Flow velocity measuring and monitoring method and device based on acoustic principle

Abstract

The invention relates to the technical field of flow velocity measurement, in particular to a flow velocity measurement monitoring method and device based on the acoustic principle, and the method comprises the steps that a transmitting end generates a control instruction according to a control unit, the control instruction comprises a modulation parameter and transmitting power, and generates an acoustic wave signal according to the control instruction; transmitting the sound wave signal in the target liquid medium; a receiving end receives the sound wave signal and obtains a pure signal of the sound wave signal according to a blind source separation technology; and performing spectral analysis on the pure signal to obtain Doppler frequency shift and time difference corresponding to the pure signal. According to the method, Doppler frequency shift and time difference information is obtained through spectral analysis, state estimation is carried out in combination with extended Kalman filtering, high-precision estimation of the flow velocity in the target liquid medium can be achieved, the extended Kalman filtering can effectively solve the state estimation problem in a nonlinear system, the precision of flow velocity estimation is further improved, and the method is suitable for large-scale popularization and application. And the limitation of the traditional method is overcome.

Description

Technical Field

[0001] The invention relates to the technical field of flow velocity measurement, and in particular to a flow velocity measurement and monitoring method and device based on acoustic principles. Background Art

[0002] Acoustic principles refer to the basic principles of sound generation, propagation, reception and their interaction.

[0003] Some flow rate measuring instruments in traditional methods, such as mechanical flow meters, may have large measurement errors due to factors such as wear of mechanical parts and changes in resistance. Even electronic flow meters may be affected by external interference, equipment aging and other issues, which may affect the measurement accuracy. Traditional methods are usually highly dependent on the characteristics of the fluid medium. Some methods require stable environmental conditions to ensure accurate measurements, and may not work effectively in changeable or extreme environments, or may require additional calibration and maintenance. Summary of the invention

[0004] The technical problem to be solved by the present invention is to overcome the shortcomings of the above-mentioned prior art and provide a flow velocity measurement and monitoring method and device based on acoustic principles.

[0005] The technical solution adopted to solve the above technical problems is: a flow velocity measurement and monitoring method based on acoustic principles, including: The transmitting end generates a control instruction according to the control unit, wherein the control instruction includes a modulation parameter and a transmitting power, generates an acoustic wave signal according to the control instruction, and propagates the acoustic wave signal in the target liquid medium; The receiving end receives the sound wave signal and processes the pure signal of the sound wave signal according to the blind source separation technology; Performing spectrum analysis on the pure signal to obtain Doppler frequency shift and time difference corresponding to the pure signal; An observation vector is constructed according to the Doppler frequency shift and the time difference, and a state estimation is performed on the observation vector according to an extended Kalman filter to obtain an estimated flow velocity.

[0006] Preferably, generating a sound wave signal according to the control instruction includes: The control instruction is input into a waveform generator to generate a multi-frequency orthogonal signal, wherein the waveform generator is expressed as follows: ; in, represents a multi-frequency orthogonal signal, Indicates the number of subcarriers, Indicates The amplitude adjustment of the subcarriers, represents the center frequency, represents the subcarrier spacing, represents the symbol period, represents a rectangular function; The multi-frequency orthogonal acoustic wave signal is input into a power amplifier to obtain an amplified multi-frequency orthogonal signal, wherein the expression of the power amplifier is as follows: ; in, represents the amplified power, represents the reference power, Represents the temperature coefficient of acoustic impedance, which is used to compensate for the effect of temperature on sound wave propagation. Indicates the current temperature. Indicates the reference temperature; The amplified multi-frequency orthogonal signal is input into the piezoelectric transducer array for acoustic wave conversion to obtain an acoustic wave signal.

[0007] Preferably, the pure signal of the acoustic wave signal according to the blind source separation technology includes: The acoustic wave signal is subjected to space-time sampling to obtain a sampling signal in the space and time domains, wherein the expression of the sampling signal is as follows: ; in, represents the sampling signal, represents the time sampling interval, Indicates the number of sampling points, Represents the first sub-sound wave signal of the sound wave signal obtained by space-time sampling; Separating the sampled signal into independent source signals according to a preset transformation matrix; The source signal is inversely transformed from the frequency domain to the time domain to obtain a pure signal of the sound wave signal.

[0008] Preferably, performing spectrum analysis on the pure signal to obtain Doppler frequency shift and time difference corresponding to the pure signal includes: The Doppler frequency shift of the pure signal is calculated, wherein the expression of the Doppler frequency shift is as follows: ; in, represents the time difference of the pure signal, represents the center frequency, represents the flow velocity to be estimated, represents the observation angle, represents the speed of light; Calculate the time difference of the pure signal, where the expression of the time difference is as follows: ; in, represents the time difference of the pure signal, Indicates the distance between the sender and the receiver.

[0009] Preferably, the expression of the observation vector is as follows: ; in, represents the observation vector.

[0010] Preferably, performing state estimation on the observation vector according to an extended Kalman filter to obtain an estimated flow velocity sequence includes: An observation equation is constructed according to the observation vector, wherein the expression of the observation equation is as follows: ; in, Indicated in The observed value at the moment, Indicated in The observation model for estimating flow velocity at a given moment, Indicated in Observe the noise at all times; The observation residual is calculated according to the observation equation, wherein the calculation formula of the observation residual is as follows: ; in, represents the observation residual; The Kalman gain is calculated, where the expression of the Kalman gain is as follows: ; in, represents the Kalman gain, which represents the weight of the new observation information in the estimation, represents the prediction covariance matrix, represents the observation matrix, represents the observation noise covariance matrix; The flow rate estimation is updated according to the Kalman gain, wherein the updating formula of the flow rate estimation is as follows: ; in, Represents the updated flow velocity estimate.

[0011] The technical solution adopted to solve the above technical problems is: a flow velocity measurement and monitoring device based on acoustic principle, which is applicable to the flow velocity measurement and monitoring method based on acoustic principle, including: An acoustic wave generating unit, wherein the acoustic wave generating unit is used for generating a control instruction at the transmitting end according to the control unit, wherein the control instruction includes a modulation parameter and a transmitting power, and generating an acoustic wave signal according to the control instruction, so that the acoustic wave signal propagates in the target liquid medium, and propagating the acoustic wave signal in the target liquid medium; An acoustic wave purification unit, wherein the acoustic wave purification unit is used for receiving the acoustic wave signal at a receiving end, and separating the acoustic wave signal into a pure signal according to a blind source separation technology; A spectrum analysis unit, the spectrum analysis unit is used to perform spectrum analysis on the pure signal to obtain Doppler frequency shift and time difference corresponding to the pure signal; A flow velocity estimation unit is used to construct an observation vector according to the Doppler frequency shift and the time difference, and perform state estimation on the observation vector according to an extended Kalman filter to obtain an estimated flow velocity.

[0012] The beneficial effects of the present invention are as follows: (1) The present invention obtains Doppler frequency shift and time difference information through spectrum analysis, and combines it with extended Kalman filtering (EKF) for state estimation, so as to achieve high-precision estimation of flow velocity in the target liquid medium. Extended Kalman filtering can effectively deal with the state estimation problem in nonlinear systems, further improve the accuracy of flow velocity estimation, overcome the limitations of traditional methods, and use blind source separation technology to extract pure signals from received sound wave signals, effectively eliminate noise and interference, and improve the stability and accuracy of the measurement system in complex environments. In particular, when there are multiple interference sources or background noise in the liquid, blind source separation technology can independently extract useful signals and reduce the influence of external interference on the measurement results. (2) The present invention is suitable for complex environments where it is difficult to access or impossible to directly measure the flow velocity, for example, It can be used in scenarios such as pipelines, groundwater flows, and rivers. It can monitor flow rate without direct contact with the measured fluid, thus avoiding the limitations and risks brought by physical contact in traditional methods. In addition, the extended Kalman filter can be used to quickly estimate the state based on the acoustic signal received in real time. Therefore, this method has good real-time performance, can continuously monitor according to dynamic flow rate changes, and quickly give flow rate estimation results, which is suitable for real-time flow rate monitoring needs. (3) The present invention realizes flow rate measurement through the propagation and reception of acoustic wave signals. It does not require physical sensors commonly found in traditional flow meters (such as flow meters, pressure sensors, etc.). By reasonably adjusting the transmission power and modulation parameters in the control instructions, it can reduce energy consumption while ensuring sufficient signal quality, so that the method can also operate stably in environments that require long-term monitoring or are energy-constrained. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 A schematic flow chart of the steps of an overall method in an embodiment of the present invention; Figure 2 A schematic diagram of the device architecture of an overall device in an embodiment of the present invention.

[0014] Figure numerals: 1. Sound wave generating unit; 2. Sound wave purification unit; 3. Spectrum analyzing unit; 4. Flow rate estimating unit. DETAILED DESCRIPTION

[0015] Embodiment 1, as Figure 1 As shown, the flow velocity measurement and monitoring method based on acoustic principle proposed by the present invention includes: S1. The transmitting end generates a control instruction according to the control unit, wherein the control instruction includes a modulation parameter and a transmission power, and generates an acoustic wave signal according to the control instruction, so that the acoustic wave signal propagates in the target liquid medium; S2, the receiving end receives the sound wave signal, and separates the sound wave signal into a pure signal according to the blind source separation technology; S3, performing spectrum analysis on the pure signal to obtain the Doppler frequency shift and time difference corresponding to the pure signal; S4. Construct an observation vector according to the Doppler frequency shift and the time difference, and perform state estimation on the observation vector according to the extended Kalman filter to obtain an estimated flow velocity.

[0016] In the present invention, the control unit is a device or system used to control the work of other components. It generates control instructions according to preset requirements to ensure that the entire system works as expected. In this system, the control unit will generate instructions for modulation parameters and transmission power to determine the characteristics of the sound wave signal; modulation parameters refer to parameters used to adjust certain characteristics of the signal (such as frequency, phase, amplitude, etc.) during signal transmission. In acoustic flow velocity measurement, modulation parameters may include the slope of the frequency modulation signal, the frequency variation range, etc., which affect the characteristics of signal propagation and thus affect the accuracy of flow velocity measurement; transmission power refers to the energy generated by the sound wave signal at the transmitting end; the sound wave signal is a mechanical wave propagated through a material medium; the target liquid medium refers to the liquid environment in which the sound wave signal propagates, such as water, oil or other liquids. The propagation speed of the sound wave in the medium is related to the physical properties of the medium (such as density, temperature, etc.), which affects the measurement results; the receiving end is the receiving device in the system, Responsible for receiving the sound wave signal transmitted through the liquid and transmitting the signal to the processing unit for analysis; blind source separation technology is a signal processing method used to extract independent source signals from mixed signals. Here, it is used to extract pure signals from the received sound wave signals, that is, to remove noise and interference and retain useful signal information; pure signal refers to the part extracted from the received mixed signal that contains the target information, removing unnecessary components such as noise and interference. In flow velocity measurement, the pure signal corresponds to the signal related to the flow velocity in the target liquid medium; spectrum analysis is the analysis process of the signal in the frequency domain. Through spectrum analysis, the intensity distribution of each frequency component in the signal can be viewed; Doppler shift refers to the change in the frequency of the signal when the source or receiver of the sound wave signal moves relative to each other; time difference refers to the time difference experienced by the signal from transmission to reception; extended Kalman filtering is an algorithm for state estimation of nonlinear systems. It is a recursive filtering technology that continuously updates the state of the system by comparing the prediction of the system state with the actual observation value. In flow velocity measurement, EKF is used to estimate the flow velocity based on the observation vector, and obtain a more accurate flow velocity estimate by continuously correcting the predicted value; state estimation refers to the process of estimating the state of a dynamic system.

[0017] Embodiment 2, the flow velocity measurement and monitoring method based on acoustic principle proposed by the present invention, compared with embodiment 1, this embodiment further includes: generating an acoustic wave signal according to a control instruction, including: A1. Input the control instruction to the waveform generator to generate a multi-frequency orthogonal signal, wherein the expression of the waveform generator is as follows: ; in, represents a multi-frequency orthogonal signal, Indicates the number of subcarriers, Indicates Amplitude modulation of subcarriers, represents the center frequency, represents the subcarrier spacing, represents the symbol period, represents a rectangular function; A2. Input the multi-frequency orthogonal sound wave signal into a power amplifier to obtain an amplified multi-frequency orthogonal signal, wherein the expression of the power amplifier is as follows: ; in, represents the amplified power, Indicates the reference power Represents the temperature coefficient of acoustic impedance, which is used to compensate for the effect of temperature on sound wave propagation. Indicates the current temperature. Indicates the reference temperature; A3. Input the amplified multi-frequency orthogonal signal to the piezoelectric transducer array for acoustic wave conversion to obtain an acoustic wave signal.

[0018] In this embodiment, the waveform generator is a device for generating a specific type of signal. It can generate various waveforms (such as sine waves, square waves, triangle waves, etc.). In this case, it is used to generate multi-frequency orthogonal signals. The task of the waveform generator is to generate signals with required frequency and amplitude modulation for subsequent system processing; multi-frequency orthogonal signals refer to signals composed of multiple frequencies. These signals are orthogonal. Orthogonality means that each signal is mathematically independent and will not interfere with each other. In communication and acoustic applications, orthogonal signals can be transmitted on the same channel at different frequencies, thereby improving the transmission efficiency of the system; the number of subcarriers refers to the number of frequency subcarriers used in the multi-frequency orthogonal signal; amplitude modulation (Amplitude AM) is a way of signal modulation, which transmits information by changing the amplitude of the signal; the center frequency refers to the main frequency component of the signal or waveform; the subcarrier interval refers to the frequency difference between two adjacent subcarriers; the symbol period refers to the length of time occupied by each symbol (information unit) in the signal; the rectangular function is a function with two states, non-zero and zero, and is usually used to represent the switch or pulse shape of the time domain signal; the piezoelectric transducer array is a group of transducers made of piezoelectric materials, which can convert electrical signals into mechanical vibrations (sound waves), or convert received sound wave signals into electrical signals.

[0019] In an optional embodiment, the pure signal of the acoustic wave signal is separated by blind source separation technology, including: B1. Perform space-time sampling on the sound wave signal to obtain a sampling signal in the space and time domains, wherein the expression of the sampling signal is as follows: ; in, represents the sampling signal, represents the time sampling interval, Indicates the number of sampling points, Represents the first sub-sound wave signal of the sound wave signal obtained by space-time sampling; B2, separating the sampled signal into independent source signals according to a preset transformation matrix; B3. Perform an inverse transform from the frequency domain to the time domain on the source signal to obtain a pure signal of the sound wave signal.

[0020] It should be noted that space-time sampling refers to the sampling of signals in both space and time dimensions, which means capturing signals within a specific time interval (time domain sampling) and at different spatial locations (spatial domain sampling). Space-time sampling is usually applied to multiple sensor arrays to collect signal data at different points in space and time in order to analyze and process more complex signals; the transformation matrix is ​​a matrix used to transform signals mathematically. Common transformations include Fourier transform, discrete cosine transform, etc. In this context, the transformation matrix is ​​used to transform the sampled signal in the time and space domain into another form, which may be the frequency domain or other forms, so as to better separate and extract independent source signals from it; the inverse transformation from frequency domain to time domain refers to the process of converting the signal from the frequency domain (i.e., the domain that describes the frequency characteristics of the signal) back to the time domain (i.e., the domain that describes the change of the signal over time).

[0021] In an optional embodiment, spectrum analysis is performed on the pure signal to obtain the Doppler frequency shift and time difference corresponding to the pure signal, including: C1. Calculate the Doppler frequency shift of the pure signal, where the expression of the Doppler frequency shift is as follows: ; in, represents the time difference of the pure signal, represents the center frequency, represents the flow velocity to be estimated, represents the observation angle, represents the speed of light; C2. Calculate the time difference of the pure signal, where the expression of the time difference is as follows: ; in, represents the time difference of the pure signal, Indicates the distance between the sender and the receiver.

[0022] In an optional embodiment, the expression of the observation vector is as follows: ; in, represents the observation vector.

[0023] In an optional embodiment, state estimation is performed on the observation vector according to an extended Kalman filter to obtain an estimated flow velocity sequence, including: D1. Construct the observation equation based on the observation vector, where the expression of the observation equation is as follows: ; in, Indicated in The observed value at the moment, Indicated in The observation model for estimating flow velocity at a given moment, Indicated in Observe the noise at all times; D2. Calculate the observation residual according to the observation equation, where the calculation formula of the observation residual is as follows: ; in, represents the observation residual; D3. Calculate the Kalman gain, where the expression of the Kalman gain is as follows: ; in, represents the Kalman gain, which represents the weight of the new observation information in the estimation, represents the prediction covariance matrix, represents the observation matrix, represents the observation noise covariance matrix; D4. Update the flow rate estimate according to the Kalman gain, where the update formula of the flow rate estimate is as follows: ; in, Represents the updated flow velocity estimate.

[0024] It should be noted that the observation vector refers to the measurement value obtained from the system at a specific point in time, usually expressed as a column vector, which contains all the observation data collected by sensors or measuring devices; observation noise is noise related to factors such as errors in the measurement system and sensor accuracy, and it cannot be completely eliminated; Kalman gain is a trade-off factor that determines the weight of new observation data when updating the estimate. The Kalman gain reflects how to adjust the estimate based on the uncertainty of the prediction (i.e., the covariance matrix) and the accuracy of the observation (i.e., the observation noise); the prediction covariance matrix is ​​an important concept in Kalman filtering, which represents the uncertainty of the current state estimate. In Kalman filtering, each time the state is updated, the prediction covariance matrix provides a measure of the uncertainty of the future state estimate; in Kalman filtering, the process of updating the flow velocity estimate is to combine the observation residual with the predicted value through the Kalman gain to obtain a more accurate flow velocity estimate.

[0025] Embodiment three, as Figure 2 As shown, the flow velocity measurement and monitoring device based on acoustic principle proposed by the present invention is applicable to the flow velocity measurement and monitoring method based on acoustic principle, comprising: The acoustic wave generating unit 1 is used for the transmitting end to generate a control instruction according to the control unit, wherein the control instruction includes a modulation parameter and a transmitting power, and to generate an acoustic wave signal according to the control instruction, so that the acoustic wave signal propagates in the target liquid medium. The sound wave purification unit 2 is used for receiving the sound wave signal at the receiving end, and separating the sound wave signal into a pure signal according to the blind source separation technology; The spectrum analysis unit 3 is used to perform spectrum analysis on the pure signal to obtain the Doppler frequency shift and time difference corresponding to the pure signal; The flow velocity estimation unit 4 is used to construct an observation vector according to the Doppler frequency shift and the time difference, and perform state estimation on the observation vector according to the extended Kalman filter to obtain an estimated flow velocity.

[0026] The embodiments of the present invention are described in detail above with reference to the accompanying drawings, but the present invention is not limited thereto, and various changes can be made within the knowledge scope of technicians in the relevant technical field without departing from the purpose of the present invention.

Claims

1. A flow velocity measurement and monitoring method based on acoustic principle, characterized in that: include: The transmitting end generates a control instruction according to the control unit, wherein the control instruction includes a modulation parameter and a transmission power, and generates an acoustic wave signal according to the control instruction, so that the acoustic wave signal propagates in the target liquid medium; The receiving end receives the sound wave signal and processes the pure signal of the sound wave signal according to the blind source separation technology; Performing spectrum analysis on the pure signal to obtain Doppler frequency shift and time difference corresponding to the pure signal; An observation vector is constructed according to the Doppler frequency shift and the time difference, and a state estimation is performed on the observation vector according to an extended Kalman filter to obtain an estimated flow velocity.

2. The flow velocity measurement and monitoring method based on acoustic principle according to claim 1 is characterized in that: Generating a sound wave signal according to the control instruction includes: The control instruction is input into a waveform generator to generate a multi-frequency orthogonal signal, wherein the waveform generator is expressed as follows: ； in, represents a multi-frequency orthogonal signal, Indicates the number of subcarriers, Indicates Amplitude modulation of subcarriers, represents the center frequency, represents the subcarrier spacing, represents the symbol period, represents a rectangular function; The multi-frequency orthogonal acoustic wave signal is input into a power amplifier to obtain an amplified multi-frequency orthogonal signal, wherein the expression of the power amplifier is as follows: ； in, represents the amplified power, represents the reference power, Represents the temperature coefficient of acoustic impedance, which is used to compensate for the effect of temperature on sound wave propagation. Indicates the current temperature. Indicates the reference temperature; The amplified multi-frequency orthogonal signal is input into the piezoelectric transducer array for acoustic wave conversion to obtain an acoustic wave signal.

3. The flow velocity measurement and monitoring method based on acoustic principle according to claim 2 is characterized in that: The pure signal of the acoustic wave signal according to the blind source separation technology includes: The acoustic wave signal is subjected to space-time sampling to obtain a sampling signal in the space and time domains, wherein the expression of the sampling signal is as follows: ； in, represents the sampling signal, represents the time sampling interval, Indicates the number of sampling points, Represents the first sub-sound wave signal of the sound wave signal obtained by space-time sampling; Separating the sampled signal into independent source signals according to a preset transformation matrix; The source signal is inversely transformed from the frequency domain to the time domain to obtain a pure signal of the sound wave signal.

4. The flow velocity measurement and monitoring method based on acoustic principle according to claim 3 is characterized in that: Performing spectrum analysis on the pure signal to obtain Doppler frequency shift and time difference corresponding to the pure signal includes: The Doppler frequency shift of the pure signal is calculated, wherein the expression of the Doppler frequency shift is as follows: ； in, represents the time difference of the pure signal, represents the center frequency, represents the flow rate to be estimated, represents the observation angle, represents the speed of light; Calculate the time difference of the pure signal, where the expression of the time difference is as follows: ； in, represents the time difference of the pure signal, Indicates the distance between the sender and the receiver.

5. The flow velocity measurement and monitoring method based on acoustic principle according to claim 4 is characterized in that: The expression of the observation vector is as follows: ； in, represents the observation vector.

6. The flow velocity measurement and monitoring method based on acoustic principle according to claim 5 is characterized in that: The state of the observation vector is estimated according to the extended Kalman filter to obtain an estimated flow velocity sequence, including: An observation equation is constructed according to the observation vector, wherein the expression of the observation equation is as follows: ； in, Indicated in The observed value at time, Indicated in The observation model for estimating flow velocity at a given moment, Indicated in Observe the noise at all times; The observation residual is calculated according to the observation equation, wherein the calculation formula of the observation residual is as follows: ； in, represents the observation residual; The Kalman gain is calculated, where the expression of the Kalman gain is as follows: ； in, represents the Kalman gain, which represents the weight of the new observation information in the estimation, represents the prediction covariance matrix, represents the observation matrix, represents the observation noise covariance matrix; The flow rate estimate is updated according to the Kalman gain, wherein the update formula of the flow rate estimate is as follows: ； in, Represents the updated flow velocity estimate.

7. A flow velocity measurement and monitoring device based on acoustic principle, which is applicable to the flow velocity measurement and monitoring method based on acoustic principle as claimed in any one of claims 1 to 6, characterized in that: include: An acoustic wave generating unit (1), the acoustic wave generating unit (1) being used for generating a control instruction at a transmitting end according to a control unit, wherein the control instruction comprises a modulation parameter and a transmitting power, and generating an acoustic wave signal according to the control instruction so that the acoustic wave signal propagates in a target liquid medium; A sound wave purification unit (2), the sound wave purification unit (2) is used for receiving the sound wave signal at a receiving end, and processing a pure signal of the sound wave signal according to a blind source separation technology; A spectrum analysis unit (3), the spectrum analysis unit (3) being used to perform spectrum analysis on the pure signal to obtain a Doppler frequency shift and a time difference corresponding to the pure signal; A flow velocity estimation unit (4), the flow velocity estimation unit (4) is used to construct an observation vector according to the Doppler frequency shift and the time difference, and perform state estimation on the observation vector according to an extended Kalman filter to obtain an estimated flow velocity.

Images