TWI811033B - A spindle temperature measurement and compensation system - Google Patents

Abstract

A spindle temperature measurement and compensation system includes a cloud computing unit and two machine tools. A multi-axis optical detection device installed between the main shaft and the platform of each machine tool, and more than one temperature sensor installed on each machine tool. When the main shaft of each machine tool rotates, the multi-axis optical detection device measures the displacement change data of the main shaft, together with the temperature change data measured by each temperature sensor, is used to construct a temperature compensation model and transmit it to the cloud computing unit, The cloud computing unit integrates and extracts characteristic data of each temperature compensation model to establish an updated temperature compensation model and update it to each tool machine compensation, so as to achieve the effect of optimizing the thermal temperature rise compensation of the spindle.

Description

Spindle Thermal Temperature Rise Measuring Remote Temperature Rise Modification Compensation System and Optimization Method

The invention relates to a tool machine precision compensation means, in particular to a spindle thermal temperature rise measurement remote temperature rise compensation system and an optimization method.

The existing thermal temperature rise compensation technology is to install a metal rod on the main shaft, and then set up multiple probes around the main ball of the metal rod, and then start the operation of the tool machine. When the machine is at different temperatures, multiple probes are used one by one. By detecting the main ball of the metal rod, the displacement of the corresponding main shaft caused by the temperature rise of the main shaft is obtained.

With the above measurements, professionals can obtain accurate data to compensate for the offset caused by the thermal temperature rise of the machine tool. However, the above-mentioned method has some disadvantages. For example, when this method cannot predict the unknown temperature, the error generated by the machine due to the increase of the thermal temperature, and the need to install multiple probes also causes inconvenience in the installation of the measurement device. Further improvements.

Since the existing thermal temperature rise compensation technology cannot predict the offset of the spindle when the temperature is unknown, the present invention collects temperature compensation models of different machine tools through the cloud, thereby integrating and extracting the characteristic data of different temperature compensation models to establish a model with better prediction accuracy Update to each machine tool to achieve the effect of optimizing the thermal compensation of the spindle.

In order to achieve the above creative purpose, the present invention provides a spindle thermal temperature rise measurement remote temperature rise repair model compensation system, including a cloud computing unit located at the remote end, two or more tools located at the local end machine, and a multi-axis optical detection device, more than one temperature sensor and a signal processing module respectively installed on each machine tool, wherein: each machine tool has a controller and a platform operated by the controller respectively and a spindle located above each platform, each spindle is equipped with a tool handle; each multi-axis optical detection device includes a spherical lens device and a sensing head module, and each spherical lens device is combined with the tool handle of each machine tool and at the free end A spherical lens is formed, and each sensor head module has a fixed seat fixed on each platform, and a bracket is provided on the top of each fixed seat, and an optical non-contact sensor group is arranged on each bracket, and an optical non-contact sensor group is installed on the sensor A measuring point is formed in the center of the measuring device group; when each machine tool moves each spherical lens to each measuring point, energy can be used to measure the displacement changes of the main shaft of each machine tool and each spherical lens due to the heat generated by the operation of the main shaft Data; each temperature sensor is respectively fixed on each machine tool to measure temperature change data; each signal processing module is connected with each sensor head module and each temperature sensor signal installed on the same machine tool, each The signal processing module is connected with the controller signal of each machine tool. When the spindle of each machine tool is in operation, each signal processing module captures multiple sets of displacement change data and temperature change data corresponding to each machine tool to input into the model, and builds A temperature compensation model is transmitted to the cloud computing unit; the cloud computing unit collects the temperature compensation models of each machine tool, integrates and extracts the characteristic data of each temperature compensation model to establish an updated temperature compensation model, and sends the updated temperature compensation model back to each signal Process the module and update to the controller of each machine tool for compensation.

In order to achieve the above creation purpose, the present invention provides a method for optimizing the temperature rise of the spindle thermal temperature rise and the compensation of the remote end. The temperature sensor, each optical detection device includes a spherical lens device combined with each machine tool spindle and a sensing head module combined with each machine tool platform, the spherical lens device is provided with a ball shaped lens, the sensing head module is provided with an optical non-contact sensor group, and a measuring point is formed in the center of the sensor group; after each machine tool moves each spherical lens to each measuring point, The main shaft of each machine tool starts to rotate. During the rotation of each main shaft, each sensor head module measures the displacement change data of the spherical lens due to the temperature rise of the main shaft where it is located. The temperature sensing of each machine tool The temperature change data is measured by the machine tool, and the displacement change data and temperature change data of each machine tool are captured by software and input into the model to build a local temperature compensation model; and the temperature compensation model of each machine tool is transmitted to a remote site. A cloud computing unit, the cloud computing unit collects the temperature compensation models of each machine tool, integrates and extracts the characteristic data of each temperature compensation model to establish an updated temperature compensation model, and sends the updated temperature compensation model back to each machine tool at the local end for compensation.

The present invention uses the above-mentioned system and method, after training the temperature compensation models corresponding to each machine tool at each machine tool, it can collect the models generated from various environments and parameter conditions to the remote cloud computing unit, and integrate them through the cloud computing unit , Extract the characteristic data of different temperature compensation models, establish a model with better prediction accuracy, and update it to each machine tool to achieve the effect of thermal compensation optimization for the spindle. At the same time, because the remote cloud computing unit only extracts the characteristic data of each temperature compensation model, There is no contact with the original displacement change data and temperature change data, so the data at the local end of each machine tool has privacy.

100: Cloud Computing Unit

10: machine tools

11: base

12: sliding seat

13: swing seat

14: Platform

15: column

16: Cutter head

17: Spindle

171: knife handle

18: Controller

20: Spherical lens device

21: insert rod

22: spherical lens

30: Sensor head module

31: fixed seat

32: Bracket

33: Sensor group

331: The first laser head

332: The second laser head

333: The first light point displacement sensor

334: the second light point displacement sensor

40:Temperature sensor

41:Magnetic base

42: Antenna

50: Signal processing module

51: Communication module

52: Data acquisition card

A: Multi-axis optical detection device

A1: Temperature compensation model

A2: Temperature compensation model

B: Measuring point

S01 to S08: Steps

Fig. 1 is a flow chart of the steps of the method of the preferred embodiment of the present invention.

FIG. 2 is a schematic block diagram of a preferred embodiment of the present invention.

Fig. 3 is a perspective view of a machine tool in a preferred embodiment of the present invention.

FIG. 4 is a side view of the sensing head module and the spherical lens device according to the preferred embodiment of the present invention.

FIG. 5 is a perspective view of a sensor head module and a spherical lens device according to a preferred embodiment of the present invention.

FIG. 6 is a perspective view of a sensing head module according to a preferred embodiment of the present invention.

FIG. 7 is a block diagram of a signal processing module of a preferred embodiment of the present invention.

In order to understand the technical features and practical functions of the present invention in detail, and implement them according to the contents of the description, a preferred embodiment as shown in the drawings is further described in detail as follows.

The preferred embodiment shown in Figure 2 to Figure 7, the present invention provides a spindle thermal temperature rise measurement remote temperature rise compensation system, used to implement the spindle thermal temperature rise measurement remote as shown in Figure 1 Temperature rise and mold repair compensation optimization method; please refer to Fig. 2 to Fig. 4 and shown in Fig. 7, this system includes a cloud computing unit 100 and more than two machine tools 10 located on the Internet, where the cloud computing unit 100 is located The place where each machine tool 10 is located is called the local end. Preferably, each machine tool 10 is located in a different place, and a multi-axis optical detection device A, a plurality of temperature sensors 40 and A signal processing module 50, the signal processing module 50 located in each machine tool 10 is connected to the cloud computing unit 100 through the Internet, wherein:

3 to 6, each machine tool 10 can be an X-axis, Y-axis machine tool or a multi-axis machine tool. In this preferred embodiment, there are three parts with X-axis, Y-axis, Z For five-axis machine tools with the same model, A-axis, and C-axis, the machine tool 10 of the same model is more suitable for the same compensation model. Each machine tool 10 is provided with a base 11, each base is provided with a sliding seat 12 movable along the X-axis and Y-axis, and a swing seat 13 is provided on the top of each sliding seat 12, which can swing along the A-axis. The top of the swing base 13 is provided with a platform 14 that can rotate along the C axis, and a column 15 is provided on the top of each base 11 rear side, and a cutter head 16 that can move along the Z axis is combined in front of each column 15. Each cutter head 16 Located directly above each platform 14, each cutter head 16 is provided with a main shaft 17, a knife handle 171 is installed at the bottom of each main shaft 17, and each machine tool 10 is also provided with a controller 18 for numerically controlling each sliding seat 12, The actions of each swing seat 13, each platform 14, each cutter head 16 and each main shaft 17.

The multi-axis optical detection device A installed on each machine tool 10 includes a spherical lens device 20 and a sensor head module 30, each spherical lens device 20 is provided with a plunger 21, each plunger 21 is a straight rod body and vertical The tool handle 171 combined with each machine tool 10 is inserted into the tool handle 171, and a spherical lens 22 is formed at the free end of the bottom of each insertion rod 21. Each spherical lens device 20 cooperates with each sensor head module 30 to form a multi-axis optical detection device A. Each sensing head module 30 is provided with a fixing base 31 for being fixed on the platform 14 of the machine tool 10. In this preferred embodiment, each fixing base 31 is a magnetic base and is combined and fixed on each On the platform 14, a surrounding support 32 is provided on the top of each fixing seat 31, and an optical non-contact sensor group 33 is provided on each support 32, and each sensor group 33 is corresponding to the X-axis on each support 32. A first laser head 331 and a first light spot displacement sensor 333 are arranged on the opposite sides of the direction, and a second laser head 332 and a second light beam are arranged on the opposite sides of each bracket 32 corresponding to the Y-axis direction. The point displacement sensor 334 is connected between each first laser head 331 and each first light point displacement sensor 333 and each second laser head 332 and each second light point displacement sensor 334. The intersections form a measurement point B, and each measurement point B is located at the center of each sensor group 33 .

When each machine tool 10 moves the spherical lens 22 where it is located to the measurement point B of each sensor head module 30, and sets this coordinate as the coordinate origin, if the spindle 17 is heated due to rotation and the temperature increases offset, so that when the spherical lens 22 moves to the origin of the coordinates, the same degree of offset will also occur. The laser light passing through the center of each spherical lens 22 no longer passes through the center of each spherical lens 22, so that the first light spot displacement sensor 333 and the second light spot displacement sensor 334 of the same sensing head module 30 can respectively It is detected that the two laser beams passing through each spherical lens 22 deviate, and by the degree of deviation of each laser beam, the multi-axis optical detection device A can calculate the spindle 17 of each machine tool 10 and the spindle 17 combined with the spindle The displacement change data of the spherical lens 22 of 17 due to the heat generated by the operation of the main shaft 17.

The plurality of temperature sensors 40 installed on each machine tool 10 are devices capable of sensing temperature and wirelessly transmitting temperature data to the outside. Each temperature sensor 40 is provided with a magnetic suction base 41, and each magnetic suction base 41 can magnetically fix a plurality of temperature sensors 40 installed on the same machine tool 10 on the side of the machine tool 10. To measure temperature at different positions, an antenna 42 is provided on each magnetic base 41, through each antenna 42, the temperature change data of different parts of the same machine tool 10 measured by each temperature sensor 40 can be wirelessly output to the outside; In this preferred embodiment, multiple temperature sensors 40 installed on the same machine tool 10 are respectively combined at different positions of the column 15 , the tool head 16 and the spindle 17 of the machine tool 10 .

In other embodiments of the present invention, only one or several temperature sensors 40 may be provided on one machine tool 10, but at least one temperature sensor 40 is installed on the main shaft 17, for example only on the main shaft 17, a temperature sensor 40 is installed, or the main shaft 17 and the cutter head 16 are respectively provided with more than one temperature sensor 40 of varying numbers; the more temperature sensors 40 arranged on the same machine tool 40, the more the obtained The more temperature change data at different positions of the machine tool 40, the more the temperature change data is not limited to the example of the setting position of this preferred embodiment, it can even be set in the environment of the local end of each machine tool 40; and each temperature sensor 40 has wireless transmission In addition to functional temperature sensors, each temperature sensor 40 can also be a temperature sensor that transmits signals through wires.

Please refer to FIG. 3 and FIG. 7 , the signal processing module 50 installed in each machine tool 10 can be installed inside the machine tool 10 or detachably arranged outside the machine tool 10 . Each signal processing module 50 includes a communication module 51 and a data acquisition card 52. In this preferred embodiment, the signal processing module 50 uses the communication module 51 to communicate with the cloud computing unit 100 through the Internet. connection, each data acquisition card 52 is connected with each temperature sensor 40 of the machine tool 10 in a wireless manner, and receives the temperature change data measured by each temperature sensor 40, and each data acquisition card 52 The sensor head module 30 is connected to the sensor head module 30 in a wired or wireless manner to receive the displacement change data of the spindle 17 , and each data acquisition card 52 is electrically connected to the controller 18 of the machine tool 10 where it is located. When each temperature sensor 40 is changed to a temperature sensor for wired transmission signals, the data acquisition card 52 of the signal processing module 50 of each machine tool 10 is connected with each temperature sensor 40 in a wired manner. .

Each signal processing module 50 can receive the displacement change data of the main shaft 17 sensed by the sensing head module 30 of each multi-axis optical detection device A during the rotation of the main shaft 17 of the machine tool 10, and the corresponding bit The number of temperature changes in the machine tool 10 received by each temperature sensor 40 when the shift changes According to the data, in this way, the software continuously captures multiple sets of displacement change data and temperature change data into the model, such as a neural network-like model, and builds a temperature compensation model A1 that can be used to predict the displacement changes caused by different temperature changes at the local end. The temperature compensation model A1 is input to the controller 18 of the machine tool 10 where each signal processing module 50 is located for compensation, and each signal processing module 50 transmits the temperature compensation model A1 trained at the machine tool 10 where it is located to the cloud computing unit 100 Do consortium learning.

The remote cloud computing unit 100 collects the temperature compensation models A1 trained at different machine tools 10 for alliance learning, collects the temperature compensation models A1 of each machine tool 10 and integrates and extracts the characteristic data of each temperature compensation model A1, for example Trends, gradients, equations and other characteristics, integrate all local temperature compensation models A1 to build an updated temperature compensation model A2 with high strength and high prediction compensation accuracy, and then send the updated temperature compensation model A2 back to each signal processing module 50, each The signal processing module 50 updates the updated temperature compensation model A2 to the controller 18 of the machine tool 10 where it is located for compensation.

Since each machine tool 10 builds a model under different conditions at the local end, the more machine tools 10 that cooperate with the cloud computing unit 100 to participate in federated learning, the updates generated after the cloud computing unit 100 performs federated learning The prediction result of the temperature compensation model A2 is more robust and accurate, and the processing accuracy of the machine tool 10 can be improved after being sent back to each machine tool 10 for update and correction. In addition, because the cloud computing unit 100 only extracts the characteristic data of the temperature compensation model A1 of each local end, the data of the local end has privacy.

When the present invention uses the above-mentioned system to execute the method for optimizing the thermal temperature rise of the main shaft by measuring the remote temperature rise and repairing the mold compensation, the following steps are performed as shown in FIG. 1 :

(S01) Set up a multi-axis optical detection device and temperature sensor: set up an optical detection device A and combine more than one temperature sensor 40 on two or more machine tools 10, such as this preferred embodiment is provided with three A machine tool 10, and a plurality of temperature sensors 40 are combined with each machine tool 10. The spherical lens device 20 of each optical detection device A is combined with the main shaft 17 of each machine tool 10, and the sensor of each optical detection device A The measuring head module 30 is combined on the platform 14 of each machine tool 10 , a measuring point B is arranged in the center of each sensor head module 30 , and a plurality of temperature sensors 40 are detachably combined with the machine tool 10 .

( S02 ) Spindle rotation of each machine tool: After each machine tool 10 moves the spherical lens 22 of each spherical lens device 20 to the measurement point B of each sensor head module 30 , the spindle 17 of each machine tool 10 starts to rotate.

(S03) Capture displacement change and temperature change data: During the rotation of each spindle 17, the sensor head module 30 measures the displacement change data of the spherical lens 22 due to the temperature rise of the spindle 17, each The multiple temperature sensors 40 of the machine tool 10 measure the temperature change data of each part of the machine tool 10 during this period, and the displacement change data and temperature change data of each machine tool 10 are captured by software.

(S04) Establish a local model: input multiple sets of displacement change data and temperature change data obtained by each machine tool 10 into the model, such as a neural network-like model, and build a local model that can be used to predict displacement changes when different temperature changes occur Temperature compensated model A1.

( S05 ) Transfer the model to the cloud: transfer the temperature compensation model A1 of each machine tool 10 to a remote cloud computing unit 100 for federated learning.

(S06) Training cloud model: the remote cloud computing unit 100 collects temperature compensation models A1 trained by different machine tools 10 for alliance learning, integrates and extracts characteristic data of each temperature compensation model A1, such as trends, gradients, equations and other characteristics, an updated temperature compensation model A2 with high strength and high prediction compensation accuracy is established.

(S07) Updating the local model: sending the updated temperature compensation model A2 trained by the cloud computing unit 100 back to each machine tool 10 for updating.

( S08 ) Compensating machine errors: each machine tool 10 uses the updated temperature compensation model A2 trained by the cloud computing unit 100 to correct and compensate processing errors.

Using the method of the present invention, the temperature compensation models trained by different machine tools 10 can be collected in the cloud computing unit 100 for alliance learning. Therefore, the more machine tools 10 that cooperate with the cloud computing unit 100 to participate in federated learning, the more predictive results of the updated temperature compensation model generated by the cloud computing unit 100 after performing federated learning. Robust and accurate, so that the updated temperature compensation model is sent back to each machine tool 10 after updating, and the effect of using the model to correct and compensate the error of the spindle 17 during machining of the machine tool 10 is better than the local temperature compensation model trained by each machine tool 10 itself .

Furthermore, before the step of establishing the local model, the operation of capturing the displacement change data and temperature change data of each machine tool 10 by software can be repeated, so as to input multiple sets of displacement change data and temperature change data captured repeatedly. The model is trained to enhance the robustness of the temperature compensation model A1 at the local end of each machine tool 10, and the adaptability under different conditions, so that the prediction accuracy of the temperature compensation model A1 at each local end is improved, and then transmitted to the cloud computing unit 100 for alliance learning .

The above descriptions are only preferred embodiments of the present invention, and are not intended to limit the scope of rights claimed by the present invention. All other equivalent changes or modifications that do not deviate from the spirit disclosed in the present invention should be included in the present invention. within the scope of the patent application.

S01 to S08: Steps

Claims (8)

A spindle thermal temperature rise measurement remote temperature rise compensation system, including a cloud computing unit located at the remote end, two or more machine tools located at the local end, and a multi-axis optical detection device respectively installed on each machine tool, More than one temperature sensor and a signal processing module, wherein: each machine tool has a controller, a platform operated by the controller and a main shaft above each platform, and a knife handle is installed on each main shaft; The multi-axis optical detection device includes a spherical lens device and a sensor head module. Each spherical lens device is combined with the tool handle of each machine tool and forms a spherical lens at the free end. Each sensor head module has a sensor head module fixed on each platform. On the fixed seat, a bracket is arranged on the top of each fixed seat, and an optical non-contact sensor group is arranged on each bracket, and a measuring point is formed in the center of the sensor group; After the spherical lens moves to each measurement point, it can measure the displacement change data of the main shaft of each machine tool and each spherical lens due to the heat generated by the operation of the main shaft; each temperature sensor is respectively fixed on each machine tool to measure Measure temperature change data; each signal processing module is connected with each sensor head module and each temperature sensor signal installed on the same machine tool, and each signal processing module is also connected with the controller signal of each machine tool. When the main shaft of the machine tool is in operation, each signal processing module captures multiple sets of displacement change data and temperature change data corresponding to each machine tool to input the model, builds a temperature compensation model and transmits it to the cloud computing unit; the cloud computing unit collects different The temperature compensation model of the machine tool is learned in an alliance, and the feature data of each temperature compensation model is integrated and extracted to establish an updated temperature compensation model, and the updated temperature compensation model is sent back to each signal processing module and updated to the controller of each machine tool for further processing. compensate. The spindle thermal temperature rise measurement and compensation system for remote temperature rise and mold repair as described in Claim 1, wherein more than one temperature sensor is respectively installed on each machine tool, wherein at least one temperature sensor is fixed on each machine tool the main axis. The spindle thermal temperature rise measurement and remote temperature rise repair compensation system as described in claim 2, wherein the fixing seats of the sensor head modules are magnetic seats, and the fixing seats are magnetically combined and fixed on each on the platform. The spindle thermal temperature rise measurement remote temperature rise compensation system as described in any one of claims 1 to 3, wherein a magnetic suction base is provided on each of the temperature sensors, and each magnetic suction base is magnetically attracted Fixed on each machine tool, an antenna is installed on each magnetic base, and the measured temperature change data is output wirelessly through each antenna; the signal processing module is connected to each temperature sensor signal in a wireless manner. As described in any one of claims 1 to 3, the spindle thermal temperature rise measurement remote temperature rise model compensation system, wherein each of the temperature sensors is a temperature sensor with wired transmission signals, and the signal processing module The group is connected with each temperature sensor signal in a wired manner. A method for optimizing the thermal temperature rise of a spindle by measuring the temperature rise at the remote end and repairing mold compensation. The device includes a spherical lens device combined with the main shaft of each machine tool and a sensing head module combined with the platform of each machine tool, the spherical lens device is provided with a spherical lens, and the sensing head module is provided with an optical non-contact The sensor group of the sensor group forms a measuring point in the center of the sensor group; after each machine tool moves each spherical lens to each measuring point, the main shaft of each machine tool starts to rotate, and during the rotation of each main shaft , each sensor head module measures the displacement change data of the spherical lens due to the rotation of the spindle where the temperature rises, and each temperature sensor of each machine tool measures the temperature change data, and the software captures the data of each machine tool Displacement change data and temperature change data are input into the model to build a local temperature compensation model; and the temperature compensation model of each machine tool is transmitted to a remote cloud computing unit, which collects the temperature compensation of different machine tools The model conducts federated learning, and integrates and extracts each temperature compensation An updated temperature compensation model is established based on the characteristic data of the model, and the updated temperature compensation model is sent back to each machine tool at the local end for compensation. According to claim 6, the spindle thermal temperature rise measurement and remote temperature rise repair model compensation optimization method, wherein the characteristic data include trends, gradients and equations. As described in claim 6 or 7, the spindle thermal temperature rise measurement and remote temperature rise repair model compensation optimization method, wherein the software repeatedly captures the displacement change data and temperature change data input models of each machine tool, and builds each local end. The operation of the temperature compensation model, so as to train each temperature compensation model, increase its robustness and adaptability and improve the prediction accuracy.

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