A digital management system and method for group metrology assurance

Abstract

The present application relates to the technical field of metrological testing, in particular to a digital management system and method for group metrological guarantee, wherein the digital management system comprises a metrological data acquisition module, a metrological data processing module, a quantity transmission control module and a process control module. The above scheme realizes the technical paradigm conversion from periodic verification of each distributed metrological instrument to group real-time guarantee through the collaborative operation of the four core modules of metrological data acquisition, processing, online closed-loop quantity transmission control and process control, constructs a digital closed-loop management and control system for group metrological guarantee, and greatly reduces the overall metrological management and control cost and improves the traceability efficiency under the premise of ensuring legal metrology compliance.

Description

Technical Field

[0001] This invention relates to the field of metrology and testing technology, and more specifically, to a digital management system and method for ensuring mass metrology. Background Technology

[0002] The Metering Assurance Program (MAP) is an internationally recognized method for traceability and quality control of metrological values. It assesses the reliability of the measurement process and the metrological characteristics of the results by comparing measurement results with reference standards. Traditional MAPs primarily target single measuring instruments or a small number of devices, relying on the periodic verification of physical standards and following an open-loop measurement transfer model, ensuring traceability of only a single instrument at the time of verification. With the deep integration of industrial automation, intelligentization, and the Internet of Things (IoT), the application scenarios of measuring instruments have rapidly evolved from traditional single-point, small-scale deployments to large-scale, distributed clusters. Examples include massive distributed measuring instrument groups such as smart meters, charging pile clusters, and sensor networks. These groups possess real-time data upload capabilities, support data interaction among multiple types of instruments, and place greater emphasis on ensuring the overall metrological reliability of the group.

[0003] However, traditional metrological assurance solutions have the following drawbacks for the aforementioned massive distributed group of metrological instruments: the traditional model relies entirely on physical standards, requiring professional calibration personnel to carry the standards to dispersed sites for calibration, or to disassemble and send the massive number of instruments for inspection one by one. This not only consumes time and effort for calibration personnel and results in long calibration cycles, but also has fixed costs for calibration materials, labor, and transportation for a single instrument. In massive deployment scenarios (hundreds to tens of thousands of instruments in a single scenario), the overall metrological cost increases exponentially, completely lacking economies of scale and making it difficult to achieve full coverage control of all instruments. Furthermore, the calibration cost of a single low-cost metrological instrument far exceeds its own value, resulting in a serious waste of regulatory resources. Summary of the Invention

[0004] The purpose of this application is to provide a digital management system and method for ensuring group measurement, so as to solve the above-mentioned technical problems.

[0005] In a first aspect, embodiments of this application provide a digital management system for group metering assurance, comprising:

[0006] The metering data acquisition module is configured to collect metering data, operating status and environmental parameters of massive distributed metering instruments in real time, and output the raw metering data through wired or wireless transmission.

[0007] The measurement data processing module, connected to the measurement data acquisition module, is configured to perform integrity, accuracy, consistency, traceability verification and anti-tampering security processing on the raw measurement data, and output valid measurement data.

[0008] The measurement transmission control module, connected to the measurement data processing module, is configured to construct physical anchor points based on historical laboratory verification data and on-site online calibration data, and to construct an algorithm model standard based on the group topology algorithm to form a dual-morphology virtual standard; and to use the dual-morphology virtual standard to implement online closed-loop measurement transmission control on the effective measurement data, perform real-time verification to monitor measurement value drift, and generate warning information when the detected measurement value drift exceeds the warning threshold;

[0009] The process control module, connected to the measurement data processing module and the measurement transmission control module respectively, is configured to receive the early warning information, classify and group the massive distributed measurement instruments based on instrument type, accuracy level and online measurement transmission status, conduct statutory metrological verification on the verification samples and issue legally valid verification certificates, and feed back the verification results to the measurement transmission control module to correct the parameters of the dual-mode virtual standard.

[0010] Furthermore, the data transfer control module performs the real-time period check, including:

[0011] For each individual instrument in the massive distributed metering instrument, the real-time measured value after processing by the metering data processing module is obtained, as well as the real-time standard value corresponding to the dual-mode virtual standard. The real-time measured value and the real-time standard value are kept at the same time.

[0012] Calculate the drift between the real-time measured value and the real-time standard value of each individual instrument;

[0013] The drift value of each individual instrument is compared with the warning threshold, and the proportion of individual instruments whose drift value does not exceed the warning threshold among the massive distributed metering instruments is counted to obtain the period verification pass rate.

[0014] The effectiveness of the online closed-loop data transfer control is determined based on the pass rate of the period verification. When the online closed-loop data transfer control is determined to be invalid, the warning information is generated and sent to the process control module to trigger the sampling verification and parameter correction of the dual-mode virtual standard.

[0015] Furthermore, the process control module is also configured to:

[0016] Establish a two-way synchronization link for full-volume control data, and synchronize the full results of the sampling verification, the verification conclusions of the statutory metrological verification, and the offline handling records of abnormal instruments to the quantity transmission control module in real time;

[0017] The measurement transmission control module is further configured to: based on the traceable standard measurement data corresponding to the verification conclusion of the statutory metrological verification, correct the physical anchor point benchmark and algorithm model standard parameters of the dual-mode virtual standard, and optimize the verification strategy of the real-time period verification based on the full results of the sampling verification and the offline processing records.

[0018] Furthermore, the process control module implements the classification, grouping, and sampling verification, including:

[0019] The massive distributed metering instruments are categorized and grouped based on instrument type, accuracy level, usage scenario, and online measurement status.

[0020] For each group of categorized appliances, a representative sample of appliances is selected using statistical sampling methods, a differentiated verification plan is developed, and the sampling verification is implemented.

[0021] Establish a dynamic adjustment mechanism for sampling strategies, and iteratively optimize the sampling frequency and sampling ratio based on historical sampling verification results: if long-term sampling verification shows no systematic deviation in online data transmission results, then gradually reduce the sampling frequency and ratio; if sampling reveals a high anomaly rate or high deviation risk, then increase the sampling frequency and tighten the sampling rules.

[0022] Furthermore, the process control module is also configured to:

[0023] For abnormal instruments warned by the measurement control module and non-conforming instruments found by the sampling inspection, a mandatory control process of first confirming the measurement and then handling them in a graded manner is established.

[0024] The metrological verification includes: performing metrological verification on all measuring instruments that are warned by the measurement transmission control module through the statutory metrological verification or calibration method, so as to locate the cause of the instrument abnormality and clarify the metrological performance deviation;

[0025] The graded handling includes: classifying the anomalies into minor, moderate, and severe levels, and implementing differentiated closed-loop handling: minor levels involve on-site parameter adjustment and correction; moderate levels involve calibration repair and metrological verification; and severe levels involve suspension of use and replacement or in-depth repair; and feeding back the metrological verification conclusions and the graded handling records to the measurement transmission control module.

[0026] Furthermore, the metering data processing module is also configured to:

[0027] The original measurement data is encrypted and hash-verified using a data tampering verification algorithm; and a data quality admission threshold is established to remove data that is determined to be abnormal after verification.

[0028] Furthermore, the measurement control module constructs the dual-mode virtual standard, including:

[0029] Based on historical laboratory testing data and on-site online calibration data, physical anchor points with legal traceability are constructed;

[0030] Furthermore, an algorithm model standard is constructed to adapt to the group topology of the massive distributed metering instruments; wherein the algorithm model standard includes: for tree topology with clear hierarchical links, a hierarchical value transfer algorithm based on energy conservation is adopted; and for wide-area distributed mesh topology, a distributed node mutual verification algorithm based on multi-source data consistency verification is adopted.

[0031] Furthermore, the process control module is also configured to: perform statutory metrological verification according to the corresponding statutory cycle for measuring instruments with statutory periodic verification requirements; and perform special statutory metrological verification for measuring instruments of key control categories determined by the classification and grouping.

[0032] Furthermore, the metering data acquisition module is also configured to: configure differentiated acquisition strategies as needed according to the type of appliance and the usage scenario, wherein the differentiated acquisition strategies include real-time acquisition and timed acquisition.

[0033] Secondly, embodiments of this application provide a digital management method for population measurement assurance, the method comprising:

[0034] It collects metering data, operating status and environmental parameters of massive distributed metering instruments in real time, and obtains raw metering data through wired or wireless transmission.

[0035] The original measurement data is verified for completeness, accuracy, consistency, traceability, and tamper-proof security, and valid measurement data is output.

[0036] Physical anchor points are constructed based on historical laboratory calibration data and on-site online calibration data, and algorithm model standards are constructed based on the group topology algorithm to build a dual-morphology virtual standard. The dual-morphology virtual standard is used to implement online closed-loop measurement transmission control on the effective measurement data, perform real-time verification to monitor measurement drift, and generate warning information when the measured drift exceeds the warning threshold.

[0037] Upon receiving the warning information, the system categorizes and groups the massive distributed measuring instruments based on instrument type, accuracy level, and online measurement status, and conducts sampling verification. The system performs statutory metrological verification on the verification samples and issues legally valid verification certificates. The verification results are then fed back to correct the parameters of the dual-mode virtual standard.

[0038] The advantages or beneficial effects of the above technical solutions include at least the following:

[0039] First, through the coordinated operation of four core modules—data acquisition, processing, online closed-loop data transmission control, and process control—a digital closed-loop management and control system for group metrology assurance is constructed. This enables a technological paradigm shift from periodic inspection of individual distributed metrology instruments to real-time group assurance, significantly reducing overall metrology management and control costs and improving traceability efficiency while ensuring legal metrology compliance.

[0040] Second, online closed-loop measurement control is implemented using dual-mode virtual standards. Digital full-link comparison replaces traditional single-point open-loop measurement, reducing the number of physical standards and the need for on-site calibration of each instrument. Combined with the classification, grouping and sampling verification mechanism of the process control module, the online evaluation results are verified by non-full offline verification. Relying on economies of scale, the measurement assurance cost of a large number of measuring instruments is reduced and the traceability cycle is shortened.

[0041] Third, by acquiring real-time data from the measurement data acquisition module and cleaning, verifying, and tamper-proofing security processing from the measurement data processing module, combined with real-time periodic verification and value drift monitoring from the measurement transmission control module, the real-time assessment and dynamic control of the value status of a large number of measuring instruments can be achieved, timely detection of value drift and data anomalies can be achieved, and the time limitations of traditional static periodic verification can be broken.

[0042] Fourth, the measurement control module, as the core online traceability carrier, enables large-scale real-time measurement calibration. The process control module provides legally valid verification certificates through statutory metrological verification and conducts sampling checks to supplement blind spots in online management. This forms a closed-loop collaborative mechanism that triggers online early warnings, enables offline metrological confirmation and graded handling, and optimizes online parameters through offline result feedback, thus balancing the technical effectiveness and legal compliance of metrological assurance.

[0043] Other features and advantages of the invention will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing the embodiments of this application. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the written description, claims, and drawings. Attached Figure Description

[0044] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0045] Figure 1 A schematic diagram of the architecture of a digital management system for population measurement assurance provided in an embodiment of this application;

[0046] Figure 2 A schematic diagram of the application process of a digital management system for group metering assurance in a certain application scenario provided in this application embodiment;

[0047] Figure 3 This is a flowchart illustrating a digital management method for population measurement assurance provided in an embodiment of this application.

[0048] The numbers in the diagram are as follows:

[0049] 100. Digital management system for group metering assurance; 110. Metering data acquisition module; 120. Metering data processing module; 130. Metering transmission control module; 140. Process control module. Detailed Implementation

[0050] The embodiments of the technical solution of the present invention will be described in detail below with reference to the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and are therefore only examples, not intended to limit the scope of protection of the present invention. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains; the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the invention; the terms "comprising" and "having," and any variations thereof, in the specification, claims, and the foregoing description of the accompanying drawings, are intended to cover non-exclusive inclusion. In the description of the embodiments of this application, technical terms such as "first," "second," etc., are only used to distinguish different objects and should not be construed as indicating or implying relative importance or implicitly indicating the number, specific order, or primary or secondary relationship of the indicated technical features. In the description of the embodiments of this application, "a plurality of" means two or more, unless otherwise explicitly specified. The reference to "embodiment" herein means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the present invention. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0051] Metrological Assurance Scheme (MAP) is an internationally recognized method for traceability and quality control of metrological values. It assesses the reliability of the measurement process and the metrological characteristics of the measurement results by comparing the measurement results with reference standards. Traditional MAPs are mainly for single measuring instruments or a small number of devices, relying on the periodic verification of physical standards and following an open-loop measurement transfer model. They can only guarantee the traceability of a single instrument at the time of verification and cannot meet the management needs of a large number of measuring devices. With the deep integration of industrial automation, intelligence and Internet of Things technologies, the application scenarios of measuring instruments have rapidly developed from traditional single-point and small-scale deployment to large-scale and distributed clusters. This system is specifically adapted to distributed measuring instruments, and its characteristics are: (1) It has the characteristics of massive deployment, with hundreds, thousands or even tens of thousands of units deployed in a single scenario / area, and mainly in a grid-like or decentralized layout; (2) It has the ability to upload data, and can upload measuring data, operating status and other information to the data platform in real time to support data interaction and analysis; (3) It supports data interaction of various types of measuring instruments, and can realize data interoperability of measuring instruments of different specifications and different uses; In addition, the metrological characteristics of such instruments are not high, and there is no need to use high-precision metrological standards for separate calibration, and more attention is paid to ensuring the overall metrological reliability of the group.

[0052] However, the above solution has the following drawbacks:

[0053] (1) High metrology costs: For a large number of distributed metrology instruments, the deployment scenarios are grid-like and decentralized. Some instruments are even deployed in remote areas or complex environments. Traditional metrology models rely entirely on physical standards. Professional calibration personnel carry the standards to the site for calibration one by one, or disassemble and send the massive number of instruments for inspection one by one. Not only is it time-consuming and labor-intensive for calibration personnel to travel back and forth, and the calibration cycle is long, but the cost of calibration materials, labor, transportation and other costs for a single instrument is fixed. In the case of a massive deployment of hundreds to tens of thousands of instruments in a single scenario, the overall metrology cost increases exponentially. It does not have the scale control effect at all and it is difficult to achieve full coverage of all instruments. Moreover, the calibration cost of a single low-cost metrology instrument far exceeds its own value, resulting in serious waste of regulatory resources.

[0054] (2) Difficulty in real-time supervision: These massive distributed metering instruments all have the function of real-time data upload. The metering data needs to be transmitted to the control platform in real time through the network for subsequent metering analysis and control. However, because the data is in a state of real-time online transmission, storage and interaction, there is a possibility of real-time tampering in multiple links such as transmission links and storage nodes. There may be cases of malicious tampering of metering data to evade supervision and seek improper benefits, and there may also be risks of illegal intrusion into the system to tamper with the data. Moreover, the tampering behavior is real-time and covert, and it is difficult to be detected in time. After the data is tampered with, it cannot reflect the real operating status and metering results of the metering instruments, resulting in the inability to monitor the drift of measurement values, abnormal operation and other situations based on real and effective data. There is a lack of pre-warning and in-process intervention mechanisms. It can only be dealt with after obvious problems occur. There is a serious risk of data distortion and metering control loopholes, and it is impossible to achieve effective supervision of massive distributed metering instruments.

[0055] In view of this, this application provides a digital management system for group metrological assurance. This system constructs a digital closed-loop management and control system for group metrological assurance through the coordinated operation of four core modules: metrological data acquisition, processing, online closed-loop measurement transmission control, and process control. This realizes the technological paradigm shift from periodic inspection of individual distributed metrological instruments to real-time group assurance, and significantly reduces the overall metrological management and control cost and improves traceability efficiency while ensuring legal metrological compliance.

[0056] like Figure 1 As shown, this application embodiment provides a digital management system 100 for group metering assurance, including:

[0057] The metering data acquisition module 110 is configured to collect metering data, operating status and environmental parameters of massive distributed metering instruments in real time, and output the raw metering data through wired or wireless transmission.

[0058] The measurement data processing module 120, connected to the measurement data acquisition module 110, is configured to perform integrity, accuracy, consistency, traceability verification and anti-tampering security processing on the raw measurement data, and output valid measurement data.

[0059] The measurement transmission control module 130 is connected to the measurement data processing module 120 and is configured to construct physical anchor points based on historical laboratory verification data and on-site online calibration data, and to construct an algorithm model standard based on the group topology algorithm to form a dual-morphology virtual standard; and to use the dual-morphology virtual standard to implement online closed-loop measurement transmission control on effective measurement data, perform real-time verification to monitor measurement drift, and generate warning information when the measured drift exceeds the warning threshold.

[0060] The process control module 140 is connected to the measurement data processing module 120 and the measurement transmission control module 130 respectively. It is configured to receive early warning information, classify and group a large number of distributed measurement instruments based on instrument type, accuracy level and online measurement transmission status, conduct statutory metrological verification on the verification samples and issue legally valid verification certificates, and feed back the verification results to the measurement transmission control module 130 to correct the parameters of the dual-mode virtual standard.

[0061] The aforementioned metering data acquisition module 110 serves as the fundamental data entry point for the digital management architecture of group metering assurance. It directly interacts with a massive number of distributed metering instruments, establishing data connections through standardized interfaces. It captures multi-dimensional information reflecting the instrument's metering characteristics and operating conditions in real time, converting the captured information into raw metering data format recognizable by subsequent processing modules before outputting it. The data collected by the metering data acquisition module 110 covers three dimensions: first, core business metering data, including quantity information reflecting the measured value such as electrical energy, voltage, and current; second, equipment operating status data, characterizing the instrument's current working mode, communication status, and hardware health; and third, environmental parameter data, such as temperature and humidity, which affect metering accuracy. These data collectively constitute a complete data foundation for evaluating the metering characteristics of the instruments.

[0062] At the data transmission level, the metering data acquisition module 110 supports both wired and wireless transmission media. It can ensure the stability of data transmission for fixed-location equipment through wired methods such as Ethernet, or adapt to the communication needs of equipment in dispersed and remote areas by using wireless technologies such as LoRa and carrier communication, so as to realize the reliable transmission of metering data from the equipment to the data processing module.

[0063] In addition, the metering data acquisition module 110 deploys a dedicated data acquisition unit to establish a physical connection or communication handshake with the metering instrument. It continuously reads the metering information stored inside the instrument and the real-time status register value according to the system's preset acquisition cycle. After performing preliminary format conversion on the read raw signal, it pushes the raw metering data to the metering data processing module in real time through the selected transmission link, thus completing the closed loop of the data acquisition process.

[0064] The aforementioned measurement data processing module 120 is deployed at the data output end of the measurement data acquisition module 110. It serves as a preprocessing hub for the raw measurement data before it enters the subsequent measurement transmission and control stages. It establishes a stable data interface with the upstream acquisition module, receives the raw measurement data stream delivered via wired or wireless transmission links, and executes standardized quality control procedures to ensure the availability of the output data. The measurement data processing module 120 implements a four-level progressive data verification mechanism: sequentially performing integrity verification to identify record gaps caused by missing data packets or transmission interruptions; accuracy verification to eliminate abnormal readings that significantly deviate from the range of physical quantities; consistency verification to eliminate logical contradictions caused by asynchronous time bases or format conflicts among multiple data sources; and traceability verification to confirm the correctness of the mapping relationship between the data source identifier and the instrument's identity. Through multi-dimensional quality screening, a data access threshold is established.

[0065] In terms of security protection, the metering data processing module 120 is embedded with an anti-tampering security processing mechanism. In response to the risk of malicious tampering or illegal intrusion attacks that may be encountered during real-time online transmission, it performs integrity protection operations on the original metering data and verifies the originality of the data in the transmission link and storage node through cryptographic means, so as to ensure that the data foundation used for subsequent metering control and legal verification is true and reliable.

[0066] After undergoing four levels of verification and anti-tampering security processing, the data is marked as valid measurement data. The measurement data processing module 120 pushes the valid measurement data to the measurement transmission control module through a standardized data interface, serving as the benchmark input for online measurement transmission comparison using a virtual standard. At the same time, it synchronizes data anomaly identification and equipment classification information to the process control module, supporting the data requirements for offline sampling verification and completing the value transformation from raw data to valid data.

[0067] The aforementioned measurement transmission control module 130 is deployed downstream of the measurement data processing module 120 at its data interface. As the core computational unit for online measurement traceability, it establishes a digital measurement value transmission link with a massive distributed group of measuring instruments by constructing a dual-form virtual standard to replace the traditional physical standard, thus implementing remote measurement transmission control without physical contact. The physical anchor points in the measurement transmission control module 130 are constructed by integrating historical laboratory verification data issued by metrology institutions with online calibration data returned from portable on-site standards. Verification conclusions with legal traceability are used as constraints for the group-level measurement value benchmark, providing a true measurement value calibration basis for the virtual standard. The algorithm model standard is constructed based on the group topology algorithm of massive distributed measuring instruments. A mathematical operation model is established for the geometric distribution characteristics and data interaction relationships of the instrument group deployment. The algorithm solves and generates virtual standard measurement values ​​that work in conjunction with the physical anchor points, forming a measurement value benchmark form parallel to the physical anchor points. The measurement control module 130 calls the effective measurement data cleaned by the measurement data processing module 120 and performs online comparison and calculation with the real-time standard value of the dual-mode virtual standard. Through the closed-loop feedback mechanism, the measurement deviation is continuously corrected, and the digital traceability of the group measurement value to the virtual standard is realized.

[0068] The aforementioned process control module 140 establishes data connections with both the metering data processing module 120 and the measurement transmission control module 130, serving as a link between online measurement transmission control and offline physical measurement. It receives warning information generated by the measurement transmission control module 130 when it detects that the measurement value drift exceeds the warning threshold, and initiates the offline verification process accordingly. Based on the received warning information and system operation data, the process control module 140 classifies and groups a massive number of distributed metering instruments. The grouping dimensions cover instrument type attributes, measurement accuracy level, and current online measurement transmission status, dividing the dispersed instrument group into several subgroups with similar risk characteristics or measurement needs, providing an organizational basis for the implementation of differentiated management strategies. After completing the classification and grouping, the process control module 140 extracts representative sample instruments from each group for sampling verification, avoiding on-site operation of each massive number of instruments and reducing offline management costs. For the selected verification samples, this module initiates a statutory metrological verification procedure, confirms the metrological characteristics of the instruments according to metrological technical specifications, and issues a legally valid verification certificate, providing a legal basis for the legal use of the instruments and traceability of measurement values. The process control module 140 can use the verification results obtained from the statutory metrological verification as traceable standard metrological data, and transmit it back to the measurement transmission control module 130 through a preset feedback link. This is used to correct the physical anchor point benchmark and algorithm model parameters of the dual-mode virtual standard, eliminate possible system deviations in online measurement transmission, and achieve measurement value unification between offline physical metrological standards and online virtual standards.

[0069] Optionally, the aforementioned measurement control module 130 performs real-time periodic verification, including: for each individual instrument in the massive distributed measurement instrumentation system, acquiring its real-time measured value after processing by the measurement data processing module 120, and the real-time standard value corresponding to the dual-mode virtual standard, with the real-time measured value and the real-time standard value remaining at the same time; calculating the value drift between the real-time measured value and the real-time standard value of each individual instrument; comparing the value drift of each individual instrument with a warning threshold, and statistically analyzing the proportion of individual instruments in the massive distributed measurement instrumentation system whose value drift does not exceed the warning threshold to obtain the periodic verification pass rate; determining the effectiveness of the online closed-loop measurement control based on the periodic verification pass rate, and generating a warning message and sending it to the process control module 140 when the online closed-loop measurement control is determined to be invalid, so as to trigger sampling verification and parameter correction of the dual-mode virtual standard.

[0070] Real-time verification is an online metering performance monitoring mechanism implemented by the metering control module 130 for a massive distributed metering device cluster. Its core lies in the dynamic comparison of two types of real-time data that maintain time synchronization. The real-time measured values ​​of the cluster metering devices refer to the core business data uploaded by each individual distributed metering device at the current moment. For smart meters, this includes parameters such as energy, voltage, and current; for charging pile clusters, it corresponds to measured data related to energy, voltage, and current. This data is cleaned and verified by the metering data processing module 120 before being input as valid measured values. The real-time standard value of the virtual standard refers to the reference benchmark value calculated in real-time by the dual-mode virtual standard based on the cluster topology, physical anchor point benchmark, and real-time cluster data through an algorithm model. For tree-structured clusters, an energy conservation algorithm is used combined with the parent node standard value and link loss parameters for calculation; for mesh-structured clusters, a multi-source data mutual verification algorithm is used combined with the physical anchor point benchmark and node credibility weights for calculation, ensuring that the measured values ​​are kept at the same time as the cluster metering devices to guarantee time consistency in the comparison.

[0071] To quantify the degree to which the measurement value of a single instrument deviates from the virtual standard reference, the measurement control module 130 calculates the drift between the real-time measured value and the real-time standard value for each instrument, and uses absolute value calculation to eliminate the influence of the deviation direction. The formula for calculating the drift is: ,in, It is the first Tableware The magnitude drift at any given time is directly calculated using the magnitude drift monitoring formula described above; It is the first The real-time values ​​of a smart meter or charging pile at time t are valid measured values ​​collected in real time by the metering data acquisition module and cleaned and verified by the processing module (smart meters focus on collecting energy, voltage, and current, while charging piles focus on collecting energy, voltage, and current related measured data). It is a virtual standard. The real-time value is calculated in real time by the quantity transmission control module based on the group topology of smart meters and charging piles using the corresponding algorithm model.

[0072] To clarify the acceptable range of measurement drift and avoid misjudgments during verification, the system sets a warning threshold as a baseline for determining whether measurement drift exceeds the limit. This threshold is determined based on the measurement uncertainty of the virtual standard. The formula for calculating the warning threshold is: ,in, The warning threshold is calculated directly from the revised warning threshold formula described above; This is the expanded uncertainty of the virtual standard, based on the legal verification uncertainty of the physical anchor point, the measurement uncertainty of each node of the smart meter and charging pile, and the combined standard uncertainty according to the uncertainty propagation law, multiplied by the coverage factor corresponding to the 95% confidence probability (fixed). The result is obtained by taking k as a fixed inclusion factor. Combined with the standard metrological verification, no additional configuration based on instrument accuracy is required, simplifying the verification process.

[0073] To assess the overall compliance of the group's verification and the effectiveness of the online measurement transmission system, the measurement transmission control module 130 statistically analyzes the proportion of devices within the group whose measurement drift did not exceed the warning threshold, thus obtaining the periodic verification compliance rate. The formula for calculating the periodic verification compliance rate is: Where R is the pass rate of the period verification, which is directly calculated by the above validity judgment formula; m is the total number of valid smart meters and charging piles participating in the verification, which is obtained by counting all smart meters and charging piles in the group and removing invalid devices with missing or abnormal data. and The values ​​are calculated using the drift monitoring formula and the early warning threshold formula, respectively. The judgment rule is: when R ≥ 0.95, the online measurement system is effective; when R < 0.95, batch sampling verification is triggered and the virtual standard correction coefficient is optimized.

[0074] When the online closed-loop measurement control is determined to be invalid, the measurement control module 130 generates an early warning message containing the instrument number, abnormality type and deviation value, and sends the message to the process control module 140 to trigger the sampling and verification process for abnormal instruments and the parameter correction operation of the dual-mode virtual standard, so as to achieve continuous optimization and deviation elimination of the online measurement system.

[0075] Optionally, the process control module 140 is further configured to: establish a two-way synchronous link for full-volume control data, and synchronize the full-volume results of sampling verification, the verification conclusions of statutory metrological verification, and the offline handling records of abnormal instruments to the quantity transmission control module 130 in real time; the quantity transmission control module 130 is further configured to: correct the physical anchor point benchmark and algorithm model standard parameters of the dual-mode virtual standard based on the traceable standard metrological data corresponding to the verification conclusions of statutory metrological verification, and optimize the verification strategy of real-time period verification based on the full-volume results of sampling verification and the offline handling records.

[0076] The aforementioned process control module 140 establishes a two-way synchronous link for full-volume control data. This link serves as a data transmission channel connecting online quantity transmission control and offline physical measurement, undertaking the information interaction function between the process control module 140 and the quantity transmission control module 130. It synchronizes the full-volume control data generated in the offline implementation process to the quantity transmission control module 130 in real time, realizing closed-loop linkage of online and offline data.

[0077] The comprehensive control data covers three key types of information: first, the full results of sampling verification, including the verification conclusions, measurement deviation data, and metrological performance status of each sample instrument; second, the verification conclusions of statutory metrological verification, referring to the conformity judgment of the instrument and the corresponding measurement data obtained through a metrological confirmation procedure with legal qualifications; and third, the offline handling records of abnormal instruments, which record the details of on-site parameter adjustments, calibration repairs, or replacement and maintenance operations carried out on the 130 warning instruments of the measurement transmission control module and the instruments that failed the sampling verification.

[0078] The measurement transmission control module 130 receives traceable standard measurement data corresponding to the verification conclusions of statutory metrological verification. This type of data has traceability through direct or indirect transmission from metrological benchmarks or public metrological standards. It serves as the physical anchor benchmark for correcting the dual-form virtual standard of the real measurement value benchmark, eliminating benchmark drift caused by the timeliness of historical verification data or the accumulation of on-site calibration deviations. At the same time, it corrects the node weight allocation and loss coefficient in the algorithm model standard based on the traceable standard measurement data, ensuring that the virtual standard measurement value output by the algorithm model is consistent with the real physical measurement value. The measurement transmission control module 130 optimizes the verification strategy of real-time period verification based on the full results of sampling verification and offline handling records. For high-stability equipment groups with no systematic deviations verified by long-term sampling verification, the verification frequency and warning threshold are relaxed. For high-risk equipment groups that frequently trigger warnings or show abnormal concentrations in handling records, the control rules are tightened and the monitoring density is increased, realizing the dynamic allocation and precise adaptation of verification resources.

[0079] Optionally, the aforementioned process control module 140 implements classification, grouping, and sampling verification, including: classifying and grouping a massive number of distributed measuring instruments based on instrument type, accuracy level, usage scenario, and online measurement status; for each grouped instrument group, using statistical sampling methods to extract representative sample instruments, formulating differentiated verification plans, and implementing sampling verification; establishing a dynamic adjustment mechanism for the sampling strategy, iteratively optimizing the sampling frequency and sampling ratio based on historical sampling verification results: if long-term sampling verification confirms no systematic deviation in the online measurement results, then gradually reducing the sampling frequency and ratio; if sampling reveals a high anomaly rate or high deviation risk, then increasing the sampling frequency and tightening the sampling rules.

[0080] The aforementioned process control module 140 implements categorized grouping management. This mechanism, centered on the full lifecycle risk management of measuring instruments, intelligently categorizes and organizes massive distributed measuring instruments based on four core dimensions: instrument type attributes, metrological accuracy level, usage scenario characteristics, and online measurement transmission status. This divides physically dispersed and heterogeneous instrument groups into several subgroups with homogeneous risk characteristics or similar metrological needs, providing a structured organizational foundation for the subsequent formulation and implementation of differentiated management strategies. For each categorized group of instruments, the process control module 140 can use statistical sampling methods to extract representative sample instruments. This method follows statistical principles to ensure that the sample reflects the metrological characteristic distribution of the overall group, avoiding the high-cost operation of conducting on-site verification of massive quantities of instruments. Based on the quantity, risk level, and historical performance of instruments in different groups, differentiated verification plans are formulated, and portable high-standard equipment is used for on-site verification to minimize offline workload and verify the accuracy of the online evaluation results of the measurement transmission control module 130.

[0081] In the above scheme, the process control module 140 establishes a dynamic adjustment mechanism for the sampling strategy. This mechanism is based on the historical sampling verification results and implements iterative optimization: if long-term sampling verification continuously verifies that there is no systematic deviation in the online data transmission results, the sampling frequency and sampling ratio are gradually reduced to reduce invalid verification; if the sampling verification finds a high anomaly rate or high deviation risk, the sampling rules are tightened and the sampling frequency is increased simultaneously to achieve accurate matching between offline control resources and the actual risk level of the group.

[0082] The aforementioned process control module 140 is also configured to: establish a mandatory control process of first confirming metrological conditions and then handling graded procedures for abnormal instruments alerted by the measurement control module 130 and non-conforming instruments found during sampling inspection; wherein, metrological confirmation includes: conducting metrological confirmation on all measuring instruments alerted by the measurement control module 130 through statutory metrological verification or calibration methods to locate the cause of instrument abnormality and clarify metrological performance deviation; graded procedures include: classifying abnormalities into minor, moderate and severe levels according to severity, and implementing differentiated closed-loop procedures: minor level requires on-site parameter adjustment and correction, moderate level requires calibration repair and metrological verification, and severe level requires suspension of use and replacement or in-depth repair; and, the verification conclusions of metrological confirmation and the handling records of graded procedures are fed back to the measurement control module 130.

[0083] The aforementioned process control module 140 establishes a mandatory control process of first confirming metrological accuracy and then handling non-conforming instruments identified by sampling inspections and for abnormal instruments alerted by the measurement transmission control module 130. This process serves as an effective supplement to the online measurement transmission system, ensuring that all abnormal instruments undergo authoritative confirmation through legal metrological procedures before entering the handling stage. Direct handling operations without metrological confirmation are strictly prohibited, thereby accurately locating the technical root cause of instrument abnormalities and quantifying the degree of metrological performance deviation, providing data support for subsequent rectification. The metrological confirmation stage is conducted for all measuring instruments alerted by the measurement transmission control module 130 through legal metrological verification or calibration. This stage is performed by legally qualified metrological technical institutions or authorized on-site metrological personnel. Based on metrological technical specifications, the measurement characteristics of the instruments, such as indication error, repeatability, and stability, are assessed for conformity, and a legally valid verification certificate or calibration report is issued, clearly specifying the specific manifestations of the instrument abnormality and the degree of deviation.

[0084] Based on the severity of the anomalies determined by the metrological confirmation conclusion, the instruments are classified into three levels: minor, moderate, and severe, and differentiated closed-loop handling is implemented: For minor anomalies, on-site parameter adjustments are made to restore metrological accuracy by modifying the instrument's internal calibration coefficients or configuration parameters; for moderate anomalies, calibration repair and metrological verification are carried out, with in-depth calibration followed by re-metrological confirmation to verify the repair effect; for severe anomalies, immediate suspension of use is implemented, and the replacement of the instrument or return to the factory for in-depth repair is initiated simultaneously to ensure that the non-conforming instrument is removed from the metrological field. The verification conclusions of the metrological confirmation and the handling records of the graded handling are fed back to the measurement transmission control module 130 through a preset data interface. This feedback data serves as an important basis for optimizing the online measurement transmission control strategy, realizing a complete closed-loop management from online early warning triggering, offline metrological confirmation, graded handling implementation to online result feedback.

[0085] Optionally, the aforementioned measurement data processing module 120 is further configured to: perform encryption verification and hash verification on the original measurement data using a data tampering verification algorithm; and establish a data quality admission threshold to remove data that is determined to be abnormal after verification.

[0086] The aforementioned data tampering verification algorithm is a security protection mechanism embedded in the metering data processing module 120. It is used to deal with the risk of malicious tampering or illegal intrusion attacks that may be encountered by a large number of distributed metering instruments during real-time online transmission. It ensures that the original metering data entering the subsequent measurement transmission control link truly reflects the actual measurement status of the instrument and prevents misjudgment of measurement values ​​and control loopholes caused by data distortion.

[0087] The metering data processing module 120 performs encryption verification and hash verification on the original metering data. Encryption verification uses cryptographic algorithms to perform integrity protection operations on the data content, verifying whether the data remains original and undamaged in the transmission link and storage node. Hash verification generates a data fingerprint through a one-way hash function, compares the consistency of the data fingerprint before and after transmission, and quickly identifies whether the data has been illegally modified. The two work together to confirm the originality and integrity of the data.

[0088] The aforementioned data quality access threshold is a data screening standard established by the measurement data processing module 120. This threshold is set based on the four-level verification results of completeness, accuracy, consistency, and traceability. It serves as a quality threshold for determining whether the original measurement data meets the requirements of subsequent measurement transmission control and offline verification. Only data that meets this access standard is considered to have usability.

[0089] Data that is determined to be abnormal through encryption verification and hash verification, i.e., original measurement data suspected of being tampered with or confirmed to have been modified, will be rejected by the measurement data processing module 120 according to the data quality access threshold, preventing it from entering the subsequent measurement transmission control module 130 and process control module 140. This ensures that the data used for online closed-loop measurement transmission control and legal verification is authentic and valid, and maintains the reliability of the group measurement assurance system.

[0090] Optionally, the aforementioned measurement transmission control module 130 constructs a dual-mode virtual standard, including: constructing physical anchor points with legal traceability based on historical laboratory verification data and on-site online calibration data; and adapting and constructing algorithm model standards according to the group topology of massive distributed measuring instruments; wherein, the algorithm model standards include: for tree topology with clear hierarchical links, adopting a hierarchical measurement value transmission algorithm based on energy conservation; and for wide-area distributed mesh topology, adopting a distributed node mutual verification algorithm based on multi-source data consistency verification.

[0091] The physical anchor points constructed by the measurement control module 130 are based on historical laboratory calibration data and on-site online calibration data. By integrating historical laboratory calibration records with legal traceability issued by metrology institutions and online calibration data returned from portable on-site standards, it provides real measurement constraints and calibration basis for the entire virtual standard system. The core of the physical anchor points is the group-level physical anchor point reference value. This reference value is obtained by statistically processing the valid historical calibration data within the group using Bayesian statistical methods. The calculation formula is as follows: ,in, The reference value for group-level physical anchor points is calculated using a formula; The total number of instruments with valid historical calibration data within the group is derived from the statistics of historical laboratory calibration records of metrology institutions. The nominal value for the calibration time of the i-th instrument is derived from the statutory calibration certificate of the corresponding instrument; For the first The error in the calibration values ​​of the instruments comes from historical laboratory calibration reports issued by metrology institutions.

[0092] For a group of metering instruments with a tree-like topology and clear hierarchical links, the metering control module 130 employs a hierarchical metering transfer algorithm based on the law of energy conservation to construct a standard algorithm model. This algorithm utilizes the relationship between energy transfer and loss in the hierarchical links to iteratively calculate the virtual standard value of each child node using the standard value of the parent node and the link loss parameters. The formula for calculating the virtual standard value of a child node is as follows: ,in, The virtual standard value of the k-th child node is calculated using the formula; The virtual standard value of the parent node is calculated from the corresponding formula of the parent node or obtained from the physical anchor point benchmark calibration; N is the total number of child nodes under the parent node, which comes from the actual deployment statistics of the tree topology. The i-th link loss is derived from the historical operating data calibration of the metering instrument group; M is the total number of loss items, derived from the statistics of line loss and equipment conversion loss of the tree link.

[0093] For a wide-area, distributed mesh topology of metering instruments, the metering control module 130 employs a distributed node mutual verification algorithm based on multi-source data consistency checking to construct an algorithm model standard. This algorithm relies on the adjacency mutual verification relationship of mesh nodes and calculates the global virtual standard value through a weighted fusion of physical anchor point benchmarks and node credibility weights. The formula for calculating the global virtual standard value is as follows: ,in, The value of the global virtual standard in the mesh is calculated by the formula; S is the total number of physical anchor nodes, which is derived from the statistics of the number of legal verification standards deployed in the mesh structure. The weight of the physical anchor point is determined by the calibration accuracy of the physical anchor point. The reference value for the physical anchor point is derived from online calibration data or historical laboratory verification data transmitted back from the portable standard in the field. This is the credibility weight of ordinary nodes, calculated based on the consistency of mutual verification data between nodes. These are measured values ​​for ordinary nodes, derived from real-time metering data collection from mesh nodes.

[0094] In the above scheme, the measurement control module 130 constructs a virtual standard system with legal traceability and adapted to the group topology through the dual-form collaboration of physical anchor points and algorithm model standards. The physical anchor points provide real measurement benchmark constraints for the algorithm model, while the algorithm model standards realize the distributed solution and dynamic update of virtual standard measurement values ​​based on the group topology characteristics. Together, they support the implementation of online closed-loop measurement control for a large number of distributed measuring instruments without the need for on-site intervention of physical standards.

[0095] Optionally, the process control module 140 is further configured to: perform statutory metrological verification according to the corresponding statutory cycle for measuring instruments with statutory periodic verification requirements; and perform special statutory metrological verification for measuring instruments of key control categories determined by classification and grouping.

[0096] The aforementioned process control module 140 implements statutory metrological verification for measuring instruments with statutory periodic verification requirements. Such instruments are included in the mandatory verification catalog or have their verification cycle determined by law in accordance with national metrological laws and regulations and metrological technical specifications. The process control module 140 actively triggers the verification process according to the corresponding statutory cycle to ensure that the measuring instruments receive metrological performance confirmation that meets the statutory requirements at the specified cycle nodes, thus meeting the compliance baseline requirements for the legal use of measuring instruments.

[0097] For key control categories of measuring instruments identified through classification and grouping, process control module 140 implements special statutory metrological verification. These instruments are identified as objects requiring enhanced supervision based on factors such as their type attributes, accuracy level, usage scenario risks, or online measurement transmission status. Special verification differs from routine periodic verification, implementing targeted control by increasing the verification frequency or expanding the range of verification parameters, thereby ensuring the metrological reliability of these instruments with a higher metrological confirmation density.

[0098] In the above scheme, the statutory metrological verification and special statutory metrological verification implemented by the process control module 140 are all performed by metrological technical institutions with legal qualifications or authorized personnel. In accordance with the metrological verification procedures or calibration specifications, the instrument is comprehensively verified for metrological performance, accurately determined whether the metrological characteristics meet the statutory requirements, and issued a verification certificate or calibration report with legal effect. This legal document serves as the legal basis for the legal use of the instrument and is a core compliance function that the measurement transmission control module 130 cannot replace in implementing online measurement transmission through the virtual standard.

[0099] Optionally, the aforementioned metering data acquisition module 110 is further configured to: configure differentiated acquisition strategies as needed based on the type of appliance and the usage scenario, including real-time acquisition and timed acquisition.

[0100] The aforementioned metering data acquisition module 110 is configured with differentiated acquisition strategies based on the type of instrument and usage scenario. These strategies are tailored to the data update frequency requirements, communication resource usage, and business criticality of different types of metering instruments. By flexibly setting acquisition timing parameters, it achieves adaptive data acquisition for diverse metering scenarios. The real-time acquisition strategy is suitable for business scenarios with frequent metering data fluctuations or requiring high-frequency monitoring. The metering data acquisition module 110 establishes a continuous data connection with the metering instrument through a dedicated acquisition unit, continuously reading instantaneous values ​​from the instrument's registers at second or millisecond intervals to ensure complete capture of value mutation events and meet the real-time tracking requirements of the dynamic characteristics of the metering process. The timed acquisition strategy is suitable for deployment scenarios where metering data changes gradually or communication bandwidth is limited. The metering data acquisition module 110 periodically wakes up the communication link at preset time intervals (e.g., minutes or hours) to acquire cumulative metering data or statistical characteristic values ​​of the instruments within the interval period in batches. This reduces energy consumption and channel occupancy caused by continuous communication, improving transmission efficiency while ensuring data integrity.

[0101] In the above scheme, the metering data acquisition module 110 implements a hybrid strategy of real-time acquisition and timed acquisition in parallel for heterogeneous metering instruments within the same group. Real-time acquisition is enabled for key nodes that need to be monitored in smart meters and charging pile clusters, while timed acquisition is enabled for auxiliary monitoring points in the sensor network that change slowly. By combining strategies, invalid data redundancy is avoided, and the optimal matching of acquisition resources and data value is achieved.

[0102] To facilitate understanding of the working principle of the digital management system 100 for group metering assurance, this application embodiment also provides a specific application example of the system in a certain application scenario. In this application scenario, the digital management system 100 for group metering assurance mainly includes:

[0103] The metering data acquisition module 110 is deployed on the edge of each smart meter and the concentrator. It is configured to collect in real time the energy, voltage, current metering data, equipment operating status and ambient temperature parameters of a large number of distributed smart meters, and output the raw metering data through a transmission method that combines power line carrier and wireless communication.

[0104] The metering data processing module 120 is deployed on an edge computing node and connected to the metering data acquisition module 110. It is configured to perform four-level verification of the original metering data (integrity, accuracy, consistency, traceability) and anti-tampering security processing, and output valid metering data.

[0105] The metering control module 130 is deployed on the cloud metering platform and connected to the metering data processing module 120. It is configured to build physical anchor points based on historical laboratory verification data and on-site online calibration data, and to build an algorithm model standard based on the distribution network topology algorithm of the smart meter cluster, forming a dual-mode virtual standard. The dual-mode virtual standard is used to implement online closed-loop metering control on effective metering data, perform real-time verification to monitor meter drift, and generate warning information when the meter drift exceeds the warning threshold.

[0106] The process control module 140, deployed in the metering center business system, is connected to the metering data processing module 120 and the measurement transmission control module 130 respectively. It is configured to receive early warning information, classify and sample a large number of distributed smart meters based on smart meter type, accuracy level and online measurement transmission status, perform statutory metrological verification on the verification samples and issue legally valid verification certificates, and feed back the verification results to the measurement transmission control module 130 to correct the parameters of the dual-mode virtual standard.

[0107] like Figure 2 As shown, the main processing flow of the digital management system 100 for group measurement assurance includes:

[0108] (1) System initialization phase: The system first deploys the basic architecture in the target distribution area, builds a tree-like hierarchical network covering the transformers in the area to the end users, and clarifies the deployment scheme of the four core modules. The quantity transmission control module 130 constructs a dual-mode virtual standard, in which the physical anchor point is established by integrating the historical laboratory verification data of the smart meters in the area issued by the metrology agency and the online calibration data returned by the portable standard in the field. The formula for calculating the reference value of the group-level physical anchor point is: For the tree-like topology of this distribution transformer area, the quantity transfer control module 130 adopts a hierarchical quantity transfer algorithm based on energy conservation to construct the algorithm model standard. The calculation formula for the virtual standard quantity value of the child node is as follows: The meter transmission control module 130 integrates physical anchor points with algorithm model standards to form a dual-mode virtual standard adapted to the smart meter cluster, and configures early warning threshold parameters for real-time verification to complete system initialization.

[0109] (2) Metering data acquisition stage: The metering data acquisition module 110 acquires data in real time according to the preset differentiated acquisition strategy through the dedicated acquisition unit deployed in each smart meter and concentrator. Real-time acquisition is carried out for key node meters, and timed acquisition is carried out for ordinary monitoring points. The acquired content includes the energy value, voltage, current, meter operating status and ambient temperature. The original metering data is transmitted to the metering data processing module 120 in real time through power line carrier and wireless communication link.

[0110] (3) Measurement data processing stage: The measurement data processing module 120 performs four-level cleaning on the original measurement data, sequentially verifying the integrity of data records, the accuracy of measurement range, the consistency of time sequence and the traceability of instrument identity. At the same time, it embeds a data tampering verification algorithm to perform encryption verification and hash verification on the data, establishes a data quality access threshold, removes data that is determined to be abnormal after verification, outputs real and valid measurement data and synchronizes it to the measurement transmission control module 130.

[0111] (4) Closed-loop metering control stage: The metering control module 130 calls the valid metering data and implements online closed-loop metering control using the dual-mode virtual standard. During the real-time verification stage, for each individual smart meter, the real-time metering measurement value processed by the metering data processing module 120 and the real-time standard value corresponding to the dual-mode virtual standard are obtained, and the two are kept synchronized at all times. The metering drift is calculated: Set early warning thresholds: The drift value of each individual meter is compared with the warning threshold, and the pass rate during the verification period is statistically analyzed. When judged When the online closed-loop data transmission control is deemed invalid, an early warning message is generated and sent to the process control module 140, triggering sampling verification and parameter correction of the dual-mode virtual standard.

[0112] (5) Process Control Stage: After receiving the early warning information, the process control module 140 classifies and groups a large number of meters based on the type, accuracy level, usage scenario, and online measurement status of the smart meters. It then uses statistical sampling to extract representative sample devices from each group and formulates a differentiated verification plan. Staff members carry portable standard equipment to the site to conduct sampling verification, perform statutory metrological verification on the verified samples, and issue legally valid verification certificates. Simultaneously, the process control module 140 establishes a two-way synchronous link for full-scale control data, synchronizing the full-scale results of the sampling verification, the verification conclusions of the statutory metrological verification, and the offline handling records of abnormal meters to the measurement control module 130 in real time. Based on the traceable standard metrological data corresponding to the verification conclusions, the measurement control module 130 corrects the physical anchor point benchmark and algorithm model standard parameters of the dual-mode virtual standard, and optimizes the verification strategy for real-time verification based on the sampling verification results, completing the closed-loop control of online and offline collaboration.

[0113] like Figure 3 As shown, based on the same inventive concept, embodiments of this application also provide a digital management method for group measurement assurance, including:

[0114] Step S210: Collect metering data, operating status and environmental parameters of massive distributed metering instruments in real time, and obtain raw metering data through wired or wireless transmission.

[0115] Step S220: Perform integrity, accuracy, consistency, traceability verification and anti-tampering security processing on the original measurement data, and output valid measurement data;

[0116] Step S230: Construct physical anchor points based on historical laboratory verification data and on-site online calibration data, and construct algorithm model standards based on the group topology algorithm to build a dual-morphology virtual standard; use the dual-morphology virtual standard to implement online closed-loop measurement transmission control of effective measurement data, perform real-time verification to monitor measurement drift, and generate warning information when the measured drift exceeds the warning threshold.

[0117] Step S240: Receive early warning information, classify and group a large number of distributed measuring instruments based on instrument type, accuracy level and online measurement status, and conduct sampling verification. Perform statutory metrological verification on the verification samples and issue a legally valid verification certificate. Feed back the verification results to correct the parameters of the dual-mode virtual standard.

[0118] It is understood that the above-described digital management method for group measurement assurance can achieve any one of the functions of the digital management system 100 for group measurement assurance provided in the embodiments of this application. For the implementation method and working principle of each function, please refer to the system embodiment. The method embodiment will not be repeated here.

[0119] The above description is merely an embodiment of the present invention and is not intended to limit the scope of protection of the present invention. For those skilled in the art, the present invention can have various modifications and variations. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A digital management system for ensuring group metering, characterized in that, include: The metering data acquisition module is configured to collect metering data, operating status and environmental parameters of massive distributed metering instruments in real time, and output the raw metering data through wired or wireless transmission. The measurement data processing module, connected to the measurement data acquisition module, is configured to perform integrity, accuracy, consistency, traceability verification and anti-tampering security processing on the raw measurement data, and output valid measurement data. The measurement transmission control module, connected to the measurement data processing module, is configured to construct physical anchor points based on historical laboratory verification data and on-site online calibration data, and to construct an algorithm model standard based on the group topology algorithm to form a dual-morphology virtual standard; and to implement online closed-loop measurement transmission control on the effective measurement data using the dual-morphology virtual standard, perform real-time verification to monitor measurement value drift, and generate warning information when the detected measurement value drift exceeds the warning threshold; The process control module, connected to the measurement data processing module and the measurement transmission control module respectively, is configured to receive the early warning information, classify and group the massive distributed measurement instruments based on instrument type, accuracy level and online measurement transmission status, conduct statutory metrological verification on the verification samples and issue legally valid verification certificates, and feed back the verification results to the measurement transmission control module to correct the parameters of the dual-mode virtual standard.

2. The digital management system for ensuring group metering according to claim 1, characterized in that, The data transfer control module performs the real-time periodic verification, including: For each individual instrument in the massive distributed metering instrument, the real-time measured value after processing by the metering data processing module is obtained, as well as the real-time standard value corresponding to the dual-mode virtual standard. The real-time measured value and the real-time standard value are kept at the same time. Calculate the drift between the real-time measured value and the real-time standard value of each individual instrument; The drift value of each individual instrument is compared with the warning threshold, and the proportion of individual instruments whose drift value does not exceed the warning threshold among the massive distributed metering instruments is counted to obtain the period verification pass rate. The effectiveness of the online closed-loop data transfer control is determined based on the pass rate of the period verification. When the online closed-loop data transfer control is determined to be invalid, the warning information is generated and sent to the process control module to trigger the sampling verification and parameter correction of the dual-mode virtual standard.

3. The digital management system for ensuring group metering according to claim 1, characterized in that, The process control module is also configured to: Establish a two-way synchronization link for full-volume control data, and synchronize the full results of the sampling verification, the verification conclusions of the statutory metrological verification, and the offline handling records of abnormal instruments to the quantity transmission control module in real time; The measurement transmission control module is further configured to: based on the traceable standard measurement data corresponding to the verification conclusion of the statutory metrological verification, correct the physical anchor point benchmark and algorithm model standard parameters of the dual-mode virtual standard, and optimize the verification strategy of the real-time period verification based on the full results of the sampling verification and the offline processing records.

4. The digital management system for ensuring group metering according to claim 1, characterized in that, The process control module implements the classification, grouping, and sampling verification, including: The massive distributed metering instruments are categorized and grouped based on instrument type, accuracy level, usage scenario, and online measurement status. For each group of categorized appliances, a representative sample of appliances is selected using statistical sampling methods, a differentiated verification plan is developed, and the sampling verification is implemented. Establish a dynamic adjustment mechanism for sampling strategies, and iteratively optimize the sampling frequency and sampling ratio based on historical sampling verification results: if long-term sampling verification shows no systematic deviation in online data transmission results, then gradually reduce the sampling frequency and ratio; if sampling reveals a high anomaly rate or high deviation risk, then increase the sampling frequency and tighten the sampling rules.

5. The digital management system for ensuring group metering according to claim 1, characterized in that, The process control module is also configured to: For abnormal instruments warned by the measurement control module and non-conforming instruments found by the sampling inspection, a mandatory control process of first confirming the measurement and then handling them in a graded manner is established. The metrological verification includes: performing metrological verification on all measuring instruments that are warned by the measurement transmission control module through the statutory metrological verification or calibration method, so as to locate the cause of the instrument abnormality and clarify the metrological performance deviation; The graded handling includes: classifying the anomalies into minor, moderate, and severe levels, and implementing differentiated closed-loop handling: minor levels involve on-site parameter adjustment and correction; moderate levels involve calibration repair and metrological verification; and severe levels involve suspension of use and replacement or in-depth repair; and feeding back the metrological verification conclusions and the graded handling records to the measurement transmission control module.

6. The digital management system for ensuring group metering according to claim 1, characterized in that, The metering data processing module is also configured to: The original measurement data is encrypted and hash-verified using a data tampering verification algorithm; and a data quality admission threshold is established to remove data that is determined to be abnormal after verification.

7. The digital management system for ensuring group metering according to claim 1, characterized in that, The quantity transmission control module constructs the dual-mode virtual standard, including: Based on historical laboratory testing data and on-site online calibration data, physical anchor points with legal traceability are constructed; Furthermore, an algorithm model standard is constructed to adapt to the group topology of the massive distributed metering instruments; wherein the algorithm model standard includes: for tree topology with clear hierarchical links, a hierarchical value transfer algorithm based on energy conservation is adopted; and for wide-area distributed mesh topology, a distributed node mutual verification algorithm based on multi-source data consistency verification is adopted.

8. The digital management system for group metering assurance according to any one of claims 1 to 7, characterized in that, The process control module is also configured to: perform statutory metrological verification according to the corresponding statutory cycle for measuring instruments with statutory periodic verification requirements; and perform special statutory metrological verification for measuring instruments of key control categories determined by the classification and grouping.

9. The digital management system for group metering assurance according to any one of claims 1 to 7, characterized in that, The metering data acquisition module is also configured to: configure differentiated acquisition strategies as needed according to the type of appliance and the usage scenario, wherein the differentiated acquisition strategies include real-time acquisition and timed acquisition.

10. A digital management method for population measurement assurance, characterized in that, The method includes: It collects metering data, operating status and environmental parameters of massive distributed metering instruments in real time, and obtains raw metering data through wired or wireless transmission. The original measurement data is verified for completeness, accuracy, consistency, traceability, and tamper-proof security, and valid measurement data is output. Physical anchor points are constructed based on historical laboratory calibration data and on-site online calibration data, and algorithm model standards are constructed based on the group topology algorithm to build a dual-morphology virtual standard. The dual-morphology virtual standard is used to implement online closed-loop measurement transmission control on the effective measurement data, perform real-time verification to monitor measurement drift, and generate warning information when the measured drift exceeds the warning threshold. Upon receiving the warning information, the system categorizes and groups the massive distributed measuring instruments based on instrument type, accuracy level, and online measurement status, and conducts sampling verification. The system performs statutory metrological verification on the verification samples and issues legally valid verification certificates. The verification results are then fed back to correct the parameters of the dual-mode virtual standard.

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