Signal processing method, device and equipment and computer storage medium

Abstract

The invention belongs to the technical field of ultra-precise laser interference displacement measurement, and particularly discloses a signal processing method, which is applied to a laser interference measurement system, and comprises the following steps: receiving a first signal from a photoelectric converter, the first signal comprising an effective signal and an interference signal; wherein the effective signal comprises displacement information, and the interference signal is generated based on non-ideal polarization characteristics of a light source and a polarization element; filtering the first signal based on a frequency domain so as to eliminate the interference signal; performing phase processing on the processed first signal; after the signal of the photoelectric converter is processed by the signal processing method, the interference signal component in the signal is reduced, and then the signal is sent to phase processing, so that the phase processing precision is improved, and the displacement measurement precision is effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of ultra-precision laser interference displacement measurement, and specifically to a signal processing method, device, equipment and computer storage medium. Background Art

[0002] In displacement interference measurement, there is a type of displacement error that varies periodically with the change of displacement, called cyclic error (CE).

[0003] In order to eliminate cyclic error, a cyclic error compensation (CEC) algorithm can be used. Existing CEC compensation algorithms mainly rely on error modeling and parameter estimation to reconstruct the error signal and subtract it from the received signal. However, the parameter estimation method involves the calculation of many variables, with a large amount of calculation (even requiring offline calculation), and moreover, there are errors caused by the differences between the calibration scenario and the actual usage scenario in the calibration and calibration method. Summary of the Invention

[0004] The purpose of the present invention is to provide a signal processing method for eliminating cyclic non-linear errors, which can solve the problems of large computational complexity involved in the parameter estimation method; and errors caused by the differences between the calibration scenario and the actual usage scenario in the calibration and calibration method.

[0005] In the first aspect of the present invention, the present invention provides a signal processing method applied to a laser interference measurement system, and the method includes:

[0006] Receiving a first signal from a photoelectric converter, where the first signal includes a valid signal and an interference signal; wherein, the valid signal includes displacement information, and the interference signal is generated based on the non-ideal polarization characteristics of the light source and the polarization element.

[0007] Performing frequency-domain based filtering processing on the first signal to eliminate the interference signal;

[0008] Performing phase processing on the processed first signal.

[0009] After the signal of the photoelectric converter is processed by the signal processing method, the CE0 and CEN components of the interference signal in the signal are reduced, and then sent to phase processing, so as to improve the accuracy of phase processing, and further effectively improve the accuracy of displacement measurement.

[0010] In an implementation manner of the present invention, performing frequency-domain based filtering processing on the first signal includes:

[0011] The first signal is successively subjected to a first process and a second process, wherein the first process is used to analyze the autocorrelation of the first signal and predict the valid signal; the second process is used to eliminate the interference signals CE0 and CEN.

[0012] In an implementation manner of the present invention, the transfer function of the first process is:

[0013] D(z) = 1 + k o ·(1 + α)·z -1 + α·z -2 .

[0014] Wherein, k o corresponds to the filter locking frequency point coefficient, and α corresponds to the bandwidth information of the filter.

[0015] In an implementation manner of the present invention, the transfer function of the second process is:

[0016] N(z) = 1 + 2k o ·z -1 + z -2

[0017] In an implementation manner of the present invention, passing the first signal through the frequency-domain based filtering process further includes:

[0018] Passing the first signal through a third process, and the third process is used to maintain tracking of the valid signal CE1.

[0019] In an implementation manner of the present invention, passing the first signal through the frequency-domain based filtering process includes:

[0020] Filtering the first signal using an IIR filter; the transfer function of the IIR filter is:

[0021]

[0022] Wherein, k o corresponds to the filter locking frequency point parameter, and α corresponds to the bandwidth information of the filter.

[0023] In an implementation manner of the present invention, the α is determined based on the measurement requirements of the laser interferometry system.

[0024] In an implementation manner of the present invention, the initial value of the k o is determined based on the sampling rate of the analog-to-digital converter.

[0025] In an implementation manner of the present invention, the k o is updated in the following manner:

[0026] B(n) = B(n - 1)+·μ·x i (n - 1)·x i (n - 1);

[0027] C(n) = C(n - 1)+·μ·x i (n - 1)·(x i (n)+x i (n - 2));

[0028]

[0029] k o (n + 1)=k o (n)+μ·K_Value;

[0030] Wherein, x i (k) represents the sampling value of the input signal x at time k; μ is a speed factor for controlling frequency point search and convergence; B(n) and C(n) are intermediate variables recursively calculated from the input signal x at times n - 2, n - 1, and n, and are finally used to calculate the current frequency coefficient result K_Value; k o (n + 1) is the frequency locking frequency point parameter k based on the current n-th moment o (n) and the current frequency coefficient result K_Value, and the next frequency locking parameter at the n + 1-th moment is calculated

[0031] In a second aspect, the present invention provides a signal processing device, including units or modules for implementing the signal processing method provided in the first aspect as described above.

[0032] In a third aspect, the present invention provides a signal processing device, including a processor, a memory, and a computer program stored on the memory and executable on the processor. When the program is executed by the processor, the method provided in the first aspect as described above is implemented.

[0033] In a fourth aspect, the present invention provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the method provided in the first aspect as described above is implemented.

[0034] By adopting the technical solution provided by the present invention, through frequency-domain filtering processing of the signal from the optical-electric converter, the interference signal component in the signal can be effectively reduced, and most of the interference signals included in the received optical signal are cancelled, improving the accuracy of phase processing, and thus effectively improving the displacement measurement accuracy. Description of the Drawings

[0035] Figure 1 It is a schematic diagram of a dual-frequency interference measurement system;

[0036] Figure 2 Schematic flow diagram of a signal processing method provided by the present invention;

[0037] Figure 3 Schematic diagram of the IIR filter structure provided by the present invention;

[0038] Figure 4 Schematic diagram of the signal spectrum analysis of the signal without being processed by the signal processing method;

[0039] Figure 5 Schematic diagram of the signal spectrum analysis of the signal processed by the signal processing method;

[0040] Figure 6 Schematic diagram of the displacement error performance structure of the signal processing method. Specific embodiments

[0041] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0042] Please refer to Figure 1 the schematic diagram of the dual - frequency interference measurement system. The non - ideal polarization characteristics of the light source and the polarization element cause beam mixing of the measurement light and the reference light before interference in displacement interference measurement (such as an interferometer), that is, a part of the measurement light enters the reference optical path or a part of the reference light enters the measurement optical path. Therefore, in displacement interference measurement, periodic nonlinear errors will be generated.

[0043] Please refer to Figure 2 , the present invention provides a signal processing method, which is applied to a laser interference measurement system and can be used to eliminate periodic nonlinear errors.

[0044] The method includes the following steps:

[0045] Step 201: Receive a first signal from a photoelectric converter. The first signal includes a valid signal and an interference signal; wherein, the valid signal includes displacement information, and the interference signal is generated based on the non - ideal polarization characteristics of the light source and the polarization element.

[0046] Exemplarily, the interference signal includes a first - order nonlinear error (CE0) and / or a second - order nonlinear error (CEN).

[0047] Step 202: Perform filtering processing on the first signal based on the frequency domain to eliminate the interference signal.

[0048] Step 203: Perform phase processing on the processed first signal.

[0049] The signal of the optical - electric converter is processed by the signal processing method to reduce the interference signal component in the signal, and then sent to the phase processing, so as to improve the accuracy of the phase processing, and further effectively improve the displacement measurement accuracy.

[0050] In one embodiment, performing frequency - domain - based filtering processing on the first signal includes: sequentially passing the first signal through a first process and a second process, where the first process is used to analyze the autocorrelation of the first signal and predict the effective signal CE1; the second process is used to eliminate the effective signals CE0 and CEN.

[0051] Optionally, the transfer function of the first process is:

[0052] D(z) = 1 + k o ·(1 + α)·z -1 + α·z -2 .

[0053] Where k o corresponds to the filter locking frequency point coefficient, and α corresponds to the bandwidth information of the filter.

[0054] The transfer function of the second process is:

[0055] N(z) = 1 + 2k o ·z -1 + z -2

[0056] In one embodiment, performing frequency - domain - based filtering processing on the first signal further includes:

[0057] Passing the first signal through a third process, and the third process is used to maintain the tracking of the effective signal CE1.

[0058] In one embodiment, performing frequency - domain - based filtering processing on the first signal includes: filtering the first signal with an IIR filter (Infinite Impulse Response Filter); the transfer function of the infinite impulse response filter is:

[0059]

[0060] Where k o corresponds to the filter locking frequency point parameter, and α corresponds to the bandwidth information of the filter.

[0061] Exemplarily, such as Figure 3As shown, the infinite impulse response filter includes an AutoRegressive Block (AR Block), a Moving Average Block (MA Block), and a K0-Adaptive Update module.

[0062] Among them, the AR Block is used to predict the main components in the data according to the autocorrelation of the analyzed input data. The MA Block is used to eliminate the interference and noise components contained in the data. The KO-Adaptive Update is used to adaptively update the parameters to maintain real-time tracking of the CE1 effective signal.

[0063] α is determined based on the measurement requirements of the laser interferometry system.

[0064] In one embodiment, the initial value of k o is determined based on the sampling rate of the analog-to-digital converter.

[0065] In one embodiment, k o can be updated in the following manner:

[0066] B(n) = B(n - 1) + ·μ·x i (n - 1)·x i (n - 1);

[0067] C(n) = C(n - 1) + ·μ·x i (n - 1)·(x i (n) + x i (n - 2));

[0068]

[0069] k o (n + 1) = k o (n) + μ·K_Value;

[0070] Among them, x i (k) represents the sampling value of the input signal x at time k; μ is used to represent the speed factor for controlling frequency point search and convergence; B(n) and C(n) are intermediate variables recursively calculated from the input signal x at times n - 2, n - 1, and n, and are finally used to calculate the current frequency coefficient result K_Value; k o (n + 1) is the frequency-locked frequency point parameter k based on the current n-th moment o(n) and the current frequency coefficient result K_Value, the frequency locking parameter at the next moment of n+1 calculated. Exemplarily, a large value of μ represents a fast convergence speed and large fluctuations in the convergence result; a small value of the speed factor represents a slow convergence speed and a stable convergence result, which can be set in advance according to the specific needs of the system.

[0071] The present invention also provides a signal processing device, including units or modules for implementing the signal processing method as Figure 2 shown.

[0072] The present invention also provides a signal processing device, characterized in that it includes a processor, a memory, and a computer program stored on the memory and executable on the processor. When the program is executed by the processor, it implements the method as Figure 2 shown.

[0073] The present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements the method as Figure 2 shown.

[0074] In one example, the signal processing flow of the present invention specifically includes:

[0075] The electrical signal "CEC In" containing effective displacement information from the optoelectronic converter contains the CE1 effective signal and the CE0 and CEN interference signals.

[0076] In the initial state of the system, the parameter α is set according to the system measurement requirements, that is, the filter bandwidth of the CE error compensation technical solution is set; according to the setting of the sampling rate of the analog-to-digital sampler (ADC) in signal processing, the parameter k o is given an initial value (the frequency point represented by this initial value is not necessarily the accurate frequency point of the useful signal CE1). This parameter is an adaptive update parameter and is continuously updated as data is input until it converges to the frequency point where the CE1 effective signal is located.

[0077] At time n, the CEC In signal is r(n); it first enters the IIR filter AR Block.

[0078] This module updates the estimation of the effective signal component in the input signal according to the current data and its correlation, designs signal processing according to the indication of the D(z) transfer function, and the output is x i (n) as the input of the IIR filter MA Block.

[0079] At time n, the output x i (n) of the AR Block is input into the MA Block.

[0080] Design signal processing according to the N(z) transfer function indication. The module filters out the estimated values x of interference signals (CE0, CEN) except for the valid signal CE1 through a moving average processing scheme f (n), and subtracts this output from the input signal r(n) at time n (eliminating the estimated value of the interference signal from the input signal) to obtain the output of the entire CE error compensation scheme module for subsequent processing; in addition, in this scheme, according to the interference estimation signal x f (n), the frequency point parameter k is designed o The updated cost function f(n), which is used for the update of the frequency point parameter k o of.

[0081] The CE error compensation technical solution updates the system frequency point parameter k based on the gradient of the system cost function f(n) o .

[0082] The frequency point parameter k o The update process, where the parameter μ is a fixed parameter that controls the convergence speed

[0083] To sum up, please refer to Figures 4 - 6 , the effect of a signal processing method of the present invention in actual measurement

[0084] According to the signal processing method given in the present invention, based on a commercial FPGA multi-purpose development platform, the above signal processing method of the present invention is implemented, and an optical path is built for actual measurement of displacement performance

[0085] Basic equipment for actual measurement verification:

[0086] 1. Commercial FPGA multi-purpose development platform

[0087] 2. Dual-frequency laser

[0088] 3. Mirror group

[0089] 4. Displacement stage

[0090] Actual measurement verification conditions:

[0091] 1. Laser wavelength used: 633 nm

[0092] 2. Movement speed of the displacement stage: 20 mm / s

[0093] 3. Frequency aliasing degree caused by the set CE error: approximately 40%

[0094] Conclusion:

[0095] 1. The signal processing method effectively reduces the signal intensity of the interference components (CE0, CEN) in the received signal by more than 20 dB

[0096] 2. In this verification, the displacement measurement error of the laser interferometric measurement system without the signal processing method is approximately 20 nm.

[0097] 3. The displacement measurement error of the laser interferometric measurement system with the signal processing method is approximately 1 nm.

[0098] This verification proves that the signal processing method effectively reduces the influence of interference components (CE0, CEN) in the received optoelectronic signal, improves the accuracy of phase estimation, and thus enhances the displacement measurement performance of the laser interferometric measurement system.

[0099] Although the embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention, and the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A signal processing method, characterized in that: Applied to a laser interferometry system, the method comprises: Receiving a first signal from a photoelectric converter, wherein the first signal includes a valid signal and an interference signal; wherein the valid signal includes displacement information, and the interference signal is generated based on non-ideal polarization characteristics of a light source and a polarization element; Performing frequency domain filtering on the first signal to eliminate the interference signal; Perform phase processing on the processed first signal.

2. The method according to claim 1, characterized in that The step of subjecting the first signal to frequency domain-based filtering includes: The first signal is sequentially subjected to a first process and a second process, wherein the first process is used to analyze the autocorrelation of the first signal and predict the effective signal; and the second process is used to eliminate the interference signal.

3. The method according to claim 2, wherein the transfer function of the first process is: D(z)=1+k o (1+α) with -1 +α with -2 。 in, k o The corresponding filter locking frequency coefficient and α correspond to the bandwidth information of the filter.

4. The method according to claim 2, wherein the transfer function of the second process is: N(z)=1+2k o ·With -1 +with -2 in, k o Corresponding filter locking frequency coefficient (same as above).

5. The method according to any one of claims 2 to 4, characterized in that: The step of subjecting the first signal to frequency domain filtering also includes: The first signal is subjected to a third process, and the third process is used to keep tracking of the valid signal.

6. The method according to claim 1, characterized in that The step of subjecting the first signal to frequency domain-based filtering includes: The first signal is filtered using an IIR filter; the transfer function of the IIR filter is: Among them, k o The corresponding filter lock frequency parameter, α corresponds to the bandwidth information of the filter.

7. The method according to any one of claims 3, 4 and 6, characterized in that: The α is determined based on the measurement requirements of the laser interferometry system.

8. The method according to any one of claims 3, 4 and 6, characterized in that: The k o The initial value of is determined based on the sampling rate of the analog-to-digital converter.

9. The method according to any one of claims 3, 4 and 6, characterized in that: The k o Update as follows: B(n)=B(n-1)+·µ·x i (n−1)·x i (n-1)? C(n)=C(n-1)+·μ·x i (n−1)·(x i (n)+x i (n-2)): k o (n+1)=k o (n)+μ·K_Value; Among them, x i (k) represents the sampling value of the input signal x at time k; μ represents the speed factor used to control the frequency search and convergence; B(n) and C(n) are intermediate variables obtained by recursively calculating the input signal x at time n-2, n-1 and n; k o (n+1) is the frequency lock frequency parameter k based on the current time n o (n) and the current frequency coefficient result K_Value, and calculate the frequency locking parameter for the next time n+1.

10. A signal processing device, comprising a unit or module for implementing the signal processing method according to any one of claims 1 to 9.

11. A signal processing device, characterized in that: The method comprises a processor, a memory and a computer program stored in the memory and executable on the processor, wherein when the program is executed by the processor, the method according to any one of claims 1 to 9 is implemented.

12. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 9 is implemented.

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