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

Abstract

The invention is suitable for the technical field of position measurement, and provides a rotor position measurement method based on combination of absolute position and relative displacement measurement, and the method comprises the steps: obtaining target composite image information based on a built image displacement measurement system; registering the target composite image information in a preset absolute position information base, and determining absolute displacement information of the rotor to be detected according to a registration result; and analyzing the relative displacement of the rotor to be measured according to the absolute displacement information and the target composite image information so as to obtain the final position information of the rotor to be measured. According to the method, global matching search is improved into feature search during registration, so that the timeliness of measurement is greatly improved; relative displacement fine measurement is added after an absolute position coarse registration stage, so that a final measurement error only depends on an error of a fine measurement algorithm, deviation caused by an overlarge sample interval is avoided, and finally high-precision absolute position information is obtained. And the position measurement precision of the rotor is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of position measurement, and in particular relates to the 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 motor (PMSLM) has a simple structure and stable operating characteristics, and has a large travel range, and can achieve smooth operation under a variety of complex working conditions. Therefore, they are widely used in long-stroke and 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 affects the processing quality of the product, and the accuracy of the position measurement of the actuator is the key factor in determining the accuracy of the servo control. Therefore, it is of great practical significance to carry out research on the position measurement algorithm of the actuator of a high-precision long-stroke linear motor.

[0003] The high-precision measurement of the position of the rotor of a long-stroke linear motor currently relies mainly on laser interferometers, incremental grating position sensors, and image displacement measurement methods. Laser interferometers are expensive, easily affected by 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 cumulative error to increase with the increase in stroke, especially when the operating temperature changes. The image displacement measurement method based on machine vision has the characteristics of non-contact, high precision, and low cost, with 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] The research on image displacement measurement methods in the field of linear motor displacement measurement mainly focuses on the performance improvement of adjacent frame displacement measurement, and successfully realizes the accurate measurement of adjacent frame displacement of linear motor movers, but fails to consider the transmission problem of cumulative error in long-stroke measurement, and cumulative error is the key factor affecting the displacement measurement accuracy of long-stroke linear motors. In this regard, a measurement method based on sample library matching is provided (patent application number: CN202310672462.7), which scans the reference image with a line scan camera and constructs multiple groups of sample sequences with different sampling intervals.

[0005] However, in the measurement phase, this method requires multiple captures of the reference image and resampling of the sample library. The captured image is compared with the resampled sample sequence to obtain the measurement result. During the comparison, the number of sample library images is huge. If the captured image is matched with all the information in the library, the rapidity of the measurement system will be seriously affected. As the stroke increases, the algorithm time consumption will also increase, making it difficult to meet the real-time requirements of the linear motor mover position feedback. 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 the target composite image information;

[0009] The target composite image information is registered in a preset absolute position information library, and the absolute displacement information of the moving element to be measured is determined according to the registration result; 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;

[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 method for measuring the position of a mover based on the combination of absolute position and relative displacement measurement. The image displacement measurement system in the method comprises a composite image formed by splicing a non-periodic sinusoidal fence image and a periodic sinusoidal fringe image. When the present invention measures the position of the mover, the linear motor displacement is quickly and roughly aligned according to the non-periodic sinusoidal fence image in the acquired target composite image information, so as to obtain the absolute position information of the mover displacement. Afterwards, the relative displacement is accurately calculated based on the periodic sinusoidal fringe image in the target composite image information. Finally, the high-precision absolute position information of the mover is obtained, so as to realize 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, so that the final measurement error only depends on the error of the precise measurement algorithm, avoiding the offset caused by excessive sample intervals, and finally 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 a mover position based on a combination of absolute position and relative displacement measurement provided by an embodiment of the present invention;

[0014] Figure 2 A principle flow chart of a mover position measurement method based on a combination of absolute position and relative displacement measurement provided in 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 An application environment diagram 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 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 library 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 solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with 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] Permanent magnet synchronous linear motor (PMSLM): is a motor that applies the rotary motion principle of permanent magnet synchronous motor to linear motion. Its basic structure includes a stator (usually the part containing electromagnetic coils) and a mover (moving part) equipped with permanent magnets. Unlike traditional rotary motors, permanent magnet synchronous linear motors directly generate linear motion, eliminating the mechanical transmission device (such as gears or belts) that converts rotary motion into linear motion, thereby improving efficiency and precision.

[0024] Image stitching technology based on SIFT (Scale-Invariant Feature Transform): First, use the SIFT algorithm to detect a series of key points with scale and rotation invariance in the two images. A descriptor is calculated for each detected key point, usually obtained by analyzing the gradient information of the surrounding area. The descriptor is a high-dimensional vector that can effectively characterize the local image information of the feature point. By comparing the descriptors of the key points in each of the two images, matching feature point pairs are found. Using the matching feature point pairs, the geometric transformation matrix between the images is estimated through algorithms such as the least squares method to achieve image alignment. According to the estimated transformation matrix, the two images are transformed and fused to eliminate the seams and generate a seamlessly stitched image.

[0025] Fourier shift theorem: It describes the effect of signal shift in the frequency domain. According to this theorem, a shift of a signal in the time domain is equivalent to a phase change of the corresponding frequency in the frequency domain. Specifically, if a signal f(t) is shifted by t0 in the time domain, i.e. f(t-t0), its Fourier transform F(w) 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, aiming to simultaneously retain the amplitude information 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. 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 radian 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 a mover position based on a combination of absolute position and relative displacement measurement provided by an embodiment of the present invention; Figure 2 A principle flow chart of a mover position measurement method based on a combination of absolute position and relative displacement measurement provided in 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 of the application environment of the mover position measurement method based on the combination of absolute position and relative displacement measurement provided in 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, obtaining 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 matched with the stator is installed on the guide rail 13 on 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 so that the computer system can obtain the target composite image information.

[0031] In this embodiment, the camera 11 is fixed on the mover 10, and follows the mover 10 to shoot the composite image 12 fixed on the operating table in real time. The collected sequence image signals are transmitted to the computer system to obtain the target composite image information, and the actual displacement of the mover is obtained by analysis through the computer system.

[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 ​​up and down; wherein the generation of the periodic sinusoidal fringe image is configured as follows:

[0034] I (i) =A+B*cos((2*π*x (i) ) / T+β) (1),

[0035] Where A is the light intensity, B is the signal amplitude, x(i) is a set of signal sequences, T is the sine period, and β is the initial phase;

[0036] Based on the generation of the periodic sinusoidal fringe image, different T and β are set to generate a non-periodic sinusoidal fence image.

[0037] Of course, speckle images, fence images and other non-periodic fence images can 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 according to the registration result, and realizing rough 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 the 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 overlapping parts of 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 non-periodic sinusoidal fence image.

[0044] Using the Fourier translation method, 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;

[0045] Cut out a section of each translated 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] 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 (XI, XII, etc.) constitute an 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] The acquired target composite image information is captured 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] Correlation matching is performed 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 matching 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]

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

[0059] In this embodiment, the absolute displacement of the mover can be expressed as X1;

[0060] X1=n Rmax *Δx d (3);

[0061] Among them, n Rmax is the image number with the largest correlation coefficient in the absolute position information library, Δx d 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, X1;

[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 that determines 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 used for correlation matching.

[0066] Change rule of correlation coefficient: Since the motor displacement changes continuously, the displacement of the mover at the current moment must be close to the displacement of the mover at the previous moment. Therefore, for the deviation corresponding to the displacement signal captured at the previous moment, its displacement deviation at the current moment must be near the main peak of the correlation coefficient. Correspondingly, the correlation coefficient between the displacement signal captured at the current moment and the displacement signal at the previous moment must 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 of this embodiment 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 X1 of the mover at the current moment, the sinusoidal signal with the initial phase corresponding to X1 can be calculated, which is recorded as I a (x); Satisfy:

[0074]

[0075] Among them, a is the light intensity, b is the signal amplitude, and w is the width of the sinusoidal fringe;

[0076] The phase difference between the periodic sinusoidal fringe part in the captured image and the sinusoidal signal is then 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] I b (x) = I a (x+Δx)(5);

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

[0080]

[0081] Therefore, the displacement Δx(t) between the signals is:

[0082]

[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 N pixels, the signal can be rewritten as a complex exponential signal, that is, xx(n);

[0085]

[0086] Where f0 is the Fourier transform coefficient, is the phase angle.

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

[0088] Γ=[xx(-N+1),…,xx(0),…,xx(N-1)] (9);

[0089] The data of (2N-1) length is divided into N segments of length N. The N*N data matrix D is given by all truncations of the central sampled data xx(0) to xx(12) in equation (9);

[0090]

[0091] The elements of each row are circularly shifted until the central data xx(0) is moved to the first position of each row;

[0092] From formula (10), we can see that we can form a new N-length data vector XX by averaging the row vectors in the matrix D. ap ,

[0093]

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

[0095]

[0096] In this way, spectrum leakage can be effectively suppressed and the phase information of the signal can be corrected, thereby 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]

[0101] Where N is the number of data points, y i is the read sinusoidal signal, A, w, φ, B are the parameters to be optimized. For nonlinear optimization, the LM algorithm can be used to calculate the Jacobian matrix, and the partial derivative of each parameter in the objective function S is obtained, that is:

[0102]

[0103] where r i =y i -(Asin(wx i +φ)+B),θ j For the parameters to be optimized, use the following update formula to iteratively solve the parameters:

[0104] θ new =θ old +(J T J+λI) -1 J T r(15);

[0105] Among them, λ is the damping factor, which can control 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 method of this embodiment is improved in robustness under different working conditions through least squares sinusoidal fitting, making this method still applicable in more complex motion modes of motor speed reciprocating.

[0108] The above is a method for measuring the position of a mover based on the combination of absolute position and relative displacement measurement; in the process of establishing the absolute position information library, first, the image displacement measurement system collects the target image in segments, and then reconstructs the non-periodic sinusoidal fence image of the motor's full stroke, and finally, the absolute position information library of the motor is established according to a certain displacement interval. In real-time displacement measurement, first, the camera follows the mover to collect the target composite image in real time (that is, the real-time collection sequence image in the figure). Then, the non-periodic sinusoidal fence image at each moment (which can also be regarded as an image signal) is 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, that is, to obtain 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, thereby achieving the goal of eliminating cumulative errors and realizing accurate mover displacement measurement.

[0110] In an example of this embodiment, the camera can be a linear array CCD or other high-speed cameras. The linear array CCD scans two images at adjacent moments at a certain time interval, which are I0 and I1, respectively, and the size of the two 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 method for measuring the position of the mover based on the combination of absolute position and relative displacement measurement provided by the embodiment of the present invention can 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 the linear motor. Secondly, based on the composite image, an absolute position information library is established offline. Thirdly, for the signal matching of the absolute position information library, the mover displacement can be roughly aligned through the set 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; finally, high-precision absolute position information is obtained to achieve accurate measurement of the mover displacement.

[0112] It should be understood that, although each step in the flow chart of each embodiment of the present invention is shown in sequence according to the indication of the arrow, these steps are not necessarily performed in sequence according to the order indicated by the arrow. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, 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-mentioned embodiments only express several implementation methods of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the patent of the present invention. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached 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 protection scope of the present invention.

Claims

1. A method for measuring the position of a mover based on the combination of absolute position and relative displacement measurement, characterized in that: The method comprises: Based on the established image displacement measurement system, obtain the target composite image information; The target composite image information is registered in a preset absolute position information library, and the absolute displacement information of the moving element to be measured is determined according to the registration result; 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; 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.

2. The method according to claim 1, characterized in that 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 ​​up and down; wherein the generation of the periodic sinusoidal fringe image is configured as follows: I (i) =A+B*cos((2*π*x (i) ) / T+β), Where A is the light intensity, B is the signal amplitude, x(i) is a set of signal sequences, T is the sine period, and β is the initial phase; Based on the generation of the periodic sinusoidal fringe image, different T and β are set to generate a non-periodic sinusoidal fence image.

3. The method according to claim 2, 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 non-periodic 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 translated 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 an absolute position information library containing the displacement of the mover.

4. The method according to claim 3, characterized in that 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: The acquired target composite image information is captured 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); Correlation matching is performed 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 matching result; The absolute displacement information of the mover to be measured is determined according to the alignment results.

5. The method according to claim 4, characterized in that The correlation coefficient R is calculated using a 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 library.

6. The method according to claim 4, characterized in that In the step of determining whether to align based on the correlation coefficient R and outputting the alignment 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 used for correlation matching.

7. The method according to claim 6, characterized in that 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.

8. The method according to claim 7, characterized in that 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.

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