CN113874798B - CNC device - Google Patents

Abstract

A numerical control device (1) according to the present invention controls the operation of a machine tool (2) for machining a workpiece with a tool, and comprises: a simultaneous movement generation unit (14) that generates a simultaneous movement command that causes the spindle rotation speed and the feed speed to each independently and continuously vary; a data acquisition unit (16) that synchronizes a control signal for controlling the work machine, which is generated based on the same-purpose operation command, with an operation state signal indicating the operation state of the corresponding work machine (2) and outputs the synchronized control signal as same-purpose data; a vibration determination unit (12) that determines, based on the same-purpose data, whether the vibration state of the machine tool (2) is stable machining, chatter vibration, or forced vibration; and a determination unit (13) that selects, as a selection parameter, a processing characteristic parameter that can be determined among processing characteristic parameters that indicate characteristics of a processing phenomenon between the tool and the workpiece, based on the determination result of the vibration determination unit (12), and determines the selection parameter using the determination data.

Description

CNC device

Technical field

The invention relates to a numerical control device for controlling working machinery.

Background technique

A machine tool is a processing device that performs removal processing by applying force or energy to a workpiece using a tool to remove unnecessary parts from the workpiece. In particular, in cutting processing, which is one type of removal processing, the cutting edge of the tool is brought into contact with the workpiece at a high speed, thereby causing shear damage on the surface of the workpiece and scraping unnecessary parts of the workpiece.

Cutting is a physical phenomenon in which machining technology and machine dynamics interact with each other. Therefore, in order to manage the machining state, it is preferable to manage both simultaneously. Here, the machining process refers to a series of processes in which the cutting edge of the tool invades the workpiece and generates chips while forming the machined surface. Mechanical dynamics refers to the behavior of mechanical components when the components constituting the machine are vibrated by vibration sources inside and outside the machine. Generally speaking, cutting processing is a phenomenon in which various physical phenomena including the above-mentioned machining technology and mechanical dynamics interact with each other in a complex manner, so it is difficult to conduct a comprehensive analysis. Therefore, at the production site, evaluation objects are limited to achieve processing management corresponding to the purpose.

As described above, in cutting processing, mechanical dynamics and machining technology influence each other, so the state of the machine tool before or after machining is different from the state of the machine tool during machining. That is, the state of the machine tool during processing cannot be accurately estimated before or after processing. Therefore, it is preferable to use the information obtained during machining to identify the mechanical dynamics and machining process. Using the results of machine dynamics and machining process identification, workers at the production site can effectively perform improvement operations such as managing tool life, setting efficient machining conditions, and changing the design of fixed fixtures. As a result, improvements in productivity are expected.

Patent Document 1 proposes the following method as a method of performing parameter identification based on information obtained by gradually changing processing conditions during actual processing. In the method described in Patent Document 1, the adaptability spectrum is calculated based on the displacement and force generated when machining is performed at multiple spindle speeds, and the peak value obtained when the adaptability spectrum of each spindle speed is synthesized is used to respond to the unique characteristics of the tool. Vibration frequency is calculated. In this method, the machine tool is made to perform machining operations in such a manner that the spindle rotation speed is changed step by step in the individual movements of each feed axis or in the combined movements of the feed axes, and the detection results of the displacement and force during processing are used to adapt the spectrum is calculated.

Patent Document 1: Japanese Patent Application Publication No. 2017-94463

Contents of the invention

However, in the method described in Patent Document 1, various adaptive spectrums are obtained by setting the feed amount so that chatter does not occur and changing the spindle rotation speed step by step, and calculating the natural vibration frequency. Therefore, in the method described in Patent Document 1, there is a problem that only the natural frequency of vibration can be identified and machining characteristic parameters such as relative cutting resistance cannot be identified. In addition, in the method described in Patent Document 1, when identifying parameters other than the natural vibration frequency, it is necessary to perform other identification operations. Furthermore, in the method described in Patent Document 1, the spindle rotation speed is only changed stepwise to a plurality of predetermined steps, so it takes time to obtain parameters corresponding to various spindle rotation speeds.

The present invention is proposed in view of the above situation, and its purpose is to obtain a numerical control device that can effectively identify machining characteristic parameters in a short time.

In order to solve the above-mentioned problems and achieve the purpose, the present invention is a numerical control device that controls the operation of a machine tool that has a spindle and a feed axis and processes a workpiece through a tool. The numerical control device has: a recognition action generation unit, It generates identification action instructions that cause the rotation speed and feed speed of the spindle to change independently and continuously. In addition, the numerical control device has a data acquisition unit that synchronizes a control signal for controlling the machine tool generated based on the recognized operation command and an operation state signal indicating an operation state of the machine tool operated based on the control signal to obtain the data as a data acquisition unit. The identification data is outputted; and the vibration determination unit determines whether the vibration state of the machine tool is stable machining, chatter vibration, or forced vibration based on the identification data. Furthermore, the numerical control device has an identification unit that selects, as a selection parameter, an identifiable machining characteristic parameter among the machining characteristic parameters indicating the characteristics of the machining phenomenon between the tool and the workpiece based on the identification result of the vibration determination unit, using The identification data is used to identify the selection parameters.

Effect of the invention

The numerical control device according to the present invention has the effect of being able to effectively identify machining characteristic parameters in a short time.

Description of drawings

FIG. 1 is a block diagram showing a structural example of a numerical control device according to Embodiment 1.

FIG. 2 is a diagram showing an example of a pattern of recognition operation instructions generated by the recognition operation generation unit in Embodiment 1. FIG.

FIG. 3 is a diagram showing an example of a pattern of recognition operation instructions generated by the recognition operation generating unit in Embodiment 1. FIG.

FIG. 4 is a diagram showing an example of a pattern of recognition operation instructions generated by the recognition operation generating unit in Embodiment 1. FIG.

FIG. 5 is a schematic diagram illustrating how interference force is transmitted to the table when the workpiece fixed to the table vibrates due to cutting force in Embodiment 1.

FIG. 6 is a diagram showing an example of the rotation angle of the tool at which the cutting edge of the tool comes into contact with the workpiece in Embodiment 1. FIG.

FIG. 7 is a diagram showing an example of the rotation angle of the tool when the cutting edge of the tool does not contact the workpiece in Embodiment 1. FIG.

FIG. 8 is a diagram showing the state of cutting at the first cutting edge when an offset amount occurs between the tool center and the spindle rotation center in Embodiment 1. FIG.

FIG. 9 is a diagram illustrating the state of cutting at the second cutting edge when an offset amount occurs between the tool center and the spindle rotation center in Embodiment 1. FIG.

FIG. 10 is a flowchart showing an example of the identification processing procedure in the identification unit of Embodiment 1 when the vibration determination unit determines that the vibration is judder.

FIG. 11 is a flowchart showing an example of the operation of the numerical control device according to the first embodiment.

FIG. 12 is a diagram showing a structural example of the processing circuit according to Embodiment 1.

FIG. 13 is a block diagram showing a structural example of a numerical control device according to Embodiment 2.

FIG. 14 is a flowchart showing an example of the operation of the numerical control device according to the second embodiment.

FIG. 15 is a block diagram showing a structural example of a numerical control device according to Embodiment 3.

FIG. 16 is a block diagram showing a structural example of a numerical control device according to Embodiment 4.

Detailed ways

Hereinafter, the numerical control device according to the embodiment of the present invention will be described in detail based on the drawings. In addition, this invention is not limited to this embodiment.

Embodiment 1.

FIG. 1 is a block diagram showing a structural example of a numerical control device 1 according to Embodiment 1 of the present invention. The numerical control device 1 of Embodiment 1 controls the operation of the machine tool 2 by transmitting a control signal to the machine tool 2 and receives an operation state signal indicating the operation state of the machine machine 2 from a sensor (not shown).

The working machine 2 has a spindle and a feed axis, and processes the workpiece through a tool. Specifically, the machine tool 2 operates at least one of a tool and a workpiece to perform cutting processing on the workpiece. For example, the machine tool 2 has a spindle that imparts rotational motion to a tool or a workpiece, and a feed axis that is a servo axis that imparts a position to the tool or the workpiece. The spindle and the feed axis each have an electric motor.

The machine tool 2 has a sensor that detects the operating state of the machine tool 2 and outputs the detection result as an operating state signal. Sensors included in the machine tool 2 include sensors capable of detecting vibration of at least one of the tool and the workpiece. Sensors capable of detecting vibration of at least one of the tool and the workpiece are, for example, linear encoders and current sensors that are previously installed in the machine tool 2 for feedback control of each motor of the machine tool 2 . The linear encoder detects the position of each axis of the machine tool 2, and the current sensor detects the motor current of the motor of each axis. Other examples of the sensor include an acceleration sensor, a position sensor, a force sensor, or a microphone. Next, as an example, a linear encoder, a current sensor, and a force sensor will be described as the sensors included in the machine tool 2 . The force sensor is provided on, for example, a member such as a worktable constituting the feed axis or inside the member. The installation position of the force sensor is not limited to this, as long as it is installed at a position where the force between the tool and the workpiece can be detected.

As shown in FIG. 1 , the numerical control device 1 includes a correction unit 11 , a vibration determination unit 12 , an identification unit 13 , an identification operation generation unit 14 , a drive control unit 15 and a data acquisition unit 16 . The operation of each part of the numerical control device 1 according to the first embodiment will be described.

The identification operation generation unit 14 generates an identification operation command that independently and continuously changes the spindle rotation speed and the feed speed of the machine tool 2 , and outputs the identification operation command to the drive control unit 15 . Spindle speed is the rotation speed of the spindle, indicating how many times the spindle rotates per unit time. The identification operation is an operation in which the drive control unit 15 and the machine tool 2 each generate a control signal and an operating state signal in order to obtain identification data that is used when the identification unit 13 performs identification processing described later. The identification action command is a command generated for the purpose of identification action, and includes a command for the spindle speed and a command for the feed speed.

2 to 4 are diagrams showing examples of patterns of recognition operation instructions generated by the recognition operation generation unit 14 in Embodiment 1. Hereinafter, the mode for recognizing action commands will also be referred to as a command mode. Figures 2 to 4 show command patterns in which the spindle rotation speed and the feed speed each continuously change from the identification operation start time t1 to the identification operation end time t2. The horizontal axis in Figures 2 to 4 represents time (moment), the vertical axis represents the spindle speed in the upper layer, and the feed speed in the lower layer. In the following, the spindle rotation speed and feed speed may be described as S and F respectively.

Here, S0 is the spindle speed before the identification operation, that is, the reference spindle speed, and S1 is the maximum value of the spindle speed during the identification operation. T1 is the time constant when accelerating from the state where the spindle rotation speed is S0 to the state where the spindle rotation speed is S1. T2 is the time constant when accelerating from the state where the feed speed is F0 to the state where the feed speed is F1. Figure 2 is a command pattern in which the spindle speed and feed speed are accelerated and decelerated respectively. In the example shown in Figure 2, after the spindle speed accelerates with the time constant T1, it decelerates if the spindle speed is called S1. Furthermore, if the spindle rotation speed reaches S0 through deceleration, it remains unchanged at S0. When the spindle speed reaches S0 through deceleration, the feed speed accelerates with the time constant T2 until it reaches F1. Then, when the feed speed becomes F1, the feed speed is decelerated.

FIG. 3 shows a command pattern in which after the spindle speed is accelerated, the feed speed is accelerated and then decelerated, and the spindle speed is decelerated. Figure 4 shows a command pattern in which the spindle speed accelerates and then decelerates, and the feed speed repeats acceleration and deceleration as the spindle speed changes.

In addition, in FIGS. 2 to 4 , an example is shown in which S1 is used as the maximum value of the spindle rotation speed in the identification operation and the spindle rotation speed is changed between S0 and S1 . However, the identification operation generation unit 14 may also be configured for the identification operation. The minimum value of the spindle speed S2 is set, showing a command pattern that changes within the range of S0 to S2. Similarly, regarding the feed speed, the minimum value F2 of the feed speed in the identification operation can also be set, and a command pattern changing between F0 and F2 can be shown.

In addition, FIGS. 2 to 4 exemplify a command pattern that accelerates and decelerates in a triangular waveform. However, if it is a command pattern that continuously accelerates and decelerates the spindle rotation speed and the feed speed, the recognition operation generating unit 14 can generate any command pattern. . For example, the recognition operation generating unit 14 may generate a command pattern that changes in a sinusoidal wave shape or an S-shaped curve shape instead of a triangular wave.

As described above, the identification operation generating unit 14 can generate an identification operation including various combinations of the spindle rotation speed and the feed speed by independently changing the spindle rotation speed and the feed speed.

It is known that the force generated when the tool cuts the workpiece, that is, the magnitude of the cutting force mainly depends on the feed amount per blade, and the vibration period of the cutting force mainly depends on the spindle speed. Therefore, generally speaking, when changing the spindle rotation speed and feed speed, make them change at the same ratio. As a result, the load on the cutting edge of the tool becomes constant, so the magnitude of the cutting force generated by one cutting edge of the tool does not change. The identification operation generating unit 14 changes the spindle rotation speed and the feed speed independently, so that the magnitude and amplitude of the cutting force can be varied in various ways, and can cause the machine tool 2 during the identification operation to generate various types of events described later. vibration state.

The drive control unit 15 generates a control signal for controlling the machine tool 2 based on the recognition operation command generated by the recognition operation generation unit 14 so that the main shaft and the feed axis of the machine machine 2 operate in the manner specified by the recognition operation command. Carry out operation. Here, the control signal is a command for the spindle and the feed axis of the machine tool 2, and includes at least one of a position command, a speed command, and a current command for each motor of the spindle and the feed axis. In addition, when the recognition operation command is not input from the recognition operation generation unit 14 , that is, during a normal machining operation, the drive control unit 15 generates a target for the machine tool based on the machining path and the reference spindle rotation speed and the reference feed speed in the machining path. 2 control signal. In addition, the drive control unit 15 obtains a correction signal from the correction unit 11 to be described later, corrects the control signal for the machine tool 2 based on the correction signal, and outputs the corrected control signal to the machine machine 2 .

A machining path, a reference spindle rotation speed, and a reference feed speed in the machining path are preset in the drive control unit 15 . The processing path and the reference spindle speed and reference feed speed in the processing path can be given by the CNC program. When the recognition operation command is input from the recognition operation generation unit 14 , the drive control unit 15 also generates a control signal so that the set machining path does not change and only the spindle rotation speed and the feed speed change according to the recognition operation command. The machine tool 2 has an electric motor and a motor control device for each axis. The electric motor control device controls the electric motor based on feedback signals such as control signals, position, speed, and motor current received from the drive control unit 15 . The position and speed feedback signals are calculated based on the position detected by the linear encoder, and the motor current feedback signal is calculated based on the detection results of the current sensor. The feedback signals of position, speed, and motor current will be referred to as position feedback signal, speed feedback signal, and current feedback signal respectively below.

The data acquisition unit 16 synchronizes the control signal output from the drive control unit 15 with an operating state signal indicating the operating state of the machine tool 2 operating based on the control signal, and outputs the synchronized control signal as identification data. Specifically, the data acquisition unit 16 uses the control signal output from the drive control unit 15 and the operating state signal output from the sensor of the machine tool 2 to temporally synchronize the data included in each signal, and provides the vibration determination data as identification data. unit 12 and recognition unit 13 output. As mentioned above, the operating state signal is a signal indicating the operating state of the machine tool 2 and includes a signal capable of detecting the vibration of at least one of the tool and the workpiece. Here, as mentioned above, it is assumed that the sensors include a linear encoder, a current sensor, and a force sensor. Therefore, the data acquisition unit 16 can acquire the feedback signals of the position, speed, and current of the spindle and the feed axis and the force sensor detection signals. The force, torque, etc. are used as operating status signals. Hereinafter, actual measured values such as force and torque detected by the force sensor will also be referred to as force information. The operating status signal is generated after the machine tool receives the control signal. Therefore, due to the influence of the time required for communication and the like, the operating status signal is temporally delayed with respect to the corresponding control signal. Therefore, the data acquisition unit 16 compensates for the time difference between the two signals by shifting the data included in the operating status signal or the data included in the control signal by a time corresponding to the difference in communication time or the like. The data acquisition unit 16 aggregates data in which the temporal offset has been compensated, that is, synchronized data, into identification data, and outputs the data to the vibration determination unit 12 and the identification unit 13 .

The vibration determination unit 12 uses the identification data to determine whether vibration has occurred in the machine tool 2 , and if it is determined that vibration has occurred, determines the type of vibration, and outputs the determination result to the identification unit 13 . Next, the details of the vibration determination unit 12 will be described. In addition, the vibration when the vibration determination unit 12 determines whether vibration has occurred indicates a vibration having a larger amplitude than a vibration component caused by the cutting force of the tool and the workpiece.

The determination of occurrence of vibration by the vibration determination unit 12 is performed by a well-known means. For example, when the force or torque indicated by the force information output from the force sensor exceeds a predetermined amplitude in the time domain, it is determined that vibration has occurred. The type of signal used for vibration determination is not limited to the force information. For example, the vibration determination unit 12 may determine whether vibration occurs using a current feedback signal included in the operating state signal. Alternatively, the vibration determination unit 12 may convert the signal used to determine whether vibration has occurred into a signal in a frequency range, and determine that vibration has occurred when the vibration component with the largest amplitude in the frequency range exceeds a predetermined amplitude.

In addition, there are forced vibration and self-excited vibration in vibration phenomena, and flutter is a type of self-excited vibration. Forced vibration is a vibration phenomenon in which the cutting force becomes the vibration source and the components existing near the tool or workpiece are excited. It is known that due to this property, the vibration frequency of the forced vibration becomes an integer multiple of the basic cutting frequency. On the other hand, self-excited vibration, that is, chatter, is a vibration phenomenon that occurs when the system composed of cutting force and displacement of the member is unstable. Based on this property, it is known that the vibration frequency of chatter becomes a non-integer multiple of the basic cutting frequency. In the above, the basic cutting frequency is the frequency obtained by multiplying the spindle speed by the number of tool edges.

When the vibration determination unit 12 determines that vibration has occurred, the vibration determination unit 12 determines the type of vibration. Specifically, the vibration determination unit 12 determines whether the generated vibration is a forced vibration or a flutter vibration as a determination of the type of vibration. The type of vibration is determined based on whether the determined frequency of vibration is an integer multiple of the basic cutting frequency. That is, if the frequency of vibration is an integer multiple of the basic cutting frequency, the vibration determination unit 12 determines it to be forced vibration, and if the frequency is a non-integer multiple of the basic cutting frequency, it determines it to be chatter vibration.

In addition, when the vibration determination unit 12 determines that no vibration occurs, it determines that the processing is stable. Stable machining is a machining state in which only vibration components caused by the cutting force of the tool and the workpiece are generated, and no vibration near the natural vibration frequency of the component is excited.

The vibration determination unit 12 always executes the above-described processing to determine whether the identification data at each time point is stable machining, forced vibration, or chatter vibration, and outputs the determination result to the identification unit 13 as a vibration determination result. That is, the vibration determination unit 12 determines, based on the identification data, which one of a plurality of states of stable machining, forced vibration, or chatter vibration the vibration state of the machine tool 2 is.

The identification unit 13 selects an identifiable machining characteristic parameter among the machining characteristic parameters as a selection parameter based on the identification result of the vibration determination unit 12 , and identifies the selection parameter using the identification data input from the data acquisition unit 16 . In addition, the identification unit 13 further selects, as a selection parameter, an identifiable dynamic characteristic parameter among the dynamic characteristic parameters based on the identification result of the vibration determination unit 12 . In the following, the selection parameters will also be referred to as identifiable parameters. The recognition unit 13 outputs the result of the recognition process to the correction unit 11 . The identification process is executed using identification data and processing condition information. The processing condition information is information indicating the processing conditions in the recognition operation, and is information set in the recognition unit 13 in advance. The processing condition information includes, for example, the tool diameter, the number of tool edges, the tool twist angle, the tool axial feed amount, the tool radial feed amount, and the machining style of upper or lower cutting.

In the following, an example will be described in which the identification unit 13 identifies both the dynamic characteristic parameters and the machining characteristic parameters. However, the identification unit 13 may identify only one of the dynamic characteristic parameters and the machining characteristic parameters. For example, based on the determination result of the vibration determination unit 12 , the identification unit 13 selects an identifiable machining characteristic parameter among the machining characteristic parameters as the selection parameter, and identifies the selection parameter using the identification data.

Generally, the spindle speed and feed rate during machining are specified as constant values. In this case, the identification unit 13 can only acquire identification data when machining is performed using a set of spindle rotational speeds and feed speeds. The identification data includes the operating state signal detected by the sensor of the machine tool 2 as described above. Therefore, the identification unit 13 can only obtain the operating state signal when processing is performed using one set of spindle rotation speed and feed speed. . However, in the present embodiment, the recognition operation generating unit 14 generates commands in which the spindle rotation speed and the feed speed each change continuously. Therefore, the recognition unit 13 can obtain the operation performed by using different combinations of the spindle rotation speed and the feed speed at each time. Operation status signal during processing.

Here, the dynamic characteristic parameters and machining characteristic parameters are explained. The dynamic characteristic parameter is a parameter that represents the characteristics of a dynamic model described later, and is a parameter that represents the vibration characteristics of the machine tool 2 . Dynamic characteristic parameters are, for example, equivalent mass, attenuation coefficient, and natural vibration frequency. On the other hand, the machining characteristic parameter is a parameter that represents the characteristics of a machining process model described later, and is a parameter that represents the characteristics of the machining phenomenon between the tool and the workpiece. Machining characteristic parameters are, for example, relative cutting resistance, edge force, tool eccentricity, and tool wear amplitude.

The dynamic model is a mathematical model describing the dynamics of the mechanical components, tools, and workpieces inside the machine tool 2 . Next, an example of a dynamic model is explained. FIG. 5 is a schematic diagram illustrating how interference force is transmitted to the table when the workpiece fixed to the table vibrates due to cutting force in Embodiment 1. FIG. 5 shows an example in which the machine tool 2 performs milling processing by rotating the tool 33 . In FIG. 5 , a structural example is assumed in which a workpiece 32 is placed on a table 31 constituting a drive shaft, and a tool system 34 constituting a spindle holds a tool 33 . In addition, in FIG. 5 , the relative displacement 35 represents the relative displacement of the front end of the workpiece relative to the worktable 31 in the vibration direction, the cutting force 36 represents the cutting force in the workpiece 32 , and the interference force 37 represents the force transmitted to the worktable 31 . Interference power. The relationship between the cutting force 36, the interference force 37, and the relative displacement 35 at this time can be expressed by the following equation (1). The dynamic model shown in equation (1) is used to calculate the interference force 37 transmitted to the feed axis through the mechanical structure including the tool 33 or the workpiece 32 when the cutting force 36 is generated. A mathematical model that calculates the positional deviation generated in each feed axis based on the mechanical structure.

Formula 1

it's here,

f _c : cutting force, f _d : interference force, m _t : equivalent mass,

x: relative displacement of the front end of the workpiece relative to the vibration direction of the worktable

ζ: attenuation coefficient, ω _n : natural vibration frequency

The dynamic model represented by equation (1) describes the workpiece 32 on the table 31 as a one-degree-of-freedom vibration system, but the dynamic model is not limited to the above example. For example, it may be described as a multi-degree-of-freedom vibration system including a fixing part for fixing the workpiece 32 and the table 31 . Furthermore, a dynamic model related to the tool-side member composed of the tool 33, the tool system 34, and the spindle motor can be set. Furthermore, a dynamic model may be set as a vibration system that combines the workpiece-side member and the tool-side member including the fixing portion that fixes the workpiece 32 and the table 31 .

The machining process model is a mathematical model that describes the cutting process between the tool and the workpiece. The following equation (2) represents an example of a machining process model.

Formula 2

_fc : cutting force, ^Kc : relative cutting resistance, ^Kce : edge force,

a: tool axial feed amount, h: workpiece removal thickness, Tool rotation angle, t: time

Tool engagement angle,/> Tool non-engagement angle

The above-mentioned equation (2) is an equation that calculates the cutting force applied to the workpiece 32 by the tool 33 based on the cutting thickness corresponding to the rotation angle of the tool 33 at each time. Here, the cutting thickness refers to the thickness of the workpiece 32 when the cutting edge of the tool 33 passes through the workpiece 32 . As shown in FIGS. 6 and 7 , the cutting force is calculated as a value greater than or equal to zero when the tool edge is in contact with the workpiece 32 , but when it is at an angle where the tool edge is not in contact with the workpiece 32 , the cutting force is calculated as a value greater than or equal to zero. Calculated as zero. FIG. 6 is a diagram showing an example of the rotation angle of the tool 33 when the tool edge is in contact with the workpiece 32 in Embodiment 1. FIG. 7 is a diagram showing an example of the rotation angle of the tool 33 when the tool edge is not in contact with the workpiece 32 . picture. That is, at each rotation angle or time of the tool 33, whether it is in contact with the workpiece is determined based on the position deviation, and the cutting thickness is calculated when the tool tip is in contact with the workpiece 32, and when the tool tip is not in contact with the workpiece 32, the cutting thickness is calculated. In the case of , the resection thickness is calculated as zero.

The calculation shown in equation (2) is performed in three directions: the tangential direction, the radial direction, and the axial direction of the tool, so that the cutting force in the three directions can be calculated. In the machining process model, the cutting force having the components in the three directions is multiplied by the rotation matrix corresponding to the rotation angle of the tool 33, that is, the tool rotation angle, and coordinate transformation is performed, whereby the coordinate transformation in the tool reference coordinate system is performed. Cutting forces are calculated. An example of coordinate transformation is shown in equation (3).

Formula 3

f _cx : cutting force in the X-axis direction, f _cy : cutting force in the Y-axis direction, f _cz : cutting force in the Z-axis direction,

f _ct : cutting force in the tangential direction of the tool, f _cr : cutting force in the radial direction of the tool, f _ca : cutting force in the axial direction of the tool

By executing the calculations shown in the above-mentioned equations (2) and (3) for the number of tool edges and accumulating the calculation results, the cutting force generated by the entire tool can be finally calculated. The machining process model shown in formula (2) is used to calculate the resection thickness based on the relative position between the tool tip and the processing object of the tool 33, that is, the workpiece 32, and the tool rotation angle. Based on the resection thickness, the relationship between the tool and the workpiece is calculated. A mathematical model for calculating the cutting forces generated during the cutting process. The cutting thickness in equation (2) can be calculated using equation (4) using the feed amount per blade and the tool rotation angle.

Formula 4

c: Feed per blade

As another example, the resection thickness can also be calculated using equation (5).

Formula 5

v: the tool center displacement in the tool radius direction, w: the front machining surface displacement in the tool radius direction,

Δr: Correction amount corresponding to each tool edge, N _tooth : Tool edge number

Equation (5) is a variation calculated based on the difference between the current tool displacement and the front machining surface generated by the tool edge in front of the first edge, and is added with the equation (4). Calculation formula for the resection thickness corresponding to the correction amount at the blade tip. In the calculation shown in Equation (5), the sum of the displacement amount that affects the shape of the machined surface is the sum of the displacement amount caused by the current tool edge and the displacement amount caused by the tool edge one edge ahead or more. The removal thickness is corrected by the difference in displacement generated at the current tool tip. That is, the cutting thickness is based on the trajectory generated based on the current tool edge related to cutting and the tool edge that affects the shape of the machined surface within the tool edge that is one or more edges in front based on the current tool edge. The difference between the sharp trajectories is calculated.

Here, the tool center displacement amount v is a displacement amount corresponding to the component of the relative displacement x in the equation (1) in the direction from the tool center to the tool edge. In addition, the displacement amount w of the front machining surface is the amount of displacement generated on the machining surface due to the relative displacement x when cutting with the tool edge that is one or more front edges. In addition, the tool edge that is equal to or greater than 1 edge is the tool edge that is related to cutting at a previous time compared to the time that is based on the tool edge that is cutting. For example, in a tool with 2 edges, if the tool edge currently cutting is the 2nd edge, the tool edge in front of the 1st edge is the 1st edge before the 180-degree rotation, and the 2nd edge is 360 degrees in front of it. The cutting edge of the tool before the 2nd and 3rd edges before rotation is the 1st edge before 540 degree rotation. When the tool is displaced during cutting and the cutting edge is temporarily separated from the workpiece 32, the current cutting edge not only affects the front machining surface generated by the cutting edge of 1 cutting edge, but also the front surface formed by the cutting edge of 2 or more cutting edges. The front machining surface generated by the tool edge is cut.

Furthermore, in the calculation shown in equation (5), the cutting thickness is corrected by a correction amount corresponding to the tool edge number, which is a number indicating the tool edge, and the tool rotation angle. Here, the correction amount is introduced in order to correct the change in the removal thickness caused by cutting with a different rotation radius for each tool edge. As an example where correction amounts need to be introduced, the following is an example. For example, when wear, curling, etc. occurs at a specific cutting edge, the rotation radius of the cutting edge becomes shorter than that of other cutting edges, so a correction amount corresponding to the wear width, curling width, etc. is added. . As another example, in a cutting edge replaceable type tool, when there is an installation error of the cutting edge of the tool, a correction amount corresponding to the installation error is added. As another example, when the spindle rotation center and the tool center do not coincide with each other, that is, when tool eccentricity exists, a correction amount corresponding to the tool eccentricity amount is added. Furthermore, the tool center is the center of the circumscribed circle of the tool.

Tool eccentricity refers to the amount of offset that occurs between the tool center and the spindle rotation center as shown in Figures 8 and 9. The amount of increase or decrease in the rotation radius of the tool edge for each tool edge is The amount by which the thickness is corrected. FIG. 8 is a diagram showing the state of cutting at the first cutting edge when an offset amount occurs between the tool center and the spindle rotation center in Embodiment 1. FIG. 9 is a diagram showing the state of cutting between the tool center and the spindle rotation center. This is a diagram of the cutting situation at the second cutting edge when there is an offset between the centers. The first blade edge 43 and the second blade edge 44 are blade edges of the tool. In the example shown in FIGS. 8 and 9 , there is a deviation between the tool center 41 and the spindle rotation center 42 . In the case described above, the cutting thickness needs to be corrected relative to the cutting thickness without deviation, and the tool eccentricity amount represents the correction amount at this time. That is, the cutter eccentricity amount corresponding to the rotation angle of the cutter 33 is added to or subtracted from the cutting thickness. The example of correcting the cutting thickness by the correction amount is not limited to the above-mentioned example, and the correction amount may be appropriately changed according to the phenomenon occurring at the cutting edge of the tool.

In addition, the processing technology model is not limited to Formula (2). For example, equation (2) can be used to change the value of the relative cutting resistance when the cutting speed is higher than or equal to the threshold value at a high speed and when the cutting speed is lower than the threshold value at a low speed. Furthermore, a model in which process damping force is added to the right side of equation (2) can be used. Here, the process damping force is the force generated by the contact between the relief surface of the tool tip and the workpiece. The process damping can be expressed, for example, as a value obtained by multiplying the contact area of the relief surface by the process damping coefficient. In this case, the process damping coefficient becomes one of the processing characteristic parameters.

As another example, a machining process model for a tool with a twist angle can be used. Specifically, the following model can be used: the tool is divided into micro-thick tools in the axial direction, the cutting force in each divided micro-thickness tool is calculated, and the cutting force is accumulated in the tool axial direction. Calculate the final cutting force. As another example, a model that calculates the cutting thickness and cutting force by finite element analysis can be used.

Next, when the dynamic model is equation (1) and the machining process model is equation (2), parameters that can be identified are determined based on the vibration determination results, and the process of identifying the parameters is described. In addition, candidates for identifiable parameters described below are dynamic characteristic parameters, namely, equivalent mass, attenuation coefficient, natural vibration frequency, and machining characteristic parameters, namely, relative cutting resistance, edge force, and tool eccentricity.

When a vibration determination result indicating that it is stable machining, forced vibration, or chatter vibration is input from the vibration determination unit 12 as a vibration determination result, the identification unit 13 performs the following processing according to the vibration determination result. In addition, it is rare that forced vibration and chatter vibration occur simultaneously. In such a case, it is determined as chatter vibration and is identified.

[The judgment result is stable processing]

The identification unit 13 selects machining characteristic parameters, that is, relative cutting resistance and edge force, as parameters that can be identified. Furthermore, the identification unit 13 identifies the relative cutting resistance and edge force through the following processing. The identification unit 13 uses the force information output from the force sensor and the machining conditions pre-recorded in the identification unit 13 to calculate relative cutting resistance and edge force according to equations (2) to (4). That is, when formula (2) and formula (4) are substituted into formula (3), the calculated value of the force in each axial direction is substantially consistent with the actual measured value of the force detected by the force sensor. ) to calculate the relative cutting resistance and edge force. The calculation method of relative cutting resistance and edge force only needs to use known optimization methods or numerical simulation. For example, the least square multiplication or the gradient method can be used.

[When the judgment result is forced vibration]

The identification unit 13 selects the attenuation coefficient and natural vibration frequency, which are dynamic characteristic parameters, and relative cutting resistance and edge force, which are machining characteristic parameters, as identifiable parameters. Furthermore, the identification unit 13 identifies the attenuation coefficient, natural vibration frequency, relative cutting resistance, and edge force through the following processing.

The identification unit 13 uses the force information output from the force sensor and the machining conditions pre-recorded in the identification unit 13 to identify the attenuation coefficient, natural vibration frequency, relative cutting resistance, and edge force according to equations (1) to (4). Specifically, the actual measured value of the force detected by the force sensor is substituted for f _d in the following equation (6) obtained by deforming equation (1).

Formula 6

Then, the calculated value of the force in each axial direction calculated when formula (2) and formula (4) are substituted into formula (3) is substituted into f _c in formula (6). At this time, there is a combination of attenuation coefficient, natural vibration frequency, relative cutting resistance, and edge force that satisfies equation (6). Therefore, the identification unit 13 determines the combination of attenuation coefficient, natural vibration frequency, relative cutting resistance, and edge force that satisfies equation (6). combinations are calculated. Specifically, the identification unit 13 uses the gradient method to minimize the errors on both sides of equation (6), and searches for the attenuation coefficient, natural vibration frequency, relative cutting resistance, and edge force. As another method, the attenuation coefficient, natural vibration frequency, relative cutting resistance, and edge force can also be calculated by the least square method.

[When the judgment result is chatter]

The identification unit 13 selects the dynamic characteristic parameters, namely equivalent mass, attenuation coefficient, and natural vibration frequency, and the machining characteristic parameters, namely relative cutting resistance, edge force, and tool eccentricity, as identifiable parameters. Furthermore, the identification unit 13 identifies the equivalent mass, attenuation coefficient, natural vibration frequency, relative cutting resistance, edge force, and tool eccentricity through the following processing.

The identification unit 13 uses the force information output from the force sensor and the processing conditions pre-recorded in the identification unit 13 to calculate the equivalent mass and attenuation coefficient according to equations (1), (2), (3) and (5). , natural vibration frequency and relative cutting resistance, edge force and tool eccentricity are identified. Specifically, according to the sequence shown in Figure 10, the equivalent mass, attenuation coefficient, natural vibration frequency and relative cutting resistance, edge force and tool eccentricity can be identified.

FIG. 10 is a flowchart showing an example of the identification processing procedure in the identification unit 13 of Embodiment 1 when the vibration determination unit 12 determines that the vibration is vibration. First, in step S1, the identification unit 13 sets initial values for the parameter groups. The set of parameters at this time is a combination of dynamic characteristic parameters, that is, equivalent mass, attenuation coefficient, and natural vibration frequency, and machining characteristic parameters, that is, relative cutting resistance, edge force, and tool eccentricity.

In step S2, the identification unit 13 calculates a displacement amount that satisfies both the dynamic model and the machining process model. For example, the displacement amount that satisfies the dynamic model (1) and the machining process model (2) and (5) is calculated. Here, the displacement amount is the relative displacement x in equation (1) and v and w in equation (5).

In step S3, the identification unit 13 calculates the interference force when a displacement is given to the dynamic model. For example, the identification unit 13 adds the displacement amount calculated in step S2 to the dynamic model, which is equation (1), and calculates the interference force f _d .

In step S4, the identification unit 13 determines whether the error between the actual measured value of the force detected by the force sensor and the calculated value of the force calculated in step S3 is less than or equal to the allowable value. If the error is less than or equal to the allowable value (step S4 Yes), the identification unit 13 uses the value of the parameter set at that time as the identification result, and ends the identification process. When the error exceeds the allowable value (step S4 No), the identification unit 13 updates the value of the parameter group in step S5 and returns to the process of step S2.

As a method of updating the parameters in step S5, for example, a method of increasing or decreasing each parameter by a predetermined amount can be used. In addition, the identification processing in the identification unit 13 when the vibration determination unit 12 determines that the vibration is vibration is not limited to the processing of steps S1 to S5 described above. For example, Equation (1), Equation (2), Equation (3), and Equation (5) can also be combined to calculate each parameter using least square multiplication.

Returning to the description of FIG. 1 , the correction unit 11 receives the dynamic characteristic parameters and machining characteristic parameters that are the identification results from the identification unit 13 , and outputs a correction signal for correcting the operation of the machine tool 2 to the drive control unit based on the identification results. 15. Specifically, the correction unit 11 executes simulation related to mechanical dynamics and machining processes, and calculates a combination of the spindle rotation speed and the feed speed at which the vibration amplitude of the tool edge is less than or equal to a predetermined value. The correction unit 11 generates a correction signal for correcting the spindle rotation speed and the feed speed based on the calculated spindle rotation speed and feed speed, and outputs the correction signal to the drive control unit 15 . The predetermined value here is a value set in advance in the correction unit 11, and is a value set in order to satisfy the dimensional tolerance that determines the processing result. In addition, in addition to the spindle rotation speed and feed speed, the objects for correction may also include the amount of feed in the tool axial direction or the tool radial direction.

An example of the operation of the numerical control device 1 according to the first embodiment described above will be described using FIG. 11 . FIG. 11 is a flowchart showing an example of the operation of the numerical control device 1 according to the first embodiment. In step S11, the numerical control device 1 starts the identification operation. Specifically, the recognition operation generation unit 14 generates a recognition operation command, and the drive control unit 15 outputs a control signal to the machine tool 2 so that the machine machine 2 executes the operation specified by the recognition operation command.

In step S12, the vibration determination unit 12 acquires identification data. Specifically, the data acquisition unit 16 acquires the control signal from the drive control unit 15 and the operating state signal from the sensor of the machine tool 2 , generates identification data in which the time difference between the two is compensated, and supplies the data to the vibration determination unit 12 and the identification unit. 13 output.

In step S13, the vibration determination unit 12 determines the state of vibration based on the identification data. Specifically, the vibration determination unit 12 determines whether vibration has occurred based on the operating state signal of the identification data. If it is determined that vibration has not occurred, it determines that the state of vibration is stable processing. In addition, when the vibration determination unit 12 determines that vibration has occurred, it determines whether it is a forced vibration or a flutter vibration based on the frequency of the vibration. The vibration determination unit 12 outputs the determination result of the vibration state to the identification unit 13 as the vibration determination result.

In step S14, the identification unit 13 selects parameters that can be identified based on the identification data and the vibration determination results. Specifically, the identification unit 13 selects parameters that can be identified from dynamic characteristic parameters and machining characteristic parameters in accordance with the vibration determination result.

In step S15, the identification unit 13 uses the identification data to identify the identifiable parameters selected in step S14. In step S16, the numerical control device 1 corrects the operation of the machine tool 2 based on the identification result after the identification operation up to step S15 is completed, that is, during the normal machining operation. Specifically, the correction unit 11 generates a correction signal for correcting the operation of the machine tool 2 based on the identification result calculated by the identification unit 13 and outputs it to the drive control unit 15 . The drive control unit 15 generates a control signal based on the machining path, the reference spindle rotation speed and the reference feed speed in the machining path, and the correction signal, and outputs the control signal to the machine tool 2 .

The numerical control device 1 executes a series of processes from step S11 to step S15 at all times during machining, thereby enabling parameter identification. Moreover, after the recognition operation, through the processing of step S16, the recognition results can be used to improve the processing status.

Next, the hardware structure of the numerical control device 1 will be described. Each part of the numerical control device 1 shown in Fig. 1 is realized by a processing circuit. The processing circuit may be a circuit having a processor, or it may be dedicated hardware.

When the processing circuit is a circuit including a processor, the processing circuit is, for example, a processing circuit having a structure shown in FIG. 12 . FIG. 12 is a diagram showing a structural example of the processing circuit according to Embodiment 1. The processing circuit 200 includes a processor 201 and a memory 202 . When each part of the numerical control device 1 is realized by the processing circuit 200 shown in FIG. 12 , the processor 201 reads and executes the program stored in the memory 202 to realize them. That is, when each part of the numerical control device 1 is implemented by the processing circuit 200 shown in FIG. 12 , their functions are implemented using software, that is, a program. The memory 202 is also used as a working area of the processor 201 . The processor 201 is a CPU (Central Processing Unit) or the like. The memory 202 is, for example, a non-volatile or volatile semiconductor memory such as a RAM (Random Access Memory), a ROM (Read Only Memory), or a flash memory, a magnetic disk, or the like.

When the processing circuit implemented in each part of the numerical control device 1 is dedicated hardware, the processing circuit is, for example, an FPGA (Field Programmable Gate Array) or an ASIC (Application Specific Integrated Circuit). In addition, each part of the numerical control device 1 can also be implemented by combining a processing circuit including a processor and dedicated hardware. Each component of the numerical control device 1 can be realized by a plurality of processing circuits.

As described above, the numerical control device 1 of Embodiment 1 generates a command for the spindle and the feed axis to continuously change the speed, and independently gives the command to the spindle and the feed axis, thereby causing the machine tool to perform the identification operation. Furthermore, the numerical control device 1 of Embodiment 1 determines the vibration state of the machine tool 2 based on the identification data collected through the identification operation, and identifies the machining characteristic parameters that can be identified in accordance with the determination result. As described above, the numerical control device 1 according to Embodiment 1 can effectively identify the machining characteristic parameters in a short time. Furthermore, the numerical control device 1 according to Embodiment 1 can also identify dynamic characteristic parameters that can identify the state of vibration according to the determination result. In addition, the numerical control device 1 of Embodiment 1 can reproduce a plurality of types of vibration states for the machine tool 2 in one identification operation. Therefore, the operator can effectively perform identification in a short time without changing the processing conditions every time. Furthermore, by reproducing the chatter state, dynamic characteristic parameters and machining characteristic parameters can be estimated simultaneously. As a result, the numerical control device 1 according to Embodiment 1 can correct the control signal for the machine tool based on the recognition result, so that machining can be continued without causing machining defects. In addition, if the spindle rotation speed is changed stepwise for identification, only the peak value that is a candidate for the natural vibration frequency can be discretely searched. On the other hand, in this embodiment, as described above, commands are generated for the spindle and the feed axis to continuously change the speed. Therefore, compared with the case where the spindle rotation speed is changed stepwise in a step-like manner, it is possible to achieve high-precision operation. Identify dynamic characteristic parameters and machining characteristic parameters.

In addition, the dynamic model and the processing process model are not limited to the above-mentioned formulas (1) and (2), and can be appropriately changed according to the mechanical structure and processing method. Therefore, the dynamic characteristic parameters are not limited to equivalent mass, attenuation coefficient and natural vibration frequency. Similarly, the machining characteristic parameters are not limited to relative cutting resistance, edge force and tool eccentricity. The dynamic characteristic parameters and the machining characteristic parameters can be appropriately changed according to the dynamic model and the machining process model, and have the same effect as the first embodiment.

In Embodiment 1, the structure in which one machine tool 2 is controlled by one numerical control device 1 has been described. However, two or more machine machines may be connected to the numerical control device 1 . For example, a command for changing the spindle rotation speed is generated for the first machine tool, a command for changing the feed speed is generated for the second machine machine, and operation commands are given to each machine machine at the same time. Compared with performing actions, the recognition effect can be completed in a shorter time. Moreover, in Embodiment 1, the machine tool 2 which performs milling processing by the rotation of a tool was demonstrated, but this invention can also be applied to the machine tool 2 which performs turning processing by the rotation of a workpiece.

In addition, in this Embodiment 1, the force is directly detected by a force sensor. However, the same effect as that in Embodiment 1 can be obtained by indirectly estimating the force using another sensor. For example, the data acquisition unit 16 or the identification unit 13 can calculate the force according to the following equation (7) using the motor current command, that is, the reference motor current, and the position detected by the linear encoder.

Formula 7

f _est ＝K _T I _ref -Mü…(7)

f _est : servo axis interference force, K _T : torque constant,

I _ref : reference motor current, M: equivalent mass of the feed axis, u: linear encoder detection position

As another example, force can be calculated similarly using an acceleration sensor. In this case, the data acquisition unit 16 or the recognition unit 13 can calculate the force using the following equation (8) using the acceleration detected by the acceleration sensor.

Formula 8

f _est ＝K _T I _ref -Mα…(8)

α: Acceleration sensing detection amount

Equations (7) and (8) are calculation equations for forces when the feed axis is regarded as one inertia body. However, calculation equations that treat multiple inertia bodies may be appropriately used depending on the structure of the feed axis. Furthermore, an item for compensating friction force can be added.

Embodiment 2.

FIG. 13 is a block diagram showing a structural example of a numerical control device according to Embodiment 2 of the present invention. In Embodiment 1, the example in which the identification process is performed based on the control signal and the operating state signal during which the identification operation is performed once has been described. In Embodiment 1, when chatter does not occur in one identification operation, there are parameters that cannot be identified among the dynamic characteristic parameters and the machining characteristic parameters. This Embodiment 2 explains an example in which the recognition operation is corrected when chattering does not occur when the recognition operation is performed. Hereinafter, the same reference numerals will be used for structural elements having the same functions as those in Embodiment 1, and repeated descriptions will be omitted. The following description will focus on differences from Embodiment 1.

As shown in FIG. 13 , the numerical control device 1 a is the same as the first embodiment except that it has an identification unit 13 a and an identification operation generation unit 14 a instead of the identification unit 13 and the identification operation generation unit 14 of the first embodiment. The recognition unit 13a and the recognition operation generation unit 14a are realized by a processing circuit in the same manner as the recognition unit 13 and the recognition operation generation unit 14 of Embodiment 1.

Like the identification unit 13 of Embodiment 1, the identification unit 13a selects parameters that can be identified among the dynamic characteristic parameters and the machining characteristic parameters using the vibration determination result input from the vibration determination unit 12. In addition, like the identification unit 13 of Embodiment 1, the identification unit 13a executes identification processing for identifying the selected identifiable parameters based on the identification data input from the data acquisition unit 16, and obtains the result of the identification processing. output to the correction unit 11. The identification process is executed by the same method as the identification unit 13 in Embodiment 1 using identification data and processing condition information.

Furthermore, in the identification unit 13a, at least one of the dynamic characteristic parameter and the machining characteristic parameter is set in advance as a parameter to be identified. After performing the recognition process once or more, the recognition unit 13a outputs a recognition operation correction signal to the recognition operation generation unit 14a described later, if there is an unrecognized parameter among the parameters to be recognized. The identification action correction signal is a signal indicating the existence of unrecognized dynamic characteristic parameters or machining characteristic parameters.

Like the recognition operation generation unit 14 of Embodiment 1, the recognition operation generation unit 14 a generates a recognition operation command that changes the main shaft rotation speed and the feed speed of the machine tool, and outputs the recognition operation command to the drive control unit 15 .

Furthermore, the recognition operation generating unit 14a corrects the command pattern of the recognition operation based on the recognition operation correction signal output from the recognition unit 13a. Like the identification unit 13 , the identification unit 13 a can identify the widest variety of parameters when chattering occurs in the machine tool. Therefore, the identification operation generating unit 14a changes the range in which the spindle rotation speed or the feed speed is changed, thereby correcting the identification operation so that chatter occurs during the identification operation. Specifically, the identification operation generating unit 14a generates an identification in which at least one of the aforementioned maximum value S1 and minimum value S2 of the spindle rotation speed and the maximum value F1 and the minimum value F2 of the feed speed is changed by a predetermined ratio. Action command mode. Specifically, for example, for at least one of the spindle rotation speed and the feed speed, the maximum value S1 and the minimum value of the spindle rotation speed are calculated so that the range of change set by the previous identification operation becomes a different range. S2, at least one of the maximum value F1 and the minimum value F2 of the feed speed is changed.

An example of the operation of the numerical control device 1a according to the second embodiment described above will be described using FIG. 14 . FIG. 14 is a flowchart showing an example of the operation of the numerical control device 1a according to the second embodiment. In step S21, the numerical control device 1a starts the identification operation. In the first step S21, the recognition operation generation unit 14a generates the first recognition operation command, and the drive control unit 15 outputs a control signal to the machine tool so that the machine machine executes the operation specified by the recognition operation command.

In steps S22 to S25, the same processing as steps S12 to S15 in FIG. 11 described in Embodiment 1 is performed. In step S26, the recognition unit 13a determines whether the parameter of the predetermined recognition target has been recognized. If the recognition is completed (step S26 Yes), the process proceeds to step S28. If there is an unidentified parameter among the parameters of the predetermined identification target (step S26 No), the numerical control device 1a corrects the identification operation command in step S27 and repeats the process from step S21. Specifically, in step S27, the recognition unit 13a outputs the recognition operation correction signal to the recognition operation generation unit 14a, so that the recognition operation generation unit 14a changes the range in which at least one of the spindle rotation speed and the feed speed changes. The recognition operation command is corrected, and the corrected recognition operation command is output to the drive control unit 15 . In the second and subsequent steps S21 , a control signal is generated for the machine tool 2 based on the recognized operation command corrected by the drive control unit 15 , and is output to the machine machine 2 .

In step S28, the numerical control device 1a corrects the operation of the machine tool 2 based on the identification result. Specifically, like the correction unit 11 of Embodiment 1, after the identification operation is completed, the correction unit 11 generates a correction signal based on the identification result calculated by the identification unit 13 a and outputs it to the drive control unit 15 . The drive control unit 15 generates a control signal based on the machining path, the reference spindle rotation speed and the reference feed speed in the machining path, and the correction signal, and outputs the control signal to the machine tool 2 .

The numerical control device 1a repeatedly executes a series of processes from step S21 to step S27 during processing. That is, the recognition unit 13a performs recognition using the recognition data for the period corresponding to the recognition operation command, and when there is a parameter for which recognition has not been completed among the parameters set as the recognition target, that is, the recognition target parameter, the recognition unit 13a generates The recognition operation correction signal instructing the change of the recognition operation is output to the recognition operation generating unit 14a. Furthermore, when the recognition operation correction signal is received, the recognition operation generation unit 14a changes the recognition operation command, and the data acquisition unit 16 uses the control signal generated based on the changed recognition operation command and the operation indicating the operation based on the control signal. The operating state signal of the operating state of the machine 2 is synchronized and output as identification data to the vibration determination unit 12 and the identification unit 13a. Furthermore, these operations are repeated until identification of all parameters set as identification targets is completed. This enables identification of all dynamic characteristic parameters and machining characteristic parameters set as identification targets. Furthermore, through the processing of step S28, the recognition results can be used to improve the processing status. In addition, here, the processing flow in the case where the recognition operation command is corrected after one recognition operation is completed has been described. However, the processing flow may also be a processing flow in which the recognition operation is corrected in the middle of the recognition operation.

As described above, the numerical control device 1a according to Embodiment 2 corrects the identification operation and performs the identification operation again when there is an unidentified parameter among the parameters of the predetermined identification target. Therefore, the numerical control device 1a according to Embodiment 2 corrects the identification operation to generate chatter when there is a parameter that cannot be identified in the command pattern of the first identification operation, thereby having the ability to also detect a predetermined identification target. All the parameters among the parameters are used to identify the effect.

Embodiment 3.

FIG. 15 is a block diagram showing a structural example of a numerical control device according to Embodiment 3 of the present invention. In Embodiment 2, the recognition operation is repeated until all the parameters of the recognition target set in advance are recognized. In Embodiment 3, an example will be described in which the parameters of the recognition target can be set externally. Hereinafter, the same reference numerals will be used for structural elements having the same functions as those in Embodiment 2, and repeated descriptions will be omitted. The following description will focus on differences from Embodiment 2.

As shown in FIG. 15 , the numerical control device 1 b according to the third embodiment has an input unit 17 added to the numerical control device 1 a according to the second embodiment. The input unit 17 can accept input of parameters of the recognition target from the outside. The input unit 17 can receive input of at least one of a dynamic characteristic parameter and a machining characteristic parameter as a parameter to be recognized, for example, from an external device, an operator, or the like. The input unit 17 may be a communication circuit that communicates with an external device, an interface circuit of an external medium that reads data from an external medium, or an input unit such as a keyboard or a mouse. In addition, when the input unit 17 accepts input from the operator, a display unit such as a display or a monitor is also used as the input unit 17 . The parameters of the identification target may be input to the input unit 17 as a numerical control program, or may be input to the input unit 17 by an operator through a conversation. In addition, the input unit 17 may accept input of parameters of the recognition object in the form of interactive programming. The input unit 17 outputs the received parameter of the identification target to the identification unit 13a. When the parameters to be identified are designated by the operator or from outside, for example, it is assumed that "it is desired to remove parameters that have been identified by other units etc. from the identification targets" (first case), "it is desired to exclude only the priority level" This is a case where high recognition targets are recognized and the time required for recognition is reduced" (second case). Therefore, assuming the first case, for example, in the menu list, the recognized parameters are displayed in such a manner that the recognized parameters can be distinguished by inputting values obtained through past recognition in advance, so that the recognized parameters are not recognized. Parameter identification becomes easy. In addition, if the second case is assumed, the parameter of the recognition target can be selected using a selection box or the like, and a display window can be provided that recognizes changes in the estimated time of recognition each time a check is input to the selection box, so that the operator can Select the most parameters when the identification time is within the identification allowable time range. The form of conversational programming is not limited to these examples and may be any form. However, by displaying the information that the operator must consider in order to make a selection as described above, the operator can easily adjust the parameters of the identification object. choose.

Like the recognition unit 13a in Embodiment 2, the recognition unit 13a uses the parameters of the recognition target input from the input unit 17 instead of the parameters of the recognition target set in advance, and performs the same operation as in Embodiment 2. In addition, the recognition unit 13 a may be able to perform both an operation using parameters of the recognition target set in advance and an operation using parameters of the recognition target input from the input unit 17 . The recognition unit 13a outputs the result of the recognition process to the correction unit 11. The operation of the correction unit 11 is the same as that in Embodiment 1. In addition, the operation of the correction unit 11 when specifying the parameters of the identification target according to the numerical control program is as follows. In CNC programs, information such as machining path, spindle speed, feed speed, tool number, etc. are usually described. When the operator specifies the parameters of the identification target from the numerical control program, the machining path for performing the identification operation and the parameters of the identification target are specified in the numerical control program. When the identification by the identification unit 13a is completed, for example, the correction unit 11 continues to generate a vibration amplitude of the tool edge that is less than or equal to A correction signal equal to a specified value. The operation of the numerical control device 1b according to the third embodiment other than the above is the same as the operation of the numerical control device 1a according to the second embodiment.

As described above, the numerical control device 1b of Embodiment 3 corrects the identification operation and performs the identification operation again when there are parameters for which identification has not been completed among the parameters of the identification target set by input from the outside. Therefore, the same effect as that of Embodiment 2 is achieved, and the parameters of the identification target can be changed according to the operator's wishes.

Embodiment 4.

FIG. 16 is a block diagram showing a structural example of a numerical control device according to Embodiment 4 of the present invention. In Embodiment 3, a structure is described in which the parameters of the recognition target can be set from the outside. In Embodiment 4, a structure in which the command mode of the recognition operation can be set by input from the outside will be further described. Hereinafter, the same reference numerals will be used for structural elements having the same functions as those in Embodiment 3, and repeated descriptions will be omitted. The following description will focus on differences from Embodiment 3.

As shown in FIG. 16 , the numerical control device 1 c is the same as the numerical control device 1 b of Embodiment 3 except that it has a recognition action generating part 14 b and an input part 17 a instead of the recognition action generating part 14 a and the input part 17 .

Like the input unit 17 of Embodiment 3, the input unit 17a can receive the parameters of the identification target from the outside and output the received parameters of the identification target to the identification unit 13a. In addition, the input unit 17a can accept input of command pattern information for determining the command pattern of the recognition operation from the outside. The input unit 17a outputs the received command pattern information to the recognition action generation unit 14b. The command pattern information is, for example, information indicating the spindle rotation speeds S0 and S1, the feed speeds F0 and F1, and the time constants T1 and T2 in FIGS. 2 to 4 . That is, the command pattern information is information indicating a waveform corresponding to the time of the spindle rotation speed and the feed speed when the spindle rotation speed and the feed speed are changed by the recognition operation command. The command mode information is input to the input unit 17a as a numerical control program or interactively, for example. In addition, command mode information can also be input through conversational programming. The command mode information may be configured such that the waveform can be set externally based on the waveforms shown in FIGS. 2 to 4 or information representing the waveforms.

Like the input unit 17 , the input unit 17 a may be a communication circuit for communicating with an external device, an interface circuit for an external medium that reads data from an external medium, or an input unit such as a keyboard or a mouse. In addition, when the input unit 17a receives input from the operator, a display unit such as a display or a monitor is also used as the input unit 17a. The parameters and command mode information of the identification object may be input to the input unit 17a from an external device in the form of a numerical control program, or may be input to the input unit 17a by an operator in the form of a conversation. In addition, the input unit 17a can create a program in the form of interactive programming, and use the program to specify parameters and command mode information of the recognition target. The input unit 17a outputs the received parameters of the recognition target to the recognition unit 13a, and outputs the received command pattern information to the recognition operation generation unit 14b. The operations of the identification unit 13a and the correction unit 11 are the same as those in the third embodiment.

The recognition operation generating unit 14 b generates a command pattern of the recognition operation based on the command pattern information of the recognition operation received from the input unit 17 a, and outputs the recognition operation command to the drive control unit 15 . Furthermore, like the recognition operation generation unit 14a of Embodiment 2, the recognition operation generation unit 14b corrects the command pattern of the recognition operation based on the recognition operation correction signal output from the recognition unit 13a. The operation of the numerical control device 1 c of this embodiment other than the above is the same as that of the numerical control device 1 b of the third embodiment.

As described above, in the numerical control device 1 c according to the fourth embodiment, in addition to the parameters of the recognition target described in the third embodiment, the command mode for the recognition operation can be set by input from the outside. Therefore, the numerical control device 1 c according to Embodiment 4 has the effect of being able to calculate the identification result with priority to a combination of parameters specified by input from the outside.

The structure shown in the above embodiment represents an example of the content of the present invention, and may be combined with other known techniques, and part of the structure may be omitted or changed without departing from the scope of the present invention.

Explanation of labels

1. 1a, 1b, 1c numerical control device, 2 working machine, 11 correction part, 12 vibration determination part, 13 identification part, 14 identification action generation part, 15 drive control part, 16 data acquisition part, 17, 17a input part.

Claims (8)

1. A numerical control device that controls the operation of a working machine having a spindle and a feed axis and processing a workpiece through a tool, The CNC device is characterized by: An identification action generation unit that generates an identification action instruction that causes the rotation speed and feed speed of the spindle to change independently and continuously; A data acquisition unit synchronizes a control signal for controlling the machine tool generated based on the recognized operation command and an operating state signal indicating an operating state of the machine machine operated based on the control signal. , and output as identification data; a vibration determination unit that determines, based on the identification data, whether the vibration state of the machine tool is one of stable machining, chatter vibration, and forced vibration; and an identification unit that selects, as a selection parameter, an identifiable machining characteristic parameter among machining characteristic parameters indicating characteristics of a machining phenomenon between the tool and the workpiece based on the determination result of the vibration determination unit, The identification data is used to identify the selection parameters. 2. The numerical control device according to claim 1, characterized in that, The identification unit further selects, as the selection parameter, an identifiable dynamic characteristic parameter among dynamic characteristic parameters indicating a vibration characteristic of the machine tool based on the determination result of the vibration determination unit. 3. The numerical control device according to claim 1 or 2, characterized in that, After the identification unit performs the identification using the identification data for a period corresponding to the identification operation command, if there are parameters that have not yet been identified among the parameters set as identification targets, that is, the identification target parameters. In the case of , a command change signal instructing a change in the recognition operation is generated and output to the recognition operation generation unit, If the recognition action generating unit receives the command change signal, it changes the recognition action command, The data acquisition unit synchronizes the control signal generated based on the changed identification operation command and an operating state signal indicating an operating state of the machine tool operated based on the control signal, as the identification operation signal. The data is output to the vibration determination unit and the identification unit. 4. The numerical control device according to claim 3, characterized in that, It has an input unit that accepts input of the recognition target parameter from the outside. 5. The numerical control device according to claim 4, characterized in that, The input unit further accepts input of command mode information from the outside. The command mode information indicates the rotation speed and the feed speed when the rotation speed and the feed speed are changed by the recognition operation command. information of the waveform corresponding to time, The recognition action generating unit generates the recognition action command based on the command pattern information. 6. The numerical control device according to claim 4 or 5, characterized in that, The input unit receives external input as a numerical control program. 7. The numerical control device according to claim 4 or 5, characterized in that, The input unit receives input from the outside in the form of conversational programming. 8. The numerical control device according to claim 1 or 2, characterized in that, The machine has a correction unit that generates a correction signal for correcting the operation of the machine tool based on the identification result.