CN-121997295-A - Heat meter verification data intelligent analysis system based on heat supply multi-parameter simulation

CN121997295ACN 121997295 ACN121997295 ACN 121997295ACN-121997295-A

Abstract

The invention relates to the technical field of safety of thermoelectric Internet of things, in particular to a heat meter verification data intelligent analysis system based on heat supply multi-parameter simulation, which comprises a multi-parameter working condition simulation module, a data acquisition and communication module, a heat meter for a user to be verified, a data processing and storage module, an intelligent analysis core module and a calibration optimization suggestion module, wherein the multi-parameter working condition simulation module accurately reproduces the coupling working conditions of water quality, temperature, flow rate and battery electric quantity, the data acquisition and communication module realizes unified acquisition of multi-brand heat meter data, the intelligent analysis core module quantifies the coupling influence of working conditions, sequences the performance of the heat meter and predicts the service life of a battery through a multivariate regression+SHAP mixed model, an entropy weight-TOPSIS method and an ARIMA model, and the calibration optimization suggestion module generates dynamic calibration coefficients. The invention realizes the full-working condition verification, the intelligent analysis and the accurate optimization of the heat meter, provides data support for the purchase, the calibration and the operation and maintenance of the heat meter of a heat supply enterprise, and improves the metering accuracy and the energy utilization efficiency.

Inventors

SU YOULIANG
YANG XIAOXIN
DING MEISHUANG
WANG WENJUN
WANG ZHONG
YAN JINFA
FANG JUNJIE
WANG JUNQIAN
LIU ZHEYUAN

Assignees

青岛能源热电集团有限公司

Dates

Publication Date: 20260508
Application Date: 20260127

Claims (10)

1. Heat meter verification data intelligent analysis system based on heat supply multiparameter simulation, which is characterized by comprising: The multi-parameter working condition simulation module (100) is used for dynamically adjusting and generating a multi-parameter coupling working condition environment comprising water quality parameters, temperature parameters, flow rate parameters and battery electric quantity according to a preset test scheme in the heating working condition simulation laboratory; The data acquisition and communication module (200) is connected with the multi-parameter working condition simulation module (100) and the household heat meter (300) to be detected and is used for acquiring working condition parameter data under the multi-parameter coupling working condition environment and metering response data of the household heat meter (300) to be detected in real time; The data processing and storage module (400) is used for receiving and storing the original data from the data acquisition and communication module (200), and performing cleaning, alignment and standardization processing on the data to form a structured test data set; The intelligent analysis core module (500) is connected with the data processing and storage module (400) and is used for calculating the performance index of the household heat meter (300) to be detected through a built-in analysis model and algorithm based on the structured test data set, analyzing the multi-parameter coupling influence rule and generating a performance evaluation report; The intelligent analysis core module (500) at least comprises a working condition coupling influence analysis unit (510) and a heat meter performance comprehensive evaluation unit (520); The working condition coupling influence analysis unit (510) adopts a mixed model based on multivariate regression and Shapley additive interpretation SHAP to quantify the independent and interactive influence contribution degree of each working condition parameter to the measurement error of the heat meter; the comprehensive thermal meter performance evaluation unit (520) constructs a comprehensive thermal meter multi-dimensional performance evaluation model based on an entropy weight-TOPSIS method, and outputs comprehensive performance ranking and adaptability grade of each thermal meter to be verified.
2. The heat meter verification data intelligent analysis system based on heat supply multi-parameter simulation according to claim 1, wherein the water quality parameter simulation in the multi-parameter working condition simulation module (100) is realized by adding chemical substances with specific concentrations into circulating water, and the concentration change function of the water quality hardness simulation is as follows: ; Wherein, the Representation of The ion concentration at the moment in time, For the initial concentration to be the same, In order to achieve the target concentration of the substance, For concentration adjustment coefficients related to the addition rate and system volume, accurate control and simulation of water quality changes is achieved by this function.
3. The intelligent analysis system for heat meter verification data based on heat supply multi-parameter simulation according to claim 1, wherein the metering response data collected by the data collection and communication module (200) comprises instantaneous flow, accumulated flow, water supply and return temperature, calculated heat and instantaneous fault codes, and the collected working condition parameter data comprises pipeline pressure, standard meter flow, system temperature, flow rate, water quality conductivity and battery voltage.
4. The heat meter verification data intelligent analysis system based on heat supply multi-parameter simulation according to claim 1, wherein in the working condition coupling influence analysis unit (510), a model core algorithm for quantifying influence contribution degree is as follows: First, build a metrology error And a plurality of working condition parameters Multiple nonlinear regression model of (c): ; Wherein, the In order to be an intercept term, And As the coefficient of regression of the coefficient of the data, And As a non-linear basis function, Is an error term; then, the trained regression model is used as a prediction model for SHAP analysis to calculate each working condition parameter SHAP value on each sample The mean value of the SHAP values I.e. the average marginal contribution of the parameter to the metering error.
5. The intelligent analysis system for heat meter verification data based on heat supply multi-parameter simulation according to claim 1, wherein in the comprehensive heat meter performance evaluation unit (520), the specific implementation steps of the entropy weight-TOPSIS method are as follows: step S1, constructing an evaluation matrix The rows represent The heat table to be evaluated, column represents Performance evaluation indexes comprise average errors, error standard deviations, maximum allowable error exceeding times and battery electric quantity attenuation rate under different working conditions; S2, calculating objective weights of all evaluation indexes by using an entropy weight method : S21, carrying out normalization processing on the evaluation matrix to obtain a normalized matrix For the forward index For negative direction index ; S22, calculating the first Entropy value of individual index : ; Wherein, the If (if) Then , , ; S23, calculating the first Weights of individual indicators : ; Step S3, calculating a comprehensive evaluation result by using a TOPSIS method: s31, constructing a weighted normalization matrix , ; S32, determining a positive ideal solution And negative ideal solution Wherein , ; S33, calculating Euclidean distances from each heat table to a positive ideal solution and a negative ideal solution: ; ; S34, calculating relative closeness : ; According to The magnitude of the values ranks the overall performance of all of the hotlists examined.
6. The intelligent analysis system for heat meter verification data based on multi-parameter simulation of heat supply according to claim 1, wherein the intelligent analysis core module (500) further comprises a battery power attenuation prediction unit (530) for predicting the remaining service life RUL of the heat meter battery based on the collected battery voltage time series data using a time series analysis algorithm, and the prediction model adopts a differential autoregressive moving average ARIMA model, which is generally formed as follows: ; Wherein, the Is that The battery voltage at the moment in time, Is a backward shift operator ), For the differential order number, Is a constant value, and is used for the treatment of the skin, As a result of the autoregressive coefficients, In order to move the coefficient of the average, In the form of a white noise sequence, And The autoregressive order and the moving average order, respectively.
7. The intelligent analysis system for heat meter verification data based on heating multiparameter simulation according to claim 6, wherein the battery level decay prediction unit (530) predicts the remaining life With a preset safety threshold Comparing when And when the system automatically generates early warning information, and the heat meter is identified to have battery power risk.
8. The heat meter verification data intelligent analysis system based on heat supply multi-parameter simulation as claimed in claim 1, further comprising a calibration optimization suggestion module (600), wherein the calibration optimization suggestion module (600) generates dynamic calibration compensation coefficients according to the output result of the working condition coupling influence analysis unit (510) for systematic errors of a heat meter of a specific brand or model under specific adverse working conditions The calculation formula is as follows: ; Wherein, the Relative to standard temperature Is used for the temperature difference of the (a), Relative to a standard flow rate Is used for controlling the flow rate difference of the air flow, Is the water hardness value, calculated by CaCO 3 , unit , And the error sensitivity coefficient specific to the model thermal table is obtained by influence analysis model fitting.
9. The heat supply multi-parameter simulation-based hotlist verification data intelligent analysis system according to claim 1, wherein the data acquisition and communication module (200) supports communication with hotlists of a plurality of different brands and different communication protocols, a configurable communication protocol library is built in, the protocols cover RS485, modbus RTU, loRa and NB-IoT mainstream protocols, and unified acquisition and standardized analysis of data are realized through protocol analysis adaptation.
10. The intelligent analysis system of heat meter verification data based on heat supply multi-parameter simulation according to any one of claims 1-9, wherein the performance evaluation report and the calibration optimization suggestion generated by the system are output to an asset management system or a meter purchasing decision support system of a heat supply enterprise through a standardized data interface, and the data interface supports RESTful API and WebSocket communication modes to realize data-driven heat meter purchasing selection, expiration replacement, field calibration and operation maintenance decision support.

Description

Heat meter verification data intelligent analysis system based on heat supply multi-parameter simulation Technical Field The invention relates to the technical field of thermoelectric internet of things safety, in particular to a heat meter verification data intelligent analysis system based on heat supply multi-parameter simulation. Background With the rapid development of the central heating industry, the household heat meter is used as a core metering device for trade settlement, the metering accuracy and the running stability of the household heat meter are directly related to the tangential interests of heating enterprises and residents, and the household heat meter has important influence on the energy saving, consumption reduction and standardized running of a heating system. However, the current heat supply industry faces a plurality of outstanding problems in the use and verification process of the heat meter, and the high-quality development of the industry is severely restricted. On one hand, the actual running environment of the heat meter is complex and changeable, the metering accuracy is influenced by multiple factor coupling, and the actual working condition is difficult to be covered in a whole way in the traditional verification mode. In long-term use, the resident heat meter not only faces the influence of external working conditions such as pipe network water quality difference (such as calcium and magnesium ion content, sediment rust and other impurities), supply and return water temperature fluctuation, pipeline flow speed non-uniformity and the like, but also is influenced by internal factors such as self battery electric quantity attenuation, disassembly and assembly loss and the like, so that the fault rate of the heat meter is high. In trade statement administration activities, a large number of faulty hotlists are detected, while hotlists that are not regularly verified lack effective verification of metering accuracy. The traditional heat meter verification is based on standard single working condition, only can test metering performance under fixed parameters, cannot simulate complex scenes of multi-parameter coupling in actual operation, causes disconnection of verification results and actual use states of the heat meter, is difficult to reveal independent influences and interaction of factors on metering errors, and cannot provide scientific basis for correction of the heat meter errors. On the other hand, the heat meter market has a plurality of brands and poor quality, lacks a unified and standard performance evaluation system, and has the advantages of lagged data acquisition and analysis means and low operation and maintenance management efficiency. According to the feedback of a thermal power company, the difference of different brands of heat meters in the aspects of failure rate, maintenance difficulty, environmental adaptability and the like is remarkable, but the existing evaluation is dependent on manual experience or simple data comparison, lacks a multi-dimensional and quantitative comprehensive evaluation model, is difficult to objectively reflect the actual performance level of the heat meters, and brings great trouble to purchase and model selection of heat supply enterprises. In addition, the traditional analysis method is mostly limited to simple statistics of single parameters, and cannot realize accurate tracing of metering errors, early warning of battery life and timely diagnosis of faults, thereby causing a series of problems of frequent metering disputes, high operation and maintenance cost, energy waste and the like. Along with the continuous improvement of the national energy saving and consumption reduction requirements of the heat supply industry and the urgent demands of heat supply enterprises on the improvement of the operation efficiency and the service quality, the limitations of the traditional heat meter verification mode in the aspects of working condition coverage, data processing, analysis and evaluation and the like are increasingly highlighted, and a heat meter verification system capable of simulating complex multi-parameter coupling working conditions, realizing data intelligent analysis and providing comprehensive performance evaluation and accurate optimization suggestion is needed to fill the blank of the prior art and promote the standardization, scientificity and intellectualization development of the metering management of the heat supply industry. Disclosure of Invention The invention aims to provide a heat meter verification data intelligent analysis system based on heat supply multi-parameter simulation, so as to solve the problem that the limitation of a heat meter verification mode in the aspects of working condition coverage, data processing, analysis and evaluation and the like is increasingly prominent in the background art. In order to achieve the above purpose, the present invention provides the following technical solut