Electromagnetic flowmeter flow prediction method based on artificial intelligence

Abstract

The invention relates to the field of flow measurement of electromagnetic flow meters, and particularly discloses an artificial intelligence-based flow prediction method of an electromagnetic flow meter, which comprises the following steps of: analyzing the influence of environmental conditions on a measurement result by acquiring environmental condition information of the electromagnetic flow meter for measuring the flow of a conductive fluid; obtaining fluid property information of the electromagnetic flowmeter for measuring the flow of the conductive fluid, analyzing the influence of the fluid property on a measurement result, obtaining surrounding magnetic field information of the electromagnetic flowmeter for measuring the flow of the conductive fluid, and analyzing the influence of a surrounding magnetic field on the measurement result; the correction amount of the measured data of the electromagnetic flowmeter for measuring the flow of the conductive fluid is further analyzed, the result of the electromagnetic flowmeter for measuring the flow of the conductive fluid is predicted, the influence of factors such as environmental conditions, fluid properties and electromagnetic interference on the measurement of the electromagnetic flowmeter is considered, and then the measured data of the electromagnetic flowmeter are calibrated and rectified. Therefore, the reliability and precision of the measurement result of the electromagnetic flowmeter are improved.

Description

Technical Field

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

[0002] With the continuous development of industrial automation, electromagnetic flowmeter, as a key instrument for measuring the flow of conductive fluids, is widely used in various industries. Electromagnetic flowmeter works 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 flowmeter uses this principle to measure the velocity of the fluid and then calculate the flow rate.

[0003] However, the existing electromagnetic flowmeter technology for measuring conductive fluid flow still has some limitations and shortcomings in practical applications.

[0004] For example, the existing Chinese patent with publication number CN103063276A discloses an electromagnetic flowmeter calibration system, including an industrial computer, a standard table, a calibration module and a calibration module, wherein the calibration module and the calibration module are built into the industrial computer; the calibration module is built with an identity authentication module, a display module and a control module; and the calibration module is built with a data processing module. The invention reduces the difficulty and complexity of operation as much as possible, and various parameters and data can be intuitively displayed on a graphical interface. The data collection and calculation of each flow point are completed by the program itself, and the operator does not need to intervene in the data processing part, which improves the reliability of calibration and calibration operations and improves work efficiency, thereby overcoming the problems of the electromagnetic flowmeter calibration method, such as high difficulty in operation, high complexity, low reliability of the calibration structure and low calibration efficiency.

[0005] However, the above patent does not take into account the influence of environmental conditions, fluid properties and electromagnetic interference on the measurement of the electromagnetic flowmeter, which limits the measurement accuracy of the electromagnetic flowmeter and reduces the accuracy of the measurement results of the electromagnetic flowmeter. Summary of the invention

[0006] In response to the above problems, the present invention proposes an electromagnetic flowmeter flow prediction method based on artificial intelligence. The specific technical scheme is as follows: An electromagnetic flowmeter flow prediction method based on artificial intelligence, comprising the following steps: Step 1, acquisition of environmental conditions affecting electromagnetic flowmeter measurement information: Acquire environmental condition information of the electromagnetic flowmeter measuring the target conductive fluid flow, wherein the environmental condition information includes ambient temperature, ambient humidity, and pipeline pressure, and combine the historical measurement data of the electromagnetic flowmeter to construct a prediction model of the impact of environmental conditions on the measurement results of the electromagnetic flowmeter, and analyze the impact of environmental conditions on the electromagnetic flowmeter measuring the target conductive fluid flow on its measurement results, wherein the impact information includes the impact trend and the impact deviation ratio.

[0007] Step 2. Obtaining information on the impact of fluid properties on electromagnetic flowmeter measurement: Obtain fluid property information of the electromagnetic flowmeter measuring the target conductive fluid flow rate, where the fluid property information includes the conductivity, impurity level, and viscosity of the target conductive fluid. Combined with the historical measurement data of the electromagnetic flowmeter, a prediction model for the impact of fluid properties on the electromagnetic flowmeter's measurement results is constructed, and the impact of fluid properties on the electromagnetic flowmeter's measurement results of the target conductive fluid flow rate is analyzed.

[0008] Step 3. Obtaining the information about the influence of the surrounding magnetic field on the electromagnetic flowmeter measurement: Obtain the surrounding magnetic field information of the electromagnetic flowmeter measuring the target conductive fluid flow rate, where the surrounding magnetic field information includes the strength and unevenness of the surrounding magnetic field, and combine it with the historical measurement data of the electromagnetic flowmeter to build a prediction model of the influence of the surrounding magnetic field on the electromagnetic flowmeter's measurement results, and analyze the influence of the surrounding magnetic field on the electromagnetic flowmeter's measurement results of the target conductive fluid flow rate.

[0009] Step 4: Acquisition of actual measured flow data of the electromagnetic flowmeter: Acquisition of actual measured data of the electromagnetic flowmeter measuring the flow rate of the target conductive fluid.

[0010] Step 5. Analysis of corrections to the electromagnetic flowmeter's measured flow data: Based on the environmental conditions, fluid properties, and information on the impact of the surrounding magnetic field on the electromagnetic flowmeter's measurement of the target conductive fluid flow rate, analyze the corrections to the electromagnetic flowmeter's measured flow data for the target conductive fluid flow rate.

[0011] Step 6: Predicting the flow measurement results of the electromagnetic flowmeter: Based on the actual measured data of the target conductive fluid flow measured by the electromagnetic flowmeter and the correction amount of the actual measured data, predict the result of the electromagnetic flowmeter measuring the target conductive fluid flow and provide feedback.

[0012] Based on the above embodiment, the specific analysis process of step one includes: detecting the ambient temperature, ambient humidity, and pipeline pressure of the target conductive fluid flow measured by the electromagnetic flowmeter through a sensor.

[0013] The historical measurement data of the electromagnetic flowmeter stored in the database are extracted, and the various ranges of ambient temperature are delineated according to the preset equal interval principle. Based on the single variable principle, the measured data and standard data of the electromagnetic flowmeter's historical measurements of the conductive fluid flow rate under each ambient temperature range are screened, and the difference between the measured data and the standard data of the electromagnetic flowmeter's historical measurements of the conductive fluid flow rate under each ambient temperature range is obtained.

[0014] The absolute value of the difference between the actual measured data and the standard data of the conductive fluid flow rate of the electromagnetic flowmeter in each historical measurement under each ambient temperature range is obtained, and the difference is recorded as the measurement data deviation of the electromagnetic flowmeter in each historical measurement under each ambient temperature range. The ratio between the measurement data deviation of the electromagnetic flowmeter in each historical measurement under each ambient temperature range and the standard data corresponding to the measurement is further obtained, and the difference is used as the measurement data deviation ratio of the electromagnetic flowmeter in each historical measurement under each ambient temperature range.

[0015] The difference sign between the actual data and the standard data of the electromagnetic flowmeter for each historical measurement of the conductive fluid flow rate under each ambient temperature range is obtained. If it is a positive sign, the actual data is greater than the standard data. At this time, the deviation direction of the measurement data measured by the electromagnetic flowmeter is too large. If it is a negative sign, the actual data is less than the standard data. At this time, the deviation direction of the measurement data measured by the electromagnetic flowmeter is too small, and then the deviation direction of the measurement data of each historical measurement of the electromagnetic flowmeter under each ambient temperature range is obtained.

[0016] On the basis of the above embodiment, the specific analysis process of step one also includes: according to the measurement data deviation direction of each historical measurement of the electromagnetic flowmeter under each ambient temperature range, the historical measurement times corresponding to each measurement data deviation direction of the electromagnetic flowmeter under each ambient temperature range are counted, and the measurement data deviation direction corresponding to the largest number of historical measurements is recorded as the influence trend of the ambient temperature measured by the electromagnetic flowmeter on its measurement result, wherein the influence trend includes being too large and too small, thereby obtaining the influence trend of the ambient temperature measured by the electromagnetic flowmeter on its measurement result under each ambient temperature range.

[0017] On the basis of the above embodiment, the specific analysis process of step one also includes: establishing a coordinate system with the number of historical measurement times of the electromagnetic flowmeter as the horizontal coordinate and the measurement data deviation ratio as the vertical coordinate, marking the corresponding data points in the coordinate system according to the measurement data deviation ratio of each historical measurement of the electromagnetic flowmeter under each ambient temperature range, and using the mathematical model establishment method to draw a linear regression horizontal line corresponding to the historical measurement data deviation ratio of the electromagnetic flowmeter under each ambient temperature range, and obtaining the measurement data deviation ratio pointed to by the linear regression horizontal line corresponding to the historical measurement data deviation ratio of the electromagnetic flowmeter under each ambient temperature range, and recording it as the deviation ratio of the influence of the ambient temperature of the electromagnetic flowmeter measurement on its measurement result under each ambient temperature range.

[0018] Based on the above embodiment, the specific analysis process of step one also includes: constructing a prediction model of the impact of ambient temperature on the measurement results of the electromagnetic flowmeter according to the impact trend and impact deviation ratio of the ambient temperature on the measurement results of the electromagnetic flowmeter under each ambient temperature range.

[0019] The ambient temperature of the target conductive fluid flow measured by the electromagnetic flowmeter is substituted into the prediction model of the ambient temperature affecting the measurement result of the electromagnetic flowmeter, and the influence trend and influence deviation ratio of the ambient temperature of the target conductive fluid flow measured by the electromagnetic flowmeter on the measurement result are obtained.

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

[0021] The ambient humidity and pipeline pressure of the target conductive fluid flow measured by the electromagnetic flowmeter are substituted into the prediction model of the influence of ambient humidity on the measurement results of the electromagnetic flowmeter and the prediction model of the influence of pipeline pressure on the measurement results of the electromagnetic flowmeter, respectively, to obtain the influence trend and influence deviation ratio of the ambient humidity and pipeline pressure on the measurement results of the target conductive fluid flow measured by the electromagnetic flowmeter.

[0022] Based on the above embodiment, the specific analysis process of step two is: the conductivity and viscosity of the target conductive fluid in the target conductive fluid flow are measured by the electromagnetic flowmeter through instrument detection, and the ratio of the impurity volume to the fluid volume of the target conductive fluid in the target conductive fluid flow measured by the electromagnetic flowmeter is obtained, and it is recorded as the impurity degree of the target conductive fluid in the target conductive fluid flow measured by the electromagnetic flowmeter.

[0023] 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 conductivity range, each impurity range, and each viscosity range of the conductive fluid are obtained respectively. A prediction model for the impact of the conductivity, impurity and viscosity of the conductive fluid on the measurement results of the electromagnetic flowmeter is further constructed. The conductivity, impurity and viscosity of the target conductive fluid in the target conductive fluid flow measured by the electromagnetic flowmeter are substituted, and the influence trend and impact deviation ratio of the conductivity, impurity and viscosity of the target conductive fluid in the target conductive fluid flow measured by the electromagnetic flowmeter are obtained.

[0024] Based on the above embodiment, the specific analysis process of step three is: measuring the strength of the magnetic field around the target conductive fluid flow through an instrument detection electromagnetic flowmeter, and obtaining the unevenness 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 described in 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 impact of environmental conditions, fluid properties, electromagnetic interference and other factors on the measurement results of the electromagnetic flowmeter through the single variable principle, and then analyzes the impact trend and impact deviation ratio of factors such as environmental conditions, fluid properties and electromagnetic interference on the measurement results of the electromagnetic flowmeter, which is conducive to the calibration of the actual measured data of the electromagnetic flowmeter and improves 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 level, and viscosity on the measurement results of the electromagnetic flowmeter, and the influence of the surrounding magnetic field strength and unevenness on the measurement results of the electromagnetic flowmeter, and further analyzes the correction amount of the electromagnetic flowmeter's measured data, and then calibrates and corrects the electromagnetic flowmeter's measured data, thereby improving the reliability and accuracy of the electromagnetic flowmeter's measurement results. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

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

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

[0036] Figure numerals: 1. Number of historical measurements of the electromagnetic flowmeter; 2. Deviation ratio of measurement data; 3. Incorrect data points; 4. Linear regression horizontal line. DETAILED DESCRIPTION

[0037] 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.

[0038] See also Figure 1As shown, the present invention provides an electromagnetic flowmeter flow prediction method based on artificial intelligence, comprising the following steps: Step 1, acquisition of measurement information of the electromagnetic flowmeter affected by environmental conditions: obtaining environmental condition information of the electromagnetic flowmeter measuring the target conductive fluid flow, wherein the environmental condition information includes ambient temperature, ambient humidity, and pipeline pressure, and combining the historical measurement data of the electromagnetic flowmeter, constructing a prediction model of the environmental conditions affecting the measurement results of the electromagnetic flowmeter, analyzing the influence of the environmental conditions of the electromagnetic flowmeter measuring the target conductive fluid flow on its measurement results, wherein the influence information includes the influence trend and the influence deviation ratio.

[0039] As a preferred solution, the specific analysis process of step one includes: detecting the ambient temperature, ambient humidity, and pipeline pressure of the target conductive fluid flow measured by the electromagnetic flowmeter through a sensor.

[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 will change with the change of temperature, which directly affects the magnitude of the generated electromotive force, and then affects the conductivity of the conductive fluid. In addition, temperature changes may cause the pipeline to expand or contract, which in turn affects the flow characteristics of the conductive fluid, thereby reducing the measurement accuracy of the conductive fluid flow.

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

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

[0044] The historical measurement data of the electromagnetic flowmeter stored in the database are extracted, and the various ranges of ambient temperature are delineated according to the preset equal interval principle. Based on the single variable principle, the measured data and standard data of the electromagnetic flowmeter's historical measurements of the conductive fluid flow rate under each ambient temperature range are screened, and the difference between the measured data and the standard data of the electromagnetic flowmeter's historical measurements of the conductive fluid flow rate under each ambient temperature range is obtained.

[0045] The absolute value of the difference between the actual measured data and the standard data of the conductive fluid flow rate of the electromagnetic flowmeter in each historical measurement under each ambient temperature range is obtained, and the difference is recorded as the measurement data deviation of the electromagnetic flowmeter in each historical measurement under each ambient temperature range. The ratio between the measurement data deviation of the electromagnetic flowmeter in each historical measurement under each ambient temperature range and the standard data corresponding to the measurement is further obtained, and the difference is used as the measurement data deviation ratio of the electromagnetic flowmeter in each historical measurement under each ambient temperature range.

[0046] The difference sign between the actual data and the standard data of the electromagnetic flowmeter for each historical measurement of the conductive fluid flow rate under each ambient temperature range is obtained. If it is a positive sign, the actual data is greater than the standard data. At this time, the deviation direction of the measurement data measured by the electromagnetic flowmeter is too large. If it is a negative sign, the actual data is less than the standard data. At this time, the deviation direction of the measurement data measured by the electromagnetic flowmeter is too small, and then the deviation direction of the measurement data of each historical measurement of the electromagnetic flowmeter under each ambient temperature range is obtained.

[0047] As a preferred scheme, the specific analysis process of step one also includes: according to the measurement data deviation direction of each historical measurement of the electromagnetic flowmeter under each ambient temperature range, the historical measurement times corresponding to each measurement data deviation direction of the electromagnetic flowmeter under each ambient temperature range are counted, and the measurement data deviation direction corresponding to the largest number of historical measurements is recorded as the influence trend of the ambient temperature measured by the electromagnetic flowmeter on its measurement results, wherein the influence trend includes being too large and too small, thereby obtaining the influence trend of the ambient temperature measured by the electromagnetic flowmeter on its measurement results under each ambient temperature range.

[0048] As a preferred solution, the specific analysis process of step 1 also includes: Figure 2 As shown, a coordinate system is established with the number of historical measurement times of the electromagnetic flowmeter as the horizontal coordinate and the measurement data deviation ratio as the vertical coordinate. According to the measurement data deviation ratio of each historical measurement of the electromagnetic flowmeter under each ambient temperature range, the corresponding data points are marked in the coordinate system. The mathematical model establishment method is used to draw a linear regression horizontal line corresponding to the deviation ratio of the historical measurement data of the electromagnetic flowmeter under each ambient temperature range, and the measurement data deviation ratio pointed to by the linear regression horizontal line corresponding to the deviation ratio of the historical measurement data of the electromagnetic flowmeter under each ambient temperature range is obtained, and it is recorded as the deviation ratio of the influence of the ambient temperature of the electromagnetic flowmeter measurement on its measurement result under each ambient temperature range.

[0049] It should be noted that when drawing the linear regression horizontal line corresponding to the deviation ratio of the electromagnetic flowmeter's historical measurement data under each ambient temperature range, the erroneous data points will be eliminated before analysis.

[0050] As a preferred solution, the specific analysis process of step one also includes: constructing a prediction model of the impact of ambient temperature on the measurement results of the electromagnetic flowmeter according to the impact trend and impact deviation ratio of the ambient temperature on the measurement results of the electromagnetic flowmeter under each ambient temperature range.

[0051] The ambient temperature of the target conductive fluid flow measured by the electromagnetic flowmeter is substituted into the prediction model of the ambient temperature affecting the measurement result of the electromagnetic flowmeter, and the influence trend and influence deviation ratio of the ambient temperature of the target conductive fluid flow measured by the electromagnetic flowmeter on the measurement result are obtained.

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

[0053] The ambient humidity and pipeline pressure of the target conductive fluid flow measured by the electromagnetic flowmeter are substituted into the prediction model of the influence of ambient humidity on the measurement results of the electromagnetic flowmeter and the prediction model of the influence of pipeline pressure on the measurement results of the electromagnetic flowmeter, respectively, to obtain the influence trend and influence deviation ratio of the ambient humidity and pipeline pressure on the measurement results of the target conductive fluid flow measured by the electromagnetic flowmeter.

[0054] Step 2. Obtaining information on the impact of fluid properties on electromagnetic flowmeter measurement: Obtain fluid property information of the electromagnetic flowmeter measuring the target conductive fluid flow rate, where the fluid property information includes the conductivity, impurity level, and viscosity of the target conductive fluid. Combined with the historical measurement data of the electromagnetic flowmeter, a prediction model for the impact of fluid properties on the electromagnetic flowmeter's measurement results is constructed, and the impact of fluid properties on the electromagnetic flowmeter's measurement results of the target conductive fluid flow rate is analyzed.

[0055] As a preferred solution, the specific analysis process of step two is: using an instrument to detect the conductivity and viscosity of the target conductive fluid in the target conductive fluid flow measured by the electromagnetic flowmeter, and obtaining the ratio of the impurity volume to the fluid volume of the target conductive fluid in the target conductive fluid flow measured by the electromagnetic flowmeter, and recording it as the impurity degree of the target conductive fluid in the target conductive fluid flow measured by the electromagnetic flowmeter.

[0056] 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 conductivity range, each impurity range, and each viscosity range of the conductive fluid are obtained respectively. A prediction model for the impact of the conductivity, impurity and viscosity of the conductive fluid on the measurement results of the electromagnetic flowmeter is further constructed. The conductivity, impurity and viscosity of the target conductive fluid in the target conductive fluid flow measured by the electromagnetic flowmeter are substituted, and the influence trend and impact deviation ratio of the conductivity, impurity and viscosity of the target conductive fluid in the target conductive fluid flow measured by the electromagnetic flowmeter are obtained.

[0057] It should be noted that the method of constructing a prediction model for the impact of conductive fluid conductivity on the measurement results of the electromagnetic flowmeter, the prediction model for the impact of conductive fluid impurity on the measurement results of the electromagnetic flowmeter, and the prediction model for the impact of conductive fluid viscosity on the measurement results of the electromagnetic flowmeter has the same principle as the method of constructing a prediction model for the impact of ambient temperature on the measurement results of the electromagnetic flowmeter.

[0058] It should be noted that the method for obtaining the influence trend and deviation ratio of the conductivity, impurity content and viscosity of the target conductive fluid on the measurement result when the electromagnetic flowmeter measures the target conductive fluid flow rate is the same as the method for obtaining the influence trend and deviation ratio of the ambient temperature on the measurement result when the electromagnetic flowmeter measures the target conductive fluid flow rate.

[0059] Step 3. Obtaining the information about the influence of the surrounding magnetic field on the electromagnetic flowmeter measurement: Obtain the surrounding magnetic field information of the electromagnetic flowmeter measuring the target conductive fluid flow rate, where the surrounding magnetic field information includes the strength and unevenness of the surrounding magnetic field, and combine it with the historical measurement data of the electromagnetic flowmeter to build a prediction model of the influence of the surrounding magnetic field on the electromagnetic flowmeter's measurement results, and analyze the influence of the surrounding magnetic field on the electromagnetic flowmeter's measurement results of the target conductive fluid flow rate.

[0060] As a preferred solution, the specific analysis process of step three is: measuring the strength of the magnetic field around the target conductive fluid flow through an instrument detection electromagnetic flowmeter, and obtaining the unevenness of the surrounding magnetic field.

[0061] It should be noted that the specific method for obtaining the inhomogeneity of the surrounding magnetic field is as follows: the surrounding area is divided according to a preset principle to obtain surrounding sub-areas, the magnetic field strength of each surrounding sub-area is obtained, the maximum fluctuation of the magnetic field strength between the surrounding sub-areas is analyzed, and the maximum fluctuation is substituted into the relationship function between the preset magnetic field strength fluctuation and the magnetic field inhomogeneity to obtain the inhomogeneity of the surrounding magnetic field.

[0062] 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.

[0063] It should be noted that the method of constructing a prediction model for the impact of ambient magnetic field strength on the measurement results of the electromagnetic flowmeter, the method of constructing a prediction model for the impact of cyclic magnetic field non-uniformity on the measurement results of the electromagnetic flowmeter, and the method of constructing a prediction model for the impact of ambient temperature on the measurement results of the electromagnetic flowmeter have the same principle.

[0064] It should be noted that the method for obtaining the influence trend and deviation ratio of the strength and unevenness of the magnetic field around the target conductive fluid flow measured by the electromagnetic flowmeter and the method for obtaining the influence trend and deviation ratio of the ambient temperature on the measurement results when the electromagnetic flowmeter measures the target conductive fluid flow have the same principle.

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

[0066] Step 4: Acquisition of actual measured flow data of the electromagnetic flowmeter: Acquisition of actual measured data of the electromagnetic flowmeter measuring the flow rate of the target conductive fluid.

[0067] Step 5. Analysis of corrections to the electromagnetic flowmeter's measured flow data: Based on the environmental conditions, fluid properties, and information on the impact of the surrounding magnetic field on the electromagnetic flowmeter's measurement of the target conductive fluid flow rate, analyze the corrections to the electromagnetic flowmeter's measured flow data for the target conductive fluid flow rate.

[0068] As a preferred solution, the specific analysis process of step 5 includes: S1: the influence ratio of the ambient temperature of the electromagnetic flowmeter on the measurement result of the target conductive fluid flow 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 TThe 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.

[0069] 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.

[0070] 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.

[0071] As a preferred solution, 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.

[0072] Step 6: Predicting the flow measurement results of the electromagnetic flowmeter: Based on the actual measured data of the target conductive fluid flow measured by the electromagnetic flowmeter and the correction amount of the actual measured data, predict the result of the electromagnetic flowmeter measuring the target conductive fluid flow and provide feedback.

[0073] As a preferred solution, 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.

[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 results of the electromagnetic flowmeter, the influence of fluid properties such as conductivity, impurity, and viscosity on the measurement results of the electromagnetic flowmeter, and the influence of the surrounding magnetic field strength and unevenness on the measurement results of the electromagnetic flowmeter, and further analyzes the correction amount of the electromagnetic flowmeter's measured data, and then calibrates and corrects the electromagnetic flowmeter's measured data, thereby improving the reliability and accuracy of the electromagnetic flowmeter's measurement results.

[0075] The above contents are merely examples and explanations of the concept of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, they shall all fall within the protection scope of the present invention.

Claims

1. A method for predicting flow rate of electromagnetic flowmeter based on artificial intelligence, characterized in that: The steps include: Step 1: Obtaining the information about the environmental conditions affecting the electromagnetic flowmeter measurement: Obtain the environmental condition information about the electromagnetic flowmeter measuring the target conductive fluid flow rate, where the environmental condition information includes the ambient temperature, ambient humidity, and pipeline pressure, and build a prediction model of the environmental conditions affecting the electromagnetic flowmeter measurement results in combination with the historical measurement data of the electromagnetic flowmeter, and analyze the influence of the environmental conditions on the electromagnetic flowmeter measuring the target conductive fluid flow rate on its measurement results, where the influence information includes the influence trend and the influence deviation ratio; Step 2, the influence of fluid properties on the electromagnetic flowmeter measurement information acquisition: obtain the fluid property information of the electromagnetic flowmeter measuring the flow rate of the target conductive fluid, wherein the fluid property information includes the conductivity, impurity degree and viscosity of the target conductive fluid, and construct a prediction model of the influence of fluid properties on the measurement results of the electromagnetic flowmeter in combination with the historical measurement data of the electromagnetic flowmeter, and analyze the influence of fluid properties on the measurement results of the electromagnetic flowmeter measuring the flow rate of the target conductive fluid; Step 3, acquisition of information about the effect of the surrounding magnetic field on the electromagnetic flowmeter measurement: obtain the surrounding magnetic field information of the electromagnetic flowmeter measuring the target conductive fluid flow rate, wherein the surrounding magnetic field information includes the strength and unevenness of the surrounding magnetic field, and combine the historical measurement data of the electromagnetic flowmeter to build a prediction model of the effect of the surrounding magnetic field on the electromagnetic flowmeter measurement results, and analyze the effect of the surrounding magnetic field on the measurement results of the electromagnetic flowmeter measuring the target conductive fluid flow rate; Step 4: Acquisition of measured flow data of the electromagnetic flowmeter: Acquisition of measured data of the electromagnetic flowmeter measuring the flow rate of the target conductive fluid; Step 5: Analysis of correction amount of electromagnetic flowmeter flow measurement data: Based on the environmental conditions, fluid properties, and the influence of the surrounding magnetic field on the measurement results of the target conductive fluid flow measured by the electromagnetic flowmeter, the correction amount of the electromagnetic flowmeter's measured flow data of the target conductive fluid flow is analyzed; Step 6: Predicting the flow measurement results of the electromagnetic flowmeter: Based on the actual measured data of the target conductive fluid flow measured by the electromagnetic flowmeter and the correction amount of the actual measured data, predict the result of the electromagnetic flowmeter measuring the target conductive fluid flow and provide feedback.

2. The electromagnetic flowmeter flow prediction method based on artificial intelligence according to claim 1 is characterized in that: The specific analysis process of step 1 includes: The electromagnetic flowmeter measures the ambient temperature, ambient humidity, and pipeline pressure of the target conductive fluid flow rate through sensors; Extract the historical measurement data of the electromagnetic flowmeter stored in the database, delineate the ranges of ambient temperature according to the preset equal interval principle, and screen the actual measured data and standard data of the electromagnetic flowmeter's historical measurements of the conductive fluid flow rate under each ambient temperature range according to the single variable principle, and obtain the difference between the actual measured data and standard data of the electromagnetic flowmeter's historical measurements of the conductive fluid flow rate under each ambient temperature range; Obtain the absolute value of the difference between the actual measured data and the standard data of the flow rate of the conductive fluid measured by the electromagnetic flowmeter in each historical measurement under each ambient temperature range, and record it as the measurement data deviation of each historical measurement of the electromagnetic flowmeter under each ambient temperature range, and further obtain the ratio between the measurement data deviation of each historical measurement of the electromagnetic flowmeter under each ambient temperature range and the standard data corresponding to the measurement, and use it as the measurement data deviation ratio of each historical measurement of the electromagnetic flowmeter under each ambient temperature range; The difference sign between the actual data and the standard data of the electromagnetic flowmeter for each historical measurement of the conductive fluid flow rate under each ambient temperature range is obtained. If it is a positive sign, the actual data is greater than the standard data. At this time, the deviation direction of the measurement data measured by the electromagnetic flowmeter is too large. If it is a negative sign, the actual data is less than the standard data. At this time, the deviation direction of the measurement data measured by the electromagnetic flowmeter is too small, and then the deviation direction of the measurement data of each historical measurement of the electromagnetic flowmeter under each ambient temperature range is obtained.

3. The electromagnetic flowmeter flow prediction method based on artificial intelligence according to claim 2 is characterized in that: The specific analysis process of step 1 also includes: According to the deviation direction of the measurement data of each historical measurement of the electromagnetic flowmeter under each ambient temperature range, the historical measurement times corresponding to each measurement data deviation direction of the electromagnetic flowmeter under each ambient temperature range are counted, and the measurement data deviation direction corresponding to the largest number of historical measurements is recorded as the influence trend of the ambient temperature measured by the electromagnetic flowmeter on its measurement results, where the influence trend includes too large and too small, thereby obtaining the influence trend of the ambient temperature measured by the electromagnetic flowmeter on its measurement results under each ambient temperature range.

4. The electromagnetic flowmeter flow prediction method based on artificial intelligence according to claim 3 is characterized in that: The specific analysis process of step 1 also includes: A coordinate system is established with the number of historical measurements of the electromagnetic flowmeter as the horizontal axis and the measurement data deviation ratio as the vertical axis. According to the measurement data deviation ratio of each historical measurement of the electromagnetic flowmeter under each ambient temperature range, the corresponding data points are marked in the coordinate system. The mathematical model establishment method is used to draw a linear regression horizontal line corresponding to the deviation ratio of the historical measurement data of the electromagnetic flowmeter under each ambient temperature range, and the measurement data deviation ratio pointed to by the linear regression horizontal line corresponding to the deviation ratio of the historical measurement data of the electromagnetic flowmeter under each ambient temperature range is obtained. It is recorded as the deviation ratio of the influence of the ambient temperature of the electromagnetic flowmeter measurement on its measurement result under each ambient temperature range.

5. The electromagnetic flowmeter flow prediction method based on artificial intelligence according to claim 4 is characterized in that: The specific analysis process of step 1 also includes: According to the influence trend and influence deviation ratio of the ambient temperature of the electromagnetic flowmeter on its measurement results under various ambient temperature ranges, a prediction model of the influence of ambient temperature on the measurement results of the electromagnetic flowmeter is constructed; Substituting the ambient temperature of the target conductive fluid flow measured by the electromagnetic flowmeter into the prediction model of the influence of the ambient temperature on the measurement result of the electromagnetic flowmeter, the influence trend and influence deviation ratio of the ambient temperature of the target conductive fluid flow measured by the electromagnetic flowmeter on the measurement result are obtained; Similarly, according to the analysis method of the prediction model of the effect of ambient temperature on the measurement result of the electromagnetic flowmeter, the prediction model of the effect of ambient humidity on the measurement result of the electromagnetic flowmeter and the prediction model of the effect of pipeline pressure on the measurement result of the electromagnetic flowmeter are obtained; The ambient humidity and pipeline pressure of the target conductive fluid flow measured by the electromagnetic flowmeter are substituted into the prediction model of the influence of ambient humidity on the measurement results of the electromagnetic flowmeter and the prediction model of the influence of pipeline pressure on the measurement results of the electromagnetic flowmeter, respectively, to obtain the influence trend and influence deviation ratio of the ambient humidity and pipeline pressure on the measurement results of the target conductive fluid flow measured by the electromagnetic flowmeter.

6. The electromagnetic flowmeter flow prediction method based on artificial intelligence according to claim 4 is characterized in that: The specific analysis process of step 2 is as follows: The conductivity and viscosity of the target conductive fluid in the target conductive fluid flow rate are measured by an electromagnetic flowmeter through instrument detection, and the ratio of the impurity volume to the fluid volume of the target conductive fluid in the target conductive fluid flow rate measured by the electromagnetic flowmeter is obtained, and recorded as the impurity degree of the target conductive fluid in the target conductive fluid flow rate measured by the electromagnetic flowmeter; 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 conductivity range, each impurity range, and each viscosity range of the conductive fluid are obtained respectively. A prediction model for the impact of the conductivity, impurity and viscosity of the conductive fluid on the measurement results of the electromagnetic flowmeter is further constructed. The conductivity, impurity and viscosity of the target conductive fluid in the target conductive fluid flow measured by the electromagnetic flowmeter are substituted, and the influence trend and impact deviation ratio of the conductivity, impurity and viscosity of the target conductive fluid in the target conductive fluid flow measured by the electromagnetic flowmeter are obtained.

7. The method for predicting flow rate of electromagnetic flowmeter based on artificial intelligence according to claim 4 is characterized in that: The specific analysis process of step three is as follows: The electromagnetic flowmeter is used to measure the strength of the magnetic field around the target conductive fluid flow and obtain the unevenness of the surrounding magnetic field; 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.

8. The electromagnetic flowmeter flow prediction method based on artificial intelligence according to claim 1 is characterized by: The specific analysis process of step 5 includes: S1: The influence 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 deviation ratio is calculated by analyzing the 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 large, then ε = 1; if the influence of the ambient temperature on the measurement result is small, then ε = -1; S2: Similarly, according to the analysis method of S1, the influence coefficient of the ambient humidity and pipeline pressure on the measurement result of the electromagnetic flowmeter measuring the target conductive fluid flow is obtained, and the influence coefficient of the ambient temperature, ambient humidity, and pipeline pressure on the measurement result of the electromagnetic flowmeter measuring the target conductive fluid flow is accumulated to obtain the influence coefficient of the environmental conditions on the measurement result of the electromagnetic flowmeter measuring the target conductive fluid flow, which is recorded as δ1; 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.

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

10. The electromagnetic flowmeter flow prediction method based on artificial intelligence according to claim 1 is characterized in that: The specific analysis process of step six is ​​as follows: The actual measured data of the target conductive fluid flow measured by the electromagnetic flowmeter and the correction amount of the actual measured data are added to obtain the result of the target conductive fluid flow measured by the electromagnetic flowmeter.

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