An enhanced Doppler frequency extraction optimization method and speed measurement system

Abstract

The invention relates to the technical field of optical logic elements, and specifically discloses an enhanced Doppler frequency extraction optimization method and a speed measurement system, which are used to solve the problems of low spectrum resolution, spectrum leakage and large measurement error in traditional laser Doppler speed measurement technology. The method comprises integrating optical logic elements and collecting data, signal preprocessing, performing fast Fourier transform, spectrum refinement, spectrum correction, extracting Doppler frequency and obtaining object speed. The system comprises a laser, which is connected to an optical logic element through an optical fiber, and the optical logic element is projected onto a target object through the optical fiber using a double-beam scattering light path model. The invention improves the spectrum resolution and accuracy of the laser Doppler speed measurement system by combining the optical logic element, an improved Hanning window function and a phase compensation refinement algorithm, dynamically adjusts the spectrum refinement multiple and a PID feedback mechanism for correcting spectrum errors, and eliminates spectrum leakage and errors in a high dynamic environment.

Description

Technical Field

[0001] The present invention relates to the technical field of optical logic elements, and more specifically, to an enhanced Doppler frequency extraction optimization method and a speed measurement system. Background Art

[0002] With the continuous advancement of laser technology, laser Doppler velocimetry has become an effective method for accurately measuring the speed of an object. Through the Doppler effect, the frequency change of the reflected light can reflect the speed of the object. Traditional laser Doppler velocimetry technology has a wide range of applications, but the spectral resolution of its velocity measurement system is limited by the performance of the equipment, especially in high-precision velocity measurement situations. The fixed spectral resolution will affect the accuracy and efficiency of velocity measurement. Although the Fourier transform refinement method is effective, it has a large amount of calculation and insufficient suppression of external noise, which will lead to a decrease in frequency extraction accuracy. In the open CNKI document (Xi Chongbin, Zhou Jian, Nie Xiaoming, et al. Influence of emission inclination on the performance of laser Doppler velocimeter [J]. Infrared and Laser Engineering, 2024), a measurement method of segmented setting of laser emission inclination or segmented setting of sampling frequency is proposed for different velocity measurement ranges and accuracies, and the steps for determining different velocity measurement intervals are given. At the same time, the effects of segmented setting of emission inclination and sampling frequency are studied. It is expected that the velocity measurement range can be adjusted and the velocity measurement accuracy can be improved by adjusting the emission inclination. In recent years, the application of optical logic elements has provided a new research direction for precision speed measurement. Optical logic elements (such as optical switches, optical storage elements, and optical amplifiers) can realize high-speed signal modulation and switching during laser transmission and processing, greatly improving the processing speed and accuracy of optical signals. These elements can be used to enhance the frequency boosting capability of the laser Doppler speed measurement system and complete high-precision frequency extraction and speed calculation in a short time. However, in the process of coherent Doppler laser speed measurement data processing, due to the fixed resolution of the segmented spectrum, the speed measurement accuracy is difficult to further improve, and the traditional Fourier transform method has limitations in spectrum leakage and error, large amount of calculation, and cannot adapt to the application scenario of fast real-time response. The irrelevant noise and interference in the signal affect the frequency extraction accuracy and the accuracy of the speed measurement results. The application of optical logic elements is not yet sufficient, and their high-speed and high-precision signal processing capabilities have not been fully utilized. Summary of the invention

[0003] In order to overcome the above-mentioned defects of the prior art, the present invention provides an enhanced Doppler frequency extraction optimization method and a speed measurement system, which improves the spectral resolution and accuracy of the laser Doppler speed measurement system by combining optical logic elements, an improved Hanning window function and a phase compensation refinement algorithm, dynamically adjusts the spectrum refinement multiple and the PID feedback mechanism for correcting the spectrum error, and eliminates spectrum leakage and errors in high dynamic environments.

[0004] With the widespread application of industrial robot arms, the rotation speed of their robot arms is monitored, especially in the robot arms and CNC machine tools on the automated production lines of high-speed rotating robots. The car speed measurement mentioned in the background technology is a straight-line speed measurement, which cannot be fully adapted to the rotation speed measurement of the robot rotating arm proposed in this application. The rotation speed is crucial to the accuracy of task execution, and high-precision rotation movements need to be completed in a very short time. Traditional laser Doppler speed measurement technology cannot meet the needs of high-precision real-time speed measurement due to limited spectral resolution and large Fourier transform calculation amount. Especially when the object rotates at a very high speed, the fixed segmented spectral resolution will lead to inaccurate speed measurement results and slow response speed.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] An enhanced Doppler frequency extraction optimization method uses the original light wave frequency information output by the detector, extracts the Doppler signal through an algorithm, extracts the Doppler signal frequency, and combines the optical path system parameters to obtain the moving speed of the object, including the following steps:

[0007] Step 1, integrating optical logic elements and collecting data: setting the laser wavelength of the laser velocimeter and the half angle of the two incident light beams, setting the sampling frequency and the signal length, using the laser velocimeter to collect the first signal sequence, using the first signal sequence data as the input of step 2, and using the optical logic element to perform high-speed signal modulation and switching, so that the optical logic element and the laser velocimeter work together;

[0008] Step 2, signal preprocessing: preprocess the first signal sequence, remove noise through autocorrelation processing, apply the improved Hanning window function to suppress spectrum leakage and errors introduced in the Fourier transform process, and obtain the second signal sequence;

[0009] Step 3, performing fast Fourier transform: performing fast Fourier transform on the windowed second signal sequence to obtain a third signal sequence in the frequency domain, and extracting first Doppler effect spectrum information reflecting the Doppler effect by analyzing the domain signal;

[0010] Step 4, spectrum refinement: According to the spectrum diagram, select the set interval where the maximum peak is located, apply the ZoomFFT algorithm (phase compensation refinement algorithm) to refine the spectrum of the interval with the set refinement multiple and spectrum resolution, and obtain the second Doppler effect spectrum information;

[0011] Step 5, spectrum correction: further correcting the second Doppler effect spectrum information, correcting the spectrum deviation in the second Doppler effect spectrum information, eliminating the error generated in step 4, and obtaining third Doppler effect spectrum information;

[0012] Step six, extract the Doppler frequency and obtain the object speed: in the spectrum sequence of the third Doppler effect spectrum information, identify the frequency value corresponding to the maximum peak as the extracted Doppler frequency, combine the relationship between the object speed and the Doppler frequency, and use the relevant parameters of the optical path system to obtain the movement speed of the object.

[0013] As a further technical solution of the present invention, in step 1, the process of the optical logic element and the laser velocimeter working in coordination includes:

[0014] Step 1, generating and modulating laser signals: the laser source emits a laser beam with a set wavelength and phase, and the optical logic element modulates the laser beam so that it can interact with the target object to produce a Doppler effect;

[0015] Step 2, real-time dynamic adjustment of the laser signal: the optical logic element obtains a preliminary Doppler frequency difference according to the initial motion state of the target object. After the laser beam is irradiated onto the target object and reflected back, the optical logic element obtains the initial frequency difference between the reflected light and the laser source through spectrum analysis. Based on the initial motion speed of the target object, the expected frequency difference between the reflected light and the laser source is obtained. The optical logic element compares the initial frequency difference and the expected frequency difference between the reflected light and the laser source to obtain the spectrum error between the two. Based on the spectrum error, the optical logic element minimizes the spectrum error according to the reflection angle fine-tuning amount dynamically adjusted based on the feedback mechanism.

[0016] In laser speed measurement, when the laser beam is irradiated on a moving target, the reflected light will produce a frequency shift due to the target. The magnitude of the frequency shift is related to the target speed, laser wavelength and incident angle. In practical applications, there will be slight deviations in the reflection angle due to specific problems such as mechanical installation and manufacturing errors, environmental influences, adaptive and feedback errors, and surface quality of optical devices. This slight error is transmitted to the Doppler frequency shift extraction process, resulting in a spectrum error. At this time, the error propagation method can be used to link the spectrum error with the fine-tuning amount of the reflection angle. According to the relationship between the Doppler effect, , is the target speed, is the frequency shift, is the laser incident angle. For small angle deviations, the Taylor expansion is used to linearize and is expressed as , and here, It is the sensitivity of frequency shift to reflection angle. In order to reflect the geometric projection effect of different directions of the optical path, the derivative term includes the laser wavelength and the sine factor of the incident angle. Therefore, the fine-tuning amount of the reflection angle is considered: the proportional effect related to the wavelength and the cosine component of the incident angle to reflect the influence of the change of the optical path difference in this direction on the frequency shift; consider the compensation for the other direction (controlled by the sine component of the incident angle) to help refine the correction effect. Finally, the dimensions of the two are transformed and aligned with the reflection angle fine-tuning amount. The corresponding dimension adjustment coefficients are used for the two to obtain the formula for the reflection angle fine-tuning amount, and the correction of the cosine and sine components are introduced respectively to form a multi-angle and sub-item compensation method, while considering the influence of the laser wavelength and the incident angle on the Doppler frequency shift.

[0017] As a further technical solution of the present invention, in step 2, the reflection angle fine-tuning amount dynamically adjusted based on the feedback mechanism dynamically adjusts the reflection angle according to the influence of the spectrum error, the laser incident angle and the wavelength to minimize the spectrum error. The formula of the reflection angle fine-tuning amount is:

[0018] ;

[0019] Where: is the reflection angle fine-tuning amount, is the laser wavelength, is the spectrum error, is the laser incident angle, , Both are adjustment coefficients, used to adjust , and The dimensional difference between them makes the dimensions of both sides of the equation the same.

[0020] As a further technical solution of the present invention, in step 2, an improved Hanning window function is used to automatically adjust the smoothness of the Hanning window function based on the characteristics of the real-time signal, and change the weighted distribution in the time domain. The improved Hanning window function formula is: ;

[0021] Where: is the time index, , , is a natural number greater than 2, is the windowed signal sequence at time The window function value on , is the signal strength of the first signal sequence, is a dynamic adjustment coefficient based on the signal strength of the first signal sequence in real time Dynamically adjust the smoothness of the window function, is the signal length, i.e. the number of sampling points, , is the noise level of the first signal sequence, To control the coefficient of spectrum leakage, based on the noise level of the first signal sequence Dynamic adjustment.

[0022] As a further technical solution of the present invention, in step 2, in the formula of the improved Hanning window function, the dynamic adjustment coefficient selects the minimum value between the ratio of the current signal strength to the maximum reference value of the signal strength and 1, and the formula of the dynamic adjustment coefficient is:

[0023] ;

[0024] Where: is the maximum reference value of the signal strength of the first signal sequence, which is determined by the maximum signal amplitude obtained through experiments, For selection The minimum value between 1 and It is obtained by taking the root mean square of the time domain signal of the first signal sequence, ,in is the time domain signal data of the first signal sequence.

[0025] As a further technical solution of the present invention, in step 2, in the formula of the improved Hanning window function, the coefficient for controlling spectrum leakage is equal to 1 plus the inverse of the sum of the noise level adjustment value, and the coefficient formula for controlling spectrum leakage is:

[0026] ;

[0027] Where: is the application scenario adjustment coefficient, which is determined according to the experimental calibration value of the actual application scenario. Obtained by the standard deviation of the time domain signal of the first signal sequence, ,in is the time domain signal mean of the first signal sequence.

[0028] As a further technical solution of the present invention, in step one, the spectrum information of the laser signal is reflected and returned, and is analyzed by the optical logic element, and is transmitted to step two through a feedback mechanism for dynamically adjusting the reflection angle and optimizing signal processing.

[0029] As a further technical solution of the present invention, in step 4, the set interval where the maximum peak value is located is ,in is the maximum peak in the first Doppler effect spectrum information spectrum graph, and the spectrum refinement multiple is , the spectrum resolution after refinement is , is the sampling frequency;

[0030] In step five, the energy center of gravity correction method is used to further correct the second Doppler effect spectrum information.

[0031] As a further technical solution of the present invention, based on the autocorrelation denoising and improved Hanning window function output of step two, combined with the spectrum refinement result in step four, the refinement multiple of the ZoomFFT algorithm is dynamically corrected by the feedback adjustment amount calculated by the PID feedback loop mechanism.

[0032] A speed measurement system, using the above-mentioned enhanced Doppler frequency extraction optimization method, includes a laser, the laser is connected to an optical logic element through an optical fiber, the optical logic element is projected onto a target object through the optical fiber using a double-beam scattering light path model, and is reflected back to an APD detector through a receiving lens group, the APD detector is connected to a computer through an acquisition card, the acquisition card collects a set number of points and transmits them to the computer for speed calculation, and the computer is connected to the laser and the optical logic element.

[0033] The technical effects of an enhanced Doppler frequency extraction optimization method and a speed measurement system proposed by the present invention are as follows:

[0034] By introducing optical logic elements, the present invention can complete high-precision frequency extraction and speed calculation in a short time, reduce the calculation amount of the measurement process, and meet the real-time speed measurement requirements of the rotating arm of the industrial robot. The improved Hanning window function and ZoomFFT algorithm effectively suppress frequency leakage and errors, further improve the accuracy of frequency extraction, overcome the limitations of traditional laser Doppler speed measurement, improve the shortcomings of segmented fixed spectrum resolution speed measurement accuracy, and adapt to the real-time response requirements of rotating arm rotation speed measurement. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 A schematic diagram of the connection of components of a test system for applying the method proposed in the present invention;

[0036] Figure 2 The algorithm processing flow chart of the method proposed by the present invention;

[0037] Figure 3 It is a line graph comparing the data in Tables 1 to 3 of the present invention;

[0038] Figure 4 It is a statistical diagram of the data in Table 4 of the present invention;

[0039] Figure 5 The flowchart of the method proposed by the present invention is shown in FIG. DETAILED DESCRIPTION

[0040] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in 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. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0041] Example 1

[0042] like Figure 5 and Figure 2 As shown, the enhanced Doppler frequency extraction optimization method proposed by the present invention uses the original light wave frequency information output by the detector, extracts the Doppler signal through an algorithm, extracts the Doppler signal frequency, and obtains the moving speed of the object in combination with the optical path system parameters, including the following steps:

[0043] Step 1, integrating optical logic elements and collecting data: setting the laser wavelength of the laser velocimeter and the half angle of the two incident light beams, setting the sampling frequency and the signal length, using the laser velocimeter to collect the first signal sequence, using the first signal sequence data as the input of step 2, and using the optical logic element to perform high-speed signal modulation and switching, so that the optical logic element and the laser velocimeter work together;

[0044] Step 2, signal preprocessing: preprocess the first signal sequence, remove noise through autocorrelation processing, apply the improved Hanning window function to suppress spectrum leakage and errors introduced in the Fourier transform process, and obtain the second signal sequence;

[0045] Step 3, performing fast Fourier transform: performing fast Fourier transform on the windowed second signal sequence to obtain a third signal sequence in the frequency domain, and extracting first Doppler effect spectrum information reflecting the Doppler effect by analyzing the domain signal;

[0046] Step 4, spectrum refinement: According to the spectrum diagram, select the set interval where the maximum peak is located, apply the ZoomFFT algorithm (phase compensation refinement algorithm) to refine the spectrum of the interval with the set refinement multiple and spectrum resolution, and obtain the second Doppler effect spectrum information;

[0047] Step 5, spectrum correction: further correcting the second Doppler effect spectrum information, correcting the spectrum deviation in the second Doppler effect spectrum information, eliminating the error generated in step 4, and obtaining third Doppler effect spectrum information;

[0048] Step six, extract the Doppler frequency and obtain the object speed: in the spectrum sequence of the third Doppler effect spectrum information, identify the frequency value corresponding to the maximum peak as the extracted Doppler frequency, combine the relationship between the object speed and the Doppler frequency, and use the relevant parameters of the optical path system to obtain the movement speed of the object.

[0049] The traditional laser Doppler speed measurement system has a fixed spectral resolution, resulting in insufficient speed measurement accuracy for objects with high rotation speeds. The present invention effectively improves the spectral resolution and ensures high-precision frequency extraction by introducing the ZoomFFT algorithm and dynamic spectrum refinement technology. ZoomFFT (Phase Compensation Refinement Algorithm) is an optimized Fast Fourier Transform (FFT) technology used to improve spectral resolution, especially when processing high-speed signals in Doppler frequency extraction. It reduces spectral leakage and errors by refining in specific frequency intervals, thereby improving the accuracy of frequency extraction. The following is the detailed processing flow of the ZoomFFT algorithm:

[0050] (1) Initial Fourier transform: In step 3, the signal sequence is first subjected to a standard fast Fourier transform (FFT) to obtain a preliminary spectrum in the frequency domain. This process converts the signal from the time domain to the frequency domain, revealing the frequency components in the signal. At this stage, the FFT maps the spectral distribution of the signal to the entire frequency range, but the resolution is low. Especially for high-frequency signals of high-speed rotating objects, the resolution may not be sufficient to accurately distinguish close frequency peaks.

[0051] (2) Selecting a refinement interval: Once the FFT obtains a preliminary spectrum, it is necessary to select a frequency interval for refinement. This interval is usually determined by the frequency of the maximum peak (or other significant peaks nearby). The key to ZoomFFT is to focus on this high-frequency area for refinement rather than refining the entire spectrum. The selection of a refinement interval helps to improve refinement accuracy and reduce the computational burden on irrelevant frequency areas. The refinement interval is the frequency around the maximum peak and is set to ,in is the maximum peak in the first Doppler effect spectrum information spectrum graph, and the spectrum refinement multiple is , the spectrum resolution after refinement is , is the sampling frequency, which ensures more details near the target frequency.

[0052] (3) Phase compensation: A key step of ZoomFFT is phase compensation. When Fourier transform processes non-periodic signals, spectrum leakage or error will occur, resulting in reduced spectrum resolution. The ZoomFFT algorithm corrects this leakage effect by introducing phase compensation. The goal of phase compensation is to correct the error caused by the sampling theorem in the spectrum and reduce the spectrum leakage caused by the application of the window function. This compensation dynamically adjusts the spectrum according to the phase information of the signal, making the frequency components in the refined area more accurate.

[0053] (4) Refining spectral resolution: After determining the refinement interval, ZoomFFT enhances the resolution by changing the FFT refinement factor. Specifically, the refinement factor determines the degree of improvement in spectral resolution. For the selected frequency interval, ZoomFFT further increases the calculation accuracy through the interpolation method, allowing more precise resolution of adjacent spectral peaks;

[0054] (5) Extracting precise frequencies: Once the refinement process is complete, the algorithm extracts the most significant frequency peaks from the refined spectrum. These peaks represent important frequency components in the signal, especially those related to the Doppler effect. By analyzing the refined spectrum, the ZoomFFT algorithm identifies the maximum peak closest to the signal source frequency. The frequency corresponding to this peak is the Doppler frequency of the signal.

[0055] (6) Spectral correction: To further improve accuracy, ZoomFFT usually performs a final spectral correction step to correct deviations that may occur during the refinement process. This process helps to eliminate spectral offsets caused by computational errors or during the refinement process. Based on the results of the refined spectrum, ZoomFFT performs spectral deviation correction to make frequency extraction more accurate and eliminate errors caused by the refinement process.

[0056] The refinement factor is an important adjustable parameter in ZoomFFT. By increasing the refinement factor, FFT can obtain finer frequency resolution and thus more accurately extract the Doppler frequency of the target signal.

[0057] The Fourier transform has a large amount of calculation and cannot respond in real time. The present invention reduces the amount of calculation and achieves real-time response through high-speed signal modulation and switching of optical logic elements combined with improved algorithms and feedback mechanisms.

[0058] Traditional methods cannot effectively suppress the influence of noise and spectrum leakage. By improving the Hanning window function and adaptive noise suppression technology, the influence of noise on the spectrum is reduced, thereby improving the accuracy of Doppler frequency extraction.

[0059] It should be noted that, in step 1, the process of the optical logic element and the laser velocimeter working together includes:

[0060] Step 1, generating and modulating laser signals: the laser source emits a laser beam with a set wavelength and phase, and the optical logic element modulates the laser beam so that it can interact with the target object to produce a Doppler effect;

[0061] Step 2, real-time dynamic adjustment of the laser signal: the optical logic element obtains a preliminary Doppler frequency difference according to the initial motion state of the target object. After the laser beam is irradiated onto the target object and reflected back, the optical logic element obtains the initial frequency difference between the reflected light and the laser source through spectrum analysis. Based on the initial motion speed of the target object, the expected frequency difference between the reflected light and the laser source is obtained. The optical logic element compares the initial frequency difference and the expected frequency difference between the reflected light and the laser source to obtain the spectrum error between the two. Based on the spectrum error, the optical logic element minimizes the spectrum error according to the reflection angle fine-tuning amount dynamically adjusted based on the feedback mechanism.

[0062] By introducing optical logic elements into the laser speed measurement system and utilizing its high-speed signal modulation and feedback mechanism, the present invention can dynamically adjust the frequency of the laser signal in real time, eliminate the spectrum error between the reflected light and the laser source, and accurately capture the Doppler frequency difference of the object, thereby achieving rapid adaptation and accurate measurement of the initial motion state of the target object. The optical logic element dynamically adjusts the reflection angle according to the spectrum error, minimizes the spectrum error, ensures high-precision frequency extraction and speed measurement, and is particularly suitable for rapidly changing motion states. Through this feedback mechanism, the interaction between the laser beam and the target object is optimized, greatly improving the extraction accuracy of the Doppler effect, and effectively solving the spectrum leakage and error problems of traditional speed measurement technology in high-speed or high-dynamic environments.

[0063] It should be noted that in step 2, the reflection angle fine-tuning amount dynamically adjusted based on the feedback mechanism dynamically adjusts the reflection angle according to the influence of the spectrum error, the laser incident angle and the wavelength to minimize the spectrum error. The formula for the reflection angle fine-tuning amount is:

[0064] ;

[0065] Where: is the reflection angle fine-tuning amount, is the laser wavelength, is the spectrum error, is the laser incident angle, , They are adjustment coefficients, which are used to control the influence of wavelength, error and incident angle on the reflection angle adjustment.

[0066] By dynamically adjusting the reflection angle fine-tuning amount based on a feedback mechanism, the present invention can accurately control the angle of the reflected light according to the changes in the spectrum error, laser incident angle and wavelength, minimize the measurement deviation caused by the spectrum error, and thus improve the accuracy of Doppler frequency extraction. The dynamic adjustment of the reflection angle fine-tuning amount enables the system to adapt to the changes in the motion state of the target object in real time, optimize the interaction between the light beam and the object, reduce spectrum leakage and errors, and ensure that the laser speed measurement system can accurately obtain the reflected light frequency and effectively calculate the object's motion speed in high-dynamic, high-precision application scenarios. This process further improves the system's real-time response capability to rapidly changing motion states by adjusting the effects of laser wavelength, error and incident angle, ensuring efficient and accurate speed measurement performance.

[0067] It should be noted that in step 2, the improved Hanning window function is used to automatically adjust the smoothness of the Hanning window function based on the characteristics of the real-time signal, and change the weighted distribution in the time domain. The improved Hanning window function formula is:

[0068] ;

[0069] Where: is the time index, , , is a natural number greater than 2, is the windowed signal sequence at time The window function value on , is the signal strength of the first signal sequence, is a dynamic adjustment coefficient based on the signal strength of the first signal sequence in real time Dynamically adjust the smoothness of the window function, is the signal length, i.e. the number of sampling points, , is the noise level of the first signal sequence, To control the coefficient of spectrum leakage, based on the noise level of the first signal sequence Dynamic adjustment.

[0070] By using an improved Hanning window function and dynamically adjusting the smoothness of the window function based on the characteristics of the real-time signal, the present invention can effectively cope with changes in signal strength and noise and optimize the signal preprocessing process. When the signal strength is strong, the window function has a smaller smoothness and retains more spectral information; when the noise is strong, the smoothness is increased to effectively suppress the influence of noise. In addition, the dynamic adjustment coefficient α (S) and the coefficient γ (N) for controlling spectrum leakage can automatically adjust the weighted distribution of the window function according to the real-time changes of the signal, reduce spectrum leakage, and improve the frequency extraction accuracy. This method significantly improves the signal processing effect in a high noise environment, making the spectral characteristics of the signal more accurate, thereby improving the accuracy of Doppler frequency extraction and the overall performance of the system.

[0071] It should be noted that in step 2, in the formula of the improved Hanning window function, the dynamic adjustment coefficient selects the minimum value between the ratio of the current signal strength to the maximum reference value of the signal strength and 1, and the formula of the dynamic adjustment coefficient is:

[0072] ;

[0073] Where: is the maximum reference value of the signal strength of the first signal sequence, which is determined by the maximum signal amplitude obtained through experiments, For selection The minimum value between 1 and It is obtained by taking the root mean square of the time domain signal of the first signal sequence, ,in is the time domain signal data of the first signal sequence.

[0074] By introducing a dynamic adjustment coefficient into the improved Hanning window function , and select the minimum value between the ratio of the current signal strength to the maximum reference value of the signal strength and 1. The present invention can dynamically adjust the smoothness of the window function according to the real-time signal strength. Specifically, when the signal strength is high, the smoothness of the window function is small, retaining more spectrum details and ensuring the accuracy of the signal; and when the signal strength is low, the smoothness is increased to effectively suppress the interference of noise. This dynamic adjustment method can adapt to the changes in signal strength in real time, significantly improve the spectrum resolution under different signal conditions, reduce spectrum leakage, thereby improving the accuracy of Doppler frequency extraction and the robustness of the system in a high-noise environment.

[0075] It should be noted that in step 2, in the formula of the improved Hanning window function, the coefficient for controlling spectrum leakage is equal to 1 plus the inverse of the sum of the noise level adjustment value, and the coefficient formula for controlling spectrum leakage is:

[0076] ;

[0077] Where: is the application scenario adjustment coefficient, which is determined according to the experimental calibration value of the actual application scenario. Obtained by the standard deviation of the time domain signal of the first signal sequence, ,in is the time domain signal mean of the first signal sequence.

[0078] It is a coefficient that is experimentally calibrated based on the signal characteristics and noise level in the actual application scenario. By collecting signal data in different noise environments and analyzing spectrum leakage, the appropriate value to ensure that spectrum leakage is effectively suppressed. For example, in the application scenario of high-speed rotation of industrial robots or high-speed moving objects, The value of can be verified experimentally to optimize the signal processing effect. When the noise level is high, a larger value to enhance the leakage suppression capability, and can be appropriately reduced when the noise is low value.

[0079] It should be noted that in step one, the spectrum information of the laser signal is reflected and returned, and is analyzed by the optical logic element, and is transmitted to step two through a feedback mechanism for dynamically adjusting the reflection angle and optimizing signal processing.

[0080] It should be noted that in step 4, the setting interval where the maximum peak value is located is ,in is the maximum peak in the first Doppler effect spectrum information spectrum graph, and the spectrum refinement multiple is , the spectrum resolution after refinement is , is the sampling frequency;

[0081] In step five, the energy center of gravity correction method is used to further correct the second Doppler effect spectrum information.

[0082] Specifically, the implementation steps of the energy center of gravity correction method include:

[0083] Step (1), obtaining spectrum information: First, through the previous steps (such as fast Fourier transform and spectrum refinement), the second Doppler effect spectrum information is obtained. This spectrum contains multiple frequency components, some of which are offset due to signal noise or refinement errors;

[0084] Step (2), calculate the energy center of gravity of the spectrum: the energy center of gravity refers to the weighted average position of all frequency components in the spectrum, the weight is the energy of the frequency component, and the energy center of gravity frequency of the spectrum is obtained according to its calculation formula;

[0085] Step (3), calculating the spectrum offset and correcting the spectrum deviation: using the frequency value corresponding to the maximum peak in the first Doppler spectrum effect spectrum minus the energy center frequency in the spectrum, to obtain the spectrum offset. By making this adjustment to all frequency points, the overall offset of the spectrum is corrected, so that the maximum peak and energy center position of the spectrum are closer to the expected ideal value;

[0086] Step (4), re-extract frequency: re-extract the most significant frequency peaks from the corrected spectrum, which will correspond to the true Doppler frequency of the target signal.

[0087] It should be noted that based on the autocorrelation denoising and improved Hanning window function output in step 2, combined with the spectrum refinement result in step 4, the feedback adjustment amount calculated by the PID feedback loop mechanism dynamically corrects the refinement multiple of the ZoomFFT algorithm.

[0088] By combining the autocorrelation denoising and improved Hanning window function output of step two, combining the spectrum refinement result in step four, and dynamically correcting the refinement multiple of the ZoomFFT algorithm through the PID feedback loop mechanism, the present invention can automatically optimize the accuracy of spectrum refinement according to the real-time characteristics and noise level of the signal. This method effectively improves the spectral resolution, reduces spectrum leakage and errors, and ensures high precision and high response speed of Doppler frequency extraction, especially in high-speed rotating objects or complex dynamic environments. The PID feedback mechanism adjusts the refinement multiple in real time, so that the refinement process adapts to different signal conditions, and finally achieves more accurate speed measurement and frequency extraction, which improves the performance and stability of the system in high-precision real-time speed measurement.

[0089] According to the wave nature of light, when a beam of light is irradiated on a moving object, the Doppler effect will occur, and the frequency of the reflected light will change according to the speed of the moving object. The single beam of reflected light wave contains detection, so the frequency difference generated by the two beams of light waves is used to calculate the speed of the moving object, and the difference frequency information can be directly detected and output frequency information. Assume that the ideal frequency difference detected is , according to the relevant parameters, the corresponding speed is through the relationship Find the speed. Among them, is the ideal difference frequency. The algorithm proposed in this invention is dedicated to finding the accurate Doppler frequency. is the angle between the two incident light beams, is the wavelength of the incident light, is the velocity of the object being measured.

[0090] In actual measurements, the detector output includes the frequency information of the original light wave, the frequency information of the reflected light wave after the frequency difference, and various external factors, which causes the effective frequency difference information to be submerged in the output signal. It is necessary to use an algorithm to extract the Doppler signal from the total output signal. After the frequency is extracted, the object's movement speed is calculated based on the optical path parameters.

[0091] To clearly illustrate the actual technical effect of the method proposed in Example 1, a high-speed rotating turntable moving at a linear speed of 50 m / s was used as the target object to simulate the high-speed rotation operation of the robot arm. The speed of three categories was measured every 30 seconds by increasing by 10 m / s, decreasing by 5 m / s after another 30 seconds, and increasing by 10 m / s after another 30 seconds. Eight groups of test data were obtained, namely test group 1, test group 2, test group 3, test group 4, test group 5, test group 6, test group 7, and test group 8. The central wavelength of the laser used was 1550 nm. 32768 points were collected each time for speed calculation. The phase compensation refinement algorithm was used to refine the spectrum of the speed measurement target frequency spectrum interval [2.601×107 Hz, 3.851×107 Hz]. The initial value of the refinement multiple was set to 20. According to the relationship between the laser frequency and the speed, , find the speed of the moving object. , are 1.2 and 0.8 respectively, The data comparison tables of the 8 test groups are shown in Tables 1 to 4, and the data of the system response time comparison for the first speed switching, the second speed switching, and the third speed switching are shown in Table 5:

[0092] Table 1 Comparison of the speed measurement results of the method proposed by the present invention and the traditional method obtained by the above test for 8 test groups when the object rotation linear speed is 50m / s

[0093]

[0094] Table 2 Comparison of the speed measurement results of the method proposed by the present invention and the traditional method obtained by the above test for 8 test groups when the object rotation linear speed is 60m / s

[0095]

[0096] Table 3 Comparison of the speed measurement results of the method proposed by the present invention and the traditional method obtained by the above test for 8 test groups when the object rotation linear speed is 55m / s

[0097]

[0098] Table 4 Comparison of the speed measurement results of the method proposed by the present invention and the traditional method obtained by the above test for 8 test groups when the object rotation linear speed is 65m / s

[0099]

[0100] Table 5 Comparison of the response time of the traditional method and the method of the present invention for three switching speeds

[0101]

[0102] The data in Tables 1 to 3 show that the comparison accuracy between the method proposed in the present invention and the traditional method is improved, and the highest measurement accuracy reaches 0.000591 m / s; Table 4 shows that the response speed of the method proposed in the present invention when switching the speed of the target object is improved, and the fastest response time reaches 5 seconds.

[0103] Figure 3 Display the data line charts from Table 1 to Table 4. Figure 4 A line chart showing the corresponding data in Table 5.

[0104] Example 2

[0105] The difference between Example 2 of the present invention and Example 1 is that this example introduces the composition of a speed measurement system using an enhanced Doppler frequency extraction optimization method introduced in Example 1.

[0106] like Figure 1 As shown, a speed measurement system proposed by the present invention uses an enhanced Doppler frequency extraction optimization method of Example 1, including a laser, the laser is connected to an optical logic element through an optical fiber, the optical logic element is projected onto the target object through the optical fiber using a double-beam scattering light path model, and is reflected back to the APD detector through a receiving lens group, the APD detector is connected to a computer through an acquisition card, the acquisition card collects a set number of points and transmits them to the computer for speed calculation, and the computer is connected to the laser and the optical logic element.

[0107] In summary, by introducing optical logic elements, the present invention can complete high-precision frequency extraction and speed calculation in a short time, reduce the calculation amount of the measurement process, meet the real-time speed measurement requirements of the industrial robot's rotating arm, and the improved Hanning window function and ZoomFFT algorithm effectively suppress frequency leakage and errors, further improve the accuracy of frequency extraction, overcome the limitations of traditional laser Doppler speed measurement, improve the shortcomings of segmented fixed spectrum resolution speed measurement accuracy, and adapt to the real-time response requirements of rotating arm rotational motion speed measurement.

[0108] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0109] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. An enhanced Doppler frequency extraction optimization method uses the original light wave frequency information output by the detector, extracts the Doppler signal through an algorithm, extracts the Doppler signal frequency, and combines the optical path system parameters to obtain the object's moving speed, characterized in that: The following steps are involved: Step 1, integrating optical logic elements and collecting data: setting the laser wavelength of the laser velocimeter and the half angle of the two incident light beams, setting the sampling frequency and the signal length, using the laser velocimeter to collect the first signal sequence, using the first signal sequence data as the input of step 2, and using the optical logic element to perform high-speed signal modulation and switching, so that the optical logic element and the laser velocimeter work together; Step 2, signal preprocessing: preprocess the first signal sequence, remove noise through autocorrelation processing, apply the improved Hanning window function to suppress spectrum leakage and errors introduced in the Fourier transform process, and obtain the second signal sequence; in the formula of the improved Hanning window function, the dynamic adjustment coefficient selects the minimum value between the ratio of the current signal strength to the maximum reference value of the signal strength and 1, and the formula of the dynamic adjustment coefficient is: Where: S max is the maximum reference value of the signal strength of the first signal sequence, which is determined by the maximum signal amplitude obtained through experiments, For selection and 1, S is obtained by the time domain signal root mean square of the first signal sequence, Where x(t) is the time domain signal data of the first signal sequence, and T is the signal length; Step 3, performing fast Fourier transform: performing fast Fourier transform on the windowed second signal sequence to obtain a third signal sequence in the frequency domain, and extracting first Doppler effect spectrum information reflecting the Doppler effect by analyzing the domain signal; Step 4, spectrum refinement: According to the spectrum diagram, select a set interval where the maximum peak is located, apply the ZoomFFT algorithm to refine the spectrum of the interval with a set refinement multiple and spectrum resolution, and obtain the second Doppler effect spectrum information; Step 5, spectrum correction: further correcting the second Doppler effect spectrum information, correcting the spectrum deviation in the second Doppler effect spectrum information, eliminating the error generated in step 4, and obtaining third Doppler effect spectrum information; Step six, extract the Doppler frequency and obtain the object speed: in the spectrum sequence of the third Doppler effect spectrum information, identify the frequency value corresponding to the maximum peak as the extracted Doppler frequency, combine the relationship between the object speed and the Doppler frequency, and use the relevant parameters of the optical path system to obtain the movement speed of the object.

2. The enhanced Doppler frequency extraction optimization method according to claim 1, characterized in that: In step 1, the process of the optical logic element and the laser velocimeter working together includes: Step 1, generating and modulating laser signals: the laser source emits a laser beam with a set wavelength and phase, and the optical logic element modulates the laser beam so that it can interact with the target object to produce a Doppler effect; Step 2, real-time dynamic adjustment of the laser signal: the optical logic element obtains a preliminary Doppler frequency difference according to the initial motion state of the target object. After the laser beam is irradiated onto the target object and reflected back, the optical logic element obtains the initial frequency difference between the reflected light and the laser source through spectrum analysis. Based on the initial motion speed of the target object, the expected frequency difference between the reflected light and the laser source is obtained. The optical logic element compares the initial frequency difference and the expected frequency difference between the reflected light and the laser source to obtain the spectrum error between the two. Based on the spectrum error, the optical logic element minimizes the spectrum error according to the reflection angle fine-tuning amount dynamically adjusted based on the feedback mechanism.

3. The enhanced Doppler frequency extraction optimization method according to claim 2, characterized in that: In step 2, the reflection angle fine-tuning amount dynamically adjusted based on the feedback mechanism dynamically adjusts the reflection angle according to the influence of the spectrum error, laser incident angle and wavelength to minimize the spectrum error. The formula of the reflection angle fine-tuning amount is: Where: Δθ ref is the reflection angle fine-tuning amount, λ is the laser wavelength, Δf err is the spectrum error, θ inc is the laser incident angle, K1 and K2 are adjustment coefficients.

4. The enhanced Doppler frequency extraction optimization method according to claim 3, characterized in that: In step 2, the improved Hanning window function is used to automatically adjust the smoothness of the Hanning window function based on the characteristics of the real-time signal, and change the weighted distribution in the time domain. The improved Hanning window function formula is: Where: t is the time index, t=1,2,…,B, B is a natural number greater than 2, ω(t) is the window function value of the windowed signal sequence at time t, S is the signal strength of the first signal sequence, α(S) is a dynamic adjustment coefficient, and the smoothness of the window function is dynamically adjusted based on the signal strength S in the real-time first signal sequence, T is the signal length, that is, the number of sampling points, T=2B+1, N is the noise level of the first signal sequence, and γ(N) is a coefficient for controlling spectrum leakage, which is dynamically adjusted based on the noise level N of the first signal sequence.

5. The enhanced Doppler frequency extraction optimization method according to claim 4, characterized in that: In step 2, in the formula of the improved Hanning window function, the coefficient for controlling spectrum leakage is equal to 1 plus the inverse of the sum of the noise level adjustment value. The coefficient formula for controlling spectrum leakage is: Where: β is the application scenario adjustment coefficient, which is determined according to the experimental calibration value of the actual application scenario; N is the noise level, which is obtained by the standard deviation of the time domain signal of the first signal sequence. Wherein μ is the time domain signal mean of the first signal sequence.

6. The enhanced Doppler frequency extraction optimization method according to claim 5, characterized in that: In step one, the spectrum information of the laser signal is reflected and returned, and is analyzed by the optical logic element, and is transmitted to step two through a feedback mechanism for dynamically adjusting the reflection angle and optimizing signal processing.

7. The enhanced Doppler frequency extraction optimization method according to claim 1, characterized in that: In step 4, the setting interval where the maximum peak value is located is [f max -0.2f max ,f max +0.2f max ], where f max is the maximum peak in the first Doppler effect spectrum information spectrum diagram, the spectrum refinement multiple is D, and the spectrum resolution after refinement is f s / D,f s is the sampling frequency; In step five, the energy center of gravity correction method is used to further correct the second Doppler effect spectrum information.

8. The enhanced Doppler frequency extraction optimization method according to claim 7, characterized in that: Based on the autocorrelation denoising and improved Hanning window function output in step 2, combined with the spectrum refinement result in step 4, the refinement multiple of the ZoomFFT algorithm is dynamically corrected by the feedback adjustment amount calculated through the PID feedback loop mechanism.

9. A speed measurement system, using the enhanced Doppler frequency extraction optimization method according to any one of claims 1 to 8, characterized in that: It includes a laser, which is connected to an optical logic element through an optical fiber. The optical logic element is projected onto a target object through the optical fiber using a double-beam scattering light path model, and is reflected back to an APD detector through a receiving lens group. The APD detector is connected to a computer through an acquisition card. The acquisition card collects a set number of points and transmits them to the computer for speed calculation. The computer is connected to the laser and the optical logic element.

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