Characteristic wave identification method and device of ultrasonic flowmeter

Abstract

The invention discloses a method and a device for identifying characteristic waves of an ultrasonic flowmeter, which are used for quickly identifying the characteristic waves by judging whether a wave crest point is one of the wave crest points of the characteristic waves or not according to a growth rate. Compared with the prior art in which a threshold value or a time window is set, the method has the advantages that even if the peak value of the clutter is high or the clutter appears in the time window, the clutter can be accurately identified and distinguished according to the growth rate k, the characteristic wave identification accuracy of the transducer is improved, and therefore the measurement accuracy of the ultrasonic flowmeter is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of signal processing, and in particular to the technical field of ultrasonic signal processing. Background Art

[0002] Ultrasonic water meters are meters that use ultrasonic technology to measure fluid flow. Its working principle is mainly based on the Doppler effect or the time difference method. The working principle of the time difference method is that two ultrasonic transducers are built into the ultrasonic water meter, one as a transmitter and the other as a receiver. The two transducers are located upstream and downstream of the fluid respectively. The transmitter of the ultrasonic flow meter will emit characteristic waves at a certain frequency, and the receiver will detect the characteristic waves after propagation through the fluid and record their arrival time. The signal processing unit will analyze the received signal, identify the characteristic waves, and calculate the flight time. By measuring the time difference between the emission and reception of the characteristic wave, the flight time of the ultrasonic wave in the fluid can be calculated. Knowing the flight time, combined with the speed of sound in the fluid, the fluid flow rate can be calculated.

[0003] Therefore, the stability and identifiability of the characteristic wave directly affect the accuracy of flow measurement. In particular, in actual application scenarios, there will be many external interference factors such as scaling on the transducer surface, a lot of impurities, environmental noise, etc. The appearance of these external interference factors will cause noise interference in the signal, which may cause the transducer to be unable to accurately identify the characteristic wave, thereby affecting the accuracy of flow measurement. In order to improve the accuracy of recognition in the prior art, an amplitude threshold is set, and only signals exceeding this threshold are regarded as characteristic waves. Alternatively, a time window is set at the receiver end, and only signals arriving within this window are considered characteristic waves. However, when the peak value of the noise is high or appears within the time window, the above technical means cannot perform good recognition. Summary of the invention

[0004] In view of the problems existing in the prior art, the present invention proposes a characteristic wave identification method and device for an ultrasonic flowmeter, which improves the accuracy of the transducer in identifying the characteristic wave, thereby improving the accuracy of flow measurement.

[0005] In order to achieve the above-mentioned object of the invention, the present invention adopts the following technical solutions:

[0006] A characteristic wave identification method for an ultrasonic flowmeter, characterized by comprising the following steps:

[0007] Receive a waveform signal v=f(t), and obtain each peak point A in the waveform signal v=f(t) i and its corresponding position (t i , f(t i )); where i is the count of the peak points;

[0008] Calculate the peak point A i The corresponding growth rate k i ,

[0009]

[0010] If the growth rate k i In the preset first theoretical interval, it is considered that the peak point A i It is a peak point of the characteristic wave.

[0011] In the application field of ultrasonic flowmeters, the received waveform signal is prone to the coexistence of characteristic waves and clutter. At this time, it is impossible to accurately identify the clutter and characteristic waves. Characteristic waves are considered to be valid waves, while clutter is basically considered to be invalid waves. Since the growth rate k corresponding to each peak point of the characteristic wave is a fixed value. For example, if the growth rate k corresponding to a peak point of a standard characteristic wave is 0.9, the staff can set the first theoretical interval to 0.9±0.15, and judge the peak points A in the waveform signal v=f(t). i The corresponding growth rate k i , whether it is in the first theoretical interval set, if so, it is considered that the peak point A i is the first peak point of the characteristic wave; of course, the staff can also set the first theoretical interval within the interval range of the growth rate k corresponding to other peak points of the standard characteristic wave. By correctly identifying one of the peak points of the characteristic wave, the technicians in this field can find the characteristic wave more conveniently and quickly, so as to continue the subsequent calculation of flight time and flow velocity. i It can be calculated by taking the derivative.

[0012] This technical solution distinguishes whether the peak point is one of the peak points of the characteristic wave by judging the growth rate, thereby quickly identifying the characteristic wave. Compared with the prior art by setting a threshold or time window, even if there is a high peak value of the clutter or it appears within the time window, it can be accurately identified and distinguished by the growth rate k, thereby improving the accuracy of the transducer in identifying the characteristic wave, thereby improving the accuracy of the ultrasonic flowmeter measurement.

[0013] As a preferred embodiment of the present invention, the characteristic wave identification method of the ultrasonic flowmeter further comprises a re-testing step:

[0014] If the growth rate k i In the first theoretical interval, we continue to judge k i+1 Is it in the preset second theoretical interval? If so, determine the peak point A i and the peak point Ai+1 Each of them is a peak point of the characteristic wave.

[0015] Those skilled in the art can preset the first theoretical interval and the second theoretical interval based on the growth rates corresponding to two different peak points of a standard characteristic wave. For example, the growth rate k corresponding to the secondary peak point of a standard characteristic wave is 0.9, and the growth rate k corresponding to the next peak point is 0.461. At this time, the staff can set the first theoretical interval to 0.9±0.15 and the second theoretical interval to 0.461±0.1. When the growth rates of two adjacent peak points fall within these two intervals at the same time, the bands corresponding to these two peak points are identified as the characteristic wave.

[0016] By setting two theoretical intervals and performing a secondary judgment and re-verification, the possibility of misidentifying clutter as a characteristic wave can be reduced. Even if the growth rate of a peak point meets the first theoretical interval of the characteristic wave, if the growth rate of the subsequent peak points does not meet the second theoretical interval, then this peak point will not be mistakenly marked as the peak of the characteristic wave. Ensure that a series of peak points that meet the characteristic wave pattern are identified, not just a single peak point.

[0017] In addition, since the second peak point of the characteristic wave is in a more stable stage than the first peak point and is easier to capture than the following peak points, the second peak point of the characteristic wave is usually identified to determine the flight time of the ultrasonic signal, which helps to improve the resolution of time measurement and thus improve the accuracy of flow velocity measurement. In short, by setting two theoretical intervals and making secondary judgments, the characteristic wave and its first and second peak points can be more accurately identified, and the flight time calculation can be more accurate, thereby improving the accuracy of ultrasonic flow meter measurement.

[0018] The peak point A i The specific way to obtain is:

[0019] Based on the waveform signal v=f(t), the voltage value v is obtained by solving j The corresponding solution set, where j is a natural number and v j <v j+1 ;

[0020] The voltage value v is calculated j The corresponding ratio R j ,

[0021]

[0022] Where T is the fixed period of the signal of the known ultrasonic transducer; t j1 and t j2 is the voltage value v jThe two solutions with the smallest values ​​in the corresponding solution set;

[0023] When R j <R j+1 When the peak point A is obtained i And corresponding (t i , f(t i )),

[0024] in,

[0025] When a peak appears, R will gradually decrease and approach 0 as the voltage value increases. If at a certain point, R j <R j+1 , indicating that another wave with a larger peak has appeared. At this time, through The peak point A is calculated i The position (t i , f(t i )). In this technical solution, by comparing R j and R j+1 , select the peak points A that increase in sequence i , reducing the number of peak points that need to be calculated and judged for the growth rate, thereby reducing the overall amount of calculation and improving the efficiency of the recognition process. Especially in scenarios that require real-time processing, reducing the amount of calculation can speed up the processing speed, allowing the system to respond and identify characteristic waves more quickly. In addition, this method focuses on the most likely peak points of characteristic waves, rather than analyzing all peak points indiscriminately, which simplifies the complexity of the calculation and reduces the possibility of misidentification, thereby improving the accuracy of characteristic wave recognition.

[0026] As a preferred embodiment of the present invention, the peak point A i The acquisition methods also include:

[0027] Set the noise threshold v t , for noise above the threshold v t The voltage value v j Then the solution is obtained to obtain the corresponding solution set, and i={1, 2, 3}.

[0028] In actual application scenarios, some noise signals in the waveform signal v=f(t) generally have small amplitudes. Therefore, a noise threshold v can be pre-set. t , for noise above the threshold v t The voltage value v j Then the corresponding ratio R jSolving, while ensuring the recognition accuracy, further reducing the amount of calculation, so that the system can respond and identify characteristic waves faster. In addition, by setting the v t And the v j ≥v t Most of the noise is filtered out. When the voltage value v is continuously increased j Calculate the ratio R j Thus we get A 1 ,A 2 ,A 3 After the first three peaks, it is almost certain that A 1 ,A 2 ,A 3 There must be one or more peak points of the characteristic wave, so there is no need to continue calculating the other voltage values ​​v j Corresponding to the ratio R j , thereby reducing the overall amount of calculation and improving the efficiency of the recognition process.

[0029] As a preferred embodiment of the present invention, the characteristic wave identification method of the ultrasonic flowmeter further comprises a confirmation step:

[0030] If the growth rate k i If it is not within the first theoretical interval, then continue to determine the growth rate k i Is it within the preset second theoretical interval? If so, it is considered that the peak point A i is the second peak of the characteristic wave; the first theoretical interval and the second theoretical interval are respectively based on the growth rate k corresponding to the first peak point and the second peak point of the standard characteristic wave i Make pre-settings.

[0031] In actual application scenarios, signal attenuation may sometimes occur. At this time, the first peak point of the characteristic wave will be close to 0 or less than the noise threshold v due to signal attenuation. t The following peaks of the characteristic wave are still higher than the noise threshold v due to their high amplitude. t . At this time, the obtained A will appear 1 ,A 2 ,A 3 It is not the first peak of the characteristic wave, but it may be the second peak of the characteristic wave. i If it is not within the first theoretical interval, then continue to determine the growth rate k i Is it within the preset second theoretical interval? If so, it means that the signal is attenuated, then it is considered that the peak point A iThe method takes into account the signal attenuation problem in practical applications and ensures that the ultrasonic flowmeter can provide accurate measurement results under various conditions through flexible judgment criteria.

[0032] A characteristic wave identification device for an ultrasonic flow meter, characterized by comprising:

[0033] A receiving module receives a waveform signal v=f(t);

[0034] The peak point acquisition module acquires each peak point A in the waveform signal v=f(t) i position(ti,f(ti));

[0035] Growth rate calculation module, calculates the peak point A i The corresponding growth rate k i , where i is the count of the peak points;

[0036]

[0037] A determination module is used to determine the growth rate k i Is it in the preset first theoretical interval? If so, determine the peak point A i It is a peak point of the characteristic wave.

[0038] As a preferred embodiment of the present invention, it is characterized in that the characteristic wave identification device of the ultrasonic flow meter further comprises a re-test module:

[0039] If the growth rate k i In the first theoretical interval, we continue to judge k i+1 Is it in the preset second theoretical interval? If so, determine the peak point A i and the peak point A i+1 Each is a peak of a characteristic wave.

[0040] As a preferred embodiment of the present invention, it is characterized in that the peak point acquisition module specifically comprises:

[0041] Solution collection acquisition module,

[0042] Set the noise threshold v t , based on the waveform signal v = f (t) above the noise threshold v t The voltage value v j Solve to get the corresponding solution set, where j is a natural number and v j <v j+1 ,

[0043] Ratio R j Computing module,

[0044] The voltage value v is calculated j The corresponding ratio R j ,

[0045]

[0046] Where T is the fixed period of the signal of the known ultrasonic transducer; t j1 and t j2 is the voltage value v j The two solutions with the smallest values ​​in the corresponding solution set;

[0047] The result acquisition module, when R j <R j+1 When the peak point A is obtained i And corresponding (t i , f(t i )),

[0048] in, i={1,2,3}.

[0049] A computer-readable storage medium stores a computer program, wherein the computer-readable storage medium stores instructions, and when the instructions are executed on a computer or a processor, the computer or the processor executes the steps of the characteristic wave identification method of the ultrasonic flow meter.

[0050] In summary, the present invention has the following beneficial effects:

[0051] 1. This technical solution distinguishes whether the peak point is one of the peak points of the characteristic wave by judging the growth rate, thereby quickly identifying the characteristic wave.

[0052] 2. By setting two theoretical intervals and conducting a secondary judgment and re-verification, the possibility of misidentifying clutter as characteristic waves can be reduced.

[0053] 3. By comparing R j and R j+1 , select the peak points A that increase in sequence i , reducing the number of peak points that need to be calculated and judged for growth rate, thereby reducing the overall amount of calculation and improving the efficiency of the recognition process.

[0054] 4. Preset a noise threshold v t , for noise above the threshold v t The voltage value v j Then the corresponding ratio R j The solution can further reduce the amount of calculation while ensuring the recognition accuracy, so that the system can respond and identify characteristic waves more quickly.

[0055] 5. Taking into account the signal attenuation problem in practical applications, flexible judgment criteria are used to ensure that the ultrasonic flow meter can provide accurate measurement results under various conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0057] Figure 1 It is a partial waveform diagram of the standard characteristic wave;

[0058] Figure 2 It is a schematic diagram for representing the ratio R;

[0059] Figure 3 Schematic diagram of the identification device;

[0060] Figure 4 Get the module diagram for the peak point. DETAILED DESCRIPTION

[0061] The present invention is further described below by specific examples and drawings. The examples of the present invention are intended to enable those skilled in the art to better understand the present invention, and do not limit the present invention in any way.

[0062] Figure 1 As shown in FIG. 1 , part of the waveform of the standard characteristic wave of the ultrasonic water meter transducer measured by an oscilloscope is shown. The ultrasonic water meter model used in the embodiment of the present invention is the GP30 ultrasonic water meter. As can be seen from the figure, the standard characteristic wave contains a plurality of successively increasing peak points, and the peak value growth of the first few peak points is more obvious, and the amplitudes are: 16mV, 68.95mV, 131.02mV, 191.44mV, 231.27mV respectively.

[0063] The corresponding growth rates k of the first three peak points of a standard characteristic wave are calculated to be 3.3, 0.9, and 0.461 respectively. Growth rate k = the difference between the amplitude of the peak point and the next peak point / the amplitude of the peak point.

[0064] In the application field of ultrasonic flowmeter, the waveform signal received by the receiver is prone to coexistence of characteristic waves and clutter. At this time, it is impossible to accurately identify clutter and characteristic waves. Those skilled in the art can identify whether it is one of the peak points of the characteristic wave by calculating the growth rate k corresponding to the signal peak point in the received waveform signal v=f(t), so as to find the characteristic wave more conveniently and quickly, and continue the subsequent calculation of flight time and flow rate.

[0065] The specific identification method is as follows:

[0066] Receive the waveform signal v=f(t), and obtain each peak point A in the waveform signal v=f(t) i and its corresponding position (t i , f(t i )). Where i is the number of peak points. Each peak point A in the waveform signal v = f(t) i It can be calculated by taking the derivative.

[0067] Calculate the peak point A i The corresponding growth rate k i ,

[0068]

[0069] If the growth rate k i In the preset first theoretical interval, it is considered that the peak point A i is a peak point of the characteristic wave. The staff can set the first theoretical interval within the interval range of the growth rate k corresponding to one of the peak points of the standard characteristic wave. Since the second peak point of the characteristic wave is in a more stable stage than the first peak point, and is easier to capture than the following peak points, it is usually determined by identifying the second peak point of the characteristic wave to determine the flight time of the ultrasonic signal, which helps to improve the resolution of time measurement and thus improve the accuracy of flow velocity measurement. Therefore, in this embodiment, the first theoretical interval is centered on the growth rate (0.9) corresponding to the second peak point of the standard characteristic waveform, and a symmetrical tolerance interval is set with a width of ±0.15. The half width (i.e., standard deviation) of the tolerance interval can be adjusted accordingly according to the actual operating environment, instrument performance, and the professional judgment of the operator.

[0070] In order to improve the recognition accuracy, a re-test step can be added to the recognition method: if the growth rate k i In the first theoretical interval, we continue to judge k i+1 Is it in the preset second theoretical interval? If so, determine the peak point A i and peak point A i+1 Each of them is a peak point of the characteristic wave.

[0071] The second theoretical interval can be set by the staff based on experience, or a parameterized interval setting strategy corresponding to the first theoretical interval can be adopted. This interval uses the growth rate corresponding to the third-level peak in the standard characteristic waveform as the reference value to determine the interval range. The setting logic of the second theoretical interval is consistent with the first theoretical interval, including the symmetry of the interval width and the adjustability based on experimental data. Therefore, a detailed description will not be repeated here.

[0072] By setting two theoretical intervals and performing a secondary judgment and re-verification, the possibility of misidentifying clutter as a characteristic wave can be reduced. Even if the growth rate of a peak point meets the first theoretical interval of the characteristic wave, if the growth rate of the subsequent peak points does not meet the second theoretical interval, then this peak point will not be mistakenly marked as the peak of the characteristic wave. Ensure that a series of peak points that meet the characteristic wave pattern are identified, not just a single peak point.

[0073] As another embodiment of the present invention, the peak point A i It can also be obtained through:

[0074] Based on the waveform signal v = f(t), the voltage value v is obtained j The corresponding solution set, where j is a natural number and v j <v j+1 ;

[0075] Calculate the voltage value v j The corresponding ratio R j ,

[0076]

[0077] Where T is the fixed period of the signal of the known ultrasonic transducer; t j1 and t j2 is the voltage value v j The two solutions with the smallest values ​​in the corresponding solution set;

[0078] When R j <R j+1 When the peak point A is obtained i And corresponding (t i , f(t i )),

[0079] in,

[0080] like Figure 2 As shown in the figure, when a peak appears, R will gradually decrease and approach 0 as the voltage value increases. If at a certain point, R j <R j+1, indicating that another wave with a larger peak has appeared. At this time, through Calculate the peak point A i The position (t i , f(t i )). In this technical solution, by comparing R j and R j+1 , select the peak points A that increase in sequence i , reducing the number of peak points that need to be calculated and judged for the growth rate, thereby reducing the overall amount of calculation and improving the efficiency of the recognition process. Especially in scenarios that require real-time processing, reducing the amount of calculation can speed up the processing speed, allowing the system to respond and identify characteristic waves more quickly. In addition, this method focuses on the most likely peak points of characteristic waves, rather than analyzing all peak points indiscriminately, which simplifies the complexity of the calculation and reduces the possibility of misidentification, thereby improving the accuracy of characteristic wave recognition.

[0081] In actual application scenarios, some noise signals in the waveform signal v = f(t) generally have small amplitudes. Therefore, in order to further simplify the overall calculation amount and improve the efficiency of the recognition process, a noise threshold v can be set in advance. t , for values ​​above the noise threshold v t The voltage value v j Then the corresponding ratio R j While ensuring the recognition accuracy, the amount of calculation is further reduced, so that the system can respond and identify characteristic waves more quickly.

[0082] In addition, by setting v t And v j ≥v t Most of the noise is filtered out. When the voltage value v is continuously increased j Calculate the ratio R j Thus we get A 1 ,A 2 ,A 3 After the first three peaks, it is almost certain that A 1 ,A 2 ,A 3 There must be one or more peak points of the characteristic wave, so there is no need to continue calculating other voltage values ​​v j Corresponding ratio R j , thereby reducing the overall amount of calculation and improving the efficiency of the recognition process.

[0083] However, in some application scenarios, signal attenuation may occur. At this time, the first peak of the characteristic wave will be close to 0 or less than the noise threshold v due to signal attenuation. t The following peaks of the characteristic wave are still higher than the noise threshold v due to their high amplitude.t . At this time, the obtained A will appear 1 ,A 2 ,A 3 Neither is the first peak of the characteristic wave, but it may be the second peak of the characteristic wave.

[0084] Therefore, the recognition method of this embodiment can also add a confirmation step: if the growth rate k i If it is not within the first theoretical interval, continue to determine the growth rate k i Is it within the preset second theoretical interval? If so, it means that the signal is attenuated, and the peak point A is considered i is the second peak of the characteristic wave. The peak value of the first peak of the characteristic wave can be obtained by reverse calculation based on the corresponding growth rate k of the first peak point of a standard characteristic wave.

[0085] This method takes into account the signal attenuation problem in practical applications and ensures that the ultrasonic flow meter can provide accurate measurement results under various conditions through flexible judgment criteria.

[0086] A characteristic wave identification device for an ultrasonic flow meter, such as Figure 3 As shown, including:

[0087] Receiver Module

[0088] Receive waveform signal v=f(t);

[0089] Peak point acquisition module,

[0090] Get each peak point A in the waveform signal v=f(t) i Position (t i , f(t i ));

[0091] Growth rate calculation module,

[0092] Calculate the peak point A i The corresponding growth rate k i , where i is the count of the peak points;

[0093]

[0094] Discrimination module,

[0095] Determine the growth rate k i Is it in the preset first theoretical interval? If so, determine the peak point A i It is a peak point of the characteristic wave.

[0096] Retest module,

[0097] If the growth rate k iIn the first theoretical interval, we continue to judge k i+1 Is it in the preset second theoretical interval? If so, determine the peak point A i and peak point A i+1 Each is a peak of a characteristic wave.

[0098] Acknowledgement module,

[0099] If the growth rate k i If it is not within the first theoretical interval, continue to determine the growth rate k i Is it within the preset second theoretical interval? If so, it is considered that the peak point A i is the second peak of the characteristic wave; the first theoretical interval and the second theoretical interval are based on the growth rate k corresponding to the first peak point and the second peak point of the standard characteristic wave respectively. i Make pre-settings.

[0100] Among them, Figure 4 As shown, the peak point acquisition module specifically includes:

[0101] Solution set acquisition module, set the noise threshold v t , based on the waveform signal v = f(t) above the noise threshold v t The voltage value v j Solve to get the corresponding solution set, where j is a natural number and v j <v j+1 ,

[0102] Ratio R j Calculation module, calculates the voltage value v j The corresponding ratio R j ,

[0103]

[0104] Where T is the fixed period of the signal of the known ultrasonic transducer; t j1 and t j2 is the voltage value v j The two solutions with the smallest values ​​in the corresponding solution set;

[0105] The result acquisition module, when R j <R j+1 When the peak point A is obtained i And corresponding (t i , f(t i )),in, i={1,2,3}.

[0106] It should be noted that the above embodiments are only detailed descriptions of the preferred embodiments and principles of the present invention. For ordinary technicians in this field, there will be changes in the specific implementation methods based on the ideas provided by the present invention, and these changes are also considered to be within the scope of protection of the present invention.

Claims

1. A characteristic wave identification method for an ultrasonic flowmeter, characterized in that: The following steps are involved: Receive a waveform signal v=f(t), and obtain a peak point A in the waveform signal v=f(t) i Position (t i , f(t i )), where i is the count of the peak points; Calculate the peak point A i The corresponding growth rate k i , If the growth rate k i In the preset first theoretical interval, it is considered that the peak point A i It is a peak point of the characteristic wave.

2. The characteristic wave identification method of an ultrasonic flowmeter according to claim 1, characterized in that: It also includes the following steps: If the growth rate k i In the first theoretical interval, we continue to judge k i+1 Is it in the preset second theoretical interval? If so, determine the peak point A i and the peak point A i+1 Each of them is a peak point of the characteristic wave.

3. The characteristic wave identification method of an ultrasonic flowmeter according to claim 1, characterized in that: The peak point A i The specific way to obtain is: Based on the waveform signal v=f(t), the voltage value v is obtained by solving j The corresponding solution set, where j is a natural number and v j <v j+1 ; The voltage value v is calculated j The corresponding ratio R j , Where T is the fixed period of the signal of the known ultrasonic transducer; t j1 and t j2 is the voltage value v j The two solutions with the smallest values ​​in the corresponding solution set; When R j <R j+1 When the peak point A is obtained i And corresponding (t i , f(t i )), in, 4. The characteristic wave identification method of an ultrasonic flowmeter according to claim 3, characterized in that: The peak point A i The acquisition methods also include: Set the noise threshold v t , only for noise values ​​above the noise threshold v t The voltage value v j The solution is obtained by solving the corresponding solution set, and i={1, 2, 3}.

5. The characteristic wave identification method of an ultrasonic flowmeter according to claim 4, characterized in that: It also includes the confirmation step: If the growth rate k i If it is not within the first theoretical interval, it is further determined whether it is within the preset second theoretical interval. If so, it is considered that the peak point A i is the second peak of the characteristic wave; the first theoretical interval and the second theoretical interval are pre-set based on the growth rates corresponding to the first peak point and the second peak point of the standard characteristic wave respectively.

6. A characteristic wave identification device for an ultrasonic flowmeter, characterized in that: Include: A receiving module receives a waveform signal v=f(t); The peak point acquisition module acquires the peak point A in the waveform signal v=f(t) i Position (t i , f(t i )), where i is the count of the peak points; Growth rate calculation module, calculates the peak point A i The corresponding growth rate k i , A determination module is used to determine the growth rate k i Is it in the preset first theoretical interval? If so, determine the peak point A i It is a peak point of the characteristic wave.

7. A characteristic wave identification device for an ultrasonic flowmeter according to claim 6, characterized in that: Also includes retest module: If the growth rate k i In the first theoretical interval, we continue to judge k i+1 Is it in the preset second theoretical interval? If so, determine the peak point A i and the peak point A i+1 Each is a peak of a characteristic wave.

8. The characteristic wave identification device of an ultrasonic flowmeter according to claim 6, characterized in that: The peak point acquisition module specifically includes: Solution collection acquisition module, Set the noise threshold v t , based on the waveform signal v = f (t) above the noise threshold v t The voltage value v j Solve to get the corresponding solution set, where j is a natural number and v j <v j+1 , Ratio R j Computing module, The voltage value v is calculated j The corresponding ratio R j , Where T is the fixed period of the signal of the known ultrasonic transducer; t j1 and t j2 is the voltage value v j The two solutions with the smallest values ​​in the corresponding solution set; Peak point acquisition module, when R j <R j+1 When the peak point A is obtained i Position (t i , f(t i )), in, 9. A computer-readable storage medium having a computer program stored thereon, wherein the computer-readable storage medium has instructions stored therein, and when the instructions are executed on a computer or a processor, the computer or the processor executes the steps of the characteristic wave identification method of the ultrasonic flow meter.

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