Information processing device, industrial system, and machine tool control method

Abstract

The information processing device includes an acquisition unit (10) that acquires a thermal image showing the temperature distribution of industrial equipment having a movable part that can be moved by a drive mechanism, a pre-processing unit (12) that changes pixels from which temperature data is extracted based on the position of the movable part when the thermal image was captured, and a thermal change amount estimation unit (13) that estimates the thermal change amount of the industrial equipment based on the extracted temperature data. The information processing device can easily estimate the thermal change amount when a heat-generating part of the industrial equipment moves.

Description

[Technical Field]

[0001] The present disclosure relates to an information processing device, an industrial system, and a method for controlling a machine tool. [Background technology]

[0002] In industrial equipment that uses a drive mechanism to move a moving part, heat generated during operation can deform the structure of the industrial equipment, potentially reducing the positioning accuracy of the moving part. For example, in a machine tool that moves a tool attached to a spindle, if the structure of the machine tool is deformed by heat, the position or orientation of the tool relative to the workpiece will change, resulting in machining errors. Changes in the position or orientation of the tool relative to the workpiece are referred to as thermal displacement of the machine tool.

[0003] Patent Document 1 discloses an error analysis device that analyzes errors in industrial equipment, which generates a model through machine learning of a data set in which thermal images of the industrial equipment during operation are paired with errors, and estimates the amount of thermal displacement of the industrial equipment based on the model and the acquired thermal images. The error analysis device disclosed in Patent Document 1 determines the mechanical structure that has a large influence on the thermal displacement, and estimates the amount of thermal displacement by acquiring the temperature of the mechanical structure that contributes greatly to the thermal displacement. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] International Publication No. 2023 / 188493 Summary of the Invention [Problem to be solved by the invention]

[0005] The conventional technology disclosed in Patent Document 1 does not take into consideration the case where the heat-generating portion of the industrial equipment moves as the moving parts move. Therefore, when estimating the amount of thermal displacement using the conventional technology, a thermal image is acquired when the mechanical structure of the industrial equipment is in the same position as when the thermal image used to generate the model was captured. Furthermore, if the heat-generating portion of the industrial equipment moves as the moving parts move, re-learning is required using a thermal image taken when the heat-generating portion has moved. Therefore, the conventional technology has the problem of making it difficult to estimate the amount of thermal displacement when the heat-generating portion of the industrial equipment moves.

[0006] The present disclosure has been made in view of the above, and aims to provide an information processing device that can easily estimate the amount of thermal displacement when a heat-generating portion of industrial equipment moves. [Means for solving the problem]

[0007] In order to solve the above-mentioned problems and achieve the objectives, the information processing device of the present disclosure includes an acquisition unit that acquires a thermal image showing the temperature distribution of industrial equipment having a movable part that can be moved by a drive mechanism, a pre-processing unit that changes pixels from which temperature data is extracted among multiple pixels that make up the thermal image based on the position of the movable part when the thermal image was captured, and a thermal displacement estimation unit that estimates the thermal displacement of the industrial equipment based on the extracted temperature data. [Effects of the Invention]

[0008] The information processing device according to the present disclosure has an effect of being able to easily estimate the amount of thermal change when a heat-generating portion of industrial equipment moves. [Brief explanation of the drawings]

[0009] [Figure 1] FIG. 1 is a diagram showing a configuration example of an industrial system according to a first embodiment; [Figure 2] FIG. 1 is a diagram showing a configuration example of a machine tool included in an industrial system according to a first embodiment; [Figure 3]FIG. 1 is a first diagram for explaining a thermal image captured by a thermal image sensor included in the industrial system according to the first embodiment; [Figure 4] FIG. 2 is a second diagram for explaining a thermal image captured by the thermal image sensor included in the industrial system according to the first embodiment; [Figure 5] FIG. 3 is a third diagram for explaining a thermal image captured by the thermal image sensor included in the industrial system according to the first embodiment. [Figure 6] FIG. 1 is a diagram for explaining processing by a preprocessing unit included in an industrial system according to a first embodiment. [Figure 7] 1 is a flowchart showing an example of an operation procedure of an industrial system according to the first embodiment. [Figure 8] FIG. 10 is a diagram showing a configuration example of an industrial system according to a second embodiment. [Figure 9] FIG. 10 is a diagram showing a configuration example of an industrial system according to a third embodiment. [Figure 10] FIG. 10 is a diagram showing an example of a result of determining whether or not there is an abnormality by a determination unit included in the industrial system according to the third embodiment. [Figure 11] FIG. 10 is a diagram showing an example of a thermal image displayed by a display unit included in the industrial system according to the third embodiment. [Figure 12] FIG. 10 is a diagram showing a configuration example of an industrial system according to a fourth embodiment. [Figure 13] FIG. 1 is a diagram showing an example of a hardware configuration for realizing a control device according to first to third embodiments. [Figure 14] FIG. 10 is a diagram showing an example of a hardware configuration for realizing a server device according to a fourth embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0010] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS An information processing device, an industrial system, and a method for controlling a machine tool according to embodiments will be described in detail below with reference to the accompanying drawings.

[0011] Embodiment 1 FIG. 1 is a diagram showing an example configuration of an industrial system 1A according to a first embodiment. The industrial system 1A includes a control device 2A, a machine tool 3 that is industrial equipment, and a thermal image sensor 4. The control device 2A controls the machine tool 3. The thermal image sensor 4 captures a thermal image showing the temperature distribution of the machine tool 3. The control device 2A functions as an information processing device that processes information shown in the thermal image captured by the thermal image sensor 4.

[0012] FIG. 2 is a diagram showing an example of the configuration of machine tool 3 included in industrial system 1A according to the first embodiment. In the first embodiment, machine tool 3 is a vertical cutting machine with three orthogonal axes. The X-axis, Y-axis, and Z-axis are three axes that are perpendicular to one another. Machine tool 3 machines a workpiece while moving the tool and workpiece relative to one another by driving multiple axes that are feed axes. In FIG. 2, the direction of the arrow representing the X-axis is the positive X-direction, and the opposite side of the positive X-direction is the negative X-direction. The direction of the arrow representing the Y-axis is the positive Y-direction, and the opposite side of the positive Y-direction is the negative Y-direction. The direction of the arrow representing the Z-axis is the positive Z-direction, and the opposite side of the positive Z-direction is the negative Z-direction.

[0013] The machine tool 3 includes a bed 30 which is the base of the machine tool 3, a column 31 fixed to the bed 30, a table 32 to which a workpiece 35 is fixed, a head 33 supported by the column 31, and a spindle 34 attached to the head 33. A tool 36 is attached to the spindle 34.

[0014] The machine tool 3 includes a spindle drive system, an X-axis drive system 37X, a Y-axis drive system 37Y, and a Z-axis drive system 37Z. The spindle drive system rotates a tool 36 attached to a spindle 34. The tool 36 is rotated by the driving force of a motor provided in the spindle drive system. The spindle drive system is not shown in the figure. Each of the X-axis drive system 37X, the Y-axis drive system 37Y, and the Z-axis drive system 37Z is a linear feed drive system.

[0015] X-axis drive system 37X has a ball screw, a motor for rotating the ball screw, and a mechanism for converting the rotational motion of the ball screw into linear motion in the X-axis direction. X-axis drive system 37X drives head 33 in the X-axis direction. Y-axis drive system 37Y has a ball screw, a motor for rotating the ball screw, and a mechanism for converting the rotational motion of the ball screw into linear motion in the Y-axis direction. Y-axis drive system 37Y drives table 32 in the Y-axis direction. Z-axis drive system 37Z has a ball screw, a motor for rotating the ball screw, and a mechanism for converting the rotational motion of the ball screw into linear motion in the Z-axis direction. Z-axis drive system 37Z drives head 33 in the Z-axis direction. Machine tool 3 moves tool 36 with X-axis drive system 37X and Z-axis drive system 37Z, and moves workpiece 35 with Y-axis drive system 37Y, thereby moving workpiece 35 and tool 36 relative to each other.

[0016] The X-axis drive system 37X and the Z-axis drive system 37Z constitute a drive mechanism that drives the spindle 34 to which the tool 36 is attached. The Y-axis drive system 37Y constitutes a drive mechanism that drives the table 32 to which the workpiece 35 is fixed. The spindle 34 and the table 32 are each movable parts that can be moved by the drive mechanism.

[0017] The spindle drive system, X-axis drive system 37X, Y-axis drive system 37Y, and Z-axis drive system 37Z are each connected to a control device 2A. The control device 2A generates commands for controlling each drive system in accordance with a machining program, which is an NC (Numerical Control) program, and sends the commands to each drive system. The spindle drive system rotates the tool 36 in accordance with the commands. The X-axis drive system 37X and Z-axis drive system 37Z each drive the spindle 34 in accordance with the commands. The Y-axis drive system 37Y drives the table 32 in accordance with the commands.

[0018] In the first embodiment, deformation of the structure of machine tool 3 due to the influence of heat is referred to as thermal deformation. Deformation of the structure of machine tool 3 refers to deformation of the structural members of machine tool 3 or deformation of each component of the drive system of machine tool 3. The structural members of machine tool 3 are bed 30, column 31, table 32, and head 33. When the position of tool 36 relative to workpiece 35 changes due to thermal deformation of machine tool 3, the amount of movement of tool 36 relative to workpiece 35 is referred to as the amount of thermal displacement of machine tool 3.

[0019] In the above description, the machine tool 3 has a three-axis linear feed drive system. However, the machine tool 3 is not limited to one having a three-axis linear feed drive system. The machine tool 3 may also be a lathe or the like having a two-axis linear feed drive system.

[0020] As shown in FIG. 1, the control device 2A includes an acquisition unit 10, a recording unit 11, a preprocessing unit 12, a thermal displacement estimation unit 13, a correction amount generation unit 14, a control unit 15, a display unit 16, a learning unit 17, and a model holding unit 18.

[0021] The thermal image sensor 4 captures a thermal image showing the temperature distribution of the machine tool 3 and transmits the thermal image to the control device 2A. The acquisition unit 10 receives the thermal image transmitted by the thermal image sensor 4. As a result, the acquisition unit 10 acquires a thermal image showing the temperature distribution of the machine tool 3. The acquisition unit 10 outputs data of the acquired thermal image to the recording unit 11. The recording unit 11 records the thermal image acquired by the acquisition unit 10.

[0022] The control device 2A may convert the thermal image data into compressed data by compressing and encoding the thermal image acquired by the acquisition unit 10. In this case, the recording unit 11 records the compressed data obtained by compressing and encoding the thermal image.

[0023] The pre-processing unit 12 reads the thermal image data from the recording unit 11 and processes the read data. The pre-processing unit 12 performs a process to extract temperature data from the thermal image. The pre-processing unit 12 changes the pixel from which temperature data is extracted, among the multiple pixels that make up the thermal image, based on the position of the movable part when the thermal image was captured. The pre-processing unit 12 outputs the extracted temperature data to the thermal displacement amount estimation unit 13.

[0024] The thermal change amount estimation unit 13 estimates the thermal change amount of the machine tool 3 based on the temperature data extracted by the preprocessing unit 12. The thermal change amount estimation unit 13 outputs information indicating the estimated thermal change amount to the correction amount generation unit 14.

[0025] The correction amount generation unit 14 calculates a correction amount for the position of the movable part, i.e., the spindle 34 or the table 32, based on the thermal change amount estimated by the thermal change amount estimation unit 13. The correction amount generation unit 14 outputs information indicating the calculated correction amount to the control unit 15.

[0026] The control unit 15 generates commands according to the machining program and sends the commands to each drive system of the machine tool 3. The control unit 15 controls the machine tool 3 by sending commands to each drive system. Furthermore, when information indicating a correction amount is input to the control unit 15, the control unit 15 generates commands that reflect the correction amount. As a result, the control unit 15 controls the machine tool 3 based on the commands that reflect the correction amount calculated by the correction amount generation unit 14. The machine tool 3 sends information indicating the positions of the spindle 34 in the X-axis direction and the Z-axis direction and information indicating the position of the table 32 in the Y-axis direction to the control device 2A. That is, the control device 2A receives position information indicating the position of the movable part from the machine tool 3. The control unit 15 adjusts the control of the machine tool 3 based on the error between the position indicated in the position information and the commanded position. Furthermore, the control unit 15 outputs the position information indicating the position of the movable part to the preprocessing unit 12.

[0027] The display unit 16 reads out the thermal image from the recording unit 11 and displays the thermal image. The control device 2A outputs the thermal image read out from the recording unit 11 by displaying the thermal image read out from the recording unit 11 on the display unit 16.

[0028] The learning unit 17 learns the relationship between the temperature of the machine tool 3 and the amount of thermal change of the machine tool 3. The learning unit 17 generates a model that is a result of learning the relationship between the temperature of the machine tool 3 and the amount of thermal change of the machine tool 3. The learning unit 17 outputs the generated model to the model holding unit 18. The model holding unit 18 holds the model generated by the learning unit 17.

[0029] Thermal change amount estimation unit 13 reads out the model from model storage unit 18 and inputs the temperature data extracted from the thermal image into the model, thereby estimating the thermal change amount of machine tool 3. In other words, thermal change amount estimation unit 13 estimates the thermal change amount of machine tool 3 by inputting the temperature data into a model that is the result of learning the relationship between the temperature of machine tool 3 and the thermal change amount of machine tool 3.

[0030] The thermal image sensor 4 has a plurality of infrared detection elements corresponding to pixels. The thermal image sensor 4 outputs a value corresponding to the amount of infrared light captured by each infrared detection element in a given time. If the thermal image sensor 4 captures an image while the moving part is moving, the value output from the thermal image sensor 4 will fluctuate depending on the speed at which the moving part is moving.

[0031] Therefore, the thermal image sensor 4 may be configured to capture a thermal image when the moving speed of the movable part is equal to or less than a preset speed. That is, the acquisition unit 10 may be configured to acquire a thermal image captured when the moving speed of the movable part is equal to or less than a preset speed. This allows the control device 2A to reduce errors in temperature data caused by the movement of the movable part, and to obtain a highly accurate thermal image.

[0032] Next, a description will be given of a thermal image captured by the thermal image sensor 4. Fig. 3 is a first diagram for describing a thermal image captured by the thermal image sensor 4 included in the industrial system 1A according to the first embodiment. Fig. 4 is a second diagram for describing a thermal image captured by the thermal image sensor 4 included in the industrial system 1A according to the first embodiment. Fig. 5 is a third diagram for describing a thermal image captured by the thermal image sensor 4 included in the industrial system 1A according to the first embodiment.

[0033] The thermal image captured by the thermal image sensor 4 consists of multiple pixels arranged in two dimensions. In the examples shown in Figures 3 to 5, the thermal image has six pixels arranged vertically and six pixels arranged horizontally. A pixel is the smallest unit that makes up a thermal image. A thermal image visually represents the temperature value indicated by each pixel. In the examples shown in Figures 3 to 5, the thermal image sensor 4 captures an image of the side of the machine tool 3. Figure 3 shows a simplified view of the side of the machine tool 3, with the capture range of the thermal image sensor 4 superimposed on the side of the machine tool 3. The dashed lines in Figure 3 indicate pixel boundaries.

[0034] The value of each pixel in the thermal image represents the temperature detected by the thermal image sensor 4. In FIG. 4, the difference in temperature shown in each pixel is represented by the shade of the halftone dot tone. In FIG. 4, the darker the halftone dot tone, the higher the temperature. In FIG. 5, the temperature shown in each pixel is represented by a numerical value. In FIG. 5, the unit of temperature is Celsius degrees.

[0035] The display unit 16 displays a thermal image as shown in Fig. 4. The display unit 16 may also display a numerical representation of temperature as shown in Fig. 5 together with or instead of the thermal image. The display unit 16 may also display a thermal image as shown in Fig. 4 superimposed on a simplified diagram of the configuration of the machine tool 3 as shown in Fig. 3.

[0036] While FIG. 3 illustrates an example in which one thermal image sensor 4 captures an image of the entire side of the machine tool 3, this is not limiting. The thermal image sensor 4 may capture an image of the machine tool 3 in any direction. The industrial system 1A may also capture an image of the machine tool 3 using multiple thermal image sensors 4. In this case, the acquisition unit 10 acquires thermal images output from each of the multiple thermal image sensors 4. The thermal image sensor 4 may also capture only a portion of the machine tool 3 rather than the entire machine tool 3. In this case, the acquisition unit 10 acquires a thermal image of only a portion of the machine tool 3, rather than a thermal image of the entire machine tool 3. The industrial system 1A may also acquire the temperature distribution of the entire machine tool 3 or a portion of the machine tool 3 by stitching together multiple thermal images captured by multiple thermal image sensors 4. The number of pixels constituting a thermal image is not limited to the above and may be any number.

[0037] Next, the processing by the pre-processing unit 12 will be described. Here, a specific method for changing the pixels from which temperature data is extracted depending on the position of the main shaft 34, which is a movable part, when the main shaft 34 is in operation, will be described. As a preliminary step, the pre-processing unit 12 determines the relationship between the movement distance of the main shaft 34 and the number of pixels in the thermal image that corresponds to the movement distance of the main shaft 34. Thereafter, the pre-processing unit 12 performs processing to change the pixels from which temperature data is extracted based on the relationship determined in the preliminary step and the movement distance of the main shaft 34 from a predetermined reference position.

[0038] In the advance preparation, the pre-processing unit 12 executes the first and second steps described below. In the first step, the pre-processing unit 12 creates a data set that associates a thermal image with position information of the spindle 34. The control device 2A causes the machine tool 3 to perform an operation to position the spindle 34 at each of two preset points, a first position and a second position. The thermal image sensor 4 captures a thermal image when the spindle 34 is positioned at the first position and a thermal image when the spindle 34 is positioned at the second position. The acquisition unit 10 acquires a thermal image when the spindle 34 is positioned at the first position and a thermal image when the spindle 34 is positioned at the second position, and records these acquired thermal images in the recording unit 11. The pre-processing unit 12 reads these thermal images from the recording unit 11.

[0039] Furthermore, the pre-processing unit 12 receives from the control unit 15 positional information of the spindle 34 when the spindle 34 is positioned at the first position and positional information of the spindle 34 when the spindle 34 is positioned at the second position. That is, the pre-processing unit 12 acquires positional information indicating the first position and positional information indicating the second position from the control unit 15. As a result, the pre-processing unit 12 generates a data set in which a thermal image taken when the spindle 34 is positioned at the first position is associated with the positional information indicating the first position, and a data set in which a thermal image taken when the spindle 34 is positioned at the second position is associated with the positional information indicating the second position.

[0040] FIG. 6 is a diagram for explaining processing by the pre-processing unit 12 included in the industrial system 1A according to the first embodiment. FIG. 6 shows a simplified side view of the machine tool 3, with the imaging range of the thermal image sensor 4 superimposed on the side view of the machine tool 3. The dashed lines in FIG. 6 represent pixel boundaries. The left side of FIG. 6 shows the side view and imaging range of the machine tool 3 when the spindle 34 is positioned at a first position. The up-down direction in the thermal image corresponds to the Z-axis direction, and the left-right direction in the thermal image corresponds to the Y-axis direction. The right side of FIG. 6 shows the side view and imaging range of the machine tool 3 when the spindle 34 is positioned at a second position. Line L1 in FIG. 6 represents the Z-axis position of the tip of the tool 36 when the spindle 34 is positioned at the first position. Line L2 in FIG. 6 represents the Z-axis position of the tip of the tool 36 when the spindle 34 is positioned at the second position.

[0041] Next, in a second step, the preprocessing unit 12 determines the relationship between the movement distance of the main shaft 34 and the number of pixels based on the data set generated in the first step. Here, it is assumed that the movement of the main shaft 34 from the first position to the second position is a movement of 300 mm in the minus Z direction. The double-headed arrow in FIG. 6 indicates the movement distance of the main shaft 34. Based on the position information indicating the first position and the position information indicating the second position, the preprocessing unit 12 determines that the movement direction of the main shaft 34 is the minus Z direction and that the movement distance of the main shaft 34 is 300 mm. In this way, the preprocessing unit 12 calculates the movement direction and movement distance of the movable unit based on the position information included in each data set.

[0042] The pre-processing unit 12 also determines the direction of movement of the image of the main shaft 34 on the thermal image and the number of pixels by which the image of the main shaft 34 has moved on the thermal image. In the example shown in Fig. 6, the image of the main shaft 34 has moved three pixels from top to bottom on the thermal image. The pre-processing unit 12 analyzes the thermal images included in each data set to determine the direction of movement of the image of the moving part and the number of pixels by which the image of the moving part has moved.

[0043] In the example described here, a movement of 300 mm in the minus Z direction corresponds to a movement of three pixels from top to bottom on the thermal image. This determines the relationship that for every 100 mm of movement of the main shaft 34 in the minus Z direction, the image of the main shaft 34 moves one pixel from top to bottom on the thermal image. In this way, the pre-processing unit 12 determines the relationship between the movement distance of the main shaft 34 and the number of pixels. The pre-processing unit 12 also determines the relationship between the movement direction of the movable part and the movement direction of the image on the thermal image.

[0044] In the above description, the pre-processing unit 12 determines the relationship between the number of pixels in the thermal image through which the image of the main shaft 34 has moved and the distance traveled by the main shaft 34. The pre-processing unit 12 may also determine the relationship between the number of pixels through which a portion appearing in a characteristic part of the thermal image, for example, a portion having a higher temperature than the surrounding area, has moved and the distance traveled by the main shaft 34.

[0045] When a thermal image for estimating the amount of thermal displacement is acquired, the preprocessing unit 12 executes the third and fourth steps described below. In the third step, the preprocessing unit 12 determines the direction of movement of the portion on the thermal image from which temperature data is extracted and the number of pixels to which the portion from which temperature data is extracted has moved. The portion from which temperature data is extracted is a portion that exhibits a characteristic feature in the thermal image, for example, a portion of the machine tool 3 that has a higher temperature than the surrounding area. Hereinafter, the portion from which temperature data is extracted is also referred to as a characteristic portion.

[0046] Here, the state in which the spindle 34 is positioned at a preset reference position is defined as the reference state. The pre-processing unit 12 calculates the direction of movement of the characteristic feature on the thermal image and the number of pixels that the characteristic feature has moved when the spindle 34 moves from the reference state to the state when the thermal image was acquired.

[0047] When a thermal image for estimating the amount of thermal displacement is captured by the thermal image sensor 4, the acquisition unit 10 acquires the captured thermal image and records the acquired thermal image in the recording unit 11. The pre-processing unit 12 reads out the thermal image for estimating the amount of thermal displacement from the recording unit 11. The pre-processing unit 12 also receives, from the control unit 15, position information of the spindle 34 when the spindle 34 is positioned at a preset reference position and position information of the spindle 34 when the thermal image for estimating the amount of thermal displacement was captured. Here, the preset reference position is the first position described above.

[0048] The pre-processing unit 12 calculates the movement direction and movement distance of the spindle 34 when the spindle 34 moves from the reference state to the state when the thermal image was acquired. The pre-processing unit 12 calculates the movement direction and movement distance of the spindle 34 based on the position information of the spindle 34 in the reference state and the position information of the spindle 34 when the thermal image for estimating the amount of thermal displacement was captured. Here, it is assumed that the movement direction of the spindle 34 is calculated to be the minus Z direction and the movement distance of the spindle 34 is calculated to be 500 mm.

[0049] The pre-processing unit 12 calculates the movement direction of the characteristic feature on the thermal image and the number of pixels moved by the characteristic feature based on the calculation results of the movement direction and movement distance and the relationship between the movement distance of the spindle 34 and the number of pixels calculated in the second step. The relationship is such that the image of the spindle 34 moves one pixel from top to bottom on the thermal image for every 100 mm of movement of the spindle 34 in the minus Z direction. Based on the calculation results and the relationship, the pre-processing unit 12 estimates that the movement of the characteristic feature on the thermal image is a movement of five pixels from top to bottom on the thermal image.

[0050] Next, in the fourth step, the pre-processing unit 12 performs processing to change the pixels from which temperature data is extracted. The pre-processing unit 12 identifies the positions of characteristic portions in the thermal image captured under the reference condition.

[0051] Here, a pixel in a thermal image is represented by the coordinates (a, b). "a" is a variable that represents the position in the left-right direction of the thermal image. "b" is a variable that represents the position in the up-down direction of the thermal image. Each pixel is assigned an "a" value from left to right in the thermal image, such as a=0,1,2,..., and a "b" value from bottom to top in the thermal image, such as b=0,1,2,...,.

[0052] As an example, assume that the position of a characteristic feature in a thermal image captured under the reference condition is identified as (5,10). As described above, in the third step, the movement of the characteristic feature on the thermal image is estimated to be a movement of five pixels from top to bottom. Based on this estimation result, the pre-processing unit 12 estimates that the position of the characteristic feature has moved to (5,5) in the thermal image for estimating the amount of thermal displacement. As a result, the pre-processing unit 12 changes the pixel from which temperature data is extracted from the pixel (5,10) to the pixel (5,5). In this way, in the thermal image for estimating the amount of thermal displacement, the pixel from which temperature data is extracted is changed to a pixel different from the pixel from which temperature data was extracted in the thermal image under the reference condition.

[0053] By completing the fourth step, the pre-processing unit 12 extracts temperature data from the pixel at (5, 5). The pre-processing unit 12 outputs the extracted temperature data to the thermal change amount estimation unit 13.

[0054] In this way, when the movable part moves, the control device 2A estimates the direction and distance of movement of the characteristic part on the thermal image and changes the pixel from which temperature data is extracted. Even when the movable part moves, the control device 2A can estimate the amount of thermal displacement based on the temperature data for the same characteristic part. This allows the control device 2A to accurately estimate the amount of thermal displacement even when the thermal image taken is in a state where the movable part has moved from the time the thermal image used to generate the model was taken.

[0055] Next, we will explain the estimation of the thermal change amount by thermal change amount estimation unit 13. Thermal change amount estimation unit 13 estimates the thermal change amount of machine tool 3 based on the temperature data extracted by preprocessing unit 12. Thermal change amount estimation unit 13 estimates the thermal change amount by inputting the temperature data into a model read out from model holding unit 18.

[0056] As an example, the thermal displacement estimation unit 13 estimates the amount of thermal displacement by inputting temperature data shown in the acquired thermal image into a model. As one example, the model used to estimate the amount of thermal displacement is generated by the learning unit 17 performing machine learning using a neural network. The neural network is composed of an input layer consisting of multiple neurons, a hidden layer which is an intermediate layer consisting of multiple neurons, and an output layer consisting of multiple neurons. Temperature data extracted by the preprocessing unit 12 is input to the input layer. The amount of thermal displacement is output from the output layer. The neural network is generated by adjusting the weights so that the output for the input approaches the label. The number of neurons in the input layer is determined by the amount of information selected as input data. The number of neurons in the intermediate layer is assumed to be arbitrary.

[0057] The model used to estimate the amount of thermal displacement is not limited to one generated by machine learning using a neural network. The model used to estimate the amount of thermal displacement may also be a model generated by finite element analysis. In finite element analysis, the structure of the machine tool 3 is divided into multiple infinitesimal elements, and a regression model is set for each of the multiple infinitesimal elements. In this case, the thermal stress when the actual measured temperature is applied to each infinitesimal element is determined, and the amount of thermal displacement of the machine tool 3 is calculated from the thermal stress determined for each infinitesimal element.

[0058] The thermal change amount estimation unit 13 may estimate the thermal change amount based on the temperature data shown in one thermal image, or may estimate the thermal change amount based on the temperature data shown in each of a plurality of thermal images. The thermal change amount estimation unit 13 may also estimate the thermal change amount based on the temperature data shown in the currently acquired thermal image and the temperature data shown in thermal images acquired in the past.

[0059] Here, an example of estimating the amount of thermal change based on temperature data shown in a currently acquired thermal image and temperature data shown in a previously acquired thermal image will be described. The thermal change amount estimation unit 13 calculates the difference between the temperature data shown in the currently acquired thermal image and the temperature data shown in a previously acquired thermal image. The thermal change amount estimation unit 13 calculates the amount of thermal change based on the temperature change obtained by multiplying the difference by a coefficient. For example, when using a multiple regression model, the thermal change amount estimation unit 13 calculates the amount of thermal change using the following formula: Thermal displacement = (T1_t1-T1_t0)*K1+(T2_t1-T2_t0)*K2++(Tn_t1-Tn_t0)*Kn

[0060] Here, the time when the current thermal image was taken is t1, and the time when the previous thermal image was taken is t2. Each pixel in the thermal image is assigned a pixel number 1, 2,...,n to identify the pixel. T1_t1, T2_t1,...,Tn_t1 are the temperatures indicated by the pixels with pixel numbers 1, 2,...,n in the thermal image at time t1. T1_t0, T2_t0,...,Tn_t0 are the temperatures indicated by the pixels with pixel numbers 1, 2,...,n in the thermal image at time t0. K1, K2,...,Kn are the coefficients set for the pixels with pixel numbers 1, 2,...,n.

[0061] When estimating the amount of thermal change based on the temperature data shown in each of the thermal images, the thermal change amount estimating unit 13 may calculate the average value of the temperature data for each pixel. By estimating the amount of thermal change based on the average value, the thermal change amount estimating unit 13 can reduce the influence of noise contained in the temperature data of each thermal image.

[0062] The model used to estimate the amount of thermal change may be the result of learning the relationship between the temperature data shown in a thermal image acquired at a certain time, the temperature data shown in a thermal image acquired at a time that is a predetermined time Δt before the time, and the amount of thermal change. In this case, the thermal change amount estimator 13 estimates the amount of thermal change by inputting the temperature data shown in a thermal image acquired at a certain time and the temperature data shown in a thermal image acquired at a time that is Δt before the time into the model.

[0063] In the above description, the learning unit 17 is assumed to be provided inside the control device 2A. That is, the thermal change amount estimation unit 13 estimates the thermal change amount based on a model generated by the learning unit 17 inside the control device 2A. The control device 2A may use a model generated outside the control device 2A to estimate the thermal change amount, rather than a model generated inside the control device 2A. In this case, the control device 2A acquires a model generated by a learning device outside the control device 2A, and estimates the thermal change amount using the acquired model.

[0064] Next, an operation procedure of the industrial system 1A will be described. Fig. 7 is a flowchart showing an example of the operation procedure of the industrial system 1A according to the first embodiment. Here, an operation will be described in which, when a workpiece 35 is machined by the machine tool 3, the amount of thermal displacement of the machine tool 3 is estimated and the machine tool 3 is controlled.

[0065] In step S1, the machine tool 3 starts machining the workpiece 35. The machine tool 3 machines the workpiece 35 in accordance with commands sent from the control device 2A. The thermal image sensor 4 captures a thermal image of the machine tool 3. In step S2, the acquisition unit 10 of the control device 2A acquires the thermal image captured by the thermal image sensor 4. The thermal image acquired by the acquisition unit 10 is recorded in the recording unit 11.

[0066] In step S3, the pre-processing unit 12 changes the pixels from which temperature data is extracted among the multiple pixels constituting the thermal image. The pre-processing unit 12 reads the thermal image data from the recording unit 11. The pre-processing unit 12 changes the pixels from which temperature data is extracted based on the position of the movable part when the thermal image was captured. In this example, the pre-processing unit 12 changes the pixels from which temperature data is extracted based on the position of the main shaft 34 when the thermal image was captured. The pre-processing unit 12 extracts temperature data from the changed pixels.

[0067] In step S4, the thermal change amount estimation unit 13 estimates the thermal change amount of the machine tool 3 based on the temperature data extracted by the preprocessing unit 12. The thermal change amount estimation unit 13 outputs information indicating the estimated thermal change amount to the correction amount generation unit 14.

[0068] In step S5, the correction amount generation unit 14 calculates the correction amount for the position of the spindle 34 based on the amount of thermal change estimated in step S4. The correction amount generation unit 14 outputs information indicating the calculated correction amount to the control unit 15.

[0069] In step S6, control unit 15 controls machine tool 3 based on a command reflecting the amount of correction calculated in step S5. Control unit 15 generates a command reflecting the amount of correction and sends the command to each drive system of machine tool 3, thereby controlling machine tool 3 based on the command reflecting the amount of correction.

[0070] In step S7, the machine tool 3 determines whether or not to end the machining of the workpiece 35. If the machining of the workpiece 35 is not to be ended (step S7, No), the industrial system 1A repeats the procedures from step S2 to step S7. On the other hand, if the machining of the workpiece 35 is to be ended (step S7, Yes), the industrial system 1A ends the operation according to the procedure shown in FIG.

[0071] According to the first embodiment, the control device 2A includes an acquisition unit 10 that acquires a thermal image, a preprocessing unit 12 that changes pixels from which temperature data is extracted based on the position of the movable part when the thermal image was captured, and a thermal change amount estimation unit 13 that estimates the amount of thermal change of the industrial equipment based on the extracted temperature data. By changing the pixels from which temperature data is extracted based on the position of the movable part, the control device 2A can estimate the amount of thermal change based on the temperature data of the same heat-generating part when the heat-generating part of the industrial equipment moves due to the movement of the movable part. The control device 2A can estimate the amount of thermal change without re-learning using a thermal image taken when the heat-generating part has moved. As described above, the control device 2A has the advantage of being able to easily estimate the amount of thermal change when the heat-generating part of the industrial equipment moves. By including the control device 2A, the industrial system 1A can easily estimate the amount of thermal change when the heat-generating part of the industrial equipment moves.

[0072] The control device 2A also includes a recording unit 11 that records the thermal images acquired by the acquisition unit 10. The control device 2A outputs the thermal images read from the recording unit 11. This allows the control device 2A to present the temperature distribution in the industrial equipment to the operator of the machine tool 3 in an easy-to-understand manner.

[0073] In addition, the compressed data obtained by compressing and encoding the thermal image is recorded in the recording unit 11. This allows the control device 2A to reduce the amount of data, allowing the thermal image to be recorded in the recording unit 11 with a small capacity.

[0074] The acquisition unit 10 also acquires thermal images taken when the moving speed of the movable part is equal to or less than a set speed, which allows the control device 2A to reduce errors in temperature data caused by the movement of the movable part and obtain highly accurate thermal images.

[0075] The thermal change amount estimation unit 13 estimates the thermal change amount of the industrial equipment by inputting the temperature data into a model that is the result of learning the relationship between the temperature of the industrial equipment and the thermal change amount of the industrial equipment. This allows the control device 2A to accurately estimate the thermal change amount of the industrial equipment based on the relationship between the temperature of the industrial equipment and the thermal change amount of the industrial equipment.

[0076] Embodiment 2 8 is a diagram showing a configuration example of an industrial system 1B according to embodiment 2. In embodiment 2, the same components as those in embodiment 1 above are denoted by the same reference numerals, and the configuration different from embodiment 1 will be mainly described.

[0077] The industrial system 1B includes a control device 2B, a machine tool 3 which is an industrial device, a thermal image sensor 4, and a temperature sensor 5. The control device 2B has a configuration similar to that of the control device 2A shown in FIG. 1. The temperature sensor 5 includes a thermistor or a thermocouple. The temperature sensor 5 is installed in the machine tool 3. The temperature sensor 5 measures the temperature of the machine tool 3. The temperature sensor 5 transmits temperature information indicating the measured temperature to the control device 2B.

[0078] The acquisition unit 10 receives the thermal image transmitted by the thermal image sensor 4 and the temperature information transmitted by the temperature sensor 5. The acquisition unit 10 outputs the thermal image data and the temperature information to the recording unit 11. The recording unit 11 records the thermal image and the temperature information.

[0079] The pre-processing unit 12 reads out the thermal image data and temperature information from the recording unit 11. The pre-processing unit 12 performs processing to extract temperature data from the thermal image. The pre-processing unit 12 also corrects the temperature data shown in the thermal image based on the temperature information. That is, the pre-processing unit 12 corrects the temperature data shown in the thermal image based on the temperature measurement results obtained by the temperature sensor 5 installed in the machine tool 3.

[0080] Here, a specific example of temperature data correction by the pre-processing unit 12 will be described. The pre-processing unit 12 references the temperature data shown in the thermal image for the same portion of the machine tool 3 as the portion whose temperature was measured by the temperature sensor 5. The pre-processing unit 12 calculates the difference between the temperature shown in the referenced temperature data and the temperature measured by the temperature sensor 5. The pre-processing unit 12 corrects the temperature data by adding the difference to the temperature value shown in each pixel of the thermal image, or by subtracting the difference from the temperature value shown in each pixel of the thermal image. Note that the method of correcting the temperature data is not limited to the method described here and may be any method.

[0081] When capturing a thermal image over a long period of time, drift may occur, resulting in errors in the temperature displayed on the thermal image. According to the second embodiment, the control device 2B corrects the temperature data displayed on the thermal image based on the temperature measurement results from the temperature sensor 5, thereby enabling highly accurate temperature measurement using the thermal image. This allows the control device 2B to estimate the amount of thermal displacement with high accuracy.

[0082] Embodiment 3 9 is a diagram showing a configuration example of an industrial system 1C according to embodiment 3. In embodiment 3, the same components as those in embodiment 1 or 2 above are denoted by the same reference numerals, and the configuration different from embodiment 1 or 2 will be mainly described.

[0083] The industrial system 1C includes a control device 2C, a machine tool 3 which is industrial equipment, and a thermal image sensor 4. The control device 2C has the same configuration as the control device 2A shown in Fig. 1. Furthermore, the control device 2C includes a determination unit 19.

[0084] The determination unit 19 reads out the thermal image data from the recording unit 11. The determination unit 19 extracts temperature data from the thermal image. The determination unit 19 determines whether or not there is an abnormality in the machine tool 3 based on the temperature data extracted from the thermal image. The determination unit 19 outputs the result of determining whether or not there is an abnormality to the display unit 16. The display unit 16 displays information indicating whether or not there is an abnormality. The control device 2C outputs the determination result by the determination unit 19 by displaying the information indicating whether or not there is an abnormality on the display unit 16.

[0085] 10 is a diagram showing an example of the result of determining whether or not there is an abnormality by the determining unit 19 included in the industrial system 1C according to embodiment 3. For example, assume that the temperature near the spindle 34 of the machine tool 3 is measured as 60 degrees Celsius, which is higher than normal, based on a thermal image.

[0086] Here, a specific example of determining whether or not an abnormality is present by the determination unit 19 will be described. The determination unit 19 obtains the maximum value of the temperature measured by the thermal image, the minimum value of the temperature measured by the thermal image, and the difference between the maximum value and the minimum value. The determination unit 19 determines whether or not the maximum value or the minimum value is within a preset range. This range represents the range of temperatures when the machine tool 3 is normal. The determination unit 19 determines that an abnormality exists if the maximum value is outside this range. The determination unit 19 determines that an abnormality exists if the minimum value is outside this range. Furthermore, the determination unit 19 determines that an abnormality exists if the difference between the maximum value and the minimum value exceeds a preset threshold value.

[0087] In the example shown in FIG. 10, the maximum temperature measured by the thermal image is 60 degrees, and the minimum temperature measured by the thermal image is 20 degrees. The difference between the maximum and minimum values ​​is calculated to be 40 degrees. Here, 60 degrees is a value outside a preset range, and 20 degrees is a value within the range. The determination unit 19 determines that the maximum value of 60 degrees is abnormal, and that the minimum value of 20 degrees is normal. Furthermore, it is assumed that the difference between the maximum and minimum values, 40 degrees, exceeds a preset threshold. The determination unit 19 determines that this difference is abnormal.

[0088] As one example, the display unit 16 displays a table showing the determination results as shown in FIG. 10. In the example shown in FIG. 10, the words "spindle motor" indicating the location where the highest value was measured and "bed" indicating the location where the lowest value was measured are displayed together with the determination results. This allows the control device 2C to present the determination results on whether or not there is an abnormality to the operator in an easy-to-understand manner. For example, the display unit 16 displays a thermal image in which the temperature difference indicated by each pixel is expressed in grayscale, superimposed on a diagram showing a simplified configuration of the machine tool 3. This allows the control device 2C to present the temperature at each location of the machine tool 3 to the operator in an easy-to-understand manner. The display unit 16 may also display a table showing the determination results together with a thermal image superimposed on a diagram showing a simplified configuration of the machine tool 3.

[0089] The criteria for determining whether or not there is an abnormality may be set to a certain range for the entire machine tool 3, or different ranges may be set for each part of the machine tool 3. Furthermore, the display format of the determination results is not limited to that shown in Fig. 10 and may be arbitrary.

[0090] The method by which the determination unit 19 determines whether or not there is an abnormality in the machine tool 3 is not limited to the above-mentioned method and may be any method. For example, the determination unit 19 may determine whether or not there is an abnormality using a model generated by machine learning. As one example, the determination unit 19 may determine whether or not there is an abnormality based on a model generated by supervised learning, using thermal images labeled with an indication of normality or abnormality as training data.

[0091] 11 is a diagram showing an example of thermal image display by the display unit 16 of the industrial system 1C according to embodiment 3. In the example described here, the display unit 16 reads out two thermal images acquired at different times from the recording unit 11 and displays the two thermal images. The control device 2C outputs the two thermal images read out from the recording unit 11 by displaying the two thermal images read out from the recording unit 11 on the display unit 16.

[0092] In the example shown in Fig. 11, the display unit 16 displays two thermal images side by side. In addition, in the example shown in Fig. 11, each thermal image represents the difference in temperature shown in each pixel using grayscale, and is displayed superimposed on a diagram showing a simplified configuration of the machine tool 3.

[0093] Here, when the determination unit 19 determines that an abnormality exists, the display unit 16 displays the information as shown in FIG. 11. Of the two thermal images, the thermal image shown on the right in FIG. 11 is the thermal image captured at the present time when it has been determined that an abnormality exists. Of the two thermal images, the thermal image shown on the left in FIG. 11 is the thermal image captured in the past when the machine tool 3 was operating normally. By displaying the two thermal images, the control device 2C can clearly show the operator the difference in temperature distribution between the two thermal images. Furthermore, by displaying the thermal image captured when it has been determined that an abnormality exists together with the thermal image captured when the machine tool 3 was operating normally, the control device 2C can clearly show the location that is causing the abnormality.

[0094] In the above description, the display unit 16 displays two thermal images, but it may also display three or more thermal images. That is, the display unit 16 may display three or more thermal images acquired at different times. The control device 2C may also output three or more thermal images read from the recording unit 11.

[0095] According to the third embodiment, the control device 2C includes a determination unit 19 that determines whether or not there is an abnormality in the industrial equipment based on temperature data extracted from a thermal image. The control device 2C outputs the determination result by the determination unit 19. This enables the control device 2C to inform the worker of an abnormality in the industrial equipment in an easy-to-understand manner, and encourages the worker to take measures to address the abnormality.

[0096] Furthermore, two or more thermal images acquired at different times are recorded in the recording unit 11. The control device 2C outputs the two or more thermal images read from the recording unit 11. This allows the control device 2C to present the difference in temperature distribution between the two thermal images to the operator in an easily understandable manner.

[0097] Embodiment 4 12 is a diagram showing a configuration example of an industrial system 1D according to embodiment 4. In embodiment 4, the same components as those in embodiments 1 to 3 above are denoted by the same reference numerals, and the configuration different from those in embodiments 1 to 3 will be mainly described.

[0098] The industrial system 1D includes a control device 2D, a machine tool 3 which is industrial equipment, a thermal image sensor 4, a server device 6, and a display device 7. The control device 2D controls the machine tool 3. The thermal image sensor 4 captures a thermal image showing the temperature distribution of the machine tool 3.

[0099] The server device 6 functions as an information processing device that processes information shown in the thermal image captured by the thermal image sensor 4. The server device 6 is configured, for example, by one or more cloud servers. A cloud server is a server built in a cloud environment that includes computer resources provided by a cloud service platform. The server device 6 is communicably connected to each of the control device 2D, the thermal image sensor 4, and the display device 7 via a network such as a VPN (Virtual Private Network).

[0100] The server device 6 includes an acquisition unit 10, a recording unit 11, a preprocessing unit 12, a thermal change amount estimation unit 13, a correction amount generation unit 14, a learning unit 17, and a model storage unit 18. The server device 6 does not include the control unit 15 and the display unit 16 shown in Fig. 1. The control device 2D performs the same functions as the control unit 15 shown in Fig. 1.

[0101] The display device 7 has the same function as the display unit 16 shown in Fig. 1. The display device 7 is, for example, a display such as an LCD (Liquid Crystal Display) or an organic EL (Electro-Luminescence) display.

[0102] The thermal image sensor 4 captures a thermal image showing the temperature distribution of the machine tool 3 and transmits the thermal image to the server device 6. The acquisition unit 10 receives the thermal image transmitted by the thermal image sensor 4. As a result, the acquisition unit 10 acquires a thermal image showing the temperature distribution of the machine tool 3.

[0103] The correction amount generation unit 14 calculates a correction amount for the position of the movable part based on the thermal change amount estimated by the thermal change amount estimation unit 13. The correction amount generation unit 14 transmits information indicating the calculated correction amount to the control device 2D.

[0104] The control device 2D generates commands in accordance with the machining program and sends the commands to each drive system of the machine tool 3. The control device 2D controls the machine tool 3 by sending commands to each drive system. Furthermore, when the control device 2D receives information indicating a correction amount, it generates commands that reflect the correction amount. As a result, the control device 2D controls the machine tool 3 based on the commands that reflect the correction amount calculated by the correction amount generation unit 14.

[0105] According to the fourth embodiment, the server device 6 includes an acquisition unit 10 that acquires a thermal image, a preprocessing unit 12 that changes pixels from which temperature data is extracted based on the position of a movable part when the thermal image was captured, and a thermal change amount estimation unit 13 that estimates the amount of thermal change of the industrial equipment based on the extracted temperature data. Similar to the control device 2A according to the first embodiment, the server device 6 can easily estimate the amount of thermal change when a heat-generating part of the industrial equipment moves. By including the server device 6, the industrial system 1D can easily estimate the amount of thermal change when a heat-generating part of the industrial equipment moves.

[0106] Next, a hardware configuration for realizing the control devices 2A, 2B, and 2C according to the first to third embodiments will be described. FIG. 13 is a diagram showing an example of a hardware configuration for realizing the control devices 2A, 2B, and 2C according to the first to third embodiments. The control devices 2A, 2B, and 2C are realized by a computer system including a processing circuit 20, an input unit 21, a display unit 24, and an output unit 25. The processing circuit 20 includes a processor 22 and a memory 23. The processing circuit 20 is a circuit on which the processor 22 executes software.

[0107] The functions of the preprocessing unit 12, thermal change amount estimating unit 13, correction amount generating unit 14, control unit 15, and learning unit 17, which are processing units possessed by the control devices 2A, 2B, and 2C, and the function of the determining unit 19, which is a processing unit possessed by the control device 2C, are realized by software, firmware, or a combination of software and firmware. The software or firmware is written as a program and stored in the memory 23.

[0108] The processing circuit 20 realizes the processing units of the control devices 2A, 2B, and 2C by having the processor 22 read and execute programs stored in the memory 23. That is, the processing circuit 20 includes the memory 23 for storing programs that result in the processing of the control devices 2A, 2B, and 2C. The programs stored in the memory 23 are programs that cause a computer to execute the processing procedures and methods of the control devices 2A, 2B, and 2C.

[0109] The functions of the recording unit 11 and model holding unit 18 possessed by the control devices 2A, 2B, and 2C are realized by using the memory 23. The memory 23 is also used as temporary memory when the processor 22 executes various processes. The input unit 21 is an interface circuit that receives data from outside the control devices 2A, 2B, and 2C and provides it to the processor 22. The functions of the acquisition unit 10 possessed by the control devices 2A, 2B, and 2C are realized by using the input unit 21. The output unit 25 is an interface circuit that sends data from the processor 22 or memory 23 to outside the control devices 2A, 2B, and 2C.

[0110] The processor 22 is a CPU (Central Processing Unit). The processor 22 may be a central processing unit, processing unit, arithmetic unit, microprocessor, microcomputer, processor, or DSP (Digital Signal Processor). The memory 23 may be, for example, a non-volatile or volatile semiconductor memory such as RAM (Random Access Memory), ROM (Read Only Memory), flash memory, EPROM (Erasable Programmable Read Only Memory), or EEPROM (Electrically Erasable Programmable Read Only Memory), a magnetic disk, a flexible disk, an optical disk, a compact disk, a minidisk, or a DVD (Digital Versatile Disc).

[0111] The display unit 24 is a display that displays information. The display unit 24 is, for example, an LCD or an organic EL display. The function of the display unit 16 of the control devices 2A, 2B, and 2C is realized by using the display unit 24, which is a display.

[0112] Next, a hardware configuration for realizing the server device 6 according to the fourth embodiment will be described. FIG. 14 is a diagram showing an example of a hardware configuration for realizing the server device 6 according to the fourth embodiment. The server device 6 is realized by a computer system including a processing circuit 20, an input unit 21, and an output unit 25. That is, the server device 6 corresponds to a hardware configuration similar to that shown in FIG. 13 except that the display unit 24 is removed. The control device 2D according to the fourth embodiment is realized using a hardware configuration similar to that shown in FIG. 14.

[0113] The processing circuit 20 of each of the control devices 2A, 2B, 2C and the server device 6 may be a dedicated circuit. The dedicated circuit is a single circuit, a composite circuit, a programmed processor, a parallel programmed processor, an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or a circuit that is a combination of these.

[0114] In the first to fourth embodiments, the industrial equipment is a machine tool 3. In the first to fourth embodiments, the industrial equipment may be equipment other than the machine tool 3, for example, a robot. The robot has an arm that is a movable part that can be moved by a drive mechanism. When the information processing device according to the first to fourth embodiments is applied to the robot, the information processing device estimates the amount of thermal displacement of the robot and corrects the position of the arm. As in the case of the machine tool 3, the information processing device can easily estimate the amount of thermal displacement when the heat-generating part of the robot moves.

[0115] The configurations shown in the above embodiments are examples of the contents of the present disclosure. The configurations of each embodiment can be combined with other known technologies. The configurations of each embodiment can also be combined as appropriate. Part of the configuration of each embodiment can be omitted or modified without departing from the gist of the present disclosure. [Explanation of symbols]

[0116] 1A, 1B, 1C, 1D Industrial system, 2A, 2B, 2C, 2D Control device, 3 Machine tool, 4 Thermal image sensor, 5 Temperature sensor, 6 Server device, 7 Display device, 10 Acquisition unit, 11 Recording unit, 12 Preprocessing unit, 13 Thermal displacement estimation unit, 14 Correction amount generation unit, 15 Control unit, 16, 24 Display unit, 17 Learning unit, 18 Model holding unit, 19 Judgment unit, 20 Processing circuit, 21 Input unit, 22 Processor, 23 Memory, 25 Output unit, 30 Bed, 31 Column, 32 Table, 33 Head, 34 Spindle, 35 Workpiece, 36 Tool, 37X X-axis drive system, 37Y Y-axis drive system, 37Z Z-axis drive system, L1, L2 Lines.

Claims

1. an acquisition unit that acquires a thermal image showing a temperature distribution of industrial equipment having a movable part that can be moved by a drive mechanism; a pre-processing unit that changes pixels from which temperature data is extracted among a plurality of pixels that constitute the thermal image based on the position of the movable part when the thermal image was captured; a thermal displacement amount estimation unit that estimates a thermal displacement amount of the industrial equipment based on the extracted temperature data. An information processing device characterized by:

2. a recording unit that records the thermal image acquired by the acquisition unit, The thermal image read from the recording unit is output.

2. The information processing device according to claim 1, wherein:

3. The recording unit records two or more of the thermal images acquired at different times, Two or more of the thermal images read from the recording unit are output.

3. The information processing device according to claim 2, wherein:

4. The recording unit records compressed data obtained by compressing and encoding the thermal image.

4. The information processing device according to claim 2 or 3.

5. a determination unit that determines whether or not there is an abnormality in the industrial equipment based on the temperature data extracted from the thermal image; outputting the determination result by the determination unit 4. The information processing device according to claim 1, wherein the information processing device is a computer.

6. The acquisition unit acquires the thermal image captured when the moving speed of the movable part is equal to or less than a set speed.

4. The information processing device according to claim 1, wherein the information processing device is a computer.

7. The thermal displacement amount estimation unit estimates the thermal displacement amount of the industrial equipment by inputting the temperature data into a model that is a result of learning a relationship between the temperature of the industrial equipment and the thermal displacement amount of the industrial equipment.

4. The information processing device according to claim 1, wherein the information processing device is a computer.

8. The preprocessing unit corrects the temperature data shown in the thermal image based on a temperature measurement result by a temperature sensor installed in the industrial equipment.

4. The information processing device according to claim 1, wherein the information processing device is a computer.

9. a machine tool having a drive mechanism and a movable part that can be moved by the drive mechanism; a thermal image sensor that captures a thermal image showing the temperature distribution of the machine tool; an information processing device that processes information shown in the thermal image; The information processing device includes: an acquisition unit that acquires the thermal image; a pre-processing unit that changes pixels from which temperature data is extracted among a plurality of pixels that constitute the acquired thermal image based on the position of the movable part when the thermal image was captured; a thermal displacement amount estimation unit that estimates a thermal displacement amount of the machine tool based on the extracted temperature data. An industrial system comprising:

10. A machine tool control method for controlling, by a computer system, a machine tool having a drive mechanism and a movable part that can be moved by the drive mechanism, comprising: acquiring a thermal image showing a temperature distribution of the machine tool; changing pixels from which temperature data is extracted among a plurality of pixels constituting the acquired thermal image based on the position of the movable part when the thermal image was captured; estimating a thermal displacement amount of the machine tool based on the extracted temperature data; calculating a correction amount for the position of the movable part based on the estimated thermal displacement amount; and controlling the machine tool based on a command reflecting the calculated correction amount. A method for controlling a machine tool, comprising:

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