Multi-axis displacement platform temperature compensation method and system

Abstract

The invention belongs to the technical field of mechanical temperature compensation, and provides a multi-axis displacement platform temperature compensation method and system, and the method comprises the steps: obtaining the temperature data of each axis segment monitoring point when a multi-axis displacement platform is not operated, and carrying out the deviation analysis of the temperature of each axis segment monitoring point, preliminarily identifying a suspected high-risk area in the shaft section of the multi-shaft displacement platform; the multi-axis displacement platform is started, a monitoring time period is preset, suspected high-risk areas in the multi-axis displacement platform are monitored in real time, the temperature gradient change rate is analyzed, and high-risk areas in the suspected high-risk areas are recognized; according to the determined high-risk area, carrying out combinatorial analysis on the risk degree of the high-risk area between the shaft sections in the multi-shaft displacement platform in combination with the distance between the shaft sections; according to the invention, through combination of the shaft segment spacing, the temperature gradient value and the temperature gradient change rate similarity during combinatorial analysis, the thermal management efficiency is improved, and the compensation cost and energy consumption are reduced.

Description

Technical Field

[0001] The present invention belongs to the technical field of mechanical temperature compensation, and in particular relates to a temperature compensation method and system for a multi-axis displacement platform. Background Art

[0002] Multi-axis displacement platforms have extremely high requirements for temperature stability in scenarios such as precision machining and semiconductor manufacturing. However, during operation, they are prone to local temperature rise due to factors such as friction and motor heating, resulting in uneven thermal expansion of the axis segments, reduced motion accuracy, and even mechanical failure.

[0003] However, there are some defects and shortcomings in the existing technology. On the one hand, traditional methods mostly rely on static temperature measurements or single dynamic thresholds when the equipment is shut down, lack dynamic tracking of the temperature gradient change rate, and find it difficult to capture early thermal anomalies. On the other hand, the existing technology cannot integrate the frequency and intensity of risk occurrence, and the compensation area combination is only based on manual experience or spatial distance, without considering the similarity of risk values, which often leads to redundant compensation.

[0004] To this end, the present invention provides a temperature compensation method and system for a multi-axis displacement platform. Summary of the Invention

[0005] In order to make up for the deficiencies of the prior art, at least one technical problem raised in the background technology is solved.

[0006] In a first aspect, the present invention provides a temperature compensation method for a multi-axis displacement platform, comprising:

[0007] Obtain temperature data from monitoring points on each axis section of the multi-axis displacement platform when it is not in operation. The temperature data includes temperature. By performing deviation analysis on the temperature of each axis section monitoring point, preliminarily identify suspected high-risk areas in the axis section of the multi-axis displacement platform.

[0008] Start the multi-axis displacement platform, preset the monitoring period, monitor the suspected high-risk areas in the multi-axis displacement platform in real time, analyze the temperature gradient change rate of the suspected high-risk areas during operation, and identify the high-risk areas in the suspected high-risk areas;

[0009] According to the determined high-risk areas, a combined analysis is performed on the risk degree of the high-risk areas between the axis segments in the multi-axis displacement platform, combined with the distance between the axis segments, to determine whether the high-risk areas should be merged for temperature compensation.

[0010] As a further solution of the present invention, the specific process of preliminarily identifying suspected high-risk areas in the shaft segments of the multi-axis displacement platform is as follows:

[0011] In a multi-axis displacement platform, monitoring points are evenly set at the same distance along the axial direction. Based on any axis segment, the temperature between two adjacent monitoring points is subtracted and then ratioed with the distance between the adjacent monitoring points to obtain the temperature gradient of the adjacent monitoring points.

[0012] If the temperature gradient between adjacent monitoring points is greater than or equal to the temperature gradient threshold, the corresponding area between the adjacent monitoring points will be recorded as a suspected high-risk area.

[0013] As a further solution of the present invention: the specific process of identifying the high-risk area among the suspected high-risk areas is:

[0014] Extract all high-risk areas in the multi-axis displacement platform and analyze the temperature gradient change rate to determine the proportion of fast-changing rate windows and the degree of temperature gradient change;

[0015] The proportion of fast-changing rate windows is multiplied by the temperature gradient change degree to obtain the operation risk value of the suspected high-risk area; if it is greater than or equal to the operation risk threshold, the suspected high-risk area is recorded as a high-risk area.

[0016] As a further solution of the present invention: the process of determining the proportion of the number of fast-changing rate windows is as follows:

[0017] The monitoring period is divided into several monitoring time points with equal time intervals. At the monitoring time points, the temperatures of two monitoring points in the suspected high-risk area of ​​the multi-axis displacement platform are collected and analyzed to determine the temperature gradient at the monitoring time points.

[0018] The temperature gradient collection time sequence of all monitoring time points is integrated into a temperature gradient sequence, and the temperature gradients of two adjacent monitoring time points are extracted as a time window to determine the temperature gradient sequence after elimination; based on the temperature gradient sequence after elimination, the temperature gradient deviation value corresponding to the time window is extracted, and the ratio is processed with the duration corresponding to the time window to obtain the temperature gradient change rate of the time window; if it is greater than or equal to the standard value of the temperature gradient change rate, the time window is recorded as a fast change rate window; the proportion of the number of fast change rate windows in the time window is calculated.

[0019] As a further solution of the present invention: the specific process of determining the temperature gradient at the monitoring time point is:

[0020] Based on any monitoring time point, the temperature of the two monitoring points contained in the suspected high-risk area at the monitoring time point is subtracted and the absolute value is taken, and then the difference is processed with the distance between the two monitoring points contained in the suspected high-risk area to obtain the temperature gradient at the monitoring time point.

[0021] As a further solution of the present invention: the process of determining the temperature gradient sequence after elimination is:

[0022] The temperature gradient deviation value is obtained by performing a difference process on the next temperature gradient in the time window and the previous temperature gradient. If the difference is less than or equal to 0, the temperature gradient data in the temperature gradient sequence corresponding to the time window is eliminated.

[0023] As a further solution of the present invention: the process of determining the temperature gradient change degree value is as follows:

[0024] The temperature gradient change rate corresponding to the fast change rate window is extracted and subtracted from the standard value of the temperature gradient change rate to obtain the temperature gradient change rate difference of the fast change rate window. The temperature gradient change rate differences of all fast change rate windows are summed and averaged, and then the sum is ratioed with the standard value of the temperature gradient change rate to obtain the temperature gradient change degree value.

[0025] As a further solution of the present invention: the specific process of determining whether to merge high-risk areas for temperature compensation is as follows:

[0026] Extract all axis segments containing high-risk areas in the multi-axis displacement platform and combine them into an axis segment sequence. Combine any two axis segments in the axis segment sequence and record them as a combined axis segment. Extract any high-risk area of ​​one axis segment in the combined axis segment and combine it one by one with all high-risk areas of the other axis segment in the combined axis segment to obtain a combined area. Obtain the distance between the midpoints of the high-risk areas in the combined area and record it as the axis segment spacing.

[0027] If it is less than the standard value of the distance between the shaft segments, the combined area is recorded as a combination of areas with close distances, and analysis is performed to determine the temperature gradient similarity value of the areas with close distances;

[0028] If it is less than or equal to the temperature gradient similarity threshold, the two high-risk areas in the combined area with close distance are merged for temperature compensation.

[0029] As a further solution of the present invention: the process of determining the temperature gradient similarity value is:

[0030] The temperature gradient sequences corresponding to the high-risk areas in the combination of regions with similar distances are extracted, and the numerical similarity between the temperature gradient sequences corresponding to the high-risk areas in the combination of regions with similar distances is calculated using the Euclidean distance formula, which is recorded as the temperature gradient similarity value.

[0031] In a second aspect, the present invention further provides a multi-axis displacement platform temperature compensation system, the system comprising:

[0032] Preliminary identification module: This module obtains temperature data of monitoring points on each axis section of the multi-axis displacement platform when the platform is not in operation. The temperature data includes temperature. By performing deviation analysis on the temperature of monitoring points on each axis section, it preliminarily identifies suspected high-risk areas in the axis sections of the multi-axis displacement platform.

[0033] High-risk area identification module: Start the multi-axis displacement platform, preset the monitoring period, monitor the suspected high-risk areas in the multi-axis displacement platform in real time, analyze the temperature gradient change rate of the suspected high-risk areas during operation, and identify the high-risk areas in the suspected high-risk areas;

[0034] Mergeability analysis module: Based on the determined high-risk areas, the risk level of the high-risk areas between the axis segments in the multi-axis displacement platform is combined with the distance between the axis segments to determine whether to merge the high-risk areas for temperature compensation.

[0035] The beneficial effects of the present invention are as follows: obtaining temperature data of monitoring points of each shaft segment when the multi-axis displacement platform is not in operation, wherein the temperature data includes temperature, and preliminarily identifying suspected high-risk areas in the shaft segments of the multi-axis displacement platform by performing deviation analysis on the temperature of the monitoring points of each shaft segment; starting the multi-axis displacement platform, presetting the monitoring period, monitoring the suspected high-risk areas in the multi-axis displacement platform in real time, and analyzing the temperature gradient change rate of the suspected high-risk areas during operation to identify high-risk areas in the suspected high-risk areas; based on the determined high-risk areas, combining and classifying the risk levels of the high-risk areas between the shaft segments in the multi-axis displacement platform in combination with the distance between the shaft segments. Analysis is performed to determine whether high-risk areas should be merged for temperature compensation. The present invention preliminarily screens suspected high-risk areas through temperature gradient analysis during static cooling, and then dynamically identifies high-risk areas in combination with the temperature gradient change rate during operation, thereby achieving dual-layer precise risk positioning combining static and dynamic methods. The operational risk value quantification model takes into account both the frequency and intensity of risk occurrence, thereby improving the comprehensiveness of judgment. During the combined analysis, the shaft segment spacing, temperature gradient value, and the similarity of the temperature gradient change rate are combined to scientifically determine whether to merge for compensation, thereby improving thermal management efficiency and reducing compensation costs and energy consumption. A closed-loop management system of monitoring, evaluation, and compensation is formed to provide data support for thermal design optimization and enhance equipment operation reliability and stability. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] The present invention will be further described below with reference to the accompanying drawings.

[0037] Figure 1 This is a flow chart of the steps of a temperature compensation method for a multi-axis displacement platform according to an embodiment of the present invention;

[0038] Figure 2 This is a system block diagram of a temperature compensation system for a multi-axis displacement platform according to an embodiment of the present invention. DETAILED DESCRIPTION

[0039] In order to make the technical means, creative features, objectives and effects achieved by the present invention easier to understand, the present invention is further described below in conjunction with specific implementation methods.

[0040] Example 1

[0041] See also Figure 1 As shown, a temperature compensation method for a multi-axis displacement platform according to an embodiment of the present invention includes the following steps:

[0042] Step 1: Obtain temperature data of monitoring points on each axis section of the multi-axis displacement platform when it is not in operation. The temperature data includes temperature. By performing deviation analysis on the temperature of monitoring points on each axis section, preliminarily identify suspected high-risk areas in the axis section of the multi-axis displacement platform.

[0043] In the multi-axis displacement platform, monitoring points are evenly set at the same distance along the axial direction. The distance between adjacent monitoring points is set according to the accuracy requirements of the multi-axis displacement platform. After the multi-axis displacement platform is completely cooled (e.g., left to stand for 12 hours), the temperature of each monitoring point is measured by a temperature sensor;

[0044] Based on any axis segment, the temperature difference between two adjacent monitoring points is processed to obtain the temperature difference of adjacent points, and the temperature gradient of adjacent monitoring points is obtained by ratio processing the temperature difference of adjacent points and the distance between adjacent monitoring points.

[0045] In some embodiments, the temperature gradients of adjacent monitoring points are compared with a temperature gradient threshold. The specific comparison process is:

[0046] If the temperature gradient between adjacent monitoring points is greater than or equal to the temperature gradient threshold, it means that the temperature variation between adjacent monitoring points is large, and the area corresponding to the adjacent monitoring points is recorded as a suspected high-risk area;

[0047] If the temperature gradient between adjacent monitoring points is less than the temperature gradient threshold, it means that the temperature change between adjacent monitoring points is small, and the area corresponding to the adjacent monitoring points is recorded as a non-suspected high-risk area;

[0048] Step 2: Start the multi-axis displacement platform, preset a monitoring period, monitor the suspected high-risk areas in the multi-axis displacement platform in real time, analyze the temperature gradient change rate of the suspected high-risk areas during operation, and identify the high-risk areas in the suspected high-risk areas;

[0049] Extract all high-risk areas in the multi-axis displacement platform, divide the monitoring period into several monitoring time points with equal time intervals, and use temperature sensors to collect the temperatures of two monitoring points in the suspected high-risk areas of the multi-axis displacement platform at each monitoring time point.

[0050] Based on any monitoring time point, the temperature of the two monitoring points included in the suspected high-risk area at the monitoring time point is subtracted and the absolute value is taken to obtain the temperature deviation value at the monitoring time point; the temperature deviation value at the monitoring time point is ratioed with the distance between the two monitoring points included in the suspected high-risk area to obtain the temperature gradient at the monitoring time point;

[0051] The temperature gradient acquisition time sequence of all monitoring time points is integrated into the temperature gradient sequence {h1, h2, …, hn}, where i = 1, 2, …, n, and n represents the total number of monitoring time points in the monitoring period;

[0052] Extract the temperature gradients of two adjacent monitoring time points from the temperature gradient sequence as a time window, perform the difference processing between the latter temperature gradient and the previous temperature gradient in the time window, and obtain the temperature gradient deviation value;

[0053] Compare the temperature gradient deviation value to 0:

[0054] If the temperature gradient deviation value is greater than 0, it means that the temperature gradient change in the time window is on an upward trend, and the temperature gradient data in the temperature gradient sequence corresponding to the time window will be retained;

[0055] If the temperature gradient deviation is less than or equal to 0, it means that the temperature gradient change in the time window is not in an upward trend, and the temperature gradient data in the temperature gradient sequence corresponding to the time window is removed;

[0056] Based on the temperature gradient sequence after elimination, the temperature gradient deviation value corresponding to the time window is extracted, and the temperature gradient deviation value is ratioed with the duration corresponding to the time window to obtain the temperature gradient change rate of the time window;

[0057] Compare the temperature gradient change rate in the time window with the standard value of the temperature gradient change rate:

[0058] If the temperature gradient change rate of the time window is greater than or equal to the standard value of the temperature gradient change rate, it means that the temperature gradient change rate in the time window is fast, and the time window is recorded as a fast change rate window;

[0059] If the temperature gradient change rate of the time window is less than the standard value of the temperature gradient change rate, it means that the temperature gradient change rate in the time window is slow, and the time window is recorded as a slow change rate window;

[0060] It should be noted that the standard value of the temperature gradient change rate is set by those skilled in the art based on the historical change characteristics of the temperature gradient;

[0061] Count the number of fast-changing rate windows in the time window and calculate the proportion of fast-changing rate windows in the time window;

[0062] Extract the temperature gradient change rate corresponding to the fast change rate window, and perform subtraction processing with the temperature gradient change rate standard value to obtain the temperature gradient change rate difference of the fast change rate window. Sum and average the temperature gradient change rate differences of all fast change rate windows, and then perform ratio processing with the temperature gradient change rate standard value to obtain the temperature gradient change degree value.

[0063] The operating risk value of the suspected high-risk area is obtained by multiplying the proportion of the fast-changing rate windows by the temperature gradient change value.

[0064] In some embodiments, the operation risk value of the suspected high-risk area is compared with the operation risk threshold. The specific comparison process is:

[0065] If the operational risk value of a suspected high-risk area is greater than or equal to the operational risk threshold, the suspected high-risk area will be recorded as a high-risk area;

[0066] If the operational risk value of a suspected high-risk area is less than the operational risk threshold, the suspected high-risk area will be recorded as a low-risk area;

[0067] It is understandable that the setting of the operation risk value realizes the assessment of high-risk areas of the multi-axis displacement platform by systematically quantifying the dynamic change characteristics of the temperature gradient. It not only improves the comprehensiveness of risk judgment by screening the data of the rising trend of the temperature gradient and taking into account the frequency and intensity of risk occurrence, but also provides reliable support for the subsequent judgment of whether high-risk areas can be combined with temperature compensation to reduce the probability of failure and improve the efficiency of temperature compensation. At the same time, it provides data support for thermal design optimization, forms a closed-loop management of monitoring, evaluation and improvement, and significantly enhances the reliability and stability of the multi-axis displacement platform operation.

[0068] Step 3: Based on the identified high-risk areas, conduct a combined analysis of the risk levels of the high-risk areas between the axis segments of the multi-axis displacement platform and the distance between the axis segments to determine whether to merge the high-risk areas for temperature compensation;

[0069] Extract all axis segments containing high-risk areas in the multi-axis displacement platform and combine them into an axis segment sequence. Combine any two axis segments in the axis segment sequence and record them as a combined axis segment.

[0070] Perform a combined analysis on the high-risk areas of the combined shaft segments to determine whether to combine the high-risk areas for temperature compensation. The specific process is as follows:

[0071] Extract any high-risk area of ​​one axis segment in the combined axis segment, and combine it with all high-risk areas of the other axis segment in the combined axis segment one by one to obtain the combined area;

[0072] The distance between the midpoints of the high-risk areas in the combined area is obtained by a laser rangefinder and recorded as the axis segment spacing;

[0073] It should be noted that the midpoint of the high-risk area is a characteristic point that is determined by mathematical methods and can represent the location of the high-risk area;

[0074] For example, assume that monitoring points are evenly distributed on a certain axis segment of the multi-axis displacement platform, the distance between adjacent monitoring points is d = 10 cm, the monitoring points are numbered P1, P2, P3, ..., and the coordinates are x = 0 cm, x = 10 cm, x = 20 cm, ..., respectively. The area between monitoring points P2 and P3 (i.e., the line segment from x = 10 cm to x = 20 cm) is a high-risk area. The midpoint of the high-risk area is:

[0075] Compare the segment spacing with the standard value for segment spacing:

[0076] If the axis segment spacing is greater than or equal to the axis segment spacing standard value, the combination operation is canceled;

[0077] If the axis segment spacing is less than the axis segment spacing standard value, the combined area is recorded as a close distance area combination;

[0078] It should be noted that the standard value of the shaft segment spacing is set by those skilled in the art based on historical experience. When combining regions, if no high-risk regions remain in the shaft segment, the combination operation will be stopped. If the number of remaining high-risk regions after the combination is completed is not 1, the combination operation will continue.

[0079] Extract the temperature gradient sequence corresponding to the high-risk area in the combination of close distance areas and perform similarity analysis. Specifically:

[0080] By the Euclidean distance formula: Calculate the numerical similarity between the temperature gradient sequences corresponding to the high-risk areas in the combination of close distance areas, and record it as the temperature gradient similarity value d, where x i represents the temperature gradient at the i-th monitoring time point of the previous high-risk area in the proximity area combination, y i represents the temperature gradient at the i-th monitoring time point of the next high-risk area in the proximity area combination, and n represents the total number of monitoring time points in the monitoring period;

[0081] It should be noted that the extracted temperature gradient sequence is the temperature gradient sequence after the temperature gradient data is eliminated;

[0082] In some embodiments, the temperature gradient similarity value of the close combined region is compared with the temperature gradient similarity threshold. The specific comparison process is:

[0083] If the temperature gradient similarity value of the close combined area is greater than or equal to the temperature gradient similarity threshold, it means that the two high-risk areas in the close combined area can be merged for temperature compensation;

[0084] If the temperature gradient similarity value of the close combined area is less than the temperature gradient similarity threshold, it means that the two high-risk areas in the close combined area cannot be merged for temperature compensation;

[0085] The technical solution of this embodiment is as follows: obtaining temperature data of monitoring points of each shaft segment when the multi-axis displacement platform is not in operation, wherein the temperature data includes temperature, and preliminarily identifying suspected high-risk areas in the shaft segments of the multi-axis displacement platform by performing deviation analysis on the temperature of the monitoring points of each shaft segment; starting the multi-axis displacement platform, presetting the monitoring period, monitoring the suspected high-risk areas in the multi-axis displacement platform in real time, and analyzing the temperature gradient change rate of the suspected high-risk areas during operation to identify high-risk areas in the suspected high-risk areas; based on the determined high-risk areas, combining and classifying the risk levels of the high-risk areas between the shaft segments in the multi-axis displacement platform in combination with the distance between the shaft segments. Analysis is used to determine whether to merge high-risk areas for temperature compensation. The present invention preliminarily screens suspected high-risk areas through temperature gradient analysis during static cooling, and then dynamically identifies high-risk areas in combination with the temperature gradient change rate during operation, thereby achieving dual-layer precise risk positioning combining static and dynamic methods. The operational risk value quantification model takes into account both the frequency and intensity of risk occurrence, thereby improving the comprehensiveness of judgment. During the combined analysis, the shaft segment spacing, temperature gradient value, and the similarity of the temperature gradient change rate are combined to scientifically determine whether to merge compensation, thereby improving thermal management efficiency and reducing compensation costs and energy consumption. A closed-loop management system of monitoring, evaluation, and compensation is formed to provide data support for thermal design optimization and enhance equipment operation reliability and stability.

[0086] Example 2

[0087] See also Figure 2 As shown, a multi-axis displacement platform temperature compensation system according to an embodiment of the present invention includes the following modules:

[0088] Preliminary identification module: This module obtains temperature data of monitoring points on each axis section of the multi-axis displacement platform when the platform is not in operation. The temperature data includes temperature. By performing deviation analysis on the temperature of monitoring points on each axis section, it preliminarily identifies suspected high-risk areas in the axis sections of the multi-axis displacement platform.

[0089] High-risk area identification module: Start the multi-axis displacement platform, preset the monitoring period, monitor the suspected high-risk areas in the multi-axis displacement platform in real time, analyze the temperature gradient change rate of the suspected high-risk areas during operation, and identify the high-risk areas in the suspected high-risk areas;

[0090] Mergeability analysis module: Based on the identified high-risk areas, the risk level of the high-risk areas between the axis segments in the multi-axis displacement platform is analyzed in combination with the distance between the axis segments to determine whether to merge the high-risk areas for temperature compensation;

[0091] The basic principles, main features, and advantages of the present invention are shown and described above. Those skilled in the art should understand that the present invention is not limited to the foregoing embodiments. The foregoing embodiments and descriptions are merely illustrative of the principles of the present invention. Various changes and modifications may be made to the present invention without departing from the spirit and scope of the present invention. Such changes and modifications are intended to fall within the scope of the present invention. The scope of protection claimed in the present invention is defined by the appended claims and their equivalents.

Claims

1. A temperature compensation method for a multi-axis displacement platform, characterized by: include: Obtain temperature data from monitoring points on each axis section of the multi-axis displacement platform when it is not in operation. The temperature data includes temperature. By performing deviation analysis on the temperature of each axis section monitoring point, preliminarily identify suspected high-risk areas in the axis section of the multi-axis displacement platform. Start the multi-axis displacement platform, preset the monitoring period, monitor the suspected high-risk areas in the multi-axis displacement platform in real time, analyze the temperature gradient change rate of the suspected high-risk areas during operation, and identify the high-risk areas in the suspected high-risk areas; According to the determined high-risk areas, a combined analysis is performed on the risk degree of the high-risk areas between the axis segments in the multi-axis displacement platform, combined with the distance between the axis segments, to determine whether the high-risk areas should be merged for temperature compensation.

2. A temperature compensation method for a multi-axis displacement platform according to claim 1, characterized in that: The specific process of preliminarily identifying suspected high-risk areas in the axis segments of the multi-axis displacement platform is as follows: In a multi-axis displacement platform, monitoring points are evenly set at the same distance along the axial direction. Based on any axis segment, the temperature between two adjacent monitoring points is subtracted and then ratioed with the distance between the adjacent monitoring points to obtain the temperature gradient of the adjacent monitoring points. If the temperature gradient between adjacent monitoring points is greater than or equal to the temperature gradient threshold, the corresponding area between the adjacent monitoring points will be recorded as a suspected high-risk area.

3. The temperature compensation method for a multi-axis displacement platform according to claim 1, characterized in that: The specific process of identifying high-risk areas among suspected high-risk areas is as follows: Extract all high-risk areas in the multi-axis displacement platform and analyze the temperature gradient change rate to determine the proportion of fast-change rate windows and the degree of temperature gradient change; The operating risk value of the suspected high-risk area is obtained by multiplying the proportion of the fast-changing rate windows by the temperature gradient change value. If it is greater than or equal to the operational risk threshold, the suspected high-risk area will be recorded as a high-risk area.

4. A temperature compensation method for a multi-axis displacement platform according to claim 3, characterized in that: The process of determining the proportion of the number of fast-changing rate windows is as follows: The monitoring period is divided into several monitoring time points with equal time intervals. At the monitoring time points, the temperatures of two monitoring points in the suspected high-risk area of ​​the multi-axis displacement platform are collected and analyzed to determine the temperature gradient at the monitoring time points. The temperature gradient acquisition time sequence of all monitoring time points is integrated into a temperature gradient sequence, and the temperature gradients of two adjacent monitoring time points are extracted as a time window to determine the temperature gradient sequence after elimination. Based on the temperature gradient sequence after elimination, the temperature gradient deviation value corresponding to the time window is extracted and the ratio is processed with the duration corresponding to the time window to obtain the temperature gradient change rate of the time window. If it is greater than or equal to the standard value of the temperature gradient change rate, the time window is recorded as a fast change rate window; the proportion of fast change rate windows in the time window is calculated.

5. The temperature compensation method for a multi-axis displacement platform according to claim 4, characterized in that: The specific process of determining the temperature gradient at the monitoring time point is as follows: Based on any monitoring time point, the temperature of the two monitoring points contained in the suspected high-risk area at the monitoring time point is subtracted and the absolute value is taken, and then the difference is processed with the distance between the two monitoring points contained in the suspected high-risk area to obtain the temperature gradient at the monitoring time point.

6. The temperature compensation method for a multi-axis displacement platform according to claim 4, characterized in that: The process of determining the temperature gradient sequence after elimination is as follows: The temperature gradient deviation value is obtained by performing a difference process on the next temperature gradient in the time window and the previous temperature gradient. If the difference is less than or equal to 0, the temperature gradient data in the temperature gradient sequence corresponding to the time window is eliminated.

7. The temperature compensation method for a multi-axis displacement platform according to claim 3, characterized in that: The process of determining the temperature gradient change degree value is as follows: The temperature gradient change rate corresponding to the fast change rate window is extracted and subtracted from the standard value of the temperature gradient change rate to obtain the temperature gradient change rate difference of the fast change rate window. The temperature gradient change rate differences of all fast change rate windows are summed and averaged, and then the sum is ratioed with the standard value of the temperature gradient change rate to obtain the temperature gradient change degree value.

8. The temperature compensation method for a multi-axis displacement platform according to claim 3, characterized in that: The specific process of determining whether to merge high-risk areas for temperature compensation is as follows: Extract all axis segments containing high-risk areas in the multi-axis displacement platform and combine them into an axis segment sequence. Combine any two axis segments in the axis segment sequence and record them as a combined axis segment. Extract any high-risk area of ​​one axis segment in the combined axis segment and combine it one by one with all high-risk areas of the other axis segment in the combined axis segment to obtain a combined area. Obtain the distance between the midpoints of the high-risk areas in the combined area and record it as the axis segment spacing. If it is less than the standard value of the distance between the shaft segments, the combined area is recorded as a combination of areas with close distances, and analysis is performed to determine the temperature gradient similarity value of the areas with close distances; If it is less than or equal to the temperature gradient similarity threshold, the two high-risk areas in the combined area with close distance are merged for temperature compensation.

9. The temperature compensation method for a multi-axis displacement platform according to claim 8, characterized in that: The process of determining the temperature gradient similarity value is as follows: The temperature gradient sequences corresponding to the high-risk areas in the combination of regions with similar distances are extracted, and the numerical similarity between the temperature gradient sequences corresponding to the high-risk areas in the combination of regions with similar distances is calculated using the Euclidean distance formula, which is recorded as the temperature gradient similarity value.

10. A multi-axis displacement platform temperature compensation system, characterized in that: The system is used to execute the method according to any one of claims 1 to 9, and the system comprises: Preliminary identification module: This module obtains temperature data of monitoring points on each axis section of the multi-axis displacement platform when the platform is not in operation. The temperature data includes temperature. By performing deviation analysis on the temperature of monitoring points on each axis section, it preliminarily identifies suspected high-risk areas in the axis sections of the multi-axis displacement platform. High-risk area identification module: Start the multi-axis displacement platform, preset the monitoring period, monitor the suspected high-risk areas in the multi-axis displacement platform in real time, analyze the temperature gradient change rate of the suspected high-risk areas during operation, and identify the high-risk areas in the suspected high-risk areas; Mergeability analysis module: Based on the determined high-risk areas, the risk level of the high-risk areas between the axis segments in the multi-axis displacement platform is combined with the distance between the axis segments to determine whether to merge the high-risk areas for temperature compensation.

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