Flow velocity sensor, flow velocity measurement method, device, flow velocity sensor and storage medium

Abstract

This application discloses a flow velocity sensor, flow velocity measurement method, apparatus, flow velocity sensor, and storage medium, relating to the field of flow velocity measurement technology. The flow velocity sensor includes an impeller assembly, a magnetohydrodynamic sealing unit, a magnetic coupling coupling, a fiber optic gyroscope, a signal processing unit, a temperature sensor, and an accelerometer. The method includes: acquiring the raw angular velocity signal output by the fiber optic gyroscope; acquiring real-time temperature data within the sealed chamber collected by the temperature sensor; performing real-time compensation on the raw angular velocity signal based on the real-time temperature data to obtain a target angular velocity value; and calculating the fluid velocity value based on the target angular velocity value. This application can improve the measurement accuracy of fluid flow velocity.

Description

Technical Field

[0001] This application relates to the field of flow velocity measurement technology, and in particular to a flow velocity sensor, flow velocity measurement method, device, flow velocity sensor and storage medium. Background Technology

[0002] Mechanical flow velocity sensors (such as impeller and turbine flow meters) are widely used in fluid measurement due to their simple structure and low cost. These sensors detect the impeller rotation speed using contact sensing methods such as magnetoelectric, photoelectric, or Hall effect elements, and then convert this speed into flow velocity. However, this contact-based speed measurement method has several inherent drawbacks: a specific gap or direct contact must be maintained between the sensing element and the rotating component; long-term operation can lead to decreased accuracy or even failure due to mechanical wear; and this results in insufficient accuracy when measuring fluid flow velocity. Therefore, improving the accuracy of fluid flow velocity measurement remains a problem that needs to be solved.

[0003] The above content is only used to help understand the technical solution of this application and does not represent an admission that the above content is prior art. Summary of the Invention

[0004] The main objective of this application is to provide a flow velocity sensor, flow velocity measurement method, apparatus, device, and storage medium, aiming to solve the technical problem of how to improve the measurement accuracy of fluid flow velocity.

[0005] To achieve the above objectives, this application proposes a flow velocity sensor and flow velocity measurement method. The flow velocity sensor includes an impeller assembly, a magnetohydrodynamic sealing unit, a magnetic coupling coupling, a fiber optic gyroscope, a signal processing unit, a temperature sensor, and an accelerometer. The impeller assembly is installed in a fluid pipeline. The main shaft of the impeller assembly rotatably passes through the magnetohydrodynamic sealing unit and extends into a sealed chamber. The magnetohydrodynamic sealing unit is disposed outside the chamber wall of the sealed chamber and sleeved on the main shaft. The magnetic coupling coupling is disposed inside the sealed chamber and connected to the main shaft. The fiber optic gyroscope is installed inside the sealed chamber with its sensitive axis coaxially aligned with the main shaft. The signal processing unit is connected to the fiber optic gyroscope. The temperature sensor and the accelerometer are integrated into the signal processing unit. The sealed chamber integrates a constant temperature control unit and is filled with inert gas. The flow velocity sensor flow velocity measurement method includes: Obtain the raw angular velocity signal output by the fiber optic gyroscope; Acquire real-time temperature data inside the sealed chamber collected by the temperature sensor; The original angular velocity signal is compensated in real time based on the real-time temperature data to obtain the target angular velocity value; The fluid velocity is calculated based on the target angular velocity value.

[0006] In one embodiment, the step of real-time compensation of the original angular velocity signal based on the real-time temperature data includes: Based on the real-time temperature data, the zero-bias compensation amount and scale factor compensation amount corresponding to the current temperature are obtained from the preset temperature compensation model; The original angular velocity signal is corrected based on the zero bias compensation amount and the scaling factor compensation amount to obtain the target angular velocity value.

[0007] In one embodiment, before the step of obtaining the zero-bias compensation amount and scaling factor compensation amount corresponding to the current temperature from a preset temperature compensation model based on the real-time temperature data, the method further includes: The fiber optic gyroscope was calibrated under different temperature conditions to obtain the zero bias value and scaling factor value corresponding to each temperature point. A preset temperature compensation model is established based on the correspondence between each temperature point and its corresponding zero bias value and scaling factor value.

[0008] In one embodiment, the step of establishing a preset temperature compensation model based on the correspondence between each temperature point and its corresponding zero bias and scaling factor values ​​includes: A piecewise fitting is performed between each temperature point and its corresponding zero bias value to generate a zero bias-temperature mapping relationship. Piecewise fitting is performed on each temperature point and its corresponding scaling factor value to generate a scaling factor-temperature mapping relationship; A preset temperature compensation model is constructed based on the zero bias-temperature mapping relationship and the scaling factor-temperature mapping relationship.

[0009] In one embodiment, before the step of real-time compensation of the original angular velocity signal based on the real-time temperature data, the method further includes: Acquire the triaxial acceleration signal output by the accelerometer; The covariance matrix of the current vibration noise is determined based on the triaxial acceleration signal. The original angular velocity signal is subjected to Kalman filtering based on the covariance matrix to obtain the original angular velocity signal after vibration suppression.

[0010] In one embodiment, the step of calculating the fluid velocity value based on the target angular velocity value includes: Obtain the preset calibration coefficients; The fluid velocity is calculated based on the target angular velocity value and the preset calibration coefficient.

[0011] In one embodiment, before the step of obtaining the preset calibration coefficients, the method further includes: Obtain the angular velocity values ​​output by the fiber optic gyroscope corresponding to multiple preset flow velocity points; The preset flow velocity point is fitted with the corresponding angular velocity value to generate a flow velocity-angular velocity correspondence curve. The calibration coefficients are determined based on the flow velocity-angular velocity correspondence curve.

[0012] Furthermore, to achieve the above objectives, this application also proposes a flow velocity sensor flow velocity measurement device, the flow velocity sensor flow velocity measurement device comprising: The acquisition module is used to acquire the raw angular velocity signal output by the fiber optic gyroscope. The data acquisition module is used to acquire real-time temperature data inside the sealed chamber collected by the temperature sensor. The compensation module is used to perform real-time compensation on the original angular velocity signal based on the real-time temperature data to obtain the target angular velocity value; The calculation module is used to calculate the flow velocity of the fluid based on the target angular velocity value.

[0013] Furthermore, to achieve the above objectives, this application also proposes a flow velocity sensor, which includes an impeller assembly, a magnetohydrodynamic sealing unit, a magnetic coupling coupling, a fiber optic gyroscope, a signal processing unit, a temperature sensor, and an accelerometer. The impeller assembly is installed in a fluid pipeline, and the main shaft of the impeller assembly rotatably passes through the magnetohydrodynamic sealing unit and extends into a sealed chamber. The magnetohydrodynamic sealing unit is disposed outside the chamber wall of the sealed chamber and sleeved on the main shaft. The magnetic coupling coupling is disposed inside the sealed chamber and connected to the main shaft. The fiber optic gyroscope is installed inside the sealed chamber with its sensitive axis coaxially aligned with the main shaft. The signal processing unit is connected to the fiber optic gyroscope. The temperature sensor and the accelerometer are integrated into the signal processing unit. A constant temperature control unit is integrated inside the sealed chamber and filled with inert gas. The flow velocity sensor also includes a memory, a processor, and a computer program stored in the memory and executable on the processor. The computer program is configured to implement the steps of the flow velocity sensor flow velocity measurement method described above.

[0014] In addition, to achieve the above objectives, this application also proposes a storage medium, which is a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the steps of the flow velocity sensor flow velocity measurement method as described above.

[0015] In addition, to achieve the above objectives, this application also provides a computer program product, which includes a computer program that, when executed by a processor, implements the steps of the flow velocity sensor flow velocity measurement method as described above.

[0016] This application provides a flow velocity sensor and a flow velocity measurement method. The flow velocity sensor includes an impeller assembly, a magnetohydrodynamic (MHD) sealing unit, a magnetic coupling coupling, a fiber optic gyroscope, a signal processing unit, a temperature sensor, and an accelerometer. The impeller assembly is installed in a fluid pipeline. The main shaft of the impeller assembly rotatably passes through the MHD sealing unit and extends into a sealed chamber. The MHD sealing unit is disposed outside the chamber wall and sleeved on the main shaft. The magnetic coupling coupling is disposed inside the sealed chamber and connected to the main shaft. The fiber optic gyroscope is installed inside the sealed chamber and its sensing axis is... The signal processing unit is coaxially aligned with the main shaft and connected to the fiber optic gyroscope. The temperature sensor and the accelerometer are integrated into the signal processing unit. A constant temperature control unit is integrated into the sealed chamber and filled with inert gas. The flow velocity sensor's flow velocity measurement method includes: acquiring the raw angular velocity signal output by the fiber optic gyroscope; acquiring real-time temperature data collected by the temperature sensor within the sealed chamber; performing real-time compensation on the raw angular velocity signal based on the real-time temperature data to obtain a target angular velocity value; and calculating the fluid flow velocity value based on the target angular velocity value. This application uses a fiber optic gyroscope to measure the main shaft rotational angular velocity instead of traditional contact-type rotational speed measurement, and utilizes real-time temperature data to perform real-time compensation on the raw angular velocity signal of the fiber optic gyroscope, thereby reducing measurement errors introduced by mechanical wear and temperature drift, and thus improving the accuracy of fluid flow velocity measurement. Attached Figure Description

[0017] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0018] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a flowchart illustrating an embodiment of the flow velocity sensor flow velocity measurement method of this application. Figure 2 This is a schematic diagram of the structure of the flow velocity sensor provided in Embodiment 1 of the flow velocity sensor measurement method of this application; Figure 3 This is a schematic diagram of the structure of the flow velocity sensor provided in Embodiment 1 of the flow velocity sensor measurement method of this application; Figure 4 This is a schematic diagram of the impeller assembly structure provided in Embodiment 2 of the flow velocity sensor flow velocity measurement method of this application; Figure 5A simplified flowchart illustrating the flow velocity measurement method using a flow velocity sensor provided in Embodiment 1 of this application; Figure 6 This is a schematic diagram of the module structure of the flow velocity sensor flow velocity measurement device according to an embodiment of this application; Figure 7 This is a schematic diagram of the device structure of the hardware operating environment involved in the flow velocity sensor flow velocity measurement method in the embodiments of this application.

[0020] Explanation of icon numbers: Impeller assembly 1, inlet 2, outlet 3, main shaft 4, magnetohydrodynamic sealing unit 5, magnetic coupling coupling 6, sensitive shaft 7, fiber optic gyroscope 8, signal and processing unit 9, sealed chamber 10.

[0021] The purpose, features, and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0022] It should be understood that the specific embodiments described herein are merely illustrative of the technical solutions of this application and are not intended to limit this application.

[0023] To better understand the technical solution of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.

[0024] The main solution of this application is that the flow velocity sensor includes an impeller assembly, a magnetohydrodynamic sealing unit, a magnetic coupling coupling, a fiber optic gyroscope, a signal processing unit, a temperature sensor, and an accelerometer. The impeller assembly is installed in a fluid pipeline. The main shaft of the impeller assembly rotatably passes through the magnetohydrodynamic sealing unit and extends into the sealed chamber. The magnetohydrodynamic sealing unit is disposed outside the chamber wall of the sealed chamber and sleeved on the main shaft. The magnetic coupling coupling is disposed inside the sealed chamber and connected to the main shaft. The fiber optic gyroscope is installed inside the sealed chamber, and its sensing axis is connected to the main shaft. The components are coaxially aligned, the signal processing unit is connected to the fiber optic gyroscope, the temperature sensor and the accelerometer are integrated into the signal processing unit, and the sealed chamber integrates a constant temperature control unit and is filled with inert gas. The flow velocity sensor flow velocity measurement method includes: acquiring the raw angular velocity signal output by the fiber optic gyroscope; acquiring real-time temperature data inside the sealed chamber collected by the temperature sensor; performing real-time compensation on the raw angular velocity signal based on the real-time temperature data to obtain a target angular velocity value; and calculating the fluid flow velocity value based on the target angular velocity value.

[0025] Currently, mechanical flow velocity sensors (such as impeller and turbine flow meters) are widely used in fluid measurement due to their simple structure and low cost. These sensors detect the impeller rotation speed using contact sensing methods such as magnetoelectric, photoelectric, or Hall effect elements, and then convert this speed into flow velocity. However, this contact-based speed measurement method has several inherent drawbacks: a specific gap or direct contact must be maintained between the sensing element and the rotating component; long-term operation can lead to decreased accuracy or even failure due to mechanical wear; and this results in insufficient accuracy when measuring fluid flow velocity. Therefore, improving the accuracy of fluid flow velocity measurement remains a problem that needs to be solved.

[0026] This application uses a fiber optic gyroscope to measure the spindle rotational angular velocity instead of the traditional contact-type rotational speed measurement, and uses real-time temperature data to compensate for the original angular velocity signal of the fiber optic gyroscope in real time, thereby reducing the measurement error introduced by mechanical wear and temperature drift, and thus improving the measurement accuracy of fluid flow velocity.

[0027] It should be noted that the executing entity in this embodiment can be a computing service device with data processing, network communication, and program execution functions, such as a tablet computer, personal computer, or mobile phone, or an electronic device or flow sensor capable of performing the above functions. The following description uses a flow sensor as an example to illustrate this embodiment and the subsequent embodiments. All actions involving the acquisition of signals, information, or data in this application are performed in accordance with the relevant data protection regulations of the country where the application is located and with authorization from the owner of the corresponding device.

[0028] Based on this, embodiments of this application provide a flow velocity sensor method for measuring flow velocity, referring to... Figure 1 , Figure 1 This is a flowchart illustrating the first embodiment of the flow velocity sensor flow velocity measurement method of this application.

[0029] For reference Figure 2 , Figure 2 This is a schematic diagram of the flow velocity sensor. In this embodiment, the flow velocity sensor includes an impeller assembly 1, a magnetohydrodynamic sealing unit 5, a magnetic coupling coupling 6, a fiber optic gyroscope 8, a signal processing unit 9, a temperature sensor (not shown in the figure), and an accelerometer (not shown in the figure). The impeller assembly 1 is installed in the fluid pipeline. Fluid enters from the inlet 2, driving the impeller to rotate and flowing out from the outlet 3. During this process, the main shaft 4 rotates together with the impeller assembly. (See reference...) Figure 3 , Figure 3This is a schematic diagram of the impeller assembly structure. The main shaft 4 rotatably passes through the magnetohydrodynamic (MHD) sealing unit 5 and extends into the sealed chamber 10. The MHD sealing unit 5 is located outside the chamber wall of the sealed chamber 10 and sleeved on the main shaft 4, used to achieve a zero-leakage dynamic seal between the inside and outside of the sealed chamber 10 when the main shaft 4 rotates. A magnetic coupling 6 is located inside the sealed chamber 10 and connected to the main shaft 4, used to transmit the rotational motion of the main shaft to the inside of the sealed chamber 10 without contact. A fiber optic gyroscope 8 is installed inside the sealed chamber 10, with its sensing shaft 7 coaxially aligned with the main shaft 4, used to measure the rotational angular velocity of the main shaft. A signal processing unit 9 is connected to the fiber optic gyroscope 8. A temperature sensor and accelerometer are integrated into the signal processing unit 9. A constant temperature control unit is integrated inside the sealed chamber 10 and filled with inert gas to maintain a constant internal temperature and isolate it from the external environment. The MHD sealing unit 5 is a magnetohydrodynamic sealing ring filled with magnetohydrodynamic fluid.

[0030] Understandably, the impeller assembly can utilize high-precision machined stainless steel or PTFE-coated impellers, with the diameter customized according to the pipe size. The magnetohydrodynamic sealing unit can employ magnetohydrodynamics to create a zero-leakage rotary seal. The fiber optic gyroscope can use a 500m long, 10cm diameter fiber optic ring, combined with a laser source, detector, and phase modulator to acquire angular velocity signals. The signal processing unit can be a digital demodulation circuit based on a Field Programmable Gate Array (FPGA) to achieve closed-loop control and high-bandwidth signal processing. The signal processing unit can also connect to a data output interface, supporting 4-20mA analog output, serial digital communication (e.g., RS485 digital communication), Ethernet, and Process Fieldbus (PROFIBUS) communication.

[0031] It is understood that, in this embodiment, the technical parameters of the flow velocity sensor may be: angular velocity measurement range of ±1000° / s; angular velocity resolution of 0.001° / h (corresponding to flow velocity resolution of 0.001 mm / s); operating temperature of -40℃ to +85℃, and the temperature inside the sealed chamber is kept constant at 25℃±0.1℃ using a constant temperature control unit.

[0032] Understandably, the flow sensor of this application possesses a multi-stage sealed transmission system. First, there is the primary seal: employing magnetohydrodynamic sealing technology, a liquid magnetic sealing ring is formed where the rotating shaft passes through the chamber wall, achieving a dynamic seal with zero friction and zero leakage. Then, the secondary transmission: inside the sealed chamber, a contactless magnetic coupling coupler transmits the rotation of the main shaft to the fiber optic gyroscope mounting platform, completely eliminating mechanical contact. Furthermore, precise temperature control is implemented: a precision temperature control system is integrated within the sealed chamber (maintaining a temperature of 25℃±0.1℃) to reduce the influence of ambient temperature.

[0033] In this embodiment, the flow velocity sensor flow velocity measurement method includes steps S10~S40: Step S10: Obtain the raw angular velocity signal output by the fiber optic gyroscope; It should be noted that in this embodiment, when using a flow velocity sensor to measure flow velocity, the fluid drives the impeller assembly to rotate. The rotational speed n is proportional to the liquid flow velocity v. The main shaft transmits the rotation to the sealed chamber through a magnetohydrodynamic seal, and then the magnetic coupling transmits the rotation to the sensitive axis of the fiber optic gyroscope. Next, the fiber optic gyroscope detects the rotational angular velocity ω and outputs a phase difference signal. The FPGA calculates the phase difference in real time to obtain the digital value of ω, which is the original angular velocity signal.

[0034] Step S20: Obtain real-time temperature data inside the sealed chamber collected by the temperature sensor; It should be noted that a temperature control unit is also integrated within the sealed chamber, which can maintain the internal temperature within a preset range (e.g., 25℃ ± 0.1℃) to reduce the impact of temperature fluctuations on measurements. However, changes in ambient temperature can cause variations in the temperature field distribution inside the fiber optic ring, leading to zero-bias drift and scaling factor errors in the fiber optic gyroscope. Therefore, continuous monitoring of the internal temperature of the sealed chamber is still possible, specifically through temperature acquisition using a temperature sensor integrated into the signal processing unit.

[0035] Step S30: Perform real-time compensation on the original angular velocity signal based on the real-time temperature data to obtain the target angular velocity value; It should be noted that, to reduce the impact of ambient temperature changes on the measurement accuracy of fiber optic gyroscopes, a mapping model between the fiber optic gyroscope's bias, scale factor, and temperature can be established through extensive experimental calibration. The signal processing unit dynamically corrects the fiber optic gyroscope output based on this established mapping model, achieving real-time compensation for bias and proportional errors, thereby improving the measurement stability, consistency, and long-term operating accuracy of the flow velocity sensor in a wide temperature range.

[0036] In one feasible approach, before the step of real-time compensation of the original angular velocity signal based on the real-time temperature data, the method further includes: acquiring the triaxial acceleration signal output by the accelerometer; determining the covariance matrix of the current vibration noise based on the triaxial acceleration signal; and performing Kalman filtering on the original angular velocity signal based on the covariance matrix to obtain the vibration-suppressed original angular velocity signal.

[0037] It's important to note that fiber optic gyroscopes operate based on the Sagnac effect, with the core principle being the detection of angular velocity using optical path difference. In vibrating environments, the fiber optic loop undergoes minute deformations or is subjected to mechanical stress disturbances. These disturbances are misinterpreted by the gyroscope as rotational signals, superimposed on the actual angular velocity measurement, resulting in significant vibration noise in the output signal. Without suppression, this vibration noise directly reduces the signal-to-noise ratio of the angular velocity measurement, thus affecting the accuracy of flow velocity calculations. Therefore, vibration suppression can be performed before temperature compensation.

[0038] When performing vibration suppression, the first step is to acquire the triaxial acceleration signal output from the accelerometer. The accelerometer, also integrated into the signal processing unit, is used to measure the acceleration values ​​of the sealed chamber in three orthogonal directions (X-axis, Y-axis, and Z-axis) in real time, representing the intensity and direction of the vibration. In actual industrial pipelines, fluid impact, pump operation, and valve actuation generate broadband mechanical vibrations, which are superimposed on the measurement signal from the fiber optic gyroscope, affecting measurement accuracy. The triaxial acceleration signal output from the accelerometer reflects the current vibration state of the sealed chamber. The signal processing unit then performs filtering preprocessing on the triaxial acceleration signal to extract the vibration characteristic components. Based on these vibration characteristic components, the covariance matrix of the current vibration noise is calculated. This covariance matrix quantifies the intensity and correlation of the current vibration noise in each direction, serving as the input parameters for subsequent Kalman filtering. The signal processing unit then uses a Kalman filter to fuse the accelerometer and fiber optic gyroscope data. The Kalman filter's prediction step predicts the current angular velocity state estimate based on the fiber optic gyroscope's system state equation and the aforementioned covariance matrix. The update step uses the original angular velocity signal output by the fiber optic gyroscope as a measurement, calculates the Kalman filter gain, and corrects the state estimate. Through Kalman filtering, the true rotation signal and vibration noise can be effectively separated, achieving a vibration suppression ratio of up to 60 dB (below 100 Hz), resulting in a vibration-suppressed original angular velocity signal, providing cleaner input data for subsequent temperature compensation.

[0039] The specific process of Kalman filtering begins with establishing a discrete-time system model for the Kalman filter, including state equations and observation equations. The state equations describe how the system state evolves over time, as follows:

[0040] in, is the system state vector at time k, which in this embodiment is the actual rotational angular velocity; It is the state transition matrix, describing the transition from k The state change from time 1 to time k; It is a control input matrix. It is a control vector; It is process noise, with a mean of zero and a covariance of... The normal distribution The process noise covariance matrix is ​​mainly determined by the vibration intensity and can be dynamically adjusted based on accelerometer data.

[0041] The observation equation, which describes the relationship between the system state and the sensor measurements, is as follows:

[0042] in, It is the measurement value vector at time k, which in this embodiment is the noisy raw angular velocity signal output by the fiber optic gyroscope; It is the observation matrix, which maps the real state space to the measurement space; It is observation noise, which follows a pattern with a mean of zero and a covariance of . The normal distribution The observation noise covariance matrix is ​​a deterministic matrix parameter used to quantify the intensity of observation noise. The larger the value, the less reliable the measurement value of the fiber optic gyroscope. It is usually preset to a fixed value.

[0043] After construction, the Kalman filter calculation process is divided into two stages: prediction and update. The prediction stage uses the optimal estimate from the previous time step to predict the state at the current time step. The state prediction formula for the prediction stage is:

[0044] in, This represents the prior state estimate at time k, predicted based on information from time k-1. This is the state transition matrix, which describes the evolution of the system state from time k-1 to k. In this embodiment, since the angular velocity can be considered constant or slowly changing in a short time, The element value can be 1; To control the input matrix, As the control vector, since there is no external control input in this embodiment, this term can be zero.

[0045] The formula for covariance prediction in the prediction phase is:

[0046] in, The covariance matrix represents the prior estimation error at time k obtained from the prediction, quantifying the uncertainty of the predicted value; Let represent the covariance matrix of the posterior estimation error at time k-1; State transition matrix The transpose of the matrix; This is the process noise covariance matrix, used to quantify the uncertainty of system model predictions. In this embodiment, Dynamically adjust based on the real-time triaxial acceleration signal output from the accelerometer: increase when the vibration intensity is high. This indicates a decrease in the confidence level of the predicted value; it decreases when the vibration is small. This indicates an increase in the confidence level of the predicted value.

[0047] Next comes the update phase, which uses the actual measurements from the fiber optic gyroscope at the current moment to correct the prior estimates obtained in the prediction phase, thus obtaining the optimal posterior estimate. The Kalman gain can be calculated first:

[0048] in, The Kalman gain matrix determines the weighting of the predicted and measured values ​​in the final estimate. The observation matrix maps the real state space to the measurement space. In this embodiment, since the dimensions of the state quantity angular velocity and the observed angular velocity are the same, The element value can be 1. Observation matrix The transpose of the matrix, The observation noise covariance matrix is ​​a deterministic matrix parameter used to quantify the intensity of observation noise. The larger the value, the less reliable the measurement value of the fiber optic gyroscope. It can be determined by the factory calibration of the fiber optic gyroscope.

[0049] Then comes the status update:

[0050] in, This is the optimal posterior state estimate at time k after measurement correction, i.e., the optimal angular velocity estimate after vibration suppression. is the actual measured value output by the fiber optic gyroscope at time k, i.e., the original angular velocity signal; is the measurement margin (or innovation). This indicates the deviation between the actual measured value and the expected measured value obtained based on the predicted state.

[0051] Finally, perform a covariance update:

[0052] in, I is the covariance matrix of the updated posterior estimation error at time k, used for the next filtering iteration; I is the identity matrix, and in this embodiment, since the state variable is a one-dimensional scalar, the element value of I is 1.

[0053] Step S40: Calculate the fluid velocity value based on the target angular velocity value.

[0054] It should be noted that, according to the principles of fluid mechanics, there is a linear relationship between the impeller rotation speed and the fluid velocity, that is, the flow velocity and angular velocity satisfy the relationship v = K·ω, where K is the calibration coefficient, v is the flow velocity, and ω is the angular velocity.

[0055] In one feasible approach, the step of calculating the fluid velocity value based on the target angular velocity value includes: obtaining a preset calibration coefficient; and calculating the fluid velocity value based on the target angular velocity value and the preset calibration coefficient.

[0056] It should be noted that a preset calibration coefficient K can be obtained. Coefficient K reflects the linear relationship between impeller speed and fluid velocity. The calibration coefficient K is determined through factory calibration by measuring the output of fiber optic gyroscopes at multiple velocity points on a standard flow meter and fitting a velocity-angular velocity curve. The velocity is then calculated using the formula for velocity versus angular velocity.

[0057] In one feasible approach, the angular velocity values ​​output by the fiber optic gyroscope corresponding to multiple preset flow velocity points are obtained; the preset flow velocity points are fitted with the corresponding angular velocity values ​​to generate a flow velocity-angular velocity correspondence curve; and calibration coefficients are determined based on the flow velocity-angular velocity correspondence curve.

[0058] It should be noted that during the factory calibration phase, the flow velocity sensor can be installed on a standard flow meter. The standard flow meter provides multiple precisely known flow velocity values. At each preset flow velocity point, after the flow velocity stabilizes, the angular velocity value output by the fiber optic gyroscope is recorded. To ensure calibration accuracy, each flow velocity point can be measured multiple times and the average value taken. A linear fit is then performed between multiple preset flow velocity points and their corresponding angular velocity values, plotted on the x-axis (or the x-axis) and y-axis (or the y-axis). Since there is a linear relationship between impeller speed and fluid velocity, the fitted result is a straight line passing through the origin, i.e., the flow velocity-angular velocity curve. The slope of the flow velocity-angular velocity curve is the coefficient K.

[0059] The flow velocity sensor in this embodiment includes an impeller assembly, a magnetohydrodynamic (MHD) sealing unit, a magnetic coupling, a fiber optic gyroscope, a signal processing unit, a temperature sensor, and an accelerometer. The impeller assembly is installed in a fluid pipeline. The main shaft of the impeller assembly rotatably passes through the MHD sealing unit and extends into the sealed chamber. The MHD sealing unit is disposed outside the chamber wall and sleeved on the main shaft. The magnetic coupling is disposed inside the sealed chamber and connected to the main shaft. The fiber optic gyroscope is installed inside the sealed chamber with its sensitive axis coaxially aligned with the main shaft. The signal processing unit is connected to the fiber optic gyroscope. The temperature sensor and the accelerometer are integrated into the signal processing unit. The sealed chamber integrates a constant temperature control unit and is filled with inert gas. The flow velocity measurement method of the flow velocity sensor includes: acquiring the raw angular velocity signal output by the fiber optic gyroscope; acquiring real-time temperature data inside the sealed chamber collected by the temperature sensor; performing real-time compensation on the raw angular velocity signal based on the real-time temperature data to obtain a target angular velocity value; and calculating the fluid velocity value based on the target angular velocity value. This embodiment uses a fiber optic gyroscope to measure the spindle rotational angular velocity instead of the traditional contact-type rotational speed measurement, and uses real-time temperature data to compensate for the original angular velocity signal of the fiber optic gyroscope in real time, thereby reducing the measurement error introduced by mechanical wear and temperature drift, and thus improving the measurement accuracy of fluid flow velocity.

[0060] Based on the first embodiment of this application, in the second embodiment of this application, the content that is the same as or similar to that in the first embodiment described above can be referred to the above description, and will not be repeated hereafter. Based on this, please refer to... Figure 4 Step S30 also includes steps S301 to S302: Step S301: Based on the real-time temperature data, obtain the zero offset compensation amount and scaling factor compensation amount corresponding to the current temperature from the preset temperature compensation model; It's important to note that zero bias refers to the deviation of the actual output value from the ideal zero point when the input angular velocity of the fiber optic gyroscope is zero (i.e., the spindle is stationary). Ideally, the output should be zero when stationary, but due to factors such as the birefringence effect of the fiber optic ring, thermal stress, and fluctuations in light source power, the actual output has a non-zero fixed bias. When the temperature changes, this bias drifts, known as zero bias temperature drift. The zero bias compensation is the correction value used to reduce this temperature drift, and its value is equal to the zero bias value measured at the current temperature. The scaling factor refers to the proportional relationship between the change in the output signal of the fiber optic gyroscope and the change in the actual input angular velocity, i.e., the output signal amplitude corresponding to a unit angular velocity. Theoretically, this proportional relationship should be a constant, but temperature changes can cause changes in parameters such as the geometric dimensions and refractive index of the fiber optic ring, resulting in scaling factor drift. The scaling factor compensation is the coefficient used to correct this proportional deviation.

[0061] To mitigate the impact of ambient temperature variations on the measurement accuracy of fiber optic gyroscopes, a mapping model between the gyroscope's bias, scale factor, and temperature can be established through extensive experimental calibration. Specifically, under different temperature points and rates of temperature change, the output characteristics of the fiber optic gyroscope are continuously sampled and analyzed to obtain the correspondence between bias drift, scale factor changes, and temperature parameters. A temperature compensation model is then constructed using polynomial fitting, piecewise linear fitting, or machine learning algorithms. During system operation, a built-in high-precision temperature sensor collects real-time temperature data from the sealed chamber. The signal processing unit dynamically corrects the fiber optic gyroscope output based on the established mapping relationship, achieving real-time compensation for bias error and proportional error. This significantly improves the sensor's measurement stability, consistency, and long-term operating accuracy under wide temperature conditions.

[0062] Understandably, after obtaining the preset temperature compensation model, the temperature can be substituted to obtain the zero bias compensation amount and the scaling factor compensation amount.

[0063] In one feasible approach, before the step of obtaining the zero bias compensation amount and scaling factor compensation amount corresponding to the current temperature from the preset temperature compensation model based on the real-time temperature data, the method further includes: calibrating the fiber optic gyroscope under different temperature conditions to obtain the zero bias value and scaling factor value corresponding to each temperature point; and establishing the preset temperature compensation model based on the correspondence between each temperature point and the corresponding zero bias value and scaling factor value.

[0064] It should be noted that during the factory calibration phase, the flow velocity sensor was placed in a high and low temperature test chamber, and calibration experiments were conducted on the fiber optic gyroscope module at multiple preset temperature points. At each temperature point, the fiber optic gyroscope module was kept stationary (input angular velocity was zero), and its output value was recorded as the zero bias value at that temperature point. Then, the spindle was driven to rotate at multiple known angular velocities, and the output value of the fiber optic gyroscope was recorded. The scaling factor value at that temperature point was obtained by fitting. A linear regression method or a piecewise linear fitting method was used to establish a zero bias temperature drift model and a scaling factor temperature model for the fiber optic gyroscope. Specifically, a zero bias-temperature mapping relationship was established with temperature T as the independent variable and the zero bias value Bias as the dependent variable; a scaling factor-temperature mapping relationship was established with temperature T as the independent variable and the scaling factor value Scale as the dependent variable. The above mapping relationships were stored in the storage unit of the signal processing unit in the form of a data table or fitting function to form a preset temperature compensation model.

[0065] In one feasible approach, the step of establishing a preset temperature compensation model based on the correspondence between each temperature point and its corresponding zero bias value and scaling factor value includes: performing piecewise fitting on each temperature point and its corresponding zero bias value to generate a zero bias-temperature mapping relationship; performing piecewise fitting on each temperature point and its corresponding scaling factor value to generate a scaling factor-temperature mapping relationship; and constructing a preset temperature compensation model based on the zero bias-temperature mapping relationship and the scaling factor-temperature mapping relationship.

[0066] It should be noted that, considering the nonlinear characteristics of the zero bias of the fiber optic gyroscope with temperature variation, a piecewise fitting method is adopted to improve modeling accuracy. The temperature range is divided into multiple intervals, and within each interval, polynomial fitting (such as quadratic or cubic polynomial) is used to fit the temperature point to the corresponding zero bias value, generating a zero bias-temperature sub-mapping relationship for each temperature interval. These sub-mapping relationships are then merged to form a complete zero bias-temperature mapping relationship. Similarly, the temperature range is divided into multiple intervals, and within each interval, polynomial fitting is used to fit the temperature point to the corresponding scaling factor value, generating a scaling factor-temperature sub-mapping relationship for each temperature interval. These sub-mapping relationships are then merged to form a complete scaling factor-temperature mapping relationship. The generated zero bias-temperature mapping relationships and scaling factor-temperature mapping relationships are integrated and stored in the signal processing unit's storage unit in the form of a data table or fitting function, forming a complete preset temperature compensation model.

[0067] Step S302: Correct the original angular velocity signal according to the zero bias compensation amount and the scaling factor compensation amount to obtain the target angular velocity value.

[0068] It should be noted that the corrected target angular velocity value is obtained by subtracting the zero-bias compensation amount from the original angular velocity signal and then multiplying it by the scale factor compensation amount. The formula is as follows:

[0069] in, This is the original angular velocity signal. For zero bias compensation, This is the scaling factor compensation amount. This represents the target angular velocity value.

[0070] This embodiment obtains the zero-bias compensation amount and scaling factor compensation amount corresponding to the current temperature from a preset temperature compensation model based on the real-time temperature data; the original angular velocity signal is then corrected according to the zero-bias compensation amount and the scaling factor compensation amount to obtain the target angular velocity value. This embodiment achieves independent compensation for the zero-bias error and scaling factor error of the fiber optic gyroscope, which can more accurately reduce the measurement error introduced by temperature, thereby effectively improving the accuracy and reliability of the compensated target angular velocity value.

[0071] For example, to help understand the implementation flow of the flow velocity sensor flow velocity measurement method obtained by combining this embodiment with the above embodiment one, please refer to... Figure 5 , Figure 5 A simplified flowchart of a flow velocity sensor method for measuring flow velocity is provided. Specifically, in a liquid pipeline, fluid drives an impeller to rotate, and the rotation is transmitted to a sealed chamber via a zero-friction seal through the rotating shaft. An angular velocity ω is measured by a fiber optic gyroscope in the sealed chamber, and then the flow velocity v = K * ω is calculated based on the system K, ultimately outputting v.

[0072] It should be noted that the above examples are only for understanding this application and do not constitute a limitation on the flow velocity sensor flow velocity measurement method of this application. Any simple modifications based on this technical concept are within the protection scope of this application.

[0073] This application also provides a flow velocity sensor and flow velocity measurement device, please refer to... Figure 6 The flow velocity sensor flow velocity measurement device includes: The acquisition module 10 is used to acquire the raw angular velocity signal output by the fiber optic gyroscope; The acquisition module 20 is used to acquire real-time temperature data inside the sealed chamber collected by the temperature sensor; The compensation module 30 is used to perform real-time compensation on the original angular velocity signal based on the real-time temperature data to obtain the target angular velocity value; The calculation module 40 is used to calculate the flow velocity of the fluid based on the target angular velocity value.

[0074] The flow velocity sensor in this embodiment includes an impeller assembly, a magnetohydrodynamic (MHD) sealing unit, a magnetic coupling, a fiber optic gyroscope, a signal processing unit, a temperature sensor, and an accelerometer. The impeller assembly is installed in a fluid pipeline. The main shaft of the impeller assembly rotatably passes through the MHD sealing unit and extends into the sealed chamber. The MHD sealing unit is disposed outside the chamber wall and sleeved on the main shaft. The magnetic coupling is disposed inside the sealed chamber and connected to the main shaft. The fiber optic gyroscope is installed inside the sealed chamber with its sensitive axis coaxially aligned with the main shaft. The signal processing unit is connected to the fiber optic gyroscope. The temperature sensor and the accelerometer are integrated into the signal processing unit. The sealed chamber integrates a constant temperature control unit and is filled with inert gas. The flow velocity measurement method of the flow velocity sensor includes: acquiring the raw angular velocity signal output by the fiber optic gyroscope; acquiring real-time temperature data inside the sealed chamber collected by the temperature sensor; performing real-time compensation on the raw angular velocity signal based on the real-time temperature data to obtain a target angular velocity value; and calculating the fluid velocity value based on the target angular velocity value. This embodiment uses a fiber optic gyroscope to measure the spindle rotational angular velocity instead of the traditional contact-type rotational speed measurement, and uses real-time temperature data to compensate for the original angular velocity signal of the fiber optic gyroscope in real time, thereby reducing the measurement error introduced by mechanical wear and temperature drift, and thus improving the measurement accuracy of fluid flow velocity.

[0075] In one embodiment, the compensation module 30 is further configured to obtain, based on the real-time temperature data, a zero-bias compensation amount and a scaling factor compensation amount corresponding to the current temperature from a preset temperature compensation model; and to correct the original angular velocity signal based on the zero-bias compensation amount and the scaling factor compensation amount to obtain a target angular velocity value.

[0076] In one embodiment, the compensation module 30 is further configured to calibrate the fiber optic gyroscope under different temperature conditions, obtain the zero bias value and scaling factor value corresponding to each temperature point, and establish a preset temperature compensation model based on the correspondence between each temperature point and the corresponding zero bias value and scaling factor value.

[0077] In one embodiment, the compensation module 30 is further configured to perform piecewise fitting between each temperature point and its corresponding zero bias value to generate a zero bias-temperature mapping relationship; perform piecewise fitting between each temperature point and its corresponding scaling factor value to generate a scaling factor-temperature mapping relationship; and construct a preset temperature compensation model based on the zero bias-temperature mapping relationship and the scaling factor-temperature mapping relationship.

[0078] In one embodiment, the compensation module 30 is further configured to acquire the triaxial acceleration signal output by the accelerometer; determine the covariance matrix of the current vibration noise based on the triaxial acceleration signal; and perform Kalman filtering on the original angular velocity signal based on the covariance matrix to obtain the original angular velocity signal after vibration suppression.

[0079] In one embodiment, the calculation module 40 is further configured to obtain a preset calibration coefficient; and calculate the flow velocity value of the fluid based on the target angular velocity value and the preset calibration coefficient.

[0080] In one embodiment, the calculation module 40 is further configured to obtain the angular velocity values ​​output by the fiber optic gyroscope corresponding to multiple preset flow velocity points; fit the preset flow velocity points with the corresponding angular velocity values ​​to generate a flow velocity-angular velocity correspondence curve; and determine the calibration coefficient based on the flow velocity-angular velocity correspondence curve.

[0081] The flow velocity sensor and flow velocity measurement device provided in this application, employing the flow velocity sensor and flow velocity measurement method described in the above embodiments, can solve the technical problem of how to improve the measurement accuracy of fluid flow velocity. Compared with the prior art, the beneficial effects of the flow velocity sensor and flow velocity measurement device provided in this application are the same as those of the flow velocity sensor and flow velocity measurement method provided in the above embodiments, and other technical features in the flow velocity sensor and flow velocity measurement device are the same as those disclosed in the methods of the above embodiments, and will not be repeated here.

[0082] This application provides a flow velocity sensor, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, which are executed by the at least one processor to enable the at least one processor to perform the flow velocity measurement method of the flow velocity sensor in Embodiment 1 above.

[0083] The following is for reference. Figure 7 The diagram illustrates a structural schematic of a flow velocity sensor suitable for implementing embodiments of this application. The flow velocity sensor in the embodiments of this application may include, but is not limited to, mobile terminals such as mobile phones, laptops, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and fixed terminals such as digital TVs and desktop computers. Figure 7 The flow rate sensor shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments of this application.

[0084] like Figure 7 As shown, the flow rate sensor may include a processing device 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in ROM (Read Only Memory) 1002 or a program loaded from storage device 1003 into RAM (Random Access Memory) 1004. RAM 1004 also stores various programs and data required for the operation of the flow rate sensor. The processing device 1001, ROM 1002, and RAM 1004 are interconnected via bus 1005. Input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to I / O interface 1006: input devices 1007 including, for example, touchscreens, touchpads, keyboards, mice, image sensors, microphones, accelerometers, gyroscopes, etc.; output devices 1008 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 1003 including, for example, magnetic tapes, hard disks, etc.; and communication devices 1009. The communication device 1009 allows the flow rate sensor to communicate wirelessly or wiredly with other devices to exchange data. While the figure shows flow rate sensors with various systems, it should be understood that implementation or possession of all the systems shown is not required. More or fewer systems may be implemented alternatively.

[0085] Specifically, according to the embodiments disclosed in this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device, or installed from storage device 1003, or installed from ROM 1002. When the computer program is executed by processing device 1001, it performs the functions defined in the methods of the embodiments disclosed in this application.

[0086] The flow velocity sensor provided in this application, employing the flow velocity measurement method described in the above embodiments, can solve the technical problem of how to improve the measurement accuracy of fluid flow velocity. Compared with the prior art, the beneficial effects of the flow velocity sensor provided in this application are the same as those of the flow velocity measurement method provided in the above embodiments, and other technical features of this flow velocity sensor are the same as those disclosed in the previous embodiment method, and will not be repeated here.

[0087] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0088] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0089] This application provides a computer-readable storage medium having computer-readable program instructions (i.e., a computer program) stored thereon, which are used to execute the flow velocity sensor flow velocity measurement method in the above embodiments.

[0090] The computer-readable storage medium provided in this application may be, for example, a USB flash drive, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, system, or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.

[0091] The aforementioned computer-readable storage medium may be included in the flow rate sensor; or it may exist independently and not assembled into the flow rate sensor.

[0092] The aforementioned computer-readable storage medium carries one or more programs that, when executed by the flow velocity sensor, cause the flow velocity sensor to: acquire the raw angular velocity signal output by the fiber optic gyroscope; acquire real-time temperature data inside the sealed chamber collected by the temperature sensor; perform real-time compensation on the raw angular velocity signal based on the real-time temperature data to obtain a target angular velocity value; and calculate the fluid velocity value based on the target angular velocity value.

[0093] Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a Local Area Network (LAN) or a Wide Area Network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0094] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0095] The modules described in the embodiments of this application can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself.

[0096] The readable storage medium provided in this application is a computer-readable storage medium that stores computer-readable program instructions (i.e., a computer program) for executing the above-described flow velocity sensor flow velocity measurement method, thereby solving the technical problem of how to improve the measurement accuracy of fluid flow velocity. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as those of the flow velocity sensor flow velocity measurement method provided in the above embodiments, and will not be repeated here.

[0097] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the flow velocity sensor flow velocity measurement method as described above.

[0098] The computer program product provided in this application can solve the technical problem of how to improve the measurement accuracy of fluid flow velocity. Compared with the prior art, the beneficial effects of the computer program product provided in this application are the same as those of the flow velocity sensor flow velocity measurement method provided in the above embodiments, and will not be repeated here.

[0099] The above description is only a part of the embodiments of this application and does not limit the patent scope of this application. All equivalent structural transformations made under the technical concept of this application and using the contents of the specification and drawings of this application, or direct / indirect applications in other related technical fields, are included in the patent protection scope of this application.

Claims

1. A flow velocity sensor and flow velocity measurement method, characterized in that, The flow velocity sensor includes an impeller assembly, a magnetohydrodynamic sealing unit, a magnetic coupling coupling, a fiber optic gyroscope, a signal processing unit, a temperature sensor, and an accelerometer. The impeller assembly is installed in a fluid pipeline. The main shaft of the impeller assembly rotatably passes through the magnetohydrodynamic sealing unit and extends into the sealed chamber. The magnetohydrodynamic sealing unit is disposed outside the chamber wall of the sealed chamber and sleeved on the main shaft. The magnetic coupling coupling is disposed inside the sealed chamber and connected to the main shaft. The fiber optic gyroscope is installed inside the sealed chamber with its sensitive axis coaxially aligned with the main shaft. The signal processing unit is connected to the fiber optic gyroscope. The temperature sensor and the accelerometer are integrated into the signal processing unit. The sealed chamber integrates a constant temperature control unit and is filled with inert gas. The flow velocity sensor flow velocity measurement method includes: Obtain the raw angular velocity signal output by the fiber optic gyroscope; Acquire real-time temperature data inside the sealed chamber collected by the temperature sensor; The original angular velocity signal is compensated in real time based on the real-time temperature data to obtain the target angular velocity value; The fluid velocity is calculated based on the target angular velocity value.

2. The method as described in claim 1, characterized in that, The step of real-time compensation of the original angular velocity signal based on the real-time temperature data includes: Based on the real-time temperature data, the zero-bias compensation amount and scale factor compensation amount corresponding to the current temperature are obtained from the preset temperature compensation model; The original angular velocity signal is corrected based on the zero bias compensation amount and the scaling factor compensation amount to obtain the target angular velocity value.

3. The method as described in claim 2, characterized in that, Before the step of obtaining the zero-bias compensation amount and scaling factor compensation amount corresponding to the current temperature from the preset temperature compensation model based on the real-time temperature data, the method further includes: The fiber optic gyroscope was calibrated under different temperature conditions to obtain the zero bias value and scaling factor value corresponding to each temperature point. A preset temperature compensation model is established based on the correspondence between each temperature point and its corresponding zero bias value and scaling factor value.

4. The method as described in claim 3, characterized in that, The step of establishing a preset temperature compensation model based on the correspondence between each temperature point and its corresponding zero bias and scaling factor values ​​includes: A piecewise fitting is performed between each temperature point and its corresponding zero bias value to generate a zero bias-temperature mapping relationship. Piecewise fitting is performed on each temperature point and its corresponding scaling factor value to generate a scaling factor-temperature mapping relationship; A preset temperature compensation model is constructed based on the zero bias-temperature mapping relationship and the scaling factor-temperature mapping relationship.

5. The method as described in claim 1, characterized in that, Before the step of real-time compensation of the original angular velocity signal based on the real-time temperature data, the method further includes: Acquire the triaxial acceleration signal output by the accelerometer; The covariance matrix of the current vibration noise is determined based on the triaxial acceleration signal. The original angular velocity signal is subjected to Kalman filtering based on the covariance matrix to obtain the original angular velocity signal after vibration suppression.

6. The method as described in claim 1, characterized in that, The step of calculating the fluid velocity value based on the target angular velocity value includes: Obtain the preset calibration coefficients; The fluid velocity is calculated based on the target angular velocity value and the preset calibration coefficient.

7. The method as described in claim 6, characterized in that, Before obtaining the preset calibration coefficients, the process also includes: Obtain the angular velocity values ​​output by the fiber optic gyroscope corresponding to multiple preset flow velocity points; The preset flow velocity point is fitted with the corresponding angular velocity value to generate a flow velocity-angular velocity correspondence curve. The calibration coefficients are determined based on the flow velocity-angular velocity correspondence curve.

8. A flow velocity sensor and flow velocity measurement device, characterized in that, The device includes: The acquisition module is used to acquire the raw angular velocity signal output by the fiber optic gyroscope. The data acquisition module is used to acquire real-time temperature data inside the sealed chamber collected by the temperature sensor. The compensation module is used to perform real-time compensation on the original angular velocity signal based on the real-time temperature data to obtain the target angular velocity value; The calculation module is used to calculate the flow velocity of the fluid based on the target angular velocity value.

9. A flow velocity sensor, characterized in that, The flow velocity sensor includes an impeller assembly, a magnetohydrodynamic sealing unit, a magnetic coupling coupling, a fiber optic gyroscope, a signal processing unit, a temperature sensor, and an accelerometer. The impeller assembly is installed in a fluid pipeline. The main shaft of the impeller assembly rotatably passes through the magnetohydrodynamic sealing unit and extends into the sealed chamber. The magnetohydrodynamic sealing unit is disposed outside the chamber wall of the sealed chamber and sleeved on the main shaft. The magnetic coupling coupling is disposed inside the sealed chamber and connected to the main shaft. The fiber optic gyroscope is installed inside the sealed chamber with its sensitive axis coaxially aligned with the main shaft. The signal processing unit is connected to the fiber optic gyroscope. The temperature sensor and the accelerometer are integrated into the signal processing unit. The sealed chamber integrates a constant temperature control unit and is filled with inert gas. The flow velocity sensor further includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the flow velocity sensor flow velocity measurement method as described in any one of claims 1 to 7.

10. A storage medium, characterized in that, The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, it implements the flow velocity sensor flow velocity measurement method as described in any one of claims 1 to 7.

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