Device for detecting tool status in machine tools

Abstract

The present application relates to a device for detecting the state of a tool in a machine tool, which may include: a sensor unit for sensing the acceleration of a spindle of the machine tool in the x-axis direction and the y-axis direction during machining; and a processing device for converting the x-axis signal and the y-axis signal sensed by the sensor unit into a signal capable of representing a cutting force by processing the x-axis and y-axis signals, detecting a resultant force, and plotting the detected resultant force on a polar coordinate system.

Description

Technical Field

[0001] An exemplary embodiment of the present application relates to a device for detecting the state of a tool in a machine tool, and more specifically, to a device for detecting the state of a tool in a machine tool, the device comprising two micro-electromechanical systems (MEMS) type vibration accelerometers attached to a non-rotating portion of a spindle, for measuring signals in a wired manner during machining, and analyzing the measured signals to detect the state of the tool. Background Art

[0002] Among the various tools commonly used, drills or taps with smaller diameters are often damaged when machining products. There are various reasons for tool damage, such as bubbles in the tool material or tool vibration.

[0003] When an operator continues to use a damaged tool to process a product without realizing that the tool is damaged, various problems may occur, such as producing defective products. That is, the damage of the tool in the machine tool causes secondary losses, namely product damage, and losses caused by the damage to the tool. Therefore, the tool monitoring system is used to detect whether the tool is damaged in advance, thereby preventing product defects that may occur after damage.

[0004] Traditional tool monitoring systems require the use of tool holders with measuring sensors attached to process products, or detect the cutting status of high-speed spindles only by measuring the vibration amplitude. Therefore, traditional tool monitoring systems are easily affected by interference and vibration as well as machine tool processing, making it difficult to accurately check the status of the tool when processing products.

[0005] In addition, the conventional tool monitoring system transmits / receives the signal measured by the tool holder through wireless communication method. Therefore, the reliability of the signal is low and the system cost is high.

[0006] The related art of the present application is disclosed in Korean Patent No. 10-1134940, registered on Apr. 3, 2012, entitled “Method of Monitoring and Controlling Processing System Status by Spindle Vibration Value”. Summary of the invention

[0007] Multiple embodiments of the present application relate to a device for detecting the status of a tool in a machine tool, which includes two MEMS-type vibration accelerometers attached to a non-rotating part of a spindle, for measuring signals in a wired manner during a machining process, and analyzing the measured signals to detect the status of the tool.

[0008] In one embodiment, a device for detecting the state of a tool in a machine tool may include: a sensor unit for sensing the acceleration of a spindle of the machine tool in the x-axis direction and the y-axis direction during machining; a processing device for converting the x-axis signal and the y-axis signal sensed by the sensor unit into signals capable of representing cutting force by processing the x-axis and y-axis signals, detecting the resultant force, and plotting the detected resultant force on a polar coordinate system.

[0009] The sensor unit may include: a first acceleration sensor for sensing the acceleration of the main shaft in the x-axis direction; a first amplifier for amplifying the signal sensed by the first acceleration sensor; a second acceleration sensor for sensing the acceleration of the main shaft in the y-axis direction; and a second amplifier for amplifying the signal sensed by the second acceleration sensor, wherein the first acceleration sensor and the second acceleration sensor are both set at a preset angle.

[0010] The sensor unit can be mounted on any of the machine tool's spindle, the coupling on the spindle, the tool, and the turret.

[0011] The processing device may include: a signal processing unit, which is used to filter the signal sensed by the sensor unit and convert the filtered signal into a digital signal to prevent signal aliasing; a tool visualization unit, which is used to convert the signal input from the signal processing unit into a signal capable of representing the cutting force based on a parameter set according to the processing conditions, generate a norm value by adding the converted x-axis signal and y-axis signal, and then create a chart by plotting the norm value on a polar coordinate system, wherein the state of the tool during the rotation process and the number of blades are reflected in the chart; and a device control unit, which is used to detect the current state of the tool based on the polar coordinate diagram of the tool visualization unit.

[0012] The signal processing unit may include: a first anti-aliasing filter, used to filter the x-axis signal to prevent aliasing of the x-axis signal; a first analog-to-digital converter (ADC), used to convert the signal output from the first anti-aliasing filter into a digital signal; a second anti-aliasing filter, used to filter the y-axis signal to prevent aliasing of the y-axis signal; and a second analog-to-digital converter, used to convert the signal output from the second anti-aliasing filter into a digital signal.

[0013] The tool visualization unit may include: a first signal conversion filter, used to extract only the signal generated when the blade of the tool contacts the material during the cutting process from the x-axis signal according to the parameters; a first low-pass filter (Low PassFilter, LPF for short), used to remove the pseudo-noise high-frequency signal from the signal filtered by the first signal conversion filter according to the parameters; a second signal conversion filter, used to extract only the signal generated when the blade of the tool contacts the material during the cutting process from the y-axis signal according to the parameters; a second low-pass filter, used to remove the pseudo-noise high-frequency signal from the signal filtered by the second signal conversion filter according to the parameters; a vector calculation module, used to calculate the norm value of the resultant force corresponding to the x-axis signal and the y-axis signal by performing norm operations on the signals filtered by the first low-pass filter and the second low-pass filter respectively; a tool visualization module, used to visualize the tool state by plotting the norm value calculated by the vector calculation module on a polar coordinate diagram.

[0014] The tool visualization module can calculate the length of the array corresponding to one rotation of the tool from the array of continuous norm values, and express the blade status of each rotation of the tool by arranging the norms corresponding to the length of the array in sequence on the polar coordinate diagram.

[0015] The equipment control unit may include: a communication module for transmitting alarm information to the computer numerical control (Computer Numerical Control, CNC) of the machine tool; an input / output (I / O) module for transmitting control signals to the programmable logic controller (Programmable Logic Controller, PLC) of the machine tool; a tool state detection module for detecting the tool state based on the polar coordinate diagram output by the tool visualization unit, and according to the detection result, transmitting the alarm information to the programmable logic controller of the machine tool through the communication module, or transmitting the control signal to the computer numerical control of the machine tool.

[0016] The tool state detection module can set the search area by dividing 360 degrees of the polar coordinate system by the number of blades of the tool, calculate the major axis length of the ellipse representing the blade by calculating the maximum value in each search area, and calculate the minor axis length of the ellipse by calculating the median of each search area.

[0017] The tool status detection module can classify the tool status into normal, worn, defective and completely damaged.

[0018] When the length of the major axis of the ellipse is within a preset range and the angle of the ellipse is the same as the actual tool blade, the tool state detection module can determine that the tool state corresponds to normal; when the major axis length of the ellipse corresponding to the worn blade decreases, and the major axis length of the ellipse corresponding to the next blade following the worn blade in the rotation direction increases, the tool state detection module can determine that the tool state corresponds to wear; when the ellipse corresponding to the defective blade disappears or the major axis length is equal to or less than the preset length, the tool state detection module can determine that the tool state corresponds to defect; when the ellipse is not expressed as the shape of a preset normal ellipse, the tool state detection module can determine that the tool state corresponds to complete damage.

[0019] According to an embodiment of the present application, a device for detecting the status of a tool in a machine tool includes two MEMS-type vibration accelerometers attached to a non-rotating part of a spindle, which are used to measure signals in a wired manner during machining, analyze the measured signals, and visualize the accurate status of the tool to detect the status of the tool.

[0020] In addition, based on the visualized tool status, the device for detecting the tool status in a machine tool according to an embodiment of the present application can output an alarm or perform control such as an emergency stop according to predetermined conditions, thereby preventing material processing defects. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 is a diagram showing a configuration of an apparatus for detecting a tool status in a machine tool according to an embodiment of the present application.

[0022] Figure 2 is a block diagram showing a device for detecting a tool status in a machine tool according to an embodiment of the present application.

[0023] Figure 3 is a schematic diagram showing the attachment position of the acceleration sensor according to the embodiment of the present application.

[0024] Figure 4 is a schematic diagram showing a sensor unit and a signal flow according to an embodiment of the present application.

[0025] Figure 5 is a graph showing the signal stability of a piezoelectric sensor and a Micro Electro-Mechanical Systems (MEMS) sensor.

[0026] Figure 6 is a schematic diagram showing the structure of a signal conversion filter according to an embodiment of the present application.

[0027] Figure 7is a flow chart showing the operation of a signal conversion filter and a low-pass filter (Low Pass Filter, LPF for short) according to an embodiment of the present application.

[0028] Figure 8 is a schematic diagram for describing a process of calculating a vector norm value during processing according to an embodiment of the present application.

[0029] Fig. 9 is a schematic diagram showing a polar coordinate diagram according to an embodiment of the present application.

[0030] Figures 10A to 10D is a schematic diagram showing a result obtained by visualizing the state of a 5-blade tool according to an embodiment of the present application.

[0031] Fig.11 Detailed description is a flowchart showing the operation of a device control unit according to an embodiment of the present application.

[0032] Fig.12 , Fig.13 : is a schematic diagram showing an example in which the present embodiment is applied to a lathe.

[0033] Fig.14 : is a schematic diagram showing another configuration example of the tool visualization unit according to the embodiment of the present application. DETAILED DESCRIPTION

[0034] As is conventional in the corresponding field, some exemplary embodiments may be shown in the accompanying drawings in the form of functional blocks, units and / or modules. It will be understood by those of ordinary skill in the art that these blocks, units and / or modules are specifically implemented by electronic (or optical) circuits (e.g., logic circuits, discrete elements, processors, hard-wired circuits, memory elements, wiring connections, etc.). When blocks, units and / or modules are implemented by processors or similar hardware, they can be programmed and controlled using software (e.g., code) to perform the various functions discussed herein. Alternatively, each block, unit and / or module may be implemented by dedicated hardware, or implemented as a combination of dedicated hardware that performs some functions and a processor that performs other functions (e.g., one or more programmed processors and associated circuits). Without departing from the scope of the present invention, each block, unit and / or module of some exemplary embodiments may be physically separated into two or more interactive and discrete blocks, units and / or modules. In addition, without departing from the scope of the present invention, the blocks, units and / or modules of some exemplary embodiments may be specifically combined into more complex blocks, units and / or modules.

[0035] Hereinafter, a device for detecting the state of a tool in a machine tool will be described with reference to the accompanying drawings through various exemplary embodiments. It should be noted that the drawings are not drawn to exact scale, and the thickness of the lines or the size of the components may be exaggerated only for the convenience and clarity of the description. In addition, the terms used herein are defined in consideration of the functions of the present invention and may be changed according to the habits or intentions of the user or operator. Therefore, the definition of the terms should be made in accordance with the overall disclosure set forth herein.

[0036] Figure 1 is a diagram showing a configuration of an apparatus for detecting a tool status in a machine tool according to an embodiment of the present application. Figure 2 is a block diagram showing a device for detecting a tool status in a machine tool according to an embodiment of the present application. Figure 3 is a schematic diagram showing the attachment position of the acceleration sensor according to the embodiment of the present application. Figure 4 is a schematic diagram showing a sensor unit and a signal flow according to an embodiment of the present application. Figure 5 is a graph showing the signal stability of a piezoelectric sensor and a Micro Electro-Mechanical Systems (MEMS) sensor. Figure 6 is a schematic diagram showing the structure of a signal conversion filter according to an embodiment of the present application. Figure 7 is a flow chart showing the operation of a signal conversion filter and a low pass filter (LPF) according to an embodiment of the present application. Figure 8 is a schematic diagram for describing a process of calculating a vector norm value during processing according to an embodiment of the present application. Fig. 9 is a schematic diagram showing a polar coordinate diagram according to an embodiment of the present application. Figures 10A to 10D is a schematic diagram showing a result obtained by visualizing the state of a 5-blade tool according to an embodiment of the present application. Fig.11 Detailed description is a flowchart showing the operation of a device control unit according to an embodiment of the present application. Fig.12 , Fig.13 : is a schematic diagram showing an example in which the present embodiment is applied to a lathe. Fig.14 : is a schematic diagram showing another configuration example of the tool visualization unit according to the embodiment of the present application.

[0037] like Figures 1 to 11 As shown, the device for detecting the state of a tool in a machine tool according to an embodiment of the present invention comprises a sensor unit 10 and a processing device 20. The processing device 20 comprises a signal processing unit 21, a tool visualization unit 22 and a device control unit 23.

[0038] During machining, the sensor unit 10 senses the vibration acceleration of the machine tool spindle in the x-axis and y-axis directions.

[0039] The sensor unit 10 includes a first acceleration sensor 11 , a first amplifier 12 , a second acceleration sensor 13 , and a second amplifier 14 .

[0040] The first acceleration sensor 11 is installed on the main shaft of the machine tool or on a coupling on the main shaft, and is used to sense the vibration acceleration of the main shaft of the machine tool in the x-axis direction.

[0041] The second acceleration sensor 13 is installed on the main shaft of the machine tool or on a coupling on the main shaft, and is used to sense the vibration acceleration of the main shaft of the machine tool in the y-axis direction.

[0042] like Figure 3 As shown, the first acceleration sensor 11 and the second acceleration sensor 13 are arranged at a preset angle of 90 degrees, for example, based on the center of the machine tool spindle or the center point of the coupling.

[0043] The first amplifier 12 amplifies the signal sensed by the first acceleration sensor 11 .

[0044] The second amplifier 14 amplifies the signal sensed by the second acceleration sensor 13 .

[0045] Considering the various structures and shapes of the internal components of the machine tool, it is necessary to reduce the size of the sensor body for the smooth measurement of the signals generated during the machining process and the convenience of the installation operation.

[0046] refer to Figure 4 The first acceleration sensor 11 and the second acceleration sensor 13 may each include a micro-electromechanical system (MEMS) core sensor installed in a housing of the sensor unit 10 .

[0047] A power supply circuit and an integrated electronic piezoelectric (IEPE) signal conversion and amplification circuit can also be embedded to drive the sensor, which has a predetermined output voltage range starting from 0V, and the power supply circuit and the IEPE signal conversion and amplification circuit are respectively connected to the first acceleration sensor 11 and the second acceleration sensor 13.

[0048] In addition, since the IEPE conversion amplifier circuit is characterized by simultaneously supplying power and outputting signals, the sensor unit 10 may further include a low pass filter (LPF for short) for reducing noise contained in the sensor output.

[0049] The outputs of the first acceleration sensor 11 and the second acceleration sensor 13 may be input to the LFP. Since the signal having passed through the LPF is transmitted to the IEPE conversion amplifier circuit, the first acceleration sensor 11 and the second acceleration sensor 13 may be mounted compatible with commercial IEPE sensors.

[0050] An IEPE conversion amplifier may be used as the first amplifier 12 and the second amplifier 14. The output of the IEPE conversion amplifier is transmitted to the processing device 20 through the shielded cable 17. Therefore, the reliability of the sensed signal can be increased, and the manufacturing cost can be reduced.

[0051] MEMS sensors are basically used as accelerometers for measuring acceleration. MEMS sensors have a measurable frequency domain of 0 Hz to 10 kHz, and the signal amplitude of 0 Hz needs to have a deviation range of ±1 mg (RMS).

[0052] The processing device 20 converts the x-axis and y-axis signals sensed by the sensor unit 10 into signals capable of representing the cutting force by processing the x-axis and y-axis signals, detects the resultant force by adding the converted signals, and then plots the detected resultant force on a polar coordinate system.

[0053] like Figure 2 As shown, the processing device 20 includes a signal processing unit 21 , a tool visualization unit 22 and a device control unit 23 .

[0054] The signal processing unit 21 filters the x-axis and y-axis signals sensed by the sensor unit 10 and converts the filtered signals into digital signals to prevent aliasing of the x-axis and y-axis signals.

[0055] The signal processing unit 21 includes a first anti-aliasing filter 211 , a first analog-to-digital converter (ADC) 212 , a second anti-aliasing filter 213 and a second analog-to-digital converter 214 .

[0056] In order to successfully visualize changes in the tool state occurring during a machining operation of the machine tool, it is necessary to prevent aliasing of signals input from the first acceleration sensor 11 and the second acceleration sensor 13 .

[0057] The first anti-aliasing filter 211 filters the x-axis signal to prevent aliasing of the x-axis signal. As the first anti-aliasing filter 211, a band pass filter (BPF for short) or LPF can be used according to the processing environment and conditions and the material of the tool.

[0058] The first analog-to-digital converter 212 converts the signal output from the first anti-aliasing filter 211 into a digital signal. The first analog-to-digital converter 212 needs to quantize the signal output from the first anti-aliasing filter 211 at a resolution of 18 bits or higher, and convert the quantized signal at a sampling rate of 10 kHz or higher.

[0059] The second anti-aliasing filter 213 filters the y-axis signal to prevent aliasing of the y-axis signal. As the second anti-aliasing filter 213, a BPF or a LPF can be used according to the processing environment and conditions and the material of the tool.

[0060] The second analog-to-digital converter 214 converts the signal output from the second anti-aliasing filter 213 into a digital signal. The second analog-to-digital converter 214 needs to quantize the signal output from the second anti-aliasing filter 213 at a resolution of 18 bits or higher, and convert the quantized signal at a sampling rate of 10 kHz or higher.

[0061] The tool visualization unit 22 converts the signal input from the signal processing unit 21 into a signal capable of representing the cutting force according to the parameters preset by the machining conditions, generates a norm value by adding the converted x-axis and y-axis signals, and then plots the generated norm value on a polar coordinate system, thereby creating a graph in which the state of the tool during rotation and the number of blades are reflected.

[0062] The tool visualization unit 22 includes a first signal conversion filter 221 , a first low-pass filter 222 , a second signal conversion filter 223 , a second low-pass filter 224 , a vector calculation module 225 , and a tool visualization module 226 .

[0063] Before the status of the tool can be visualized, it is necessary to extract only the signal generated when the blade of the tool contacts the material during cutting from the input sensor signal. From the perspective of cutting mechanics, this signal becomes an important factor that enables estimation of the cutting force generated during machining.

[0064] During the cutting process, when the tool rotates one circle, the material is repeatedly cut by multiple blades of the tool. During this process, vibration acceleration signals are periodically generated in the x-axis and y-axis directions. In the formula F=ma, the cutting force F is proportional to the generated acceleration a, and the mass m remains unchanged because the mass is the total mass of the tool, tool holder and spindle coupling. Therefore, the nonlinearity of the tool holder-spindle vibration system can be ignored, and the cutting force can be estimated by measuring the acceleration in each axial direction.

[0065] Since the present embodiment aims to visualize the change of the tool state, the present embodiment can achieve the desired purpose by using only the relative values ​​between various components, including the nonlinearity of the tool holder-spindle vibration system.

[0066] The first signal conversion filter 221 is a comb filter having Figure 6 The first signal conversion filter 221 can obtain desired characteristics according to the coefficients a and b and the signs.

[0067] The coefficients a and b can be calculated based on the processing conditions received from the communication module described below. In addition, based on the received processing conditions, such as revolutions per minute (RPM), number of blades and tool type, the filter order, signal passing characteristics and cutoff frequency of the first low-pass filter 222 can be calculated.

[0068] In order to improve the efficiency of repeated processing, the coefficients calculated in this way can be stored in a database (DB). When the processing conditions are equal to the processing conditions previously input, the coefficients stored in the DB can be used without the above coefficient calculation process.

[0069] The response of the first signal conversion filter 221 has N peaks or notches at constant frequency intervals. Each peak passes a signal, and each notch interrupts a signal. At this time, N becomes the order of the filter, and the number of coefficients a and b calculated by the first signal conversion filter 221 can correspond to the order N, expressed as a coefficient array.

[0070] The coefficient array is characterized in that only the first and last items have values, the other items are filled with 0, and the first item of the array of coefficient a is always 1. Therefore, in order to save the memory resources required by the tool visualization unit 22, only the cutoff frequency of the first low-pass filter 222 and the main coefficient values ​​of the first signal conversion filter 221 (i.e., the comb filter) are stored in the DB.

[0071] The cutoff frequency of the first low-pass filter 222 can be calculated by the equation Fc (Hz) = (frpm × Nfl) + 10. Here, frpm represents the tool rotation frequency, and Nfl represents the number of blades. The cutoff frequency of the first low-pass filter 222 can be calculated by the number of blades and the RPM obtained from the communication module 232.

[0072] The coefficients of the first signal conversion filter 221 calculated in this way are input to the digital filter together with the sensor signal, and then filtered. In this case, it is necessary to input a coefficient array having a normal number of coefficients corresponding to the order to the digital filter. Therefore, a process of generating an array of coefficients a and b according to the values ​​stored in the DB is performed.

[0073] The norm array of coefficients a and b and the sensor signal are input to the digital filter to perform a filtering operation, and then pass through the first low-pass filter 222 with the recalculated cutoff frequency Fc to remove unnecessary pseudo noise high-frequency signals.

[0074] This series of processes is executed as follows Figure 7 The first signal conversion filter 221 receives machining conditions, such as RPM and the number of blades, from the communication module 232 in step S10, and determines in step S12 whether the received machining conditions correspond to the previously received machining conditions.

[0075] When the received processing condition corresponds to the previously received processing condition, the first signal conversion filter 221 takes out the filter coefficient previously stored in the DB in step S14. On the other hand, when the received processing condition does not correspond to the previously received processing condition, the first signal conversion filter 221 calculates the filter coefficient in step S16, and the first low-pass filter 222 calculates the LPF coefficient in step S18. At this time, in step S20, the filter coefficient of the first signal conversion filter 221 and the LPF coefficient of the first low-pass filter 222 may be stored in the DB.

[0076] Since a coefficient array (the coefficient array has a norm number of coefficients corresponding to the order) needs to be input into the digital filter, in step S22, the first signal conversion filter 221 generates an array of coefficients a and b based on the values ​​stored in DB, and in step S24, the digital filter filters the array of coefficients a and b and the x-axis signal.

[0077] In step S26 , the first low pass filter 222 removes the pseudo noise high frequency signal from the signal filtered by the digital filter.

[0078] The second signal conversion filter 223 and the second low pass filter 224 operate in the same manner as the first signal conversion filter 221 and the first low pass filter 222, except that the second signal conversion filter 223 and the second low pass filter 224 filter the y-axis signal. Therefore, a detailed description thereof will be omitted herein.

[0079] The vector calculation module 225 calculates the norm value of the resultant force corresponding to the x-axis signal and the y-axis signal by performing a norm operation on the x-axis signal filtered by the first low-pass filter 222 and the y-axis signal filtered by the second low-pass filter 224 .

[0080] like Figure 8As shown, each of the x-axis and y-axis signals can be considered as a vector component having a direction and a magnitude. Since the sensors are arranged at a 90 degree angle to collect signals, the vector calculation module 225 can calculate the value corresponding to the combined force of the two axes through a norm operation.

[0081] The tool visualization module 226 visualizes the state of the tool through a polar coordinate graph based on the norm value calculated by the vector calculation module 225 .

[0082] Typically, the estimated cutting force calculated from the x-axis signal and the y-axis signal belongs to a tool holder-spindle vibration system, and therefore includes the same nonlinear elements, and the relative values ​​of the x-axis and y-axis at the same cutting position and conditions are always uniformly represented. When non-uniform cutting forces occur between the tool and the material, the corresponding state is immediately reflected in the signal. Therefore, the state change information generated when the material is cut by the tool can be found from the array of calculated continuous norm values.

[0083] According to this principle, the tool visualization module 226 calculates the length Npl of the array corresponding to one rotation of the tool in the array of continuous norm values, and arranges the norm value array in sequence, the norm value array corresponding to the length of the array on the polar coordinate diagram, thereby representing the blade state of each rotation of the tool. That is, the tool visualization module 226 uses Fig. 9 The tool state is visualized by using the polar coordinate diagram shown in FIG. 226. At this time, the tool visualization module 226 calculates the length Npl of the array corresponding to one rotation of the tool in the continuous norm value array based on the equation Npl=fs / frpm using the RPM information in the machining conditions received from the communication module 232. Here, fs represents the sampling frequency of the ADC, and frpm represents the rotation frequency of the tool.

[0084] Then, the tool visualization module 226 may sequentially store the norm value array corresponding to the calculated length Npl in a temporary memory, and plot the norm value array on a polar coordinate graph, thereby expressing the state of the blade for each rotation of the tool.

[0085] The equipment control unit 23 can detect the current state of the tool based on the polar coordinate diagram of the tool visualization unit 22, and transmit the alarm information to the computer numerical control (Computer Numerical Control, CNC) 30 of the machine tool or transmit the control signal to the programmable logic controller (PLC) 40 of the machine tool according to the detection result.

[0086] The device control unit 23 includes a communication module 232 , an input / output (I / O) module 233 , and a tool state detection module 231 .

[0087] The communication module 232 transmits the alarm information to the programmable logic controller 40 of the machine tool, and transmits the machining conditions to the tool visualization unit 22 .

[0088] The I / O module 233 transmits a control signal (eg, a stop signal of the machine tool) to the CNC 30 of the machine tool.

[0089] The tool state detection module 231 receives the polar coordinate diagram finally output by the tool visualization unit 22, detects the current tool state, and generates an output signal according to the current tool state. The process of detecting the tool state from the received polar coordinate diagram is as follows: Fig.11 shown.

[0090] Tool status detection is performed based on the shape of the graph displayed on the polar coordinate system. The tool status is divided into normal, worn, defective and completely damaged.

[0091] The tool status by the tool visualization unit 22 is characterized in that the shape of each blade is represented as an elliptical closed curve, and the status of each blade is represented as a change in the ratio of the major axis to the minor axis of the corresponding ellipse.

[0092] The tool state detection module 231 sets a search area to detect the tool state by dividing 360 degrees of the polar coordinates by the number of blades of the tool received from the communication module 232. Then, the tool state detection module 231 calculates the maximum value in each search area to calculate the major axis length of the ellipse representing the blade, and calculates the median value in each search area to calculate the minor axis length of the ellipse.

[0093] Fig. 10A It is shown that the tool state corresponds to a normal situation, the major axis lengths of the various ellipses are similar to each other, and the angle of the ellipse is the same as the actual tool blade angle.

[0094] Fig. 10B It shows that the tool state corresponds to a case of wear, the major axis length of the ellipse corresponding to the worn blade decreases, and the major axis length of the ellipse corresponding to the next blade following the worn blade in the rotation direction increases.

[0095] Fig. 10C It is shown that the tool state corresponds to a defect, and the ellipse corresponding to the defective blade disappears or has a very short major axis.

[0096] Fig. 10D The tool state is shown corresponding to a completely damaged case, and the normal ellipse is not shown.

[0097] When a state other than the normal tool state is detected based on the detection result, the tool state detection module 231 provides alarm information to the CNC 30 of the machine tool by using a communication module of Ethernet or other networks. In addition, when rapid equipment control is required, the tool state detection module 231 transmits a signal to the program logic controller 40 of the machine tool through the I / O module 233 to perform immediate control of the equipment such as transport stop or emergency stop.

[0098] In addition, the tool state detection module 231 can receive a digital signal (SYNC signal) from the program logic controller 40 of the machine tool through the I / O module 233, and perform tool state monitoring and tool visualization in the user's desired processing section so as to accurately match the actual processing point with the tool state monitoring point.

[0099] Thus, in step S30 , the tool state detection module 231 calls the polar coordinate diagram finally output from the tool visualization unit 22 .

[0100] In step S32 , the tool state detection module 231 receives the digital signal (SYNC signal) from the I / O module 233 , and in step S34 , the tool state detection module 231 determines whether the digital signal (SYNC signal) is in an on state.

[0101] When the judgment result of step S34 indicates that the digital signal (SYNC signal) is in the on state, the tool state detection module 231 receives the processing conditions (number of blades) from the communication module in step S36, and in step S38, sets the search area by dividing 360 degrees of the polar coordinates by the number of blades of the tool.

[0102] With the search area set, in step S40, the tool state detection module 231 calculates the major axis length of the ellipse representing each blade by calculating the maximum value in each search area, and calculates the minor axis length of the ellipse by calculating the median value in each search area.

[0103] At this time, in steps S42, S44 and S46, the tool state detection module 231 detects the tool state according to the shape of the graph displayed on the polar coordinate system, and determines whether the tool state corresponds to normal, worn or damaged.

[0104] When the judgment result indicates that the tool state corresponds to wear, in step S48, the tool state detection module 231 outputs an alarm message to the program logic controller 40 of the machine tool. In addition, when the judgment result indicates that the tool state corresponds to damage, in step S50, the tool state detection module 231 outputs a damage alarm to the program logic controller 40 of the machine tool, and in step S52, outputs a stop signal of the machine tool to the CNC 30.

[0105] Fig.12 , Fig.13 It is a schematic diagram showing that the present embodiment is applied to a lathe.

[0106] The sensor unit 10 may be Fig.12 Mounted on the spindle of a lathe as shown, or as Fig.13 The first acceleration sensor 11 and the second acceleration sensor 13 are respectively mounted on a tool or a turret.

[0107] Fig.14 is a schematic diagram of an example of another configuration of a tool visualization unit according to an embodiment of the present application.

[0108] refer to Fig.14 The tool visualization unit 22 may have a configuration in which the signal conversion filter 226 and the low-pass filter 227 are arranged behind the vector calculation module 225, thereby reducing the total data volume. This configuration may reduce the manufacturing cost of the tool visualization unit 22 and improve the efficiency of the tool visualization unit 22.

[0109] According to an embodiment of the present application, a device for detecting the status of a tool in a machine tool includes two MEMS-type vibration accelerometers attached to a non-rotating part of a spindle, which are used to measure signals in a wired manner during machining, analyze the measured signals, and visualize the accurate status of the tool, thereby detecting the status of the tool.

[0110] In addition, based on the visualized tool status, the device for detecting the tool status in a machine tool according to an embodiment of the present application can output an alarm or perform control (such as emergency stop) according to predetermined conditions, thereby preventing material processing defects.

[0111] The embodiments described in this specification can be implemented, for example, with methods or processes, devices, software programs, data streams or signals. Although features are discussed only in a single text (e.g., only in methods), the features discussed can be implemented in another type (e.g., devices or programs). The device can be implemented in suitable hardware, software or firmware. The method can be implemented in a device such as a processor, which generally refers to a processing device including, for example, a computer, a microprocessor, an integrated circuit or a programmable logic device. The processor includes communication devices such as computers, mobile phones, personal digital assistants (PDAs) and other devices that can facilitate information communication between end users.

[0112] Although the exemplary embodiments of the present application are disclosed for illustrative purposes, it will be appreciated by those skilled in the art that various modifications, additions and substitutions are possible without departing from the scope and spirit of the present application as defined in the appended claims. Therefore, the true technical scope of the present application should be defined by the claims.

Claims

1. A device for detecting the state of a tool in a machine tool, comprising: A sensor unit, used for sensing the acceleration of the spindle of the machine tool in the x-axis direction and the y-axis direction during the machining process; and a processing device for converting the x-axis signal and the y-axis signal sensed by the sensor unit into a signal capable of representing the cutting force by processing the x-axis signal and the y-axis signal, detecting a resultant force, and plotting the detected resultant force on a polar coordinate system; in, The resultant force is represented by the norm value generated by adding the signals representing the cutting force in the x-axis direction and the y-axis direction. Wherein, the processing equipment comprises: A signal processing unit, configured to filter the signal sensed by the sensor unit and convert the filtered signal into a digital signal to prevent aliasing of the signal; a tool visualization unit for converting the signal input from the signal processing unit into a signal capable of representing a cutting force based on a parameter set according to a machining condition, generating a norm value by adding the converted x-axis signal and the y-axis signal, and then creating a graph by plotting the norm value on a polar coordinate system, wherein a state of the tool during rotation and the number of blades are reflected in the graph; and The device control unit is configured to detect a current state of the tool based on the polar coordinate diagram of the tool visualization unit and according to a shape of the diagram displayed on the polar coordinate system.

2. The device according to claim 1, wherein: The sensor unit comprises: A first acceleration sensor, used for sensing the acceleration of the spindle in the x-axis direction; a first amplifier, used to amplify the signal sensed by the first acceleration sensor; A second acceleration sensor, used for sensing the acceleration of the main shaft in the y-axis direction; a second amplifier, used to amplify the signal sensed by the second acceleration sensor, The first acceleration sensor and the second acceleration sensor are both arranged at a preset angle.

3. The device according to claim 1, wherein: The sensor unit is mounted on any one of a main shaft of the machine tool, a coupling on the main shaft, a tool, and a turret.

4. The device according to claim 1, wherein: The signal processing unit comprises: A first anti-aliasing filter, used for filtering the x-axis signal to prevent aliasing of the x-axis signal; A first analog-to-digital converter, configured to convert a signal output from the first anti-aliasing filter into a digital signal; A second anti-aliasing filter, configured to filter the y-axis signal to prevent aliasing of the y-axis signal; and The second analog-to-digital converter is used to convert the signal output from the second anti-aliasing filter into a digital signal.

5. The device according to claim 1, wherein: The tool visualization unit comprises: a first signal conversion filter, for extracting from the x-axis signal only a signal generated when the blade of the tool contacts the material during the cutting process according to the parameter; a first low-pass filter, for removing a pseudo-noise high-frequency signal from the signal filtered by the first signal conversion filter according to the parameter; a second signal conversion filter, for extracting from the y-axis signal only a signal generated when the blade of the tool contacts the material during the cutting process according to the parameter; a second low pass filter LPF, used to remove a pseudo noise high frequency signal from the signal filtered by the second signal conversion filter according to the parameter; a vector calculation module, configured to calculate a norm value of a resultant force corresponding to the x-axis signal and the y-axis signal by performing norm operations on the signals filtered by the first low-pass filter and the second low-pass filter respectively; and A tool visualization module is used to visualize the tool state by plotting the norm value calculated by the vector calculation module on a polar coordinate graph.

6. The device according to claim 5, wherein: The tool visualization module calculates the length of the array corresponding to one rotation of the tool from an array of continuous norm values, and expresses the blade state of the tool each rotation of the tool by arranging the norms corresponding to the length of the array in sequence on the polar coordinate diagram.

7. The device according to claim 1, wherein: The device control unit comprises: a communication module for transmitting alarm information to the computer numerical control of the machine tool; an input / output module for transmitting control signals to a programmable logic controller of the machine tool; The tool status detection module is used to detect the tool status based on the polar coordinate diagram output by the tool visualization unit, and according to the detection result, transmit the alarm information to the programmable logic controller of the machine tool through the communication module, or transmit the control signal to the computer numerical control of the machine tool.

8. The device according to claim 7, wherein: The tool state detection module sets the search area by dividing 360 degrees of the polar coordinate system by the number of blades of the tool, calculates the major axis length of the ellipse representing the blade by calculating the maximum value in each of the search areas, and calculates the minor axis length of the ellipse by calculating the median of each of the search areas.

9. The device according to claim 8, wherein: The tool status detection module classifies the tool status into normal, worn, defective and completely damaged.

10. The device according to claim 8, wherein: When the length of the major axis of the ellipse is within a preset range, and the angle of the ellipse is the same as the actual tool blade angle, the tool state detection module determines that the tool state corresponds to normal; When the major axis length of the ellipse corresponding to the worn blade decreases, and the major axis length of the ellipse corresponding to the next blade following the worn blade in the rotation direction increases, the tool state detection module determines that the tool state corresponds to wear; when the ellipse corresponding to the defective blade disappears or the major axis length is equal to or less than a preset length, the tool state detection module determines that the tool state corresponds to defect; When the ellipse does not represent the shape of a preset normal ellipse, the tool state detection module determines that the tool state corresponds to complete damage.

Images