidance strategy processing during the screening process, and annotates the candidate location set with spatial coordinate information and unique location identifiers, which serve as the input basis for the candidate location adaptability score output module and drive the subsequent reasoning and scoring process.

[0036] The candidate location adaptability score output module is used to call the predefined multi-factor reasoning rule library after the candidate installation location model construction module outputs the candidate installation location set, perform reasoning calculations on each candidate location based on indicators such as communication signal quality, electromagnetic compatibility, post-maintenance convenience, structural stability, and construction feasibility, and output the candidate location adaptability score.

[0037] It should also be noted that the candidate location adaptability score output module completes the standardized mapping of each indicator score, dynamic loading of inference rules, and inference calculation log recording, and directly passes the output adaptability score matrix to the comprehensive evaluation module. At the same time, it outputs the score anomaly monitoring results for reference when the comprehensive evaluation module adjusts the weights.

[0038] The comprehensive evaluation module is used to dynamically adjust the weights of each indicator based on the adaptability score provided by the candidate location adaptability score output module according to the scenario weight adjustment rules, calculate the comprehensive evaluation score of the output candidate location, and generate the ranking result.

[0039] It should also be noted that during the calculation process, the comprehensive evaluation module completes scene label identification, weight adjustment parameter loading, and dynamic correction of target reference values, and generates a comprehensive score matrix and ranking optimization results for candidate locations, which serve as input to the installation location recommendation module and drive the final recommendation process.

[0040] The installation location recommendation module is used to optimize the output of the target installation location based on the sorting results of the comprehensive evaluation module, and automatically generate an auxiliary decision-making report containing information such as recommendation reasons, location score details, and precautions.

[0041] It should also be noted that during the recommendation process, the installed location recommendation module completes the screening of preferred locations, generation of recommendation reasons, visual arrangement of scoring details, supplementation of risk warning items, and records the metadata of this round of recommendation results (such as evaluation rule version, timestamp, scenario label) for system tracing and optimization and improvement.

Claims

1. A method for evaluating the installation position of an electric meter collector, characterized in that: include: Collect multi-source environmental data of the installation area, build a candidate installation location model and screen installation conditions; The multi-source environmental data of the installation area includes the spatial layout of the building structure, the distribution density of electric meters, information about obstructions, wall materials, power access conditions, wireless communication signal quality, and the distribution of electromagnetic interference sources; For the candidate installation locations, call the multi-factor inference rule to output the candidate location suitability score; Based on the candidate location's suitability score, the scenario weight adjustment rules and indicator weights are used to output a comprehensive evaluation score for the candidate location. Constructing a candidate installation location model to screen installation conditions includes automatically constructing a candidate installation location model based on multi-source environmental data of the installation area and using preset spatial topology rules, dynamically screening a set of location nodes that meet the installation conditions, and constructing a candidate installation location set; Calling the multi-factor reasoning rule to output the candidate location suitability score includes calling a predefined multi-factor reasoning rule library for the candidate location set, scoring each candidate location based on communication signal quality, electromagnetic compatibility, post-maintenance convenience, structural stability, and construction feasibility indicators, and dynamically generating the candidate location suitability score.

2. The method for evaluating the installation position of an electric meter collector according to claim 1, wherein: The comprehensive evaluation score of the candidate position outputted based on the scenario weight adjustment rules and indicator weights includes: According to the scenario weight adjustment rules, the indicator weights are dynamically adjusted, the comprehensive evaluation scores of the candidate locations are output, and the ranking optimization results are generated.

3. The method for evaluating the installation position of an electric meter collector according to claim 2, wherein: The comprehensive evaluation score of the candidate position outputted based on the scenario weight adjustment rules and indicator weights includes: Based on the suitability scores of the candidate locations, the installation location is output and an auxiliary decision report is generated.

4. The method for evaluating the installation position of an electric meter collector according to claim 3, wherein: The decision support report includes: Reasons for recommendation, location score details, and precautions.

5. A system for evaluating the installation location of an electric meter collector, characterized by: It includes the installation area multi-source environmental data collection module, candidate installation location model construction module, candidate location adaptability score output module, comprehensive evaluation module, and installation location recommendation module; The installation area multi-source environmental data acquisition module is used to collect real-time multi-source environmental data of the installation area, including building structure spatial layout, meter distribution density, obstruction information, wall material, power access conditions, wireless communication signal quality, and electromagnetic interference source distribution; The candidate installation location model building module is used to build a candidate installation location model using preset spatial topology rules after the installation area multi-source environment data collection module completes the collection, screen the location node set that meets the installation conditions, and build a candidate installation location set; The candidate location suitability score output module is used to call a predefined multi-factor reasoning rule library after the candidate installation location model construction module outputs the candidate installation location set, and to reason and output a candidate location suitability score for each candidate location based on communication signal quality, electromagnetic compatibility, post-maintenance convenience, structural stability, and construction feasibility indicators; The comprehensive evaluation module is used to output the comprehensive evaluation score of the candidate position based on the candidate position adaptability score and the scene weight adjustment rule after the candidate position adaptability score output module outputs the candidate position adaptability score, and generate a ranking result; The installation location recommendation module is used to output the installation location based on the sorting results of the comprehensive evaluation module.

6. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method for evaluating the installation location of an electricity meter collector according to any one of claims 1 to 4 are implemented.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for evaluating the installation location of an electricity meter collector according to any one of claims 1 to 4 are implemented.

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