A gas meter counting detection method

Abstract

The present invention discloses a gas meter counting detection method, which relates to the technical field of gas meter counting detection. When the environmental condition coefficient Htj is within the preset threshold range, the reading of the actual flow rate is calibrated by the first calibration coefficient K1, which can reduce the counting inaccuracy caused by residual gas and leakage. When the environmental condition coefficient Htj exceeds the preset threshold range, the system adopts the first calibration coefficient K1 and the second calibration coefficient K2 to consider the difference in the turbine rotation speed and the influence of environmental conditions on calibration, so as to more accurately correct the measured reading and reduce errors. This method comprehensively considers the influence of multiple factors such as environmental conditions, temperature, humidity, and particulate matter concentration on the counting system, reduces the measurement error, and ensures that customers obtain accurate gas measurement. The calibration strategy is intelligently selected according to the changes in actual environmental conditions, which not only improves the measurement efficiency but also reduces the maintenance cost.

Description

Technical Field

[0001] The invention relates to the technical field of gas meter counting detection, and in particular to a gas meter counting detection method. Background Art

[0002] Gas meter counting is a key application that is widely used in industrial, commercial and domestic applications to measure the amount of gas used. These counters typically use turbine flowmeters to measure the flow of gas and thus determine the amount consumed. However, accurate measurement of gas flow is essential for billing and monitoring energy usage.

[0003] In actual use, many gas meters use turbine flowmeters to measure the flow rate of gas. This flowmeter contains a turbine blade that rotates as the gas passes through. The speed of rotation is proportional to the gas flow rate. The sensor detects the speed of the blade rotation and converts it into volume flow, thereby calculating the amount of gas consumed.

[0004] However, there is usually some residual gas in the pipeline between the turbine flowmeter and the safety valve. The volume value of this residual gas will cause inaccurate counting when the gas ventilation is turned off. In addition, the gas counting is often affected by environmental conditions such as temperature, humidity and particle concentration. These factors can cause inaccurate counting, so a method is needed to calibrate and correct the counter reading. Summary of the invention

[0005] 1. Technical issues to be resolved

[0006] In view of the deficiencies of the prior art, the present invention provides a gas meter counting detection method, which comprehensively considers the impact of multiple factors such as environmental conditions, temperature, humidity, and particle concentration on the counting system through an intelligent calibration strategy, reduces the measurement error, and ensures that customers obtain accurate gas measurement. The calibration strategy is intelligently selected according to the changes in actual environmental conditions. This not only improves the efficiency of measurement, but also reduces maintenance costs. When the environmental conditions change slightly, reducing the calibration frequency reduces maintenance costs; and when the environmental conditions change dramatically, increasing the calibration frequency ensures the accuracy of measurement. This intelligent calibration strategy helps to improve the maintainability of the system and reduce the workload of maintenance personnel.

[0007] (II) Technical solution

[0008] To achieve the above objectives, the present invention is implemented through the following technical solutions: A gas meter counting detection method, comprising the following steps:

[0009] Before the gas meter starts ventilation counting, the temperature conditions, air conditions and humidity conditions in the gas pipeline and the internal area of ​​the turbine flowmeter are first detected, and the environmental condition coefficient Htj is generated according to the detection results. When the environmental condition coefficient Htj is within the preset threshold range, the gas ventilation counting is performed, the turbine rotation data of the turbine flowmeter is obtained, and the first turbine rotation speed data set is established. When the gas gap stops ventilation, the gas pressure inside the gas pipeline from the turbine flowmeter to the safety valve is detected to obtain the first calibration coefficient K 1 , the first calibration coefficient K 1 Calculated by the following formula:

[0010]

[0011] The meaning of the formula is that the first calibration coefficient K 1 It indicates the volume value of the residual gas inside the pipeline between the turbine flowmeter and the safety valve. When the gas is shut off and the ventilation is stopped, it indicates the actual consumption of the residual gas leakage. The turbine speed of the turbine flowmeter at this stage causes inaccuracy; V indicates the volume inside the pipeline between the turbine flowmeter and the safety valve, P indicates the pressure value of the original gas, T indicates the temperature value of the original gas, Pc indicates the standard gas pressure, which is set to 101.325 kPa, or 1 atmosphere, and Tc indicates the standard gas temperature, which is usually 273.15 Kelvin, or 0 degrees Celsius, C 1 Expressed as a correction constant;

[0012] Based on the first turbine rotation speed data set, the actual flow reading is compared with the first calibration coefficient K 1 Associated, the first count value Q is obtained 1 It is generated by the following formula:

[0013] Q 1 =K 1 *(N-Nc)

[0014] Where N is the actual rotation speed of the turbine flowmeter, expressed in revolutions per minute (rpm), and Nc is the rotation speed of the turbine flowmeter recorded during calibration, which represents the rotation speed at which the residual gas leakage is actually consumed;

[0015] The first calibration coefficient K 1 Compared with the preset leakage threshold XL, if the first calibration coefficient K 1 If the preset leakage threshold XL is exceeded, it indicates that there is a leakage, triggering the first early warning alarm and prompting the corresponding valve or pipeline to repair the leakage problem.

[0016] Preferably, a temperature sensor is installed in the gas pipeline and inside the turbine flowmeter to detect and obtain the pipeline temperature Wd 1 and turbine temperature Wd2 , and after dimensionless processing, the temperature expansion influence index TIE is calculated by the following formula:

[0017]

[0018] Where, TIE represents the temperature expansion influence index, which is set in units of one thousandth of ‰; Wd 1 is the pipe temperature value, set in degrees Celsius, Wd 2 It is the turbine temperature value, which is set in degrees Celsius; Tref is the reference temperature value, which is set to the standard temperature, including 20℃ or 25℃, in degrees Celsius. The formula means that the temperature expansion influence index TIE result is a positive value, which means that the flow meter reading increases when the temperature rises, while a negative value means that the flow meter reading decreases when the temperature rises. It is used to calibrate the flow meter reading to correct the error caused by temperature changes.

[0019] Preferably, a particle sensor is used to measure the particle size concentration in the pipeline and the dust particle size attached to the surface of the turbine blade to obtain the pipeline particle size concentration KL 1 and leaf particle size concentration KL 2 , and after dimensionless processing, the deceleration coefficient K is calculated by the following formula r :

[0020]

[0021] The meaning of the formula is: the value of the deceleration coefficient Kr represents the degree of deceleration of the flowing fluid by the particles. If Kr is a positive value, it means that the particles cause the fluid to decelerate, otherwise it means that the fluid speed increases. It is used to evaluate the impact of particles on the pipe fluid and the attachment of turbine blades, and is needed to calibrate or correct the flow meter readings to correct the errors caused by particles.

[0022] Preferably, a humidity sensor is used to detect the humidity condition of the internal area of ​​the turbine flowmeter, and the real-time humidity value Sd is obtained. After dimensionless processing, the humidity influence coefficient SDx is calculated by the following formula:

[0023]

[0024] In the formula, Sd ref Represents standard humidity values, including 50% relative humidity. The unit of SDx calculation result is ‰, which indicates the performance change of the flow meter under a given humidity change. A positive value indicates that the flow meter reading increases when the humidity increases, while a negative value indicates that the flow meter reading decreases when the humidity increases. The humidity influence coefficient SDx is used to calibrate the flow meter reading to correct the error caused by humidity.

[0025] Preferably, the temperature expansion influence index TIE and the deceleration coefficient Kr Fitting with humidity influence coefficient SDx, the environmental condition coefficient Htj is generated by the following formula:

[0026] Htj=γ*TIE+θ*K r +β*SDx

[0027] Among them, 0≤γ≤1, 0≤θ≤1, 0≤β≤1, and γ+θ+β=1, γ, θ, β are weights, and their specific values ​​are adjusted and set by the user according to the actual local environment characteristics.

[0028] Preferably, when the environmental condition coefficient Htj is within a preset threshold range, according to the first turbine rotation speed data set, only the first calibration coefficient K 1 Calibrate the actual flow rate to obtain the first count value Q 1 as the final count value;

[0029] When the environmental condition coefficient Htj exceeds the preset threshold range, the gas ventilation count is performed, the turbine rotation data of the turbine flowmeter is obtained, and a second turbine rotation speed data set is established;

[0030] The first turbine rotation speed data set and the second turbine rotation speed data set are extracted to obtain the first average revolutions per minute value Zs respectively. 1 and the second average rpm value Zs 2 , according to the first average revolutions per minute value Zs 1 and the second average rpm value Zs 2 The difference between the environmental condition coefficient Htj and the second calibration coefficient K is calculated based on the environmental condition coefficient Htj. 2 , the second calibration coefficient K 2 Generated by the following formula:

[0031] K 2 =f(Zs 2 -Zs 1 )*Htj

[0032] Where f represents the calibration function, taking into account the difference in turbine rotation speed and the influence of environmental conditions on the calibration.

[0033] Preferably, when the environmental condition coefficient Htj exceeds a preset threshold range, the second calibration coefficient K 2 and the first count value Q 1 Associated calculation, obtain the second count value Q 2 Generated by the following formula:

[0034] Q 2 =K 2 *Q 1

[0035] The meaning of the formula is that the first count value Q is calculated according to the environmental conditions. 1 Make corrections to improve counting accuracy.

[0036] Preferably, connect to big data and obtain weather station data. When the temperature difference between day and night is more than 10 degrees Celsius within a day, adjust the calibration frequency every hour according to the changes in environmental conditions; if the environmental conditions change slowly and the temperature difference is less than 10 degrees, reduce the calibration frequency every 4 hours to reduce maintenance costs; if the environmental conditions change quickly, increase the calibration frequency to ensure accuracy, and record the number of calibrations.

[0037] Preferably, an extreme environmental threshold is set, and the environmental condition coefficient Htj is compared with the extreme environmental threshold. When the environmental condition coefficient Htj is within the extreme environmental threshold, a second early warning alarm is triggered, indicating that the current environmental season is severe and that icing may occur due to extreme cold, causing gas pipeline blockage, and prompting corresponding repair processing.

[0038] (III) Beneficial effects

[0039] The present invention provides a gas meter counting detection method, which has the following beneficial effects:

[0040] (1) A gas meter counting detection method, a first calibration coefficient K 1 The volume of the residual gas in the pipeline between the turbine flowmeter and the safety valve, as well as the impact of gas leakage on actual consumption, are considered. 1 Calibrating the actual flow reading can reduce the inaccuracy of counting caused by residual gas and leakage, and improve the accuracy of counting. The first calibration coefficient K 1 By comparing with the preset leakage threshold XL, potential leakage can be detected in time. The first calibration coefficient K 1 When the preset leakage threshold XL is exceeded, the first warning alarm will be triggered, indicating that there may be a valve or pipeline leakage problem. This helps to detect and repair potential safety risks early and ensure the stability and reliability of the method. 1 , you can know the residual gas situation inside the pipeline in time without frequent inspection or maintenance of the gas meter. This reduces maintenance costs and workload while ensuring the accuracy of the counting.

[0041] (2) This gas meter counting detection method can significantly improve the accuracy of counting by monitoring and calibrating the effects of multiple factors such as temperature, humidity, and particle concentration on the counting system. This helps ensure that customers receive accurate gas measurement and reduces measurement errors and disputes.

[0042] (3) In the gas meter counting detection method, when the environmental condition coefficient Htj exceeds the preset threshold range, the system uses the second calibration coefficient K 2 To account for differences in turbine rotation speed and the effects of environmental conditions on calibration. This approach fine-tunes the calibration to more accurately correct the metered readings, reducing errors. Unnecessary calibration operations can be reduced by intelligently selecting a calibration strategy based on actual conditions. This helps reduce maintenance costs and system downtime, and improves system availability.

[0043] (4) This gas meter counting detection method can reduce maintenance costs and improve the maintainability of the system through intelligent calibration strategies, reduced maintenance frequency and reduced disputes. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 A schematic diagram of a counting step flow of a gas meter counting detection method according to the present invention; DETAILED DESCRIPTION

[0045] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0046] Gas meter counting is a key application that is widely used in industrial, commercial and domestic applications to measure the amount of gas used. These counters typically use turbine flowmeters to measure the flow of gas and thus determine the amount consumed. However, accurate measurement of gas flow is essential for billing and monitoring energy usage.

[0047] In actual use, many gas meters use turbine flowmeters to measure the flow rate of gas. This flowmeter contains a turbine blade that rotates as the gas passes through. The speed of rotation is proportional to the gas flow rate. The sensor detects the speed of the blade rotation and converts it into volume flow, thereby calculating the amount of gas consumed.

[0048] However, there is usually some residual gas in the pipeline between the turbine flowmeter and the safety valve. The volume value of this residual gas will cause inaccurate counting when the gas ventilation is turned off. In addition, the gas counting is often affected by environmental conditions such as temperature, humidity and particle concentration. These factors can cause inaccurate counting, so a method is needed to calibrate and correct the counter reading.

[0049] Example 1

[0050] The present invention provides a gas meter counting detection method, please refer to Figure 1 , including the following steps:

[0051] Before the gas meter starts ventilation counting, the temperature conditions, air conditions and humidity conditions in the gas pipeline and the internal area of ​​the turbine flowmeter are first detected, and the environmental condition coefficient Htj is generated according to the detection results. When the environmental condition coefficient Htj is within the preset threshold range, the gas ventilation counting is performed, the turbine rotation data of the turbine flowmeter is obtained, and the first turbine rotation speed data set is established. When the gas gap stops ventilation, the gas pressure inside the gas pipeline from the turbine flowmeter to the safety valve is detected to obtain the first calibration coefficient K 1 , the first calibration coefficient K 1 Calculated by the following formula:

[0052]

[0053] The meaning of the formula is that the first calibration coefficient K 1 It indicates the volume value of the residual gas inside the pipeline between the turbine flowmeter and the safety valve. When the gas is shut off and the ventilation is stopped, it indicates the actual consumption of the residual gas leakage. The turbine speed of the turbine flowmeter at this stage causes inaccuracy; V indicates the volume inside the pipeline between the turbine flowmeter and the safety valve, P indicates the pressure value of the original gas, T indicates the temperature value of the original gas, Pc indicates the standard gas pressure, which is set to 101.325 kPa, or 1 atmosphere, and Tc indicates the standard gas temperature, which is usually 273.15 Kelvin, or 0 degrees Celsius, C 1 Expressed as a correction constant;

[0054] Based on the first turbine rotation speed data set, the actual flow reading is compared with the first calibration coefficient K 1 Associated, the first count value Q is obtained 1 It is generated by the following formula:

[0055] Q 1 =K 1 *(N-Nc)

[0056] Where N is the actual rotation speed of the turbine flowmeter, expressed in revolutions per minute (rpm), and Nc is the rotation speed of the turbine flowmeter recorded during calibration, which represents the rotation speed at which the residual gas leakage is actually consumed;

[0057] The first calibration coefficient K 1 Compared with the preset leakage threshold XL, if the first calibration coefficient K 1 If the preset leakage threshold XL is exceeded, it indicates that there is a leakage, triggering the first early warning alarm and prompting the corresponding valve or pipeline to repair the leakage problem.

[0058] In this embodiment, the first calibration coefficient K 1 The volume of the residual gas in the pipeline between the turbine flowmeter and the safety valve, as well as the actual consumption of the gas leakage, are considered. 1 Calibrating the actual flow reading can reduce the inaccuracy of counting caused by residual gas and leakage, and improve the accuracy of counting. The first calibration coefficient K 1 By comparing with the preset leakage threshold XL, potential leakage can be detected in time. The first calibration coefficient K 1 When the preset leakage threshold XL is exceeded, the first warning alarm will be triggered, indicating that there may be a valve or pipeline leakage problem. This helps to detect and repair potential safety risks early and ensure the stability and reliability of the system.

[0059] By monitoring and calibrating the first calibration factor K 1 , you can know the residual gas situation inside the pipeline in time without frequent inspection or maintenance of the gas meter. This reduces maintenance costs and workload while ensuring the accuracy of the counting.

[0060] Example 2

[0061] This embodiment is an explanation of the embodiment 1. Specifically, temperature sensors are installed in the gas pipeline and inside the turbine flow meter to detect and obtain the pipeline temperature Wd. 1 and turbine temperature Wd 2 , and after dimensionless processing, the temperature expansion influence index TIE is calculated by the following formula:

[0062]

[0063] Where, TIE represents the temperature expansion influence index, which is set in units of one thousandth of ‰; Wd 1 is the pipe temperature value, set in degrees Celsius, Wd 2 It is the turbine temperature value, which is set in degrees Celsius; Tref is the reference temperature value, which is set to the standard temperature, including 20℃ or 25℃, in degrees Celsius. The formula means that the temperature expansion influence index TIE result is a positive value, which means that the flow meter reading increases when the temperature rises, while a negative value means that the flow meter reading decreases when the temperature rises. It is used to calibrate the flow meter reading to correct the error caused by temperature changes.

[0064] In this embodiment, temperature affects the gas density. By monitoring the pipeline temperature Wd 1 and turbine temperature Wd 2, and calculate the temperature expansion effect index TIE, which can more accurately calibrate the flow meter readings to correct errors caused by temperature changes. This helps to improve the accuracy of measurement and ensure that customers get accurate gas measurement. When the temperature rises, the density of the gas decreases, and an uncalibrated flow meter may overestimate the actual gas consumption, resulting in unnecessary energy waste. The use of TIE can reduce this waste. The calculation of the temperature expansion effect index TIE allows the system to dynamically adapt to changes in ambient temperature. When the temperature rises, TIE is positive and the calibrated readings will increase, and vice versa. This ensures that the flow meter can remain accurate under different temperature conditions without manual adjustment or downtime for maintenance.

[0065] Example 3

[0066] This embodiment is an explanation of the embodiment 1. Specifically, a particle sensor is used to measure the particle size concentration in the pipeline and the dust particle size attached to the surface of the turbine blade to obtain the pipeline particle size concentration KL 1 and leaf particle size concentration KL 2 , and after dimensionless processing, the deceleration coefficient K is calculated by the following formula r :

[0067]

[0068] The meaning of the formula is: the value of the deceleration coefficient Kr represents the degree of deceleration of the flowing fluid by the particles. If Kr is a positive value, it means that the particles cause the fluid to decelerate, otherwise it means that the fluid speed increases. It is used to evaluate the impact of particles on the pipe fluid and the attachment of turbine blades, and is needed to calibrate or correct the flow meter readings to correct the errors caused by particles.

[0069] In this example, without considering the effect of particulate matter, the flow meter may overestimate the actual gas consumption, especially when there is a large amount of particulate matter in the pipeline. By using Kr to correct these errors, the metering error can be reduced, thereby reducing disputes between suppliers and users. Understanding the particle concentration in the pipeline and the blade attachment condition can help improve the maintainability of the system. If the pipeline particle concentration KL 1 and leaf particle size concentration KL 2 Abnormally high levels may indicate that the pipeline needs cleaning or maintenance, thus avoiding possible failures and downtime.

[0070] Example 4

[0071] This embodiment is an explanation of the embodiment 1. Specifically, a humidity sensor is used to detect the humidity condition in the internal area of ​​the turbine flowmeter, and a real-time humidity value Sd is obtained. After dimensionless processing, the humidity influence coefficient SDx is calculated by the following formula:

[0072]

[0073] In the formula, Sd ref Represents standard humidity values, including 50% relative humidity. The unit of SDx calculation result is ‰, which indicates the performance change of the flow meter under a given humidity change. A positive value indicates that the flow meter reading increases when the humidity increases, while a negative value indicates that the flow meter reading decreases when the humidity increases. The humidity influence coefficient SDx is used to calibrate the flow meter reading to correct the error caused by humidity.

[0074] In this embodiment, humidity is one of the important factors affecting the performance of the turbine flowmeter. Moisture can change the density of the gas, thereby affecting the flow rate and the flowmeter reading. By detecting humidity and calculating the humidity influence coefficient SDx, the flowmeter reading can be calibrated more accurately to account for the influence of humidity. This helps to improve the accuracy of metering and ensure that customers get accurate gas metering. Without considering the influence of humidity, the flowmeter may overestimate or underestimate the actual gas consumption, especially when the humidity changes greatly. By using SDx to calibrate these errors, the metering errors can be reduced, thereby reducing disputes between suppliers and users.

[0075] Example 5

[0076] This embodiment is an explanation of the embodiment 1. Specifically, the temperature expansion influence index TIE, the deceleration coefficient K r Fitting with humidity influence coefficient SDx, the environmental condition coefficient Htj is generated by the following formula:

[0077] Htj=γ*TIE+θ*K r +β*SDx

[0078] Wherein 0≤γ≤1, 0≤θ≤1, 0≤β≤1, and γ+θ+β=1, γ, θ, β are weights, and their specific values ​​are adjusted and set by the user according to the actual local environment characteristics.

[0079] In this embodiment, by allowing the user to adjust the weights (γ, θ, and β) according to the actual local environmental characteristics, this method becomes highly customizable. The degree of influence of factors such as temperature, particulate matter concentration, and humidity may vary in different regions or environments. This method is more adaptable to changes in different seasons and meteorological conditions. For example, the calibration frequency can be automatically adjusted according to temperature changes and humidity fluctuations to ensure the consistency of measurement. Therefore, users can adjust the weights according to actual conditions to ensure the accuracy of measurement.

[0080] Example 6

[0081] This embodiment is explained in Example 1, please refer to Figure 1Specifically, when the environmental condition coefficient Htj is within the preset threshold range, according to the first turbine rotation speed data set, only the first calibration coefficient K 1 Calibrate the actual flow rate to obtain the first count value Q 1 as the final count value;

[0082] When the environmental condition coefficient Htj exceeds the preset threshold range, the gas ventilation count is performed, the turbine rotation data of the turbine flowmeter is obtained, and a second turbine rotation speed data set is established;

[0083] The first turbine rotation speed data set and the second turbine rotation speed data set are extracted to obtain the first average revolutions per minute value Zs respectively. 1 and the second average rpm value Zs 2 , according to the first average revolutions per minute value Zs 1 and the second average rpm value Zs 2 The difference between the environmental condition coefficient Htj and the second calibration coefficient K is calculated based on the environmental condition coefficient Htj. 2 , the second calibration coefficient K 2 Generated by the following formula:

[0084] K 2 =f(Zs 2 -Zs 1 )*Htj

[0085] Where f represents the calibration function, taking into account the difference in turbine rotation speed and the influence of environmental conditions on the calibration.

[0086] In this embodiment, according to the actual value of the environmental condition coefficient Htj, the system can intelligently select an appropriate calibration strategy. When the environmental condition changes slightly and is within the preset threshold range, only the first calibration coefficient K 1 Calibration is performed, which can improve the efficiency of measurement.

[0087] When the environmental condition coefficient Htj exceeds the preset threshold range, the system uses the second calibration coefficient K 2 To account for differences in turbine rotation speed and the effects of environmental conditions on calibration. This approach fine-tunes the calibration to more accurately correct the metered readings, reducing errors. Unnecessary calibration operations can be reduced by intelligently selecting a calibration strategy based on actual conditions. This helps reduce maintenance costs and system downtime, and improves system availability.

[0088] Example 7

[0089] This embodiment is explained in Example 1, please refer to Figure 1 Specifically, when the environmental condition coefficient Htj exceeds the preset threshold range, the second calibration coefficient K2 and the first count value Q 1 Associated calculation, obtain the second count value Q 2 Generated by the following formula:

[0090] Q 2 =K 2 *Q 1

[0091] The meaning of the formula is that the first count value Q is calculated according to the environmental conditions. 1 Make corrections to improve counting accuracy.

[0092] In this embodiment, the second calibration coefficient K 2 With the first count value Q 1 Correlate to generate a second count value Q 2 , and as the final determined value, more accurate and reliable measurement can be achieved under different environmental conditions, thereby improving the performance and reliability of the counting system.

[0093] Example 8

[0094] This embodiment is an explanation of the embodiment 1. Specifically, big data is connected to obtain weather station data. When the temperature difference between day and night is more than 10 degrees Celsius within a day, the calibration frequency is adjusted every hour according to the changes in environmental conditions. If the environmental conditions change slowly and the temperature difference is less than 10 degrees, the calibration frequency is reduced to every 4 hours to reduce maintenance costs. If the environmental conditions change quickly, the calibration frequency is increased to ensure accuracy, and the number of calibrations is recorded.

[0095] In this embodiment, connecting big data and weather station data to dynamically adjust the calibration frequency is an intelligent method that can improve the performance, accuracy and reliability of the counting system while reducing maintenance costs.

[0096] Example 9

[0097] This embodiment is explained in Example 1, please refer to Figure 1 Specifically, an extreme environmental threshold is set, and the environmental condition coefficient Htj is compared with the extreme environmental threshold. When the environmental condition coefficient Htj is within the extreme environmental threshold, a second early warning alarm is triggered, indicating that the current environmental season is severe and that the gas pipeline may be blocked due to icing caused by extreme cold, and corresponding repair processing is prompted.

[0098] In this embodiment, the setting of extreme environmental thresholds allows the system to detect extreme changes in environmental conditions, such as high temperature or ice, in a timely manner. This helps to detect situations that may lead to pipeline blockage or other safety issues in advance, thereby reducing potential safety risks. By triggering the second early warning alarm, the system can prompt maintenance personnel to take appropriate repair measures to prevent potential problems from further deteriorating. This preventive maintenance can save time and resources and reduce the risk of equipment downtime.

[0099] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A gas meter counting detection method, characterized in that: The following steps are involved: Before the gas meter starts to count the ventilation, the temperature, air and humidity conditions in the gas pipeline and the internal area of ​​the turbine flowmeter are tested, and the environmental condition coefficient Htj is generated according to the test results; the environmental condition coefficient Htj is generated by the following formula: Htj=γ*TIE+θ*K r +β*SDx Where TIE represents the temperature expansion influence index, K r represents the deceleration coefficient, SDx represents the humidity influence coefficient, 0≤γ≤1, 0≤θ≤1, 0≤β≤1, and γ+θ+β=1, γ, θ, β are weights, and their specific values ​​are adjusted and set by the user according to the actual local environment characteristics; When the environmental condition coefficient Htj is within the preset threshold range, the gas ventilation count is performed, the turbine rotation data of the turbine flowmeter is obtained, and the first turbine rotation speed data set is established. When the gas gap stops ventilation, the gas pressure inside the gas pipeline from the turbine flowmeter to the safety valve is detected to obtain the first calibration coefficient K1. The first calibration coefficient K1 is calculated and generated by the following formula: The meaning of the formula is that the first calibration coefficient K1 represents the volume value of the residual gas inside the pipeline between the turbine flowmeter and the safety valve. When the gas is turned off and the ventilation is stopped, it represents the actual consumption of the leakage of the residual gas at this time. The turbine speed of the turbine flowmeter at this stage causes inaccuracy; V represents the volume inside the pipeline between the turbine flowmeter and the safety valve, P represents the pressure value of the original gas, T represents the temperature value of the original gas, Pc represents the standard gas pressure, which is set to 101.325 kilopascals, or 1 atmosphere, Tc represents the standard gas temperature, which is 273.15 Kelvin, or 0 degrees Celsius, and C1 represents the correction constant; Based on the first turbine rotation speed data set, and correlating the actual flow reading with the first calibration coefficient K1, the first count value Q1 is generated by the following formula: Q1=K1*(N-Nc) Where N is the actual rotation speed of the turbine flowmeter, expressed in revolutions per minute (rpm), and Nc is the rotation speed of the turbine flowmeter recorded during calibration, which represents the rotation speed at which the residual gas leakage is actually consumed; The first calibration coefficient K1 is compared with the preset leakage threshold XL. If the first calibration coefficient K1 exceeds the preset leakage threshold XL, it indicates that there is a leakage, triggering the first early warning alarm and prompting the corresponding valve or pipeline to repair the leakage problem.

2. A gas meter counting detection method according to claim 1, characterized in that: Temperature sensors are installed in the gas pipeline and inside the turbine flowmeter to detect the pipeline temperature Wd1 and the turbine temperature Wd2. After dimensionless processing, the temperature expansion influence index TIE is calculated by the following formula: Wherein, TIE represents the temperature expansion influence index, which is set in one thousandth of ‰; Wd1 is the pipe temperature value, which is set in degrees Celsius; Wd2 is the turbine temperature, which is set in degrees Celsius; Tref is the reference temperature value, which is set to the standard temperature, including 20℃ or 25℃, in degrees Celsius. The meaning of the formula is that a positive value of the temperature expansion influence index TIE indicates that the flow meter reading increases when the temperature rises, while a negative value indicates that the flow meter reading decreases when the temperature rises. It is used to calibrate the flow meter reading to correct the error caused by temperature changes.

3. A gas meter counting detection method according to claim 1, characterized in that: Use a particle sensor to measure the particle size concentration in the pipeline and the dust particle size attached to the surface of the turbine blade, obtain the pipeline particle size concentration KL1 and the blade particle size concentration KL2, and after dimensionless processing, calculate the deceleration coefficient K by the following formula r : The meaning of the formula is: the value of the deceleration coefficient Kr represents the degree of deceleration of the flowing fluid by the particles. If Kr is a positive value, it means that the particles cause the fluid to decelerate, otherwise it means that the fluid speed increases. It is used to evaluate the impact of particles on the pipe fluid and the attachment of turbine blades, and is needed to calibrate or correct the flow meter readings to correct the errors caused by particles.

4. A gas meter counting detection method according to claim 1, characterized in that: A humidity sensor is used to detect the humidity conditions in the internal area of ​​the turbine flowmeter to obtain the real-time humidity value Sd. After dimensionless processing, the humidity influence coefficient SDx is calculated by the following formula: In the formula, Sd ref Represents standard humidity values, including 50% relative humidity. The unit of SDx calculation result is ‰, which indicates the performance change of the flow meter under a given humidity change. A positive value indicates that the flow meter reading increases when the humidity increases, while a negative value indicates that the flow meter reading decreases when the humidity increases. The humidity influence coefficient SDx is used to calibrate the flow meter reading to correct the error caused by humidity.

5. A gas meter counting detection method according to claim 1, characterized in that: When the environmental condition coefficient Htj is within the preset threshold range, according to the first turbine rotation speed data set, it is only necessary to calibrate the actual flow rate by the first calibration coefficient K1 to obtain the first count value Q1 as the final count value; When the environmental condition coefficient Htj exceeds the preset threshold range, the gas ventilation count is performed, the turbine rotation data of the turbine flowmeter is obtained, and a second turbine rotation speed data set is established; The first turbine rotation speed data set and the second turbine rotation speed data set are extracted to obtain a first average revolutions per minute value Zs1 and a second average revolutions per minute value Zs2, respectively. The second calibration coefficient K2 is calculated based on the difference between the first average revolutions per minute value Zs1 and the second average revolutions per minute value Zs2 and the environmental condition coefficient Htj. The second calibration coefficient K2 is generated by the following formula: K2=f(Zs2-Zs1)*Htj Where f represents the calibration function, taking into account the difference in turbine rotation speed and the influence of environmental conditions on the calibration.

6. A gas meter counting detection method according to claim 5, characterized in that: When the environmental condition coefficient Htj exceeds the preset threshold range, the second calibration coefficient K2 is associated with the first count value Q1 and the second count value Q2 is obtained by the following formula: Q2=K2*Q1 The meaning of the formula is that the first count value Q1 is corrected according to environmental conditions to improve the counting accuracy.

7. A gas meter counting detection method according to claim 1, characterized in that: Connect to big data and obtain weather station data. When the temperature difference between day and night is more than 10 degrees Celsius within a day, adjust the calibration frequency every hour according to the changes in environmental conditions; if the environmental conditions change slowly and the temperature difference is less than 10 degrees, reduce the calibration frequency to every 4 hours to reduce maintenance costs; if the environmental conditions change quickly, increase the calibration frequency to ensure accuracy and record the number of calibrations.

8. A gas meter counting detection method according to claim 1, characterized in that: Set the extreme environmental threshold and compare the environmental condition coefficient Htj with the extreme environmental threshold. When the environmental condition coefficient Htj is within the extreme environmental threshold, a second early warning alarm is triggered, indicating that the current environmental season is severe and that the gas pipeline may be blocked due to icing caused by extreme cold, and corresponding repair measures are prompted.

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