Rotor flow meter and flow measurement method and system based on filtering algorithm

Abstract

The invention provides a rotor flow meter and a flow measuring method and system based on a filtering algorithm, and relates to the field of flow measuration.The rotor flow meter comprises a flow sensing device, the flow sensing device comprises a conical pipe with an upward flaring, and a rotor is arranged in the conical pipe; the rotor floats in the length direction of the conical pipe under the action of fluid, and a magnet is mounted on the rotor; the magnetic field sensing device is arranged on the flow sensing device and is used for collecting real-time magnetic field data; the environment sensing device is used for collecting real-time environment data; the flow correction device is used for determining a real-time magnet angle value based on the real-time magnetic field data and the real-time environment data and determining the real-time fluid flow based on the real-time magnet angle value, and the flow measurement accuracy is improved.

Description

Technical Field

[0001] The present invention relates to the field of flow measurement, and in particular to a rotor flowmeter, and a flow measurement method and system based on a filtering algorithm. Background Art

[0002] Fluids such as air, water, and gas are closely intertwined with our daily lives and social activities. When using these fluids, it's crucial to measure their properties and quantities. With the rapid development of electronic control systems, precision flow devices are widely used in a wide range of fields, including aircraft, automobiles, and agricultural production. With the continued development of the economy and society, the demand for precision flow devices is increasing in an increasing number of fields.

[0003] Existing ultrasonic flowmeters are susceptible to interference from bubbles, scaling, ultrasonic noise from pumps, and other sound sources, which can affect measurement accuracy. Especially when measuring fluids containing large amounts of bubbles or suspended matter, ultrasonic signals are susceptible to scattering and attenuation, leading to increased measurement errors. Furthermore, because the propagation of ultrasonic signals in fluids is affected by a variety of factors, such as fluid temperature, pressure, density, and pipe material, ultrasonic flowmeters generally offer limited reliability and accuracy. Furthermore, the measurement circuitry of ultrasonic flowmeters is relatively complex, requiring a comprehensive measurement circuit and precise algorithms to achieve high-precision measurements.

[0004] Therefore, it is necessary to provide a rotor flowmeter, a flow measurement method and a system based on a filtering algorithm to improve the accuracy of flow measurement. Summary of the Invention

[0005] The present invention provides a rotor flowmeter, including a flow sensing device, wherein the flow sensing device includes a tapered tube with an upward flared mouth, a rotor is arranged inside the tapered tube, and the rotor floats along the length direction of the tapered tube under the action of the fluid, and a magnet is installed on the rotor; the rotor also includes a magnetic field sensing device arranged on the flow sensing device, which is used to collect real-time magnetic field data; the rotor also includes an environmental sensing device, which is used to collect real-time environmental data; and the rotor also includes a flow correction device, which is used to determine a real-time magnet angle value based on the real-time magnetic field data and the real-time environmental data, and determine the real-time fluid flow based on the real-time magnet angle value.

[0006] Furthermore, the magnetic field sensing device includes an X-axis Hall sensor, a Y-axis Hall sensor, and a Z-axis Hall sensor; the flow correction device determines the real-time magnet angle value based on the real-time magnetic field data and the real-time environmental data, including: determining the real-time magnet angle value to be corrected based on the X-axis Hall sensor, the Y-axis Hall sensor, and the Z-axis Hall sensor; and correcting the real-time magnet angle value to be corrected based on the real-time environmental data to generate a real-time magnet angle value.

[0007] The present invention provides a flow measurement method based on a filtering algorithm, which is applied to the above-mentioned rotor flowmeter, comprising: performing data correction on real-time magnetic field data at multiple consecutive time points through a data correction model to obtain the corrected real-time magnetic field data at the multiple consecutive time points; determining a real-time magnet angle value to be corrected based on the corrected real-time magnetic field data at the multiple consecutive time points; calculating an environmental impact coefficient based on the real-time environmental data at the multiple consecutive time points; when the environmental impact coefficient is greater than an environmental impact coefficient threshold, correcting the real-time magnet angle value to be corrected based on the real-time environmental data at the multiple consecutive time points to generate a real-time magnet angle value; when the environmental impact coefficient is less than or equal to the environmental impact coefficient threshold, using the real-time magnet angle value to be corrected as the real-time magnet angle value; smoothing the real-time magnet angle values ​​at the multiple consecutive time points through a filtering algorithm to obtain a processed real-time magnet angle value; and determining the real-time fluid flow based on the processed real-time magnet angle value.

[0008] Furthermore, the real-time magnetic field data of multiple consecutive time points are corrected by the data correction model to obtain the corrected real-time magnetic field data of multiple consecutive time points, including: for each of the time points, based on a first preset time window, intercepting a first real-time magnetic field data sequence corresponding to the time point from the real-time magnetic field data of the multiple consecutive time points, determining the X-axis magnetic field component fluctuation parameters, Y-axis magnetic field component fluctuation parameters and Z-axis magnetic field component fluctuation parameters corresponding to the time point based on the first real-time magnetic field data sequence corresponding to the time point, determining the abnormal parameters of the time point based on the X-axis magnetic field component fluctuation parameters, Y-axis magnetic field component fluctuation parameters and Z-axis magnetic field component fluctuation parameters corresponding to the time point, if the abnormal parameters of the time point are greater than the abnormal parameter threshold, marking the time point as an abnormal time point; correcting the real-time magnetic field data of the abnormal time point based on the real-time magnetic field data of multiple consecutive time points by the data correction model to obtain the corrected real-time magnetic field data of multiple consecutive time points.

[0009] Furthermore, the determining of the real-time magnet angle value to be corrected based on the corrected real-time magnetic field data of the plurality of consecutive time points includes: for each of the time points, based on a second preset time window, intercepting a second real-time magnetic field data sequence corresponding to the time point from the real-time magnetic field data of the plurality of consecutive time points after correction, and determining the real-time magnetic field difference parameter corresponding to the time point based on the second real-time magnetic field data sequence corresponding to the time point; taking the time point at which the real-time magnetic field difference parameter is less than the real-time magnetic field difference parameter threshold as the target time point; and determining the real-time magnet angle value to be corrected corresponding to the target time point based on the second real-time magnetic field data sequence corresponding to the target time point.

[0010] Furthermore, the calculation of the environmental impact coefficient based on the real-time environmental data at multiple consecutive time points includes: performing empirical mode decomposition on the real-time environmental temperature data at multiple consecutive time points to obtain the real-time environmental temperature eigenmode function and the real-time environmental temperature residual; performing empirical mode decomposition on the real-time magnetic field interference data at multiple consecutive time points to obtain the real-time magnetic field interference eigenmode function and the real-time magnetic field interference residual; performing empirical mode decomposition on the real-time vibration data of the flow sensing device at multiple consecutive time points to obtain the real-time vibration eigenmode function and the real-time vibration residual, wherein the real-time environmental data at least includes real-time environmental temperature data, real-time magnetic field interference data and real-time vibration data; and calculating the environmental impact coefficient based on the real-time environmental temperature eigenmode function and the real-time environmental temperature residual, the real-time magnetic field interference eigenmode function and the real-time magnetic field interference residual, and the real-time vibration eigenmode function and the real-time vibration residual through the impact prediction model.

[0011] Furthermore, the real-time environmental data based on multiple consecutive time points corrects the real-time magnet angle value to be corrected, including: correcting the real-time magnet angle value to be corrected based on the real-time environmental temperature eigenmode function and the real-time environmental temperature residual, the real-time magnetic field interference eigenmode function and the real-time magnetic field interference residual, and the real-time vibration eigenmode function and the real-time vibration residual through an angle correction model.

[0012] Furthermore, the smoothing of the real-time magnet angle values ​​at multiple consecutive time points by a filtering algorithm to obtain the processed real-time magnet angle values ​​at multiple consecutive time points includes: smoothing the real-time magnet angle values ​​at multiple consecutive time points by a sliding filtering algorithm and a mean filtering algorithm to obtain the processed real-time magnet angle values ​​at multiple consecutive time points.

[0013] Furthermore, based on the processed real-time magnet angle value, the real-time fluid flow is determined, including: establishing a mapping relationship between angle and fluid flow; and determining the real-time fluid flow based on the processed real-time magnet angle value and the mapping relationship between angle and fluid flow.

[0014] The present invention provides a flow measurement system based on a filtering algorithm, which is used to execute the above-mentioned flow measurement method based on the filtering algorithm, including: a flow sensing module, including a flow sensing device and a magnetic field sensing device, wherein the flow sensing device includes a tapered tube with an upward flared mouth, a rotor is provided inside the tapered tube, the rotor floats along the length direction of the tapered tube under the action of the fluid, a magnet is installed on the rotor, and the magnetic field sensing device is used to collect real-time magnetic field data; an environmental perception module is used to collect real-time environmental data; a flow calculation module is used to perform data correction on the real-time magnetic field data of multiple consecutive time points through a data correction model, and obtain the corrected real-time magnetic field data of multiple consecutive time points, based on The real-time magnetic field data of multiple consecutive time points after correction are used to determine the real-time magnet angle value to be corrected. The environmental impact coefficient is calculated based on the real-time environmental data of the multiple consecutive time points. When the environmental impact coefficient is greater than an environmental impact coefficient threshold, the real-time magnet angle value to be corrected is corrected based on the real-time environmental data of the multiple consecutive time points to generate a real-time magnet angle value. When the environmental impact coefficient is less than or equal to the environmental impact coefficient threshold, the real-time magnet angle value to be corrected is used as the real-time magnet angle value. The real-time magnet angle values ​​of the multiple consecutive time points are smoothed using a filtering algorithm to obtain a processed real-time magnet angle value. The real-time fluid flow rate is determined based on the processed real-time magnet angle value.

[0015] Compared with the prior art, the rotor flowmeter, the flow measurement method and system based on the filtering algorithm provided by the present invention have at least the following beneficial effects: 1. Correcting magnetic field data using a data correction model can eliminate or minimize the impact of adverse factors such as measurement error and noise, improving data accuracy and reliability. Taking into account the impact of real-time environmental data (such as temperature, magnetic field interference, and vibration) on the magnet angle and calculating an environmental impact coefficient for correction further improves magnet angle accuracy. Setting an environmental impact coefficient threshold and determining whether angle correction is necessary based on real-time environmental data allows the system to flexibly adapt to changing environmental conditions, enhancing its robustness and adaptability. Smoothing real-time magnet angle values ​​at multiple consecutive time points eliminates or minimizes angle fluctuations caused by measurement noise, resulting in more stable and smooth angle values, facilitating accurate subsequent fluid flow calculations. Because the magnet angle values ​​undergo multiple optimization steps, including data correction, environmental impact correction, and smoothing, the fluid flow calculated based on these processed angle values ​​is more accurate and reliable.

[0016] 2. Taking into account the influence of multiple factors such as real-time ambient temperature, magnetic field interference and vibration on the magnet angle, by establishing the eigenmode functions and residuals of these factors respectively, the influence of these factors on angle measurement can be more comprehensively captured and corrected, thereby improving the accuracy of angle measurement. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] This specification will be further described in the form of exemplary embodiments, which will be described in detail with reference to the accompanying drawings. These embodiments are not limiting, and in these embodiments, the same numbers represent the same structures, wherein:

[0018] Figure 1 is a schematic diagram of a rotor flowmeter according to some embodiments of this specification; Figure 2 is a flow chart of a flow measurement method based on a filtering algorithm according to some embodiments of this specification; Figure 3 It is a module diagram of a flow measurement system based on a filtering algorithm according to some embodiments of this specification. DETAILED DESCRIPTION

[0019] To more clearly illustrate the technical solutions of the embodiments of this specification, the following briefly describes the drawings required for describing the embodiments. Obviously, the drawings described below are merely examples or embodiments of this specification. Those skilled in the art can apply this specification to other similar scenarios based on these drawings without inventive effort. Unless otherwise apparent from the context or otherwise noted, the same reference numerals in the figures represent the same structure or operation.

[0020] Figure 1 is a schematic diagram of a rotor flowmeter according to some embodiments of this specification, such as Figure 1 As shown, the rotameter includes a flow sensing device, which includes an upwardly flared conical tube. A rotor is disposed within the conical tube. The rotor floats along the length of the conical tube under the influence of the fluid, and a magnet is mounted on the rotor. The rotameter also includes a magnetic field sensing device disposed on the flow sensing device for collecting real-time magnetic field data. The rotameter also includes an environmental sensing device for collecting real-time environmental data. The rotameter also includes a flow correction device for determining a real-time magnet angle value based on the real-time magnetic field data and real-time environmental data, and for determining the real-time fluid flow rate based on the real-time magnet angle value.

[0021] Specifically, as fluid passes through the conical tube, it creates an upward buoyancy force on the rotor, causing it to float up and down within the tube. As the flow rate increases, the rotor rises higher; as the flow rate decreases, the rotor descends. The height change of the magnet on the rotor is captured by a magnetic field sensor and converted into an electrical signal, which is then used to calculate the real-time magnet angle.

[0022] In some embodiments, the magnetic field sensing device includes an X-axis Hall sensor, a Y-axis Hall sensor, and a Z-axis Hall sensor, wherein the Z-axis may be parallel to the length direction of the tapered tube.

[0023] In some embodiments, the flow correction device determines a real-time magnet angle value based on real-time magnetic field data and real-time environmental data, including: Determine the real-time magnet angle value to be corrected based on the X-axis Hall sensor, the Y-axis Hall sensor, and the Z-axis Hall sensor; Based on the real-time environmental data, the real-time magnet angle value to be corrected is corrected to generate a real-time magnet angle value.

[0024] The performance indicators of the rotor flowmeter can be shown in Table 1.

[0025] Table 1 Dimensions: 70×70 mm Supply voltage: 9V~32V DC; Power supply impact: No more than 0.01% / V Output load change: No more than 0.05% Accuracy: ≤±1％； stability: ≤±0.2％; Operating temperature range: -20℃~+70℃ (with backlight LCD display) -40℃~+85℃ (without LCD display) Temperature effects ≤±1％ / 50℃ The main functions of the rotor flowmeter can be shown in Table 2.

[0026] Table 2 Output: 4~20mA output, superimposed HART communication; Diagnostic function: When the instrument fails, it outputs alarm output current; Configuration functions: Configuration of engineering unit, measured medium, medium density, float density, range, display, alarm value, etc.; and has the function of clearing the accumulated flow and zero point correction Alarm function: The upper and lower alarm limits can be set. If the value is lower than the lower limit, the output is 3.8mA and the LCD displays ALM_L. If the value is higher than the upper limit, the output is 22mA and the LCD displays ALM_H. Monitoring dynamic variables function: Instantaneous flow, percentage, output current, cumulative flow, etc. Current calibration function: The analog output current can be calibrated; Flow calibration function: You can choose 2 to 16 points calibration; Primary variable zeroing: Zero point correction function Local configuration function: Configuration of engineering unit, measured medium, medium density, float density, range, display, alarm value, etc., and with functions of clearing accumulated flow and zero point correction Local current fine-tuning: Able to fine-tune 4 mA and 20 mA current. Configuration software is available LCD display function: 5-digit LCD display with backlight and symbols; can display various engineering units Data backup: After configuring and calibrating the instrument, back up the manufacturer's original information

[0027] Connect a 24V DC power supply to the 24V power socket J6 on the rotameter board (marked ±24V on the circuit board). The board's supply voltage range is DC9V to 32V. Plug the LCD plug into socket J7 on the rotameter board. If using an LCD, the LCD module already has three buttons. The circuit board typically has two buttons, with one reserved. If not using an LCD, simply remove the LCD panel.

[0028] Before using a rotameter, several steps are required, including assembly, calibration, and parameter setting. During assembly, the sensor installation position must be determined. When using a Honghu Technology rotameter, for optimal accuracy, the following installation conditions must be met: 1. The center plane of the magnet should be flush with the circuit board. 2. Enter the "Process Monitoring" screen of the configuration software and select "Sensor Value." Adjust the magnet position so that the sensor value is between 110 and 150 at a flow rate of 50%. To ensure optimal accuracy, each magnet in the float flowmeter must be adjusted to meet the requirements of "2." As long as the polarity of the magnet remains unchanged during installation, determining the magnet position only requires one step. Enter the "User Calibration" screen of the configuration software, select the number of calibration points, enter the calibration value, select "Acquire," and click "OK" after the sensor value stabilizes.

[0029] The LCD supports dual-variable display. The display variables that can be set include current, cumulative amount, primary variable percentage and primary variable. If the two display variables are the same, the LCD will only display one variable; otherwise, the LCD will alternately display the set display variables at a time interval of 4 seconds.

[0030] The rotor flowmeter can perform flow detection according to the flow measurement method based on the filtering algorithm. For more description of the rotor flowmeter, please refer to the relevant description of the flow measurement method based on the filtering algorithm, which will not be repeated here.

[0031] Figure 2 is a flow chart of a flow measurement method based on a filtering algorithm according to some embodiments of this specification, such as Figure 2 As shown, the flow measurement method based on the filtering algorithm may include the following steps.

[0032] Step 210 , performing data correction on the real-time magnetic field data at multiple consecutive time points using a data correction model to obtain corrected real-time magnetic field data at multiple consecutive time points.

[0033] Specifically include: For each time point, based on a first preset time window, a first real-time magnetic field data sequence corresponding to the time point is intercepted from the real-time magnetic field data of multiple consecutive time points, based on the first real-time magnetic field data sequence corresponding to the time point, the X-axis magnetic field component fluctuation parameter, the Y-axis magnetic field component fluctuation parameter and the Z-axis magnetic field component fluctuation parameter corresponding to the time point are determined, based on the X-axis magnetic field component fluctuation parameter, the Y-axis magnetic field component fluctuation parameter and the Z-axis magnetic field component fluctuation parameter corresponding to the time point, the abnormal parameter of the time point is determined, if the abnormal parameter of the time point is greater than the abnormal parameter threshold, the time point is marked as an abnormal time point; The real-time magnetic field data at the abnormal time point is corrected based on the real-time magnetic field data at multiple consecutive time points through a data correction model to obtain the corrected real-time magnetic field data at the multiple consecutive time points, wherein the data correction model can be a long short-term memory network (LSTM) model.

[0034] For example, the X-axis magnetic field component fluctuation parameter can be calculated based on the following formula: in, is the X-axis magnetic field component fluctuation parameter at the i-th time point, is the first real-time magnetic field data sequence at the i-th time point The X-axis magnetic field component at a time point, is the total number of time points included in the first preset time window corresponding to the i-th time point.

[0035] The calculation method of the Y-axis magnetic field component fluctuation parameter and the Z-axis magnetic field component fluctuation parameter is similar to the calculation method of the X-axis magnetic field component fluctuation parameter, and will not be repeated here.

[0036] The anomaly parameter can be calculated based on the following formula: in, is the abnormal parameter at the i-th time point, 、 and is the preset weight, 、 and are greater than 0, and , is the Y-axis magnetic field component fluctuation parameter at the i-th time point, is the Z-axis magnetic field component fluctuation parameter at the i-th time point, It is the preset Z-axis magnetic field component fluctuation parameter.

[0037] Step 220 : Determine the real-time magnet angle value to be corrected based on the corrected real-time magnetic field data at multiple consecutive time points.

[0038] Specifically include: For each time point, based on the second preset time window, intercepting a second real-time magnetic field data sequence corresponding to the time point from the corrected real-time magnetic field data of the plurality of consecutive time points, and determining the real-time magnetic field difference parameter corresponding to the time point based on the second real-time magnetic field data sequence corresponding to the time point; The time point at which the real-time magnetic field difference parameter is less than the real-time magnetic field difference parameter threshold is used as the target time point; Based on the second real-time magnetic field data sequence corresponding to the target time point, the real-time magnet angle value to be corrected corresponding to the target time point is determined.

[0039] For example, the real-time magnetic field difference parameter can be calculated based on the following formula: in, is the real-time magnetic field difference parameter at the i-th time point, for, is the total number of time points included in the second preset time window, The second real-time magnetic field data sequence corresponding to the i-th time point includes the Real-time magnetic field data at a given time point.

[0040] Step 230 : Calculate the environmental impact coefficient based on the real-time environmental data at multiple consecutive time points.

[0041] Specifically include: Perform empirical mode decomposition on the real-time ambient temperature data at multiple consecutive time points to obtain the real-time ambient temperature eigenmode function and the real-time ambient temperature residual; Performing empirical mode decomposition on the real-time magnetic field interference data at multiple consecutive time points to obtain the real-time magnetic field interference eigenmode function and real-time magnetic field interference residual; Performing empirical mode decomposition on real-time vibration data of the flow sensing device at multiple consecutive time points to obtain a real-time vibration eigenmode function and a real-time vibration residual, wherein the real-time environmental data at least includes real-time ambient temperature data, real-time magnetic field interference data, and real-time vibration data; The environmental impact coefficient is calculated based on the real-time ambient temperature eigenmode function and the real-time ambient temperature residual, the real-time magnetic field interference eigenmode function and the real-time magnetic field interference residual, and the real-time vibration eigenmode function and the real-time vibration residual through the impact prediction model, wherein the impact prediction model can be a convolutional neural network (CNN) model.

[0042] Specifically, the process of empirical mode decomposition is: 1. Identifying extreme points Finding extreme points: First, we need to find all the local maximum and local minimum points in the signal sequence. These extreme points are the basis for the subsequent steps.

[0043] 2. Fitting Envelope Fitting upper and lower envelopes: Using extreme points, use cubic spline interpolation or other methods, such as quadratic spline interpolation, to fit the upper and lower envelopes of the signal. These two envelopes represent the signal envelope at local maxima and local minima, respectively.

[0044] 3. Calculate the mean envelope Calculate the mean: Average the upper and lower envelopes to get the mean envelope. This mean envelope reflects the average variation of the signal on a local time scale.

[0045] 4. Screening Process Original signal minus mean envelope: Subtract the mean envelope from the original signal to obtain a new signal, called the intermediate signal or residual signal.

[0046] Determine if it is an IMF: Check whether the new signal meets the Intrinsic Mode Function (IMF) conditions. IMF conditions include: the number of local extreme points and zero crossings must be equal or differ by at most one over the entire time range; and at any point in time, the average value of the upper envelope formed by the local maximum points and the lower envelope formed by the local minimum points is zero.

[0047] Repeated screening: If the new signal does not meet the IMF conditions, it is treated as a new original signal and steps 2 to 4 are repeated until the IMF conditions are met or the preset stopping conditions are reached, such as the residual signal contains no more than two extreme points.

[0048] 5. Decomposition completed Obtaining IMF components: Through the above screening process, multiple IMF components can be obtained in sequence. These IMF components are arranged in order from high frequency to low frequency, representing local characteristic signals of different time scales in the original signal.

[0049] Residual term: After obtaining all IMF components, the residual term is the sum of all IMF components subtracted from the original signal.

[0050] Step 240 : When the environmental impact coefficient is greater than the environmental impact coefficient threshold, the real-time magnet angle value to be corrected is corrected based on the real-time environmental data at multiple consecutive time points to generate a real-time magnet angle value.

[0051] Specifically include: The real-time magnet angle value to be corrected is corrected through an angle correction model based on the real-time ambient temperature eigenmode function and the real-time ambient temperature residual, the real-time magnetic field interference eigenmode function and the real-time magnetic field interference residual, and the real-time vibration eigenmode function and the real-time vibration residual. The angle correction model can be a convolutional neural network (CNN) model.

[0052] Step 250 : When the environmental impact coefficient is less than or equal to the environmental impact coefficient threshold, the real-time magnet angle value to be corrected is used as the real-time magnet angle value.

[0053] Step 260 : Smoothing the real-time magnet angle values ​​at multiple consecutive time points using a filtering algorithm to obtain processed real-time magnet angle values.

[0054] Specifically, the method includes: using a sliding filter algorithm and a mean filter algorithm to smooth the real-time magnet angle values ​​at multiple consecutive time points, and obtaining the processed real-time magnet angle values ​​at multiple consecutive time points.

[0055] Specifically, the sliding filter algorithm smoothes the data by averaging the real-time magnet angle values ​​at multiple consecutive time points within a fixed window. The window size (i.e., the number of data points included) is predefined. For each new time point, the window slides forward one position and the average is recalculated.

[0056] The mean filter algorithm smoothes the data by calculating the average of the real-time magnet angle values ​​at multiple consecutive time points.

[0057] In step 270 , the real-time fluid flow rate is determined based on the processed real-time magnet angle value.

[0058] Specifically include: Establishing the mapping relationship between angle and fluid flow rate; The real-time fluid flow rate is determined based on the processed real-time magnet angle value and the mapping relationship between the angle and the fluid flow rate.

[0059] Specifically, a mathematical model of angle and fluid flow mapping can be established, multiple sets of experimental data can be obtained, the multiple sets of experimental data can be brought into the mathematical model of angle and fluid flow mapping, and the model parameters of the mathematical model of angle and fluid flow mapping can be solved, thereby establishing a mapping relationship between angle and fluid flow.

[0060] After obtaining the processed real-time magnet angle value, the processed real-time magnet angle value is substituted into the mapping relationship between angle and fluid flow rate to obtain the real-time fluid flow rate.

[0061] Figure 3 is a schematic diagram of a flow measurement system based on a filtering algorithm according to some embodiments of this specification, such as Figure 3 As shown, the flow measurement system based on the filtering algorithm may include a flow sensing module, an environment perception module and a flow calculation module.

[0062] The flow sensing module may include a flow sensing device and a magnetic field sensing device, wherein the flow sensing device includes a conical tube with an upward flared mouth, a rotor is provided inside the conical tube, and the rotor floats along the length direction of the conical tube under the action of the fluid. A magnet is installed on the rotor, and the magnetic field sensing device is used to collect real-time magnetic field data.

[0063] The environmental perception module can be used to collect real-time environmental data.

[0064] The flow calculation module can be used to correct the real-time magnetic field data of multiple continuous time points through a data correction model, obtain the corrected real-time magnetic field data of multiple continuous time points, determine the real-time magnet angle value to be corrected based on the corrected real-time magnetic field data of multiple continuous time points, calculate the environmental impact coefficient based on the real-time environmental data of multiple continuous time points, when the environmental impact coefficient is greater than the environmental impact coefficient threshold, correct the real-time magnet angle value to be corrected based on the real-time environmental data of multiple continuous time points to generate a real-time magnet angle value, when the environmental impact coefficient is less than or equal to the environmental impact coefficient threshold, use the real-time magnet angle value to be corrected as the real-time magnet angle value, smooth the real-time magnet angle values ​​of multiple continuous time points through a filtering algorithm, obtain the processed real-time magnet angle value, and determine the real-time fluid flow based on the processed real-time magnet angle value.

[0065] The flow measurement system based on the filtering algorithm can be used to execute the flow measurement method based on the filtering algorithm. For more description of the flow measurement system based on the filtering algorithm, please refer to the relevant description of the flow measurement method based on the filtering algorithm, which will not be repeated here.

[0066] Finally, it should be understood that the embodiments described in this specification are intended only to illustrate the principles of the embodiments of this specification. Other variations may also fall within the scope of this specification. Therefore, by way of example and not limitation, alternative configurations of the embodiments of this specification may be considered consistent with the teachings of this specification. Accordingly, the embodiments of this specification are not limited to the embodiments explicitly described and illustrated in this specification.

Claims

1. A rotor flow meter, characterized in that: The flow sensing device comprises a conical tube with an opening expanded upward, a rotor is arranged inside the conical tube, the rotor floats along the length direction of the conical tube under the action of the fluid, and a magnet is installed on the rotor; It also includes a magnetic field sensing device disposed on the flow sensing device, for collecting real-time magnetic field data; It also includes an environmental sensing device for collecting real-time environmental data; It also includes a flow correction device for determining a real-time magnet angle value based on the real-time magnetic field data and the real-time environmental data, and determining a real-time fluid flow based on the real-time magnet angle value.

2. The rotor flowmeter according to claim 1, characterized in that: The magnetic field sensing device includes an X-axis Hall sensor, a Y-axis Hall sensor and a Z-axis Hall sensor; The flow correction device determines the real-time magnet angle value based on the real-time magnetic field data and the real-time environmental data, including: Based on the X-axis Hall sensor, the Y-axis Hall sensor and the Z-axis Hall sensor, determining the real-time magnet angle value to be corrected; Based on the real-time environmental data, the real-time magnet angle value to be corrected is corrected to generate a real-time magnet angle value.

3. A flow measurement method based on a filtering algorithm, applied to the rotor flowmeter according to claim 2, characterized in that: include: The real-time magnetic field data at multiple consecutive time points are corrected by a data correction model to obtain the corrected real-time magnetic field data at multiple consecutive time points; Determine the real-time magnet angle value to be corrected based on the corrected real-time magnetic field data at multiple consecutive time points; Calculate environmental impact coefficients based on real-time environmental data at multiple consecutive time points; When the environmental impact coefficient is greater than the environmental impact coefficient threshold, based on the real-time environmental data at multiple consecutive time points, the real-time magnet angle value to be corrected is corrected to generate a real-time magnet angle value; When the environmental impact coefficient is less than or equal to the environmental impact coefficient threshold, the real-time magnet angle value to be corrected is used as the real-time magnet angle value; The real-time magnet angle values ​​at multiple consecutive time points are smoothed by a filtering algorithm to obtain the processed real-time magnet angle values; Based on the processed real-time magnet angle value, a real-time fluid flow rate is determined.

4. The flow measurement method based on filtering algorithm according to claim 3 is characterized in that: The method of performing data correction on the real-time magnetic field data at multiple consecutive time points by using a data correction model to obtain the corrected real-time magnetic field data at multiple consecutive time points includes: For each of the time points, based on a first preset time window, a first real-time magnetic field data sequence corresponding to the time point is intercepted from the real-time magnetic field data of the multiple consecutive time points, based on the first real-time magnetic field data sequence corresponding to the time point, an X-axis magnetic field component fluctuation parameter, a Y-axis magnetic field component fluctuation parameter and a Z-axis magnetic field component fluctuation parameter corresponding to the time point are determined, based on the X-axis magnetic field component fluctuation parameter, the Y-axis magnetic field component fluctuation parameter and the Z-axis magnetic field component fluctuation parameter corresponding to the time point, an abnormal parameter of the time point is determined, and if the abnormal parameter of the time point is greater than an abnormal parameter threshold, the time point is marked as an abnormal time point; The data correction model is used to correct the real-time magnetic field data at abnormal time points based on the real-time magnetic field data at multiple consecutive time points, so as to obtain the corrected real-time magnetic field data at multiple consecutive time points.

5. The flow measurement method based on filtering algorithm according to claim 4 is characterized in that: The method of determining the real-time magnet angle value to be corrected based on the corrected real-time magnetic field data at multiple consecutive time points includes: For each of the time points, based on a second preset time window, a second real-time magnetic field data sequence corresponding to the time point is intercepted from the corrected real-time magnetic field data of the plurality of consecutive time points, and based on the second real-time magnetic field data sequence corresponding to the time point, a real-time magnetic field difference parameter corresponding to the time point is determined; The time point at which the real-time magnetic field difference parameter is less than the real-time magnetic field difference parameter threshold is taken as the target time point; Based on the second real-time magnetic field data sequence corresponding to the target time point, the real-time magnet angle value to be corrected corresponding to the target time point is determined.

6. The flow measurement method based on filtering algorithm according to claim 3, characterized in that: The calculation of the environmental impact coefficient based on the real-time environmental data at multiple consecutive time points includes: Performing empirical mode decomposition on the real-time ambient temperature data at multiple consecutive time points to obtain the real-time ambient temperature eigenmode function and the real-time ambient temperature residual; Performing empirical mode decomposition on real-time magnetic field interference data at multiple consecutive time points to obtain real-time magnetic field interference eigenmode function and real-time magnetic field interference residual; Performing empirical mode decomposition on the real-time vibration data of the flow sensing device at multiple consecutive time points to obtain a real-time vibration eigenmode function and a real-time vibration residual, wherein the real-time environmental data at least includes real-time environmental temperature data, real-time magnetic field interference data and real-time vibration data; The environmental impact coefficient is calculated based on the real-time ambient temperature eigenmode function and the real-time ambient temperature residual, the real-time magnetic field interference eigenmode function and the real-time magnetic field interference residual, and the real-time vibration eigenmode function and the real-time vibration residual through the impact prediction model.

7. The flow measurement method based on filtering algorithm according to claim 6, characterized in that: The method of correcting the real-time magnet angle value to be corrected based on the real-time environmental data at multiple consecutive time points includes: The real-time magnet angle value to be corrected is corrected through the angle correction model based on the real-time ambient temperature eigenmode function and the real-time ambient temperature residual, the real-time magnetic field interference eigenmode function and the real-time magnetic field interference residual, and the real-time vibration eigenmode function and the real-time vibration residual.

8. The flow measurement method based on filtering algorithm according to any one of claims 3 to 7, characterized in that: The method of smoothing the real-time magnet angle values ​​at multiple consecutive time points by using a filtering algorithm to obtain the processed real-time magnet angle values ​​at multiple consecutive time points includes: The real-time magnet angle values ​​at multiple consecutive time points are smoothed using a sliding filtering algorithm and a mean filtering algorithm to obtain the processed real-time magnet angle values ​​at multiple consecutive time points.

9. The flow measurement method based on filtering algorithm according to any one of claims 3 to 7, characterized in that: Determining the real-time fluid flow rate based on the processed real-time magnet angle value includes: Establishing the mapping relationship between angle and fluid flow rate; Based on the processed real-time magnet angle value and the mapping relationship between the angle and the fluid flow rate, the real-time fluid flow rate is determined.

10. A flow measurement system based on a filtering algorithm, used to execute the flow measurement method based on a filtering algorithm as claimed in any one of claims 3 to 9, characterized in that: include: The flow sensing module includes a flow sensing device and a magnetic field sensing device, wherein the flow sensing device includes a tapered tube with an opening expanded upward, a rotor is arranged inside the tapered tube, the rotor floats along the length direction of the tapered tube under the action of the fluid, a magnet is installed on the rotor, and the magnetic field sensing device is used to collect real-time magnetic field data; Environmental perception module, used to collect real-time environmental data; The flow calculation module is used to perform data correction on the real-time magnetic field data of multiple continuous time points through a data correction model, obtain the corrected real-time magnetic field data of multiple continuous time points, determine the real-time magnet angle value to be corrected based on the corrected real-time magnetic field data of multiple continuous time points, calculate the environmental impact coefficient based on the real-time environmental data of multiple continuous time points, when the environmental impact coefficient is greater than the environmental impact coefficient threshold, correct the real-time magnet angle value to be corrected based on the real-time environmental data of multiple continuous time points to generate a real-time magnet angle value, when the environmental impact coefficient is less than or equal to the environmental impact coefficient threshold, use the real-time magnet angle value to be corrected as the real-time magnet angle value, smooth the real-time magnet angle values ​​of multiple continuous time points through a filtering algorithm, obtain the processed real-time magnet angle value, and determine the real-time fluid flow based on the processed real-time magnet angle value.

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