Numerical control lathe processing system and method based on precision correction

Abstract

The invention discloses a numerical control lathe processing system and method based on precision correction, and relates to the technical field of numerical control machine tool management. A plurality of temperature sensors are arranged on a lathe, temperature records of a plurality of working areas of the lathe are correspondingly collected, numerical value sampling is conducted on the temperature records, and the predicted temperature of each working area is calculated; carrying out weighted calculation on the predicted temperature to obtain a machining reference temperature of the lathe, obtaining a thermal expansion coefficient of the part, correcting the measured size of the part through the thermal expansion coefficient and the machining reference temperature, monitoring the temperature of the working area in the next time period after the size of the part is corrected, and obtaining predicted data of the temperature. And the size change of the part is reasonably estimated and fed back to a lathe control system to pre-adjust the tool feeding amount, so that the problem that the machining precision is reduced due to the size change of the part in the machining process is solved.

Description

Technical Field

[0001] The invention relates to the technical field of numerical control machine tool management, and in particular to a numerical control lathe processing system and method based on precision correction. Background Art

[0002] During the lathe cutting process, the workpiece will expand due to heat, resulting in dimensional changes. If the thermal expansion of the material is severe, the change in the workpiece size will be more obvious, thus affecting the processing accuracy. For example, the size of the cut part may not meet the design requirements, or the position accuracy of the processed holes and slots may be affected. Especially for some lathe equipment with unsatisfactory factory temperature, affected by the room temperature and cutting fluid temperature, there will be a large deviation between the actual processing size and the measured size. If the deviation exceeds the part size tolerance, it is very easy to cause a quality accident in which the part is scrapped. Summary of the invention

[0003] The object of the present invention is to provide a CNC lathe processing system and method based on precision correction to solve the problems raised in the prior art.

[0004] To achieve the above object, the present invention provides the following technical solution: a CNC lathe processing method based on precision correction, the method comprising:

[0005] Step S100: several temperature sensors are arranged on the lathe to collect temperature records of several working areas of the lathe;

[0006] Step S200: sampling the temperature records, extracting the numerical variation rules of the sampled values, and calculating the predicted temperature of each working area;

[0007] Step S300: performing weighted calculation on the predicted temperature to obtain a machining reference temperature of the lathe, obtaining the thermal expansion coefficient of the part, and correcting the measured dimensions of the part by the thermal expansion coefficient and the machining reference temperature;

[0008] Step S400: monitor the temperature of the working area in the next time period after the part size is corrected, and when the difference between the actual temperature and the predicted temperature of the working area is greater than a threshold, issue an alarm to the relevant management personnel.

[0009] Furthermore, step S100 includes:

[0010] In the present invention, the working area includes: the cutting fluid circulation system of the lathe, the cutting processing area of ​​the lathe, the longitudinal axis ram tool end of the vertical lathe and the working environment of the lathe equipment;

[0011] Cutting fluid is a lubricating medium that provides lubrication and cooling for tools and workpieces during machining. The temperature of the parts can be indirectly obtained by measuring the temperature of the cutting fluid.

[0012] The longitudinal axis ram tool end of the vertical lathe is located on the ram of the machine tool. The ram usually moves in the X-axis and Z-axis directions on the crossbeam. The main function of the ram tool end is to clamp the tool and realize the cutting movement of the tool on the workpiece through the movement of the ram. The cutting effect of the ram tool end is affected by many factors, such as tool wear, cutting parameter settings, workpiece material and hardness, etc.

[0013] Further, step S200 includes:

[0014] Step S201: taking any working area as a target working area, taking a time period of length R as a temperature monitoring time period, and dividing the temperature monitoring time period into a number of unit time periods of equal length;

[0015] Step S202: In each unit time period, collect a temperature sampling value, and collect all temperature sampling values ​​into a temperature sampling sequence Q1, where Q1: (d1, d2, d3, ..., d n ), where d1, d2, d3, ... and d n Respectively represent the temperature sampling values ​​corresponding to the 1st, 2nd, 3rd, ... and nth unit time periods in the temperature monitoring time period;

[0016] Step S203: Accumulate the temperature sampling values ​​in Q1 to obtain a data sequence Q2, where Q2 is (q1, q2, q3, ... q n ), where q1 = d1, where d j Indicates the jth temperature sampling value, satisfying the condition j≤n;

[0017] Step S204: construct a data matrix B, Get vector K, K = (d2, d3, d4, ..., d n ) T ;

[0018] The B matrix is ​​a matrix with n-1 rows and 2 columns. The first column is the data processed by the adjacent mean generation method, the purpose is to smooth the data and reduce randomness, and the second column is the constant term 1;

[0019] Step S205: Set coefficient a and coefficient b to establish coefficient equation Solve for coefficient a and coefficient b;

[0020] Sample the temperature data of the temperature sensor and predict the temperature value in the next unit time period through the grey prediction model;

[0021] The grey prediction model can predict the value under the condition of using a small amount of discrete data. Usually, the machine tool processing process is a continuous working state, which needs to be judged and adjusted in a short time. Therefore, data prediction through discrete data can effectively improve the operation efficiency of the system and ensure the smooth operation of the lathe.

[0022] Step S206: Calculate the temperature prediction value temp of the target working area in the n+1th unit time period n , The n+1th unit time period is the first unit time period after the temperature monitoring time period;

[0023] Step S207: Gather historical temperature records of each working area, and calculate the temperature prediction value of each working area in the n+1th unit time period;

[0024] The prediction function established according to the grey prediction model is: Where t represents the index of the time series, starting from 0. In the sequence, the corresponding t values ​​of the data sequences from 1 to n are 0 to n-1. Therefore, when calculating the temperature prediction value of the n+1th unit time period, t=(n+1)-1=n.

[0025] Furthermore, step S300 includes:

[0026] Step S301: Set the temperature weights of the temperature sensors corresponding to each working area, obtain all temperature weights and calculate the total weight value H. Among them, w m represents the temperature weight of the temperature sensor corresponding to the mth working area, and u represents the total number of working areas;

[0027] Step S302: Calculate the predicted processing temperature T for the n+1th unit time period fore ,

[0028] Among them, temp m n+1 It represents the predicted temperature value of the mth working area in the n+1th unit time period;

[0029] Step S303: Setting the reference temperature value AT and calculating the processing reference temperature T wavg ,

[0030] Among them, T wavg =T fore -AT;

[0031] Step S304: Obtain the thermal expansion coefficient G of the part processed during the temperature monitoring period and calculate the size correction value L of the part real , L real =L0×(1+T wavg ×G), where L0 represents the length, width or height of the part measured at the reference temperature;

[0032] By T wavg ×G calculates the coefficient of change of part size due to temperature change, and estimates the size change of the part in the next stage through the predicted temperature value. After feeding back to the control system of the lathe, it can pre-adjust the cutting amount in the next stage by calling the pre-set relationship code between part size and cutting amount, which can reduce the decrease in machining accuracy caused by dimensional change caused by part deformation during machining.

[0033] Furthermore, step S400 includes:

[0034] Step S401: In the n+1th unit time period, sampling is performed on the temperature sensors corresponding to all working areas to obtain the actual temperature value of each working area;

[0035] Step S402: Calculate the temperature detection value T in the n+1th unit time period moni ,

[0036] Among them, coll m n+1 Indicates the actual temperature value of the mth working area in the n+1th unit time period;

[0037] Step S403: Setting the difference judgment threshold γ, when |T moni -T fore When |>γ, an alarm is given to the lathe manager;

[0038] A supervision mechanism is established between actual data and predicted data. When the actual temperature value deviates from the predicted data, timely alarm is issued to reduce the occurrence of scrapped parts.

[0039] In order to better implement the above method, a CNC lathe processing system based on precision correction is also proposed. The system includes: a temperature sensor management module, a temperature prediction module, a size correction module and a temperature management module. Among them, the temperature sensor management module is used to manage the temperature sensor, the temperature prediction module is used to calculate the predicted temperature of each working area, the size correction module is used to correct the measured size of the part, and the temperature management module is used to monitor the actual temperature of the working area. When the alarm condition is met, an alarm prompt is given to the relevant management personnel;

[0040] Further, the temperature prediction module includes: a time management unit, a temperature sampling unit, a sampling sequence management unit, a data matrix management unit, a data vector management unit, a coefficient management unit, a temperature prediction model management unit and a prediction value management unit;

[0041] Among them, the time management unit is used to obtain the temperature monitoring time period and manage the unit time period in the temperature time period. The temperature sampling unit is used to obtain the temperature record of the temperature sensor and collect the temperature sampling value corresponding to the unit time period. The sampling sequence management unit is used to manage the temperature sampling sequence Q1 and the data sequence Q2. The data matrix management unit is used to manage the data matrix B. The data vector management unit is used to manage the vector K. The coefficient management unit is used to manage the coefficient a and the coefficient b, and solve the coefficient a and the coefficient b through the coefficient equation. The temperature prediction model management unit is used to calculate the temperature prediction value of the corresponding working area in the n+1th unit time period. The prediction value management unit is used to collect the temperature prediction values ​​corresponding to each working area in the n+1th unit time period.

[0042] Further, the size correction module includes: a weight management unit, a processing prediction temperature calculation unit, a reference temperature calculation unit and a size correction value calculation unit;

[0043] Among them, the weight management unit is used to manage the temperature weights of the temperature sensors corresponding to each working unit, the processing prediction temperature calculation unit is used to calculate the processing prediction temperature of the n+1th unit time period, the reference temperature calculation unit is used to obtain the reference temperature value and calculate the processing reference temperature, and the size correction value calculation unit is used to obtain the thermal expansion coefficient of the part and calculate the size correction value of the part.

[0044] Further, the temperature management module includes: an actual temperature management unit, a temperature detection value calculation unit, a threshold judgment unit and an alarm information management unit;

[0045] Among them, the actual temperature management unit is used to obtain the actual temperature value of each working area, the temperature detection value calculation unit is used to obtain the temperature weight of the temperature sensor and calculate the temperature detection value in the n+1th unit time period, the threshold judgment unit is used to obtain the difference judgment threshold to judge whether the temperature difference is greater than the threshold, and the alarm information management unit is used to obtain the judgment condition. When the judgment condition is met, an alarm prompt is given to the lathe management personnel.

[0046] Compared with the prior art, the beneficial effects of the present invention are: by establishing a temperature prediction model, the correlation between the dimensional change and temperature of the part being processed is obtained, and by feeding back the dimensional change of the part, the cutting amount of the lathe is further adjusted in real time. The present application obtains the predicted data of the temperature, makes a reasonable estimate of the dimensional change of the part, and feeds back to the lathe control system to pre-adjust the cutting amount, so as to reduce the problem of reduced processing accuracy caused by the dimensional change of the part during the processing. In addition, the predicted value is supervised in combination with the supervision mechanism, and an alarm is issued when there is a large deviation between the actual value and the predicted value, so as to reduce the generation of scrap parts and further improve the production accuracy of the lathe. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 It is a structural schematic diagram of a CNC lathe processing system based on precision correction of the present invention;

[0048] Figure 2 A schematic flow chart of a CNC lathe processing method based on precision correction according to the present invention; DETAILED DESCRIPTION

[0049] 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 only 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 ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0050] Example: Figure 1 and Figure 2 As shown, the present invention provides a technical solution, a CNC lathe processing system and method based on precision correction, the method comprising:

[0051] Step S100: several temperature sensors are arranged on the lathe to collect temperature records of several working areas of the lathe;

[0052] Among them, the working area includes: the cutting fluid circulation system of the lathe, the cutting processing area of ​​the lathe, the longitudinal axis slide tool end of the vertical lathe and the working environment of the lathe equipment.

[0053] Step S200: sampling the temperature records, extracting the numerical variation rules of the sampled values, and calculating the predicted temperature of each working area;

[0054] Wherein, step S200 includes:

[0055] Step S201: taking any working area as a target working area, taking a time period of length R as a temperature monitoring time period, and dividing the temperature monitoring time period into a number of unit time periods of equal length;

[0056] Step S202: In each unit time period, collect a temperature sampling value, and collect all temperature sampling values ​​into a temperature sampling sequence Q1, where Q1: (d1, d2, d3, ..., d n ), where d1, d2, d3, ... and d n Respectively represent the temperature sampling values ​​corresponding to the 1st, 2nd, 3rd, ... and nth unit time periods in the temperature monitoring time period;

[0057] Step S203: Accumulate the temperature sampling values ​​in Q1 to obtain a data sequence Q2, where Q2 is (q1, q2, q3, ... q n ), where q1 = d1, where d j Indicates the jth temperature sampling value, satisfying the condition j≤n;

[0058] Step S204: construct a data matrix B, Get vector K, K = (d2, d3, d4, ..., d n ) T ;

[0059] Step S205: Set coefficient a and coefficient b to establish coefficient equation Solve for coefficient a and coefficient b;

[0060] Step S206: Calculate the temperature prediction value temp of the target working area in the n+1th unit time period n , The n+1th unit time period is the first unit time period after the temperature monitoring time period;

[0061] Step S207: Gather the historical temperature records of each working area, and calculate the temperature prediction value of each working area in the n+1th unit time period.

[0062] Step S300: performing weighted calculation on the predicted temperature to obtain a machining reference temperature of the lathe, obtaining the thermal expansion coefficient of the part, and correcting the measured dimensions of the part by the thermal expansion coefficient and the machining reference temperature;

[0063] Wherein, step S300 includes:

[0064] Step S301: Set the temperature weights of the temperature sensors corresponding to each working area, obtain all temperature weights and calculate the total weight value H. Among them, w m represents the temperature weight of the temperature sensor corresponding to the mth working area, and u represents the total number of working areas;

[0065] Step S302: Calculate the predicted processing temperature T for the n+1th unit time period fore ,

[0066] Among them, temp m n+1 It represents the predicted temperature value of the mth working area in the n+1th unit time period;

[0067] Step S303: Setting the reference temperature value AT and calculating the processing reference temperature T wavg ,

[0068] Among them, T wavg =T fore -AT;

[0069] Step S304: Obtain the thermal expansion coefficient G of the part processed during the temperature monitoring period and calculate the size correction value L of the part real , L real =L0×(1+T wavg ×G), where L0 represents the length, width or height of the part measured at the reference temperature;

[0070] In an embodiment, the temperature of AT can be set to 20°C. wavg and G only take numerical values, where T wavg The positive and negative values ​​represent the high and low relative to the reference temperature, with "+" for higher and "-" for lower.

[0071] Take the commonly processed materials iron, copper and titanium alloy as examples;

[0072] When the material of the part is iron, G is 11.8×10 -3 ;

[0073] When the material of the part is copper, G is 16.5×10 -3 ;

[0074] When the material of the part is titanium alloy, G is 8.5×10 -3 ;

[0075] During implementation, the expansion coefficient of the material may be pre-stored in the processing system. In the formula, G represents a transition parameter, and the preset expansion coefficient is called by initiating a request.

[0076] Step S400: monitoring the temperature of the working area in the next time period after the part size is corrected, and when the difference between the actual temperature of the working area and the predicted temperature is greater than a threshold, an alarm is given to the relevant management personnel;

[0077] Wherein, step S400 includes:

[0078] Step S401: In the n+1th unit time period, sampling is performed on the temperature sensors corresponding to all working areas to obtain the actual temperature value of each working area;

[0079] Step S402: Calculate the temperature detection value T in the n+1th unit time period moni ,

[0080] Among them, coll m n+1 Indicates the actual temperature value of the mth working area in the n+1th unit time period;

[0081] Step S403: Setting the difference judgment threshold γ, when |T moni -T fore |>γ, an alarm is given to the lathe manager.

[0082] Preferably, during implementation, the subroutine for executing part dimension correction and the tool loading adjustment program can be encapsulated in the workpiece measurement subroutine to avoid erroneous modification of parameters resulting in measurement dimension correction errors.

[0083] The system includes: a temperature sensor management module, a temperature prediction module, a size correction module and a temperature management module;

[0084] Wherein, the temperature sensor management module is used to manage the temperature sensor;

[0085] Wherein, the temperature prediction module is used to calculate the predicted temperature of each working area, wherein the temperature prediction module includes: a time management unit, a temperature sampling unit, a sampling sequence management unit, a data matrix management unit, a data vector management unit, a coefficient management unit, a temperature prediction model management unit and a prediction value management unit, wherein, wherein, the time management unit is used to obtain the temperature monitoring time period and manage the unit time period in the temperature time period, the temperature sampling unit is used to obtain the temperature record of the temperature sensor and collect the temperature sampling value corresponding to the unit time period, the sampling sequence management unit is used to manage the temperature sampling sequence Q1 and the data sequence Q2, the data matrix management unit is used to manage the data matrix B, the data vector management unit is used to manage the vector K, the coefficient management unit is used to manage the coefficient a and the coefficient b, and the coefficient a and the coefficient b are solved by the coefficient equation, the temperature prediction model management unit is used to calculate the temperature prediction value of the corresponding working area in the n+1th unit time period, and the prediction value management unit is used to collect the temperature prediction values ​​corresponding to each working area in the n+1th unit time period;

[0086] The dimension correction module is used to correct the measured dimension of the part, wherein the dimension correction module includes: a weight management unit, a processing prediction temperature calculation unit, a reference temperature calculation unit and a dimension correction value calculation unit, wherein the weight management unit is used to manage the temperature weight of the temperature sensor corresponding to each working state, the processing prediction temperature calculation unit is used to calculate the processing prediction temperature of the n+1th unit time period, the reference temperature calculation unit is used to obtain the reference temperature value and calculate the processing reference temperature, and the dimension correction value calculation unit is used to obtain the thermal expansion coefficient of the part and calculate the dimension correction value of the part;

[0087] Among them, the temperature management module is used to monitor the actual temperature of the working area, and when the alarm conditions are met, an alarm prompt is given to relevant management personnel. Among them, the temperature management module includes: an actual temperature management unit, a temperature detection value calculation unit, a threshold judgment unit and an alarm information management unit. Among them, the actual temperature management unit is used to obtain the actual temperature value of each working area, the temperature detection value calculation unit is used to obtain the temperature weight of the temperature sensor, calculate the temperature detection value in the n+1th unit time period, the threshold judgment unit is used to obtain the difference judgment threshold to judge whether the temperature difference is greater than the threshold, and the alarm information management unit is used to obtain the judgment conditions. When the judgment conditions are met, an alarm prompt is given to the management personnel of the lathe.

[0088] It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above and that the invention can be implemented in other specific forms without departing from the spirit or essential features of the invention. Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations falling within the meaning and scope of the equivalent elements of the claims be included in the invention. Any reference numeral in a claim should not be considered as limiting the claim to which it relates.

Claims

1. A CNC lathe processing method based on precision correction, characterized in that: Step S100: several temperature sensors are arranged on the lathe to collect temperature records of several working areas of the lathe; Step S200: sampling the temperature records, extracting the numerical variation rules of the sampled values, and calculating the predicted temperature of each working area; Step S300: performing weighted calculation on the predicted temperature to obtain a machining reference temperature of the lathe, obtaining the thermal expansion coefficient of the part, and correcting the measured dimensions of the part by the thermal expansion coefficient and the machining reference temperature; Step S400: monitor the temperature of the working area in the next time period after the part size is corrected, and when the difference between the actual temperature and the predicted temperature of the working area is greater than a threshold, issue an alarm to the relevant management personnel.

2. The CNC lathe processing method based on precision correction according to claim 1 is characterized in that: The working area includes: a cutting fluid circulation system of a lathe, a cutting processing area of ​​the lathe, a longitudinal axis slide tool end of a vertical lathe and a working environment of the lathe equipment.

3. The CNC lathe processing method based on precision correction according to claim 1 is characterized in that: Step S200 includes: Step S201: taking any working area as a target working area, taking a time period of length R as a temperature monitoring time period, and dividing the temperature monitoring time period into a number of unit time periods of equal length; Step S202: In each unit time period, collect a temperature sampling value, and collect all temperature sampling values ​​into a temperature sampling sequence Q1, where Q1: (d1, d2, d3, ..., d n ), where d1, d2, d3, ... and d n Respectively represent the temperature sampling values ​​corresponding to the 1st, 2nd, 3rd, ... and nth unit time periods in the temperature monitoring time period; Step S203: Accumulate the temperature sampling values ​​in Q1 to obtain a data sequence Q2, where Q2 is (q1, q2, q3, ... q n ), where q1 = d1, ..., where d j Indicates the jth temperature sampling value, satisfying the condition j≤n; Step S204: construct a data matrix B, Get vector K, K = (d2, d3, d4, ..., d n ) T ; Step S205: Set coefficient a and coefficient b to establish coefficient equation Solve for coefficient a and coefficient b; Step S206: Calculate the temperature prediction value temp of the target working area in the n+1th unit time period n , The n+1th unit time period is the first unit time period after the temperature monitoring time period; Step S207: Gather the historical temperature records of each working area, and calculate the temperature prediction value of each working area in the n+1th unit time period.

4. The CNC lathe processing method based on precision correction according to claim 3 is characterized in that: Step S300 includes: Step S301: Set the temperature weights of the temperature sensors corresponding to each working area, obtain all temperature weights and calculate the total weight value H. Among them, w m represents the temperature weight of the temperature sensor corresponding to the mth working area, and u represents the total number of working areas; Step S302: Calculate the predicted processing temperature T for the n+1th unit time period fore , Among them, temp m n+1 It represents the predicted temperature value of the mth working area in the n+1th unit time period; Step S303: Setting the reference temperature value AT and calculating the processing reference temperature T wavg , Among them, T wavg =T fore -AT; Step S304: Obtain the thermal expansion coefficient G of the part processed during the temperature monitoring period and calculate the size correction value L of the part real , L real =L0×(1+T wavg ×G), where L0 represents the length, width or height of the part measured under the temperature condition of the reference temperature value.

5. The CNC lathe processing method based on precision correction according to claim 4 is characterized in that: Step S400 includes: Step S401: In the n+1th unit time period, sampling is performed on the temperature sensors corresponding to all the working areas to obtain the actual temperature value of each working area; Step S402: Calculate the temperature detection value T in the n+1th unit time period moni , Among them, coll m n+1 Indicates the actual temperature value of the mth working area in the n+1th unit time period; Step S403: Setting the difference judgment threshold γ, when |T moni -T fore |>γ, an alarm is given to the lathe manager.

6. A CNC lathe processing system based on precision correction, used to execute a CNC lathe processing method based on precision correction as claimed in any one of claims 1 to 5, characterized in that: The system includes: The temperature sensor management module, the temperature prediction module, the size correction module and the temperature management module are used to manage the temperature sensor, the temperature prediction module is used to calculate the predicted temperature of each working area, the size correction module is used to correct the measured size of the parts, and the temperature management module is used to monitor the actual temperature of the working area. When the alarm conditions are met, an alarm prompt is given to the relevant management personnel.

7. The CNC lathe processing system based on precision correction according to claim 6 is characterized in that: The temperature prediction module includes: a time management unit, a temperature sampling unit, a sampling sequence management unit, a data matrix management unit, a data vector management unit, a coefficient management unit, a temperature prediction model management unit and a prediction value management unit; Among them, the time management unit is used to obtain the temperature monitoring time period and manage the unit time period in the temperature time period. The temperature sampling unit is used to obtain the temperature record of the temperature sensor and collect the temperature sampling value corresponding to the unit time period. The sampling sequence management unit is used to manage the temperature sampling sequence Q1 and the data sequence Q2. The data matrix management unit is used to manage the data matrix B. The data vector management unit is used to manage the vector K. The coefficient management unit is used to manage the coefficient a and the coefficient b, and solve the coefficient a and the coefficient b through the coefficient equation. The temperature prediction model management unit is used to calculate the temperature prediction value of the corresponding working area in the n+1th unit time period. The prediction value management unit is used to collect the temperature prediction values ​​corresponding to each working area in the n+1th unit time period.

8. The CNC lathe processing system based on precision correction according to claim 6, characterized in that: The size correction module includes: a weight management unit, a processing prediction temperature calculation unit, a reference temperature calculation unit and a size correction value calculation unit; Among them, the weight management unit is used to manage the temperature weights of the temperature sensors corresponding to each working unit, the processing prediction temperature calculation unit is used to calculate the processing prediction temperature of the n+1th unit time period, the reference temperature calculation unit is used to obtain the reference temperature value and calculate the processing reference temperature, and the size correction value calculation unit is used to obtain the thermal expansion coefficient of the part and calculate the size correction value of the part.

9. The CNC lathe processing system based on precision correction according to claim 6, characterized in that: The temperature management module includes: an actual temperature management unit, a temperature detection value calculation unit, a threshold judgment unit and an alarm information management unit; Among them, the actual temperature management unit is used to obtain the actual temperature value of each working area, the temperature detection value calculation unit is used to obtain the temperature weight of the temperature sensor and calculate the temperature detection value in the n+1th unit time period, the threshold judgment unit is used to obtain the difference judgment threshold to judge whether the temperature difference is greater than the threshold, and the alarm information management unit is used to obtain the judgment condition. When the judgment condition is met, an alarm prompt is given to the lathe management personnel.

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