An electromagnetic flowmeter flow prediction method based on artificial intelligence

Abstract

The present invention relates to the field of flow measurement of electromagnetic flowmeters, and specifically discloses an electromagnetic flowmeter flow prediction method based on artificial intelligence. The present invention obtains the environmental condition information for measuring the flow rate of conductive fluids by an electromagnetic flowmeter, analyzes the influence of environmental conditions on its measurement results, obtains the fluid property information for measuring the flow rate of conductive fluids by an electromagnetic flowmeter, analyzes the influence of fluid properties on its measurement results, obtains the surrounding magnetic field information for measuring the flow rate of conductive fluids by an electromagnetic flowmeter, analyzes the influence of the surrounding magnetic field on its measurement results, further analyzes the correction amount of the measured data for measuring the flow rate of conductive fluids by an electromagnetic flowmeter, predicts the result of measuring the flow rate of conductive fluids by an electromagnetic flowmeter, takes into account the influence of factors such as environmental conditions, fluid properties, and electromagnetic interference on the measurement of electromagnetic flowmeters, and then calibrates and corrects the measured data of electromagnetic flowmeters, thereby improving the reliability and accuracy of the measurement results of electromagnetic flowmeters.

Description

Technical Field

[0001] The present invention relates to the field of electromagnetic flowmeter flow measurement, and relates to a flow prediction method for electromagnetic flowmeters based on artificial intelligence. Background Art

[0002] With the continuous development of industrial automation, electromagnetic flowmeters, as a key instrument for measuring the flow of conductive fluids, are widely used in various industries. Electromagnetic flowmeters work based on Faraday's law of electromagnetic induction. When a conductor moves in a magnetic field, an electromotive force is generated in the conductor. Electromagnetic flowmeters use this principle to measure the velocity of the fluid and then calculate the flow rate.

[0003] However, the existing technologies for measuring the flow of conductive fluids using electromagnetic flowmeters still have some limitations and deficiencies in practical applications.

[0004] For example, the Chinese patent with the publication number CN103063276A discloses an electromagnetic flowmeter calibration system, which includes an industrial computer, a standard meter, a calibration module, and a verification module. The calibration module and the verification module are built into the industrial computer; the calibration module is built with an identity authentication module, a display module, and a control module; the verification module is built with a data processing module. This invention reduces the operation difficulty and complexity as much as possible. Various parameters and data can be intuitively displayed on the graphical interface. The data acquisition and calculation of each flow point are completed by the program itself, without the need for operators to intervene in the data processing part, improving the reliability of calibration and verification operations and improving work efficiency, thereby overcoming the problems of relatively high operation difficulty, relatively high complexity, relatively low reliability of verification results, and relatively low verification efficiency existing in the electromagnetic flowmeter calibration method.

[0005] However, the above patent does not consider the influence of factors such as environmental conditions, fluid properties, and electromagnetic interference on the measurement of electromagnetic flowmeters, which limits the measurement accuracy of electromagnetic flowmeters and further reduces the accuracy of the measurement results of electromagnetic flowmeters. Summary of the Invention

[0006] In view of the above problems, the present invention proposes a flow prediction method for electromagnetic flowmeters based on artificial intelligence. The specific technical solution is as follows: A flow prediction method for electromagnetic flowmeters based on artificial intelligence includes the following steps: Step 1: Obtaining information on the influence of environmental conditions on electromagnetic flowmeter measurements: Obtain the environmental condition information of the electromagnetic flowmeter measuring the flow of the target conductive fluid, where the environmental condition information includes environmental temperature, environmental humidity, and pipeline pressure, and combine the historical measurement data of the electromagnetic flowmeter to construct a prediction model for the influence of environmental conditions on the measurement results of the electromagnetic flowmeter, and analyze the influence information of the environmental conditions of the electromagnetic flowmeter measuring the flow of the target conductive fluid on its measurement results, where the influence information includes the influence trend and the influence deviation ratio.

[0007] Step 2. Acquisition of measurement information of electromagnetic flowmeter affected by fluid properties: Obtain the fluid property information of the target conductive fluid whose flow rate is measured by the electromagnetic flowmeter, where the fluid property information includes the conductivity, impurity degree, and viscosity of the target conductive fluid. Combine the historical measurement data of the electromagnetic flowmeter to construct a prediction model for the influence of fluid properties on the measurement results of the electromagnetic flowmeter, and analyze the influence information of the fluid properties of the target conductive fluid measured by the electromagnetic flowmeter on its measurement results.

[0008] Step 3. Acquisition of measurement information of electromagnetic flowmeter affected by surrounding magnetic field: Obtain the surrounding magnetic field information of the target conductive fluid whose flow rate is measured by the electromagnetic flowmeter, where the surrounding magnetic field information includes the intensity and non-uniformity of the surrounding magnetic field. Combine the historical measurement data of the electromagnetic flowmeter to construct a prediction model for the influence of the surrounding magnetic field on the measurement results of the electromagnetic flowmeter, and analyze the influence information of the surrounding magnetic field of the target conductive fluid measured by the electromagnetic flowmeter on its measurement results.

[0009] Step 4. Acquisition of actual measurement data of electromagnetic flowmeter flow rate: Obtain the actual measurement data of the target conductive fluid whose flow rate is measured by the electromagnetic flowmeter.

[0010] Step 5. Analysis of correction amount of actual measurement data of electromagnetic flowmeter flow rate: Analyze the correction amount of the actual measurement data of the target conductive fluid whose flow rate is measured by the electromagnetic flowmeter according to the influence information of the environmental conditions, fluid properties, and surrounding magnetic field on the measurement results of the electromagnetic flowmeter.

[0011] Step 6. Prediction of electromagnetic flowmeter flow measurement result: Predict the result of the target conductive fluid whose flow rate is measured by the electromagnetic flowmeter according to the actual measurement data and the correction amount of the actual measurement data of the electromagnetic flowmeter, and give feedback.

[0012] Based on the above embodiments, the specific analysis process of the said Step 1 includes: Detect the environmental temperature, environmental humidity, and pipeline pressure of the target conductive fluid whose flow rate is measured by the electromagnetic flowmeter through sensors.

[0013] Extract the historical measurement data of the electromagnetic flowmeter stored in the database, delimit each range of environmental temperature according to the preset equal-interval principle, and according to the single-variable principle, screen the actual measurement data and standard data of the historical measurements of the conductive fluid flow rate by the electromagnetic flowmeter in each environmental temperature range, and obtain the difference between the actual measurement data and the standard data of the historical measurements of the conductive fluid flow rate by the electromagnetic flowmeter in each environmental temperature range.

[0014] Obtain the absolute value of the difference between the measured data and the standard data of the historical measured flow rates of conductive fluids by the electromagnetic flowmeter at each ambient temperature range, and record it as the measurement data deviation amount of each historical measurement of the electromagnetic flowmeter at each ambient temperature range. Further, obtain the ratio between the measurement data deviation amount of each historical measurement of the electromagnetic flowmeter at each ambient temperature range and the standard data corresponding to its measurement, and use it as the measurement data deviation ratio of each historical measurement of the electromagnetic flowmeter at each ambient temperature range.

[0015] Obtain the sign of the difference between the measured data and the standard data of the historical measured flow rates of conductive fluids by the electromagnetic flowmeter at each ambient temperature range. If it is a positive sign, the measured data is greater than the standard data, and at this time, the measurement data deviation direction of the electromagnetic flowmeter measurement is on the high side. If it is a negative sign, the measured data is less than the standard data, and at this time, the measurement data deviation direction of the electromagnetic flowmeter measurement is on the low side. Furthermore, obtain the measurement data deviation direction of each historical measurement of the electromagnetic flowmeter at each ambient temperature range.

[0016] Based on the above embodiments, the specific analysis process of step one further includes: According to the measurement data deviation direction of each historical measurement of the electromagnetic flowmeter at each ambient temperature range, count the historical measurement times corresponding to each measurement data deviation direction of the electromagnetic flowmeter at each ambient temperature range, and record the measurement data deviation direction corresponding to the most historical measurement times as the influence trend of the measurement ambient temperature of the electromagnetic flowmeter on its measurement result, where the influence trend includes on the high side and on the low side. Furthermore, obtain the influence trend of the measurement ambient temperature of the electromagnetic flowmeter on its measurement result at each ambient temperature range.

[0017] Based on the above embodiments, the specific analysis process of step one further includes: Establish a coordinate system with the serial number of the historical measurement times of the electromagnetic flowmeter as the abscissa and the measurement data deviation ratio as the ordinate. According to the measurement data deviation ratio of each historical measurement of the electromagnetic flowmeter at each ambient temperature range, mark the corresponding data points in the coordinate system. Using the mathematical model establishment method, draw the linear regression horizontal line corresponding to the measurement data deviation ratio of the historical measurement of the electromagnetic flowmeter at each ambient temperature range, and obtain the measurement data deviation ratio pointed to by the linear regression horizontal line corresponding to the measurement data deviation ratio of the historical measurement of the electromagnetic flowmeter at each ambient temperature range, and record it as the influence deviation ratio of the measurement ambient temperature of the electromagnetic flowmeter on its measurement result at each ambient temperature range.

[0018] Based on the above embodiments, the specific analysis process of step one further includes: Construct a prediction model for the influence of ambient temperature on the measurement result of the electromagnetic flowmeter according to the influence trend and influence deviation ratio of the measurement ambient temperature of the electromagnetic flowmeter on its measurement result at each ambient temperature range.

[0019] Substitute the ambient temperature at which the electromagnetic flowmeter measures the flow rate of the target conductive fluid into the prediction model of the influence of ambient temperature on the measurement result of the electromagnetic flowmeter, and obtain the influence trend and influence deviation ratio of the ambient temperature of the electromagnetic flowmeter measuring the flow rate of the target conductive fluid on its measurement result.

[0020] Similarly, according to the analysis method of the prediction model of the influence of ambient temperature on the measurement result of the electromagnetic flowmeter, obtain the prediction model of the influence of ambient humidity on the measurement result of the electromagnetic flowmeter and the prediction model of the influence of pipeline pressure on the measurement result of the electromagnetic flowmeter.

[0021] Substitute the ambient humidity and pipeline pressure at which the electromagnetic flowmeter measures the flow rate of the target conductive fluid into the prediction model of the influence of ambient humidity on the measurement result of the electromagnetic flowmeter and the prediction model of the influence of pipeline pressure on the measurement result of the electromagnetic flowmeter, and obtain the influence trend and influence deviation ratio of the ambient humidity and pipeline pressure of the electromagnetic flowmeter measuring the flow rate of the target conductive fluid on its measurement result.

[0022] On the basis of the above embodiments, the specific analysis process of the second step is as follows: Detect the conductivity and viscosity of the target conductive fluid in the electromagnetic flowmeter measuring the flow rate of the target conductive fluid through an instrument, and obtain the ratio of the impurity volume to the fluid volume of the target conductive fluid in the electromagnetic flowmeter measuring the flow rate of the target conductive fluid, which is denoted as the impurity degree of the target conductive fluid in the electromagnetic flowmeter measuring the flow rate of the target conductive fluid.

[0023] Extract the historical measurement data of the electromagnetic flowmeter stored in the database. According to the principle of single variable, obtain the measurement data deviation ratio and measurement data deviation direction of each historical measurement of the electromagnetic flowmeter under different conductivity ranges, different impurity degree ranges, and different viscosity ranges of the conductive fluid respectively. Further construct a prediction model of the influence of the conductivity, impurity degree, and viscosity of the conductive fluid on the measurement result of the electromagnetic flowmeter, and substitute the conductivity, impurity degree, and viscosity of the target conductive fluid in the electromagnetic flowmeter measuring the flow rate of the target conductive fluid, and obtain the influence trend and influence deviation ratio of the conductivity, impurity degree, and viscosity of the target conductive fluid in the electromagnetic flowmeter measuring the flow rate of the target conductive fluid on its measurement result.

[0024] On the basis of the above embodiments, the specific analysis process of the third step is as follows: Detect the intensity of the magnetic field around the electromagnetic flowmeter measuring the flow rate of the target conductive fluid through an instrument, and obtain the non-uniformity of the surrounding magnetic field.

[0025] The historical measurement data of the electromagnetic flowmeter stored in the database are extracted. According to the single variable principle, the measurement data deviation ratio and measurement data deviation direction of each historical measurement of the electromagnetic flowmeter under each intensity range and each unevenness range of the surrounding magnetic field are obtained respectively. A prediction model for the impact of the surrounding magnetic field strength and unevenness on the measurement results of the electromagnetic flowmeter is further constructed. The strength and unevenness of the magnetic field around the target conductive fluid flow measured by the electromagnetic flowmeter are substituted into the model to obtain the influence trend and impact deviation ratio of the strength and unevenness of the magnetic field around the target conductive fluid flow measured by the electromagnetic flowmeter.

[0026] Based on the above embodiment, the specific analysis process of step 5 includes: S1: the influence ratio of the ambient temperature of the target conductive fluid flow rate measured by the electromagnetic flowmeter on the measurement result is recorded as k, and the analysis formula δ T =ε*k to obtain the influence coefficient δ of the ambient temperature on the measurement result of the electromagnetic flowmeter measuring the target conductive fluid flow T , where ε represents δ T The sign factor is: if the influence of the ambient temperature of the electromagnetic flowmeter on the measurement result of the target conductive fluid flow rate is relatively large, then ε = 1; if the influence of the ambient temperature on the measurement result is relatively small, then ε = -1.

[0027] S2: Similarly, according to the analysis method of S1, the influence coefficients of the ambient humidity and pipeline pressure on the measurement results of the target conductive fluid flow measured by the electromagnetic flowmeter are obtained, and the influence coefficients of the ambient temperature, ambient humidity, and pipeline pressure on the measurement results of the target conductive fluid flow measured by the electromagnetic flowmeter are accumulated to obtain the influence coefficient of the environmental conditions on the measurement results of the target conductive fluid flow measured by the electromagnetic flowmeter, which is recorded as δ1.

[0028] S3: Similarly, according to the analysis method of S1-S2, the fluid properties of the electromagnetic flowmeter measuring the flow rate of the target conductive fluid and the influence coefficient of the surrounding magnetic field on its measurement result are obtained, and they are recorded as δ2 and δ3 respectively.

[0029] Based on the above embodiment, the specific analysis process of step five also includes: obtaining the correction value ξ of the actual measured data of the target conductive fluid flow measured by the electromagnetic flowmeter through the analysis formula ξ=-ξ0*(δ1+δ2+δ3), where ξ0 represents the actual measured data of the target conductive fluid flow measured by the electromagnetic flowmeter.

[0030] Based on the above embodiment, the specific analysis process of step six is: adding the measured data of the target conductive fluid flow measured by the electromagnetic flowmeter and the correction amount of the measured data to obtain the result of the target conductive fluid flow measured by the electromagnetic flowmeter.

[0031] Compared with the prior art, the electromagnetic flowmeter flow prediction method based on artificial intelligence of the present invention has the following beneficial effects: 1. According to the historical measurement data of the electromagnetic flowmeter, the present invention constructs a prediction model for the influence of factors such as environmental conditions, fluid properties, and electromagnetic interference on the measurement results of the electromagnetic flowmeter through the principle of single variable, and then analyzes the influence trend and influence deviation ratio of factors such as environmental conditions, fluid properties, and electromagnetic interference on the measurement results of the electromagnetic flowmeter, so as to facilitate the verification of the measured data of the electromagnetic flowmeter and improve the measurement accuracy and flow prediction ability of the electromagnetic flowmeter.

[0032] 2. The present invention takes into account the influence of environmental conditions such as temperature, humidity, and pipeline pressure on the measurement results of the electromagnetic flowmeter, the influence of fluid properties such as conductivity, impurity degree, and viscosity on the measurement results of the electromagnetic flowmeter, and the influence of the surrounding magnetic field intensity and non-uniformity on the measurement results of the electromagnetic flowmeter, further analyzes the correction amount of the measured data of the electromagnetic flowmeter, and then calibrates and corrects the measured data of the electromagnetic flowmeter, so as to improve the reliability and accuracy of the measurement results of the electromagnetic flowmeter. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0034] Figure 1 It is a schematic flow chart of the method of the present invention.

[0035] Figure 2 It is a schematic diagram of the linear regression horizontal line of the present invention.

[0036] Reference numerals: 1. Serial number of the historical measurement times of the electromagnetic flowmeter; 2. Measurement data deviation ratio; 3. Incorrect data points; 4. Linear regression horizontal line. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0037] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0038] Please refer to Figure 1As shown in the figure, an electromagnetic flowmeter flow prediction method based on artificial intelligence provided by the present invention includes the following steps: Step 1, obtaining measurement information of the electromagnetic flowmeter affected by environmental conditions: obtaining environmental condition information for measuring the flow rate of the conductive fluid by the electromagnetic flowmeter, where the environmental condition information includes environmental temperature, environmental humidity, and pipeline pressure, and combining the historical measurement data of the electromagnetic flowmeter to construct a prediction model for the influence of environmental conditions on the measurement results of the electromagnetic flowmeter, and analyzing the influence information of the environmental conditions for measuring the flow rate of the conductive fluid by the electromagnetic flowmeter on its measurement results, where the influence information includes the influence trend and the influence deviation ratio.

[0039] As a preferred solution, the specific analysis process of Step 1 includes: detecting the environmental temperature, environmental humidity, and pipeline pressure of the electromagnetic flowmeter for measuring the flow rate of the conductive fluid through sensors.

[0040] It should be noted that the sensors include a temperature sensor, a humidity sensor, and a pressure sensor.

[0041] It should be noted that the conductivity of the conductive fluid changes with temperature, which directly affects the magnitude of the generated electromotive force, and further affects the conductivity of the conductive fluid. Moreover, temperature changes may cause the pipeline to expand or contract, further affecting the flow characteristics of the conductive fluid, thereby reducing the measurement accuracy of the flow rate of the conductive fluid.

[0042] It should be noted that in a high-humidity environment, moisture may condense on the electrode surface, resulting in a change in the resistance between the electrodes, and further affecting the measurement of the flow rate of the conductive fluid.

[0043] It should be noted that the conductive fluid needs to have a sufficient straight pipe section before entering the electromagnetic flowmeter to form a stable flow pattern. Changes in pipeline pressure may affect the density and viscosity of the conductive fluid, and further affect its conductivity and flow characteristics, thereby affecting the measurement results of the flow rate of the conductive fluid.

[0044] Extract the historical measurement data of the electromagnetic flowmeter stored in the database, delimit each range of environmental temperature according to the preset equal-interval principle, and screen the measured data and standard data of the historical measurements of the flow rate of the conductive fluid by the electromagnetic flowmeter under each environmental temperature range according to the single-variable principle, and obtain the difference between the measured data and the standard data of the historical measurements of the flow rate of the conductive fluid by the electromagnetic flowmeter under each environmental temperature range.

[0045] Obtain the absolute value of the difference between the measured data and the standard data of the historical measurements of the conductive fluid flow rate by the electromagnetic flowmeter at each ambient temperature range, and record it as the measurement data deviation amount of each historical measurement of the electromagnetic flowmeter at each ambient temperature range. Further, obtain the ratio between the measurement data deviation amount of each historical measurement of the electromagnetic flowmeter at each ambient temperature range and the standard data corresponding to its measurement, and use it as the measurement data deviation ratio of each historical measurement of the electromagnetic flowmeter at each ambient temperature range.

[0046] Obtain the sign of the difference between the measured data and the standard data of the historical measurements of the conductive fluid flow rate by the electromagnetic flowmeter at each ambient temperature range. If it is a positive sign, the measured data is greater than the standard data, and at this time, the measurement data deviation direction of the electromagnetic flowmeter measurement is on the high side. If it is a negative sign, the measured data is less than the standard data, and at this time, the measurement data deviation direction of the electromagnetic flowmeter measurement is on the low side. Furthermore, obtain the measurement data deviation direction of each historical measurement of the electromagnetic flowmeter at each ambient temperature range.

[0047] As a preferred solution, the specific analysis process of the first step further includes: according to the measurement data deviation direction of each historical measurement of the electromagnetic flowmeter at each ambient temperature range, count the historical measurement times corresponding to each measurement data deviation direction of the electromagnetic flowmeter at each ambient temperature range, and record the measurement data deviation direction corresponding to the most historical measurement times as the influence trend of the measurement ambient temperature of the electromagnetic flowmeter on its measurement result, where the influence trend includes on the high side and on the low side. Furthermore, obtain the influence trend of the measurement ambient temperature of the electromagnetic flowmeter on its measurement result at each ambient temperature range.

[0048] As a preferred solution, the specific analysis process of the first step further includes: refer to Figure 2 As shown, establish a coordinate system with the serial number of the historical measurement times of the electromagnetic flowmeter as the abscissa and the measurement data deviation ratio as the ordinate. According to the measurement data deviation ratio of each historical measurement of the electromagnetic flowmeter at each ambient temperature range, mark the corresponding data points in the coordinate system. Using the mathematical model establishment method, draw the linear regression horizontal line corresponding to the measurement data deviation ratio of the historical measurements of the electromagnetic flowmeter at each ambient temperature range, and obtain the measurement data deviation ratio pointed to by the linear regression horizontal line corresponding to the measurement data deviation ratio of the historical measurements of the electromagnetic flowmeter at each ambient temperature range, and record it as the influence deviation ratio of the measurement ambient temperature of the electromagnetic flowmeter on its measurement result at each ambient temperature range.

[0049] It should be noted that when drawing the linear regression horizontal line corresponding to the measurement data deviation ratio of the historical measurements of the electromagnetic flowmeter at each ambient temperature range, incorrect data points will be excluded and then analyzed.

[0050] As a preferred solution, the specific analysis process of the first step further includes: constructing a prediction model for the influence of ambient temperature on the measurement result of the electromagnetic flowmeter according to the influence trend and influence deviation ratio of the ambient temperature measured by the electromagnetic flowmeter on its measurement result in each ambient temperature range.

[0051] Substitute the ambient temperature at which the electromagnetic flowmeter measures the flow rate of the target conductive fluid into the prediction model for the influence of ambient temperature on the measurement result of the electromagnetic flowmeter, and obtain the influence trend and influence deviation ratio of the ambient temperature at which the electromagnetic flowmeter measures the flow rate of the target conductive fluid on its measurement result.

[0052] Similarly, according to the analysis method of the prediction model for the influence of ambient temperature on the measurement result of the electromagnetic flowmeter, obtain the prediction model for the influence of ambient humidity on the measurement result of the electromagnetic flowmeter and the prediction model for the influence of pipeline pressure on the measurement result of the electromagnetic flowmeter.

[0053] Substitute the ambient humidity and pipeline pressure at which the electromagnetic flowmeter measures the flow rate of the target conductive fluid into the prediction model for the influence of ambient humidity on the measurement result of the electromagnetic flowmeter and the prediction model for the influence of pipeline pressure on the measurement result of the electromagnetic flowmeter respectively, and obtain the influence trend and influence deviation ratio of the ambient humidity and pipeline pressure at which the electromagnetic flowmeter measures the flow rate of the target conductive fluid on its measurement result.

[0054] Step 2: Obtaining the influence of fluid properties on the measurement information of the electromagnetic flowmeter: Obtain the fluid property information of the target conductive fluid whose flow rate is measured by the electromagnetic flowmeter, where the fluid property information includes the conductivity, impurity content, and viscosity of the target conductive fluid, and combine the historical measurement data of the electromagnetic flowmeter to construct a prediction model for the influence of fluid properties on the measurement result of the electromagnetic flowmeter, and analyze the influence information of the fluid properties of the target conductive fluid whose flow rate is measured by the electromagnetic flowmeter on its measurement result.

[0055] As a preferred solution, the specific analysis process of the second step is: detect the conductivity and viscosity of the target conductive fluid in the flow rate of the target conductive fluid measured by the electromagnetic flowmeter through an instrument, and obtain the ratio of the impurity volume to the fluid volume of the target conductive fluid in the flow rate of the target conductive fluid measured by the electromagnetic flowmeter, and record it as the impurity content of the target conductive fluid in the flow rate of the target conductive fluid measured by the electromagnetic flowmeter.

[0056] Extract the historical measurement data of the electromagnetic flowmeter stored in the database. According to the principle of single variable, respectively obtain the measurement data deviation ratio and measurement data deviation direction of each historical measurement of the electromagnetic flowmeter under different conductivity ranges, different impurity degrees, and different viscosity ranges of the conductive fluid. Further construct a prediction model for the influence of the conductivity, impurity degree, and viscosity of the conductive fluid on the measurement result of the electromagnetic flowmeter, and substitute the conductivity, impurity degree, and viscosity of the target conductive fluid in the target conductive fluid flow measured by the electromagnetic flowmeter to obtain the influence trend and influence deviation ratio of the conductivity, impurity degree, and viscosity of the target conductive fluid in the target conductive fluid flow measured by the electromagnetic flowmeter on its measurement result.

[0057] It should be noted that the methods for constructing the prediction model of the influence of the conductivity of the conductive fluid on the measurement result of the electromagnetic flowmeter, the prediction model of the influence of the impurity degree of the conductive fluid on the measurement result of the electromagnetic flowmeter, and the prediction model of the influence of the viscosity of the conductive fluid on the measurement result of the electromagnetic flowmeter are the same as the method for constructing the prediction model of the influence of the ambient temperature on the measurement result of the electromagnetic flowmeter in terms of principle.

[0058] It should be noted that the method for obtaining the influence trend and influence deviation ratio of the conductivity, impurity degree, and viscosity of the target conductive fluid in the target conductive fluid flow measured by the electromagnetic flowmeter on its measurement result is the same as the method for obtaining the influence trend and influence deviation ratio of the ambient temperature of the target conductive fluid flow measured by the electromagnetic flowmeter on its measurement result in terms of principle.

[0059] Step 3: Obtain the influence of the surrounding magnetic field on the measurement information of the electromagnetic flowmeter: Obtain the surrounding magnetic field information of the electromagnetic flowmeter measuring the target conductive fluid flow, where the surrounding magnetic field information includes the intensity and non-uniformity of the surrounding magnetic field, and combine it with the historical measurement data of the electromagnetic flowmeter to construct a prediction model for the influence of the surrounding magnetic field on the measurement result of the electromagnetic flowmeter, and analyze the influence information of the surrounding magnetic field of the electromagnetic flowmeter measuring the target conductive fluid flow on its measurement result.

[0060] As a preferred solution, the specific analysis process of Step 3 is: Detect the intensity of the surrounding magnetic field of the electromagnetic flowmeter measuring the target conductive fluid flow through an instrument, and obtain the non-uniformity of the surrounding magnetic field.

[0061] It should be noted that the specific method for obtaining the non-uniformity of the surrounding magnetic field is: Divide the surrounding area according to a preset principle to obtain each surrounding sub-area, obtain the magnetic field intensity of each surrounding sub-area, analyze the maximum fluctuation amount of the magnetic field intensity between the surrounding sub-areas, and substitute it into the relationship function between the preset magnetic field intensity fluctuation amount and the magnetic field non-uniformity to obtain the non-uniformity of the surrounding magnetic field.

[0062] Extract the historical measurement data of the electromagnetic flowmeter stored in the database. According to the principle of single variable, obtain the measurement data deviation ratio and measurement data deviation direction of each historical measurement of the electromagnetic flowmeter under each intensity range of the surrounding magnetic field and each non-uniformity range respectively. Further construct a prediction model for the influence of the surrounding magnetic field intensity and non-uniformity on the measurement result of the electromagnetic flowmeter, and substitute the intensity and non-uniformity of the surrounding magnetic field of the conductive fluid flow measured by the electromagnetic flowmeter to obtain the influence trend and influence deviation ratio of the intensity and non-uniformity of the surrounding magnetic field of the conductive fluid flow measured by the electromagnetic flowmeter on its measurement result.

[0063] It should be noted that the method for constructing the prediction model of the influence of the surrounding magnetic field intensity on the measurement result of the electromagnetic flowmeter and the prediction model of the influence of the non-uniformity of the weekly magnetic field on the measurement result of the electromagnetic flowmeter is the same as the method for constructing the prediction model of the influence of the ambient temperature on the measurement result of the electromagnetic flowmeter in terms of principle.

[0064] It should be noted that the method for obtaining the influence trend and influence deviation ratio of the intensity and non-uniformity of the surrounding magnetic field of the conductive fluid flow measured by the electromagnetic flowmeter on its measurement result is the same as the method for obtaining the influence trend and influence deviation ratio of the ambient temperature of the conductive fluid flow measured by the electromagnetic flowmeter on its measurement result in terms of principle.

[0065] In this embodiment, the present invention constructs a prediction model for the influence of factors such as environmental conditions, fluid properties, and electromagnetic interference on the measurement result of the electromagnetic flowmeter based on the historical measurement data of the electromagnetic flowmeter through the principle of single variable, and then analyzes the influence trend and influence deviation ratio of factors such as environmental conditions, fluid properties, and electromagnetic interference on the measurement result of the electromagnetic flowmeter, which is beneficial to verifying the measured data of the electromagnetic flowmeter and improving the measurement accuracy and flow prediction ability of the electromagnetic flowmeter.

[0066] Step 4: Obtain the measured data of the electromagnetic flowmeter flow: Obtain the measured data of the conductive fluid flow measured by the electromagnetic flowmeter.

[0067] Step 5: Analyze the correction amount of the measured data of the electromagnetic flowmeter flow: Analyze the correction amount of the measured data of the conductive fluid flow measured by the electromagnetic flowmeter according to the influence information of the environmental conditions, fluid properties, and surrounding magnetic field on the measurement result of the conductive fluid flow measured by the electromagnetic flowmeter.

[0068] As a preferred solution, the specific analysis process of the said Step 5 includes: S1: Denote the influence deviation ratio of the ambient temperature of the conductive fluid flow measured by the electromagnetic flowmeter on its measurement result as k, and obtain the influence coefficient δ of the ambient temperature of the conductive fluid flow measured by the electromagnetic flowmeter on its measurement result through the analysis formula δ T = ε * k, where ε represents δ T , TFor the symbol factor, if the influence trend of the ambient temperature of the electromagnetic flowmeter measuring the flow rate of the target conductive fluid on its measurement result is on the high side, then ε = 1; if the influence trend of the ambient temperature on its measurement result is on the low side, then ε = -1.

[0069] S2: Similarly, according to the analysis method of S1, obtain the influence coefficients of the ambient humidity and pipeline pressure of the electromagnetic flowmeter measuring the flow rate of the target conductive fluid on its measurement result, and accumulate the influence coefficients of the ambient temperature, ambient humidity, and pipeline pressure of the electromagnetic flowmeter measuring the flow rate of the target conductive fluid on its measurement result to obtain the influence coefficient of the ambient conditions of the electromagnetic flowmeter measuring the flow rate of the target conductive fluid on its measurement result, and denote it as δ1.

[0070] S3: Similarly, according to the analysis methods of S1 - S2, obtain the influence coefficients of the fluid properties and the surrounding magnetic field of the electromagnetic flowmeter measuring the flow rate of the target conductive fluid on its measurement result, and denote them as δ2 and δ3 respectively.

[0071] As a preferred solution, the specific analysis process of step five further includes: obtaining the correction amount ξ of the measured data of the electromagnetic flowmeter measuring the flow rate of the target conductive fluid through the analysis formula ξ = -ξ0 * (δ1 + δ2 + δ3), where ξ0 represents the measured data of the electromagnetic flowmeter measuring the flow rate of the target conductive fluid.

[0072] Step six, prediction of the electromagnetic flowmeter flow measurement result: According to the measured data of the electromagnetic flowmeter measuring the flow rate of the target conductive fluid and the correction amount of the measured data, predict the result of the electromagnetic flowmeter measuring the flow rate of the target conductive fluid and give feedback.

[0073] As a preferred solution, the specific analysis process of step six is: Add the measured data of the electromagnetic flowmeter measuring the flow rate of the target conductive fluid and the correction amount of the measured data to obtain the result of the electromagnetic flowmeter measuring the flow rate of the target conductive fluid.

[0074] In this embodiment, the present invention takes into account the influence of environmental conditions such as temperature, humidity, and pipeline pressure on the measurement result of the electromagnetic flowmeter, the influence of fluid properties such as conductivity, impurity degree, and viscosity on the measurement result of the electromagnetic flowmeter, and the influence of the surrounding magnetic field intensity and non-uniformity on the measurement result of the electromagnetic flowmeter, further analyzes the correction amount of the measured data of the electromagnetic flowmeter, and then calibrates and corrects the measured data of the electromagnetic flowmeter, thereby improving the reliability and accuracy of the measurement result of the electromagnetic flowmeter.

[0075] The above content is only an example and explanation of the concept of the present invention. Those skilled in the art of this technology can make various modifications or supplements to the described specific embodiments or use similar methods to replace them, as long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, they should all fall within the protection scope of the present invention.

Claims

1. An electromagnetic flowmeter flow prediction method based on artificial intelligence, characterized in that, It includes the following steps: Step 1. Acquisition of measurement information of electromagnetic flowmeter affected by environmental conditions: Obtain the environmental condition information for the electromagnetic flowmeter to measure the flow rate of the target conductive fluid. The environmental condition information includes environmental temperature, environmental humidity, and pipeline pressure. Combine the historical measurement data of the electromagnetic flowmeter to construct a prediction model for the influence of environmental conditions on the measurement results of the electromagnetic flowmeter, and analyze the influence information of the environmental conditions for the electromagnetic flowmeter to measure the flow rate of the target conductive fluid on its measurement results. The influence information includes influence trend and influence deviation ratio; Step 2. Acquisition of measurement information of electromagnetic flowmeter affected by fluid properties: Obtain the fluid property information for the electromagnetic flowmeter to measure the flow rate of the target conductive fluid. The fluid property information includes the conductivity, impurity degree, and viscosity of the target conductive fluid. Combine the historical measurement data of the electromagnetic flowmeter to construct a prediction model for the influence of fluid properties on the measurement results of the electromagnetic flowmeter, and analyze the influence information of the fluid properties for the electromagnetic flowmeter to measure the flow rate of the target conductive fluid on its measurement results; Step 3. Acquisition of measurement information of electromagnetic flowmeter affected by surrounding magnetic field: Obtain the surrounding magnetic field information for the electromagnetic flowmeter to measure the flow rate of the target conductive fluid. The surrounding magnetic field information includes the intensity and non-uniformity of the surrounding magnetic field. Combine the historical measurement data of the electromagnetic flowmeter to construct a prediction model for the influence of the surrounding magnetic field on the measurement results of the electromagnetic flowmeter, and analyze the influence information of the surrounding magnetic field for the electromagnetic flowmeter to measure the flow rate of the target conductive fluid on its measurement results; Step 4. Acquisition of actual measurement data of electromagnetic flowmeter flow rate: Obtain the actual measurement data for the electromagnetic flowmeter to measure the flow rate of the target conductive fluid; Step 5. Analysis of correction amount of actual measurement data of electromagnetic flowmeter flow rate: According to the influence information of the environmental conditions, fluid properties, and surrounding magnetic field on the measurement results of the electromagnetic flowmeter for measuring the flow rate of the target conductive fluid, the influence of the environmental conditions, fluid properties, and surrounding magnetic field on the measurement results of the electromagnetic flowmeter is determined by the influence deviation ratio of the environmental conditions, fluid properties, and surrounding magnetic field of the target conductive fluid on its measurement results; Analyze the correction amount of the actual measurement data of the electromagnetic flowmeter for measuring the flow rate of the target conductive fluid; Step 6. Prediction of electromagnetic flowmeter flow measurement result: According to the actual measurement data and the correction amount of the actual measurement data of the electromagnetic flowmeter for measuring the flow rate of the target conductive fluid, predict the result of the electromagnetic flowmeter for measuring the flow rate of the target conductive fluid, and give feedback.

2. The flow prediction method of an electromagnetic flowmeter based on artificial intelligence according to claim 1, characterized in that: The specific analysis process of the said Step 1 includes: Detect the environmental temperature, environmental humidity, and pipeline pressure of the electromagnetic flowmeter for measuring the flow rate of the target conductive fluid through sensors; Extract the historical measurement data of the electromagnetic flowmeter stored in the database, delimit each range of environmental temperature according to the preset equal interval principle, and according to the single variable principle, screen the actual measurement data and standard data of the historical measurements of the electromagnetic flowmeter for the flow rate of the conductive fluid in each environmental temperature range, and obtain the difference between the actual measurement data and the standard data of the historical measurements of the electromagnetic flowmeter for the flow rate of the conductive fluid in each environmental temperature range; Obtain the absolute value of the difference between the measured data and the standard data of the historical measured flow rates of conductive fluids by the electromagnetic flowmeter at each ambient temperature range, and record it as the measurement data deviation amount of each historical measurement of the electromagnetic flowmeter at each ambient temperature range. Further, obtain the ratio between the measurement data deviation amount of each historical measurement of the electromagnetic flowmeter at each ambient temperature range and the standard data corresponding to its measurement, and use it as the measurement data deviation ratio of each historical measurement of the electromagnetic flowmeter at each ambient temperature range; Obtain the sign of the difference between the measured data and the standard data of the historical measured flow rates of conductive fluids by the electromagnetic flowmeter at each ambient temperature range. If it is a positive sign, the measured data is greater than the standard data, and at this time, the deviation direction of the measurement data measured by the electromagnetic flowmeter is on the high side. If it is a negative sign, the measured data is less than the standard data, and at this time, the deviation direction of the measurement data measured by the electromagnetic flowmeter is on the low side. Furthermore, obtain the deviation direction of the measurement data of each historical measurement of the electromagnetic flowmeter at each ambient temperature range.

3. The flow prediction method of an electromagnetic flowmeter based on artificial intelligence according to claim 2, characterized in that: The specific analysis process of the first step further includes: According to the deviation direction of the measurement data of each historical measurement of the electromagnetic flowmeter at each ambient temperature range, count the historical measurement times corresponding to each measurement data deviation direction of the electromagnetic flowmeter at each ambient temperature range, and record the measurement data deviation direction corresponding to the most historical measurement times as the influence trend of the ambient temperature of the electromagnetic flowmeter on its measurement result, where the influence trend includes on the high side and on the low side. Furthermore, obtain the influence trend of the ambient temperature of the electromagnetic flowmeter on its measurement result at each ambient temperature range.

4. The flow prediction method of an electromagnetic flowmeter based on artificial intelligence according to claim 3, wherein: The specific analysis process of the first step further includes: Establish a coordinate system with the serial number of the historical measurement times of the electromagnetic flowmeter as the abscissa and the measurement data deviation ratio as the ordinate. According to the measurement data deviation ratio of each historical measurement of the electromagnetic flowmeter at each ambient temperature range, mark the corresponding data points in the coordinate system. Using the mathematical model establishment method, draw the linear regression horizontal line corresponding to the measurement data deviation ratio of the historical measurement of the electromagnetic flowmeter at each ambient temperature range, and obtain the measurement data deviation ratio pointed to by the linear regression horizontal line corresponding to the measurement data deviation ratio of the historical measurement of the electromagnetic flowmeter at each ambient temperature range, and record it as the influence deviation ratio of the ambient temperature of the electromagnetic flowmeter on its measurement result at each ambient temperature range.

5. A flow prediction method for an electromagnetic flowmeter based on artificial intelligence according to claim 4, characterized in that: The specific analysis process of the first step further includes: According to the influence trend and influence deviation ratio of the ambient temperature of the electromagnetic flowmeter on its measurement result at each ambient temperature range, construct a prediction model for the influence of ambient temperature on the measurement result of the electromagnetic flowmeter; Substitute the ambient temperature of the electromagnetic flowmeter measuring the target conductive fluid flow rate into the prediction model for the influence of ambient temperature on the measurement result of the electromagnetic flowmeter to obtain the influence trend and influence deviation ratio of the ambient temperature of the electromagnetic flowmeter measuring the target conductive fluid flow rate on its measurement result; Similarly, according to the analysis method of the prediction model for the influence of ambient temperature on the measurement result of the electromagnetic flowmeter, obtain the prediction model for the influence of ambient humidity on the measurement result of the electromagnetic flowmeter and the prediction model for the influence of pipeline pressure on the measurement result of the electromagnetic flowmeter; Substitute the ambient humidity and pipeline pressure for measuring the flow rate of the target conductive fluid by the electromagnetic flowmeter into the prediction models of the ambient humidity affecting the measurement result of the electromagnetic flowmeter and the pipeline pressure affecting the measurement result of the electromagnetic flowmeter, and obtain the influence trends and influence deviation ratios of the ambient humidity and pipeline pressure of the electromagnetic flowmeter measuring the flow rate of the target conductive fluid on its measurement result.

6. The flow prediction method of an electromagnetic flowmeter based on artificial intelligence according to claim 4, characterized in that: The specific analysis process of step 2 is as follows: Detect the conductivity and viscosity of the target conductive fluid in the electromagnetic flowmeter measuring the flow rate of the target conductive fluid through an instrument, and obtain the ratio of the impurity volume to the fluid volume of the target conductive fluid in the electromagnetic flowmeter measuring the flow rate of the target conductive fluid, and record it as the impurity degree of the target conductive fluid in the electromagnetic flowmeter measuring the flow rate of the target conductive fluid; Extract the historical measurement data of the electromagnetic flowmeter stored in the database. According to the principle of single variable, respectively obtain the measurement data deviation ratios and measurement data deviation directions of each historical measurement of the electromagnetic flowmeter under each conductivity range, each impurity degree range, and each viscosity range of the conductive fluid, and further construct prediction models of the conductivity, impurity degree, and viscosity of the conductive fluid affecting the measurement result of the electromagnetic flowmeter. Substitute the conductivity, impurity degree, and viscosity of the target conductive fluid in the electromagnetic flowmeter measuring the flow rate of the target conductive fluid, and obtain the influence trends and influence deviation ratios of the conductivity, impurity degree, and viscosity of the target conductive fluid in the electromagnetic flowmeter measuring the flow rate of the target conductive fluid on its measurement result.

7. A flow prediction method for an electromagnetic flowmeter based on artificial intelligence according to claim 4, characterized in that: The specific analysis process of step 3 is as follows: Detect the intensity of the magnetic field around the electromagnetic flowmeter measuring the flow rate of the target conductive fluid through an instrument, and obtain the non-uniformity of the surrounding magnetic field; Extract the historical measurement data of the electromagnetic flowmeter stored in the database. According to the principle of single variable, respectively obtain the measurement data deviation ratios and measurement data deviation directions of each historical measurement of the electromagnetic flowmeter under each intensity range and each non-uniformity range of the surrounding magnetic field, and further construct prediction models of the intensity and non-uniformity of the surrounding magnetic field affecting the measurement result of the electromagnetic flowmeter. Substitute the intensity and non-uniformity of the magnetic field around the electromagnetic flowmeter measuring the flow rate of the target conductive fluid, and obtain the influence trends and influence deviation ratios of the intensity and non-uniformity of the magnetic field around the electromagnetic flowmeter measuring the flow rate of the target conductive fluid on its measurement result.

8. A flow prediction method for an electromagnetic flowmeter based on artificial intelligence according to claim 1, characterized in that: The specific analysis process of step 5 includes: S1: Denote the influence deviation ratio of the ambient temperature of the electromagnetic flowmeter measuring the flow rate of the target conductive fluid on its measurement result as k. By analyzing the formula δ T = ε * k, obtain the influence coefficient δ of the ambient temperature of the electromagnetic flowmeter measuring the flow rate of the target conductive fluid on its measurement result T , where ε represents the sign factor of δ T . If the influence trend of the ambient temperature of the electromagnetic flowmeter measuring the flow rate of the target conductive fluid on its measurement result is on the high side, then ε = 1; if the influence trend of the ambient temperature on its measurement result is on the low side, then ε = -1. S2: Similarly, according to the analysis method of S1, obtain the influence coefficients of the ambient humidity and pipeline pressure of the electromagnetic flowmeter measuring the flow rate of the target conductive fluid on its measurement result, and accumulate the influence coefficients of the ambient temperature, ambient humidity, and pipeline pressure of the electromagnetic flowmeter measuring the flow rate of the target conductive fluid on its measurement result to obtain the influence coefficient of the ambient conditions of the electromagnetic flowmeter measuring the flow rate of the target conductive fluid on its measurement result, and record it as δ1; S3: Similarly, according to the analysis methods of S1-S2, obtain the influence coefficients of the fluid properties and the surrounding magnetic field of the electromagnetic flowmeter measuring the flow rate of the target conductive fluid on its measurement result, and record them as δ2 and δ3 respectively.

9. The flow prediction method of an electromagnetic flowmeter based on artificial intelligence according to claim 8, characterized in that: The specific analysis process of step 5 also includes: The correction amount ξ of the measured data of the electromagnetic flowmeter for measuring the flow rate of the target conductive fluid is obtained by analyzing the formula ξ = -ξ0 * (δ1 + δ2 + δ3), where ξ0 represents the measured data of the electromagnetic flowmeter for measuring the flow rate of the target conductive fluid.

10. A flow prediction method for an electromagnetic flowmeter based on artificial intelligence according to claim 1, characterized in that: The specific analysis process of step six is as follows: Add the measured data of the electromagnetic flowmeter for measuring the flow rate of the target conductive fluid and the correction amount of the measured data to obtain the result of the electromagnetic flowmeter for measuring the flow rate of the target conductive fluid.

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