Mover position measurement method based on the combination of absolute position and relative displacement measurement

Abstract

The present invention is applicable to the field of position measurement technology, and provides a method for measuring the position of a mover based on a combination of absolute position and relative displacement measurement. The method includes: obtaining target composite image information based on an established image displacement measurement system; aligning the target composite image information in a preset absolute position information library, and determining the absolute displacement information of the mover to be measured based on the alignment result; analyzing the relative displacement of the mover to be measured based on the absolute displacement information and the target composite image information to obtain the final position information of the mover to be measured. In the present invention, the global matching search is improved to a feature search during alignment, which greatly improves the timeliness of the measurement; the relative displacement fine measurement is added after the absolute position coarse alignment stage, so that the final measurement error only depends on the error of the fine measurement algorithm, avoiding the offset caused by the excessively large sample interval, and finally obtaining high-precision absolute position information; improving the position measurement accuracy of the mover.

Description

Technical Field

[0001] The present invention belongs to the technical field of position measurement, and in particular relates to position measurement of a linear motor mover, and specifically discloses a mover position measurement method based on a combination of absolute position and relative displacement measurement. Background Art

[0002] Permanent magnet synchronous linear motors (PMSLMs) boast a simple structure, stable operating characteristics, and a wide travel range, enabling smooth operation under a variety of complex operating conditions. Consequently, they are widely used in long-stroke, high-precision manufacturing systems, such as lithography machines, 3D printers, and CNC machine tools. In these applications, the control accuracy of the servo system directly impacts the product's machining quality, and the accuracy of the actuator position measurement is a key factor in determining servo control accuracy. Therefore, research on high-precision, long-stroke linear motor actuator position measurement algorithms is of great practical significance.

[0003] High-precision measurement of the position of long-stroke linear motor rotors currently relies mainly on laser interferometers, incremental grating position sensors, and image displacement measurement methods. Laser interferometers are expensive, susceptible to system vibration, and need to operate in a dry and clean environment. Although incremental grating position sensors have strong anti-interference capabilities, the manufacturing difficulty and cost increase significantly with the increase in measurement length. In addition, the characteristics of incremental grating position sensors cause the system's cumulative error to increase with the length of the stroke, which is especially significant when the operating temperature changes. The image displacement measurement method based on machine vision is non-contact, high-precision, and low-cost. It has low installation requirements, and its measurement cost does not increase with the increase in measurement distance. In the field of linear motor displacement measurement, the feasibility and stability of the image displacement measurement method have also been verified accordingly.

[0004] Research on image-based displacement measurement methods for linear motor displacement measurement has primarily focused on improving the performance of adjacent-frame displacement measurement. While these methods have successfully achieved accurate measurement of adjacent-frame displacements of linear motor rotors, they have failed to address the issue of cumulative error propagation during long-stroke measurements, a key factor affecting the accuracy of long-stroke linear motor displacement measurements. To address this issue, a measurement method based on sample library matching (patent application number: CN202310672462.7) was proposed. This method uses a line scan camera to scan a reference image and construct multiple sample sequences with varying sampling intervals.

[0005] However, during the measurement phase, this method requires multiple captures of the reference image and resampling of the sample library. The captured image is then compared with the resampled sample sequence to obtain the final measurement result. The sample library is large, and matching the captured image with all the information in the library would severely impact the measurement system's speed. Furthermore, as the stroke length increases, the algorithm's time consumption also increases, making it difficult to achieve the real-time position feedback required for linear motor actuators. Therefore, improvements are necessary. Summary of the Invention

[0006] The purpose of the present invention is to provide a mover position measurement method based on the combination of absolute position and relative displacement measurement, aiming to further improve the measurement accuracy and feedback real-time performance of existing digital image measurement methods.

[0007] The present invention is implemented as follows: a method for measuring the position of a mover based on a combination of absolute position and relative displacement measurement, the method comprising the following steps:

[0008] Based on the established image displacement measurement system, obtain target composite image information;

[0009] Registering the target composite image information in a preset absolute position information library, and determining the absolute displacement information of the mover to be measured based on the registration result; searching the absolute position information library using a fast search strategy based on the main peak of the correlation coefficient during the registration;

[0010] The relative displacement of the mover to be measured is analyzed according to the absolute displacement information and the target composite image information to obtain the final position information of the mover to be measured.

[0011] The present invention provides a mover position measurement method based on the combination of absolute position and relative displacement measurement. The image displacement measurement system in the method includes a composite image that is spliced ​​based on a non-periodic sinusoidal fence image and a periodic sinusoidal fringe image. When the present invention measures the mover position, the linear motor displacement is quickly and roughly aligned based on the non-periodic sinusoidal fence image in the acquired target composite image information, so that the absolute position information of the mover displacement can be obtained. Thereafter, the relative displacement is accurately calculated based on the periodic sinusoidal fringe image in the target composite image information. Finally, high-precision absolute position information of the mover is obtained, realizing accurate measurement of the global high-resolution displacement of the motor.

[0012] The present invention performs precise measurement of relative displacement after rough absolute position alignment. In this way, the final measurement error only depends on the error of the precise measurement algorithm, avoiding the offset caused by excessive sample spacing, and ultimately obtaining high-precision absolute position information, which can effectively improve the accuracy of position measurement. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1A flow chart of a method for measuring the position of a mover based on a combination of absolute position and relative displacement measurement provided by an embodiment of the present invention;

[0014] Figure 2 A flow chart showing the principle of a method for measuring the position of a mover based on a combination of absolute position and relative displacement measurement according to an embodiment of the present invention;

[0015] Figure 3 is an example of a composite image in an embodiment of the present invention;

[0016] Figure 4 A diagram illustrating an application environment of a mover position measurement method based on a combination of absolute position and relative displacement measurement provided by an embodiment of the present invention;

[0017] Figure 5 This is a flowchart of building an absolute position information database in an embodiment of the present invention;

[0018] Figure 6 A trend curve diagram of the correlation coefficient between the captured signal and the absolute position information library signal in an embodiment of the present invention;

[0019] Figure 7 This is a flow chart of a fast search strategy for an absolute position information database based on a main peak of a correlation coefficient in an embodiment of the present invention;

[0020] In the figure: 10 - mover; 11 - camera; 12 - composite image; 13 - guide rail. DETAILED DESCRIPTION

[0021] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0022] Glossary:

[0023] A permanent magnet synchronous linear motor (PMSLM) applies the rotary motion principle of a permanent magnet synchronous motor to linear motion. Its basic structure consists of a stator (typically containing electromagnetic coils) and a mover (moving element) mounted with permanent magnets. Unlike traditional rotary motors, PMSLMs generate linear motion directly, eliminating the need for mechanical transmission devices (such as gears or belts) to convert rotary motion into linear motion, thereby improving efficiency and precision.

[0024] Image stitching technology based on SIFT (Scale-Invariant Feature Transform): First, the SIFT algorithm is used to detect a series of scale- and rotation-invariant keypoints in the two images. A descriptor is calculated for each detected keypoint, typically by analyzing the gradient information of the surrounding area. Descriptors are high-dimensional vectors that effectively represent the local image information of the feature point. By comparing the descriptors of the keypoints in the two images, matching pairs of feature points are found. Using these matching pairs of feature points, algorithms such as the least squares method are used to estimate the geometric transformation matrix between the images to achieve image alignment. Based on the estimated transformation matrix, the two images are transformed and fused to eliminate the seams and produce a seamlessly stitched image.

[0025] Fourier shift theorem: It describes the effect of signal shift in the frequency domain. According to this theorem, a signal shift in the time domain is equivalent to a phase shift of the corresponding frequency in the frequency domain. Specifically, if the signal Shifted in time domain ,Right now , whose Fourier transform will be multiplied by a phase factor This means that the purpose of image translation in the spatial domain can be achieved by changing the phase factor in the frequency domain. This method is more accurate and stable than direct translation in the spatial domain.

[0026] Time phase analysis method of full phase Fourier transform (Apfft-Tpa): It is a method that extends the traditional Fourier transform and aims to simultaneously retain the amplitude and phase information of the signal or image. The traditional Fourier transform only focuses on the amplitude spectrum in the frequency domain and ignores the phase information. However, phase information is very important for signal reconstruction and image details. The loss of phase information usually leads to signal distortion of the image, especially when processing complex signals. The core idea of ​​the full phase Fourier transform is to retain the complete phase information of each frequency component in the frequency domain. By performing Fourier transform on the signal, a complex number representation in the frequency domain is obtained, where the amplitude and phase are the modulus and argument of the complex number, which can more accurately represent the structure and details of the signal.

[0027] Figure 1 A flow chart of a method for measuring the position of a mover based on a combination of absolute position and relative displacement measurement provided by an embodiment of the present invention; Figure 2 A flow chart showing the principle of a method for measuring the position of a mover based on a combination of absolute position and relative displacement measurement according to an embodiment of the present invention; Figure 3 is an example of a composite image in an embodiment of the present invention; Figure 4 A diagram illustrating the application environment of the mover position measurement method based on the combination of absolute position and relative displacement measurement provided by an embodiment of the present invention.

[0028] In one embodiment, a method for measuring the position of a mover based on a combination of absolute position and relative displacement measurement is proposed, which may specifically include the following steps S101 to S103;

[0029] Step S101: acquiring target composite image information based on the established image displacement measurement system;

[0030] Among them, the image displacement measurement system includes a camera 11 and a computer system. The stator of the permanent magnet synchronous linear motor is installed on an operating table, and the mover 10 cooperating with the stator is installed on the guide rail 13 at the top of the stator and can be driven by the magnetic induction of the stator to perform linear motion on the guide rail 13; the camera 11 is installed on the mover 10, and the composite image 12 is set on the operating table along the length direction of the guide rail 13, and the camera 11 can focus on the composite image 12 to collect the target composite image for the computer system to obtain the target composite image information.

[0031] In this embodiment, a camera 11 is fixed to the mover 10 and follows the mover 10 to capture a composite image 12 fixed to the operating table in real time. The captured sequence of image signals is transmitted to a computer system to obtain the target composite image information, which is analyzed by the computer system to obtain the actual displacement of the mover.

[0032] In this embodiment, the method of this embodiment further includes: generating a composite image to facilitate building an image displacement measurement system;

[0033] The composite image includes a periodic sinusoidal fringe image and a non-periodic sinusoidal fence image spliced ​​together from top to bottom; wherein the generation of the periodic sinusoidal fringe image is configured as follows:

[0034] (1),

[0035] in, is the light intensity, is the signal amplitude, is a set of signal sequences, is a sine period, is the initial phase;

[0036] Based on the generation of the periodic sinusoidal fringe image, different and , a non-periodic sinusoidal fence image is generated.

[0037] Of course, speckle images, fence images, and other non-periodic fence images may also be used in the composite image.

[0038] Step S102, registering the target composite image information in a preset absolute position information library, determining the absolute displacement information of the moving element to be measured based on the registration result, and achieving coarse registration; during the registration, a fast search strategy based on the main peak of the correlation coefficient is used to search the absolute position information library;

[0039] Step S103 , analyzing the relative displacement of the mover to be measured according to the absolute displacement information and the target composite image information, that is, achieving precise measurement to obtain final position information of the mover to be measured.

[0040] like Figure 5 As shown, in this embodiment, the preset of the absolute position information library in step S102 specifically includes:

[0041] Based on the image displacement measurement system, the adjacent segments of the non-periodic sinusoidal fence image are obtained by collecting the composite image with a camera;

[0042] To ensure the stitching quality, the overlap between adjacent image segments should be greater than 30%.

[0043] Adjacent segments are stitched together using a scale-invariant feature transform (SIFT)-based image stitching method to form a complete full-stroke aperiodic sinusoidal fence image.

[0044] Using the Fourier translation method, the full-stroke aperiodic sinusoidal fence image is translated at equal intervals until the total translation displacement reaches the length of the full-stroke aperiodic sinusoidal fence image;

[0045] Cut out a section of each shifted image according to the preset shooting length;

[0046] Among them, the preset shooting length is the shooting length of the camera, and the appropriate length can be flexibly selected for different cameras.

[0047] Each image is sampled single-line, and a line of grayscale image signal is extracted from it, which is recorded as signal g(u); these grayscale image signals (XI, XII, etc.) constitute the absolute position information library containing the displacement of the mover.

[0048] In this embodiment, the step of registering the target composite image information in a preset absolute position information library and determining the absolute displacement information of the mover to be measured according to the registration result specifically includes:

[0049] Capturing the acquired target composite image information to obtain a non-periodic sinusoidal fence image;

[0050] Perform single-line sampling on the non-periodic sinusoidal fence image to obtain a signal to be matched, which is recorded as signal h(u);

[0051] Perform correlation matching between the signal h(u) and the signal g(u) in the absolute position information library to obtain the correlation coefficient R between the two signals;

[0052] Determine whether to match based on the correlation coefficient R and output the registration result;

[0053] The absolute displacement information of the mover to be measured is determined according to the alignment results.

[0054] like Figure 6 As shown, in this embodiment, the signal h(u) is matched one by one with the signal g(u) in the absolute position information library, and the change trend of the correlation coefficient R can be obtained;

[0055] It can be seen from this that when the displacement deviation of the signal h(u) and the signal g(u) approaches 0, the main peak of the correlation coefficient R gradually approaches 1.

[0056] In this embodiment, the correlation coefficient R of this embodiment can be calculated using a standardized covariance cross-correlation function, satisfying:

[0057] (2),

[0058] in, To capture the mean value of the image signal, is the mean value of the signal in the absolute position information database.

[0059] The absolute displacement of the mover in this embodiment can be expressed as ;

[0060] (3);

[0061] in, is the image number with the largest correlation coefficient in the absolute position information library, is the displacement interval for building the absolute position information database.

[0062] In this embodiment, in the step of determining whether to register according to the correlation coefficient R and outputting the registration result,

[0063] When the displacement deviation of signal h(u) and signal g(u) approaches 0, the main peak of the correlation coefficient R gradually approaches 1. Figure 6 ; At this time, the position information corresponding to the signal g(u) is the absolute displacement of the mover, that is, ;

[0064] Since the image signal data in the absolute position information library is huge, under the high-frequency feedback requirements of high-speed cameras, the search method of determining the absolute position information by enumeration is difficult to meet the real-time requirements of measurement.

[0065] Therefore, in the step of performing correlation matching between the signal h(u) and the signal g(u) in the absolute position information library, a fast search strategy based on the main peak of the correlation coefficient is adopted for correlation matching.

[0066] Correlation coefficient variation: Because motor displacement changes continuously, the current actuator displacement is always close to the previous actuator displacement. Therefore, for the deviation corresponding to the displacement signal captured at the previous moment, the current displacement deviation will always be near the main peak of the correlation coefficient. Accordingly, the correlation coefficient between the current displacement signal and the previous displacement signal will always fall near the main peak of the correlation coefficient.

[0067] like Figure 7 As shown, in this embodiment, the fast search strategy based on the main peak of the correlation coefficient is configured as follows:

[0068] Record the position n of the mover in the absolute position information database at the last moment;

[0069] Compare the correlation coefficient R at this moment n and R n+1 The size of ,determines the matching direction;

[0070] Continue signal matching in the direction of increasing correlation coefficient R until the correlation coefficient R stops increasing.

[0071] Search for the position n of the signal corresponding to the maximum correlation coefficient R Rmax ;

[0072] The position n where the correlation coefficient R is the largest Rmax The corresponding position is the absolute position of the mover, and the absolute displacement of the mover at this moment can be calculated.

[0073] In this embodiment, after determining the absolute displacement of the mover at the current moment Afterwards, we can calculate The sinusoidal signal corresponding to the initial phase is recorded as ;satisfy:

[0074] (4);

[0075] in, is the light intensity, is the signal amplitude, is the width of the sinusoidal fringe;

[0076] Then, the phase difference between the periodic sinusoidal fringe portion in the captured image and the sinusoidal signal is calculated; that is, the phase difference between the periodic sinusoidal fringe image information in the acquired target composite image and the sinusoidal signal is calculated.

[0077] In this embodiment, considering the one-dimensional linear motion of the permanent magnet synchronous linear motor, the two signals should satisfy the following relationship:

[0078] (5);

[0079] in, is the pixel displacement between the two signals. Equation (4) can be rewritten as:

[0080] (6);

[0081] Therefore, the displacement between the signals for:

[0082] (7);

[0083] in, is the phase difference.

[0084] In this embodiment, if the Fourier transform method is used to calculate the phase, when the signal is non-integer periodic, spectrum leakage will occur, which may affect the accurate calculation of the phase angle. In order to suppress spectrum leakage, this embodiment is improved to use full-phase Fourier transform to calculate the phase angle. Assuming that the signal length is pixels, the signal can be rewritten as a complex exponential signal, that is ;

[0085] (8);

[0086] in, are the Fourier transform coefficients, is the phase angle.

[0087] In order to obtain full-phase pre-processed data of N points, the data of length (2N-1) is sampled to satisfy:

[0088] (9);

[0089] ( ) length is divided into segments of length N. Data Matrix The central sampling data of formula (9) arrive All cutoffs of are given;

[0090] (10);

[0091] The elements of each row are shifted cyclically until the center data Moved to the first position in each line;

[0092] From formula (10), we can see that the matrix The row vectors in are averaged to form a new Length data vector ,

[0093] (11);

[0094] The phase angle can then be calculated using the inverse tangent function:

[0095] (12);

[0096] In this way, spectrum leakage can be effectively suppressed and the phase information of the signal can be corrected, achieving precise subdivision of motor displacement measurement.

[0097] In this embodiment, in the step of analyzing the relative displacement of the mover to be measured according to the absolute displacement information and the target composite image information to obtain the final position information of the mover to be measured, the analysis algorithm used to analyze the relative displacement of the mover to be measured is the Apfft-Tpa algorithm.

[0098] In this embodiment, in order to improve the measurement robustness of the Apfft-Tpa algorithm under different working conditions, the Levenberg-Marquardt (LM) algorithm in the least squares parameter optimization algorithm is used to correct the collected sinusoidal signal, that is, the least squares sinusoidal fitting, to obtain an improved Apfft-Tpa algorithm. Specifically,

[0099] First, define the error square sum objective function S;

[0100] (13);

[0101] Where N is the number of data points, is the sinusoidal signal read, 、 、 、 is the parameter to be optimized. For nonlinear optimization, the LM algorithm can be used to calculate the Jacobian matrix and find the partial derivative of each parameter in the objective function S, that is:

[0102] (14);

[0103] in , For the parameters to be optimized, use the following update formula to iteratively solve the parameters:

[0104] (15);

[0105] in, is the damping factor, which controls the update step size;

[0106] Finally, the improved Apfft-Tpa algorithm is obtained.

[0107] This embodiment uses a fast search strategy based on the main peak of the correlation coefficient to quickly search and match the absolute position information library, so that the position of the mover can be quickly estimated, which greatly improves the real-time performance of the position feedback. The least squares sine fitting is used to improve the robustness of the method of this embodiment under different working conditions, making this method still applicable in the more complex motion mode of the motor's variable speed reciprocating motion.

[0108] The above-mentioned method for measuring the position of a mover is based on a combination of absolute position and relative displacement measurements. During the establishment of the absolute position information library, the image displacement measurement system first captures the target image in segments, then reconstructs the non-periodic sinusoidal fence image of the motor's full stroke, and finally, establishes the absolute position information library of the motor at certain displacement intervals. In real-time displacement measurement, the camera first follows the mover to capture a composite image of the target in real time (i.e., the real-time acquisition sequence of images in the figure). The non-periodic sinusoidal fence image at each moment (which can also be considered an image signal) is then searched and matched in the absolute position information library to determine the initial absolute position of the mover. Next, the improved Apfft-Tpa algorithm is used to calculate the phase difference between the periodic sinusoidal fringe information at each moment and the periodic sinusoidal signal corresponding to the absolute position to determine the relative displacement, thereby obtaining high-precision absolute position information.

[0109] Among them, when determining the relative displacement, each measurement is independent of the previous measurement, and the measurement error of the mover position depends only on the calculation error of the relative displacement, achieving the goal of eliminating cumulative errors and realizing accurate mover displacement measurement.

[0110] In one example of this embodiment, the camera can be a linear array CCD or other high-speed camera. The linear array CCD scans two images at adjacent moments at a certain time interval, respectively, I0 and I1, and the size of both images is M×1. The linear array CCD effectively reduces the redundancy of image information, converts two-dimensional image information into one-dimensional signals, and improves measurement efficiency.

[0111] The embodiment of the present invention provides a method for measuring the position of a mover based on a combination of absolute position and relative displacement measurement. It is possible to first establish a composite image based on a non-periodic sinusoidal fence image and a periodic sinusoidal fringe image, and use the composite image as the target image to establish an image displacement measurement system for a linear motor. Secondly, based on the composite image, an absolute position information library is established offline. Thirdly, for signal matching in the absolute position information library, the mover displacement can be roughly aligned by setting a fast search strategy to obtain the absolute position information of the mover displacement. Finally, based on the periodic sinusoidal fringe image, a high-precision adjacent frame displacement measurement method is introduced, that is, the improved Apfft-Tpa algorithm is used to accurately calculate the relative displacement; ultimately, high-precision absolute position information is obtained, and accurate measurement of the mover displacement is achieved.

[0112] It should be understood that, although the various steps in the flow chart of each embodiment of the present invention are shown in sequence according to the indication of the arrows, these steps are not necessarily performed in sequence according to the order indicated by the arrows. Unless otherwise specified herein, the execution of these steps is not strictly limited in order, and these steps can be performed in other orders. Moreover, at least a portion of the steps in each embodiment may include a plurality of sub-steps or a plurality of stages, and these sub-steps or stages are not necessarily performed at the same time, but can be performed at different times, and the execution order of these sub-steps or stages is not necessarily performed in sequence, but can be performed in turn or alternately with at least a portion of other steps or sub-steps or stages of other steps.

[0113] The above-described embodiments merely illustrate several implementations of the present invention, and while their descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art would be able to make numerous variations and improvements without departing from the spirit of the present invention, all of which fall within the scope of protection of the present invention. Therefore, the scope of protection of the present invention shall be determined by the appended claims.

[0114] 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 and improvements made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for measuring the position of a mover based on a combination of absolute position and relative displacement measurement, characterized in that: The method comprises: Based on the established image displacement measurement system, obtain target composite image information; Registering the target composite image information in a preset absolute position information library, and determining the absolute displacement information of the mover to be measured based on the registration result; searching the absolute position information library using a fast search strategy based on the main peak of the correlation coefficient during the registration; Analyze the relative displacement of the mover to be measured according to the absolute displacement information and the target composite image information to obtain final position information of the mover to be measured; The method further includes: generating a composite image to facilitate building the image displacement measurement system; The composite image includes a periodic sinusoidal fringe image and a non-periodic sinusoidal fence image spliced ​​together from top to bottom; wherein the generation of the periodic sinusoidal fringe image is configured as follows: , in, is the light intensity, is the signal amplitude, is a set of signal sequences, is a sine cycle, is the initial phase; Based on the generation of the periodic sinusoidal fringe image, different and , then a non-periodic sinusoidal fence image is generated; The step of registering the target composite image information in a preset absolute position information library and determining the absolute displacement information of the mover to be measured according to the registration result specifically includes: Capturing the acquired target composite image information to obtain a non-periodic sinusoidal fence image; Perform single-line sampling on the non-periodic sinusoidal fence image to obtain a signal to be matched, which is recorded as signal h(u); Perform correlation matching between the signal h(u) and the signal g(u) in the absolute position information library to obtain the correlation coefficient R between the two signals; Determine whether to match based on the correlation coefficient R and output the registration result; Determine the absolute displacement information of the mover to be measured according to the registration result; The fast search strategy based on the main peak of the correlation coefficient is configured as follows: Record the position n of the mover in the absolute position information database at the last moment; Compare the correlation coefficient R at this moment n and R n+1 The size of ,determines the matching direction; Continue signal matching in the direction of increasing correlation coefficient R until the correlation coefficient R stops increasing. Search for the position n of the signal corresponding to the maximum correlation coefficient R Rmax ; Calculate the absolute displacement of the mover at this moment; The improved Apfft-Tpa algorithm is used to calculate the phase difference between the periodic sinusoidal fringe information at each moment and the periodic sinusoidal signal corresponding to the absolute position to determine the relative displacement.

2. The method according to claim 1, characterized in that The preset of the absolute position information library specifically includes: Based on the image displacement measurement system, adjacent segments of the non-periodic sinusoidal fence image are obtained; Adjacent segments are stitched together using an image stitching method based on scale-invariant feature transformation to form a complete full-stroke aperiodic sinusoidal fence image. The full-stroke non-periodic sinusoidal fence image is translated at equal intervals until the total translation displacement reaches the length of the full-stroke non-periodic sinusoidal fence image; Cut out a section of each shifted image according to the preset shooting length; Single-line sampling is performed on each image, and a line of grayscale image signal is extracted from it, which is recorded as signal g(u); these grayscale image signals constitute the absolute position information library containing the displacement of the mover.

3. The method according to claim 2, characterized in that The correlation coefficient R is calculated using the standardized covariance cross-correlation function, satisfying: ， in, To capture the mean value of the image signal, is the mean value of the signal in the absolute position information database.

4. The method according to claim 2, characterized in that In the step of determining whether to register based on the correlation coefficient R and outputting the registration result, When the displacement deviation of the signal h(u) and the signal g(u) approaches 0, the main peak of the correlation coefficient R gradually approaches 1. At this time, the position information corresponding to the signal g(u) is the absolute displacement of the mover. Therefore, in the step of performing correlation matching between the signal h(u) and the signal g(u) in the absolute position information library, a fast search strategy based on the main peak of the correlation coefficient is adopted for correlation matching.

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