CN118149920A - Correction optimization method and system for gas data of NB (node B) Internet of things gas meter - Google Patents
Correction optimization method and system for gas data of NB (node B) Internet of things gas meter Download PDFInfo
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- 238000012937 correction Methods 0.000 title claims abstract description 99
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- 238000004458 analytical method Methods 0.000 claims abstract description 8
- 239000007789 gas Substances 0.000 claims description 300
- 239000002737 fuel gas Substances 0.000 claims description 34
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01F—MEASURING VOLUME, VOLUME FLOW, MASS FLOW OR LIQUID LEVEL; METERING BY VOLUME
- G01F15/00—Details of, or accessories for, apparatus of groups G01F1/00 - G01F13/00 insofar as such details or appliances are not adapted to particular types of such apparatus
- G01F15/02—Compensating or correcting for variations in pressure, density or temperature
- G01F15/04—Compensating or correcting for variations in pressure, density or temperature of gases to be measured
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01F—MEASURING VOLUME, VOLUME FLOW, MASS FLOW OR LIQUID LEVEL; METERING BY VOLUME
- G01F15/00—Details of, or accessories for, apparatus of groups G01F1/00 - G01F13/00 insofar as such details or appliances are not adapted to particular types of such apparatus
- G01F15/02—Compensating or correcting for variations in pressure, density or temperature
- G01F15/04—Compensating or correcting for variations in pressure, density or temperature of gases to be measured
- G01F15/043—Compensating or correcting for variations in pressure, density or temperature of gases to be measured using electrical means
- G01F15/046—Compensating or correcting for variations in pressure, density or temperature of gases to be measured using electrical means involving digital counting
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01F—MEASURING VOLUME, VOLUME FLOW, MASS FLOW OR LIQUID LEVEL; METERING BY VOLUME
- G01F25/00—Testing or calibration of apparatus for measuring volume, volume flow or liquid level or for metering by volume
- G01F25/10—Testing or calibration of apparatus for measuring volume, volume flow or liquid level or for metering by volume of flowmeters
- G01F25/15—Testing or calibration of apparatus for measuring volume, volume flow or liquid level or for metering by volume of flowmeters specially adapted for gas meters
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Abstract
The invention discloses a correction optimization method and a correction optimization system for gas data of an NB (node B) internet of things gas meter, and relates to the technical field of gas data correction, wherein the method comprises the steps of carrying out first correction on initial gas consumption according to temperature and pressure to obtain first corrected gas consumption; the correlation between the environmental humidity, the gas humidity and the total service time of the NB Internet of things gas meter and the error rate of each maintenance is analyzed to obtain a correlation coefficient, and the second corrected gas consumption is further obtained through analysis; and obtaining the second correction gas consumption and the initial gas consumption, calculating to obtain the total error index of the NB (network of things) gas meter, judging the precision grade of the NB (network of things) gas meter according to the total error index of the NB (network of things) gas meter, and selecting different correction early warning treatment strategies. The accuracy of gas metering can be obviously improved, corrective measures can be taken pertinently, manpower and material resources are saved, and the normal operation of the gas meter is ensured.
Description
Technical Field
The invention relates to the technical field of gas data correction, in particular to a correction and optimization method and system for gas data of an NB (node B) internet of things gas meter.
Background
Along with the rapid development of the internet of things technology, the NB internet of things gas meter is used as intelligent and remote monitoring gas metering equipment and is widely applied to urban gas supply systems. Based on the narrowband internet of things (Narrow Band Internet of Things, NB-IoT for short) technology, the method realizes the real-time acquisition, transmission and processing of the gas data and brings great convenience to gas management. However, in practical applications, due to the influence of environmental factors (such as temperature, pressure, humidity, etc.) and factors of equipment itself (such as wear, aging, etc.), the measurement accuracy of the NB internet of things gas meter often deviates. These deviations may not only lead to inaccurate calculation of the gas costs, but may also affect the stable operation of the gas supply system and the safe use of gas by the user.
In the Chinese application with the application publication number of CN117433615A, a gas meter correction method, a system, electronic equipment and a medium are disclosed, which comprise the steps of obtaining the quantity of gas meters to be corrected in a target production line and the ambient temperature; dividing each gas meter into at least one gas meter group according to the number of the gas meters and a preset distribution standard; performing pre-correction operation on each gas meter group to obtain a correction error value corresponding to each gas meter group; determining a temperature compensation value according to the ambient temperature and the standard ambient temperature; determining a calibration coefficient according to each correction error value and the temperature compensation value, and generating a parameter correction table according to the calibration coefficient; and correcting the gas meters in each gas meter group according to the parameter correction table.
In the application of the invention, correction error data of each group of tables are collected according to the number of tables to be corrected and the ambient temperature, the calibration coefficient is determined by combining the ambient temperature compensation value, the mapping relation between each gas table and the correction parameters thereof is established, the standardized extraction of the parameters is realized, each group of gas tables is automatically corrected in batches according to the parameter correction tables, the consistency adjustment of the whole batch of products is quickly realized, the correction of each group of gas tables is not needed, and the correction efficiency of the gas tables in the production process of the gas tables is improved;
However, the correction of the gas meter still adopts conventional temperature compensation and pressure compensation, and the gas meter is affected by various factors such as humidity, mechanical abrasion and the like besides temperature and pressure in the actual operation process. If only temperature and pressure are considered in correction and other factors are ignored, the metering accuracy of the gas meter may be lost, resulting in inaccurate metering.
Therefore, the invention provides a correction optimization method and a correction optimization system for gas data of an NB (node) internet of things gas meter.
Disclosure of Invention
(One) solving the technical problems
Aiming at the defects of the prior art, the invention provides the correction optimization method and the correction optimization system for the gas data of the NB (network of things) gas meter, which are characterized in that the initial gas consumption is corrected for the first time according to the temperature and the pressure, the influence of the environmental humidity, the gas humidity and the total service time on the accuracy of the NB gas meter of the Internet of things is analyzed, the secondary correction is carried out on the first correction result, the error of the second correction gas consumption and the initial gas consumption is analyzed, the accuracy grade of the NB gas meter of the Internet of things is judged, different correction early warning treatment strategies are selected, the accuracy of gas metering can be obviously improved, correction measures are taken in a targeted manner, the manpower and material resource are saved, and the normal operation of the gas meter is ensured, so that the technical problem recorded in the background art is solved.
(II) technical scheme
In order to achieve the above purpose, the invention is realized by the following technical scheme: a correction optimization method for gas data of an NB (network of things) gas meter comprises the following steps:
Acquiring the gas use flow in real time by using an NB (network) gas meter to obtain an initial gas consumption Cy, and correcting the initial gas consumption Cy for the first time according to the temperature and the pressure to obtain a first corrected gas consumption Djr;
analysis of environmental humidity of NB (node b) Internet of things gas meter Gas humidity/>And total usage time/>And error rate per maintenance/>Obtain correlation coefficient/>、/>/>And each first corrected gas consumption/>, according to the NB internet of things gas meterReal-time ambient humidity/>Real-time gas humidity/>Real time total usage time/>And correlation coefficient/>、/>Obtaining the second corrected fuel gas consumption/>; Error rate per maintenance/>For each maintenance of the number of gas meters to be measuredAnd standard notation/>Error rate between;
obtaining the second corrected fuel gas consumption And initial gas usage/>Calculating to obtain total error index/>, of NB (node B) gas meter through Internet of thingsAccording to total error index/>, of NB (network of things) gas metersAnd judging the precision grade of the NB internet of things gas meter, and selecting different correction early warning processing strategies.
Further, the average use temperature of the current charging period is obtainedAverage pressure of use/>And initial gas consumption Cy, carrying out first correction on the gas consumption according to an ideal gas state equation to obtain first corrected gas consumption Djr:
And (3) finishing to obtain:
Wherein, Refers to standard use pressure, and takes any one of 2000-3000 Pa,/>The standard use temperature is any one of 15-25 ℃.
Further, environmental humidity of NB (network of things) gas meter is periodically detectedAnd gas humidity/>And obtaining the maintenance and installation records of the NB-Internet-of-things gas meter from the NB-Internet-of-things terminal database, and obtaining the total service time of the NB-Internet-of-things gas meter by arrangementAnd maintaining the number of gas meters to be measured at each time/>And standard notation/>And further calculating and obtaining each maintenance error rate/>, of the NB internet of things gas meter：
Wherein a represents the serial number of the NB internet of things gas meter,Y represents the chronological number of each maintenance,/>K and y are integers.
Further, the environmental humidity of the NB Internet of things gas meter is obtainedGas humidity/>And total usage time/>Analysis of the error rate per maintenance/>, respectivelyObtain correlation coefficient/>、/>/>：
Wherein,Is a correlation coefficient between ambient humidity and maintenance error rate,/>Is the correlation coefficient between the humidity of the fuel gas and the maintenance error rate,/>Is a correlation coefficient between the total usage time and the maintenance error rate, x represents the time sequence number of each detected humidity data,/>X is an integer.
Further, acquiring first correction gas consumption of each NB (network of things) gas meterReal-time ambient humidity/>Real-time gas humidity/>Real time total usage time/>And correlation coefficient/>、/>/>After linear normalization processing, calculating to obtain the second corrected fuel gas consumption/>：
Corresponding second correction fuel gas consumptionThe calculation formula of (2) is as above.
Further, the second corrected fuel gas consumption is obtainedAnd initial gas usage/>After linear normalization processing, calculating to obtain total error index/>, of the NB (network of things) gas meter：
Corresponding NB (node b) Internet of things gas meter total error indexThe calculation formula of (2) is as above.
Further, acquiring total error index of NB (node B) internet of things gas meterAccording to total error index/>, of NB (network of things) gas metersJudging the precision level of the NB internet of things gas meter, and selecting different correction early warning processing strategies, wherein the method specifically comprises the following steps:
When (when) When the method is used, the accuracy of feeding back the current NB internet of things gas meter is high, no measures are needed, and monitoring is kept continuously so as to prevent abnormal conditions.
When (when)And when the accuracy of the current NB internet of things gas meter is moderate, a secondary correction early warning command is sent to the NB internet of things terminal, maintenance time is scheduled for the current NB internet of things gas meter, and intervention correction is carried out.
When (when)When the accuracy of the current NB internet of things gas meter is low, a primary correction early warning command is sent to the NB internet of things terminal, intervention correction is needed to be performed on the current NB internet of things gas meter immediately, and potential safety hazards are eliminated.
Wherein,Is the total error index/>, of all NB (node B) IOT (Internet of things) gas metersIs a mean value of (c).
Correction optimizing system of NB thing networking gas table's gas data includes:
the first correction module is used for acquiring the gas use flow in real time by using the NB internet of things gas meter to obtain an initial gas consumption amount Cy, and carrying out first correction on the initial gas consumption amount Cy according to the temperature and the pressure to obtain a first corrected gas consumption amount Djr;
The second correction module is used for analyzing environmental humidity of the NB (network of things) gas meter Gas humidity/>And total use timeAnd error rate per maintenance/>Obtain correlation coefficient/>、/>/>And each first corrected gas consumption/>, according to the NB internet of things gas meterReal-time ambient humidity/>Real-time gas humidity/>Total real-time use timeAnd correlation coefficient/>、/>/>Obtaining the second corrected fuel gas consumption/>; Error rate per maintenance/>For each maintenance of the number/>, of the gas meter to be measuredAnd standard notation/>Error rate between;
correction early warning module for obtaining second correction fuel gas consumption And initial gas usage/>Calculating to obtain total error index/>, of NB (node B) gas meter through Internet of thingsAccording to total error index/>, of NB (network of things) gas metersAnd judging the precision grade of the NB internet of things gas meter, and selecting different correction early warning processing strategies.
(III) beneficial effects
The invention provides a correction optimization method and a system for gas data of an NB (node B) internet of things gas meter, which have the following beneficial effects:
1. The initial gas consumption Cy is obtained by collecting the gas usage flow in real time through the NB Internet of things gas meter, the initial gas consumption Cy is corrected for the first time according to the temperature and the pressure, the first corrected gas consumption Djr is obtained, the influence of temperature and pressure changes on the gas metering precision can be eliminated, the gas metering accuracy is improved, more accurate gas consumption data is obtained, and a reliable basis is provided for subsequent gas cost calculation and gas management.
2. Through analysis of NB Internet of things gas meter environmental humidityGas humidity/>And total usage time/>And error rate per maintenance/>Obtain correlation coefficient/>、/>/>And further analyzing to obtain the second corrected fuel gas consumption/>By considering the influence of factors such as ambient humidity, gas humidity, total service time and the like on the performance of the gas meter and carrying out corresponding correction, the accuracy of gas metering can be remarkably improved.
3. By obtaining the second corrected fuel gas consumptionAnd initial gas usage/>Calculating to obtain total error index/>, of NB (node B) gas meter through Internet of thingsAccording to total error index/>, of NB (network of things) gas metersThe accuracy grade of the NB internet of things gas meter is judged, different correction early warning treatment strategies are selected, correction measures can be adopted in a targeted manner, unnecessary correction and maintenance work can be reduced for the gas meter with higher accuracy, manpower and material resources are saved, necessary correction measures can be timely adopted for the gas meter with lower accuracy, waste of resources is avoided, and normal operation of the gas meter is ensured.
Drawings
FIG. 1 is a schematic flow chart of a correction optimization method for gas data of an NB (node) IOT (Internet of things) gas meter;
Fig. 2 is a schematic structural diagram of a system for correcting and optimizing gas data of an NB internet of things gas meter according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, the invention provides a method for correcting and optimizing gas data of an NB internet of things gas meter, comprising the following steps:
Step one, acquiring gas usage flow in real time by using an NB (network of things) gas meter to obtain initial gas consumption Cy, and correcting the initial gas consumption Cy for the first time according to temperature and pressure to obtain first corrected gas consumption Djr.
The first step comprises the following steps:
step 101, acquiring gas use flow in real time by using an NB (network) internet of things gas meter, constructing a gas database, periodically acquiring temperature and pressure in the gas use process by using a temperature sensor and a pressure sensor, and acquiring average use temperature of a current charging period after finishing statistics Average pressure of use/>Initial fuel gas usage Cy.
Step 102, obtaining the average use temperature of the current charging periodAverage pressure of use/>And initial gas consumption Cy, carrying out first correction on the gas consumption according to an ideal gas state equation to obtain first corrected gas consumption Djr:
And (3) finishing to obtain:
Wherein, Refers to standard use pressure, and takes any one of 2000-3000 Pa,/>The standard use temperature is any one of 15-25 ℃.
Ideal gas state equation (pv=nrt), where P is pressure, V is volume, n is number of moles of gas, R is gas constant, and T is absolute temperature. This equation can help quantitatively describe the volume change of a gas at different pressures and temperatures. Absolute temperature, also known as thermodynamic temperature, is one of the important parameters in thermodynamics and statistics. The absolute temperature versus celsius temperature can be expressed by the following formula: t=t+273.15, T being absolute temperature and T being degrees celsius.
In use, the contents of steps 101 and 102 are combined:
the initial gas consumption Cy is obtained by collecting the gas usage flow in real time through the NB Internet of things gas meter, the initial gas consumption Cy is corrected for the first time according to the temperature and the pressure, the first corrected gas consumption Djr is obtained, the influence of temperature and pressure changes on the gas metering precision can be eliminated, the gas metering accuracy is improved, more accurate gas consumption data is obtained, and a reliable basis is provided for subsequent gas cost calculation and gas management.
Analyzing environmental humidity of NB (node B) internet of things gas meterGas humidity/>And total usage time/>And error rate per maintenance/>Obtain correlation coefficient/>、/>/>And each first corrected gas consumption/>, according to the NB internet of things gas meterReal-time ambient humidity/>Real-time gas humidity/>Real time total usage time/>And correlation coefficient/>、/>/>Obtaining the second corrected fuel gas consumption/>。
The second step comprises the following steps:
step 201, periodically detecting environmental humidity of NB (network of things) gas meter by using humidity sensor And gas humidityAnd obtaining the maintenance and installation records of the NB-Internet-of-things gas meter from the NB-Internet-of-things terminal database, and finishing to obtain the total service time/>, of the NB-Internet-of-things gas meterAnd maintaining the number of gas meters to be measured at each time/>And standard notation/>And further calculating and obtaining each maintenance error rate/>, of the NB internet of things gas meter：
Wherein a represents the serial number of the NB internet of things gas meter,Y represents the chronological number of each maintenance,/>K and y are integers.
And when the NB internet of things gas meter is maintained, the gas meter to be calibrated and the standard meter are installed on the same gas pipeline, so that the inlet and outlet conditions of the gas meter to be calibrated and the standard meter are identical, the gas meter to be calibrated and the standard meter are started to operate for a period of time, so that comparison is performed under the same working condition, readings of the gas meter to be calibrated and the standard meter are recorded, differences of the gas meter to be calibrated and the standard meter are compared, and the gas meter to be calibrated is calibrated according to the standard meter.
Step 202, acquiring environmental humidity of NB (node B) internet of things gas meterGas humidity/>And total usage time/>Analysis of the error rate per maintenance/>, respectivelyObtain correlation coefficient/>、/>/>：
Wherein,Is a correlation coefficient between ambient humidity and maintenance error rate,/>Is the correlation coefficient between the humidity of the fuel gas and the maintenance error rate,/>Is a correlation coefficient between the total usage time and the maintenance error rate, x represents the time sequence number of each detected humidity data,/>X is an integer.
Step 203, obtaining a first corrected gas consumption of each NB (network of things) gas meterReal-time ambient humidity/>Real-time gas humidity/>Real time total usage time/>And correlation coefficient/>、/>/>After linear normalization processing, calculating to obtain the second corrected fuel gas consumption/>：
Corresponding second correction fuel gas consumptionThe calculation formula of (2) is as above.
In use, the contents of steps 201 to 203 are combined:
Through analysis of NB Internet of things gas meter environmental humidity Gas humidity/>And total usage time/>And error rate per maintenance/>Obtain correlation coefficient/>、/>/>And further analyzing to obtain the second corrected fuel gas consumption/>By considering the influence of factors such as ambient humidity, gas humidity and total service time on the performance of the gas meter and carrying out corresponding correction, the accuracy of gas metering can be remarkably improved, and the intelligent and digital development of the gas industry is promoted.
Step three, obtaining the second correction fuel gas consumptionAnd initial gas usage/>Calculating to obtain total error index/>, of NB (node B) gas meter through Internet of thingsAccording to total error index/>, of NB (network of things) gas metersAnd judging the precision grade of the NB internet of things gas meter, and selecting different correction early warning processing strategies.
The third step comprises the following steps:
Step 301, obtaining the second correction fuel gas consumption And initial gas usage/>After linear normalization processing, calculating to obtain total error index/>, of the NB (network of things) gas meter：
Corresponding NB (node b) Internet of things gas meter total error indexThe calculation formula of (2) is as above.
Step 302, obtaining total error index of NB (node B) internet of things gas meterAccording to total error index of NB (node B) internet of things gas meterJudging the precision level of the NB internet of things gas meter, and selecting different correction early warning processing strategies, wherein the method specifically comprises the following steps:
When (when) When the method is used, the accuracy of feeding back the current NB internet of things gas meter is high, no measures are needed, and monitoring is kept continuously so as to prevent abnormal conditions.
When (when)And when the accuracy of the current NB internet of things gas meter is moderate, a secondary correction early warning command is sent to the NB internet of things terminal, maintenance time is scheduled for the current NB internet of things gas meter, and intervention correction is carried out.
When (when)When the accuracy of the current NB internet of things gas meter is low, a primary correction early warning command is sent to the NB internet of things terminal, intervention correction is needed to be performed on the current NB internet of things gas meter immediately, and potential safety hazards are eliminated.
Wherein,Is the total error index/>, of all NB (node B) IOT (Internet of things) gas metersIs a mean value of (c).
In use, the contents of steps 301 and 302 are combined:
by obtaining the second corrected fuel gas consumption And initial gas usage/>Calculating to obtain total error index/>, of NB (node B) gas meter through Internet of thingsAccording to total error index/>, of NB (network of things) gas metersThe accuracy grade of the NB internet of things gas meter is judged, different correction early warning treatment strategies are selected, correction measures can be adopted in a targeted manner, unnecessary correction and maintenance work can be reduced for the gas meter with higher accuracy, manpower and material resources are saved, necessary correction measures can be timely adopted for the gas meter with lower accuracy, waste of resources is avoided, and normal operation of the gas meter is ensured.
Referring to fig. 2, the invention provides a correction and optimization system for gas data of an NB internet of things gas meter, including:
The first correction module acquires the gas usage flow in real time by using the NB internet of things gas meter to obtain the initial gas usage amount Cy, and corrects the initial gas usage amount Cy for the first time according to the temperature and the pressure to obtain the first corrected gas usage amount Djr.
The second correction module is used for analyzing environmental humidity of the NB (network of things) gas meterGas humidity/>And total use timeAnd error rate per maintenance/>Obtain correlation coefficient/>、/>/>And each first corrected gas consumption/>, according to the NB internet of things gas meterReal-time ambient humidity/>Real-time gas humidity/>Total real-time use timeAnd correlation coefficient/>、/>/>Obtaining the second corrected fuel gas consumption/>. Error rate per maintenance/>For each maintenance of the number/>, of the gas meter to be measuredAnd standard notation/>Error rate between;
correction early warning module for obtaining second correction fuel gas consumption And initial gas usage/>Calculating to obtain total error index/>, of NB (node B) gas meter through Internet of thingsAccording to total error index/>, of NB (network of things) gas metersAnd judging the precision grade of the NB internet of things gas meter, and selecting different correction early warning processing strategies.
The above embodiments may be implemented in whole or in part by software, hardware, firmware, or any other combination. When implemented in software, the above-described embodiments may be implemented in whole or in part in the form of a computer program product. Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
The foregoing is merely illustrative of the present application, and the present application is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present application.
Claims (8)
- A correction optimization method for gas data of an NB (node B) internet of things gas meter is characterized by comprising the following steps: the method comprises the following steps:Acquiring the gas use flow in real time by using an NB (network) gas meter to obtain an initial gas consumption Cy, and correcting the initial gas consumption Cy for the first time according to the temperature and the pressure to obtain a first corrected gas consumption Djr;analysis of environmental humidity of NB (node b) Internet of things gas meter Gas humidity/>And total usage time/>And error rate per maintenance/>Obtain correlation coefficient/>、/>/>And according to the first correction gas consumption/>, of each NB Internet of things gas meterReal-time ambient humidity/>Real-time gas humidity/>Real time total usage time/>And correlation coefficient/>、/>/>Obtaining the second corrected fuel gas consumption/>; Error rate per maintenance/>For each maintenance of the number/>, of the gas meter to be measuredAnd standard notation/>Error rate between;obtaining the second corrected fuel gas consumption And initial gas usage/>Calculating to obtain total error index/>, of NB (node B) gas meter through Internet of thingsAccording to total error index/>, of NB (network of things) gas metersAnd judging the precision grade of the NB internet of things gas meter, and selecting different correction early warning processing strategies.
- 2. The correction and optimization method for the fuel gas data of the NB internet of things gas meter according to claim 1, wherein:Obtaining average use temperature of current charging period Average pressure of use/>And initial gas consumption Cy, carrying out first correction on the gas consumption according to an ideal gas state equation to obtain first corrected gas consumption Djr:And (3) finishing to obtain:Wherein, Refers to standard use pressure,/>Refers to standard use temperatures.
- 3. The correction and optimization method for the fuel gas data of the NB internet of things gas meter according to claim 1, wherein:Periodic detection NB thing networking gas table ambient humidity And gas humidity/>And obtaining the maintenance and installation records of the NB-Internet-of-things gas meter from the NB-Internet-of-things terminal database, and finishing to obtain the total service time/>, of the NB-Internet-of-things gas meterAnd maintaining the number of gas meters to be measured at each time/>And standard notation/>And further calculating and obtaining each maintenance error rate/>, of the NB internet of things gas meter：Wherein a represents the serial number of the NB internet of things gas meter,Y represents the chronological number of each maintenance,/>K and y are integers.
- 4. The method for correcting and optimizing the gas data of the NB internet of things gas meter according to claim 3, wherein:acquiring environmental humidity of NB (node b) internet of things gas meter Gas humidity/>And total usage time/>Analysis of the error rate per maintenance/>, respectivelyObtain correlation coefficient/>、/>/>：Wherein,Is a correlation coefficient between ambient humidity and maintenance error rate,/>Is the correlation coefficient between the humidity of the fuel gas and the maintenance error rate,/>Is a correlation coefficient between the total usage time and the maintenance error rate, x represents the time sequence number of each detected humidity data,/>X is an integer.
- 5. The correction and optimization method for the fuel gas data of the NB internet of things gas meter according to claim 4, wherein the method is characterized in that:Acquiring first correction gas consumption of each NB (network of things) gas meter Real-time ambient humidity/>Real-time gas humidityReal time total usage time/>And correlation coefficient/>、/>/>After linear normalization processing, calculating to obtain the second corrected fuel gas consumption/>：Corresponding second correction fuel gas consumptionThe calculation formula of (2) is as above.
- 6. The correction and optimization method for the fuel gas data of the NB internet of things gas meter according to claim 5, wherein the method is characterized in that:obtaining the second corrected fuel gas consumption And initial gas usage/>After linear normalization processing, calculating to obtain total error index/>, of the NB (network of things) gas meter：Corresponding NB (node b) Internet of things gas meter total error indexThe calculation formula of (2) is as above.
- 7. The correction and optimization method for the fuel gas data of the NB internet of things gas meter according to claim 6, wherein:acquiring total error index of NB (node b) internet of things gas meter According to total error index/>, of NB (network of things) gas metersJudging the precision level of the NB internet of things gas meter, and selecting different correction early warning processing strategies, wherein the method specifically comprises the following steps:When (when) When the accuracy of feeding back the current NB internet of things gas meter is high, no measures are needed;When (when) When the accuracy of the current NB internet of things gas meter is moderate, a secondary correction early warning command is sent to the NB internet of things terminal;When (when) When the accuracy of the current NB internet of things gas meter is low, a primary correction early warning command is sent to the NB internet of things terminal;Wherein, Is the total error index/>, of all NB (node B) IOT (Internet of things) gas metersIs a mean value of (c).
- Correction optimizing system of NB thing networking gas table's gas data, its characterized in that: comprising the following steps:the first correction module is used for acquiring the gas use flow in real time by using the NB internet of things gas meter to obtain an initial gas consumption amount Cy, and carrying out first correction on the initial gas consumption amount Cy according to the temperature and the pressure to obtain a first corrected gas consumption amount Djr;The second correction module is used for analyzing environmental humidity of the NB (network of things) gas meter Gas humidity/>And total usage time/>And error rate per maintenance/>Obtain correlation coefficient/>、/>/>And according to the first correction gas consumption/>, of each NB Internet of things gas meterReal-time ambient humidity/>Real-time gas humidity/>Real time total usage time/>And correlation coefficient/>、/>/>Obtaining the second corrected fuel gas consumption/>; Error rate per maintenance/>For each maintenance of the number/>, of the gas meter to be measuredAnd standard notation/>Error rate between;correction early warning module for obtaining second correction fuel gas consumption And initial gas usage/>Calculating to obtain total error index/>, of NB (node B) gas meter through Internet of thingsAccording to total error index/>, of NB (network of things) gas metersAnd judging the precision grade of the NB internet of things gas meter, and selecting different correction early warning processing strategies.
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| JP2000337938A (en) * | 1999-06-01 | 2000-12-08 | Aichi Tokei Denki Co Ltd | Gas meter |
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| JP2000337938A (en) * | 1999-06-01 | 2000-12-08 | Aichi Tokei Denki Co Ltd | Gas meter |
| CN104700506A (en) * | 2015-03-31 | 2015-06-10 | 成都秦川科技发展有限公司 | Safety cut-off type remotely-controlled intelligent mass flow rate gas meter and management system thereof |
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