Intelligent control method and system for high-precision CNC machine tools

Abstract

The present invention relates to the field of data processing technology, and in particular to an intelligent control method and system for high-precision CNC machine tools. The method includes the following steps: collecting the spindle surface temperature and the coolant temperature; obtaining the temperature difference at each moment and the degree of change of the temperature difference at each moment, clustering the temperature differences at all moments before each moment, and obtaining a number of clusters at each moment; obtaining the compactness of each cluster at each moment, and obtaining the stability of the temperature difference at each moment according to the compactness; adjusting the temperature difference at each moment according to the degree of change and stability of the temperature difference at each moment, and obtaining a corrected temperature difference value at each moment, and obtaining the corrected coolant temperature value at each moment based on the corrected temperature difference value; predicting the coolant temperature value at the next moment according to the corrected coolant temperature value at each moment, and the present invention improves the accuracy of coolant temperature control.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to an intelligent control method and system for high-precision CNC machine tools. Background Art

[0002] In modern manufacturing, high-precision CNC machine tools have been widely used in aerospace, automobile manufacturing, precision instruments and other fields due to their high precision and high efficiency. However, the spindle of the machine tool and its surrounding components will generate a lot of heat when running at high speed. If the coolant temperature during the operation of the cooling system is too high, the spindle components will not be able to dissipate heat in time, affecting the processing accuracy; if the coolant temperature is too low, it may cause other problems, such as the formation of condensed water, which will affect the accuracy of the electrical components inside the machine tool and cause errors in the processing process. Therefore, in order to ensure the quality of the product, an intelligent control method and system are needed to dynamically adjust the coolant temperature so that it can effectively dissipate heat without being overcooled, ensuring that the spindle surface temperature remains at an appropriate level, thereby improving the processing accuracy and ensuring the production quality of the product.

[0003] The patent document with the authorization announcement number CN115913114B discloses a photovoltaic aging detection method based on the least squares method. First, by sampling the voltage and current data of the maximum power tracking, the IV curve of the entire photovoltaic system is predicted using the least squares method to calculate the actual MPP of the photovoltaic system and compare it with its theoretical MPP value to determine whether the measured photovoltaic system has aged and the degree of aging.

[0004] The least squares method in the above method obtains the coolant temperature at the next moment by fitting the coolant temperature at all the moments that have been obtained, thereby realizing real-time control of the coolant temperature. However, in the actual processing process, the load of the spindle may suddenly increase, which will cause the spindle surface temperature to rise rapidly. Due to the response lag, the adjustment of the coolant temperature often takes a certain amount of time and may not be able to keep up with the change of the spindle surface temperature immediately. Therefore, based on the obtained coolant temperature, the coolant temperature at the next moment may be predicted with errors, which in turn affects the accuracy of the electrical components inside the machine tool and causes errors in the processing process. Summary of the invention

[0005] In order to solve the technical problem that the spindle surface temperature rises rapidly due to the sudden increase in the spindle load, and the adjustment of the coolant temperature cannot immediately keep up with the change in the spindle surface temperature, resulting in the temperature difference value at the next moment predicted based on the temperature difference value at the historical moment may have an error, the present invention provides an intelligent control method and system for high-precision CNC machine tools.

[0006] In the first aspect, the present invention provides an intelligent control method for a high-precision CNC machine tool, which adopts the following technical solution:

[0007] The intelligent control method of high-precision CNC machine tools comprises the following steps:

[0008] Collect the spindle surface temperature and coolant temperature; obtain the temperature difference at each moment, the temperature difference is the difference between the spindle surface temperature and the coolant temperature; obtain the degree of change of the temperature difference at each moment , Represents the degree of change of temperature difference at the i-th moment; Represents the temperature difference at the i-th moment; represents the temperature difference at the i-1th moment; represents the temperature difference at the i-2th moment;

[0009] Get the stability of temperature difference at each moment ; Represents the stability of the temperature difference at the i-th moment; Represents the Euclidean distance between the temperature difference at the i-th moment and the cluster center of the target cluster at the i-th moment; Represents the mean of the Euclidean distances between all data in the target cluster at the i-th moment and its cluster center; || represents the absolute value symbol;

[0010] Get the corrected coolant temperature value at each moment , represents the corrected coolant temperature value at the i-th moment; Represents the correction weight of the temperature difference at the i-th moment; Represents the spindle surface temperature value at the i-th moment;

[0011] According to the corrected coolant temperature value at each moment, the coolant temperature value at the next moment is predicted.

[0012] The innovation of the present invention lies in correcting the temperature difference at each moment according to the degree of change and stability of the temperature difference at each moment, and finally correcting the coolant temperature value at each moment, so that the corrected coolant temperature value obtained at each moment is more accurate, effectively reducing the problem of error in the collected coolant temperature value due to response lag, and finally predicting the coolant temperature value at the next moment according to the corrected coolant temperature value at each moment, thereby improving the accuracy of coolant control.

[0013] Preferably, the process of acquiring the target cluster at the i-th moment includes:

[0014] The compactness of each cluster at the i-th moment is obtained; the cluster with the largest compactness among the clusters at the i-th moment is recorded as the target cluster at the i-th moment.

[0015] It is convenient to cluster the clusters according to the target at each moment and obtain the stability of the temperature difference at each moment.

[0016] Preferably, obtaining the compactness of each cluster at the i-th moment includes:

[0017] Get each cluster at the i-th moment;

[0018] ;

[0019] In the formula, Represents the compactness of the a-th cluster at the i-th moment; Represents the number of data in the ath cluster at the i-th moment; Represents the mean of the Euclidean distances between all data in the a-th cluster at the i-th moment and its cluster center; Represents the Euclidean distance between the jth data in the ath cluster at the i-th moment and its cluster center; exp() represents an exponential function with a natural constant as the base.

[0020] Preferably, the obtaining of each cluster at the i-th moment includes:

[0021] The DBSCAN clustering algorithm is used to cluster the temperature differences at all times before the i-th time, and several clusters at the i-th time are obtained.

[0022] It is convenient to analyze the compactness of each cluster at each moment and subsequently obtain clusters with high stability.

[0023] Preferably, the process of obtaining the correction weight of the temperature difference includes:

[0024] If the temperature difference at the i-th moment minus the temperature difference at the i-1th moment is greater than 0, the correction weight of the temperature difference at the i-th moment is 1. If the temperature difference at the i-th moment minus the temperature difference at the i-1th moment is less than 0, the correction weight of the temperature difference at the i-th moment is -1. If the temperature difference at the i-th moment minus the temperature difference at the i-1th moment is equal to 0, the correction weight of the temperature difference at the i-th moment is 0.

[0025] It is convenient to judge whether to increase or decrease the temperature difference according to the correction weight of the temperature difference at each moment.

[0026] Preferably, predicting the coolant temperature value at the next moment according to the corrected coolant temperature value at each moment includes:

[0027] The corrected coolant temperature value at each moment is curve fitted according to the least squares method to obtain the coolant temperature value at the next moment.

[0028] The prediction of the coolant temperature value at the next moment is more accurate, which improves the accuracy of coolant control.

[0029] Preferably, collecting the spindle surface temperature and the coolant temperature includes:

[0030] The preset collection time is 1 minute / time, and the collection time is two hours. An infrared temperature sensor is installed at a certain distance outside the spindle area, and a temperature sensor is installed at the position where the coolant enters the spindle. The spindle surface temperature and coolant temperature are collected at the same time.

[0031] In a second aspect, the present invention provides an intelligent control system for a high-precision CNC machine tool, which adopts the following technical solution:

[0032] The intelligent control system of a high-precision CNC machine tool comprises: a processor and a memory, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, the intelligent control method of the high-precision CNC machine tool is implemented.

[0033] By adopting the above technical solution, the intelligent control method of the above high-precision CNC machine tool is generated into a computer program and stored in a memory to be loaded and executed by a processor, so that a terminal device is made according to the memory and the processor for easy use.

[0034] The present invention has the following technical effects: the purpose of the present invention is to correct the temperature difference at each moment according to the degree of change and stability of the temperature difference at each moment, and finally correct the coolant temperature value at each moment, so that the corrected coolant temperature value obtained at each moment is more accurate, effectively reducing the problem of errors in the collected coolant temperature value due to response lag, and finally predicting the coolant temperature value at the next moment according to the corrected coolant temperature value at each moment, thereby improving the accuracy of coolant control. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] By reading the detailed description below with reference to the accompanying drawings, the above and other purposes, features and advantages of the exemplary embodiments of the present invention will become readily understood. In the accompanying drawings, several embodiments of the present invention are shown in an exemplary and non-restrictive manner, and the same or corresponding reference numerals represent the same or corresponding parts.

[0036] Figure 1 It is a method flow chart of the intelligent control method of a high-precision CNC machine tool in an embodiment of the present invention. DETAILED DESCRIPTION

[0037] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0038] It should be understood that when the terms "first", "second", etc. are used in the claims, descriptions, and drawings of the present invention, they are only used to distinguish different objects, rather than to describe a specific order. The terms "include" and "comprise" used in the description and claims of the present invention indicate the presence of the described features, wholes, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components, and / or their collections.

[0039] The embodiment of the present invention discloses an intelligent control method for a high-precision CNC machine tool, referring to Figure 1 , comprising steps S1 to S3:

[0040] S1: Collect the spindle surface temperature and coolant temperature.

[0041] In an embodiment of the present invention, the preset collection time is 1 minute / time, the collection time is two hours, an infrared temperature sensor is installed at a certain distance outside the spindle area, and a temperature sensor is installed at the position where the coolant enters the spindle. The spindle surface temperature and the coolant temperature are collected at the same time, and the spindle surface temperature and the coolant temperature correspond in time series.

[0042] It should be noted that an infrared temperature sensor is installed at a certain distance outside the spindle area to collect the spindle surface temperature in a non-contact manner. This can avoid interfering with the operation of the spindle. The temperature sensor is installed at the position where the coolant enters the spindle to monitor the temperature of the coolant when it enters the spindle.

[0043] S2: Obtain the temperature difference at each moment and the degree of change of the temperature difference at each moment, cluster the temperature differences of all moments before each moment, and obtain several clusters at each moment; obtain the compactness of each cluster at each moment, and obtain the stability of the temperature difference at each moment according to the compactness.

[0044] It should be noted that the traditional least squares method obtains the coolant temperature at the next moment by fitting the coolant temperature at all moments, thereby achieving real-time control of the coolant temperature. However, in the actual processing process, the load of the spindle may suddenly increase, which will cause the spindle surface temperature to rise rapidly, and the adjustment of the coolant temperature often takes a certain amount of time, which may not be able to immediately keep up with the change of the spindle surface temperature. Therefore, according to the obtained coolant temperature, the coolant temperature at the next moment may be predicted to have errors, which in turn affects the accuracy of the electrical components inside the machine tool, resulting in errors in the processing process. Therefore, the present invention combines the degree of change and stability of the temperature difference at each moment to calculate the error factor of the temperature difference at each moment in real time and correct the temperature difference value at each moment. Finally, the corrected coolant temperature at each moment is obtained according to the corrected temperature difference value at each moment, effectively reducing the error caused by this response lag, ensuring the accuracy of the predicted coolant temperature at the next moment, so that the cooling system responds to the spindle temperature change in time and maintains the stability of the spindle temperature, and improves the accuracy of coolant temperature control.

[0045] Step S2 includes steps S20 and S21, which are specifically as follows:

[0046] S20: Obtain the temperature difference at each moment and the degree of change of the temperature difference at each moment.

[0047] It should be noted that the temperature difference refers to the difference between the spindle surface temperature and the coolant temperature at the same time. Since the temperature difference is the direct driving force of heat transfer, heat always flows from the object with high temperature to the object with low temperature until the temperatures of the two are equal or reach a certain stable temperature difference state. During the normal operation of the high-precision CNC machine tool, the spindle surface temperature gradually increases. At this time, the system coolant temperature should adjust its temperature in real time with the change of the spindle surface temperature to maintain the spindle surface temperature within a relatively stable range, that is, the temperature difference change is consistent with the change trend of the spindle surface temperature, so as to ensure that the cooling system can effectively control the spindle surface temperature. Therefore, when the temperature difference change is consistent with the change trend of the spindle surface temperature, the difference in the change rate of the temperature difference value at adjacent moments is not significant, and when the difference in the change rate of the temperature difference value at adjacent moments is significant, it may be caused by untimely adjustment of the coolant temperature or a failure of the cooling system. Therefore, according to the difference in the change rate of the temperature difference value at adjacent moments, the degree of change of the temperature difference at each moment is obtained.

[0048] In the embodiment of the present invention, the difference between the spindle surface temperature and the coolant temperature at each moment is taken as the temperature difference at each moment.

[0049] Get the degree of change of temperature difference at moment i:

[0050] ;

[0051] In the formula, Represents the degree of change of temperature difference at the i-th moment; Represents the temperature difference at the i-th moment; represents the temperature difference at the i-1th moment; represents the temperature difference at the i-2th moment; Represents the rate of change of the temperature difference at the i-th moment. The larger the value, the greater the temperature difference at the i-th moment compared to the temperature difference at the i-1-th moment. Represents the rate of change of the temperature difference at the i-1th moment. The larger the value is, the greater the difference between the temperature difference at the i-1th moment and the temperature difference at the i-2th moment. The larger the absolute value of the difference between the rate of change of the temperature difference at the i-th moment and the rate of change of the temperature difference at the i-1th moment is, the more unstable the change of the temperature difference at the i-th moment is, indicating that the degree of change of the temperature difference at the i-th moment is large.

[0052] S21: clustering the temperature differences at all moments before each moment to obtain a number of clusters at each moment; obtaining the compactness of each cluster at each moment, and obtaining the stability of the temperature difference at each moment according to the compactness.

[0053] It should be noted that if the temperature difference changes at historical moments show large fluctuations, this also indicates that the state of the cooling system may be unstable and cannot effectively respond in time to changes in the spindle surface temperature. Therefore, it is not enough to rely solely on the degree of change in the temperature difference at each moment to determine whether there is an error in the temperature difference value at each moment. It is necessary to consider whether the temperature difference changes at historical moments are stable, and compare whether the temperature difference at each moment is consistent with the stable state of the temperature difference at the historical moment before that moment, so as to obtain the stability of the temperature difference at each moment.

[0054] It should be further explained that after clustering the temperature differences at historical moments before each moment, the similarity of the temperature differences in each cluster is analyzed as the compactness of each cluster. When the compactness of the cluster is greater, the temperature difference in the cluster is more stable. Therefore, if the temperature difference at each moment is very close to the cluster center of the cluster with the largest compactness, the temperature difference at each moment is more stable.

[0055] In an embodiment of the present invention, the traditional DBSCAN clustering algorithm is used to cluster the temperature differences at all times before the i-th moment, and several clusters at the i-th moment are obtained, and the mean of all data in each cluster is used as the cluster center of each cluster. It should be noted that the DBSCAN clustering algorithm is a well-known technology and will not be described in detail in the embodiment of the present invention.

[0056] Get the compactness of each cluster at the i-th moment:

[0057] ;

[0058] In the formula, Represents the compactness of the a-th cluster at the i-th moment; Represents the number of data in the ath cluster at the i-th moment; Represents the mean of the Euclidean distances between all data in the a-th cluster at the i-th moment and its cluster center; Represents the Euclidean distance between the jth data in the ath cluster at the i-th time and its cluster center; exp() represents an exponential function with a natural constant as the base; The larger the value is, the more data there are in the a-th cluster and the smaller the mean of the Euclidean distance between all data in the a-th cluster and its cluster center is, which means the tightness of the a-th cluster is greater; The smaller the value is, the closer the distance between each data in the cluster and its cluster center is. That is, the more concentrated the data in the a-th cluster is, the greater the compactness of the a-th cluster at the i-th moment is.

[0059] In the embodiment of the present invention, the cluster with the largest degree of compactness among the clusters at the i-th moment is recorded as the target cluster at the i-th moment; the stability of the temperature difference at the i-th moment is obtained:

[0060] ;

[0061] In the formula, Represents the stability of the temperature difference at the i-th moment; Represents the Euclidean distance between the temperature difference at the i-th moment and the cluster center of the target cluster at the i-th moment; Represents the mean of the Euclidean distances between all data in the target cluster at the i-th moment and its cluster center; || represents the absolute value symbol; The larger the value of , the more significant the Euclidean distance between the temperature difference at the i-th moment and the cluster center of the target cluster is, which means that when the temperature difference at the i-th moment is inconsistent with the temperature difference at the stable moment, it deviates significantly from the stable state, that is, the lower the stability of the temperature difference at the i-th moment.

[0062] S3: Adjust the temperature difference at each moment according to the degree of change and stability of the temperature difference at each moment to obtain a corrected temperature difference value at each moment, and obtain a corrected coolant temperature value at each moment based on the corrected temperature difference value; predict the coolant temperature value at the next moment according to the corrected coolant temperature value at each moment.

[0063] Step S3 includes steps S30 and S31, which are specifically as follows:

[0064] S30: adjusting the temperature difference at each moment according to the degree of change and stability of the temperature difference at each moment to obtain a corrected temperature difference value at each moment, and obtaining a corrected coolant temperature value at each moment based on the corrected temperature difference value.

[0065] It should be noted that the degree of change of temperature difference at any moment is obtained by analyzing local data, which can only reflect whether there is a deviation in the local area. At this time, if the temperature difference at this moment is inconsistent with the temperature difference at the stable moment, that is, the stability of the temperature difference at this moment is low, it means that the error of the temperature difference at this moment is large, and the temperature difference at this moment needs to be adjusted. Therefore, the temperature difference at each moment is adjusted according to the degree of change and stability of the temperature difference at each moment to obtain the corrected temperature difference value at each moment, and then the difference between the spindle surface temperature value at each moment and the corrected temperature difference value at each moment is subtracted to obtain the corrected coolant temperature value at each moment. When adjusting the temperature difference at each moment, if the temperature difference is large, it should be reduced, otherwise it should be increased.

[0066] In an embodiment of the present invention, if the temperature difference value at the i-th moment minus the temperature difference value at the i-1th moment is greater than 0, the correction weight of the temperature difference at the i-th moment is 1; if the temperature difference value at the i-th moment minus the temperature difference value at the i-1th moment is less than 0, the correction weight of the temperature difference at the i-th moment is -1; if the temperature difference value at the i-th moment minus the temperature difference value at the i-1th moment is equal to 0, the correction weight of the temperature difference at the i-th moment is 0.

[0067] Get the corrected coolant temperature value at time i:

[0068] ;

[0069] In the formula, represents the corrected coolant temperature value at the i-th moment; Represents the temperature difference at the i-th moment; Represents the degree of change of temperature difference at the i-th moment; Represents the stability of the temperature difference at the i-th moment; Represents the correction weight of the temperature difference at the i-th moment; Represents the spindle surface temperature value at the i-th moment;

[0070] represents the error factor of the temperature difference at the i-th moment, The larger the value of , the greater the degree of local change of the temperature difference at the i-th moment. At this time, if the temperature difference at the i-th moment is inconsistent with the temperature difference at the stable moment, that is, the lower the stability of the temperature difference at the i-th moment, it is considered that the error of the temperature difference at the i-th moment is larger, and the error factor of the temperature difference at the i-th moment is larger; represents the error value of the temperature difference at the i-th moment, The larger the value of is, the larger the error value of the temperature difference at the i-th moment is;

[0071] The value of is 1, indicating that the temperature difference at the i-th moment is too high, and the temperature difference value at the i-th moment needs to be reduced. Therefore, the temperature difference value at the i-th moment is subtracted from the temperature difference error value at the i-th moment to obtain the corrected temperature difference value at the i-th moment; The value of is -1, which means that the temperature difference at the i-th moment is too small, and the temperature difference at the i-th moment needs to be increased. Therefore, the temperature difference at the i-th moment is added to the error value of the temperature difference at the i-th moment to obtain the corrected temperature difference at the i-th moment; When the value of is 0, it means that the temperature difference at the i-th moment is normal and no adjustment is needed; Represents the corrected temperature difference at the i-th moment.

[0072] S31: predicting the coolant temperature value at the next moment according to the corrected coolant temperature value at each moment.

[0073] In the embodiment of the present invention, a curve fitting is performed on the corrected coolant temperature value at each moment according to the least square method to obtain the coolant temperature value at the next moment, thereby achieving real-time control of the coolant temperature.

[0074] An embodiment of the present invention further discloses an intelligent control system for a high-precision CNC machine tool, including a processor and a memory, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, an intelligent control method for a high-precision CNC machine tool according to the present invention is implemented.

[0075] The above system also includes other components well known to those skilled in the art, such as a communication bus and a communication interface, and their configuration and functions are known in the art, so they will not be described in detail here.

[0076] In the present invention, the aforementioned memory may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. For example, a computer-readable storage medium may be any suitable magnetic storage medium or magneto-optical storage medium, such as a resistive random access memory, a dynamic random access memory, a static random access memory, an enhanced dynamic random access memory, a high bandwidth memory, a hybrid storage cube, etc., or any other medium that can be used to store the required information and can be accessed by an application, a module, or both. Any such computer storage medium may be part of the device or accessible or connectable to the device.

[0077] Although this specification has shown and described a number of embodiments of the present invention, it will be apparent to those skilled in the art that such embodiments are provided by way of example only. Those skilled in the art will conceive of many modifications, changes and alternatives without departing from the ideas and spirit of the present invention. It should be understood that in the practice of the present invention, various alternatives to the embodiments of the present invention described herein may be employed.

[0078] The above are all preferred embodiments of the present invention, and are not intended to limit the protection scope of the present invention. Therefore, any equivalent changes made based on the structure, shape, and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. An intelligent control method for high-precision CNC machine tools, characterized in that: Includes steps: Collect the spindle surface temperature and coolant temperature; obtain the temperature difference at each moment, the temperature difference is the difference between the spindle surface temperature and the coolant temperature; obtain the degree of change of the temperature difference at each moment , is the degree of change of temperature difference at the i-th moment; is the temperature difference at the i-th moment; and is the temperature difference between the i-1th moment and the i-2th moment; Get the compactness of each cluster at each moment: ; is the compactness of the a-th cluster at the i-th moment; is the number of data in the ath cluster at the i-th moment; is the mean of the Euclidean distances between all data in the a-th cluster at the i-th moment and its cluster center; is the Euclidean distance between the jth data in the ath cluster at the i-th moment and its cluster center; exp() represents an exponential function with a natural constant as the base; the cluster with the largest degree of compactness among the clusters at each moment is recorded as the target cluster at each moment; Get the stability of temperature difference at each moment ; is the stability of the temperature difference at the i-th moment; is the Euclidean distance between the temperature difference at the i-th moment and the cluster center of the target cluster at the i-th moment; is the mean of the Euclidean distances between all data in the target cluster at the i-th moment and its cluster center; The correction weight of the temperature difference at the i-th moment is recorded as ,like greater than 0, is 1; if Less than 0, is -1; if is equal to 0, is 0; Get the corrected coolant temperature value at each moment , is the corrected coolant temperature value at the i-th moment; is the spindle surface temperature value at the i-th moment; The coolant temperature value at the next moment is predicted according to the corrected coolant temperature value.

2. The intelligent control method for high-precision CNC machine tools according to claim 1 is characterized in that: The acquisition of each cluster at each moment includes: The DBSCAN clustering algorithm is used to cluster the temperature differences at all times before the i-th time, and several clusters at the i-th time are obtained.

3. The intelligent control method for high-precision CNC machine tools according to claim 1 is characterized in that: The method of predicting the coolant temperature value at the next moment according to the corrected coolant temperature value at each moment includes: The corrected coolant temperature value at each moment is curve fitted according to the least squares method to obtain the coolant temperature value at the next moment.

4. The intelligent control method for high-precision CNC machine tools according to claim 1 is characterized in that: The collecting of the spindle surface temperature and the coolant temperature includes: The preset collection time is 1 minute / time, and the collection time is two hours. An infrared temperature sensor is installed at a certain distance outside the spindle area, and a temperature sensor is installed at the position where the coolant enters the spindle. The spindle surface temperature and coolant temperature are collected at the same time.

5. Intelligent control system for high-precision CNC machine tools, characterized in that: include: A processor and a memory, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, the intelligent control method for a high-precision CNC machine tool according to any one of claims 1 to 4 is implemented.

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