A method for measuring time-of-flight of ultrasonic echo signals with low signal-to-noise ratio

Abstract

Embodiments of the present invention provide a method for measuring the time-of-flight of a low-signal-to-noise ratio ultrasonic echo signal, relating to the field of measurement technology. The method comprises the steps of acquiring an echo signal; performing noise reduction and reconstruction on the acquired echo signal using an empirical wavelet transform to obtain a reconstructed echo signal; obtaining a preset reference echo peak value and a reconstructed echo peak value, and calculating the echo characteristic peak of the echo signal using a preset characteristic peak location algorithm; obtaining echo characteristic points of the echo; and measuring the echo time-of-flight based on the obtained echo characteristic points according to a preset measurement algorithm. This method can achieve higher-precision time-of-flight measurements of ultrasonic echo signals using a simpler calculation method.

Description

Technical Field

[0001] The present invention relates to the field of measurement technology, and in particular to a method for measuring the time of flight of a low signal-to-noise ratio ultrasonic echo signal. Background Art

[0002] Gas ultrasonic flowmeters have the advantages of simple structure, high measurement accuracy, small pressure loss, and wide range ratio. They are widely used in petrochemical, electric power, metallurgy, environmental protection, water conservancy and other fields.

[0003] Currently, most gas ultrasonic flowmeters use the time-of-flight method for measurement. This method uses the difference in the forward and reverse flight times of ultrasonic waves propagating through the pipeline medium to determine the linear velocity of the medium and, in turn, calculate the instantaneous flow rate. Therefore, the accuracy of time-of-flight measurements determines the metering performance of the gas ultrasonic flowmeter. However, in actual operating conditions, gas ultrasonic flowmeters based on the time-of-flight method suffer from high echo noise, low signal-to-noise ratio, inaccurate echo feature point positioning, and low time-of-flight measurement accuracy.

[0004] Currently, time-of-flight measurement methods primarily include threshold methods, cross-correlation methods, and signal fitting. The threshold method is widely used for time-of-flight measurement due to its low computational complexity, ease of implementation, and simple principle. This method accurately determines the time of flight by locating echo feature points. However, changes in the operating environment can easily lead to inaccurate positioning of echo feature points. While accurate positioning of echo feature points through threshold adjustment can improve time-of-flight measurement accuracy, it still has certain limitations in low signal-to-noise ratio conditions. Summary of the Invention

[0005] In order to solve the problems in the prior art, the present invention provides a method for measuring the flight time of an ultrasonic echo signal with a low signal-to-noise ratio, which can obtain a more accurate measurement method of the flight time of an echo signal through simple calculation.

[0006] The embodiments of the present invention can be implemented as follows:

[0007] A method for measuring the time of flight of a low signal-to-noise ratio ultrasonic echo signal comprises the following steps:

[0008] S1: collect echo signals;

[0009] S2: De-noise and reconstruct the collected echo signal through empirical wavelet transform, and obtain the reconstructed echo signal;

[0010] Step S2 includes:

[0011] S21: adaptively decomposing the collected echo signal through empirical wavelet transform to obtain decomposition components;

[0012] S22: Obtaining useful components from the decomposed components according to a preset extraction algorithm;

[0013] Step S22: Obtaining useful components from the decomposed components according to a preset extraction algorithm includes the following steps:

[0014] S221: Obtain the number of maximum values ​​in the decomposed components in step S21, and the number of preset values ​​to define boundary points;

[0015] S222: Based on the empirical wavelet function ω n and scaling function φ n (ω) and the detail coefficient generated by the inner product of the signal and approximation coefficients obtaining a reconstructed echo signal;

[0016] The empirical wavelet function ω in step S222 n for:

[0017]

[0018] The original signal is decomposed into N continuous intervals, using Λ n =[ω n-1 ,ω n ], n=1,2,3..., N represents the division interval,

[0019] where ω n Indicates the boundary between each segment, ω0=0, ω n =π

[0020] The scaling function φ in step S222 n (ω) is:

[0021]

[0022] The original signal is decomposed into N continuous intervals, using Λ n =[ω n-1 ,ω n ], n=1,2,3..., N represents the division interval,

[0023] where ω n Indicates the boundary between each segment, ω0=0, ω n =π

[0024] The detail coefficients generated by the inner product of the signal in step S222

[0025]

[0026] The original signal is decomposed into N continuous intervals, using Λ n =[ω n-1,ω n ], n=1,2,3..., N represents the division interval,

[0027] where ω n Indicates the boundary between each segment, ω0=0, ω n =π

[0028] is ψ n (ω),φ n The complex conjugate of (ω), F -1 [*] is the inverse Fourier transform

[0029] Approximation coefficient in step S222

[0030]

[0031] The original signal is decomposed into N continuous intervals, using Λ n =[ω n-1 ,ω n ], n=1,2,3..., N represents the division interval,

[0032] where ω n Indicates the boundary between each segment, ω0=0, ω n =π

[0033] is ψ n (ω),φ n The complex conjugate of (ω), F -1 [*] is the inverse Fourier transform

[0034] The reconstructed echo signal is:

[0035]

[0036] Among them, X k (t) is the decomposition component:

[0037]

[0038] S223: performing correlation calculation on the obtained decomposition components and the echo signal collected in step S1 in sequence according to a preset order;

[0039] S224: When the correlation is greater than a preset threshold, the decomposed component corresponding to the correlation is a preset useful component.

[0040] S23: Superimposing the obtained useful components to obtain a reconstructed echo signal.

[0041] S3: Obtain a preset reference echo, perform normalization processing on the preset reference echo signal, obtain the preset reference echo peak value and the reconstructed echo peak value, and calculate the echo characteristic peak of the echo signal by using a preset characteristic peak positioning algorithm;

[0042] Step S3 includes:

[0043] S31: Acquire a preset reference echo;

[0044] S32: performing normalization processing on the acquired preset reference echo signal, and obtaining a preset reference echo peak value and a reconstructed echo peak value;

[0045] S33: obtaining the first echo peak value, the second echo peak value, and the third echo peak value of three consecutive cycles preset in the reference echo, and obtaining the echo peak value of any three consecutive cycles of the reconstructed echo;

[0046] S34: performing cosine distance calculation between the echo peak value of three consecutive cycles preset in the reference echo and the echo peak value of any three consecutive cycles in the obtained reconstructed echo;

[0047] S35: Obtaining the cosine distances between the echo peaks of the remaining three consecutive cycles in the reconstructed echo and the echo peaks of the preset three consecutive cycles in the reference echo; sorting all the calculated cosine distances according to their numerical values, and finding the reconstructed echo of three consecutive cycles corresponding to the maximum cosine distance;

[0048] S36: Obtain the preset echo characteristic peak position in the preset reference echo in step S33, and obtain the echo characteristic peak position of the reconstructed echo corresponding to the maximum value of the cosine distance in step S35 according to the preset echo characteristic peak position.

[0049] S4: Obtain high-frequency sampling points corresponding to the preset reference echo in step S3, and map the obtained high-frequency sampling points corresponding to the reference echo to a preset area corresponding to the echo characteristic peak, obtain a data sequence corresponding to the preset area, perform a preset interpolation algorithm on the obtained data sequence, and obtain echo characteristic points corresponding to the data sequence;

[0050] Step S4 includes:

[0051] S41: Obtain high-frequency sampling points corresponding to the preset reference echo in step S3;

[0052] S42: Mapping the high-frequency sampling points corresponding to the obtained reference echo to a preset area corresponding to the echo characteristic peak, and obtaining a data sequence corresponding to the preset area;

[0053] S43: Obtaining the preset zero point position of the data sequence corresponding to the preset area in step S42;

[0054] S44: performing a preset interpolation algorithm calculation on the pre-sequence position of the preset zero point and the post-sequence position of the preset zero point, and obtaining echo feature points corresponding to the data sequence.

[0055] S5: Measure the echo flight time based on the acquired echo feature points according to a preset measurement algorithm.

[0056] The beneficial effects of the embodiments of the present invention include:

[0057] 1. Empirical wavelet transform overcomes the modal aliasing problem in signal decomposition and has low computational complexity. The empirical wavelet transform decomposes the echo signal into multiple components, which are then correlated with the original signal. Components with low correlation coefficients are removed, and the remaining useful components are superimposed to obtain a reconstructed echo signal, achieving both noise reduction and reconstruction of the echo signal.

[0058] 2. The characteristic peak of the echo is accurately located by calculating the cosine distance between the reference echo and the reconstructed echo. The echo's characteristic points are then accurately located using the preset sampling information of the reference echo and the reconstructed echo. Because the sampling frequency of the reference echo is much higher than that of the reconstructed echo, the accuracy of locating the echo's characteristic points is higher. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments. It should be understood that the following drawings only illustrate certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without paying any creative work.

[0060] Figure 1 A method for measuring the time of flight of a low signal-to-noise ratio ultrasonic echo signal provided in an embodiment of the present invention Figure 1 ;

[0061] Figure 2 A method for measuring the time of flight of a low signal-to-noise ratio ultrasonic echo signal provided in an embodiment of the present invention Figure 2 ;

[0062] Figure 3 A schematic diagram of Fourier spectrum segmentation provided in an embodiment of the present invention;

[0063] Figure 4 Normalized echo signals under different flow rates provided in an embodiment of the present invention;

[0064] Figure 5 Schematic diagram of echo characteristic peak judgment provided in an embodiment of the present invention;

[0065] Figure 6A schematic diagram of echo feature point positioning provided in an embodiment of the present invention;

[0066] Figure 7 This is a schematic diagram of time-of-flight measurement provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0067] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings herein can be arranged and designed in various different configurations.

[0068] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention as claimed, but rather merely represents selected embodiments of the present invention. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without creative effort are intended to fall within the scope of protection of the present invention.

[0069] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, it does not need to be further defined or explained in subsequent drawings.

[0070] In the description of the present invention, it should be noted that if the terms "upper", "lower", "inside", "outside", etc. appear, the orientation or position relationship indicated is based on the orientation or position relationship shown in the accompanying drawings, or is the orientation or position relationship in which the product of the invention is usually placed when in use. It is only for the convenience of describing the present invention and simplifying the description, and does not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it should not be understood as a limitation on the present invention.

[0071] In addition, the terms "first", "second", etc., if used, are merely used to distinguish and describe, and should not be understood as indicating or implying relative importance.

[0072] It should be noted that, in the absence of conflict, the features in the embodiments of the present invention may be combined with each other.

[0073] In view of this, please refer to Figure 1-7 , the embodiments provided by this method are:

[0074] A method for measuring the time of flight of a low signal-to-noise ratio ultrasonic echo signal comprises the following steps:

[0075] S1: collect echo signals;

[0076] S2: De-noise and reconstruct the collected echo signal through empirical wavelet transform, and obtain the reconstructed echo signal;

[0077] Step S2 includes:

[0078] S21: adaptively decomposing the collected echo signal through empirical wavelet transform to obtain decomposition components;

[0079] S22: Obtaining useful components from the decomposed components according to a preset extraction algorithm;

[0080] S221: Obtain the number of maximum values ​​in the decomposed components in step S21, and the number of preset values ​​to define boundary points;

[0081] S222: Based on the empirical wavelet function ω n and scaling function φ n (ω) and the detail coefficient generated by the inner product of the signal and approximation coefficients obtaining a reconstructed echo signal;

[0082] S223: performing correlation calculation on the obtained decomposition components and the echo signal collected in step S1 in sequence according to a preset order;

[0083] S224: When the correlation is greater than a preset threshold, the decomposed component corresponding to the correlation is a preset useful component.

[0084] S23: Superimposing the obtained useful components to obtain a reconstructed echo signal.

[0085] Reference Figures 1 to 3 First, the collected echo signal f(t) is Fourier transformed and normalized to obtain a Fourier spectrum in the range of [0,π]. The local maximum points are found in the spectrum and arranged in descending order. Determine the number of maximum values ​​M found and the number of preset values ​​N for signal decomposition. If M≥N, it means that the number of selected maximum values ​​is large enough to provide a basis for spectrum segmentation. At this time, retain the first N-1 maximum values; when M<N, it means that the preset value of the number of mode components in the signal is too large. At this time, retain the maximum value and correct N. Divide the boundary point ω according to the angular frequency corresponding to the N maximum values ​​in the frequency domain n , take the middle value of two adjacent angular frequencies as the frequency domain boundary point ω n .

[0086] At this time, the original signal is decomposed into N continuous intervals, and n =[ω n-1 ,ω n ], n=1,2,3..., N represents the division interval. n Indicates the boundary between each segment, ω0=0, ω n =π.n As the center, the width is defined as 2τ n The transition section, τ n =γω n (0<γ<1), where The signal segmentation results are as follows Figure 1 shown.

[0087] Construct the empirical wavelet function ψ based on the ideas of Littlewood-Paley and Meyer wavelets n (ω) and the scaling function φ n (ω), is expressed by the following formula:

[0088]

[0089]

[0090] The empirical wavelet function ψ n The inner product of (ω) and the signal f(t) can produce the detail coefficient The scaling function φ n (ω) and the inner product of the signal can be used to obtain the approximation coefficient The formula is as follows:

[0091]

[0092]

[0093] Where, is ψ n (ω),φ n The complex conjugate of (ω), F -1 [*] is the inverse Fourier transform. The final reconstructed echo signal f(t) after the empirical wavelet transform is:

[0094]

[0095] Among them, X k (t) is the AM-FM component:

[0096]

[0097] The correlation between the N AM-FM components and the original signal is calculated in sequence, and the correlation coefficient is used to represent the correlation between the components and the original signal. The expression is:

[0098]

[0099] Where, X k represents the kth AM-FM component, Y represents the original echo signal f(t), is the correlation coefficient, cov(X k,Y) is the product of covariances, is the product of the standard deviation. Set a threshold ε, when When the component is considered as a useful component, all useful components X k (t) can be superimposed to obtain the reconstructed echo signal S(t), where k is the valid component number.

[0100] S(t)=∑X k (t)

[0101] S3: Obtain a preset reference echo, perform normalization processing on the preset reference echo signal, obtain the preset reference echo peak value and the reconstructed echo peak value, and calculate the echo characteristic peak of the echo signal by using a preset characteristic peak positioning algorithm;

[0102] Step S3 includes:

[0103] S31: Acquire a preset reference echo;

[0104] S32: performing normalization processing on the acquired preset reference echo signal, and obtaining a preset reference echo peak value and a reconstructed echo peak value;

[0105] S33: obtaining the first echo peak value, the second echo peak value, and the third echo peak value of three consecutive cycles preset in the reference echo, and obtaining the echo peak value of any three consecutive cycles of the reconstructed echo;

[0106] S34: performing cosine distance calculation between the echo peak value of three consecutive cycles preset in the reference echo and the echo peak value of any three consecutive cycles in the obtained reconstructed echo;

[0107] S35: Obtaining the cosine distances between the echo peaks of the remaining three consecutive cycles in the reconstructed echo and the echo peaks of the preset three consecutive cycles in the reference echo; sorting all the calculated cosine distances according to their numerical values, and finding the reconstructed echo of three consecutive cycles corresponding to the maximum cosine distance;

[0108] S36: Obtain the preset echo characteristic peak position in the preset reference echo in step S33, and obtain the echo characteristic peak position of the reconstructed echo corresponding to the maximum value of the cosine distance in step S35 according to the preset echo characteristic peak position.

[0109] Reference Figure 4 Typically, an echo signal is divided into two parts: a rising part and a falling part. The waveform of the rising part of the normalized echo signal is highly similar under different flow rates. The cosine distance is used to calculate the similarity of the waveform characteristic peaks and locate the echo feature points in the rising part of the echo signal.

[0110] Normalize the pre-stored reference echo signal, and the expression is as follows:

[0111]

[0112] Where y n is the normalized value, V n is the voltage of the nth sampling point of the reference echo, V ref is the DC bias voltage of the echo signal, V max is the maximum peak voltage of the reference echo.

[0113] Reference Figure 5 , select the 3rd, 4th, and 5th peaks in the dotted box of the reference echo as reference object A, reconstruct any three consecutive cycle peaks of the echo as evaluation object B, and set the 4th peak of reference object A as the characteristic peak. Keeping reference object A unchanged, select different objects B to calculate the cosine distance with reference object A. The formula is as follows:

[0114]

[0115] Where A=(a1,a2,...,a n ) and B=(b1,b2,...,b n ) is the similarity evaluation object, a n and b n is the normalized value of the peak voltage of each echo signal of objects A and B, and n is the nth peak of the echo.

[0116] Based on the calculation results of the cosine distance, a group of three consecutive periodic peaks with the largest cosine distance is selected as the similar echo. The characteristic peak of the reconstructed echo under actual working conditions can be determined based on the position of the characteristic peak in the reference object A.

[0117] S4: Obtain high-frequency sampling points corresponding to the preset reference echo in step S3, and map the obtained high-frequency sampling points corresponding to the reference echo to a preset area corresponding to the echo characteristic peak, obtain a data sequence corresponding to the preset area, perform a preset interpolation algorithm on the obtained data sequence, and obtain echo characteristic points corresponding to the data sequence;

[0118] Step S4 includes:

[0119] S41: Obtain high-frequency sampling points corresponding to the preset reference echo in step S3;

[0120] S42: Mapping the high-frequency sampling points corresponding to the obtained reference echo to a preset area corresponding to the echo characteristic peak, and obtaining a data sequence corresponding to the preset area;

[0121] S43: Obtaining the preset zero point position of the data sequence corresponding to the preset area in step S42;

[0122] S44: performing a preset interpolation algorithm calculation on the pre-sequence position of the preset zero point and the post-sequence position of the preset zero point, and obtaining echo feature points corresponding to the data sequence.

[0123] refer to Figure 6 , the high-frequency sampling point sequence of the reference echo is mapped to the corresponding position of the reconstructed echo characteristic peak sampling point sequence to form a new data sequence. By searching the new sequence, the echo characteristic points are obtained by interpolation calculation based on the data before and after the zero point.

[0124] Assume that the sampling point sequence of the rising part of the reconstructed echo characteristic peak is L=[l1,l2,...,l m-1 ,l m ,...,l n ],l n To reconstruct the normalized value of the sampling voltage corresponding to the echo; the sampling point sequence H = [h1,h2,...,h q ,...,h p ,...,h i ], h i is the normalized value of the sampling voltage corresponding to the reference echo.

[0125] Find the first point greater than zero in the sequence L and set it as P1, P1 corresponds to l in the sequence L m ;Remember the point before P1 is P2, P2 corresponds to l in sequence L m-1 According to the values ​​of the two points P1 and P2 found, search for the first point A and point D in sequence H that are greater than the values ​​of P1 and P2. The two points correspond to h in sequence H. p ,h q . The h found from the sequence H p ,h q The high-frequency sampling points between two points are inserted into the sequence L according to their size to form a new data sequence with non-uniform spacing: Z = [l1,...,l m-1 ,h q ,h q+1 ,...,h p-1 ,l m ,h p ,l m+1 ,...,l n ], search sequence Z, find the data before and after the zero point and perform interpolation calculation, and the zero point obtained is the desired echo feature point.

[0126] S5: Measure the echo flight time based on the acquired echo feature points according to a preset measurement algorithm.

[0127] Reference Figure 7 , the flight time is measured based on the echo feature points found. The data l in the new data sequence Z m-1,h D ,h C ,h p-1 ,l m ,h p Corresponding respectively Figure 5 In the equation, P2, D, C, B, P1, and A are three points, where P is the desired echo feature point. The relative position of P1 between points A and B is determined by interpolation, and the time T1 between point B and point P1 is calculated based on the reference echo sampling period:

[0128]

[0129] Where, t H is the reference echo sampling period. Similarly, if the sequence H is mapped to the point D between P1 and P2, the value is less than zero, such as Figure 5 , then interpolation calculation is performed based on points C and D to obtain the time T2 of the echo feature point P and point C:

[0130]

[0131] If the point D value is greater than zero, the situation is as follows Figure 5 As shown, the time T3 of the echo feature points P and D is obtained by interpolation calculation based on the two points P2 and D:

[0132]

[0133] The final echo flight time t can be expressed as:

[0134]

[0135] Where, t d t is the time from transducer excitation to echo signal sampling. L is the sampling period of FPGA echo signal, N is the Nth point of P1 in sampling, n BC is the number of mapping points B and C, n BD is the number of mapping points between B and D.

[0136] In order to verify the effectiveness and accuracy of the flight time measurement method of the low signal-to-noise ratio ultrasonic echo signal provided in this embodiment, a flow experiment was conducted to compare the method in this embodiment with the conventional zero-crossing fitting method.

[0137] The experiment was carried out according to the relevant requirements of JJG1030-2007 "Ultrasonic Flowmeter Verification Procedure". The flow test was carried out at room temperature of 25℃ and atmospheric pressure of 101kPa. Five flow points of 1m3 / h, 20m3 / h, 40m3 / h, 115m3 / h and 160m3 / h were selected for calibration and the experiment was repeated 3 times at each flow point. The experimental results are shown in Table 1 and Table 2:

[0138] Table 1 Flow rate calibration results of the method in this embodiment

[0139]

[0140] Table 2 Flow calibration results of conventional zero-crossing fitting method

[0141]

[0142]

[0143] Experimental results show that the flight time measurement method of the low signal-to-noise ratio ultrasonic echo signal in this embodiment has a measurement error of only 1.115% at the minimum flow point, and a repeatability of less than 0.2%. The errors at other flow points are all less than ±0.6%, and the repeatability is less than 0.035%, which is better than the requirements of the Level 1 table in the "Ultrasonic Flowmeter Verification Procedure". Compared with the conventional zero-crossing fitting method, it reduces the impact of fitting on the measurement results, improves the accuracy of echo feature point positioning and the accuracy of flight time calculation, and has certain improvements in flow calibration error and repeatability, especially in the measurement of small flow rates.

[0144] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the present invention should be included in the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.

Claims

1. A method for measuring the time of flight of a low signal-to-noise ratio ultrasonic echo signal, characterized in that: Including steps: S1: collect echo signals; S2: De-noise and reconstruct the collected echo signal through empirical wavelet transform, and obtain the reconstructed echo signal; S3: Obtain a preset reference echo, perform normalization processing on the preset reference echo signal, obtain the preset reference echo peak value and the reconstructed echo peak value, and calculate the echo characteristic peak of the echo signal by using a preset characteristic peak positioning algorithm; Step S3 includes: S31: Acquire a preset reference echo; S32: performing normalization processing on the acquired preset reference echo signal, and obtaining a preset reference echo peak value and a reconstructed echo peak value; S33: obtaining the first echo peak value, the second echo peak value, and the third echo peak value of three consecutive cycles preset in the reference echo, and obtaining the echo peak value of any three consecutive cycles of the reconstructed echo; S34: performing cosine distance calculation between the echo peak value of three consecutive cycles preset in the reference echo and the echo peak value of any three consecutive cycles in the obtained reconstructed echo; S35: Obtaining the cosine distances between the echo peaks of the remaining three consecutive cycles in the reconstructed echo and the echo peaks of the preset three consecutive cycles in the reference echo; sorting all the calculated cosine distances according to their numerical values, and finding the reconstructed echo of three consecutive cycles corresponding to the maximum cosine distance; S36: Obtaining a preset echo characteristic peak position in the preset reference echo in step S33, and obtaining the echo characteristic peak position of the reconstructed echo corresponding to the maximum value of the cosine distance in step S35 according to the preset echo characteristic peak position; S4: Obtain high-frequency sampling points corresponding to the preset reference echo in step S3, and map the obtained high-frequency sampling points corresponding to the reference echo to a preset area corresponding to the echo characteristic peak, obtain a data sequence corresponding to the preset area, perform a preset interpolation algorithm on the obtained data sequence, and obtain echo characteristic points corresponding to the data sequence; Step S4 includes: S41: Obtain high-frequency sampling points corresponding to the preset reference echo in step S3; S42: Mapping the high-frequency sampling points corresponding to the obtained reference echo to a preset area corresponding to the echo characteristic peak, and obtaining a data sequence corresponding to the preset area; S43: Obtaining the preset zero point position of the data sequence corresponding to the preset area in step S42; S44: performing a preset interpolation algorithm calculation on the pre-sequence position of the preset zero point and the post-sequence position of the preset zero point, and obtaining echo feature points corresponding to the data sequence; S5: Measure the echo flight time based on the acquired echo feature points according to a preset measurement algorithm.

2. The method for measuring the time of flight of a low signal-to-noise ratio ultrasonic echo signal according to claim 1, wherein: Step S2 includes: S21: adaptively decomposing the collected echo signal through empirical wavelet transform to obtain decomposition components; S22: Obtaining useful components from the decomposed components according to a preset extraction algorithm; S23: Superimposing the obtained useful components to obtain a reconstructed echo signal.

3. The method for measuring the time of flight of a low signal-to-noise ratio ultrasonic echo signal according to claim 2, wherein: Step S22: Obtaining useful components from the decomposed components according to a preset extraction algorithm includes the following steps: S221: Obtain the number of maximum values ​​in the decomposed components in step S21, and the number of preset values ​​to define boundary points; S222: Based on the empirical wavelet function ψ n (ω) and the scaling function φ n (ω) and the detail coefficient generated by the inner product of the signal and approximation coefficients obtaining a reconstructed echo signal; S223: performing correlation calculation on the obtained decomposition components and the echo signal collected in step S1 in sequence according to a preset order; S224: When the correlation is greater than a preset threshold, the decomposed component corresponding to the correlation is a preset useful component.

4. The method for measuring the time of flight of a low signal-to-noise ratio ultrasonic echo signal according to claim 3, wherein: The empirical wavelet function ψ in step S222 n (ω) is: The original signal is decomposed into N continuous intervals, using Λ n =[ω n-1 ,ω n ], n=1,2,3..., N represents the division interval, ω n Indicates the boundary between each segment, ω0=0, ω n =π.

5. The method for measuring the time of flight of a low signal-to-noise ratio ultrasonic echo signal according to claim 4, wherein: The scaling function φ in step S222 n (ω) is: The original signal is decomposed into N continuous intervals, using Λ n =[ω n-1 ,ω n ], n=1,2,3..., N represents the division interval, ω n Indicates the boundary between each segment, ω0=0, ω n =π.

6. The method for measuring the time of flight of a low signal-to-noise ratio ultrasonic echo signal according to claim 5, characterized in that: The detail coefficients generated by the inner product of the signal in step S222 The original signal is decomposed into N continuous intervals, using Λ n =[ω n-1 ,ω n ], n=1,2,3..., N represents the division interval, ω n Indicates the boundary between each segment, ω0=0, ω n =π is ψ n The complex conjugate of (ω), F -1 [*] is the inverse Fourier transform.

7. The method for measuring the time of flight of a low signal-to-noise ratio ultrasonic echo signal according to claim 6, wherein: Approximation coefficient in step S222 The original signal is decomposed into N continuous intervals, using Λ n =[ω n-1 ,ω n ], n=1,2,3..., N represents the division interval, ω n Indicates the boundary between each segment, ω0=0, ω n =π is φ n The complex conjugate of (ω), F -1 [*] is the inverse Fourier transform.

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