Control method and control module for Coriolis flowmeter

Abstract

The invention discloses a control method and control module for a Coriolis flowmeter, and the control method comprises the steps: obtaining a vibration signal of the Coriolis flowmeter, carrying out the frequency shift of the vibration signal with the inherent frequency of the Coriolis flowmeter as a target frequency and the zero frequency as an end point frequency, obtaining a frequency shift signal, carrying out the filtering of the frequency shift signal, obtaining a filtering signal, and carrying out the control of the Coriolis flowmeter. Re-sampling the filtered signal to obtain a re-sampled signal, performing FFT calculation on the re-sampled signal to obtain a frequency spectrum of the re-sampled signal, and performing frequency mapping on the frequency spectrum of the re-sampled signal to obtain a first frequency spectrum of the vibration signal. The frequency spectrum of the inherent frequency section of the Coriolis flowmeter is refined, the resolution of the frequency band is improved, the frequency detection precision is effectively improved, and the method is particularly suitable for processing complex signals or narrow-band signals. While the computing power is saved, a finer and more accurate signal frequency spectrum can be obtained, the phase difference calculation precision can be improved, and the excitation signal can be adjusted.

Description

Technical Field

[0001] The present invention belongs to the technical field of intelligent sensors, and in particular relates to a control method and a control module for a Coriolis flowmeter. Background Art

[0002] Coriolis mass flowmeter (Coriolis flowmeter) has been widely used in industry due to its high accuracy, wide range of fluid measurement, and ability to measure multiple parameters. Figure 1 As shown, the Coriolis flowmeter uses the Coriolis force in the measuring tube during operation. The phase difference between the output signals of the two vibration sensors on the input and output sections is proportional to the mass of the object flowing through the pipe, thereby obtaining the mass flow rate value. Therefore, the key to processing the signal of the Coriolis flowmeter is to be able to accurately measure the frequency and phase of the output signals from the two sensors. Accurately measuring the phase difference between the two signals first requires accurately measuring the frequency of the two signals, and then obtaining the phase difference by multiplying the frequency by the time it takes to generate the phase difference. Therefore, it is necessary to accurately track and measure the frequency of the sensor output signal in real time. Existing frequency measurement methods or calculations based on adaptive notch filters are relatively complex, making it difficult to continuously track changes in signal frequency for a long time.

[0003] The drive system is a crucial component of the Coriolis mass flowmeter. It provides the driving force for the measuring tube, causing it to vibrate at its natural frequency and with a stable amplitude, and to track changes in the tube's natural frequency. Therefore, the drive system must accurately calculate the signal frequency and be able to track changes in the tube's vibration frequency caused by changes in fluid properties.

[0004] The information disclosed in this background technology section is only intended to enhance understanding of the overall background of the invention and should not be regarded as an admission or any form of suggestion that the information constitutes the prior art already known to a person skilled in the art. Summary of the Invention

[0005] The object of the present invention is to provide a control method and a control module for a Coriolis flowmeter, which can solve the problem of complex calculation and insufficient precision in the signal processing process of the Coriolis flowmeter in the prior art.

[0006] In order to achieve the above object, a specific embodiment of the present invention provides the following technical solutions:

[0007] A control method for a Coriolis flowmeter, comprising: acquiring a vibration signal of the Coriolis flowmeter; performing frequency shift on the vibration signal with the natural frequency of the Coriolis flowmeter as the target frequency and zero frequency as the end frequency to obtain a frequency-shifted signal; filtering the frequency-shifted signal to obtain a filtered signal; resampling the filtered signal to obtain a resampled signal; performing FFT calculation on the resampled signal to obtain the spectrum of the resampled signal; and performing frequency mapping on the spectrum of the resampled signal to obtain the first spectrum of the vibration signal.

[0008] In one or more embodiments of the present invention, the signal processing method further comprises: calculating the bandwidth of the vibration signal; determining the cut-off frequency when filtering the frequency-shifted signal according to the bandwidth of the vibration signal; and / or determining the resampling multiple according to the bandwidth of the vibration signal.

[0009] In one or more embodiments of the present invention, calculating the bandwidth of the vibration signal comprises: performing FFT calculation on the vibration signal to obtain the second spectrum of the vibration signal; and calculating the bandwidth of the vibration signal based on the second spectrum of the vibration signal.

[0010] In one or more embodiments of the present invention, performing FFT calculation on the vibration signal to obtain the second spectrum of the vibration signal comprises: performing signal windowing on the vibration signal based on a window function to obtain a windowed signal; and performing FFT calculation on the windowed signal to obtain the second spectrum of the vibration signal.

[0011] In one or more embodiments of the present invention, the window function includes a Hamming window function.

[0012] In one or more embodiments of the present invention, the control method further comprises: calculating the mass flow rate based on the first spectrum; and / or performing feedback control on the vibration frequency of the Coriolis flowmeter based on the first spectrum.

[0013] In one or more embodiments of the present invention, the control method further comprises: calculating the deviation value between the amplitude of the vibration signal and the desired amplitude; and performing feedback control on the vibration amplitude of the Coriolis flowmeter based on the deviation value.

[0014] In one or more embodiments of the present invention, the deviation value includes the logarithmic difference between the amplitude of the vibration signal and the desired amplitude.

[0015] A specific embodiment of the present invention further provides a control module for a Coriolis flowmeter. A computer program is stored on the control module, and when the control module executes the computer program, the above-mentioned control method for a Coriolis flowmeter is implemented.

[0016] In one or more embodiments of the present invention, the control module includes an FPGA unit and a DSP unit connected to each other. The FPGA unit is used to acquire the vibration signal of the Coriolis flowmeter, and the DSP unit is used to: perform frequency shift on the vibration signal with the natural frequency of the Coriolis flowmeter as the target frequency and zero frequency as the end frequency to obtain the frequency-shifted signal; filter the frequency-shifted signal to obtain the filtered signal; resample the filtered signal to obtain the resampled signal; perform FFT calculation on the resampled signal to obtain the spectrum of the resampled signal; perform frequency mapping on the spectrum of the resampled signal to obtain the first spectrum of the vibration signal.

[0017] Compared with the prior art, the control method and control module for a Coriolis flowmeter according to the present invention refine the spectrum in the natural frequency band of the Coriolis flowmeter, and effectively improve the accuracy of frequency detection by improving the resolution of this frequency band, especially suitable for processing complex signals or narrowband signals. While saving computing power, a more refined and accurate signal spectrum can be obtained, which helps to improve the accuracy of phase difference calculation and adjust the excitation signal.

[0018] At the same time, the advantages of DSP and FPGA are combined in hardware, the signal processing process is optimized, and the overall performance of the system is also improved, meeting the requirements of high-precision flow measurement applications. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments recorded in the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0020] Figure 1 It is a diagram of the output signals of two vibration sensors of a Coriolis flowmeter in the prior art.

[0021] Figure 2 It is a flowchart of the control method in an embodiment of the present invention.

[0022] Figure 3 It is a preferred flowchart of the control method in an embodiment of the present invention.

[0023] Figure 4 It is a comparison diagram of the first spectrum in an embodiment of the present invention.

[0024] Figure 5 It is a flowchart of the control method in another embodiment of the present invention.

[0025] Figure 6This is a comparison chart of the vibration amplitude simulation results in an embodiment of the present invention.

[0026] Figure 7 This is a structural diagram of the control module in an embodiment of the present invention.

[0027] Figure 8 This is a diagram of the algorithm processing module of the DSP unit in an embodiment of the present invention. Detailed implementation manners

[0028] In order to enable those skilled in the art to better understand the technical solutions in the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without making creative efforts shall fall within the protection scope of the present invention.

[0029] "Coupled" or "connected" or "linked" in the specification includes both direct connection and indirect connection. Indirect connection is a connection through an intermediate medium, such as a connection through an electrical conduction medium, which may have parasitic inductance or parasitic capacitance; indirect connection may also include a connection through other active devices or passive devices on the basis of achieving the same or similar functional purposes, such as a connection through circuits or components such as switches and follower circuits. In addition, in the invention, words such as "first" and "second" are mainly used to distinguish one technical feature from another technical feature, and do not necessarily require or imply that there is a certain actual relationship, quantity or order between these technical features.

[0030] In the detailed description of the specification, reference is made to the accompanying drawings that form a part of it, in which the same reference numerals always represent the same components, and in which the exemplary embodiments that can be implemented are shown by way of illustration. It should be understood that other embodiments can be utilized without departing from the scope of the present application, and structural or logical changes can be made. Therefore, the following detailed description should not be regarded as having a limiting meaning.

[0031] The various operations in the specification can be described as a plurality of discrete actions or operations in the order that is most helpful for understanding the claimed subject matter. However, the described order should not be construed as implying that these operations must be order-related. Specifically, these operations may not be performed in the order presented. The described operations can be performed in an order different from that of the described embodiments. Various additional operations can be performed in additional embodiments and / or the described operations can be omitted.

[0032] For the purposes of this application, the phrase "A and / or B" means (A), (B), or (A and B). For the purposes of this application, the phrase "A, B, and / or C" means (A), (B), (C), (A and B), (A and C), (B and C), or (A, B, and C).

[0033] Various components and devices may be referred to or shown herein in the singular, but this is merely for convenience of discussion, and any element referred to in the singular may include a plurality of such elements in accordance with the teachings herein.

[0034] The specification describes the use of the phrases "in one embodiment" or "in other embodiments" or "in some embodiments", which may each refer to one or more of the same or different embodiments. Further, the terms "comprising", "including", "having", etc., used with respect to the embodiments of this application are synonymous.

[0035] Embodiment 1

[0036] As Figure 2 shown, a control method for a Coriolis flowmeter in one embodiment of the present invention includes:

[0037] Obtaining a vibration signal of the Coriolis flowmeter.

[0038] Taking the natural frequency of the Coriolis flowmeter as the target frequency and zero frequency as the end frequency, performing frequency shift on the vibration signal to obtain a frequency-shifted signal.

[0039] Filtering the frequency-shifted signal to obtain a filtered signal.

[0040] Resampling the filtered signal to obtain a resampled signal.

[0041] Performing FFT calculation on the resampled signal to obtain the spectrum of the resampled signal.

[0042] Performing frequency mapping on the spectrum of the resampled signal to obtain the first spectrum of the vibration signal.

[0043] In the above method, by adopting the Zoom-FFT signal processing technology, it is possible to locally focus on the frequency band of interest in the frequency domain, namely near the natural frequency of the Coriolis flowmeter. By improving the resolution of this frequency band, the accuracy of frequency detection is effectively improved, especially suitable for processing complex signals or narrowband signals.

[0044] Further, the signal processing method may further include:

[0045] Calculating the bandwidth of the vibration signal.

[0046] Determining the cut-off frequency when filtering the frequency-shifted signal according to the bandwidth of the vibration signal.

[0047] Determine the resampling multiple according to the bandwidth of the vibration signal.

[0048] Among them, calculating the bandwidth of the vibration signal may include:

[0049] Perform FFT calculation on the vibration signal to obtain the second spectrum of the vibration signal.

[0050] Calculate the bandwidth of the vibration signal based on the second spectrum of the vibration signal.

[0051] Among them, performing FFT calculation on the vibration signal to obtain the second spectrum of the vibration signal may include:

[0052] Perform signal windowing on the vibration signal based on the window function to obtain the windowed signal.

[0053] Perform FFT calculation on the windowed signal to obtain the second spectrum of the vibration signal.

[0054] As Figure 3 shown is a preferred implementation process of the above control method. First, obtain the vibration signal of the Coriolis flowmeter.

[0055] In one embodiment, a vibration sensor is installed on the measuring tube of the Coriolis flowmeter, and the vibration signal can be output through the vibration sensor. Then, for the convenience of calculation and processing, the analog vibration signal x(t) can be converted into a digital vibration signal x(n) through an analog-to-digital converter:

[0056] x(n) = x(t n )(n = 1, 2, 3,..., N)

[0057] Among them, N is the total number of sampling points within the sampling time period, and the sampling time period can generally be set by itself according to the hardware conditions. n is the discrete time index, and t n is the moment corresponding to n.

[0058] Then, perform windowing on the vibration signal x(n) to obtain the windowed signal x windowed (n):

[0059] x windowed (n) = x(n) · w(n), n = 0, 1,..., N - 1

[0060] Among them, w(n) is the window function. Preferably, the window function includes the Hamming window function:

[0061]

[0062] By windowing the signal, spectral leakage can be reduced.

[0063] Then, for the windowed signal x windowed(n) Perform FFT calculation to obtain the second spectrum X2(k), where k is the frequency index of the second spectrum:

[0064]

[0065] Next, calculate the bandwidth of the vibration signal based on the second spectrum X2(k). First, the energy spectrum P(k) can be calculated:

[0066] P(k) = |X2(k)| 2

[0067] Next, calculate the frequency resolution Δf:

[0068]

[0069] where F s is the sampling rate of the digital vibration signal x(n). In a specific embodiment, F s is 1000 Hz. The original frequency f k corresponding to the frequency index k is:

[0070] f k = k·Δf

[0071] where, due to the symmetry of the real signal, only the first 1 / 2 of the frequency index k (taking 0 ≤ k ≤ N / 2) is analyzed.

[0072] Next, set the energy threshold T abs , traverse all the energy spectra P(k) greater than the energy threshold T abs in the first 1 / 2 of the frequency index k, and record the minimum frequency index k L and the maximum frequency index k R .

[0073] Finally, calculate the bandwidth B:

[0074] B = (k R - k L )·Δf

[0075] In a specific embodiment, the value of the bandwidth B is 20 Hz.

[0076] Then, perform frequency shift on the vibration signal x(n) to shift the natural frequency to zero frequency to obtain the frequency-shifted signal x min (n). Since complex exponential multiplication is equivalent to frequency-domain translation, it can be obtained:

[0077]

[0078] Among them, f0 is the natural frequency of the Coriolis flowmeter. In one embodiment, the Coriolis flowmeter may have a range of natural frequencies, and the center frequency within this range of natural frequencies is taken as the natural frequency f0. The natural frequency of the Coriolis flowmeter may also change continuously during the measurement operation, and its value can be the initial set value or the natural frequency value calculated in the previous sampling period.

[0079] In this step, the original spectrum of the vibration signal x(n) is shifted to the left by f0, so that the spectrum range changes from f0±B / 2 to -B / 2~B / 2.

[0080] Next, the frequency-shifted signal x min (n) is filtered to obtain a filtered signal x filter (n), and at the same time, the cut-off frequency for filtering the frequency-shifted signal x min (n) is determined according to the bandwidth B of the vibration signal x(n).

[0081] The purpose here is to filter out the signals that fall outside the frequency band width after frequency shift through low-pass filtering. Since the bandwidth B of the vibration signal x(n) is known, the cut-off frequency f c can be directly taken as B / 2 = 10 Hz.

[0082] In one embodiment, an FIR filter can be used for filtering here, and preferably the Hamming window method is used to design the filter. The filter order L is determined by the transition bandwidth Δf transition and the stopband attenuation. Specifically, if the transition bandwidth Δf transition here is 2 Hz and the stopband attenuation is -60 dB, then the filter order L is:

[0083]

[0084] In other embodiments, other methods can also be used to design the filter, such as the Parks-McClellan algorithm, etc.

[0085] Next, the filtered signal x filter (n) is resampled to obtain a resampled signal x down (m), and at the same time, the resampling multiple is determined according to the bandwidth B of the vibration signal x(n).

[0086] Specifically, the resampling multiple D is:

[0087]

[0088] The filtered signal x filter (n) is resampled at a multiple of D to obtain a resampled signal x down (m):

[0089] x down(m) = x filter (D·m), m = 0, 1, …, M - 1

[0090] where M = N / D and M is the length of the resampled data.

[0091] At this time, the new sampling rate F s ′ is:

[0092]

[0093] It can be seen that the new sampling rate F s ’ satisfies the Nyquist sampling theorem: F s ′ ≥ 2 × B / 2.

[0094] Next, perform FFT calculation on the resampled signal x down (m) to obtain the spectrum X zoom (k′) of the resampled signal.

[0095] Specifically, at this time, perform an N′-point complex FFT on the signal, and the number of points N′ can be selected according to the required resolution Δf′ at this time:

[0096] *

[0097] In a specific embodiment, Δf′ is 0.1 Hz, and the calculated theoretical number of points N′ is 200 at this time. In practical applications, the number of points N′ can actually take a power-of-two value near the theoretical number of points, such as 256, to further optimize the calculation speed.

[0098] At this time, the spectrum X zoom (k′) of the resampled signal is:

[0099]

[0100] where k′ is the frequency index of the spectrum X zoom (k′).

[0101] Performing FFT after resampling can improve the frequency resolution.

[0102] Next, perform frequency mapping on the spectrum X zoom (k′) of the resampled signal to obtain the first spectrum X1(f) of the vibration signal.

[0103] As can be seen from the above, the original vibration signal frequency f corresponding to the frequency index k′ k′ is:

[0104]

[0105] Based on the above mapping relationship, the first spectrum X1(f) of the vibration signal x(n) can be obtained.

[0106] In the above process, in the two steps of low-pass filtering and resampling, the measured bandwidth B is used, which enables accurate focusing within the actually required bandwidth when refining the spectrum of the vibration signal x(n), contributing to improving the accuracy of the first spectrum X1(f).

[0107] In other embodiments, it is also possible not to determine the cut-off frequency for filtering the frequency-shifted signal x min (n) according to the bandwidth B of the vibration signal x(n), but to determine the cut-off frequency through a preset bandwidth value. It is also possible not to determine the resampling multiple according to the bandwidth B of the vibration signal x(n), but to determine the resampling multiple through a preset bandwidth value.

[0108] Figure 4 (a) shows the spectrum diagram of the vibration signal directly calculated by FFT in the prior art. Figure 4 (b) shows the spectrum diagram of the first spectrum obtained by refining the signal near the natural frequency through this method. It can be seen that the more accurate natural frequency value obtained by this method is 100.4 Hz, with the accuracy improved by 0.18 Hz.

[0109] In one embodiment, the control method may further include calculating the mass flow rate based on the first spectrum.

[0110] Specifically, the vibration frequency of the Coriolis flowmeter can be accurately obtained based on the first spectrum, and then combined with the time when the vibration signals of the two sensors generate a phase difference, multiplied to obtain the phase difference, and finally the mass flow rate is calculated based on the phase difference. The specific manner of calculating the mass flow rate based on the first spectrum can be implemented using the prior art.

[0111] In one embodiment, the control method may further include performing feedback control on the vibration frequency of the Coriolis flowmeter based on the first spectrum.

[0112] The above vibration frequency specifically refers to the vibration frequency of the measuring tube in the Coriolis flowmeter. During the operation of the Coriolis flowmeter, it is necessary to drive the measuring tube to vibrate at its natural frequency. After accurately measuring the real-time vibration frequency of the measuring tube through the first spectrum, it is possible to track the change in the vibration frequency of the measuring tube caused by the change in fluid characteristics, thereby performing feedback adjustment control. The specific manner of performing feedback control on the vibration frequency of the Coriolis flowmeter based on the first spectrum can be implemented using the prior art.

[0113] In one embodiment, the control method may further include detecting whether the Coriolis flowmeter is operating within a preset range based on the first frequency spectrum. For example, a normal frequency range may be set, and when the vibration frequency exceeds the normal frequency range, it is determined to be abnormal. Based on the detection result, instructions such as error reporting, continued operation, and restart can be issued.

[0114] In summary, by adopting the signal processing technology of refined spectrum FFT, the frequency detection accuracy near the natural frequency is improved, thereby effectively improving the phase difference calculation accuracy, achieving high-precision and high-resolution flow measurement, and also improving the adjustment of the excitation signal.

[0115] Example 2

[0116] like Figure 5 As shown, this embodiment provides a control method. Based on the control method in Example 1, the control method of this embodiment further includes:

[0117] Calculate the deviation between the amplitude of the vibration signal x(n) and the expected amplitude.

[0118] Feedback control is performed on the vibration amplitude of the Coriolis flowmeter based on the deviation value.

[0119] Preferably, the deviation value includes the logarithmic difference between the amplitude of the vibration signal x(n) and the expected amplitude. The deviation value ΔA(n) can be expressed as:

[0120] ΔA[n]=ln(A hope )-ln(x(n))

[0121] Among them, A hope is the expected amplitude, which can specifically be a value given by the system.

[0122] In one embodiment, when feedback control is performed on the vibration amplitude of the Coriolis flowmeter based on the deviation value, a PI control method can be used. The deviation value ΔA(n) is used as the optimization target value of the PI algorithm to perform PI control on the drive system of the Coriolis flowmeter. The algorithm is:

[0123]

[0124] Among them, K p is the proportional gain, K i is the integral gain.

[0125] Preferably, K p ∈[0.01,0.05], K i ∈[0.00001,0.0001].

[0126] In other embodiments, when performing feedback control on the vibration amplitude of the Coriolis flowmeter based on the deviation value, PID or other feedback control methods can also be used.

[0127] Figure 6 (a) shows the simulation results of the vibration amplitude of the measuring tube when the vibration amplitude is not feedback-controlled based on the above method. Figure 6 (b) shows the simulation results obtained by performing feedback control on the vibration amplitude based on this method. It can be seen that the curve after feedback control is smoother and has no burrs. By performing non-linear PI amplitude control on the sampled signal, the system stability can be maintained.

[0128] Embodiment 3

[0129] This embodiment provides a control module for a Coriolis flowmeter. A computer program is stored on the control module. When the control module executes the computer program, the control method for the Coriolis flowmeter in Embodiment 1 or 2 is implemented.

[0130] As Figure 7 shown, further, the control module may include an FPGA unit 10 and a DSP unit 20 connected to each other. The FPGA unit 10 and the DSP unit 20 can use existing products. Relevant computer programs are respectively stored on the FPGA unit 10 and the DSP unit 20, so that when the FPGA unit 10 and the DSP unit 20 respectively execute their own computer programs, the above control method can be implemented.

[0131] Among them, the FPGA unit 10 is used to acquire the vibration signal x(n) of the Coriolis flowmeter.

[0132] Specifically, the FPGA unit 10 is connected to a vibration sensor to receive the vibration signal x(n).

[0133] In one embodiment, 2 vibration sensors are provided. The FPGA unit 10 is connected to the 2 vibration sensors and receives the vibration signals x(n) respectively generated by the 2 vibration sensors.

[0134] Preferably, the control module may further include an amplification and filtering unit and an analog-to-digital conversion unit. The amplification and filtering unit is connected to the vibration sensor to perform amplification and filtering processing on the vibration signal x(t) generated by the vibration sensor. The analog-to-digital converter is connected to the amplification and filtering unit to perform analog-to-digital conversion on the vibration signal x(t) after amplification and filtering processing. The FPGA unit 10 is connected to the analog-to-digital converter to receive the vibration signal x(n) converted into a digital quantity.

[0135] In one embodiment, 2 amplification and filtering units and 2 analog-to-digital conversion units are provided, and each corresponds to a vibration sensor.

[0136] The DSP unit 20 is used to: perform frequency shift on the vibration signal x(n) with the natural frequency of the Coriolis flowmeter as the target frequency and zero frequency as the end frequency to obtain the frequency-shifted signal x min (n). Filter the frequency-shifted signal x min (n) to obtain the filtered signal x filter (n). Resample the filtered signal x filter (n) to obtain the resampled signal x down (m). Perform FFT calculation on the resampled signal x down (m) to obtain the spectrum X zoom (k′) of the resampled signal. Perform frequency mapping on the spectrum X[[ID=XX]] zoom (k′) of the resampled signal to obtain the first spectrum X1(f) of the vibration signal.

[0137] Specifically, the GPIO interface of the DSP unit 20 is connected to the IO interface of the FPGA unit 10 to receive the digital vibration signal x(n). The process of the DSP unit 20 performing calculation and processing on the vibration signal x(n) to obtain the first spectrum X1(f) is as described in Embodiment 1 and will not be elaborated here.

[0138] Preferably, the DSP unit 20 can also be used to calculate the mass flow rate based on the first spectrum X1(f). The specific process is also as described in Embodiment 1.

[0139] Preferably, the FPGA unit 10 can also be used to perform feedback control on the vibration frequency of the Coriolis flowmeter based on the first spectrum X1(f).

[0140] Specifically, the FPGA unit 10 can be connected to the DDS (Direct Digital Synthesizer) in the drive system of the Coriolis flowmeter. The FPGA unit 10 controls the DDS to generate the corresponding drive signal. After the drive signal undergoes digital-to-analog conversion and power amplification by the MDAC in the drive system, it is transmitted to the exciter in the drive system to generate the excitation signal to make the measuring tube of the Coriolis flowmeter vibrate.

[0141] In this process, the FPGA unit 10 performs feedback control on the frequency of the drive signal generated by the DDS based on the first spectrum X1(f) to ensure that the measuring tube always vibrates at its natural frequency. [[ID=XX]]

[0142] Preferably, the DSP unit 20 and the FPGA unit 10 can also calculate the deviation value ΔA(n) between the amplitude of the vibration signal x(n) and the desired amplitude A hope and perform feedback control on the vibration amplitude of the Coriolis flowmeter based on the deviation value ΔA(n).

[0143] Specifically, the DSP unit 20 can calculate the amplitude of the vibration signal x(n) and the expected amplitude A based on the control method in Example 2. hope Based on the control method in Example 2, the FPGA unit 10 can use the deviation value ΔA(n) as the optimization target value of the PI algorithm to perform PI control on the amplitude of the drive signal generated by the DDS to adjust the vibration amplitude of the measuring tube so that the measuring tube vibrates at a stable amplitude.

[0144] Preferably, the FPGA unit 10 can also be connected to the temperature sensing unit in the Coriolis flowmeter to receive a temperature signal, and transmit the temperature signal to the DSP unit 20. The DSP unit 20 can also compensate and correct the calculation result of the mass flow based on the temperature signal.

[0145] Preferably, the DSP unit 20 can also be connected to the power failure monitoring unit, serial communication unit, storage unit and indication unit in the Coriolis flowmeter to complete functions such as power failure monitoring, external serial communication, information storage and light indication.

[0146] Preferably, the DSP unit 20 can also detect whether the Coriolis flowmeter operates within a preset range based on the first spectrum, and can further issue instructions such as error reporting, continuing operation, and restarting based on the detection result.

[0147] Figure 8 An optimal algorithm processing module of the DSP unit 20 is provided. First, the DSP unit 20 system will perform the setting of the initialization module to ensure that all parameters and settings are correct, and then configure the interrupt program to ensure that the DSP unit 20 can operate stably during the real-time data processing process. Next, the DSP unit 20 will calculate the amplitude of the received vibration signal x(n), and lay the foundation for subsequent frequency analysis by analyzing the amplitude change of the signal. Then, the DSP unit 20 calculates the frequency based on the above-mentioned control method, and sends the frequency calculation result to the FPGA unit 10 for specific frequency drive to ensure the efficient operation of the system. At the same time, the frequency calculation result is also used for frequency detection to determine the working status of the flowmeter. Finally, the DSP unit 20 calculates the phase difference and mass flow based on the frequency calculation result, and outputs the result, thereby completing the entire signal processing process and ensuring the high precision and real-time performance of the flowmeter. This process not only improves the performance of the system, but also ensures the accuracy and stability of the measurement.

[0148] In the above process, the FPGA unit 10 is mainly responsible for collecting vibration signals x(n) and temperature signals and performing some parallel computing functions. Since the FPGA unit 10 has low latency and high computing efficiency, it is very suitable for the FPGA unit 10 to serve as the processing module for driving signals. At the same time, the FPGA unit 10 transports the collected vibration signal x(n) to the DSP unit 20 through the IO port, and uses the advantages of the DSP unit 20's algorithm processing to complete the calculation and processing of the vibration signal x(n), including the calculation of phase, amplitude, and frequency. The DSP unit 20 also transmits the more precise frequency calculation result to the FPGA unit 10 for frequency driving. The parallel processing ability of the FPGA unit 10 enables the system to process a large amount of data quickly and efficiently, while the DSP unit 20 provides precise calculation functions, ensuring the accuracy and real-time performance of data processing. Through this combination, the system can effectively filter out noise during real-time measurement, improve signal quality, and ensure the high precision and reliability of the flow measurement result. This method not only optimizes the signal processing process but also improves the overall performance of the system, meeting the requirements of high-precision flow measurement applications.

[0149] In summary, the control module in this solution uses the FPGA unit 10 to complete the signal acquisition work it is good at, and the DSP unit 20 performs precise signal algorithm processing, combining the advantages of each chip to complete the hardware design of the entire system.

[0150] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0151] The present invention is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to embodiments of the present invention. It should be understood that each flow and / or block in the flowchart and / or block diagram, and the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices produce means for implementing the functions specified in Figure 1 one or more of the flows or multiple flows and / or blocks Figure 1 one or more of the blocks or multiple blocks.

[0152] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to work in a particular manner, such that the instructions stored in the computer-readable memory produce a manufacture including an instruction means which implements the functions specified in the flowchart(s) Figure 1 a flowchart or flowcharts and / or block(s) Figure 1 a block or blocks.

[0153] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, so that the instructions executed on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart(s) Figure 1 a flowchart or flowcharts and / or block(s) Figure 1 a block or blocks.

[0154] It is apparent to those skilled in the art that the present invention is not limited to the details of the above-described exemplary embodiments, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics thereof. Therefore, in any regard, the embodiments should be regarded as exemplary and non-limiting, and the scope of the present invention is defined by the appended claims rather than the above description, and all changes falling within the meaning and scope of the equivalent elements of the claims are intended to be embraced within the present invention. Any reference signs in the claims should not be construed as limiting the claims concerned.

[0155] In addition, it should be understood that although this specification is described in terms of embodiments, not every embodiment contains only one independent technical solution, and this narrative manner of the specification is only for clarity. Those skilled in the art should regard the specification as a whole, and the technical solutions in the various embodiments can also be appropriately combined to form other embodiments understandable to those skilled in the art.

Claims

1. A control method for a Coriolis flowmeter, characterized in that, Including: Obtaining the vibration signal of the Coriolis flowmeter; Performing frequency shift on the vibration signal with the natural frequency of the Coriolis flowmeter as the target frequency and zero frequency as the end frequency to obtain a frequency-shifted signal; Filtering the frequency-shifted signal to obtain a filtered signal; Resampling the filtered signal to obtain a resampled signal; Performing FFT calculation on the resampled signal to obtain the spectrum of the resampled signal; Performing frequency mapping on the spectrum of the resampled signal to obtain the first spectrum of the vibration signal.

2. The control method for a Coriolis flowmeter according to claim 1, characterized in that, The signal processing method further includes: Calculating the bandwidth of the vibration signal; Determining the cut-off frequency when filtering the frequency-shifted signal according to the bandwidth of the vibration signal; and / or Determining the resampling multiple according to the bandwidth of the vibration signal.

3. The control method for a Coriolis flowmeter according to claim 2, characterized in that, Calculating the bandwidth of the vibration signal includes: Performing FFT calculation on the vibration signal to obtain the second spectrum of the vibration signal; Calculating the bandwidth of the vibration signal based on the second spectrum of the vibration signal.

4. The control method for a Coriolis flowmeter according to claim 3, characterized in that, Performing FFT calculation on the vibration signal to obtain the second spectrum of the vibration signal includes: Performing signal windowing on the vibration signal based on a window function to obtain a windowed signal; Performing FFT calculation on the windowed signal to obtain the second spectrum of the vibration signal.

5. The control method for a Coriolis flowmeter according to claim 4, characterized in that, The window function includes a Hamming window function.

6. The control method for a Coriolis flowmeter according to claim 1, wherein, The control method further includes: Calculating the mass flow rate based on the first spectrum; and / or Performing feedback control on the vibration frequency of the Coriolis flowmeter based on the first spectrum.

7. The control method for a Coriolis flowmeter according to claim 1, characterized in that, The control method further includes: Calculating the deviation value between the amplitude of the vibration signal and the expected amplitude; Performing feedback control on the vibration amplitude of the Coriolis flowmeter based on the deviation value.

8. The control method for a Coriolis flowmeter according to claim 7, characterized in that, The deviation value includes the logarithmic difference between the amplitude of the vibration signal and the expected amplitude.

9. A control module for a Coriolis flowmeter, characterized in that, A computer program is stored on the control module, and when the control module executes the computer program, the control method for the Coriolis flowmeter according to any one of claims 1 to 8 is implemented.

10. The control module according to claim 9, characterized in that The control module includes an FPGA unit and a DSP unit connected to each other. The FPGA unit is used to obtain the vibration signal of the Coriolis flowmeter, and the DSP unit is used for: Performing frequency shift on the vibration signal with the natural frequency of the Coriolis flowmeter as the target frequency and zero frequency as the end frequency to obtain the frequency-shifted signal; Filtering the frequency-shifted signal to obtain the filtered signal; Resampling the filtered signal to obtain the resampled signal; Performing FFT calculation on the resampled signal to obtain the spectrum of the resampled signal; Performing frequency mapping on the resampled spectrum to obtain the first spectrum of the vibration signal.

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