A velocity measurement method and system applied to a laser Doppler velocimeter

Abstract

The present invention discloses a speed measurement method and system applied to a laser Doppler velocimeter. The above method includes: collecting the motion signal of the object to be measured by the laser Doppler velocimeter, and performing parameter setting according to the motion signal; filtering and segmenting the motion signal according to the set parameters, converting the signal of each segment to the frequency domain through fast Fourier transform and performing spectrum analysis to obtain the frequency search range of the signals of each segment; performing wavelet transform on the signals within the segment through the set parameters and frequency search range, and obtaining the instantaneous frequency estimation curve segment of the signal of each segment by extracting the wavelet ridge line; splicing the instantaneous frequency estimation curve segments of each segment, and reconstructing the time-frequency signal to obtain the velocity-time curve of the object to be measured. The present invention uses wavelet transform to process the signal, and combines fast Fourier transform to effectively improve the time resolution and data processing speed of the system.

Description

Technical Field

[0001] The present invention relates to the field of speed and acceleration measurement, and particularly to a speed measurement method and system applied to a laser Doppler velocimeter. Background Art

[0002] Laser Doppler measurement technology uses laser as the information carrier. A laser beam is irradiated onto a moving target object, and by detecting the frequency shift of its scattered light relative to the incident light, i.e., the Doppler frequency shift, the motion speed information of the target object is obtained using data processing methods. Laser Doppler velocimetry has the advantages of non-contact measurement, no interference with the target motion, high spatial resolution, high measurement accuracy, and large measurement range, and has been widely applied in many industries such as military, aviation, aerospace, and machinery.

[0003] The Fourier transform algorithm is a commonly used frequency-domain detection method at present. However, the Fourier transform obtains the frequency information on the entire time axis and cannot obtain the frequency information in a certain time period, and the corresponding relationship between the transient time and frequency cannot be obtained. Therefore, the short-time Fourier transform is usually used to improve this drawback. However, because the window size of the short-time Fourier transform is fixed and cannot change with the frequency, it lacks the time localization property and is only applicable to stationary signals with small frequency fluctuations, and there are still limitations in the detection of non-stationary signals with large frequency fluctuations. Summary of the Invention

[0004] Aiming at the technical problem that the time-frequency detection accuracy of the laser Doppler velocimeter for non-stationary signals is relatively low using a single window length, the present invention proposes a speed measurement method and system applied to a laser Doppler velocimeter.

[0005] In a first aspect, an embodiment of the present application provides a speed measurement method applied to a laser Doppler velocimeter, including:

[0006] Data acquisition step: Collect the motion signal of the object to be measured through a laser Doppler velocimeter, and perform parameter settings according to the motion signal;

[0007] Data segmentation step: Filter and segment the motion signal according to the set parameters, and use the starting paragraph as the current paragraph;

[0008] Fast Fourier transform step: Transform the signal in the current paragraph to the frequency domain through the fast Fourier transform and perform spectrum analysis to obtain the frequency search range of the signal in the current paragraph;

[0009] Wavelet transform step: Perform wavelet transform on the signal in the current paragraph through the set parameters and the frequency search range, and obtain the instantaneous frequency estimation curve segment of the signal in the current paragraph by extracting the wavelet ridge line;

[0010] Steps for obtaining the velocity-time curve: Determine whether the current paragraph is the last paragraph; if not, increment the paragraph number of the current paragraph by one and return the fast Fourier transform step; if so, splice the instantaneous frequency estimation curve segments of the signals in each paragraph, and reconstruct the time-frequency signal to obtain the velocity-time curve of the object under test.

[0011] The above velocity measurement method, wherein the set parameters include: the velocity detection range of the object under test, the data window length, the wavelet basis function, and the step size of the wavelet transform scale factor.

[0012] The above velocity measurement method, wherein the data segmentation step further includes: designing a band-pass filter according to the velocity detection range of the object under test, and filtering the motion signal through the band-pass filter.

[0013] The above velocity measurement method, wherein the data segmentation step includes:

[0014] Steps for obtaining the number of intercepted segments: Calculate the number of intercepted segments of the motion signal according to the total number of data points in the motion signal and the data window length;

[0015] Data segmentation processing step: Segment the filtered motion signal according to the number of intercepted segments.

[0016] The above velocity measurement method, wherein the fast Fourier transform step includes:

[0017] Steps for obtaining the estimated value of the instantaneous frequency: Obtain the estimated value of the instantaneous frequency of the signal in the current paragraph by solving the frequency corresponding to the modulus maximum value of the spectrum in the frequency domain of the signal in the current paragraph;

[0018] Steps for obtaining the frequency search range: Determine the frequency search range of the signal in the current paragraph according to the estimated value of the instantaneous frequency of the signal in the current paragraph.

[0019] The above velocity measurement method, wherein the wavelet transform step includes:

[0020] Steps for obtaining the scale factor search range: Obtain the scale factor search range of the wavelet transform of the signal in the current paragraph according to the step size of the wavelet transform scale factor and the frequency search range of the signal in the current paragraph;

[0021] Steps for obtaining wavelet coefficients: Perform wavelet transform on the signal in the current paragraph through the wavelet basis function, the step size of the wavelet transform scale factor, and the scale factor search range of the wavelet transform of the signal in the current paragraph to obtain wavelet coefficients;

[0022] Steps for extracting wavelet ridge line: The wavelet ridge line is extracted by using the modulus maximum method according to the wavelet coefficients, and the instantaneous frequency estimation curve segment of the signal in the current paragraph is obtained.

[0023] The above velocity measurement method, wherein the step of obtaining the velocity-time curve includes:

[0024] Data splicing step: The instantaneous frequency estimation curve segments of each paragraph are spliced to obtain the signal instantaneous frequency spectrum estimation curve in the full time domain;

[0025] Time-frequency signal reconstruction step: The velocity-time curve of the object to be measured is obtained by time-frequency signal reconstruction according to the signal instantaneous frequency spectrum estimation curve in the full time domain.

[0026] In a second aspect, an embodiment of the present application provides a velocity measurement system applied to a laser Doppler velocimeter, including:

[0027] Data acquisition unit: Collect the motion signal of the object to be measured through a laser Doppler velocimeter, and perform parameter setting according to the motion signal;

[0028] Data segmentation unit: Filter and segment the motion signal according to the set parameters, and use the starting paragraph as the current paragraph;

[0029] Fast Fourier transform unit: Convert the signal in the current paragraph to the frequency domain through fast Fourier transform and perform spectrum analysis to obtain the frequency search range of the signal in the current paragraph;

[0030] Wavelet transform unit: Perform wavelet transform on the signal in the current paragraph through the set parameters and the frequency search range, and obtain the instantaneous frequency estimation curve segment of the signal in the current paragraph by extracting the wavelet ridge line;

[0031] Velocity-time curve acquisition unit: Determine whether the current paragraph is the last paragraph; if not, increment the paragraph number of the current paragraph by one, and return to the fast Fourier transform unit; if so, splice the instantaneous frequency estimation curve segments of the signal in each paragraph, and obtain the velocity-time curve of the object to be measured through time-frequency signal reconstruction.

[0032] The above velocity measurement system, wherein the fast Fourier transform unit includes:

[0033] Instantaneous frequency estimation value acquisition module: Obtain the instantaneous frequency estimation value of the signal in the current paragraph by solving the frequency corresponding to the modulus maximum of the spectrum in the frequency domain of the signal in the current paragraph;

[0034] Frequency search range acquisition module: Determine the frequency search range of the signal in the current paragraph according to the instantaneous frequency estimation value of the signal in the current paragraph.

[0035] The above speed measurement system, wherein the wavelet transform unit includes:

[0036] A scale factor search range obtaining module: obtaining the scale factor search range of the wavelet transform of the signal in the current paragraph according to the step size of the wavelet transform scale factor and the frequency search range of the signal in the current paragraph;

[0037] A wavelet coefficient obtaining module: performing wavelet transform on the signal in the current paragraph through the wavelet basis function, the step size of the wavelet transform scale factor, and the scale factor search range of the wavelet transform of the signal in the current paragraph to obtain wavelet coefficients;

[0038] A wavelet ridge extraction module: extracting the wavelet ridge according to the wavelet coefficients by using the modulus maximum method to obtain the instantaneous frequency estimation curve segment of the signal in the current paragraph.

[0039] Compared with the prior art, the advantages and positive effects of the present invention are as follows:

[0040] 1. The present invention applies wavelet transform to a laser Doppler velocimeter, breaking through the limitations of time-frequency analysis caused by a fixed window when using conventional methods. It can adaptively adjust the window size according to the high or low frequency of the signal for multi-resolution analysis. For non-stationary signals with large fluctuations, it can focus on any details of the signal, better track the detailed information at the signal mutation, and has higher time resolution.

[0041] 2. In the present invention, wavelet transform is combined with fast Fourier transform. The fast Fourier transform is used to preprocess the signal to determine the frequency change range of the signal in each time segment, narrowing the search range of the scale factor in wavelet transform. While improving the time resolution of detecting non-stationary signals, it reduces the computational amount of the algorithm, speeds up the data processing speed, and improves the real-time performance of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 It is a step schematic diagram of a speed measurement method applied to a laser Doppler velocimeter provided by the present invention;

[0043] Figure 2 Based on the present invention Figure 1 It is a flow schematic diagram of step S2;

[0044] Figure 3 Based on the present invention Figure 1 It is a flow schematic diagram of step S3;

[0045] Figure 4 Based on the present invention Figure 1 It is a flow schematic diagram of step S4;

[0046] Figure 5 The flow diagram based on step S5 provided by the present invention; Figure 1 in the figure;

[0047] Figure 6 The flow diagram of an embodiment of a speed measurement method applied to a laser Doppler velocimeter provided by the present invention;

[0048] Figure 7 The framework diagram of a speed measurement system applied to a laser Doppler velocimeter provided by the present invention;

[0049] Among them, the reference signs are:

[0050] 11. Data acquisition unit; 12. Data segmentation unit; 13. Fast Fourier transform unit; 131. Instantaneous frequency estimation value acquisition module; 132. Frequency search range acquisition module; 14. Wavelet transform unit; 141. Scale factor search range acquisition module; 142. Wavelet coefficient acquisition module; 143. Wavelet ridge extraction module; 15. Speed-time curve acquisition unit. Detailed implementation manners

[0051] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be described and explained below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application. Based on the embodiments provided by the present application, all other embodiments obtained by those of ordinary skill in the art without making creative efforts belong to the scope of protection of the present application.

[0052] Obviously, the accompanying drawings in the following description are only some examples or embodiments of the present application. For those of ordinary skill in the art, the present application can also be applied to other similar scenarios based on these drawings without making creative efforts. In addition, it can also be understood that although the efforts made in this development process may be complex and lengthy, for those of ordinary skill in the art related to the content disclosed in the present application, some design, manufacturing or production changes based on the technical content disclosed in the present application are only conventional technical means and should not be understood that the content disclosed in the present application is insufficient.

[0053] Referring to "embodiment" in the present application means that the specific features, structures or characteristics described in combination with the embodiment may be included in at least one embodiment of the present application. The appearance of this phrase in various positions in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those of ordinary skill in the art explicitly and implicitly understand that the embodiments described in the present application can be combined with other embodiments without conflict.

[0054] Unless otherwise defined, the technical terms or scientific terms involved in this application shall have the ordinary meanings understood by those with ordinary skills in the technical field to which this application belongs. The similar words such as "a", "an", "one kind", "the" and the like involved in this application do not indicate a limitation in quantity and may represent a singular or plural number. The terms "comprising", "including", "having" and any variations thereof involved in this application are intended to cover non-exclusive inclusion; for example, a process, method, system, product or device comprising a series of steps or modules (units) is not limited to the listed steps or units, but may further include steps or units not listed, or may further include other steps or units inherent to these processes, methods, products or devices. The similar words such as "connected", "coupled" and "joined" involved in this application are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The "plurality" involved in this application means two or more. "And / or" describes the association relationship of associated objects and indicates that three relationships may exist. For example, "A and / or B" may represent: A exists alone, A and B exist simultaneously, and B exists alone. The character " / " generally represents an "or" relationship between the associated objects before and after. The terms "first", "second", "third" and the like involved in this application are only used to distinguish similar objects and do not represent a specific order for the objects.

[0055] The present invention will be described in detail below in conjunction with the various embodiments shown in the drawings. However, it should be noted that these embodiments are not limitations on the present invention, and equivalent transformations or substitutions in terms of functions, methods, or structures made by those of ordinary skill in the art according to these embodiments all fall within the protection scope of the present invention.

[0056] Before elaborating on each embodiment of the present invention in detail, an overview of the core inventive concept of the present invention is given and will be elaborated in detail through the following several embodiments.

[0057] The present invention combines fast Fourier transform and wavelet transform to adaptively segment the signals collected by a laser Doppler velocimeter, uses fast Fourier transform for preprocessing to initially obtain the signal frequency change range within the segment, thereby determining the search range and step size of the scale factor of wavelet transform, then performs wavelet transform on the signals, extracts the ridge line of the wavelet coefficients to obtain the instantaneous frequency of the moving target object, and through time-frequency signal reconstruction, obtains the time-velocity curve of the object to be measured.

[0058] Embodiment 1:

[0059] Figure 1 It is a schematic diagram of the steps of a speed measurement method applied to a laser Doppler velocimeter provided by the present invention. As Figure 1As shown in the figure, this embodiment discloses a specific implementation of a speed measurement method (hereinafter referred to as "the method") applied to a laser Doppler velocimeter.

[0060] Wavelet Transform (WT) is an adaptive time-frequency analysis method. Its main feature is that it has good localization characteristics both in time and frequency. Through stretching and translation operations, the signal is gradually refined at multiple scales, which can focus on any detail of the signal, enabling multi-resolution analysis and being more effective for the time-frequency analysis and processing of non-stationary signals. However, due to the large computational complexity of using wavelet transform, it is not conducive to the real-time performance of system signal processing and analysis. Therefore, the present invention uses a method that combines wavelet transform and fast Fourier transform to improve the time resolution for detecting the mutation moment of non-stationary signals while reducing the computational amount of the algorithm and enhancing the system real-time performance.

[0061] Specifically, the method disclosed in this embodiment mainly includes the following steps:

[0062] Step S1: Collect the motion signal of the object to be measured through a laser Doppler velocimeter and perform parameter settings according to the motion signal;

[0063] Specifically, the set parameters include: the speed detection range of the object to be measured, the data window length, the wavelet basis function, and the step size of the wavelet transform scale factor.

[0064] Step S2: Filter and segment the motion signal according to the set parameters, and use the starting paragraph as the current paragraph;

[0065] Among them, as Figure 2 shown, step S2 specifically includes the following content:

[0066] Step S21: Design a band-pass filter according to the speed detection range of the object to be measured, and filter the motion signal through the band-pass filter;

[0067] Step S22: Calculate the number of intercepted segments of the motion signal according to the total number of data points in the motion signal and the data window length;

[0068] Step S23: Segment the filtered motion signal according to the number of intercepted segments.

[0069] Step S3: Convert the signal in the current paragraph to the frequency domain through fast Fourier transform and perform spectrum analysis to obtain the frequency search range of the signal in the current paragraph;

[0070] Among them, as Figure 3 shown, step S3 specifically includes the following content:

[0071] Step S31: Obtain the instantaneous frequency estimate value of the signal in the current paragraph by solving for the frequency corresponding to the modulus maximum of the spectrum in the frequency domain of the signal in the current paragraph;

[0072] Step S32: Determine the frequency search range of the signal in the current paragraph according to the instantaneous frequency estimate value of the signal in the current paragraph.

[0073] Step S4: Perform wavelet transform on the signal in the current paragraph using the set parameters and the frequency search range, and obtain the instantaneous frequency estimate curve segment of the signal in the current paragraph by extracting the wavelet ridge line;

[0074] Among them, as Figure 4 shown, Step S4 specifically includes the following content:

[0075] Step S41: Obtain the scale factor search range of the wavelet transform of the signal in the current paragraph according to the step size of the wavelet transform scale factor and the frequency search range of the signal in the current paragraph;

[0076] Step S42: Perform wavelet transform on the signal in the current paragraph using the wavelet basis function, the step size of the wavelet transform scale factor, and the scale factor search range of the wavelet transform of the signal in the current paragraph to obtain wavelet coefficients;

[0077] Step S43: Extract the wavelet ridge line using the modulus maximum method according to the wavelet coefficients to obtain the instantaneous frequency estimate curve segment of the signal in the current paragraph.

[0078] Step S5: Determine whether the current paragraph is the last paragraph; if not, increment the paragraph number of the current paragraph by one and return to Step S3; if so, splice the instantaneous frequency estimate curve segments of the signals in each paragraph, and obtain the velocity-time curve of the object to be measured through time-frequency signal reconstruction.

[0079] Among them, as Figure 5 shown, Step S5 specifically includes the following content:

[0080] Step S51: Splice the instantaneous frequency estimate curve segments of each paragraph to obtain the instantaneous frequency spectrum estimate curve of the signal in the full time domain;

[0081] Step S52: Obtain the velocity-time curve of the object to be measured through time-frequency signal reconstruction according to the instantaneous frequency spectrum estimate curve of the signal in the full time domain.

[0082] Next, please refer to Figure 6 . Figure 6 FIG. is a schematic flowchart of an embodiment of a speed measurement method applied to a laser Doppler velocimeter provided by the present invention. Combining Figure 6 , the application process of this method is specifically described as follows:

[0083] Step 1: The laser Doppler velocimeter collects data to obtain the motion signal of the object to be measured;

[0084] Step 2: Parameter settings are performed according to the collected motion signal: set the speed detection range of the object to be measured, the data window length, the wavelet basis function, and the step size of the wavelet transform scale factor;

[0085] Step 3: Design a band-pass filter according to the speed detection range in Step 2;

[0086] Step 4: Filter the motion signal collected by the laser Doppler velocimeter through the band-pass filter in Step 3 to remove noise;

[0087] Step 5: Calculate the number of data intercept segments according to the total number of data points collected by the laser Doppler velocimeter and the data window length set in Step 2;

[0088] Step 6: Segment the filtered motion signal obtained in Step 4 according to the above number of data intercept segments;

[0089] Step 7: Initialize the current paragraph parameter value to 1;

[0090] Step 8: Use the fast Fourier transform to convert the signal in the current paragraph to the frequency domain for spectral analysis;

[0091] Step 9: Obtain the instantaneous frequency estimate of the current paragraph signal by solving the frequency corresponding to the modulus maximum value of the spectrum in the frequency domain;

[0092] Step 10: Determine the frequency search range of the current paragraph signal according to the obtained instantaneous frequency estimate value of the current paragraph signal;

[0093] Step 11: Calculate the scale factor search range of the current paragraph wavelet transform through the step size of the wavelet transform scale factor set in Step 2 and the frequency search range of the current paragraph signal determined in Step 10;

[0094] Step 12: Perform wavelet transform on the signal in the current paragraph through the wavelet basis function set in Step 1, the step size of the wavelet transform scale factor, and the scale factor search range of the continuous wavelet transform of the current paragraph obtained in Step 11;

[0095] Step 13: Extract the wavelet ridge line using the modulus maximum value method, and obtain the instantaneous frequency estimate curve segment of the current paragraph signal through the relationship between the scale factor of the wavelet and the instantaneous frequency;

[0096] Step 14: Determine whether the current paragraph is the last paragraph. If not, increment the current paragraph parameter value by one and jump to Step 8. If so, end the loop and jump to Step 15;

[0097] Step 15: splice the instantaneous frequency estimation curve segments obtained for each paragraph to obtain the signal instantaneous frequency spectrum estimation curve for the entire time domain.

[0098] Step 16: Reconstruct the time-frequency signal and calculate the velocity-time curve of the object under test.

[0099] Next, a specific formula is used to further elaborate on an embodiment of the velocity measurement method proposed by the present invention for a laser Doppler velocimeter.

[0100] Step 1: The laser Doppler velocimeter collects data to obtain the motion signal S(T) of the object under test, where F s is the sampling frequency of the Doppler velocimeter, and N s is the total number of data points collected by the Doppler velocimeter.

[0101] Step 2: Set the velocity detection range of the object under test: V min and V max ; Set the measurement parameters: the wavelet basis function ψ a (t), the step size df of the wavelet transform scale factor a, and the data window length wlen;

[0102] Step 3: Design a band-pass filter according to the velocity detection range in Step 2. The passband cut-off frequency of the band-pass filter is: The stopband cut-off frequency of the band-pass filter is: where λ is the laser wavelength used by the Doppler velocimeter;

[0103] Step 4: Filter the motion signal collected by the laser Doppler velocimeter using the band-pass filter in Step 3 to remove noise;

[0104] Step 5: Calculate the number of segments into which the motion signal is intercepted according to the total number of data points N s collected by the laser Doppler velocimeter and the data window length wlen set in Step 1

[0105] Step 6: Intercept the filtered motion signal obtained in Step 4 into N segments. The signal length of each segment of signal S i (t i ) is wlen, where i = 1, 2,..., N,

[0106] Step 7: Initialize the current paragraph parameter value i = 1;

[0107] Step 8: Use the fast Fourier transform to convert the signal of the current paragraph into the frequency domain S i (ω) = FFT(S i (t i )) and perform spectral analysis;

[0108] Step 9: Obtain the instantaneous frequency estimate of the signal in the current paragraph by solving for the frequency corresponding to the modulus maximum value of the spectrum in the frequency domain

[0109] Step 10: Determine the frequency search range [f min (i), f max (i)] of the signal in the current paragraph based on the obtained instantaneous frequency estimates of each paragraph, where i = 1, 2,..., N.

[0110] Step 11: Calculate the scale factor search range in the continuous wavelet transform of the signal in the current paragraph through the step size of the wavelet transform scale factor set in Step 1 and the frequency search range obtained in Step 10

[0111] Step 12: Use the wavelet basis function ψ a (t), the step size df of the wavelet transform scale factor a, and the scale factor search range a of the wavelet transform of the current paragraph obtained in Step 11 i to perform wavelet transform on the signal in the current paragraph to obtain wavelet coefficients

[0112] Step 13: Use the modulus maximum value method to extract the wavelet ridge line to obtain the instantaneous frequency estimate curve segment of the signal in the current paragraph

[0113] Step 14: Determine whether the current paragraph is the last paragraph, that is, determine whether the current paragraph parameter value is greater than N. If not, the current paragraph parameter value i = i + 1, and jump to Step 8; if so, end the loop and jump to Step 15;

[0114] Step 15: Concatenate the data of the instantaneous frequency estimate curve segment obtained in Step 13 to obtain where

[0115] Step 16: Through time-frequency signal reconstruction, calculate the velocity-time curve

[0116] The present invention processes signals by using the time-frequency characteristics of wavelet transform multi-resolution analysis, improving the time accuracy of object motion speed detection; and, combines wavelet transform with fast Fourier transform to adaptively adjust the frequency search space, effectively accelerating the data processing speed and improving the real-time performance of the system.

[0117] Embodiment 2:

[0118] Combined with a speed measurement method applied to a laser Doppler velocimeter disclosed in Embodiment 1, this embodiment discloses a specific implementation example of a speed measurement system (hereinafter referred to as "the system") applied to a laser Doppler velocimeter.

[0119] Referring to Figure 7 as shown, the system includes:

[0120] Data acquisition unit 11: Collects the motion signal of the object to be measured through a laser Doppler velocimeter and performs parameter settings according to the motion signal;

[0121] Data segmentation unit 12: Filters and segments the motion signal according to the set parameters, and takes the starting paragraph as the current paragraph;

[0122] Fast Fourier transform unit 13: Converts the signal in the current paragraph to the frequency domain through fast Fourier transform and performs spectrum analysis to obtain the frequency search range of the signal in the current paragraph;

[0123] Specifically, the above fast Fourier transform unit 13 includes:

[0124] Instantaneous frequency estimate value obtaining module 131: Obtains the instantaneous frequency estimate value of the signal in the current paragraph by solving the frequency corresponding to the modulus maximum value of the spectrum in the frequency domain of the signal in the current paragraph;

[0125] Frequency search range obtaining module 132: Determines the frequency search range of the signal in the current paragraph according to the instantaneous frequency estimate value of the signal in the current paragraph.

[0126] Wavelet transform unit 14: Performs wavelet transform on the signal in the current paragraph through the set parameters and the frequency search range, and obtains the instantaneous frequency estimate curve segment of the signal in the current paragraph by extracting the wavelet ridge line;

[0127] Specifically, the above wavelet transform unit 14 includes:

[0128] Scale factor search range obtaining module 141: Obtains the scale factor search range of the wavelet transform of the signal in the current paragraph according to the step size of the wavelet transform scale factor and the frequency search range of the signal in the current paragraph;

[0129] Wavelet coefficient acquisition module 142: Perform wavelet transform on the signal in the current paragraph through the wavelet basis function, the step size of the wavelet transform scale factor, and the search range of the scale factor of the wavelet transform of the signal in the current paragraph to obtain wavelet coefficients;

[0130] Wavelet ridge extraction module 143: Extract the wavelet ridge using the modulus maximum method according to the wavelet coefficients to obtain the instantaneous frequency estimation curve segment of the signal in the current paragraph.

[0131] Velocity-time curve acquisition unit 15: Determine whether the current paragraph is the last paragraph; if not, increment the paragraph number of the current paragraph by one and return to the fast Fourier transform unit 13; if so, splice the instantaneous frequency estimation curve segments of the signals in each paragraph, and reconstruct the time-frequency signal to obtain the velocity-time curve of the object under test.

[0132] For the technical solutions of the same parts in a velocity measurement system applied to a laser Doppler velocimeter disclosed in this embodiment and a velocity measurement method applied to a laser Doppler velocimeter disclosed in Embodiment 1, please refer to what is described in Embodiment 1 and will not be repeated here.

[0133] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope recorded in this specification.

[0134] The above embodiments only represent several implementation manners of the present application. The description is relatively specific and detailed, but it should not be construed as a limitation on the scope of the invention patent. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several deformations and improvements can still be made, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application should be subject to the appended claims.

Claims

1. A speed measurement method applied to a laser Doppler velocimeter, characterized in that, Including: Data acquisition step: Collect the motion signal of the object to be measured by a laser Doppler velocimeter, and perform parameter settings according to the motion signal. Among them, the set parameters include: the speed detection range of the object to be measured and the data windowing length; Data segmentation step: Filter and segment the motion signal according to the set parameters, and use the starting paragraph as the current paragraph; Fast Fourier transform step: Transform the signal in the current paragraph to the frequency domain through fast Fourier transform and perform spectrum analysis to obtain the frequency search range of the signal in the current paragraph; Wavelet transform step: Perform wavelet transform on the signal in the current paragraph through the set parameters and the frequency search range, and obtain the instantaneous frequency estimation curve segment of the signal in the current paragraph by extracting the wavelet ridge line; Velocity-time curve obtaining step: Determine whether the current paragraph is the last paragraph; if not, increment the paragraph number of the current paragraph by one and return to the fast Fourier transform step; if so, splice the instantaneous frequency estimation curve segments of the signal in each paragraph, and obtain the velocity-time curve of the object to be measured through time-frequency signal reconstruction; Among them, the data segmentation step specifically includes: Filtering processing step: Design a band-pass filter according to the speed detection range of the object to be measured, and filter the motion signal through the band-pass filter; Intercept segment number obtaining step: Calculate the intercept segment number of the motion signal according to the total number of data points in the motion signal and the data windowing length; Segmentation processing step: Segment the filtered motion signal according to the intercept segment number.

2. The speed measurement method according to claim 1, wherein The set parameters also include: the wavelet basis function and the step size of the wavelet transform scale factor.

3. The speed measurement method according to claim 2, characterized in that The fast Fourier transform step includes: Instantaneous frequency estimation value obtaining step: Obtain the instantaneous frequency estimation value of the signal in the current paragraph by solving the frequency corresponding to the modulus maximum value of the spectrum in the frequency domain of the signal in the current paragraph; Frequency search range obtaining step: Determine the frequency search range of the signal in the current paragraph according to the instantaneous frequency estimation value of the signal in the current paragraph.

4. The speed measurement method according to claim 3, characterized in that, The wavelet transform step includes: Scale factor search range obtaining step: Obtain the scale factor search range of the wavelet transform of the signal in the current paragraph according to the step size of the wavelet transform scale factor and the frequency search range of the signal in the current paragraph; Wavelet coefficient obtaining step: Perform wavelet transform on the signal in the current paragraph through the wavelet basis function, the step size of the wavelet transform scale factor, and the scale factor search range of the wavelet transform of the signal in the current paragraph to obtain wavelet coefficients; Wavelet ridge line extraction step: Extract the wavelet ridge line by using the modulus maximum value method according to the wavelet coefficients to obtain the instantaneous frequency estimation curve segment of the signal in the current paragraph.

5. The speed measurement method according to claim 4, wherein The velocity-time curve obtaining step includes: Data splicing step: Splice the instantaneous frequency estimation curve segments of each paragraph to obtain the instantaneous spectrum estimation curve of the signal in the full time domain; Time-frequency signal reconstruction step: Obtain the velocity-time curve of the object to be measured through time-frequency signal reconstruction according to the instantaneous spectrum estimation curve of the signal in the full time domain.

6. A velocity measurement system applied to a laser Doppler velocimeter, characterized in that, The velocity measurement system applied to a laser Doppler velocimeter executes the velocity measurement method according to any one of claims 2-5. The velocity measurement system applied to a laser Doppler velocimeter includes: A data acquisition unit: acquiring the motion signal of the object to be measured through a laser Doppler velocimeter and performing parameter setting according to the motion signal; A data segmentation unit: filtering and segmenting the motion signal according to the set parameters, and taking the starting paragraph as the current paragraph; A fast Fourier transform unit: converting the signal in the current paragraph to the frequency domain through fast Fourier transform and performing spectrum analysis to obtain the frequency search range of the signal in the current paragraph; A wavelet transform unit: performing wavelet transform on the signal in the current paragraph according to the set parameters and the frequency search range, and obtaining the instantaneous frequency estimation curve segment of the signal in the current paragraph by extracting the wavelet ridge line; A velocity-time curve obtaining unit: determining whether the current paragraph is the last paragraph; if not, incrementing the number of segments of the current paragraph by one and returning to the fast Fourier transform unit; if so, splicing the instantaneous frequency estimation curve segments of the signals in each paragraph and obtaining the velocity-time curve of the object to be measured through time-frequency signal reconstruction Wherein, the data segmentation unit first designs a band-pass filter according to the velocity detection range of the object to be measured, and filters the motion signal through the band-pass filter; then calculates the number of intercepted segments of the motion signal according to the total number of data points in the motion signal and the data window length; finally, segments the filtered motion signal according to the number of intercepted segments.

7. The speed measurement system according to claim 6, wherein The fast Fourier transform unit includes: An instantaneous frequency estimation value obtaining module: obtaining the instantaneous frequency estimation value of the signal in the current paragraph by solving the frequency corresponding to the modulus maximum value of the spectrum in the frequency domain of the signal in the current paragraph; A frequency search range obtaining module: determining the frequency search range of the signal in the current paragraph according to the instantaneous frequency estimation value of the signal in the current paragraph.

8. The speed measurement system according to claim 7, wherein The wavelet transform unit includes: A scale factor search range obtaining module: obtaining the scale factor search range of the wavelet transform of the signal in the current paragraph according to the step size of the wavelet transform scale factor and the frequency search range of the signal in the current paragraph; A wavelet coefficient obtaining module: performing wavelet transform on the signal in the current paragraph through the wavelet basis function, the step size of the wavelet transform scale factor, and the scale factor search range of the wavelet transform of the signal in the current paragraph to obtain wavelet coefficients; A wavelet ridge line extraction module: extracting the wavelet ridge line by using the modulus maximum value method according to the wavelet coefficients to obtain the instantaneous frequency estimation curve segment of the signal in the current paragraph.

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