Heat meter status detection and analysis system

Abstract

The present invention relates to the technical field of state detection and analysis, and specifically to a heat meter state detection and analysis system, comprising a data acquisition module, a data processing module and a data calibration and analysis module, wherein the data acquisition module is used to acquire heat meter related data and send the acquisition result to the data processing module; the data processing module is used to perform data processing on the data acquired by the data acquisition module and send the processing result to the data calibration and analysis module; the data calibration and analysis module is used to implement data calibration and heat meter state analysis based on the processing result of the data processing module; the present invention increases the application scenarios of data correction by using correction coefficients for dynamic correction; improves data processing speed by introducing asynchronous concurrent calibration rules, improves data matching accuracy by setting accuracy levels, and increases the dimension of heat meter state analysis.

Description

Technical Field

[0001] The present invention relates to the technical field of state detection and analysis, and in particular to a heat meter state detection and analysis system. Background Art

[0002] Heat meters are widely used in trade settlement measurement for heating provided by heating companies, heating departments, etc. to residents, industrial and commercial users. They are also commonly used to measure heat absorbed by refrigeration. Heat meter status detection refers to the monitoring and evaluation of the working condition, performance and readings of the heat meter to ensure its accurate and reliable operation. The purpose of status detection is to discover and solve problems in a timely manner to ensure the normal operation of the system.

[0003] At present, the status detection and analysis of heat meters faces the following challenges:

[0004] 1. During long-term use, in different use environments (such as temperature, humidity, and pressure, etc.), the heat meter sensor may be affected by factors such as ambient temperature, humidity, and pressure, and the heat meter reading may gradually deviate from the actual value, affecting the accuracy of the data;

[0005] 2. During the routine maintenance of the heat meter, the collected data is affected by the collection environment and does not match the currently working heat meter, which affects the maintenance of the heat meter and shortens the service life of the heat meter. Summary of the invention

[0006] In view of the above-mentioned problems, the present invention is proposed.

[0007] In order to solve the above technical problems, the present invention provides the following technical solutions: a heat meter status detection and analysis system, comprising a data acquisition module, a data processing module and a data calibration and analysis module.

[0008] The data acquisition module is used to collect data related to the heat meter and send the collection results to the data processing module;

[0009] The data processing module is used to process the data collected by the data collection module and send the processing results to the data calibration and analysis module;

[0010] The data calibration and analysis module is used to implement data calibration and status analysis of the heat meter based on the processing results of the data processing module.

[0011] As a preferred solution of the heat meter status detection and analysis system of the present invention, the data processing module corrects the collected data by constructing a data analysis model, as follows:

[0012] When the temperature data is corrected, we have:

[0013] T=T t +T′

[0014] T′=α(T env ,H env ,P env )·(T env -T ref )

[0015] Where T represents the corrected temperature data, which provides the data basis for the calibration analysis module. t represents the current temperature data of the heat meter, T′ represents the data corrected by the environmental data, and T ref Indicates the standard parameter temperature, which is set manually based on historical data, T env Indicates the current ambient temperature, H env Indicates the current ambient humidity, P env represents the current environmental pressure, and α represents the correction parameter;

[0016] When the flow data is corrected, we have:

[0017] Q=Q t ·(1+Q′)

[0018] Q′α·(T env -T ref )+α·(H env -H ref )+α·(P env -P ref )

[0019] Among them, Q represents the corrected flow data, Q′ represents the data corrected by environmental data, and T ref Indicates the standard parameter temperature, which is set manually based on historical data. ref Indicates standard parameter humidity, which is set manually based on historical data, T env Indicates the current ambient temperature, H env Indicates the current ambient humidity, P env represents the current environmental pressure, and α represents the correction parameter.

[0020] As a preferred solution of the heat meter state detection and analysis system of the present invention, the correction parameter α is dynamically adjusted according to the correction function of the environmental data, as follows:

[0021] Correction function α(T env ,H env ,P env ) indicates that the data is dynamically modified according to the relationship between the environmental data, as follows:

[0022] α(Tenv ,H env ,P env )=a0+a1T env +a2H env +a3P env +a4T env H env +a5T env P env +a6H env P env

[0023] Among them, a0 represents the constant term, which is the correction parameter under standard conditions; a1, a2, and a3 represent the linear term coefficients, which represent the linear influence of ambient temperature, humidity, and pressure on the correction coefficient; a4, a5, and a6 represent the quadratic term coefficients, which represent the influence of the interaction between ambient temperature, humidity, and pressure on the correction coefficient. The constant term, linear term coefficient, and quadratic term coefficient in the correction function are obtained through experiments based on the status data of the heat meter in the historical data.

[0024] As a preferred solution of the heat meter state detection and analysis system of the present invention, the data calibration analysis module performs state analysis on the heat meter by constructing a calibration analysis model, the calibration analysis model includes data calibration and state analysis of the heat meter, and the data calibration is performed using asynchronous concurrent calibration rules, which are as follows:

[0025] Multiple calibrations are performed on multiple data sets simultaneously, and the accuracy level of the current data is matched according to the calibration results. The secondary correction of the data is completed by dynamically adjusting the correction parameters according to the accuracy level requirements of the current data.

[0026] As a preferred solution of the heat meter state detection and analysis system of the present invention, the specific calculation formula for performing multiple calibrations on multiple data sets simultaneously is as follows:

[0027] When calculating the error value of temperature data, we have,

[0028] When calculating the error value of flow data, we have,

[0029] Among them, E T 、E Q They represent the error value of the calculated temperature data and the error value of the flow data, T ref , Q ref Respectively represent temperature data and standard flow data, T ik , Q ikThey represent the total temperature data of the ith data set and the total flow data of the ith data set respectively, and n represents the total number of calibrations.

[0030] As a preferred solution of the heat meter state detection and analysis system of the present invention, the accuracy level is specifically set as follows:

[0031] The accuracy levels are set as level 1, level 2 and level 3, and the maximum allowable errors in the three levels are different, as follows:

[0032] When the accuracy level is level 1, the maximum allowable temperature error satisfies the formula and The maximum allowable error of flow rate satisfies the formula and

[0033] When the accuracy level is level 2, the maximum allowable temperature error satisfies the formula and The maximum allowable error of flow rate satisfies the formula and

[0034] When the accuracy level is level 3, the maximum allowable temperature error satisfies the formula and The maximum allowable error of flow rate satisfies the formula and

[0035] Among them, T 1,min Indicates the lowest temperature of the heat meter and cold meter, T 2,min Indicates the lowest temperature of the heat meter, T t Indicates the current temperature data of the heat meter, T t-1 Indicates the temperature data of the heat meter at the previous moment, Q e Indicates the common flow rate of the heat meter, Q t Indicates the instantaneous flow rate of the heat meter.

[0036] As a preferred solution of the heat meter status detection and analysis system of the present invention, the accuracy level matching of the current data is performed according to the calibration result, as follows:

[0037] When the calculated temperature error value satisfies the formula E T ≤0.1℃ and the flow error value satisfies formula E Q When ≤1%, it matches the first level accuracy level;

[0038] When the calculated temperature error value satisfies the formula 0.1℃ <E T ≤0.5℃ and the flow error value satisfies the formula 1% <E QWhen it is ≤3%, it matches the second level accuracy level;

[0039] When the calculated temperature error value satisfies the formula 0.5℃ <E T ≤1℃ and the flow error value satisfies the formula 3% <E Q When ≤5%, it matches the third level accuracy grade.

[0040] As a preferred solution of the heat meter state detection and analysis system of the present invention, the state analysis of the heat meter is specifically analyzed as follows:

[0041] When analyzing data matching the first level of accuracy, when the calculated temperature error value satisfies the formula 0.05℃ <E T When the temperature is ≤0.1℃, there is a risk of error fluctuation in the system. Immediately calibrate the system error value and re-collect and re-check the data based on the calibration results.

[0042] When the calculated flow error value meets the formula 0.5% <E Q When the flow rate is less than or equal to 1%, immediately replace the flow collection sensor to recollect data and recheck the collected data to ensure the normal operation of the system;

[0043] When analyzing data matching the secondary accuracy, when the calculated temperature error value satisfies the formula 0.3℃ <E T When the temperature is less than or equal to 0.5℃, the data correction parameters are adjusted immediately, the collected data are re-corrected, and the temperature error value is recalculated based on the re-corrected result. If the calculated error value still satisfies the formula, the heat meter is repaired.

[0044] When the calculated flow error value satisfies the formula 2% <E Q When the temperature is less than or equal to 3%, immediately increase the monitoring frequency and calibrate the data acquisition equipment. At the same time, calibrate and maintain the running heat meters to avoid damage to the heat meters.

[0045] When analyzing data matching the third level of accuracy, when the calculated temperature error value satisfies the formula 0.8℃ <E T When ≤1℃ and the calculated flow error value satisfies the formula 4% <E Q When it is ≤5%, immediately notify relevant personnel to check the current heat meter and take measures to replace the heat meter based on the inspection results.

[0046] Beneficial effects of the present invention: The present invention improves the accuracy of the data by using environmental data to correct the heat meter status data. At the same time, the correction coefficient is used for dynamic correction to increase the application scenarios of data correction. By introducing asynchronous concurrent calibration rules, the data processing speed is improved, and the accuracy of data analysis is increased. By setting the accuracy level, the data matching accuracy is improved, the dimension of heat meter status analysis is increased, and at the same time, the use of analysis resources is reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. Among them:

[0048] Figure 1 It is a schematic diagram of the overall composition structure of the heat meter status detection and analysis system of the present invention. DETAILED DESCRIPTION

[0049] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0050] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0051] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0052] The present invention is described in detail with reference to schematic diagrams. When describing the embodiments of the present invention, for the sake of convenience, the cross-sectional diagrams showing the device structure will not be partially enlarged according to the general scale, and the schematic diagrams are only examples, which should not limit the scope of protection of the present invention. In addition, in actual production, the three-dimensional dimensions of length, width and depth should be included.

[0053] Meanwhile, in the description of the present invention, it should be noted that the terms "first, second or third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0054] In the present invention, unless otherwise clearly specified and limited, the terms "install, connect, connect" should be understood in a broad sense, for example: it can be a fixed connection, a detachable connection or an integral connection; it can also be a mechanical connection, an electrical connection or a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0055] Example 1

[0056] Reference Figure 1 , which is the first embodiment of the present invention, provides a heat meter state detection and analysis system, including a data acquisition module, a data processing module and a data calibration and analysis module;

[0057] Specifically, the data acquisition module is used to acquire data related to the heat meter, the data processing module is used to process the acquired data, and the data calibration analysis module is used to perform calibration analysis based on the processed data.

[0058] Furthermore, the data acquisition module includes a temperature acquisition unit and a flow acquisition unit; the temperature acquisition unit uses a temperature sensor to collect temperature data of the heat meter, including the maximum temperature T of the heat meter and the cold meter. 1,max , heat meter cold meter minimum temperature T 1,min , heat meter heat meter maximum temperature T 2,max , heat meter heat meter minimum temperature T 2,min , heat meter temperature data T t The flow collection unit uses a flow sensor to collect heat meter flow data, including the heat meter commonly used flow Q e , maximum flow rate of heat meter Q max , heat meter minimum flow Q min And the instantaneous flow rate Q of the heat meter t .

[0059] Furthermore, the data processing module collects current environmental data, performs data correction on the collected data, and transmits the corrected data to the calibration analysis module so as to perform status analysis on the heat meter. The environmental data includes the environmental temperature data T env , environmental humidity data H env And the environmental pressure data P env ;

[0060] It should be noted that before building the data processing model, the collected data is preprocessed to improve the accuracy of the data. The data preprocessing includes data cleaning, data deduplication and data smoothing. The data preprocessing methods in this embodiment are all existing public technologies and will not be explained in detail here. They are intended to improve the accuracy of the data.

[0061] Specifically, the data processing model uses the collected environmental data to perform data correction on the heat meter related data so as to eliminate the environmental error of the heat meter related data, which is specifically implemented as follows:

[0062] When the temperature data is corrected, we have:

[0063] T=T t +T′

[0064] T′=α(T env ,H env ,P env )·(T env -T ref )

[0065] Where T represents the corrected temperature data, which provides the data basis for the calibration analysis module. t represents the current temperature data of the heat meter, T′ represents the data corrected by the environmental data, and T ref Indicates the standard parameter temperature, which is set manually based on historical data, T env Indicates the current ambient temperature, H env Indicates the current ambient humidity, P env represents the current environmental pressure, and α represents the correction parameter;

[0066] When the flow data is corrected, we have:

[0067] Q=Q t ·(1+Q′)

[0068] Q′α·(T env -T ref )+α·(H env -H ref )+α·(P env -P ref )

[0069] Among them, Q represents the corrected flow data, Q′ represents the data corrected by environmental data, and T ref Indicates the standard parameter temperature, which is set manually based on historical data, T env Indicates the current ambient temperature, H ref Indicates standard parameter humidity, which is set manually based on historical data. env Indicates the current ambient humidity, Penv represents the current environmental pressure, and α represents the correction parameter.

[0070] It should be noted that the correction parameter α is dynamically adjusted according to the correction function of the environmental data, as follows:

[0071] Correction function α(T env ,H env ,P env ) indicates that the data is dynamically modified according to the relationship between the environmental data, as follows:

[0072] α(T env ,H env ,P env )=a0+a1T env +a2H env +a3P env +a4T env H env +a5T env P env +a6H env P env

[0073] Wherein, a0 represents a constant term, which is a correction parameter under standard conditions; a1, a2, and a3 represent linear term coefficients, which represent the linear influence of ambient temperature, humidity, and pressure on the correction coefficient; a4, a5, and a6 represent quadratic term coefficients, which represent the influence of the interaction between ambient temperature, humidity, and pressure on the correction coefficient. The constant term, linear term coefficient, and quadratic term coefficient in the correction function are obtained by experiments based on the state data of the heat meter in the historical data. In this embodiment, the data in the following table are taken as an example for supplementary explanation.

[0074] <![CDATA[a0]]> <![CDATA[a1]]> <![CDATA[a2]]> <![CDATA[a3]]> <![CDATA[a4]]> <![CDATA[a5]]> <![CDATA[a6]]> 0.5 0.01 0.02 0.03 0.001 0.002 0.003

[0075] At this time, the correction coefficient is,

[0076] α(T env ,H env ,P env )=0.5+0.01T env +0.02H env +0.03P env +0.001T env H env ,

[0077] +0.002T env P env +0.003H env P env

[0078] In practical applications, the dynamic adjustment of the correction parameters is performed according to the difference between the current environmental data and the standard environmental data.

[0079] Furthermore, the data calibration analysis module constructs a calibration analysis model, uses the collected heat meter related data as the input of the model, and performs status analysis of the heat meter based on the output results of the model.

[0080] It should be noted that before the collected heat meter related data is input into the model, the collected data is constructed as a set including the corrected temperature data and the corrected flow data, then X = {T, Q}, and the corrected temperature data is a feature set composed of multiple feature values, T = [T 1,max ,T 1,min ,T 2,max ,T 2,min ,T t ], the corrected traffic data is a feature set composed of multiple feature values, Q = [Q e ,Q max ,Q min ,Q t ], and divide the constructed data set into three equal parts according to the data collection time, then X=X1+X2+X3, and the data composition in X1, X2 and X3 is the same, only the collection time series is different.

[0081] Specifically, the calibration analysis model includes data calibration and heat meter status analysis. The data calibration is to calibrate the constructed data set. The specific calibration is as follows:

[0082] By calibrating the data sets X1, X2 and X3 respectively through asynchronous concurrent calibration rules, the accuracy of calibration can be improved, thereby improving the accuracy of subsequent heat meter status analysis;

[0083] The asynchronous concurrent calibration rule is to calibrate multiple data sets simultaneously for multiple times, match the accuracy level of the current data according to the calibration results, and complete the secondary correction of the data by dynamically adjusting the correction parameters according to the accuracy level requirements of the current data.

[0084] Furthermore, the multiple calibrations performed on multiple data sets simultaneously are performed by using multiple averages to complete the error value calculation of the characteristic values ​​in the data sets. The specific calculation formula is as follows:

[0085] When calculating the error value of temperature data, we have,

[0086] When calculating the error value of flow data, we have,

[0087] Among them, E T 、E Q They represent the error value of the calculated temperature data and the error value of the flow data, T ref , Q ref Respectively represent temperature data and standard flow data, T ik , Q ik They represent the temperature sum data of the ith data set and the flow sum data of the ith data set respectively, and n represents the total number of calibrations;

[0088] It should be noted that the accuracy level classification in this embodiment is set according to the specifications of the heat meter in actual application. Different heat meters have different numerical upper limits for the classification levels. The numerical values ​​in this implementation are secondarily limited according to the following rules, as follows:

[0089] When limiting the error value of the flow characteristic value, the ratio of the maximum flow to the minimum flow value is not less than 2, then, Q max / Q min ≥2 and, when the common flow rate satisfies the formula 0.6≤Q e When ≤10, Q e / Q min ≥50;

[0090] When limiting the temperature characteristic value error, the ratio of the maximum temperature difference to the minimum temperature difference of the heat meter is not less than 10, then, And, the lower limit of the temperature of the heat meter satisfies the formula And, the lower limit of the temperature difference between the cold meter and the heat meter satisfies the formula

[0091]

[0092] Among them, T 1,min Indicates the lowest temperature of the heat meter and cold meter, T 2,min Indicates the minimum temperature of the heat meter, Q e Indicates the common flow rate of the heat meter.

[0093] Furthermore, the accuracy level matching of the current data according to the calibration result is to match the error value calculation result of the characteristic value in the data set with the accuracy level, as follows:

[0094] Before completing the pairing, the accuracy level is set according to the maximum allowable error. The accuracy level is set to level 1, level 2, and level 3, and the maximum allowable errors in the three levels are different, as follows:

[0095] When the accuracy level is level 1, the maximum allowable temperature error satisfies the formula and The maximum allowable error of flow rate satisfies the formula and

[0096] When the accuracy level is level 2, the maximum allowable temperature error satisfies the formula and The maximum allowable error of flow rate satisfies the formula and

[0097] When the accuracy level is level 3, the maximum allowable temperature error satisfies the formula and The maximum allowable error of flow rate satisfies the formula and

[0098] Among them, T 1,min Indicates the lowest temperature of the heat meter and cold meter, T 2,min Indicates the lowest temperature of the heat meter, T t Indicates the current temperature data of the heat meter, T t-1 Indicates the temperature data of the heat meter at the previous moment, Q e Indicates the common flow rate of the heat meter, Q t Indicates the instantaneous flow rate of the heat meter.

[0099] When the accuracy level is set, pairing is completed according to the calculation result of the error value and the set accuracy level, as follows:

[0100] When the calculated temperature error value satisfies the formula E T ≤0.1℃ and the flow error value satisfies formula E Q When ≤1%, it matches the first level accuracy level;

[0101] When the calculated temperature error value satisfies the formula 0.1℃ <E T ≤0.5℃ and the flow error value satisfies the formula 1% <E Q When it is ≤3%, it matches the second level accuracy level;

[0102] When the calculated temperature error value satisfies the formula 0.5℃ <E T ≤1℃ and the flow error value satisfies the formula 3% <E Q When ≤5%, it matches the third level accuracy grade.

[0103] Furthermore, the state analysis of the heat meter is performed by constructing a distributed analysis model to perform distributed analysis on data of different accuracy, and different analysis criteria are formulated according to the data of different accuracy, thereby realizing multi-dimensional analysis of the state of the heat meter.

[0104] Specifically, the distributed analysis model analyzes data with different accuracy matches by formulating different analysis criteria, as follows:

[0105] When analyzing data matching the first level of accuracy, when the calculated temperature error value satisfies the formula 0.05℃ <E T When the temperature is ≤0.1℃, there is a risk of error fluctuation in the system. Immediately calibrate the system error value and re-collect and re-check the data based on the calibration results.

[0106] When the calculated flow error value meets the formula 0.5% <E Q When the value is less than or equal to 1%, there is a risk of sensor failure. Immediately replace the flow collection sensor to recollect data and recheck the collected data to ensure the normal operation of the system.

[0107] When analyzing data matching the secondary accuracy, when the calculated temperature error value satisfies the formula 0.3℃ <E T When the temperature is ≤0.5℃, there is a risk of system deviation and heat meter aging. Immediately adjust the data correction parameters, re-correct the collected data, and recalculate the temperature error value based on the re-correction result. If the calculated error value still satisfies the formula, the heat meter should be repaired.

[0108] When the calculated flow error value satisfies the formula 2% <E Q When the value is less than or equal to 3%, there is a risk of data error. Immediately increase the monitoring frequency and calibrate the data acquisition equipment. At the same time, calibrate and maintain the running heat meters to avoid damage to the heat meters.

[0109] When analyzing data matching the third level of accuracy, when the calculated temperature error value satisfies the formula 0.8℃ <E T When ≤1℃ and the calculated flow error value satisfies the formula 4% <E Q When the value is less than or equal to 5%, the data of the working heat meter is abnormal. The relevant personnel shall be notified immediately to check the current heat meter and take measures to replace the heat meter according to the inspection results.

[0110] Furthermore, in order to further reflect the beneficial effects of the present invention, the technical solution of the present invention is now compared with the prior art to reflect the beneficial effects of the present invention, as shown in the following table:

[0111]

[0112]

[0113] According to the above table, it is not difficult to find that in our invention, through the technical solution adopted by the present invention, the accuracy of the data is improved, the application scenarios of data correction are increased, the data processing speed is improved, the accuracy of data analysis is increased, the data matching accuracy is improved, the dimension of heat meter status analysis is increased, the resource utilization efficiency is improved, the resources used for analysis are reduced, and at the same time, the compatibility of the system is enhanced, data integration and analysis are facilitated, the reliability of data transmission is improved, and data loss is reduced.

[0114] Furthermore, if the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the system described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0115] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0116] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0117] Additionally, in order to provide a concise description of exemplary embodiments, all features of an actual embodiment (ie, those features that are not relevant to the best mode presently contemplated for carrying out the invention or those that are not relevant to implementing the invention) may not be described.

[0118] It will be appreciated that in the development of any actual implementation, as in any engineering or design project, numerous implementation-specific decisions may be made. Such a development effort may be complex and time-consuming, but will be a routine task of design, fabrication, and production for those of ordinary skill having the benefit of this disclosure without undue experimentation.

[0119] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. Heat meter status detection and analysis system, characterized by: Including data acquisition module, data processing module and data calibration and analysis module, The data acquisition module is used to collect data related to the heat meter and send the collection results to the data processing module; The data processing module is used to process the data collected by the data collection module and send the processing results to the data calibration and analysis module; The data processing module performs data correction on the collected data by constructing a data analysis model, as follows: When the temperature data is corrected, we have: T=T t +T′ T′=α(T env ,H env ,P env )·(T env -T ref ) Where T represents the corrected temperature data, which provides the data basis for the calibration analysis module. t represents the current temperature data of the heat meter, T′ represents the data corrected by the environmental data, and T ref Indicates the standard parameter temperature, which is set manually based on historical data, T env Indicates the current ambient temperature, H env Indicates the current ambient humidity, P env represents the current environmental pressure, and α represents the correction parameter; When the flow data is corrected, we have: Q=Q t ·(1+Q′) Q′=α·(T env -T ref )+α·(H env -H ref )+α·(P env -P ref ) Among them, Q represents the corrected flow data, Q′ represents the data corrected by environmental data, and T ref Indicates the standard parameter temperature, which is set manually based on historical data. ref Indicates standard parameter humidity, which is set manually based on historical data, T env Indicates the current ambient temperature, H env Indicates the current ambient humidity, P env represents the current environmental pressure, and α represents the correction parameter; The correction parameter α is dynamically adjusted according to the correction function of the environmental data, as follows: Correction function α(T env ,H env ,P env ) indicates that the data is dynamically modified according to the relationship between the environmental data, as follows: α(T env ,H env ,P env )=a0+a1T env +a2H env +a3P env +a4T env H env +a5T env P env +a6H env P env Among them, a0 represents the constant term, which is the correction parameter under standard conditions; a1, a2, and a3 represent the linear term coefficients, which represent the linear influence of ambient temperature, humidity, and pressure on the correction coefficient; a4, a5, and a6 represent the quadratic term coefficients, which represent the influence of the interaction between ambient temperature, humidity, and pressure on the correction coefficient. The constant term, linear term coefficient, and quadratic term coefficient in the correction function are obtained through experiments based on the status data of the heat meter in the historical data; The data calibration and analysis module is used to implement data calibration and status analysis of the heat meter based on the processing results of the data processing module.

2. The heat meter status detection and analysis system according to claim 1, characterized in that: The data calibration analysis module performs state analysis on the heat meter by constructing a calibration analysis model. The calibration analysis model includes data calibration and state analysis of the heat meter. The data calibration is performed using asynchronous concurrent calibration rules, as follows: Multiple calibrations are performed on multiple data sets simultaneously, and the accuracy level of the current data is matched according to the calibration results. The secondary correction of the data is completed by dynamically adjusting the correction parameters according to the accuracy level requirements of the current data.

3. The heat meter status detection and analysis system according to claim 2, characterized in that: The specific calculation formula for performing multiple calibrations on multiple data sets simultaneously is as follows: When calculating the error value of temperature data, we have, When calculating the error value of flow data, we have, Among them, E T 、E Q They represent the error value of the calculated temperature data and the error value of the flow data, T ref , Q ref Respectively represent standard parameter temperature and standard flow data, T ik , Q ik They represent the total temperature data of the ith data set and the total flow data of the ith data set respectively, and n represents the total number of calibrations.

4. The heat meter status detection and analysis system according to claim 3, characterized in that: The accuracy levels are specifically set as follows: The accuracy levels are set as level 1, level 2 and level 3, and the maximum allowable errors in the three levels are different, as follows: When the accuracy level is level 1, the maximum allowable temperature error satisfies the formula and The maximum allowable error of flow rate satisfies the formula and When the accuracy level is level 2, the maximum allowable temperature error satisfies the formula and The maximum allowable error of flow rate satisfies the formula and When the accuracy level is level 3, the maximum allowable temperature error satisfies the formula and The maximum allowable error of flow rate satisfies the formula and Among them, T 1,min Indicates the lowest temperature of the heat meter and cold meter, T 2,min Indicates the lowest temperature of the heat meter, T t Indicates the current temperature data of the heat meter, T t-1 Indicates the temperature data of the heat meter at the previous moment, Q e Indicates the common flow rate of the heat meter, Q t Indicates the instantaneous flow rate of the heat meter.

5. The heat meter status detection and analysis system according to claim 4, characterized in that: The accuracy level matching of the current data is performed according to the calibration result, as follows: When the calculated temperature error value satisfies the formula E T ≤0.1℃ and the flow error value satisfies formula E Q When ≤1%, it matches the first level accuracy level; When the calculated temperature error value satisfies the formula 0.1℃ <E T ≤0.5℃ and the flow error value satisfies the formula 1% <E Q When it is ≤3%, it matches the second level accuracy level; When the calculated temperature error value satisfies the formula 0.5℃ <E T ≤1℃ and the flow error value satisfies the formula 3% <E Q When ≤5%, it matches the third level accuracy grade.

6. The heat meter status detection and analysis system according to claim 5, characterized in that: The state analysis of the heat meter is specifically analyzed as follows: When analyzing data matching the first level of accuracy, when the calculated temperature error value satisfies the formula 0.05℃ <E T When the temperature is ≤0.1℃, there is a risk of error fluctuation in the system. Immediately calibrate the system error value and re-collect and re-check the data based on the calibration results. When the calculated flow error value satisfies the formula 0.5% <E Q When the flow rate is less than or equal to 1%, immediately replace the flow collection sensor to recollect data and recheck the collected data to ensure the normal operation of the system; When analyzing data matching the secondary accuracy, when the calculated temperature error value satisfies the formula 0.3℃ <E T When the temperature is less than or equal to 0.5℃, the data correction parameters are adjusted immediately, the collected data are re-corrected, and the temperature error value is recalculated based on the re-corrected result. If the calculated error value still satisfies the formula, the heat meter is repaired. When the calculated flow error value satisfies the formula 2% <E Q When the temperature is less than or equal to 3%, immediately increase the monitoring frequency and calibrate the data acquisition equipment. At the same time, calibrate and maintain the running heat meters to avoid damage to the heat meters. When analyzing data matching the third level of accuracy, when the calculated temperature error value satisfies the formula 0.8℃ <E T When ≤1℃ and the calculated flow error value satisfies the formula 4% <E Q When it is ≤5%, immediately notify relevant personnel to check the current heat meter and take measures to replace the heat meter based on the inspection results.

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