A temperature field reconstruction method

Abstract

The present application relates to the field of cutting tool temperature measurement, and particularly relates to an intelligent temperature measuring tool and a tool rake face temperature field reconstruction method based on inverse heat conduction. The present application comprises a blade arranged on a tool shank body, a blade surface groove, an ultra-fine thermocouple, a PCB circuit board, a battery and a data display device. The blade is connected to the tool shank body through a blade mounting screw, and the blade surface groove is arranged on the blade rake face. The present application proposes a tool rake face temperature field reconstruction method based on inverse heat conduction to solve the technical problem of tool temperature measurement in the turning process. By integrating advanced temperature measurement technology and mathematical modeling, the present application can realize temperature monitoring in a complex machining environment and effectively capture the temperature dynamic changes of the tool and workpiece contact area.

Description

Technical Field

[0001] This invention relates to the field of temperature measurement of cutting tools, specifically to an intelligent temperature-measuring tool and a method for reconstructing the temperature field of the tool rake face based on reverse heat conduction. Background Technology

[0002] During the cutting process, metal deformation is highly concentrated in a narrow area near the cutting edge on the tool's rake face. This area typically experiences the highest temperatures, making accurate temperature measurement in this region crucial for meeting the high demands of modern manufacturing. Due to the long and narrow shear band and the contact and movement between the tool and chips, measuring and predicting the temperature in the cutting zone is extremely challenging. High temperatures significantly impact tool wear, workpiece machining quality, and cutting stability, leading to tool thermal deformation, a significant source of error in the machining process. Current temperature measurement methods can achieve in-situ temperature measurement at limited points within the tool-chip contact area and outside this area, but obtaining the most critical temperature field and maximum temperature value in the tool-chip contact area remains difficult. Commonly used methods include non-contact measurement and artificial thermocouples. Non-contact measurement relies heavily on environmental parameter adjustments, resulting in significant uncertainty and subjectivity in temperature measurement. Artificial thermocouple temperature measurement requires multiple drillings on the workpiece, resulting in a limited measurement point and lacking continuous monitoring of transient cutting temperatures. This hinders intelligent machining processes, thus necessitating an intelligent temperature measurement method for tool and rake face temperature field reconstruction. Summary of the Invention

[0003] The technical problem to be solved by the present invention is to provide a method for reconstructing the temperature field of a thermocouple-based intelligent temperature measuring tool and the tool rake face, so as to accurately obtain the temperature distribution in the cutting area.

[0004] To solve the above technical problems, the present invention adopts the following technical solution:

[0005] The present invention includes a blade, a blade surface groove, an ultrafine thermocouple, a PCB circuit board, a battery, and a data display device disposed on a blade holder body; the blade is connected to the blade holder body by a blade mounting screw, and the blade surface groove is disposed on the blade rake face; the ultrafine thermocouple is disposed in the blade surface groove.

[0006] The following steps are taken when using the intelligent temperature-measuring cutting tool proposed in this invention to implement a method for reconstructing the temperature field of the tool rake face based on reverse heat conduction:

[0007] ①Establish an analytical model for heat transfer from a point heat source;

[0008] 101 point heat sources It instantaneously generates heat in an infinitely large medium, and after time... After that, any point The temperature rise is Solving the differential equation of heat conduction in solids using Fourier transform yields the instantaneous heat output from a point heat source. Specific heat capacity of the medium Density of the medium and the thermal diffusivity of the medium The analytical expression representing the temperature field is:

[0009] (one);

[0010] 102 point heat sources It continues to generate heat in an infinitely large medium, at the time of observation. any point The temperature rise is Using point heat source heat flux density and the thermal conductivity of the medium Represented as:

[0011] (two);

[0012] ②Establish a heat transfer model of the heat source on the cutting edge rake face;

[0013] 201 considers the contact surface between the chip formed during turning and the rake face of the cutting tool as the surface heat source region causing the temperature rise of the rake face, where the tool tip angle... The rounded tip of the knife Cutting depth Length of contact between cutting tool and chip The x-coordinate of the point of tangency between the tool tip arc and the secondary cutting edge is obtained as follows:

[0014] (three);

[0015] 202. The surface heat source is discretized along the tool-chip contact direction into a stationary, finite-length, continuously heating line heat source perpendicular to the tool-chip contact direction; at any given time... The x-coordinates of the points are respectively and Point heat sources on a line heat source pass through After emitting a certain amount of heat, and then after a period of time... Then, it led to the observation time. any point temperature rise and They are represented as follows:

[0016] (Four);

[0017] 203 respectively and Integrating, we can obtain the x-coordinates as follows: and Temperature rise caused by linear heat source and :

[0018] (five);

[0019] (six);

[0020] 204 time setting Place, The temperature rise caused by the surface heat source is , The temperature rise caused by the surface heat source is ,have ;

[0021] The entire surface heat source 205 continued to generate heat until the observation time. Point on the front face of the blade The temperature rise is Then we have:

[0022] (seven);

[0023] in For heat flux density, For point The initial temperature;

[0024] ③ Combining the heat source method and particle swarm optimization algorithm, the heat source intensity is calculated inversely, and the temperature field of the blade rake face near the blade tip and the chip contact area is solved.

[0025] The 301 algorithm combines particle swarm optimization with the heat source method for solving the temperature field of the cutting edge rake face, transforming the two-dimensional unsteady-state heat conduction inverse problem into an optimization problem for solution. The particle velocity and position are updated according to the following formula:

[0026] (eight);

[0027] in, For the first The iteration, the The speed of each particle; For the first The iteration, the The position of each particle; For the first The historical optimal position of each particle; This is the historical best position for the entire particle population; Inertial weight; Constraint factors; Cognitive factors; Social factors; for Random numbers between;

[0028] The heat source intensity of 302 is represented by a power series. The position of the particle represents a parameter in the heat source intensity expression. Each particle position corresponds to a heat source intensity expression, used to predict the temperature curve at the measurement point. The criterion for judging the quality of a particle position is the sum of the squared errors of the predicted temperature and the measured temperature, which is called fitness. ;

[0029] (Nine);

[0030] in, This represents the total number of time steps. For the first Time step, measure temperature; For the first Time step, number Individual particles, predicting temperature;

[0031] The optimization objective of the 303 particle swarm optimization algorithm is to find a heat flux density expression that minimizes the error between the predicted temperature and the measured temperature; the measured temperature is regarded as the predicted temperature to make the error zero, and the heat flux density is represented by the position of the particles.

[0032] (ten);

[0033] in, For the first The iteration, the The position of the first particle dimension; The highest order of the power series fitting method used to measure the temperature; The order of magnitude of the j-th coefficient used to fit the measured temperature using a power series;

[0034] In the first iteration, 304... The position of the first particle Vie de Di The first particle The dimensions are determined, while the dimensions of the first particle are random numbers between -1 and 1;

[0035] (eleven);

[0036] The inertia weight update method used by the 305 is as follows:

[0037] (twelve);

[0038] in, For the first The iteration, the The velocity of each particle; For the first The iteration, the The position of each particle; This represents the current iteration number; Maximum number of iterations.

[0039] The tip of the ultrafine thermocouple is positioned 1 mm from the blade tip. 2 Within the range, the other end is connected to the PCB circuit board; the data display device and the battery are both located on one side of the PCB circuit board.

[0040] The ultra-fine thermocouple has a cross-sectional dimension of 0.1 mm × 0.2 mm, and its end is spherical with a diameter of 0.25 mm.

[0041] The positive effects of this invention are as follows: Addressing the technical challenge of tool temperature measurement during turning, this invention proposes a tool rake face temperature field reconstruction method based on reverse heat conduction. By integrating advanced temperature measurement technology and mathematical modeling, this invention enables temperature monitoring in complex machining environments, effectively capturing the dynamic temperature changes in the tool-workpiece contact area. The reconstructed temperature field provides crucial data support for optimizing cutting parameters and real-time monitoring of the machining process, significantly improving machining accuracy and stability. This method not only identifies the thermal load on the tool during machining but also allows for timely adjustment of cutting strategies, preventing tool wear or failure due to overheating and extending tool life. By optimizing tool temperature distribution, this invention further improves workpiece machining quality and reduces machining errors caused by thermal deformation or material burns, making it particularly suitable for scenarios with high requirements for surface quality and precision. Furthermore, while achieving efficient temperature monitoring, this invention enhances the adaptability and intelligence of intelligent manufacturing systems. Its applicability covers various materials, tools, and machining conditions, and it is widely used in high-end manufacturing fields such as aerospace, automotive, and mold manufacturing, not only reducing production costs for enterprises but also providing new research directions and application value for the development of advanced manufacturing technologies. Attached Figure Description

[0042] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0043] Figure 1 This is a schematic diagram of the temperature measuring cutting tool structure of the present invention;

[0044] Figure 2 This is a schematic diagram of the embedding of the ultrafine thermocouple in the temperature measuring cutting tool of the present invention;

[0045] Figure 3 The coordinates of the temperature field on the rake face;

[0046] Figure 4 Temperature profiles obtained from the turning temperature measurement system;

[0047] Figure 5 The achieved rake face is 1mm. 2 Reconstruct the temperature field.

[0048] In the figure: 1. Tool holder body, 2. Blade, 201. Blade surface groove, 3. Ultra-fine thermocouple, 4. PCB circuit board, 5. Battery, 6. Data display device. Detailed Implementation

[0049] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0050] Establish a turning temperature measuring device characterizing the present invention:

[0051] like Figure 1-2 As shown, the turning temperature measuring device consists of a tool holder body 1, a cutting blade 2, a cutting blade surface groove 201, an ultra-fine thermocouple 3, a PCB circuit board 4, a battery 5, and a data display device 6. The cutting blade 2 has a prototype structure of APKT1235. The cutting blade 2 is mounted on the tool holder body 1 by cutting blade mounting screws; the cutting blade surface groove 201 is located near the cutting tip; the ultra-fine thermocouple 3 is bonded to the cutting blade surface groove 201 with a high-temperature resistant adhesive, and its end temperature measuring point is located within a 1 mm * 1 mm range of the cutting tip; the terminal of the ultra-fine thermocouple 3 is connected to the PCB circuit board 4, and the PCB circuit board 4 is connected to the data display device 6; the battery 5 is connected to the PCB circuit board 4 and is used to power the circuit board.

[0052] Implementation of the temperature field reconstruction method of the present invention:

[0053] The temperature field is reconstructed by combining the temperature data obtained from the turning temperature measurement system with the heat transfer model of the cutting tool 2. The steps are as follows:

[0054] ①Establish an analytical model for heat transfer from a point heat source;

[0055] 101 point heat sources After a certain amount of heat is instantaneously emitted in an infinitely large medium, time passes. After that, any point The temperature rise is Solving the differential equation of heat conduction in a solid using Fourier transform yields the instantaneous heat output from a point heat source. Specific heat capacity of the medium Density of the medium and the thermal diffusivity of the medium The analytical expression representing the temperature field is:

[0056] (one);

[0057] 102 thus obtains a point heat source It continues to generate heat in an infinitely large medium, at the time of observation. any point The temperature rise is Using point heat source heat flux density and the thermal conductivity of the medium Represented as:

[0058] (two);

[0059] ②Establish a heat transfer model of the heat source on the rake face of blade 2;

[0060] 201 Figure 3 The temperature field coordinates shown treat the contact surface between the chip formed during turning and the rake face of insert 2 as the surface heat source region causing the temperature rise of the rake face, where the tool tip angle is 93° and the tool tip radius is [missing information]. mm, depth of cut Length of contact between cutting tool and chip The x-coordinate of the point of tangency between the tool tip arc and the secondary cutting edge is obtained as follows:

[0061] (three);

[0062] 202. The surface heat source is discretized along the tool-chip contact direction into countless stationary, finite-length, continuously heating line heat sources with directions perpendicular to the tool-chip contact direction; at any given time... The x-coordinates of the points are respectively and Point heat sources on a line heat source pass through After emitting a certain amount of heat, after a period of time Then, it led to the observation time. any point temperature rise and They are represented as follows:

[0063] (Four);

[0064] 203 respectively and Integrating, we can obtain the x-coordinates as follows: and Temperature rise caused by linear heat source and :

[0065] (five);

[0066] (six);

[0067] 204 time setting Place, The temperature rise caused by the surface heat source is , The temperature rise caused by the surface heat source is ,have ;

[0068] 205 The entire surface heat source continuously generates heat, causing observation time Point on the front face of blade 2 The temperature rise is Then we have:

[0069] (seven);

[0070] in For heat flux density, For point Given the initial temperature and the intensity of the heat source, the temperature field can be derived.

[0071] ② Combine the heat source method and particle swarm optimization algorithm to inversely calculate the heat source intensity;

[0072] The 301 algorithm combines particle swarm optimization with the heat source method for solving the temperature field of the cutting edge 2, transforming the two-dimensional unsteady-state heat conduction inverse problem into an optimization problem for solution; the particle velocity and position can be updated according to the following formula:

[0073] (eight);

[0074] in, For the first The iteration, the The speed of each particle; For the first The iteration, the The position of each particle; For the first The historical optimal position of each particle; This is the historical best position for the entire particle population; Inertial weight; Constraint factors; Cognitive factors; Social factors; for Random numbers between;

[0075] The heat source intensity of 302 is represented by a power series, and the particle position represents a parameter in the heat source intensity expression. Each particle position corresponds to a heat source intensity expression. These expressions can be substituted into the temperature field solution formula to predict the temperature curve at the measurement point. The criterion for judging the quality of a particle position is the sum of the squared errors of the predicted temperature and the measured temperature, which is called fitness. ;

[0076] (Nine);

[0077] in, This represents the total number of time steps. For the first Time step, measure temperature; For the first Time step, number Individual particles, predicting temperature;

[0078] The optimization goal of the 303 particle swarm optimization algorithm is to find a heat flux density expression that minimizes the error between the predicted temperature and the measured temperature. The measured temperature can be regarded as the predicted temperature, so that the error is zero, and the heat flux density can be represented by the position of the particles.

[0079] (ten);

[0080] in, For the first The iteration, the The position of the first particle dimension; The highest order of the power series fitting method used to measure the temperature; The order of magnitude of the j-th coefficient used to fit the measured temperature using a power series;

[0081] In the first iteration, 304... The position of the first particle Vie de Di The first particle The dimensions are determined, while the dimensions of the first particle are random numbers between -1 and 1;

[0082] (eleven);

[0083] The 305 algorithm uses a larger inertia weight in the early stages of iteration to maintain the strength of the global search, while using a smaller inertia weight in the later stages to promote a more accurate local search. The inertia weight update method is as follows:

[0084] (twelve);

[0085] in, For the first The iteration, the The velocity of each particle; For the first The iteration, the The position of each particle; This represents the current iteration number; Maximum number of iterations.

[0086] Utilize Figure 4 The temperature curves shown are obtained by performing steps ① to ③ to achieve the following results. Figure 5 The blade shown has a 1 mm rake face. 2 Temperature field.

[0087] The embodiments described above are merely preferred embodiments of the present invention, and not an exhaustive list of all possible implementations of the present invention. Any obvious modifications made by those skilled in the art without departing from the principles and spirit of the present invention should be considered to be included within the scope of protection of the claims of the present invention.

Claims

1. A method for reconstructing a temperature field, characterized in that... It includes: The following components are mounted on the tool holder body (1): blade (2), blade surface groove (201), ultrafine thermocouple (3), PCB circuit board (4), battery (5), and data display device (6); the blade (2) is connected to the tool holder body (1) by blade mounting screws, and the blade surface groove (201) is set on the rake face of the blade (2); the ultrafine thermocouple (3) is set in the blade surface groove (201); the tool rake face temperature field reconstruction method based on reverse heat conduction is implemented using the blade (2), characterized by the following steps: ①Establish an analytical model for heat transfer from a point heat source; 101 point heat sources It instantaneously generates heat in an infinitely large medium, and after time... After that, any point The temperature rise is Solving the differential equation of heat conduction in solids using Fourier transform yields the instantaneous heat output from a point heat source. Specific heat capacity of the medium Density of the medium and the thermal diffusivity of the medium The analytical expression representing the temperature field is: (one); 102 point heat sources It continues to generate heat in an infinitely large medium, at the time of observation. any point The temperature rise is Using point heat source heat flux density and the thermal conductivity of the medium Represented as: (two); ②Establish a heat transfer model of the heat source on the rake face of the cutting tool (2); 201 The contact surface between the chip formed during turning and the rake face of the cutting tool (2) is regarded as the surface heat source region that causes the temperature rise of the rake face, wherein the tool tip angle The rounded tip of the knife Cutting depth Length of contact between cutting tool and chip The x-coordinate of the point of tangency between the tool tip arc and the secondary cutting edge is obtained as follows: (three); 202. The surface heat source is discretized along the tool-chip contact direction into a stationary, finite-length, continuously heating line heat source perpendicular to the tool-chip contact direction; at any given time... The x-coordinates of the points are respectively and Point heat sources on a line heat source pass through After emitting a certain amount of heat, and then after a period of time... Then, it led to the observation time. any point temperature rise and They are represented as follows: (Four); 203 respectively and Integrating, we can obtain the x-coordinates as follows: and Temperature rise caused by linear heat source and : (five); (six); 204 time setting place, The temperature rise caused by the surface heat source is , The temperature rise caused by the surface heat source is ,have ; The entire surface heat source 205 continued to generate heat until the observation time. The tip of the blade (2) on the rake face The temperature rise is Then we have: (seven); in For heat flux density, For point The initial temperature; ③ Combining the heat source method and particle swarm algorithm to inversely calculate the heat source intensity, the temperature field of the blade (2) near the tip and chip contact area on the front face is solved.

2. The temperature field reconstruction method according to claim 1, characterized in that, Step ③ includes: 301 combines the particle swarm optimization algorithm with the heat source method for solving the temperature field of the cutting edge (2) rake face, transforming the two-dimensional unsteady heat conduction inverse problem into an optimization problem for solution. The particle velocity and position are updated according to the following formula: (eight); in, For the first The iteration, the... The velocity of each particle; For the first The iteration, the... The position of each particle; For the first The historical optimal position of each particle; This is the historical best position for the entire particle population; Inertial weights; Constraint factors; Cognitive factors; Social factors; for Random numbers between; The heat source intensity of 302 is represented by a power series. The position of the particle represents a parameter in the heat source intensity expression. Each particle position corresponds to a heat source intensity expression, used to predict the temperature curve at the measurement point. The criterion for judging the quality of a particle position is the sum of the squared errors of the predicted temperature and the measured temperature, which is called fitness. ; (Nine); in, This represents the total number of time steps. For the first Time step, measure temperature; For the first Time step, number Individual particles, predicting temperature; The optimization objective of the 303 particle swarm optimization algorithm is to find a heat flux density expression that minimizes the error between the predicted temperature and the measured temperature; the measured temperature is regarded as the predicted temperature to make the error zero, and the heat flux density is represented by the position of the particles. (ten); in, For the first The iteration, the... The position of the first particle dimension; The highest order of the power series fitting is used to measure the temperature. The order of magnitude of the j-th coefficient used to fit the measured temperature using a power series; In the first iteration, 304... The position of the first particle Veyddi The first particle The dimensions are determined, while the dimensions of the first particle are random numbers between -1 and 1; (eleven); The inertia weight update method used by the 305 is as follows: (twelve); in, For the first The iteration, the... The velocity of each particle; For the first The iteration, the... The position of each particle; This represents the current iteration number; Maximum number of iterations.

3. The temperature field reconstruction method according to claim 1, characterized in that: The end of the ultrafine thermocouple (3) is set at the tip of the blade by 1 mm. 2 Within the range, the other end is connected to the PCB circuit board (4); the data display device (6) and the battery (5) are both located on one side of the PCB circuit board (4).

4. The temperature field reconstruction method according to claim 1, characterized in that: The ultrafine thermocouple (3) has a cross-sectional dimension of 0.1 mm × 0.2 mm, and the end is spherical with a diameter of 0.25 mm.

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