Grating-based micrometer-scale position adjustment and control system

Abstract

The application relates to the technical field of grating signal processing, and discloses a micron-level position adjustment and control system based on a grating, which comprises a signal acquisition and analysis module, a jitter identification module, an intelligent optimization module and a spectrum reconstruction module.The signal acquisition and analysis module is used for acquiring original electric signals of the grating and performing frequency domain conversion processing on the original electric signals to generate a frequency domain spectrum; the jitter identification module is used for identifying interference frequency components in the frequency domain spectrum based on a preset characteristic frequency range of a displacement signal; the intelligent optimization module is used for constructing an initial interference set and optimizing spectrum reconstruction parameters through a genetic algorithm; the spectrum reconstruction module is used for performing amplitude suppression and phase compensation on the interference frequency according to an optimization result and performing transition band smoothing processing; and the signal reconstruction module is used for restoring the frequency domain spectrum to a time domain signal, correcting phase distortion and outputting a stable displacement measurement result.The application realizes adaptive identification and reconstruction suppression of interference frequencies in a grating signal, and improves the precision and stability of displacement measurement.

Description

Technical Field

[0001] This invention belongs to the field of grating signal processing technology, specifically relating to a micron-level position adjustment and control system based on gratings. Background Technology

[0002] With the rapid development of modern industry and precision measurement technology, grating displacement sensors are widely used in displacement and position measurement. Grating ruler technology, with its high precision and reliability, has been widely applied in precision measurement, automation control, and testing equipment. However, with the increasing complexity of measurement environments and the improvement of system operating speeds, existing grating displacement sensors often experience problems such as signal jitter, phase distortion, and spectral interference during high-frequency signal acquisition and dynamic measurement, which directly affect the accuracy of displacement measurement and system stability.

[0003] Traditional grating displacement measurement systems typically employ signal processing techniques such as amplitude suppression and phase compensation to address these issues. However, these methods are usually limited to simple spectral filtering or static phase correction, failing to effectively handle the complexity of spectral variations in dynamic environments. Under conditions of wide-ranging environmental fluctuations and high-frequency noise, the system's signal processing capabilities are often insufficient, leading to decreased measurement accuracy and system instability. Furthermore, existing spectral reconstruction methods often lack specificity and adaptability. Since different application scenarios have varying requirements for spectral reconstruction, traditional methods typically employ fixed parameters and static algorithms, resulting in poor adaptability to complex environments and an inability to achieve accurate real-time compensation and dynamic optimization. Summary of the Invention

[0004] This invention provides a micron-level position adjustment and control system based on a grating, which solves the technical problems in related technologies such as insufficient spectrum reconstruction capability, inability to effectively suppress noise and dynamically optimize parameters, resulting in difficulty in guaranteeing measurement accuracy and system stability.

[0005] This invention provides a grating-based micrometer-level position adjustment and control system, comprising:

[0006] The signal acquisition and analysis module is used to acquire the raw electrical signal output by the grating displacement sensor during operation, and to perform frequency domain conversion processing to generate a frequency domain spectrum containing the amplitude and phase of frequency components.

[0007] The jitter identification module is used to identify interference frequency components in the frequency domain spectrum based on the preset characteristic frequency range of the displacement signal. The interference frequency components include a first type of interference frequency that exceeds the characteristic frequency range and a second type of interference frequency that is within the characteristic frequency range.

[0008] The intelligent optimization module is used to construct an initial interference set containing interference frequency components. By evaluating the smoothness and amplitude deviation of the signal after spectrum reconstruction, a genetic algorithm is used to iteratively optimize the spectrum reconstruction parameters within a first preset time window to maximize the stability of the reconstruction result and minimize the frequency domain error. The spectrum reconstruction parameters include: interference frequency removal threshold, phase compensation coefficient, and bandwidth transition width, which constitute a combination of reconstruction parameters for spectrum reconstruction adjustment.

[0009] The spectrum reconstruction module is used to perform amplitude suppression and phase compensation operations on the interference frequency components according to the optimized reconstruction parameter combination, and to perform transition band smoothing on the frequency band boundary region;

[0010] The signal reconstruction module is used to convert the frequency domain spectrum processed by the spectrum reconstruction module into a time domain signal, eliminate phase distortion in the time domain signal, and output the displacement measurement value after anti-jitter processing.

[0011] Furthermore, within the characteristic frequency range of the preset displacement signal, the amplitude of each frequency component within N consecutive sampling periods is squared, and the average value of the accumulated energy is calculated to obtain the energy concentration degree. The energy concentration degree is compared with the predetermined first energy threshold, and when the energy concentration degree is greater than the first energy threshold, the frequency component is determined to be a first type of interference frequency.

[0012] Furthermore, the identification of the second type of interference frequencies includes:

[0013] For each frequency component within the characteristic frequency range, extract the phase value within P consecutive sampling periods to construct a first-order phase difference sequence;

[0014] Calculate the phase change stability characteristics based on the first-order phase difference sequence;

[0015] When the phase change stability feature exceeds the set phase change threshold, the frequency component is identified as a second type of interference frequency. The phase change stability feature is obtained by calculating the mean square error of the difference sequence.

[0016] Furthermore, the intelligent optimization module uses a genetic algorithm to optimize the combination of reconstruction parameters. Within the first preset time window, the removal threshold of each interference frequency component in the initial interference set is periodically rewritten. By evaluating the cumulative difference of the current spectrum reconstruction effect, the phase compensation coefficient and the bandwidth transition width are adjusted successively until a combination of reconstruction parameters that meets the set requirements is obtained.

[0017] During the adjustment of parameter combinations during reconstruction, conditions are imposed, including:

[0018] The interference frequency elimination threshold is limited to the range between the mean frequency domain energy minus the preset standard deviation and the mean frequency domain energy plus the preset standard deviation;

[0019] The adjustment range of the phase compensation coefficient shall not exceed the allowable range for phase continuity;

[0020] The bandwidth of the frequency band transition region is less than the upper limit of the allowed frequency response.

[0021] Furthermore, after the intelligent optimization module completes the correction of the first round of reconstruction parameter combinations for the interference frequency components within the first preset time window, it compares the degree of difference between the reconstructed frequency domain distribution information collected within the second preset time window and the initial reference spectrum distribution. When the degree of difference exceeds a preset difference threshold, it triggers the correction process of the next round of reconstruction parameter combinations.

[0022] Furthermore, after determining the combination of reconstruction parameters that meets the reconstruction setting requirements, the intelligent optimization module uses the combination of reconstruction parameters as the final output result and uses it to update the initial interference set, providing the updated initial interference set to predictive parameter compensation in the next cycle of spectrum reconstruction process.

[0023] Furthermore, the amplitude suppression operation includes:

[0024] Calculate the difference between the maximum and minimum phase values ​​of the interference frequency components within a preset time window, and use this as the phase fluctuation amplitude;

[0025] When the phase fluctuation amplitude exceeds the fluctuation amplitude threshold, nonlinear compression processing is triggered, and the amplitude of the frequency component is attenuated in the form of an exponential function.

[0026] The phase compensation operation includes: constructing a phase change sequence for the phase values ​​of the interference frequency component in multiple consecutive sampling periods; calculating the phase instability characteristics based on the first-order differential fluctuation of the sequence; and injecting a phase reconstruction function into the frequency point corresponding to the interference frequency component when the phase instability characteristics exceed the phase instability threshold.

[0027] The transition band smoothing process includes: constructing the transition band range of the current frequency band boundary region based on the interference frequency distribution characteristics recorded in the previous period, and dynamically adjusting the transition band width in combination with the frequency domain amplitude gradient change.

[0028] Furthermore, the generation steps of the phase reconstruction function include:

[0029] S401: Extract historical phase data of the current frequency point for D consecutive processing cycles from the reference spectrum, and use a first-order linear regression algorithm to generate the target phase reference trajectory that changes linearly with time.

[0030] S402, calculate the phase difference between the current frequency point and the two adjacent frequency points on the left and right, and construct the slip compensation weight coefficient;

[0031] S403 multiplies the deviation between the current measured phase value and the target phase reference trajectory by the slip compensation weight coefficient to generate a phase reconstruction function.

[0032] Furthermore, the phase distortion removal operation includes:

[0033] S501, a time series model is constructed based on the historical phase change rate data in E consecutive optimization cycles at the current frequency point, which is used to output the predicted value of the target phase change rate;

[0034] S502, obtain the actual phase change rate of the frequency point within the current optimization cycle, and calculate the deviation between the actual phase change rate and the predicted value of the target phase change rate;

[0035] S503, Generate a corrected phase vector based on the deviation, and superimpose it onto the real-time phase value at the current frequency point.

[0036] The beneficial effects of this invention are as follows: By constructing a multi-module signal processing system including interference frequency identification, intelligent optimization, and spectrum reconstruction, this invention achieves accurate identification and adaptive suppression of jitter interference in the output signal of a grating displacement sensor. By introducing a spectrum optimization mechanism based on error feedback and a dynamic phase compensation strategy, it effectively improves the system's adaptability to non-steady-state interference, significantly reduces frequency domain distortion and phase jump problems, and can still achieve stable and high-precision displacement signal reconstruction under different working conditions and complex environments. This enhances the robustness and reliability of the measurement system and overcomes the problems of strong fixedness and weak adjustment capability in spectrum reconstruction in the prior art. Attached Figure Description

[0037] Figure 1 This is a schematic diagram of the module of the micron-level position adjustment and control system based on grating of the present invention. Detailed Implementation

[0038] The subject matter described herein will now be discussed with reference to exemplary embodiments. It should be understood that these embodiments are discussed only to enable those skilled in the art to better understand and implement the subject matter described herein, and changes may be made to the function and arrangement of the elements discussed without departing from the scope of this specification. Various processes or components may be omitted, substituted, or added as needed in the examples. Furthermore, features described in some examples may be combined in other examples.

[0039] like Figure 1 As shown, the micron-level position adjustment and control system based on a grating includes:

[0040] The signal acquisition and analysis module 101 is used to acquire the raw electrical signal output by the grating displacement sensor during operation, and to perform frequency domain conversion processing on it to generate a frequency domain spectrum containing the amplitude and phase of frequency components.

[0041] The jitter identification module 102 is used to identify interference frequency components in the frequency domain spectrum based on the preset characteristic frequency range of the displacement signal, wherein the interference frequency components include a first type of interference frequency that exceeds the characteristic frequency range and a second type of interference frequency that is within the characteristic frequency range.

[0042] The intelligent optimization module 103 is used to construct an initial interference set containing interference frequency components. By evaluating the smoothness and amplitude deviation of the signal after spectrum reconstruction, a genetic algorithm is used to iteratively optimize the spectrum reconstruction parameters within a first preset time window to maximize the stability of the reconstruction result and minimize the frequency domain error. The spectrum reconstruction parameters include: interference frequency removal threshold, phase compensation coefficient, and bandwidth transition width. The three parameters constitute a combination of reconstruction parameters for spectrum reconstruction adjustment.

[0043] The spectrum reconstruction module 104 is used to perform amplitude suppression and phase compensation operations on the interference frequency components according to the optimized reconstruction parameter combination, and to perform transition band smoothing on the frequency band boundary region.

[0044] The signal reconstruction module 105 is used to convert the frequency domain spectrum processed by the spectrum reconstruction module into a time domain signal, eliminate phase distortion in the time domain signal, and output the displacement measurement value after anti-jitter processing.

[0045] In one embodiment of the present invention, the system periodically acquires real-time raw electrical signals from the output of the grating displacement sensor via a high-speed analog-to-digital converter. During the acquisition process, the system sets a sampling time window and continuously acquires Q sampling points within the time window to form a time-domain sampling sequence. The system then performs a fast Fourier transform on the sampling sequence to convert it from the time domain to the frequency domain, thereby obtaining the amplitude spectrum and phase spectrum of the corresponding frequency components. This constitutes the frequency domain spectrum within the current time window. The frequency domain spectrum is represented in complex form and includes the amplitude and phase angle corresponding to each frequency component.

[0046] In one embodiment of the present invention, within the characteristic frequency range of a preset displacement signal, the amplitude of each frequency component within N consecutive sampling periods is squared, the accumulated energy is then calculated to obtain the mean value, and the energy concentration degree is obtained. The energy concentration degree is compared with a predetermined first energy threshold, and when the energy concentration degree is greater than the first energy threshold, the frequency component is determined to be a first type of interference frequency.

[0047] In one embodiment of the present invention, the characteristic frequency range of the preset displacement signal refers to the frequency interval corresponding to the effective displacement signal caused by the actual displacement change under the normal operating conditions of the grating displacement sensor; specifically, the step of determining the frequency range includes:

[0048] S201, Based on the mechanical motion characteristics of the object measured by the grating displacement sensor, such as the motion speed, motion period, and maximum allowable acceleration, determine the lowest possible frequency limit of the effective displacement signal.

[0049] S202, based on the working characteristics of the grating displacement sensor and the required measurement resolution, determine the upper limit of the highest frequency that can be effectively detected and distinguished;

[0050] S203 defines the frequency range between the determined lower frequency limit and the upper frequency limit as the characteristic frequency range of the preset displacement signal.

[0051] In one embodiment of the present invention, energy concentration indicates whether the energy of a certain frequency component is continuously concentrated at that frequency point within multiple sampling periods, rather than fluctuating sporadically; the method for setting the first energy threshold is as follows: in a stable environment where the system is free from interference and only has normal displacement signals, M sets of frequency domain data are continuously collected, and the mean and standard deviation of the energy of the frequency components in each set that are greater than the upper limit of the characteristic frequency are statistically analyzed, and a first energy threshold is set. ,in, Indicates the first energy threshold. This represents the mean, and k represents the amplification factor, which is preferably set to 2. It represents the standard deviation.

[0052] In one embodiment of the present invention, the identification of the second type of interference frequency includes: extracting the phase value within P consecutive sampling periods for each frequency component in the characteristic frequency range, and constructing a first-order phase difference sequence; calculating the phase change stability feature based on the first-order phase difference sequence; and determining the frequency component as the second type of interference frequency when the phase change stability feature exceeds a set phase change threshold. The phase change stability feature is obtained by calculating the mean square error of the difference sequence. The phase change threshold is set as follows: under reference conditions where there is no external disturbance and only normal displacement signal exists, phase difference sequences of multiple frequency points are collected, the fluctuation range of phase change is statistically obtained, and a "fluctuation upper limit" is set as the phase change threshold.

[0053] In one embodiment of the present invention, the intelligent optimization module uses a genetic algorithm to optimize the combination of reconstruction parameters. Within a first preset time window, the removal threshold for each interference frequency component in the initial interference set is periodically rewritten. By evaluating the cumulative difference in the current spectrum reconstruction effect, the phase compensation coefficient and the bandwidth transition zone width are adjusted successively until a combination of reconstruction parameters that meets the set requirements is obtained. Specifically, the set requirements include: the energy of the removed interference frequency components is reduced to below a preset interference threshold to ensure that the interference signal is effectively suppressed; after spectrum reconstruction, the difference between the reconstructed signal and the original signal is lower than a preset tolerance threshold, i.e., the cumulative difference in the spectrum reconstruction effect reaches a minimum; the combination of reconstruction parameters remains stable during multiple iterations, and the adjusted parameters do not cause excessive fluctuations in the spectrum reconstruction result.

[0054] During the adjustment of parameter combinations during reconstruction, conditions are imposed, including:

[0055] The interference frequency elimination threshold is limited to the range between the mean frequency domain energy minus the preset standard deviation and the mean frequency domain energy plus the preset standard deviation;

[0056] The adjustment range of the phase compensation coefficient shall not exceed the allowable range for phase continuity;

[0057] The bandwidth of the frequency band transition region is less than the upper limit of the allowed frequency response.

[0058] In one embodiment of the present invention, the intelligent optimization module performs periodic parameter correction on the initial interference set and evaluates the current spectrum reconstruction effect using a cumulative difference index, thereby successively adjusting the interference frequency removal threshold, phase compensation coefficient, and bandwidth transition width. This process includes the following steps:

[0059] S301, the frequency domain distribution over a period of time is recorded by the main control system under initial conditions, and is denoted as the reference spectrum. This reference spectrum is used as the benchmark for subsequent comparison of differences.

[0060] S302, within the first preset time window, continuously acquire the raw signal output by the grating displacement sensor, convert it into frequency domain data, and then perform spectrum reconstruction using the current parameter combination; after each reconstruction is completed, the reconstructed frequency domain distribution is obtained and sent to the intelligent optimization module;

[0061] S303, compare the reconstructed frequency domain distribution with the reference spectrum, calculate the amplitude difference for each frequency component and accumulate them to obtain the cumulative difference value within the current time window; the cumulative value reflects the overall deviation of the reconstructed spectrum from the reference spectrum;

[0062] S304, after each cumulative difference calculation, the cumulative value is compared with the set reconstruction difference threshold; when the cumulative difference is lower than the threshold, it is determined that the current parameter combination meets the setting requirements of the present invention, and further parameter correction within the current cycle is no longer triggered; when the cumulative difference is higher than the threshold, a parameter adjustment process is triggered.

[0063] During parameter adjustment, the intelligent optimization module uses the current difference as the driving signal to perform a search and replacement operation for candidate parameter combinations in the parameter space. All candidate parameter combinations must meet preset parameter constraints, including: the interference frequency elimination threshold must be limited to the mean of the reference spectrum energy ± the preset standard deviation; the adjustment range of the phase compensation coefficient must not exceed the set phase continuity boundary; and the bandwidth of the frequency band transition region should be limited to the allowable range of frequency response.

[0064] S305 If multiple parameter corrections within this time window still fail to reduce the cumulative difference to below the reconstruction difference threshold, then proceed to the next time window and continue collecting data. During the iteration process of multiple consecutive time windows, once the reconstruction parameters stabilize the cumulative difference below the reconstruction difference threshold, it is considered that the expected reconstruction accuracy of the system has been achieved. At this time, the parameter combination is recorded as the final optimal solution and output to the spectrum reconstruction module.

[0065] In one embodiment of the present invention, after the intelligent optimization module completes the correction of the first round of reconstruction parameter combination of the interference frequency components within a first preset time window, it applies the reconstruction parameter combination to the grating displacement signal processing within a second preset time window. Within the second preset time window, the system accumulates the reconstructed frequency domain distribution and compares it with the initial reference spectrum, calculating the error index and stability index of the current spectrum respectively, and constructing a comprehensive objective function to evaluate the effectiveness of the current reconstruction parameter combination. The mean square error of the amplitude is used as the error index of the current spectrum, and the rate of change of the parameters is used as the stability index of the current spectrum. When the objective function value fails to meet the preset performance threshold, the system triggers the correction operation of the next round of reconstruction parameter combination.

[0066] During this correction process, the intelligent optimization module uses a genetic algorithm to generate and screen candidate reconstruction parameter combinations. The fitness function guides the population to evolve in the direction of maximizing the stability of spectrum reconstruction and minimizing the error until the optimization converges or the stopping condition is met, and finally determines the optimal reconstruction parameter combination under the current working condition.

[0067] In one embodiment of the present invention, after determining the combination of reconstruction parameters that meets the reconstruction setting requirements, the intelligent optimization module uses the combination of reconstruction parameters as the final output result and uses it to update the initial interference set, and provides the updated initial interference set to the predictive parameter compensation in the next cycle spectrum reconstruction process.

[0068] In one embodiment of the present invention, the final combination of reconstructed parameters includes the optimal frequency band transition width, interference frequency elimination threshold and corresponding phase compensation coefficient obtained under the current operating conditions. The system records this combination as an "experience reference template" in the parameter history table and provides a reference in the interference identification and parameter initialization stage of the next cycle. This is used to accelerate the convergence speed of the optimization process and reduce repeated parameter tuning, thereby achieving predictive response capability for complex dynamic environments.

[0069] In one embodiment of the present invention, the amplitude suppression operation includes:

[0070] Calculate the difference between the maximum and minimum phase values ​​of the interference frequency components within a preset time window, and use this as the phase fluctuation amplitude;

[0071] When the phase fluctuation amplitude exceeds the fluctuation amplitude threshold, nonlinear compression processing is triggered, and the amplitude of the frequency component is attenuated in the form of an exponential function.

[0072] The phase compensation operation includes: constructing a phase change sequence for the phase values ​​of the interference frequency component over multiple consecutive sampling periods; calculating the phase instability characteristic based on the first-order differential variability of the sequence; and injecting a phase reconstruction function into the frequency point corresponding to the interference frequency component when the phase instability characteristic exceeds the phase instability threshold. Specifically, the mean square variability of the phase change sequence is calculated as the phase instability characteristic. The phase reconstruction function fits the historical phase trend of the frequency point in the reference spectrum and introduces a phase slip coefficient to maintain the continuity of the current phase response in the time series, thereby suppressing phase jumps in the short-time frequency domain and improving the phase fidelity and system stability after signal reconstruction.

[0073] The transition band smoothing process includes: constructing the transition band range of the current frequency band boundary region based on the interference frequency distribution characteristics recorded in the previous period, and dynamically adjusting the transition band width in combination with the frequency domain amplitude gradient change.

[0074] In one embodiment of the present invention, the interference frequency distribution features include: the distribution range, energy distribution gradient, and relative concentration of all interference frequency components identified in a certain optimization cycle on the frequency axis, specifically including but not limited to: the minimum frequency, maximum frequency, frequency center, number of interference frequencies, and the first-order rate of change of spectral energy density in the frequency band; the interference frequency distribution features are extracted by the intelligent optimization module after parameter iteration and used as a reference for the subsequent spectrum reconstruction module to perform boundary smoothing processing;

[0075] When performing transition band smoothing in the frequency band boundary region, the spectrum reconstruction module adopts an adaptive adjustment strategy based on the amplitude change rate. The system first determines the frequency window length within the boundary region, calculates the first-order difference sequence of amplitude between every two adjacent frequency points within the window, and obtains the average amplitude gradient of the current boundary region accordingly. The system sets an amplitude gradient threshold to identify the intensity of response change at the boundary frequency. When the average amplitude gradient is greater than the amplitude gradient threshold, it is determined that there is a steep frequency response change at the current boundary. The system multiplies the current default transition band width by the width amplification factor to amplify it. Otherwise, the system maintains the current width to ensure the fidelity of the main signal frequency band. The value range of the width amplification factor is 1.5 to 2.

[0076] In one embodiment of the present invention, the step of generating the phase reconstruction function includes:

[0077] S401, extract historical phase data of the current frequency point for D consecutive processing cycles from the reference spectrum, and use a first-order linear regression algorithm to generate a target phase reference trajectory that changes linearly with time. Preferably, the value of D is 5.

[0078] S402, calculate the phase difference between the current frequency point and its two adjacent frequency points on the left and right, and construct the slip compensation weight coefficient. The formula for calculating the slip compensation weight coefficient is as follows: ,in, This represents the slip compensation weighting coefficient. Indicates the frequency point index. This represents the phase difference between the current frequency point and its left adjacent frequency point. This indicates the phase difference between the current frequency point and the frequency point adjacent to it on the right.

[0079] S403 multiplies the deviation between the current measured phase value and the target phase reference trajectory by the slip compensation weight coefficient to generate a phase reconstruction function.

[0080] In one embodiment of the present invention, the phase distortion elimination operation includes:

[0081] S501, a time series model is constructed based on the historical phase change rate data in E consecutive optimization cycles at the current frequency point, which is used to output the target phase change rate prediction value. Preferably, E is set to 5.

[0082] S502, obtain the actual phase change rate of the frequency point within the current optimization cycle, and calculate the deviation between the actual phase change rate and the predicted value of the target phase change rate;

[0083] S503, Generate a corrected phase vector based on the deviation, and superimpose it onto the real-time phase value at the current frequency point.

[0084] In one embodiment of the present invention, the signal reconstruction module adopts a phase compensation method based on phase dynamic evolution. The system first extracts the phase data of the current frequency point in multiple historical optimization cycles, and uses the first-order polynomial method to construct a time series model for these data. Through the prediction function of the model, the system can predict the future trend of the target frequency component based on the phase change of the target frequency component during each frequency domain to time domain conversion process.

[0085] The system combines real-time spectrum feedback to generate a corrected phase vector based on the calculated target phase change rate, adjusting the phase value at that frequency point in the current cycle. This method not only ensures a smooth transition during the spectrum reconstruction process, but also effectively eliminates errors caused by phase jumps or discontinuities during the spectrum reconstruction process, improving the phase fidelity of the final output signal and the system stability.

[0086] In one embodiment of the present invention, the displacement measurement value is used to construct a filter weight function based on the frequency-time domain error feedback within the current time window. The filter weight function adjusts the shape of the filter kernel and the length of the response window according to the phase continuity residual of the current output signal and the target response delay constraint.

[0087] In one embodiment of the present invention, the signal reconstruction module introduces a dynamic filter based on error feedback. During the frequency-to-time domain signal conversion, the system continuously collects time-domain error feedback information of the current output signal, mainly including the amplitude difference and phase continuity residual between the current signal and the reference spectrum. The system dynamically adjusts the weighting function of the filter by real-time calculation of the current error. In the filter design, the weighting function not only considers the smoothness of the frequency response but also introduces a target response delay constraint, enabling the filter to minimize jitter while ensuring the real-time performance of the signal response speed. By adjusting the shape of the filter kernel and the length of the response window, the system can flexibly respond to different noise levels and signal changes at different signal processing stages, optimizing the balance between anti-jitter performance and response speed.

[0088] The embodiments of the present invention have been described above, but the present invention is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms based on the guidance of the present embodiments, all of which are within the protection scope of the present embodiments.

Claims

1. A micrometer-level position adjustment and control system based on a grating, characterized in that, include: The signal acquisition and analysis module is used to acquire the raw electrical signal output by the grating displacement sensor during operation, and to perform frequency domain conversion processing to generate a frequency domain spectrum containing the amplitude and phase of frequency components. The jitter identification module is used to identify interference frequency components in the frequency domain spectrum based on the preset characteristic frequency range of the displacement signal. The interference frequency components include a first type of interference frequency that exceeds the characteristic frequency range and a second type of interference frequency that is within the characteristic frequency range. The intelligent optimization module is used to construct an initial interference set containing interference frequency components. By evaluating the smoothness and amplitude deviation of the signal after spectrum reconstruction, a genetic algorithm is used to iteratively optimize the spectrum reconstruction parameters within a first preset time window to maximize the stability of the reconstruction result and minimize the frequency domain error. The spectrum reconstruction parameters include: interference frequency removal threshold, phase compensation coefficient, and bandwidth transition width, which constitute a combination of reconstruction parameters for spectrum reconstruction adjustment. Within the first preset time window, the removal threshold for each interference frequency component in the initial interference set is periodically rewritten. By evaluating the cumulative difference in the current spectrum reconstruction effect, the phase compensation coefficient and the bandwidth transition zone width are adjusted successively until a reconstruction parameter combination that meets the set requirements is obtained. Specifically, the set requirements include: the energy of the removed interference frequency components is reduced to below the preset interference threshold to ensure that the interference signal is effectively suppressed; after spectrum reconstruction, the difference between the reconstructed signal and the original signal is lower than the preset tolerance threshold, that is, the cumulative difference in the spectrum reconstruction effect reaches the minimum value; the reconstruction parameter combination remains stable during multiple iterations, and the adjusted parameters do not cause excessive fluctuations in the spectrum reconstruction result. The spectrum reconstruction module is used to perform amplitude suppression and phase compensation operations on the interference frequency components according to the optimized reconstruction parameter combination, and to perform transition band smoothing on the frequency band boundary region; The signal reconstruction module is used to convert the frequency domain spectrum processed by the spectrum reconstruction module into a time domain signal, eliminate phase distortion in the time domain signal, and output the displacement measurement value after anti-jitter processing.

2. The micron-level position adjustment and control system based on a grating according to claim 1, characterized in that, Within the characteristic frequency range of the preset displacement signal, the amplitude of each frequency component within N consecutive sampling periods is squared, and the average value of the accumulated energy is calculated to obtain the energy concentration degree. The energy concentration degree is compared with the predetermined first energy threshold, and when the energy concentration degree is greater than the first energy threshold, the frequency component is determined to be a first type of interference frequency.

3. The micron-level position adjustment and control system based on a grating according to claim 1, characterized in that, The identification of the second type of interference frequencies includes: For each frequency component within the characteristic frequency range, extract the phase value within P consecutive sampling periods to construct a first-order phase difference sequence; Calculate the phase change stability characteristics based on the first-order phase difference sequence; When the phase change stability feature exceeds the set phase change threshold, the frequency component is identified as a second type of interference frequency. The phase change stability feature is obtained by calculating the mean square error of the difference sequence.

4. The micron-level position adjustment and control system based on a grating according to claim 1, characterized in that, The intelligent optimization module uses a genetic algorithm to optimize the combination of reconstruction parameters. Within the first preset time window, the removal threshold of each interference frequency component in the initial interference set is periodically rewritten. By evaluating the cumulative difference of the current spectrum reconstruction effect, the phase compensation coefficient and the bandwidth transition width are adjusted one by one until a combination of reconstruction parameters that meets the set requirements is obtained. During the adjustment of parameter combinations during reconstruction, conditions are imposed, including: The interference frequency elimination threshold is limited to the range between the mean frequency domain energy minus the preset standard deviation and the mean frequency domain energy plus the preset standard deviation; The adjustment range of the phase compensation coefficient shall not exceed the allowable range for phase continuity; The bandwidth of the frequency band transition region is less than the upper limit of the allowed frequency response.

5. The micron-level position adjustment and control system based on a grating according to claim 4, characterized in that, After the intelligent optimization module completes the correction of the first round of reconstruction parameter combinations for the interference frequency components within the first preset time window, it compares the degree of difference between the reconstructed frequency domain distribution information collected within the second preset time window and the initial reference spectrum distribution. When the degree of difference exceeds a preset difference threshold, it triggers the correction process of the next round of reconstruction parameter combinations.

6. The micron-level position adjustment and control system based on a grating according to claim 5, characterized in that, After determining the combination of reconstruction parameters that meets the reconstruction setting requirements, the intelligent optimization module uses the combination of reconstruction parameters as the final output result and uses it to update the initial interference set. The updated initial interference set is then provided to the predictive parameter compensation in the next cycle of spectrum reconstruction.

7. The micron-level position adjustment and control system based on a grating according to claim 1, characterized in that, Amplitude suppression operations include: Calculate the difference between the maximum and minimum phase values ​​of the interference frequency components within a preset time window, and use this as the phase fluctuation amplitude; When the phase fluctuation amplitude exceeds the fluctuation amplitude threshold, nonlinear compression processing is triggered, and the amplitude of the frequency component is attenuated in the form of an exponential function. The phase compensation operation includes: constructing a phase change sequence for the phase values ​​of the interference frequency component in multiple consecutive sampling periods; calculating the phase instability characteristics based on the first-order differential fluctuation of the sequence; and injecting a phase reconstruction function into the frequency point corresponding to the interference frequency component when the phase instability characteristics exceed the phase instability threshold. The transition band smoothing process includes: constructing the transition band range of the current frequency band boundary region based on the interference frequency distribution characteristics recorded in the previous period, and dynamically adjusting the transition band width in combination with the frequency domain amplitude gradient change.

8. The micron-level position adjustment and control system based on a grating according to claim 7, characterized in that, The steps for generating the phase reconstruction function include: S401: Extract historical phase data of the current frequency point for D consecutive processing cycles from the reference spectrum, and use a first-order linear regression algorithm to generate the target phase reference trajectory that changes linearly with time. S402, calculate the phase difference between the current frequency point and the two adjacent frequency points on the left and right, and construct the slip compensation weight coefficient; S403 multiplies the deviation between the current measured phase value and the target phase reference trajectory by the slip compensation weight coefficient to generate a phase reconstruction function.

9. The micron-level position adjustment and control system based on a grating according to claim 1, characterized in that, Phase distortion correction operations include: S501, a time series model is constructed based on the historical phase change rate data in E consecutive optimization cycles at the current frequency point, which is used to output the target phase change rate prediction value; S502, obtain the actual phase change rate of the frequency point within the current optimization cycle, and calculate the deviation between the actual phase change rate and the predicted value of the target phase change rate; S503, Generate a corrected phase vector based on the deviation, and superimpose it onto the real-time phase value at the current frequency point.

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