Intelligent flow meter and calculation method based on differential pressure precise calculation

Abstract

The present invention discloses an intelligent flow meter and calculation method based on differential pressure precise calculation, which belongs to the technical field of intelligent flow meters, including a pipe body, a pressure pipe is arranged on the pipe body, an intelligent flow meter body is arranged on the pressure pipe, and a display screen is arranged on the intelligent flow meter body, wherein the intelligent flow meter body includes: a data acquisition module and a precise calculation microprocessor. The present invention solves the problem that the existing flow meter flow cannot be accurately calculated, resulting in inaccurate measurement results of the intelligent flow meter, and cannot better meet the demand for precise calculation of the flow of the intelligent flow meter. The present invention accurately calculates the flow of the intelligent flow meter based on the real-time data of the differential pressure flow meter based on the optimal intelligent flow meter precise calculation model, and automatically presents the precise calculation results of the flow of the intelligent flow meter in a visual form on the display screen, which can accurately calculate the flow of the flow meter, make the measurement results of the intelligent flow meter accurate, and can better meet the demand for precise calculation of the flow of the intelligent flow meter.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent flowmeters, and in particular to an intelligent flowmeter and a calculation method based on differential pressure precise calculation. Background Art

[0002] The differential pressure flowmeter uses the working principle that there is a certain relationship between the pressure difference and the flow rate when the medium fluid flows through the throttling device. The throttling device is a local contraction element installed in the pipeline. The most commonly used ones are orifice plates, nozzles and venturi tubes. In the fluid pipeline, a differential pressure flowmeter is usually installed to measure the flow rate of the fluid passing through.

[0003] The Chinese patent with publication number CN110967073B discloses a pressure differential flowmeter in a wastewater pipeline, including a pipe body, a pressure pipe is arranged on the outer surface of the upper end of the pipe body, the lower end of the pressure pipe extends to the inner side of the pipe body, and the pressure pipe and the pipe body are fixedly connected, a buffer structure is arranged on the outer surface of the pressure pipe, the upper end of the pressure pipe is connected to the flowmeter body, the front end of the flowmeter body is movably equipped with a protection structure, the rear end of the flowmeter body is provided with an anti-collision structure, and a dredging structure is arranged on the side of the upper end of the outer surface of the pipe body close to the pressure pipe; it has the advantages that the pressure pipe is not easy to be damaged, the instrument panel is not easy to be scratched, it plays a good protective role during transportation, and it is easy to clean the dirt accumulated in the pipe body; however, the patent has the following defects:

[0004] The existing flow meter cannot accurately calculate the flow rate, resulting in inaccurate measurement results of the intelligent flow meter, and cannot better meet the demand for accurate flow calculation of the intelligent flow meter. Summary of the invention

[0005] The purpose of the present invention is to provide an intelligent flow meter and calculation method based on differential pressure precise calculation, which can accurately calculate the flow rate of the flow meter, make the measurement result of the intelligent flow meter accurate, better meet the demand for precise calculation of the flow rate of the intelligent flow meter, and solve the problems raised in the above background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] An intelligent flow meter based on differential pressure precise calculation comprises a tube body, flanges are arranged at both ends of the tube body, mounting holes arranged in a circular array with the central axis of the tube body as the axis are provided on the flange, a pressure pipe is provided at the upper end of the tube body, an intelligent flow meter body is provided on the pressure pipe, and a display screen is provided on the intelligent flow meter body; wherein the intelligent flow meter body comprises:

[0008] A data acquisition module is used to collect fluid differential pressure data, fluid density data, fluid flow data and throttling device cross-sectional area data, and determine the historical data of the differential pressure flow meter based on big data;

[0009] The precise calculation microprocessor is used to process and train the historical data of the differential pressure flow meter based on big data, and to accurately calculate the flow of the intelligent flow meter, so as to determine the precise calculation result of the flow of the intelligent flow meter.

[0010] Preferably, the data acquisition module includes:

[0011] The differential pressure collection unit is used to monitor and collect the pressure difference generated when the fluid in the pipe body flows through the throttling device in real time, and obtain the fluid differential pressure data;

[0012] The density acquisition unit is used to monitor and acquire the density of the fluid flowing through the throttling device in the pipe body in real time to obtain the fluid density data;

[0013] A flow collection unit is used to monitor and collect the flow of the fluid flowing through the throttling device in the pipe body in real time to obtain fluid flow data;

[0014] A cross-sectional area acquisition unit is used to monitor and acquire the cross-sectional area of ​​the throttling device in the pipe body in real time and obtain the cross-sectional area data of the throttling device;

[0015] Among them, based on the fluid differential pressure data, fluid density data, fluid flow data and throttling device cross-sectional area data, the historical data of the differential pressure flowmeter based on big data is determined.

[0016] Preferably, the data acquisition module further includes:

[0017] A real-time monitoring module, used for real-time monitoring of the data collection frequency per unit time of the differential pressure collection unit, the density collection unit, the flow collection unit and the cross-sectional area collection unit;

[0018] a target acquisition unit determination module, for marking the acquisition unit whose data acquisition frequency changes as a target acquisition unit when the data acquisition frequency of any one of the differential pressure acquisition unit, the density acquisition unit, the flow acquisition unit and the cross-sectional area acquisition unit changes;

[0019] A data acquisition frequency value extraction module is used to extract the data acquisition frequency value of the target acquisition unit after the change and the data acquisition frequency value before the change;

[0020] A data acquisition frequency difference determination module is used to obtain a data acquisition frequency difference by using a data acquisition frequency value after the change and a data acquisition frequency value before the change of the target acquisition unit;

[0021] A first acquisition frequency compensation value acquisition module, configured to acquire acquisition frequency compensation values ​​of other acquisition units except the target acquisition unit by using the data acquisition frequency difference value when the data acquisition frequency difference value is lower than a preset frequency change difference value threshold value;

[0022] The acquisition frequency compensation amount of the acquisition units other than the target acquisition unit is obtained by the following formula: Wherein, Δf represents the acquisition frequency compensation of other acquisition units except the target acquisition unit; M represents the change ratio of the temperature of the environment in which the differential pressure acquisition unit, density acquisition unit, flow acquisition unit and cross-sectional area acquisition unit are located; V represents the ratio between the data transmission load of the current differential pressure acquisition unit, density acquisition unit, flow acquisition unit and cross-sectional area acquisition unit and the maximum data transmission load that the network bandwidth can bear; L represents the ratio between the minimum data acquisition frequency and the maximum data acquisition frequency of other acquisition units except the target acquisition unit; α, β and γ represent the weight values ​​corresponding to the ambient temperature change ratio, load ratio and data acquisition frequency ratio respectively; f h and f x They represent the data acquisition frequency value of the target acquisition unit after the change and the data acquisition frequency value before the change respectively; f min represents the minimum value of the data acquisition frequency of other acquisition units except the target acquisition unit; n represents the number of other acquisition units except the target acquisition unit; f i represents the data collection frequency value of the i-th collection unit other than the target collection unit; f z Indicates the median value of the data acquisition frequency of the differential pressure acquisition unit, the density acquisition unit, the flow acquisition unit, and the cross-sectional area acquisition unit;

[0023] The first acquisition frequency compensation adjustment module is used to compensate and adjust the acquisition frequencies of other acquisition units except the target acquisition unit by using the acquisition frequency compensation amount of the other acquisition units; wherein the adjusted acquisition frequencies of other acquisition units except the target acquisition unit are obtained by the following formula: Among them, f t01 Indicates the adjusted acquisition frequency of other acquisition units except the target acquisition unit; f n represents the acquisition frequency of other acquisition units except the target acquisition unit before adjustment; Δf represents the acquisition frequency compensation amount of other acquisition units except the target acquisition unit.

[0024] Preferably, the data acquisition module further includes:

[0025] A first data acquisition frequency difference acquisition module is used to extract the data acquisition frequency difference between the changed data acquisition frequency of the target acquisition unit and the current data acquisition frequency of other acquisition units as the first data acquisition frequency difference when the data acquisition frequency difference is not lower than a preset frequency change difference threshold;

[0026] A second data acquisition frequency difference acquisition module is used to extract the data acquisition frequency difference between the data acquisition frequency of the target acquisition unit before the change and the current data acquisition frequency of other acquisition units as the second data acquisition frequency difference;

[0027] A second acquisition frequency compensation value acquisition module is used to acquire acquisition frequency adjustment values ​​of other acquisition units except the target acquisition unit by using the first data acquisition frequency difference value and the second data acquisition frequency difference value and the difference between the data acquisition frequency value of the target acquisition unit after the change and the data acquisition frequency value before the change;

[0028] The acquisition frequency adjustment amount of the acquisition units other than the target acquisition unit is obtained by the following formula: Where Δf c represents the acquisition frequency adjustment amount of other acquisition units except the target acquisition unit; K represents a preset adjustment coefficient, and the value range of the adjustment coefficient is [0,10]; f h and f x They represent the data acquisition frequency value of the target acquisition unit after the change and the data acquisition frequency value before the change respectively; n represents the number of other acquisition units except the target acquisition unit; f i represents the data collection frequency value of the i-th collection unit other than the target collection unit; f y Indicates the preset frequency change difference threshold;

[0029] A second acquisition frequency compensation adjustment module, used to adjust the acquisition frequencies of other acquisition units except the target acquisition unit by using the acquisition frequency adjustment amount of the other acquisition units;

[0030] Among them, f t02 represents the acquisition frequency of other acquisition units except the target acquisition unit after the acquisition frequency is adjusted by using the acquisition frequency adjustment amount; f n Indicates the acquisition frequency of other acquisition units except the target acquisition unit before adjustment; Δf c Indicates the acquisition frequency adjustment amount of other acquisition units except the target acquisition unit.

[0031] Preferably, the precise computing microprocessor comprises:

[0032] A data processing module, used for processing the historical data of the differential pressure flow meter based on big data, and determining the characteristic data of the differential pressure flow meter based on big data;

[0033] Model training module, used to build an intelligent flow meter precision calculation model based on differential pressure precision calculation according to the precision calculation requirements of the intelligent flow meter;

[0034] An evaluation and optimization module is used to evaluate and optimize the precise calculation model of the intelligent flow meter based on differential pressure precise calculation, and determine the optimal precise calculation model of the intelligent flow meter;

[0035] The precise calculation module is used to accurately calculate the flow rate of the intelligent flow meter and determine the precise calculation result of the flow rate of the intelligent flow meter.

[0036] Preferably, the data processing module includes:

[0037] A data cleaning unit, used for cleaning historical data of differential pressure flowmeter based on big data;

[0038] Obtain historical data of differential pressure flowmeter based on big data;

[0039] Conduct consistency check on historical data of differential pressure flowmeter based on big data;

[0040] According to the reasonable value range and mutual relationship of each variable in the historical data of the differential pressure flowmeter, check whether the historical data of the differential pressure flowmeter meets the requirements;

[0041] Remove inconsistent data that is beyond the normal range, logically unreasonable or contradictory in the historical data of the differential pressure flow meter;

[0042] Process invalid and missing values ​​of historical data of differential pressure flowmeter based on big data;

[0043] Remove invalid and missing data from the historical data of the differential pressure flow meter that are of no value to the accurate calculation of the intelligent flow meter;

[0044] Determine the historical data of differential pressure flowmeter that is valuable for accurate calculation of intelligent flowmeter;

[0045] A feature extraction unit, used for extracting features from historical data of the differential pressure flowmeter after cleaning;

[0046] Obtain historical data of differential pressure flowmeter after cleaning, which is valuable for accurate calculation of intelligent flowmeter;

[0047] Extract features from valuable historical data of differential pressure flowmeters for accurate calculation of intelligent flowmeters;

[0048] Determine the characteristic data of differential pressure flowmeter based on big data.

[0049] Preferably, the model training module includes:

[0050] A data division unit, used for dividing characteristic data of a differential pressure flow meter based on big data;

[0051] Obtain characteristic data of differential pressure flowmeter based on big data;

[0052] Divide the characteristic data of differential pressure flowmeter based on big data;

[0053] Determine the intelligent flow meter accurate calculation training set and the intelligent flow meter accurate calculation test set;

[0054] Model training unit, used to build precise calculation model of intelligent flow meter;

[0055] According to the precise calculation requirements of the intelligent flow meter, select the neural network model framework suitable for the precise calculation of the intelligent flow meter;

[0056] Based on the intelligent flow meter accurate calculation training set, the neural network model framework suitable for the intelligent flow meter accurate calculation is trained;

[0057] Determine the precise calculation model of the intelligent flow meter based on differential pressure precise calculation.

[0058] Preferably, the evaluation and optimization module includes:

[0059] Test and evaluation unit, used to test and evaluate the precise calculation model of the intelligent flow meter;

[0060] Obtain the precise calculation model of the intelligent flow meter based on differential pressure precise calculation;

[0061] Based on the intelligent flow meter precision calculation test set, the intelligent flow meter precision calculation model based on differential pressure precision calculation is tested and evaluated;

[0062] Determine the test evaluation results based on the precise calculation model of the intelligent flow meter;

[0063] Optimization and adjustment unit, used to optimize and adjust the precise calculation model of the intelligent flow meter;

[0064] Obtain test evaluation results based on the precise calculation model of intelligent flow meter;

[0065] Analyze the test evaluation results based on the precise calculation model of the intelligent flow meter;

[0066] Determine the optimal adjustment plan based on the precise calculation model of the intelligent flow meter;

[0067] Optimize and adjust the precise calculation model of the intelligent flow meter according to the optimization adjustment scheme based on the precise calculation model of the intelligent flow meter;

[0068] Determine the optimal intelligent flow meter accurate calculation model.

[0069] Preferably, the precise calculation module includes:

[0070] A data acquisition unit, used for acquiring real-time data of a differential pressure flow meter;

[0071] According to the precise calculation requirements of the intelligent flow meter, obtain the real-time data of the differential pressure flow meter;

[0072] Precision calculation unit, used to accurately calculate the flow of the intelligent flow meter;

[0073] Obtain the optimal intelligent flow meter accurate calculation model;

[0074] Input the real-time data of the differential pressure flow meter into the optimal intelligent flow meter precision calculation model;

[0075] Based on the optimal intelligent flow meter accurate calculation model, the real-time data of the differential pressure flow meter is used to accurately calculate the flow rate of the intelligent flow meter;

[0076] The precise flow calculation result of the intelligent flow meter is determined, and the precise flow calculation result of the intelligent flow meter is automatically presented on the display screen in a visual form.

[0077] According to another aspect of the present invention, a calculation method of an intelligent flow meter based on differential pressure precise calculation is provided, which is implemented based on the intelligent flow meter based on differential pressure precise calculation as described above, and includes the following steps:

[0078] S1: collecting historical data of the differential pressure flowmeter based on big data, processing the historical data of the differential pressure flowmeter based on big data, and determining characteristic data of the differential pressure flowmeter based on big data;

[0079] S2: According to the precise calculation requirements of the intelligent flow meter, a precise calculation model of the intelligent flow meter based on differential pressure precise calculation is constructed, the precise calculation model of the intelligent flow meter is evaluated and optimized, and the optimal precise calculation model of the intelligent flow meter is determined;

[0080] S3: According to the precise calculation requirements of the intelligent flow meter, the real-time data of the differential pressure flow meter is obtained, and the intelligent flow meter flow is precisely calculated on the real-time data of the differential pressure flow meter based on the optimal precise calculation model of the intelligent flow meter, and the precise calculation result of the intelligent flow meter flow is determined, and the precise calculation result of the intelligent flow meter flow is automatically presented on the display screen in a visual form.

[0081] Compared with the prior art, the present invention has the following beneficial effects:

[0082] The present invention collects historical data of differential pressure flowmeter based on big data, processes the historical data of differential pressure flowmeter based on big data, determines characteristic data of differential pressure flowmeter based on big data, constructs precise calculation model of intelligent flowmeter based on differential pressure precise calculation according to precise calculation requirement of intelligent flowmeter, evaluates and optimizes the precise calculation model of intelligent flowmeter, determines the optimal precise calculation model of intelligent flowmeter, obtains real-time data of differential pressure flowmeter according to precise calculation requirement of intelligent flowmeter, performs precise calculation of flow of intelligent flowmeter on real-time data of differential pressure flowmeter based on the optimal precise calculation model of intelligent flowmeter, determines the precise calculation result of flow of intelligent flowmeter, and automatically presents the precise calculation result of flow of intelligent flowmeter in visual form on display screen, can accurately calculate flow of flowmeter, make measurement result of intelligent flowmeter accurate, and can better meet the precise calculation requirement of flow of intelligent flowmeter. BRIEF DESCRIPTION OF THE DRAWINGS

[0083] Figure 1 It is a structural schematic diagram of the intelligent flow meter based on differential pressure precise calculation of the present invention;

[0084] Figure 2 It is a module framework of the intelligent flow meter based on differential pressure precise calculation of the present invention;

[0085] Figure 3 This is a calculation flow chart of the intelligent flow meter based on differential pressure precise calculation of the present invention.

[0086] In the figure: 1. pipe body; 2. flange; 3. pressure pipe; 4. smart flow meter body; 5. display screen. DETAILED DESCRIPTION

[0087] 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.

[0088] In order to solve the problem that the existing flow meter cannot accurately calculate the flow, resulting in inaccurate measurement results of the intelligent flow meter, and cannot better meet the demand for accurate flow calculation of the intelligent flow meter, please refer to Figure 1-Figure 3 , this embodiment provides the following technical solutions:

[0089] The intelligent flow meter based on differential pressure precise calculation includes a pipe body 1, flanges 2 are provided at both ends of the pipe body 1, mounting holes arranged in a circular array with the central axis of the pipe body 1 as the axis are provided on the flange 2, a pressure pipe 3 is provided at the upper end of the pipe body 1, an intelligent flow meter body 4 is provided on the pressure pipe 3, and a display screen 5 is provided on the intelligent flow meter body 4; wherein, the intelligent flow meter body 4 includes:

[0090] A data acquisition module is used to collect fluid differential pressure data, fluid density data, fluid flow data and throttling device cross-sectional area data, and determine the historical data of the differential pressure flow meter based on big data;

[0091] The precise calculation microprocessor is used to process and train the historical data of the differential pressure flow meter based on big data, and to accurately calculate the flow of the intelligent flow meter, so as to determine the precise calculation result of the flow of the intelligent flow meter.

[0092] It should be noted that by collecting fluid differential pressure data, fluid density data, fluid flow data and throttling device cross-sectional area data, the historical data of the differential pressure flowmeter based on big data is determined. By processing and training the historical data of the differential pressure flowmeter based on big data, and accurately calculating the flow of the intelligent flowmeter, the precise calculation result of the flow of the intelligent flowmeter is determined. The flowmeter flow can be accurately calculated, so that the measurement results of the intelligent flowmeter are accurate, which can better meet the precise calculation needs of the flow of the intelligent flowmeter.

[0093] In this embodiment, the data acquisition module includes:

[0094] The differential pressure collection unit is used to monitor and collect the pressure difference generated when the fluid in the pipe body 1 flows through the throttling device in real time, and obtain the fluid differential pressure data;

[0095] The density acquisition unit is used to monitor and acquire the density of the fluid flowing through the throttling device in the pipe body 1 in real time, and obtain the fluid density data;

[0096] A flow collection unit is used to monitor and collect the flow of the fluid flowing through the throttling device in the pipe body 1 in real time to obtain fluid flow data;

[0097] The cross-sectional area acquisition unit is used to monitor and acquire the cross-sectional area of ​​the throttling device in the pipe body 1 in real time, and obtain the cross-sectional area data of the throttling device;

[0098] Among them, based on the fluid differential pressure data, fluid density data, fluid flow data and throttling device cross-sectional area data, the historical data of the differential pressure flowmeter based on big data is determined.

[0099] Specifically, the data acquisition module further includes:

[0100] A real-time monitoring module, used for real-time monitoring of the data collection frequency per unit time of the differential pressure collection unit, the density collection unit, the flow collection unit and the cross-sectional area collection unit;

[0101] a target acquisition unit determination module, for marking the acquisition unit whose data acquisition frequency changes as a target acquisition unit when the data acquisition frequency of any one of the differential pressure acquisition unit, the density acquisition unit, the flow acquisition unit and the cross-sectional area acquisition unit changes;

[0102] A data acquisition frequency value extraction module is used to extract the data acquisition frequency value of the target acquisition unit after the change and the data acquisition frequency value before the change;

[0103] A data acquisition frequency difference determination module is used to obtain a data acquisition frequency difference by using a data acquisition frequency value after the change and a data acquisition frequency value before the change of the target acquisition unit;

[0104] A first acquisition frequency compensation value acquisition module, configured to acquire acquisition frequency compensation values ​​of other acquisition units except the target acquisition unit by using the data acquisition frequency difference value when the data acquisition frequency difference value is lower than a preset frequency change difference value threshold value;

[0105] The acquisition frequency compensation amount of the acquisition units other than the target acquisition unit is obtained by the following formula: Wherein, Δf represents the acquisition frequency compensation of other acquisition units except the target acquisition unit; M represents the change ratio of the temperature of the environment in which the differential pressure acquisition unit, density acquisition unit, flow acquisition unit and cross-sectional area acquisition unit are located; V represents the ratio between the data transmission load of the current differential pressure acquisition unit, density acquisition unit, flow acquisition unit and cross-sectional area acquisition unit and the maximum data transmission load that the network bandwidth can bear; L represents the ratio between the minimum data acquisition frequency and the maximum data acquisition frequency of other acquisition units except the target acquisition unit; α, β and γ represent the weight values ​​corresponding to the ambient temperature change ratio, load ratio and data acquisition frequency ratio respectively; f h and f x They represent the data acquisition frequency value of the target acquisition unit after the change and the data acquisition frequency value before the change respectively; f min represents the minimum value of the data acquisition frequency of other acquisition units except the target acquisition unit; n represents the number of other acquisition units except the target acquisition unit; f i represents the data collection frequency value of the i-th collection unit other than the target collection unit; f z Indicates the median value of the data acquisition frequency of the differential pressure acquisition unit, the density acquisition unit, the flow acquisition unit, and the cross-sectional area acquisition unit;

[0106] The first acquisition frequency compensation adjustment module is used to compensate and adjust the acquisition frequencies of other acquisition units except the target acquisition unit by using the acquisition frequency compensation amount of the other acquisition units; wherein the adjusted acquisition frequencies of other acquisition units except the target acquisition unit are obtained by the following formula: Among them, f t01 Indicates the adjusted acquisition frequency of other acquisition units except the target acquisition unit; f n represents the acquisition frequency of other acquisition units except the target acquisition unit before adjustment; Δf represents the acquisition frequency compensation amount of other acquisition units except the target acquisition unit.

[0107] The technical effect of the above technical solution is: through the real-time monitoring module, the data acquisition frequency of the differential pressure acquisition unit, the density acquisition unit, the flow acquisition unit and the cross-sectional area acquisition unit can be tracked in real time. This helps to promptly detect abnormalities in the data acquisition process and ensure the accuracy and integrity of the data. When the data acquisition frequency of any acquisition unit changes, the target acquisition unit determination module can quickly mark the unit, providing a basis for subsequent data analysis and processing. The data acquisition frequency value extraction module can extract the data acquisition frequency value before and after the target acquisition unit changes, providing data support for calculating the data acquisition frequency difference.

[0108] The data acquisition frequency difference determination module can evaluate the degree of frequency change by calculating the data acquisition frequency difference before and after the target acquisition unit changes. When the data acquisition frequency difference is lower than the preset frequency change difference threshold, the first acquisition frequency compensation amount acquisition module will use the difference to calculate the acquisition frequency compensation amount of other acquisition units except the target acquisition unit. This compensation mechanism helps to balance the data acquisition frequency of each acquisition unit and ensure the stability and consistency of the overall data acquisition. The first acquisition frequency compensation adjustment module uses the calculated acquisition frequency compensation amount to compensate and adjust the acquisition frequency of other acquisition units except the target acquisition unit. This helps to optimize the data acquisition process and improve the efficiency and accuracy of data acquisition.

[0109] When calculating the acquisition frequency compensation, the scheme comprehensively considers multiple factors such as the ambient temperature change ratio, load ratio, and data acquisition frequency ratio, making the calculation of the compensation more accurate and reasonable. By introducing weight values ​​α, β, and γ, the proportion of each factor in the compensation calculation can be adjusted according to actual conditions, improving the flexibility and adaptability of the compensation effect.

[0110] In summary, the above technical solution optimizes the data collection process and improves the accuracy and efficiency of data collection through real-time monitoring, data analysis, frequency compensation and adjustment, and comprehensive consideration of multiple factors. At the same time, the solution also has certain flexibility and adaptability, and can be adjusted and optimized according to actual conditions.

[0111] Specifically, the data acquisition module further includes:

[0112] A first data acquisition frequency difference acquisition module is used to extract the data acquisition frequency difference between the changed data acquisition frequency of the target acquisition unit and the current data acquisition frequency of other acquisition units as the first data acquisition frequency difference when the data acquisition frequency difference is not lower than a preset frequency change difference threshold;

[0113] A second data acquisition frequency difference acquisition module is used to extract the data acquisition frequency difference between the data acquisition frequency of the target acquisition unit before the change and the current data acquisition frequency of other acquisition units as the second data acquisition frequency difference;

[0114] A second acquisition frequency compensation value acquisition module is used to acquire acquisition frequency adjustment values ​​of other acquisition units except the target acquisition unit by using the first data acquisition frequency difference value and the second data acquisition frequency difference value and the difference between the data acquisition frequency value of the target acquisition unit after the change and the data acquisition frequency value before the change;

[0115] The acquisition frequency adjustment amount of the acquisition units other than the target acquisition unit is obtained by the following formula: Where Δf c represents the acquisition frequency adjustment amount of other acquisition units except the target acquisition unit; K represents a preset adjustment coefficient, and the value range of the adjustment coefficient is [0,10]; f h and f x They represent the data acquisition frequency value of the target acquisition unit after the change and the data acquisition frequency value before the change respectively; n represents the number of other acquisition units except the target acquisition unit; f i represents the data collection frequency value of the i-th collection unit other than the target collection unit; f y Indicates the preset frequency change difference threshold;

[0116] A second acquisition frequency compensation adjustment module, used to adjust the acquisition frequencies of other acquisition units except the target acquisition unit by using the acquisition frequency adjustment amount of the other acquisition units;

[0117] Among them, f t02represents the acquisition frequency of other acquisition units except the target acquisition unit after the acquisition frequency is adjusted by using the acquisition frequency adjustment amount; f n Indicates the acquisition frequency of other acquisition units except the target acquisition unit before adjustment; Δf c Indicates the acquisition frequency adjustment amount of other acquisition units except the target acquisition unit.

[0118] The technical effect of the above technical solution is: when the data acquisition frequency difference exceeds the preset frequency change difference threshold, the technical solution introduces the concept of the first data acquisition frequency difference and the second data acquisition frequency difference to conduct a more detailed analysis of the difference between the data acquisition frequency before and after the target acquisition unit changes and the current data acquisition frequency of other acquisition units. This refined frequency adjustment mechanism helps to more accurately evaluate the frequency deviation between the acquisition units and provide more powerful data support for subsequent frequency adjustment. The second acquisition frequency compensation amount acquisition module uses the first and second data acquisition frequency differences, as well as the data acquisition frequency difference before and after the target acquisition unit changes, to calculate the acquisition frequency adjustment amount of other acquisition units except the target acquisition unit. This dynamic adjustment method can automatically adjust the acquisition frequency of other acquisition units according to the real-time data acquisition situation to better adapt to changes in the data acquisition environment.

[0119] When calculating the acquisition frequency adjustment amount, a preset adjustment coefficient K is introduced, and its value range is between [0,10]. By adjusting the value of K, the adjustment amplitude of the acquisition frequency can be flexibly controlled according to actual needs, so that the adjustment process is more in line with the needs of actual application scenarios. By adjusting the acquisition frequency of other acquisition units except the target acquisition unit, this technical solution helps to balance the overall data acquisition efficiency. When the acquisition frequency of the target acquisition unit changes significantly, by adjusting the acquisition frequency of other acquisition units, the stability and consistency of the overall data acquisition can be maintained, avoiding the decrease in the overall data acquisition efficiency due to abnormal frequencies of individual acquisition units.

[0120] Overall, this technical solution improves the stability and reliability of the data acquisition system by real-time monitoring of the data acquisition frequency, dynamically calculating the acquisition frequency adjustment amount and making corresponding adjustments. It can respond to abnormal situations in the data acquisition process in a timely manner and take corresponding adjustment measures to ensure the accuracy and continuity of data acquisition. This is especially important for application scenarios that require high-precision and high-reliability data acquisition.

[0121] In summary, the above technical solution significantly improves the stability and reliability of the data acquisition system by introducing a more sophisticated frequency adjustment mechanism, dynamically adjusting the acquisition frequency, flexible adjustment coefficients, and balancing the overall data acquisition efficiency.

[0122] In this embodiment, the precision computing microprocessor includes:

[0123] A data processing module, used for processing the historical data of the differential pressure flow meter based on big data, and determining the characteristic data of the differential pressure flow meter based on big data;

[0124] It should be noted that the data processing module includes:

[0125] A data cleaning unit, used for cleaning historical data of differential pressure flowmeter based on big data;

[0126] Obtain historical data of differential pressure flowmeter based on big data;

[0127] Conduct consistency check on historical data of differential pressure flowmeter based on big data;

[0128] According to the reasonable value range and mutual relationship of each variable in the historical data of the differential pressure flowmeter, check whether the historical data of the differential pressure flowmeter meets the requirements;

[0129] Remove inconsistent data that is beyond the normal range, logically unreasonable or contradictory in the historical data of the differential pressure flow meter;

[0130] Process invalid and missing values ​​of historical data of differential pressure flowmeter based on big data;

[0131] Remove invalid and missing data from the historical data of the differential pressure flow meter that are of no value to the accurate calculation of the intelligent flow meter;

[0132] Determine the historical data of differential pressure flowmeter that is valuable for accurate calculation of intelligent flowmeter;

[0133] A feature extraction unit, used for extracting features from historical data of the differential pressure flowmeter after cleaning;

[0134] Obtain historical data of differential pressure flowmeter after cleaning, which is valuable for accurate calculation of intelligent flowmeter;

[0135] Extract features from valuable historical data of differential pressure flowmeters for accurate calculation of intelligent flowmeters;

[0136] Determine the characteristic data of differential pressure flowmeter based on big data.

[0137] Model training module, used to build an intelligent flow meter precision calculation model based on differential pressure precision calculation according to the precision calculation requirements of the intelligent flow meter;

[0138] It should be noted that the model training module includes:

[0139] A data division unit, used for dividing characteristic data of a differential pressure flow meter based on big data;

[0140] Obtain characteristic data of differential pressure flowmeter based on big data;

[0141] Divide the characteristic data of differential pressure flowmeter based on big data;

[0142] Determine the intelligent flow meter accurate calculation training set and the intelligent flow meter accurate calculation test set;

[0143] Model training unit, used to build precise calculation model of intelligent flow meter;

[0144] According to the precise calculation requirements of the intelligent flow meter, select the neural network model framework suitable for the precise calculation of the intelligent flow meter;

[0145] Based on the intelligent flow meter accurate calculation training set, the neural network model framework suitable for the intelligent flow meter accurate calculation is trained;

[0146] Determine the precise calculation model of the intelligent flow meter based on differential pressure precise calculation.

[0147] An evaluation and optimization module is used to evaluate and optimize the precise calculation model of the intelligent flow meter based on differential pressure precise calculation, and determine the optimal precise calculation model of the intelligent flow meter;

[0148] It should be noted that the evaluation and optimization module includes:

[0149] Test and evaluation unit, used to test and evaluate the precise calculation model of the intelligent flow meter;

[0150] Obtain the precise calculation model of the intelligent flow meter based on differential pressure precise calculation;

[0151] Based on the intelligent flow meter precision calculation test set, the intelligent flow meter precision calculation model based on differential pressure precision calculation is tested and evaluated;

[0152] Determine the test evaluation results based on the precise calculation model of the intelligent flow meter;

[0153] Optimization and adjustment unit, used to optimize and adjust the precise calculation model of the intelligent flow meter;

[0154] Obtain test evaluation results based on the precise calculation model of intelligent flow meter;

[0155] Analyze the test evaluation results based on the precise calculation model of the intelligent flow meter;

[0156] Determine the optimal adjustment plan based on the precise calculation model of the intelligent flow meter;

[0157] Optimize and adjust the precise calculation model of the intelligent flow meter according to the optimization adjustment scheme based on the precise calculation model of the intelligent flow meter;

[0158] Determine the optimal intelligent flow meter accurate calculation model.

[0159] The precise calculation module is used to accurately calculate the flow rate of the intelligent flow meter and determine the precise calculation result of the flow rate of the intelligent flow meter.

[0160] It should be noted that the precise calculation module includes:

[0161] A data acquisition unit, used for acquiring real-time data of a differential pressure flow meter;

[0162] According to the precise calculation requirements of the intelligent flow meter, obtain the real-time data of the differential pressure flow meter;

[0163] Precision calculation unit, used to accurately calculate the flow of the intelligent flow meter;

[0164] Obtain the optimal intelligent flow meter accurate calculation model;

[0165] Input the real-time data of the differential pressure flow meter into the optimal intelligent flow meter precision calculation model;

[0166] Based on the optimal intelligent flow meter accurate calculation model, the real-time data of the differential pressure flow meter is used to accurately calculate the flow rate of the intelligent flow meter;

[0167] The precise calculation result of the flow rate of the intelligent flow meter is determined, and the precise calculation result of the flow rate of the intelligent flow meter is automatically presented on the display screen 5 in a visual form.

[0168] In order to better demonstrate the calculation process of the intelligent flow meter based on differential pressure precise calculation, this embodiment now provides a calculation method of the intelligent flow meter based on differential pressure precise calculation, which is implemented based on the intelligent flow meter based on differential pressure precise calculation as described above, and includes the following steps:

[0169] S1: collecting historical data of the differential pressure flowmeter based on big data, processing the historical data of the differential pressure flowmeter based on big data, and determining characteristic data of the differential pressure flowmeter based on big data;

[0170] S2: According to the precise calculation requirements of the intelligent flow meter, a precise calculation model of the intelligent flow meter based on differential pressure precise calculation is constructed, the precise calculation model of the intelligent flow meter is evaluated and optimized, and the optimal precise calculation model of the intelligent flow meter is determined;

[0171] S3: According to the precise calculation requirements of the intelligent flow meter, the real-time data of the differential pressure flow meter is obtained, and the precise flow calculation of the intelligent flow meter is performed on the real-time data of the differential pressure flow meter based on the optimal precise calculation model of the intelligent flow meter, and the precise calculation result of the flow of the intelligent flow meter is determined, and the precise calculation result of the flow of the intelligent flow meter is automatically presented in a visual form on the display screen 5.

[0172] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0173] 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. An intelligent flow meter based on differential pressure precise calculation, comprising a pipe body (1), characterized in that: Both ends of the tube body (1) are provided with flanges (2), the flanges (2) are provided with mounting holes arranged in a circular array with the central axis of the tube body (1) as the axis, the upper end of the tube body (1) is provided with a pressure guide tube (3), the pressure guide tube (3) is provided with an intelligent flow meter body (4), and the intelligent flow meter body (4) is provided with a display screen (5); wherein the intelligent flow meter body (4) comprises: A data acquisition module is used to collect fluid differential pressure data, fluid density data, fluid flow data and throttling device cross-sectional area data, and determine the historical data of the differential pressure flow meter based on big data; A precise calculation microprocessor is used to process and train the historical data of the differential pressure flowmeter based on big data, and to accurately calculate the flow of the intelligent flowmeter, and determine the precise calculation result of the flow of the intelligent flowmeter; The data acquisition module comprises: A differential pressure collection unit, used to monitor and collect the pressure difference generated when the fluid in the pipe body (1) flows through the throttling device in real time, and obtain fluid differential pressure data; A density collection unit, used to monitor and collect the density of the fluid flowing through the throttling device in the pipe body (1) in real time, and obtain fluid density data; A flow collection unit, used to monitor and collect the flow of the fluid flowing through the throttling device in the pipe body (1) in real time, and obtain fluid flow data; A cross-sectional area acquisition unit, used for real-time monitoring and acquisition of the cross-sectional area of ​​the throttling device in the pipe body (1), and obtaining cross-sectional area data of the throttling device; Wherein, based on the fluid differential pressure data, the fluid density data, the fluid flow data and the cross-sectional area data of the throttling device, the historical data of the differential pressure flow meter based on big data is determined; The data acquisition module further includes: A real-time monitoring module, used for real-time monitoring of the data collection frequency per unit time of the differential pressure collection unit, the density collection unit, the flow collection unit and the cross-sectional area collection unit; a target acquisition unit determination module, for marking the acquisition unit whose data acquisition frequency changes as a target acquisition unit when the data acquisition frequency of any one of the differential pressure acquisition unit, the density acquisition unit, the flow acquisition unit and the cross-sectional area acquisition unit changes; A data acquisition frequency value extraction module is used to extract the data acquisition frequency value of the target acquisition unit after the change and the data acquisition frequency value before the change; A data acquisition frequency difference determination module is used to obtain a data acquisition frequency difference by using a data acquisition frequency value after the change and a data acquisition frequency value before the change of the target acquisition unit; A first acquisition frequency compensation value acquisition module, configured to acquire acquisition frequency compensation values ​​of other acquisition units except the target acquisition unit by using the data acquisition frequency difference value when the data acquisition frequency difference value is lower than a preset frequency change difference value threshold value; The acquisition frequency compensation amount of the acquisition units other than the target acquisition unit is obtained by the following formula: Wherein, Δf represents the acquisition frequency compensation of other acquisition units except the target acquisition unit; M represents the change ratio of the temperature of the environment in which the differential pressure acquisition unit, density acquisition unit, flow acquisition unit and cross-sectional area acquisition unit are located; V represents the ratio between the data transmission load of the current differential pressure acquisition unit, density acquisition unit, flow acquisition unit and cross-sectional area acquisition unit and the maximum data transmission load that the network bandwidth can bear; L represents the ratio between the minimum data acquisition frequency and the maximum data acquisition frequency of other acquisition units except the target acquisition unit; α, β and γ represent the weight values ​​corresponding to the ambient temperature change ratio, load ratio and data acquisition frequency ratio respectively; f h and f x They represent the data acquisition frequency value of the target acquisition unit after the change and the data acquisition frequency value before the change respectively; f min represents the minimum value of the data acquisition frequency of other acquisition units except the target acquisition unit; n represents the number of other acquisition units except the target acquisition unit; f i represents the data collection frequency value of the i-th collection unit other than the target collection unit; f z Indicates the median value of the data acquisition frequency of the differential pressure acquisition unit, the density acquisition unit, the flow acquisition unit, and the cross-sectional area acquisition unit; The first acquisition frequency compensation adjustment module is used to compensate and adjust the acquisition frequencies of other acquisition units except the target acquisition unit by using the acquisition frequency compensation amount of the other acquisition units; wherein the adjusted acquisition frequencies of other acquisition units except the target acquisition unit are obtained by the following formula: Among them, f t01 Indicates the adjusted acquisition frequency of other acquisition units except the target acquisition unit; f n Indicates the acquisition frequency of other acquisition units except the target acquisition unit before adjustment.

2. The intelligent flow meter based on differential pressure precise calculation according to claim 1 is characterized in that: The data acquisition module further includes: A first data acquisition frequency difference acquisition module is used to extract the data acquisition frequency difference between the changed data acquisition frequency of the target acquisition unit and the current data acquisition frequency of other acquisition units as the first data acquisition frequency difference when the data acquisition frequency difference is not lower than a preset frequency change difference threshold; A second data acquisition frequency difference acquisition module is used to extract the data acquisition frequency difference between the data acquisition frequency of the target acquisition unit before the change and the current data acquisition frequency of other acquisition units as the second data acquisition frequency difference; A second acquisition frequency compensation value acquisition module is used to acquire acquisition frequency adjustment values ​​of other acquisition units except the target acquisition unit by using the first data acquisition frequency difference value and the second data acquisition frequency difference value and the difference between the data acquisition frequency value of the target acquisition unit after the change and the data acquisition frequency value before the change; The acquisition frequency adjustment amount of the acquisition units other than the target acquisition unit is obtained by the following formula: Where Δf c represents the acquisition frequency adjustment amount of other acquisition units except the target acquisition unit; K represents a preset adjustment coefficient, and the value range of the adjustment coefficient is [0,10]; f y Indicates the preset frequency change difference threshold; A second acquisition frequency compensation adjustment module, used to adjust the acquisition frequencies of other acquisition units except the target acquisition unit by using the acquisition frequency adjustment amount of the other acquisition units; Among them, f t02 It indicates the acquisition frequencies of other acquisition units except the target acquisition unit after the acquisition frequencies are adjusted by using the acquisition frequency adjustment amount.

3. The intelligent flow meter based on differential pressure precise calculation according to claim 2 is characterized in that: The precision computing microprocessor comprises: A data processing module, used for processing the historical data of the differential pressure flow meter based on big data, and determining the characteristic data of the differential pressure flow meter based on big data; Model training module, used to build an intelligent flow meter precision calculation model based on differential pressure precision calculation according to the precision calculation requirements of the intelligent flow meter; An evaluation and optimization module is used to evaluate and optimize the precise calculation model of the intelligent flow meter based on differential pressure precise calculation, and determine the optimal precise calculation model of the intelligent flow meter; The precise calculation module is used to accurately calculate the flow rate of the intelligent flow meter and determine the precise calculation result of the flow rate of the intelligent flow meter.

4. The intelligent flow meter based on differential pressure precise calculation according to claim 3 is characterized in that: The data processing module comprises: A data cleaning unit, used for cleaning historical data of differential pressure flowmeter based on big data; Obtain historical data of differential pressure flowmeter based on big data; Conduct consistency check on historical data of differential pressure flowmeter based on big data; According to the reasonable value range and mutual relationship of each variable in the historical data of the differential pressure flowmeter, check whether the historical data of the differential pressure flowmeter meets the requirements; Remove inconsistent data that is beyond the normal range, logically unreasonable or contradictory in the historical data of the differential pressure flow meter; Process invalid and missing values ​​of historical data of differential pressure flowmeter based on big data; Remove invalid and missing data from the historical data of the differential pressure flow meter that are of no value to the accurate calculation of the intelligent flow meter; Determine the historical data of differential pressure flowmeter that is valuable for accurate calculation of intelligent flowmeter; A feature extraction unit, used for extracting features from historical data of the differential pressure flowmeter after cleaning; Obtain historical data of differential pressure flowmeter after cleaning, which is valuable for accurate calculation of intelligent flowmeter; Extract features from valuable historical data of differential pressure flowmeters for accurate calculation of intelligent flowmeters; Determine the characteristic data of differential pressure flowmeter based on big data.

5. The intelligent flow meter based on differential pressure precise calculation according to claim 4 is characterized in that: The model training module includes: A data division unit, used for dividing characteristic data of a differential pressure flow meter based on big data; Obtain characteristic data of differential pressure flowmeter based on big data; Divide the characteristic data of differential pressure flowmeter based on big data; Determine the intelligent flow meter accurate calculation training set and the intelligent flow meter accurate calculation test set; Model training unit, used to build precise calculation model of intelligent flow meter; According to the precise calculation requirements of the intelligent flow meter, select the neural network model framework suitable for the precise calculation of the intelligent flow meter; Based on the intelligent flow meter accurate calculation training set, the neural network model framework suitable for the intelligent flow meter accurate calculation is trained; Determine the precise calculation model of the intelligent flow meter based on differential pressure precise calculation.

6. The intelligent flow meter based on differential pressure precise calculation according to claim 5, characterized in that: The evaluation and optimization module includes: Test and evaluation unit, used to test and evaluate the precise calculation model of the intelligent flow meter; Obtain the precise calculation model of the intelligent flow meter based on differential pressure precise calculation; Based on the intelligent flow meter precision calculation test set, the intelligent flow meter precision calculation model based on differential pressure precision calculation is tested and evaluated; Determine the test evaluation results based on the precise calculation model of the intelligent flow meter; Optimization and adjustment unit, used to optimize and adjust the precise calculation model of the intelligent flow meter; Obtain test evaluation results based on the precise calculation model of intelligent flow meter; Analyze the test evaluation results based on the precise calculation model of the intelligent flow meter; Determine the optimal adjustment plan based on the precise calculation model of the intelligent flow meter; Optimize and adjust the precise calculation model of the intelligent flow meter according to the optimization adjustment scheme based on the precise calculation model of the intelligent flow meter; Determine the optimal intelligent flow meter accurate calculation model.

7. The intelligent flow meter based on differential pressure precise calculation according to claim 6 is characterized in that: The precise calculation module comprises: A data acquisition unit, used for acquiring real-time data of a differential pressure flow meter; According to the precise calculation requirements of the intelligent flow meter, obtain the real-time data of the differential pressure flow meter; Precision calculation unit, used to accurately calculate the flow of the intelligent flow meter; Obtain the optimal intelligent flow meter accurate calculation model; Input the real-time data of the differential pressure flow meter into the optimal intelligent flow meter precision calculation model; Based on the optimal intelligent flow meter accurate calculation model, the real-time data of the differential pressure flow meter is used to accurately calculate the flow rate of the intelligent flow meter; The accurate calculation result of the flow rate of the intelligent flow meter is determined, and the accurate calculation result of the flow rate of the intelligent flow meter is automatically presented on the display screen (5) in a visual form.

8. A calculation method of an intelligent flowmeter based on differential pressure accurate calculation, implemented based on the intelligent flowmeter based on differential pressure accurate calculation as claimed in claim 7, characterized in that: The steps include: S1: collecting historical data of the differential pressure flowmeter based on big data, processing the historical data of the differential pressure flowmeter based on big data, and determining characteristic data of the differential pressure flowmeter based on big data; S2: According to the precise calculation requirements of the intelligent flow meter, a precise calculation model of the intelligent flow meter based on differential pressure precise calculation is constructed, the precise calculation model of the intelligent flow meter is evaluated and optimized, and the optimal precise calculation model of the intelligent flow meter is determined; S3: According to the precise calculation requirements of the intelligent flow meter, the real-time data of the differential pressure flow meter is obtained, and the intelligent flow meter flow precise calculation is performed on the real-time data of the differential pressure flow meter based on the optimal intelligent flow meter precise calculation model, and the precise calculation result of the intelligent flow meter flow is determined, and the precise calculation result of the intelligent flow meter flow is automatically presented in a visual form on the display screen (5).

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