High-precision measuring method of radar flowmeter

Abstract

The invention provides a high-precision measuring method of a radar flowmeter. The high-precision measuring method comprises the steps that flow is calculated according to the section area and the section flow velocity of a pipe network; wherein the step of calculating the section area of the pipe network corresponding to the measuring point comprises the following steps: acquiring a discrete liquid level intermediate frequency signal; extracting a target spectral range; performing spectral analysis, and calculating to obtain a space height between the liquid level and the radar sensor; calculating to obtain a pipe network section area; the section flow velocity calculation comprises the following steps: acquiring a discrete speed intermediate frequency signal; performing frequency spectrum estimation processing, and extracting a target frequency interval; estimating an actual peak value frequency point position in the target frequency interval to obtain a frequency estimation value; and calculating the section flow velocity according to the frequency estimation value. According to the high-precision measurement method of the radar flowmeter, the number of frequency points needing to be processed is reduced, the memory needed for storing intermediate data is reduced, and the measurement precision is effectively improved under the condition that the hardware condition is limited; the algorithm is simplified, the calculation amount is reduced, the hardware requirement is reduced, and the cost is saved.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of radar flowmeter, in particular to a high-precision measurement method of radar flowmeter. BACKGROUND

[0002] With the continuous development of electronic information technology, artificial intelligence and urbanization, traditional cities are moving towards smart cities, and water resource management, water environment protection and waterlogging prevention are the key points for evaluating smart cities. Therefore, obtaining various physical parameters of urban hydrology is particularly important for evaluating smart cities. Flow information, as an important parameter in hydrological monitoring, is of great significance for understanding water movement and reasonably controlling the use of water resources.

[0003] The propagation of electromagnetic waves is not affected by air temperature, humidity, pressure, dust and steam. Using electromagnetic waves to measure water level and flow rate is actually a problem of spectrum estimation of difference frequency signals. The current common processing method is to use band selection fast Fourier transform algorithm for spectrum estimation. This method has the following problems: first, the memory space required for storing intermediate data is huge, which limits the maximum refinement multiple and increases the cost; second, the characteristics of the low-pass filter limit the precision and the maximum refinement multiple; third, the calculation amount is large, which requires a high calculation module and increases the hardware cost; fourth, the frequency component adjustment is complex, which makes it difficult to ensure the measurement accuracy. SUMMARY

[0004] The purpose of the present disclosure is to provide a high-precision measurement method of radar flowmeter, which can solve one or more of the above-mentioned problems in the prior art.

[0005] According to one aspect of the present disclosure, a high-precision measurement method of radar flowmeter is provided, comprising the following steps: calculating the pipe network cross-sectional area and the cross-sectional flow rate corresponding to the measuring point, calculating the flow rate according to the pipe network cross-sectional area and the cross-sectional flow rate; The calculation of the pipe network cross-sectional area corresponding to the measuring point comprises the following steps: obtaining a discrete liquid level intermediate frequency signal; extracting a target frequency spectrum range from the discrete liquid level intermediate frequency signal; performing spectrum analysis on the target frequency spectrum range to calculate the air height between the liquid surface and the radar sensor; calculating the pipe network cross-sectional area according to the air height between the liquid surface and the radar sensor and the pipe network size; The calculation of the cross-sectional flow rate comprises the following steps: obtaining a discrete velocity intermediate frequency signal; performing spectrum estimation processing on the discrete velocity intermediate frequency signal to extract a target frequency interval; Estimating the actual peak frequency position in the target frequency interval to obtain a frequency estimation value; The cross-section flow rate is calculated according to the frequency estimation value.

[0006] In some embodiments, the discrete liquid level intermediate frequency signal is obtained, including: The radar sensor transmits a signal, The radar sensor collects a return signal, After mixing the transmitted signal and the return signal, the discrete liquid level intermediate frequency signal is obtained through a low-pass filter and an ADC process.

[0007] In some embodiments, a target frequency spectrum range is extracted from the discrete liquid level intermediate frequency signal, including: The sequence length N of the discrete liquid level intermediate frequency signal is obtained, If the sequence length N of the discrete liquid level intermediate frequency signal is equal to the preset sequence length B, the sequence length B is directly called for recursive FFT processing, If N > B, the sequence of the discrete liquid level intermediate frequency signal is split into odd rows and even rows, and it is judged whether the split sequence length is equal to B, If the split sequence length is equal to B, the sequence length B is called for recursive FFT processing, If the split sequence length is greater than B, the split sequence is further split according to the odd rows and the even rows until the split sequence length is equal to B, and the sequence length B is called for recursive FFT processing, and the recursive FFT simulation ends; According to the preset frequency range, the frequency interval on both sides of the frequency point with the maximum amplitude in the recursive FFT simulation result is extracted, which is the target frequency spectrum range.

[0008] In some embodiments, the target frequency spectrum range is subjected to spectrum analysis to calculate the air height between the liquid surface and the radar sensor, including: The target frequency spectrum range is subjected to spectrum analysis by using a linear frequency modulation z transform algorithm to obtain a frequency point corresponding to the maximum amplitude, The frequency corresponding to the maximum amplitude is substituted into a detection distance formula to obtain the air height between the radar sensor and the liquid surface.

[0009] In some embodiments, the discrete velocity intermediate frequency signal is subjected to spectrum estimation processing, and the target frequency interval is extracted, including: The Bartlett spectrum estimation method is used to perform spectrum estimation processing on the discrete velocity intermediate frequency signal, According to the spectrum estimation processing result, the frequency points corresponding to the peak amplitudes and the frequency points corresponding to the secondary peak amplitudes on both sides are obtained, and the interval between the two frequency points corresponding to the secondary peak amplitudes is the target frequency interval.

[0010] In some implementations, estimating the actual peak frequency location within the target frequency range to obtain a frequency estimate includes: Calculate the deviation of the actual frequency from the peak frequency, where the peak frequency is the frequency value at the point corresponding to the peak amplitude. Calculate the frequency estimate based on the deviation value.

[0011] In some implementations, calculating the deviation of the actual frequency from the main peak frequency includes: Let A denote the amplitudes of the second-peak frequencies on either side of the peak amplitude as A. L and A R Compare A L and A R Size, If A R >A L Then the deviation of the actual frequency from the main peak frequency is Δk = (A R -A L ) / (A max -A L In the formula, A max The peak value is the main peak value. If A R <A L Then the deviation of the actual frequency from the main peak frequency is Δk = (A L -A R ) / (A max -A R ), If A R =A L If the actual frequency deviates from the main peak frequency, then the value of Δk = 0.

[0012] In some implementations, calculating the cross-sectional flow velocity based on the frequency estimate includes: The frequency estimate is substituted into the Doppler effect velocity measurement formula to calculate the cross-sectional velocity.

[0013] The high-precision measurement method for radar flowmeters disclosed herein has the following advantages: it reduces the number of frequency points that need to be processed, reduces the memory required to store intermediate data, and effectively improves measurement accuracy under limited hardware conditions; it simplifies the algorithm, reduces the amount of computation, reduces hardware requirements, and saves costs.

[0014] Furthermore, unless otherwise specified in this disclosure, all technical solutions can be implemented using conventional methods in the field. Attached Figure Description

[0015] In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the following will briefly introduce the drawings needed to be used in the embodiments. Obviously, the drawings in the following description are some embodiments of the present disclosure, and other drawings can be obtained by those skilled in the art without creative effort.

[0016] Figure 1 A flow chart of a high-precision measurement method of a radar flowmeter provided by an embodiment of the present disclosure.

[0017] Figure 2 A recursive FFT simulation result in a high-precision measurement method of a radar flowmeter provided by an embodiment of the present disclosure.

[0018] Figure 3 A result of performing spectrum analysis on a target frequency spectrum range by using a linear frequency modulation z transform algorithm in a high-precision measurement method of a radar flowmeter provided by an embodiment of the present disclosure.

[0019] Figure 4 A Bartlett spectrum estimation processing result in a high-precision measurement method of a radar flowmeter provided by an embodiment of the present disclosure. DETAILED DESCRIPTION

[0020] In order to make the objects, technical solutions and advantages of the embodiments of the present disclosure clearer, the following will combine the drawings in the embodiments of the present disclosure to clearly and completely describe the technical solutions in the embodiments of the present disclosure. Obviously, the described embodiments are some, but not all of the embodiments of the present disclosure. Based on the embodiments in the present disclosure, all other embodiments obtained by those skilled in the art without creative effort fall within the protection scope of the present disclosure.

[0021] Embodiment: With reference to the drawings accompanying the specification Figure 1 , a high-precision measurement method of a radar flowmeter provided by an embodiment of the present disclosure can include the following steps: Step 1: calculating the pipe network cross-sectional area and cross-sectional flow velocity corresponding to the measurement point, Step 2: calculating the flow rate according to the pipe network cross-sectional area and cross-sectional flow velocity.

[0022] The measurement point represents a flow detection point. In the present embodiment, the measurement point can represent the position of a radar sensor in the radar flowmeter. The radar sensor does not need to be in contact with the water body in the process of flow measurement, and has strong adaptability to the harsh environment of the urban drainage pipe network, such as wetness, medium containing silt and floating impurities, closed space and easy breeding of dirt. The radar sensor can include a transmitting antenna and a receiving antenna, the transmitting antenna is used for transmitting signals, and the receiving antenna is used for receiving echo signals.

[0023] wherein, in step 1, the calculation of the pipe network cross-section area corresponding to the measuring point can comprise the following steps: Step 1.1: obtaining a discrete liquid level intermediate frequency signal; Step 1.2: extracting a target frequency spectrum range from the discrete liquid level intermediate frequency signal; Step 1.3: performing a spectrum analysis on the target frequency spectrum range to calculate a liquid level height; Step 1.4: calculating a pipe network cross-section area according to the liquid level height and the pipe network size; In step 1.1, obtaining a discrete liquid level intermediate frequency signal can comprise the following steps: Step 1.1.1: the radar sensor transmits a signal, Step 1.1.2: the radar sensor collects a return signal, Step 1.1.3: after mixing the transmitted signal and the return signal, processing them through a low-pass filter and an analog-to-digital converter (ADC) to obtain a discrete liquid level intermediate frequency signal.

[0024] In an optional embodiment, in order to obtain the liquid level intermediate frequency signal, a FMCW wave radar can be used. The FMCW wave radar, i.e. the frequency-modulated continuous wave radar, is a radar that realizes target detection by transmitting a continuous wave with a varying frequency. The intermediate frequency signal is the frequency difference signal. Since there is a fixed proportional relationship between the frequency difference, the electromagnetic wave propagation delay, the frequency modulation bandwidth, and the frequency modulation period, the electromagnetic wave propagation delay can be calculated by using the obtained liquid level intermediate frequency signal in combination with the frequency modulation bandwidth and the frequency modulation period. The electromagnetic wave propagation delay is actually twice the time of the electromagnetic wave propagation target distance, so half of the electromagnetic wave propagation delay in combination with the propagation speed of the electromagnetic wave can calculate the distance. Therefore, the liquid level intermediate frequency signal can calculate the height of the liquid surface from the radar sensor.

[0025] In an optional embodiment, the transmitted signal and the return signal of the radar sensor are both cosine quantities. Mixing the transmitted signal and the return signal, i.e. multiplying the two cosine quantities, can obtain a signal superimposed by the sum and the difference of the frequencies of the transmitted signal and the return signal. The difference of the frequencies of the transmitted signal and the return signal is the frequency difference signal, which can be extracted by a low-pass filter.

[0026] In step 1.2, extracting a target frequency spectrum range from the discrete liquid level intermediate frequency signal can comprise the following steps: Step 1.2.1: obtaining a sequence length N of the discrete liquid level intermediate frequency signal, Step 1.2.2: judging whether the sequence length N of the discrete liquid level intermediate frequency signal is equal to a preset sequence length B. If N = B, step 1.2.3 is executed, and if N > B, step 1.2.4 is executed, Step 1.2.3: calling the recursive FFT processing of the sequence of the discrete liquid level intermediate frequency signal with the length of B, obtaining the recursive FFT simulation result, and executing step 1.2.5, Step 1.2.4: splitting the sequence of the discrete liquid level intermediate frequency signal into odd rows and even rows, and judging whether the lengths of the split sequences are equal to the preset sequence length B, if the lengths of the split sequences are equal to the preset sequence length B, executing step 1.2.3, if the lengths of the split sequences are greater than the preset sequence length B, executing step 1.2.4, Step 1.2.5: extracting the frequency range on both sides of the frequency point where the maximum amplitude value is located in the recursive FFT simulation result according to the preset frequency range, that is, the target frequency range.

[0027] Therefore, the base-2 time decimation FFT algorithm is used to perform recursive FFT processing on the discrete liquid level intermediate frequency signal, the frequency range to be processed in the subsequent steps is reduced, the intermediate data in the calculation is effectively reduced, the demand for hardware is reduced, and higher measurement accuracy is obtained under limited hardware conditions.

[0028] In optional embodiments, the value of B can be 4096. The value of B can be set according to actual conditions.

[0029] In optional embodiments, the preset frequency range is limited by the ADC bandwidth and measurement accuracy of the embedded device. For example, if the bandwidth of the FFT simulation is 100 khz, and 1000-point FFT is to be performed, the preset frequency range can be a region with a range of 100 hz before and after the maximum frequency point.

[0030] In optional embodiments, the recursive FFT simulation can be implemented using Matlab.

[0031] When the frequency of the liquid level intermediate frequency signal is set to 212345.67 Hz, the recursive FFT simulation result obtained in step 1.2.3 can be as shown in the accompanying drawings. Figure 2 At this time, the frequency corresponding to the maximum amplitude value in the figure is 212305 Hz, and the left and right frequency intervals of the frequency point where the maximum amplitude value is located in the figure are extracted, that is, the target frequency range.

[0032] In step 1.3, the target frequency range is subjected to spectrum analysis, and the air height between the liquid surface and the radar sensor is calculated. The spectrum analysis on the target frequency range can include the following steps: Step 1.3.1: performing spectrum analysis on the target frequency range by using a linear frequency modulation z transform algorithm, obtaining a frequency point corresponding to a maximum amplitude value, Step 1.3.2: substituting the frequency corresponding to the maximum amplitude value into a detection distance formula to obtain the air height between the radar sensor and the liquid surface.

[0033] Specifically, the linear frequency modulation Z transform algorithm is to calculate the frequency spectrum of a signal on an arbitrary specified complex plane Z domain path.

[0034] Let the input signal be , , N represents the sequence length, and the linear frequency modulation Z transform is used to obtain formula (1) as follows:

[0035] Let the sampling points of Z be , and the expression formula (2) is as follows:

[0036] In the formula, M is the number of frequency points in the target frequency spectrum range, is a starting factor, which determines the initial frequency; is a rotation factor, which controls the path shape, such as resolution and change trend; The sequence Z k is decomposed, and each term in the sequence is obtained as formula (3) as follows:

[0037] Substitute formula (2) into formula (1) to obtain formula (4) as follows:

[0038] Since , formula (4) can be rearranged to obtain formula (5) as follows:

[0039] Let , then formula (5) can be converted to formula (6) as follows:

[0040] Take a minimum integer L, which satisfies L≥N+M and , B can be 4096, Pad the zero value points of to become an L-length sequence, and the expression of g(n) is as follows:

[0041] Solve by using the FFT method to obtain

[0042] Generate the sequence , and extend the sequence with L as the period , and the expression is as follows:

[0043] Solving by FFT method, we get

[0044]

[0045] Solving by FFT method , we get

[0046] In the formula, the first M values are the results of linear convolution in the target frequency range The expression is calculated as follows

[0047] The amplitudes of are sorted to get the frequency point corresponding to the maximum amplitude .

[0048] The traditional FFT is equally divided in the whole sampling frequency band, while the linear frequency modulation z transform algorithm is equally divided in a certain frequency range. The essence of the linear frequency modulation z transform algorithm is to use the phase characteristics of the linear frequency modulation signal to convert the Z transform of the self-defined Z domain path into a convolution that can be quickly calculated by FFT. The self-defined Z domain sampling point achieves the purpose of local high resolution, realizes fast convolution, and can simplify the calculation and reduce the hardware load.

[0049] In an optional embodiment, the linear frequency modulation z transform can be realized by Matlab.

[0050] Referring to the drawings accompanying the specification Figure 3 , the results of the spectrum analysis of the target frequency spectrum range by the linear frequency modulation z transform algorithm are shown. As can be seen from the drawings accompanying the specification Figure 3 , the frequency corresponding to the maximum amplitude is 212345.6955 Hz, which is closer to the originally set frequency 212345.67 Hz of the liquid level intermediate frequency signal than 212305 Hz in the recursive FFT simulation result.

[0051] Step 1.3.2: Substitute the frequency corresponding to the maximum amplitude into the detection distance formula to get the distance between the radar sensor and the liquid surface. The expression of the air height R between the liquid surface and the radar sensor is:

[0052] In the formula, c represents the propagation speed of electromagnetic waves in air, T represents the period of the frequency modulation signal, B represents the bandwidth of the frequency modulation signal, represents the frequency point corresponding to the maximum amplitude.

[0053] ​In step 1.4, the pipe network cross-sectional area is calculated according to the air height between the liquid surface and the radar sensor and the pipe network size, which includes the following steps: determine the liquid level height according to the air height between the liquid surface and the radar sensor and the pipe network caliber; solve the pipe network cross-sectional area according to the liquid level height and the water flow in the pipe network.

[0054] The air height between the liquid surface and the radar sensor refers to the vertical distance between the radar sensor and the liquid surface. The pipe network cross-section is circular, and the pipe network caliber is a known quantity. According to the diameter of the pipe network cross-section and the vertical distance between the liquid surface and the radar sensor, the liquid level height in the pipe network can be calculated according to the basic plane geometric relationship.

[0055] Specifically, solving the pipe network cross-sectional area according to the liquid level height in the pipe network and the water flow in the pipe network can be divided into four cases: In this application, the pipe network cross-sectional area to be solved actually refers to the area of the water flow cross-section, When there is no water in the pipe network, the pipe network cross-sectional area to be solved is equal to 0; When the liquid level height in the pipe network is lower than the center height of the pipe network cross-section, the water flow cross-section shape is an arc shape at this time, and the pipe network cross-sectional area to be solved can be obtained according to the arc area formula, that is, the water flow cross-sectional area at this time is equal to the area of the corresponding sector minus the area of the corresponding triangle; When the liquid level height in the pipe network is higher than the center height of the pipe network cross-section, the water flow cross-sectional area, that is, the pipe network cross-sectional area to be solved, is the pipe network cross-sectional area (i.e. the area of the pipe network cross-section circle) minus the arc area of the waterless area, wherein the arc area of the waterless area is still calculated by using the arc area formula; When the liquid in the pipe network is full, the pipe network cross-sectional area to be solved is equal to the pipe network cross-sectional area.

[0056] In step 1, calculating the cross-sectional flow velocity includes the following steps: Step 1.5: obtaining discrete velocity intermediate frequency signals; Step 1.6: performing frequency spectrum estimation processing on the discrete velocity intermediate frequency signals to extract a target frequency interval; Step 1.7: estimating the actual velocity intermediate frequency signal peak frequency point position in the target frequency interval to obtain a frequency estimation value; Step 1.8: calculating the cross-sectional flow velocity according to the frequency estimation value.

[0057] In an optional embodiment, in order to obtain the velocity intermediate frequency signal, a pulse coherent wave radar can be used. The pulse coherent wave radar is a radar that uses coherent technology to process pulse signals. The intermediate frequency signal can calculate the liquid surface flow velocity according to the Doppler principle.

[0058] In step 1.6, the spectral estimation process for the discrete velocity intermediate frequency signal to extract the target frequency range may include the following steps: Step 1.6.1: Perform spectrum estimation on the discrete velocity intermediate frequency signal using the Bartlett spectrum estimation method. Step 1.6.2: Based on the results of the spectrum estimation process, obtain the frequency points corresponding to the secondary peak amplitudes on both sides of the frequency point corresponding to the peak amplitude. The interval between the frequency points corresponding to the two secondary peak amplitudes is the target frequency interval.

[0059] In step 1.6.1, the spectral estimation process for the discrete velocity intermediate frequency signal using the Bartlett spectral estimation method may include the following steps: The discrete velocity intermediate frequency signal is segmented, for example, the discrete velocity intermediate frequency signal is divided into M segments. b Segments, each segment containing N signal samples. b ; Based on the sample size N b Generate a Bartlett window of the corresponding length; Perform a Fast Fourier Transform on the function after Bartlett window processing to obtain the spectrum of each signal segment, and then perform M... b The amplitude spectrum of each signal segment is obtained by averaging the spectrograms. The results of Bartlett's spectrum estimation are obtained by summing all the amplitude spectra.

[0060] Therefore, by dividing the signal to be processed into several short signal segments, applying a window function to each segment, calculating the periodogram of each segment, and averaging the periodograms, the final amplitude spectrum estimate is obtained. The overall variance is reduced by canceling out the random errors of different segments, thereby improving the stability of the estimate and reducing spectral leakage caused by discontinuities at the signal segment boundaries.

[0061] In an optional embodiment, when the amplitude data varies significantly, the power spectrum can be used instead of the amplitude spectrum.

[0062] In an optional embodiment, the spectral estimation of discrete velocity intermediate frequency signals using the Bartlett spectral estimation method can be implemented using MATLAB.

[0063] When the frequency of the velocity intermediate frequency signal is set to 284500Hz, the Bartlett spectrum estimation result obtained in step 1.6.1 may be as shown in the appendix to the instruction manual. Figure 4 As shown in the figure, the frequency corresponding to the maximum amplitude is 284375Hz. The frequency corresponding to the maximum amplitude is recorded as the main peak frequency.

[0064] In step 1.6.2, according to the result of the spectrum estimation processing, the frequency points corresponding to the secondary peak values on both sides of the peak value are obtained, and the interval between the two secondary peak value corresponding frequency points is the target frequency interval. Specifically, the peak value in the result of the spectrum estimation processing is the maximum amplitude value, and the frequency corresponding to the maximum amplitude value is the main peak frequency point. On both sides of the main peak frequency point, a secondary peak value is found on the left and right sides of the main peak frequency point, respectively, i.e., a point with an amplitude only less than the main peak frequency point, which is the secondary peak value corresponding frequency point. The interval between the two secondary peak value corresponding frequency points is the target frequency interval, and the actual peak value frequency point is within the target frequency interval.

[0065] In step 1.7, the actual peak value frequency point position is estimated within the target frequency interval to obtain the frequency estimation value, including: Step 1.7.1: Calculate the deviation value of the actual frequency relative to the main peak frequency, and the main peak frequency is the frequency value of the frequency point corresponding to the maximum amplitude value, Step 1.7.2: Calculate the frequency estimation value according to the deviation value.

[0066] In step 1.7.1, calculating the deviation value of the actual frequency relative to the main peak frequency includes: Let the secondary peak values on both sides of the frequency point corresponding to the maximum amplitude value be A L and A R , respectively, and compare the sizes of A L and A R , If A R >A L , then the deviation value of the actual frequency relative to the main peak frequency is Δk= (A R -A L ) / (A max -A L ), where A max is the main peak value corresponding to the main peak frequency point, If A R <A L , then the deviation value of the actual frequency relative to the main peak frequency is Δk= (A L -A R ) / (A max -A R ), If A R =A L , then the deviation value of the actual frequency relative to the main peak frequency is Δk=0.

[0067] In step 1.7.2, the formula for calculating the frequency estimation value according to the deviation value is as follows:

[0068] In the formula, represents a frequency estimation value, represents a frequency corresponding to the maximum amplitude, and Δk represents a deviation value of the actual frequency relative to the main peak frequency, represents a sampling rate, and N b represents the number of samples of each signal after division.

[0069] In step 1.8, the cross-section flow rate is calculated according to the frequency estimation value, and the cross-section flow rate calculated according to the frequency estimation value includes: The frequency estimation value is brought into the Doppler effect velocity measurement formula to calculate the cross-section flow rate.

[0070] Specifically, the calculation formula of the cross-section flow rate is:

[0071] In the formula, c is the propagation speed of electromagnetic waves in air, is the carrier frequency, and θ is the angle between the electromagnetic wave and the liquid level.

[0072] Wherein, θ is determined by the installation position of the radar flowmeter.

[0073] Since the spectrum of the sine signal can be approximately assumed as a circle, the positions and amplitudes of the maximum spectrum line and the left and right two secondary peak spectrum lines of the spectrum amplitude can be obtained by interpolation through geometric principles, so as to obtain the frequency corresponding to the actual maximum spectrum line.

[0074] In step 2, the flow rate is calculated according to the pipe network cross-section area and the cross-section flow rate, and the following formula is used:

[0075] In the formula, Q represents the cross-section flow rate, v represents the cross-section flow rate, and A represents the cross-section area.

[0076] In an optional embodiment, a verification link can be arranged between step 1.6.1 and step 1.6.2, and the reliability of the Bartlett spectrum estimation processing result is judged by setting a first threshold value. Specifically, the maximum power spectrum amplitude is obtained from the result of the Bartlett spectrum estimation processing, and when the maximum power spectrum amplitude is less than the first threshold value, it is determined that the current measurement result is unreliable, and the current measurement result is abandoned.

[0077] In an optional embodiment, a Kalman filter can be arranged to filter the calculated pipe network cross-section area and cross-section flow rate, so as to improve the stability of the measurement result.

[0078] The high-precision measurement method of the radar flowmeter provided by the present disclosure has the following beneficial effects: before the linear frequency modulation z transformation, the recursive fast Fourier transformation is used to reduce the number of frequency points that need to be processed, reduce the memory required for storing intermediate data, and effectively improve the measurement accuracy; the Bartlett spectrum estimation method and the frequency interpolation method are used to calculate the cross-sectional flow velocity, which simplifies the algorithm, reduces the calculation amount, reduces the requirement for hardware, and saves the cost.

[0079] Finally, it should be noted that: the above examples are only used to illustrate the technical solutions of the present disclosure, and not to limit them; although the present disclosure has been described in detail with reference to the foregoing examples, those skilled in the art should understand that: it can still modify the technical solutions recorded in the foregoing examples, or make equivalent replacement for part of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present disclosure.

Claims

1. A method of high accuracy measurement of a radar flowmeter, characterized in that, The method comprises the following steps: calculating the pipe network cross-section area corresponding to the measuring point and the cross-section flow rate, calculating the flow rate according to the pipe network cross-section area and the cross-section flow rate; wherein the calculation of the pipe network cross-section area corresponding to the measuring point comprises the following steps: obtaining a discrete liquid level intermediate frequency signal; extracting a target frequency spectrum range from the discrete liquid level intermediate frequency signal; performing spectrum analysis on the target frequency spectrum range to calculate the air height between the liquid surface and the radar sensor; calculating the pipe network cross-section area according to the air height between the liquid surface and the radar sensor and the pipe network size; the calculation of the cross-section flow rate comprises the following steps: obtaining a discrete velocity intermediate frequency signal; performing spectrum estimation processing on the discrete velocity intermediate frequency signal to extract a target frequency interval; estimating the actual peak frequency point position in the target frequency interval to obtain a frequency estimation value; calculating the cross-section flow rate according to the frequency estimation value.

2. A high accuracy measurement method of a radar flowmeter according to claim 1, characterized in that, The obtaining of the discrete liquid level intermediate frequency signal comprises: the radar sensor transmits a signal, the radar sensor collects a return signal, after the transmitted signal and the return signal are mixed, the mixed signal is processed by a low-pass filter and an ADC to obtain the discrete liquid level intermediate frequency signal.

3. The method of claim 1, wherein, The extraction of the target frequency spectrum range from the discrete liquid level intermediate frequency signal comprises: obtaining the sequence length N of the discrete liquid level intermediate frequency signal, judging whether the sequence length N of the discrete liquid level intermediate frequency signal is equal to a preset sequence length B, if N = B, directly calling the sequence length B to perform recursive FFT processing, if N > B, splitting the sequence of the discrete liquid level intermediate frequency signal into odd rows and even rows, and judging whether the split sequence length is equal to B, if the split sequence length is equal to B, calling the sequence length B to perform recursive FFT processing, if the split sequence length is greater than B, continuing to split the split sequence according to the odd rows and the even rows until the split sequence length is equal to B, calling the sequence length B to perform recursive FFT processing, and ending the recursive FFT simulation; according to a preset frequency range, extracting a frequency interval on both sides of a frequency point corresponding to a maximum amplitude in a recursive FFT simulation result, which is the target frequency spectrum range.

4. The method of claim 1, wherein, The spectrum analysis on the target frequency spectrum range to calculate the air height between the liquid surface and the radar sensor comprises: performing spectrum analysis on the target frequency spectrum range by using a linear frequency modulation z transform algorithm to obtain a frequency point corresponding to a maximum amplitude, substituting the frequency corresponding to the maximum amplitude into a detection distance formula to obtain the air height between the radar sensor and the liquid surface.

5. The method of claim 1, wherein, The spectrum estimation processing on the discrete velocity intermediate frequency signal to extract the target frequency interval comprises: performing spectrum estimation processing on the discrete velocity intermediate frequency signal by using a Bartlett spectrum estimation method, according to the spectrum estimation processing result, obtaining frequency points corresponding to secondary peak amplitudes on both sides of a frequency point corresponding to a peak amplitude, and the interval between the two frequency points corresponding to the secondary peak amplitudes is the target frequency interval.

6. The method of claim 1, wherein, The estimation of the actual peak frequency point position in the target frequency interval to obtain the frequency estimation value comprises: calculating a deviation value of an actual frequency relative to a main peak frequency, the main peak frequency being a frequency value of the frequency point corresponding to the peak amplitude, calculating the frequency estimation value according to the deviation value.

7. A method of high precision measurement of a radar flow meter according to claim 6, characterized in that, The calculation of the deviation value of the actual frequency relative to the main peak frequency comprises: The peak amplitude corresponding to the frequency point is recorded as A L and A R , and the size of A L and A R is compared. If A R > A L , then the deviation of the actual frequency from the main peak frequency is Δk = (A R - A L ) / (A max - A L ), where A max is the main peak peak value, If A R <A L , then the deviation of the actual frequency from the main peak frequency is Δk = (A L -A R ) / (A max -A R ). If A R = A L then the deviation of the actual frequency from the main peak frequency is Δk = 0.

8. The method of claim 1, wherein, The calculation of the cross-section flow rate according to the frequency estimation value comprises: The frequency estimation value is brought into the Doppler effect velocity formula, and the cross-section flow velocity is calculated.

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