High-precision metering method and system suitable for ultrasonic flowmeter

Abstract

The embodiment of the invention provides a high-precision metering method and system suitable for an ultrasonic flowmeter, and the method comprises the steps: collecting original signals received by a transducer, carrying out the differential operation of the original signals, building an identification window based on the signal parameters of the original signals, and enabling the original signals to comprise an original upstream signal and an original downstream signal; acquiring transducer parameters, establishing a theoretical model based on the transducer parameters, sampling the theoretical model, and performing cross-correlation operation on sampled reference signals and identification window signals in the identification window; correcting the reference signal based on the correlation coefficient of the cross-correlation operation, and measuring the time difference between the arrival time of an upstream signal and the arrival time of a downstream signal in the reference signal for multiple times; and calculating time difference stability based on multiple measurement results of the time difference, and dynamically adjusting associated parameters of the identification window through the time difference stability.

Description

Technical Field

[0001] The present invention relates to the field of ultrasonic signal technology, and in particular to a high-precision metering method and system suitable for an ultrasonic flowmeter. Background Art

[0002] Ultrasonic flow meters have high measurement accuracy and are widely used in civil, industrial and other fields. Among them, ultrasonic flow meters can calculate pipeline flow through the propagation time difference of ultrasonic signals received by upstream and downstream transducers.

[0003] However, traditional calculation solutions typically use timing chips, which rely heavily on the quality of the received signal. In practical applications, however, the received signal is susceptible to factors such as impurities in the pipeline, transducer aging, and changes in the flow field. This can lead to a decrease in the signal-to-noise ratio and even deformation, making it impossible for the timing chip to accurately determine the signal arrival time, resulting in errors in the calculated pipeline flow rate. Summary of the Invention

[0004] In order to solve the problems existing in the prior art, the embodiments of the present invention provide a high-precision measurement method and system applicable to an ultrasonic flowmeter.

[0005] An embodiment of the present invention provides a high-precision measurement method applicable to an ultrasonic flowmeter, the method comprising:

[0006] Collecting an original signal received by the transducer, and establishing an identification window based on signal parameters of the original signal after performing a differential operation on the original signal, wherein the original signal includes an original upstream signal and an original downstream signal;

[0007] Acquiring transducer parameters, establishing a theoretical model based on the transducer parameters, sampling the theoretical model, and performing a cross-correlation operation on the sampled reference signal and the identification window signal within the identification window;

[0008] Correcting the reference signal based on the correlation coefficient of the cross-correlation operation, and measuring the time difference between the arrival times of the upstream signal and the downstream signal in the reference signal multiple times;

[0009] The time difference stability is calculated based on multiple measurement results of the time difference, and the associated parameters of the identification window are dynamically adjusted according to the time difference stability.

[0010] In one embodiment, the calculation formula for the recognition window width includes:

[0011]

[0012] Among them, L is the window width of the recognition window, is the sampling rate of the original signal, is the excitation frequency of the original signal, and round is the rounding function.

[0013] In one embodiment, the method further comprises:

[0014] Slide the sampled reference signal along the opposite side, and at each sliding position, calculate the correlation coefficient of the correlation series between the reference signal and the series of original signal segments at the sliding position;

[0015] The calculation formula of the correlation coefficient includes:

[0016]

[0017] Where r is the correlation coefficient, is the signal after the differential operation of the original upstream signal, i is the array table below, is the rising signal in the reference signal.

[0018] In one embodiment, the method further comprises:

[0019] When the correlation coefficient is greater than or equal to the preset threshold, the sliding times of the identification window are used as the reference signal arrival time, and the rising edge reference signal is corrected online. The correction formula is:

[0020]

[0021] Among them, j is the sliding measurement index, a is the correction coefficient, When the sliding signal rises, it is the original upstream signal Part of the signal in, the length is L;

[0022] When the correlation coefficient is less than the preset threshold, the reference signal continues to slide according to the specified step size.

[0023] In one embodiment, the method further comprises:

[0024] The sliding times of the reference signal are counted, and when it is detected that the sliding times are greater than a preset sliding times threshold, and within the sliding times, the correlation coefficient is continuously less than the preset threshold, it is determined that the reference signal is abnormal.

[0025] In one embodiment, the calculation formula for calculating the time difference stability based on multiple time difference measurement results includes:

[0026]

[0027] in, is the time difference calculated for the current measurement, is the time difference calculated for the last measurement, and m is the number of calculations for the time difference stability.

[0028] In one embodiment, the method further comprises:

[0029] Adjusting the sliding step size of the recognition window includes:

[0030] When S> *20%, reduce the sliding step size to unit step size;

[0031] When S≤ *20%, increase the sliding step size to L;

[0032] Adjusting the window width of the recognition window includes:

[0033] Detecting a difference in pipe water temperature between two measurements, and when the water temperature difference is greater than a preset temperature difference, expanding the window width;

[0034] When the water temperature difference is less than a preset temperature difference, the window width is reduced.

[0035] An embodiment of the present invention provides a high-precision metering system suitable for an ultrasonic flowmeter, the system comprising:

[0036] A differential module, configured to collect an original signal received by the transducer, and establish an identification window based on signal parameters of the original signal after performing a differential operation on the original signal, wherein the original signal includes an original upstream signal and an original downstream signal;

[0037] a sampling module, configured to obtain transducer parameters, establish a theoretical model based on the transducer parameters, sample the theoretical model, and perform a cross-correlation operation on the sampled reference signal and the identification window signal within the identification window;

[0038] a correction module, configured to correct the reference signal based on the correlation coefficient of the cross-correlation operation, and to measure the time difference between the arrival times of the upstream signal and the downstream signal in the reference signal multiple times;

[0039] An adjustment module is configured to calculate the time difference stability based on multiple measurement results of the time difference, and dynamically adjust the associated parameters of the identification window according to the time difference stability.

[0040] An embodiment of the present invention provides an electronic device, including a processor and a memory;

[0041] The processor is connected to the memory;

[0042] The memory is used to store executable program code;

[0043] The processor reads the executable program code stored in the memory to run a program corresponding to the executable program code, so as to execute the method described in one or more embodiments.

[0044] An embodiment of the present invention provides a non-transitory computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the steps of the high-precision metering method applicable to an ultrasonic flowmeter are implemented.

[0045] In view of the above, in one or more embodiments of the present specification, the original signal received by the transducer is collected, and after performing a differential operation on the original signal, an identification window is established based on the signal parameters of the original signal, wherein the original signal includes an original upstream signal and an original downstream signal; the transducer parameters are obtained, a theoretical model is established based on the transducer parameters, the theoretical model is sampled, and a cross-correlation operation is performed between the sampled reference signal and the identification window signal within the identification window; the reference signal is corrected based on the correlation coefficient of the cross-correlation operation, and the time difference between the arrival times of the upstream signal and the downstream signal in the reference signal is measured multiple times; the time difference stability is calculated based on the multiple measurement results of the time difference, and the associated parameters of the identification window are dynamically adjusted based on the time difference stability. In this way, by establishing a theoretical model of the signal, the model can be corrected online with the actual received signal, and the signal arrival time can be determined by calculating the correlation coefficient, thereby improving the anti-interference ability and the reliability of the measurement accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0047] Figure 1 This is a flow chart of a high-precision measurement method applicable to an ultrasonic flowmeter provided in one embodiment of this specification.

[0048] Figure 2 This is a structural diagram of a high-precision metering system suitable for an ultrasonic flowmeter provided in an embodiment of this specification.

[0049] Figure 3 This is a structural diagram of an electronic device provided by an embodiment of this specification. DETAILED DESCRIPTION

[0050] The subject matter described herein will now be discussed with reference to example embodiments. It should be understood that these embodiments are discussed only to enable those skilled in the art to better understand and implement the subject matter described herein, and are not intended to limit the scope of protection, applicability, or examples set forth in the claims. The functions and arrangements of the elements discussed may be changed without departing from the scope of protection of this specification. Various examples may omit, replace, or add various processes or components as needed. For example, the described method may be performed in an order different from the order described, and various steps may be added, omitted, or combined. In addition, features described relative to some examples may also be combined in other examples.

[0051] As used herein, the term "including" and its variations are open terms meaning "including but not limited to". The term "based on" means "based at least in part on". The terms "one embodiment" and "an embodiment" mean "at least one embodiment". The term "another embodiment" means "at least one other embodiment". The terms "first", "second", etc. may refer to different or the same objects. Other definitions may be included below, whether explicit or implicit. Unless the context clearly indicates otherwise, the definition of a term is consistent throughout the specification.

[0052] like Figure 1 As shown, an embodiment of the present invention provides a high-precision measurement method applicable to an ultrasonic flow meter, comprising:

[0053] Step S102 : collecting the original signal received by the transducer, performing a differential operation on the original signal, and establishing an identification window based on signal parameters of the original signal, wherein the original signal includes an original upstream signal and an original downstream signal.

[0054] Specifically, the original signal received by the transducer is collected. The original signal includes the original upstream signal transmitted against the direction of fluid flow and received by the upstream transducer, and the original downstream signal transmitted along the direction of fluid flow and received by the downstream transducer. After receiving the original signal, there is noise in the original signal (such as 50 / 60Hz interference from the power supply, motor noise, environmental electromagnetic noise, and other noise). To suppress the noise, a differential operation is performed on the original signal. The differential operation only amplifies the voltage difference between the two signal lines, while significantly suppressing the same voltage (common-mode voltage) on the two lines. As a result, the useful part of the original signal (ultrasonic signal) is amplified and retained, while the useless part (common-mode noise) is significantly weakened. This improves the signal-to-noise ratio, making it easier for subsequent processing to identify the true ultrasonic signal.

[0055] Furthermore, after performing a differential operation on the original signal, an identification window is established based on the original signal's signal parameters. In principle, ultrasonic waves require a certain amount of time (propagation time) from emission to reception. Based on the pipe length and the estimated sound velocity (or flow velocity range), the time range for signal arrival can be roughly predicted. The identification window can be set within this predicted range. The specific values ​​can be expressed as follows:

[0056]

[0057] Where L is the window width (window duration) of the recognition window. The starting time of the recognition window starts from the upstream / downstream transducer receiving the original signal and gradually slides toward the opposite side. is the sampling rate of the original signal, is the excitation frequency of the original signal, and round is the rounding function.

[0058] Step S104 , obtaining transducer parameters, establishing a theoretical model based on the transducer parameters, sampling the theoretical model, and performing a cross-correlation operation on the sampled reference signal and the identification window signal within the identification window.

[0059] Specifically, a series of transducer parameters are acquired and corresponding theoretical models are established based on these parameters. Specifically, a rising-edge theoretical model is established using the parameters of the upstream transducer, and a falling-edge theoretical model is established using the parameters of the downstream transducer. The following description uses the rising-edge theoretical model as an example; the falling-edge theoretical model is similar.

[0060] The rising edge theoretical model is a preset or learned waveform template that represents the shape of the beginning (rising edge) of an ideal ultrasonic signal. It represents the ideal situation (amplitude, slope, shape, etc.) of the signal rising rapidly from nothing under good conditions. The expression of the rising edge theoretical model is as follows:

[0061]

[0062] in, is the transducer damping coefficient, is the angular frequency, is the initial phase, A is the amplitude, and t is the independent variable.

[0063] After establishing the rising edge theoretical model, the continuous analog signal (theoretical model) is discretized and measured at a fixed time interval (sampling interval) and recorded as the rising edge reference signal. , the signal length is consistent with the recognition window width (similarly, the sampling signal of the falling edge theoretical model is the falling edge parameter signal). The rising edge reference signal can provide a reference standard for the correction steps in the subsequent steps.

[0064] Furthermore, a cross-correlation operation is performed on the sampled reference signal and the identification window signal within the identification window to calculate the correlation coefficient between the two. Furthermore, the correlation coefficient can be calculated by sliding the reference signal along the identification window signal sequence to the opposite side within the identification window, with a default step size of 1 (one or more sampling points at a time). At each sliding position, the correlation coefficient between the reference signal and the original signal segment sequence at that position is calculated.

[0065] Taking the rising edge reference signal as an example, the calculation formula of the corresponding correlation coefficient can be as follows:

[0066]

[0067] Where r is the correlation coefficient, It is the signal after the difference operation of the original upstream signal. i is the array table below and starts from 0 by default.

[0068] The correlation coefficient r is an indicator that measures the similarity of the waveform shapes of two signals (the theoretical signal in the theoretical model and the original signal segment in the identification window). The closer the value is to 1, the more similar the shapes are; the closer the value is to 0, the less correlated they are; and the value close to -1 indicates that the shapes are opposite.

[0069] Step S106 , correcting the reference signal based on the correlation coefficient of the cross-correlation operation, and measuring the time difference between the arrival times of the upstream signal and the downstream signal in the reference signal multiple times.

[0070] Specifically, after calculating the correlation coefficient of the cross-correlation operation, the reference signal in the theoretical model is corrected online according to the result of the cross-correlation operation, thereby realizing automatic learning of the real signal characteristics in the current environment. If the aging of the transducer causes the signal to rise slowly, or if there are slight attachments on the inner wall of the pipe that change the acoustic characteristics, the corrected template can gradually adapt to this change and maintain the accuracy of subsequent matching. The robustness of the system to slowly changing interference is greatly improved. Among them, the specific correction scheme can be, for example, pre-setting the correlation threshold, such as 0.8 (which can be freely adjusted and set according to the accuracy level of the flow meter, and is not uniquely limited):

[0071] When the correlation coefficient is greater than or equal to the preset threshold, the correlation between the two is high. The sliding times of the recognition window are used as the arrival time of the reference signal. The rising edge of the current signal is used to correct the rising edge reference signal online. The correction formula is:

[0072]

[0073] Among them, j is the sliding measurement index of the current time, a is the correction coefficient, which can be the minimum value of the correlation coefficient of the five adjacent measurements. When the sliding signal rises, it is the original upstream signal The length of the partial signal in is L.

[0074] When the correlation coefficient is less than the preset threshold, the correlation between the two is low, and the sliding continues according to the specified step size.

[0075] When the number of continuous sliding times is greater than the preset sliding times threshold X, and the correlation coefficient value is less than the preset threshold within the continuous sliding times, it is considered that the reference signal is abnormal and the last calculated value is used instead.

[0076] The preset sliding number threshold X=0.8*N / L, where N is the length of the original signal after the differential operation and L is the recognition window width.

[0077] Furthermore, after the reference signal (including the reference upstream signal and the reference downstream signal) is determined through correction, the absolute time of arrival of the reference signal is calculated. The absolute time of arrival can be calculated as the start time of the identification window + the number of identification window slides * the sampling interval. The difference between the arrival time of the reference downstream signal and the arrival time of the reference upstream signal is calculated multiple times. The term "multiple times" can be a plural number, for example, 10, meaning the difference between the arrival time of the downstream signal and the reference upstream signal is calculated 10 times. This provides a data foundation for parameter stability in subsequent steps.

[0078] Step S108 : calculating the time difference stability based on the multiple measurement results of the time difference, and dynamically adjusting the associated parameters of the recognition window according to the time difference stability.

[0079] Specifically, the time difference stability is calculated based on multiple calculation results of the time difference, wherein the calculation formula of the time difference stability S can be:

[0080]

[0081] in, is the time difference calculated for the current measurement, is the time difference calculated for the last measurement, and m is the number of calculations for the time difference stability.

[0082] Furthermore, the associated parameters of the recognition window, such as the sliding step size and window width of the recognition window, can be dynamically adjusted through the time difference stability S.

[0083] For adjustment of sliding step size:

[0084] When S> A value of *20% indicates significant fluctuations in the data across multiple measurements, indicating high instability. This further indicates poor pipeline stability, a harsh signal environment, or strong interference, making the measurement results unreliable. In this case, the sliding step size can be reduced, for example to 1, to achieve point-by-point sliding and the most precise and intensive search. This increases the probability of finding the true correlation peak amidst noise or distortion, improving detection success rate and positioning accuracy under adverse conditions.

[0085] On the contrary, S≤ *20%, at which point the pipeline is relatively stable and the measurement results are reliable. At this point, the sliding step size can be increased to L. This significantly reduces the amount of calculation and improves system efficiency. Furthermore, because the environment is stable, a larger step size can usually find the accurate peak position.

[0086] To adjust the window width:

[0087] Detect the water temperature value of the pipeline between two measurements. When the water temperature value deviation exceeds 10℃ (preset temperature difference), the temperature difference is large, indicating that the sound speed has changed significantly and the signal arrival time point may be offset. At this time, set the window width to the maximum , expanding the search range to ensure that even if the signal arrival time point has an expected large offset, it can still be covered by the window.

[0088] When the water temperature deviation does not exceed 10°C and the temperature difference is small, it indicates that the sound velocity is basically stable and the expected deviation of the signal arrival time is small. In this case, the window width can be reduced accordingly, for example to 1 / 2 of L. This narrows the search range, means that less irrelevant noise is included, and the risk of false matches is reduced.

[0089] The embodiment of the present invention provides a high-precision metering method suitable for an ultrasonic flowmeter, which collects the original signal received by the transducer, and after performing a differential operation on the original signal, establishes an identification window based on the signal parameters of the original signal, wherein the original signal includes an original upstream signal and an original downstream signal; obtains the transducer parameters, establishes a theoretical model based on the transducer parameters, samples the theoretical model, and performs a cross-correlation operation on the sampled reference signal and the identification window signal in the identification window; corrects the reference signal based on the correlation coefficient of the cross-correlation operation, and measures the time difference between the arrival time of the upstream signal and the downstream signal in the reference signal multiple times; calculates the time difference stability based on the multiple measurement results of the time difference, and dynamically adjusts the associated parameters of the identification window through the time difference stability. In this way, by establishing a signal theoretical model, correcting the model online with the actual received signal, and using the correlation coefficient to calculate and judge the signal arrival time, the anti-interference ability can be improved and the reliability of the metering accuracy can be improved.

[0090] See Figure 2 , Figure 2This is a schematic diagram of a high-precision metering system for ultrasonic flowmeters provided in an embodiment of the present application. Figure 2 As shown, the system includes:

[0091] A differential module S202 is configured to collect an original signal received by the transducer, and after performing a differential operation on the original signal, establish an identification window based on signal parameters of the original signal, wherein the original signal includes an original upstream signal and an original downstream signal;

[0092] Sampling module S204, configured to obtain transducer parameters, establish a theoretical model based on the transducer parameters, sample the theoretical model, and perform a cross-correlation operation on the sampled reference signal and the identification window signal within the identification window;

[0093] a correction module S206, configured to correct the reference signal based on the correlation coefficient of the cross-correlation operation, and measure the time difference between the arrival times of the upstream signal and the downstream signal in the reference signal multiple times;

[0094] The adjustment module S208 is configured to calculate the time difference stability based on multiple measurement results of the time difference, and dynamically adjust the associated parameters of the identification window according to the time difference stability.

[0095] Those skilled in the art will clearly understand that the technical solutions of the embodiments of the present application can be implemented with the help of software and / or hardware. "Unit" and "module" in this specification refer to software and / or hardware that can independently perform or cooperate with other components to perform specific functions, where the hardware can be, for example, a field-programmable gate array (FPGA) or an integrated circuit (IC).

[0096] Each processing unit and / or module in the embodiments of the present application may be implemented by an analog circuit that implements the functions described in the embodiments of the present application, or may be implemented by software that executes the functions described in the embodiments of the present application.

[0097] See also Figure 3 , which shows a schematic diagram of the structure of an electronic device involved in an embodiment of the present application, the electronic device can be used to implement Figure 1 The method in the embodiment shown. Figure 3 As shown, the electronic device 300 may include: at least one processor 301 , at least one network interface 304 , a user interface 303 , a memory 305 , and at least one communication bus 302 .

[0098] The communication bus 302 is used to implement the connection and communication between these components.

[0099] The user interface 303 may include a display screen (Display) and a camera (Camera). Optionally, the user interface 303 may also include a standard wired interface and a wireless interface.

[0100] The network interface 304 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0101] The processor 301 may include one or more processing cores. The processor 301 utilizes various interfaces and circuits to connect various components within the electronic device 300. It executes instructions, programs, code sets, or instruction sets stored in the memory 305, and accesses data stored in the memory 305 to perform various functions and process data within the electronic device 300. Optionally, the processor 301 may be implemented using at least one of the following hardware forms: a digital signal processing (DSP), a field-programmable gate array (FPGA), or a programmable logic array (PLA). The processor 301 may integrate one or a combination of a central processing unit (CPU), a graphics processing unit (GPU), and a modem. The CPU primarily processes the operating system, user interface, and application programs; the GPU is responsible for rendering and drawing content displayed on the display; and the modem handles wireless communications. It is understood that the modem may also be implemented independently of the processor 301 and implemented on a separate chip.

[0102] Among them, the memory 305 may include a random access memory (RAM) or a read-only memory (Read-Only Memory). Optionally, the memory 305 includes a non-transitory computer-readable storage medium. The memory 305 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 305 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc.; the data storage area may store data involved in the above-mentioned various method embodiments, etc. The memory 305 may also be optionally at least one storage device located away from the aforementioned processor 301. As Figure 3 As shown, the memory 305 as a computer storage medium may include an operating system, a network communication module, a user interface module, and program instructions.

[0103] exist Figure 3 In the electronic device 300 shown, the user interface 303 is mainly used to provide an input interface for the user and obtain the data input by the user; and the processor 301 can be used to call the image-generated interactive application stored in the memory 305, and perform the following operations: collect the original signal received by the transducer, and after performing a differential operation on the original signal, establish an identification window based on the signal parameters of the original signal, the original signal includes the original upstream signal and the original downstream signal; obtain the transducer parameters, establish a theoretical model based on the transducer parameters, sample the theoretical model, and perform a cross-correlation operation on the sampled reference signal and the identification window signal in the identification window; correct the reference signal based on the correlation coefficient of the cross-correlation operation, and measure the time difference between the arrival times of the upstream signal and the downstream signal in the reference signal multiple times; calculate the time difference stability based on the multiple measurement results of the time difference, and dynamically adjust the associated parameters of the identification window according to the time difference stability.

[0104] The present application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the above method. The computer-readable storage medium may include, but is not limited to, any type of disk, including a floppy disk, an optical disk, a DVD, a CD-ROM, a microdrive, a magneto-optical disk, a ROM, a RAM, an EPROM, an EEPROM, a DRAM, a VRAM, a flash memory device, a magnetic card or an optical card, a nanosystem (including a molecular memory IC), or any type of medium or device suitable for storing instructions and / or data.

[0105] It should be noted that for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that this application is not limited by the order of the actions described, because according to this application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by this application.

[0106] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0107] In the several embodiments provided in this application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some service interface, and the indirect coupling or communication connection of the device or unit can be electrical or other forms.

[0108] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0109] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0110] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a memory and includes a number of instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned memory includes: U disk, read-only memory (ROM), random access memory (RAM), mobile hard disk, magnetic disk, or optical disk, etc., various media that can store program code.

[0111] Those skilled in the art will appreciate that all or part of the steps in the various methods of the above embodiments may be completed by instructing related hardware through a program. The program may be stored in a computer-readable memory, which may include a flash drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0112] The foregoing description of this specification describes specific embodiments. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be performed in an order different from that described in the embodiments and still achieve the desired results. Furthermore, the processes depicted in the accompanying drawings do not necessarily require the specific order shown or the sequential order to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

Claims

1. A high-precision measurement method applicable to an ultrasonic flowmeter, the method comprising: Collecting an original signal received by the transducer, and establishing an identification window based on signal parameters of the original signal after performing a differential operation on the original signal, wherein the original signal includes an original upstream signal and an original downstream signal; Acquiring transducer parameters, establishing a theoretical model based on the transducer parameters, sampling the theoretical model, and performing a cross-correlation operation on the sampled reference signal and the identification window signal within the identification window; Correcting the reference signal based on the correlation coefficient of the cross-correlation operation, and measuring the time difference between the arrival times of the upstream signal and the downstream signal in the reference signal multiple times; The time difference stability is calculated based on multiple measurement results of the time difference, and the associated parameters of the identification window are dynamically adjusted according to the time difference stability.

2. The method according to claim 1, characterized in that The calculation formula of the recognition window width includes: ， Among them, L is the window width of the recognition window, is the sampling rate of the original signal, is the excitation frequency of the original signal, and round is the rounding function.

3. The method according to claim 2, characterized in that The cross-correlation operation of the sampled reference signal and the identification window signal within the identification window includes: Slide the sampled reference signal along the opposite side, and at each sliding position, calculate the correlation coefficient of the correlation series between the reference signal and the series of original signal segments at the sliding position; The calculation formula of the correlation coefficient includes: ， Where r is the correlation coefficient, is the signal after the differential operation of the original upstream signal, i is the array table below, is the rising signal in the reference signal.

4. The method according to claim 3, characterized in that The modifying the reference signal based on the correlation coefficient of the cross-correlation operation includes: When the correlation coefficient is greater than or equal to the preset threshold, the sliding times of the identification window are used as the reference signal arrival time, and the rising edge reference signal is corrected online. The correction formula is: ， Among them, j is the sliding measurement index, a is the correction coefficient, When the sliding signal rises, it is the original upstream signal Part of the signal in, the length is L; When the correlation coefficient is less than the preset threshold, the reference signal continues to slide according to the specified step size.

5. The method according to claim 4, characterized in that The method further comprises: The sliding times of the reference signal are counted, and when it is detected that the sliding times are greater than a preset sliding times threshold, and within the sliding times, the correlation coefficient is continuously less than the preset threshold, it is determined that the reference signal is abnormal.

6. The method according to claim 5, characterized in that The calculation formula for calculating the time difference stability based on multiple time difference measurement results includes: ， in, is the time difference calculated for the current measurement, is the time difference calculated for the last measurement, and m is the number of calculations for the time difference stability.

7. The method according to claim 6, characterized in that The dynamically adjusting the associated parameters of the identification window by using the time difference stability includes: Adjusting the sliding step size of the recognition window includes: When S> *20%, reduce the sliding step size to unit step size; When S≤ *20%, increase the sliding step size to L; Adjusting the window width of the recognition window includes: Detecting a difference in pipe water temperature between two measurements, and when the water temperature difference is greater than a preset temperature difference, expanding the window width; When the water temperature difference is less than a preset temperature difference, the window width is reduced.

8. A high-precision metering system suitable for ultrasonic flowmeters, characterized in that: The system comprises: A differential module, configured to collect an original signal received by the transducer, and establish an identification window based on signal parameters of the original signal after performing a differential operation on the original signal, wherein the original signal includes an original upstream signal and an original downstream signal; a sampling module, configured to obtain transducer parameters, establish a theoretical model based on the transducer parameters, sample the theoretical model, and perform a cross-correlation operation on the sampled reference signal and the identification window signal within the identification window; a correction module, configured to correct the reference signal based on the correlation coefficient of the cross-correlation operation, and to measure the time difference between the arrival times of the upstream signal and the downstream signal in the reference signal multiple times; An adjustment module is configured to calculate the time difference stability based on multiple measurement results of the time difference, and dynamically adjust the associated parameters of the identification window according to the time difference stability.

9. An electronic device comprising a processor and a memory; The processor is connected to the memory; The memory is used to store executable program code; The processor reads the executable program code stored in the memory to run a program corresponding to the executable program code, so as to execute the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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