JP2017209743A - Machining device - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a machining device which measures progress of tool wear according to signals of the machining device, and thereby allowing for detects abnormality determination before the tool is in an abnormal condition.SOLUTION: A machining device for cutting a cutting object includes: a machining device body provided with a main shaft holding a tool for machining the cutting object and a drive unit for rotationally driving the main shaft; a measuring unit for measuring a signal obtained from the main shaft rotationally driven by the drive unit of the machining device; a normal signal storage unit for storing signals obtained during normal operation of the main shaft out of signals obtained from the main shaft; a signal processing unit for extracting and processing a measured signal obtained by measuring using the measuring unit and a normal signal stored in the normal signal storage unit, at prescribed time intervals and for a prescribed duration of time; an integration processing unit for integrating a result of processing the measured signal and the normal signal using the signal processing unit at the prescribed time intervals and for the prescribed duration of time; and a processing machine command unit for controlling the machining device body on the basis of the result of the integration processing by the integration processing unit.SELECTED DRAWING: Figure 1

Description

  The present invention relates to a machining apparatus, and more particularly to a machining apparatus having a function of predicting tool abnormality.

  Japanese Patent Application Laid-Open No. 2005-22052 (Patent Document 1) describes a method and an apparatus capable of detecting an abnormality or life of a processing tool such as a cutting tool. In this publication, “a standard that includes a cumulative power consumption calculation unit that calculates cumulative power consumption for each machining of a machining tool, and that stores the cumulative power consumption per machining calculated by the cumulative power consumption calculation unit in a storage unit. The abnormality / life of the machining tool is determined in comparison with the power consumption, and the reference power consumption is preferably the cumulative power consumption at the first machining with a new machining tool. It is desirable to obtain the power consumption by removing the equivalent of the power consumed by the idling of the tool, since the tool life can be accurately detected by eliminating errors due to variations in the manufacturing and usage environment of the cutting tool. Can be reduced. ”

JP 2005-22052 A

  Patent Document 1 describes a method and an apparatus capable of detecting an abnormality and a life of a processing tool. However, the apparatus described in Patent Document 1 determines that the accumulated power consumption exceeds a certain threshold compared to the reference power consumption, and that the tool is abnormal or has a life, and even when the tool is hardly worn. When a certain amount of electric power is consumed, it is determined that the tool is abnormal in a state where machining is still possible, and the tool is replaced.

  Further, since it cannot be said that there is a correlation between the power consumption and the wear state of the tool, there is a possibility that an abnormality such as chipping of the tool occurs and then determined to be abnormal. At this time, the machining is advanced with the tool in an abnormal state, and there is a possibility that the spindle and the workpiece collide, or the workpiece cannot be processed as desired and a defective product is produced.

  In addition, Patent Document 1 describes not only the accumulated power amount but also “characterizes determining abnormality / life of a machining tool in comparison with an instantaneous threshold with respect to power consumption”. There may be a case where it is determined that the tool is abnormal even if the tool is not abnormal due to an increase in the electric power value due to sudden chipping during machining or an instantaneous increase in electric power value due to noise.

  Therefore, in the prior art described in Patent Document 1, in order to stabilize production such as ensuring the accuracy of the work material to be manufactured and improving the yield, management for exchanging the tool while the tool wear has not progressed yet. There are problems such as an increase in machining lead time due to an increase in the number of tool changes and an increase in tool costs due to an increase in the number of tools used.

  Therefore, the present invention provides a machining apparatus that allows the progress of tool wear to be measured with a signal from the machining apparatus and to detect an abnormality determination before the tool enters an abnormal state.

  That is, the present invention solves the above-mentioned problems of the prior art, enables the tool to be processed to a worn state before abnormal machining occurs, improves the usage period of each tool, and reduces the number of times of tool change The present invention provides a machining apparatus having a function of predicting tool abnormality that enables reduction of machining lead time by means of cutting and reduction of tool cost by reducing the number of tools used.

In order to solve the above problems, for example, the configuration described in the claims is adopted.
The present application includes a plurality of means for solving the above problems. To give an example, a processing device for cutting a work material, a main shaft for holding a tool for processing the work material, and the main shaft are driven to rotate. A machining device main body provided with a driving unit, a measuring unit for measuring a signal obtained from a main shaft that is rotationally driven by the driving unit of the machining device main body, and the main shaft among the signals obtained from the main shaft is operated normally. A normal signal storage unit for storing a signal obtained when the signal is received, and a measurement signal obtained by measurement by the measurement unit and a normal signal stored in the normal signal storage unit are extracted for a predetermined time interval at predetermined time intervals. Based on the signal processing unit to be processed, the integration processing unit that integrates the result of processing the measurement signal and the normal signal by the signal processing unit at a predetermined time interval for each predetermined time interval, and the result of the integration processing by the integration processing unit To control the processing equipment body Was constructed and a that machine instruction unit.

  According to the present invention, since the tool can be processed to a worn state before abnormal processing occurs, the usage period of each tool is improved, the tool lead time is shortened by reducing the number of tool exchanges, and the tool by reducing the number of tools used. Benefits such as cost reduction can be obtained.

  Problems, configurations, and effects other than those described above will become apparent from the following description of the embodiments.

It is a block diagram which shows the structure of the outline of the processing apparatus provided with the function which estimates the abnormality of the tool which concerns on Example 1 of this invention. It is a perspective view which shows the external appearance of the cutting tool which concerns on Example 1 of this invention. It is a perspective view near the tip part of alternate cutting which shows the example of the tool wear in the cutting tool concerning Example 1 of the present invention. It is a flowchart which shows the operation | movement flow of the processing apparatus which estimates the abnormality of the tool which concerns on Example 1 of this invention. It is a current waveform diagram which shows the electric current value of the measurement signal which concerns on Example 1 of this invention. It is a current waveform diagram which shows the electric current value of the normal signal which concerns on Example 1 of this invention. It is a current waveform diagram which shows the example which extracts the data of fixed time from the measurement signal which concerns on Example 1 of this invention. It is a current waveform diagram which shows the example which sets a sample line with respect to the extracted signal which concerns on Example 1 of this invention. FIG. 6 is a current waveform diagram for explaining a cross count and a count amount from the sample line according to the first embodiment of the present invention. It is a histogram explaining the count data amount obtained by processing the measurement signal which concerns on Example 1 of this invention. It is a histogram explaining the count data amount obtained by processing the normal signal which concerns on Example 1 of this invention. It is a graph which shows the relationship between the tool wear width which concerns on Example 1 of this invention, and a normal data ratio. It is a block diagram which shows the structure of the input part which concerns on Example 1 of this invention, and the relationship between a control part and a processing apparatus main body. It is a front view of the screen which shows the example of the display screen which inputs the signal processing method of the input part which concerns on Example 1 of this invention. It is a front view of the screen which shows the example of a display screen when the pre-processing method is selected with the signal processing method of the input part which concerns on Example 1 of this invention. It is a block diagram which shows the structure of the outline of the processing apparatus which estimates the abnormality of the tool which concerns on Example 2 of this invention with acceleration data. It is a block diagram which shows the structure of the outline of the processing apparatus which estimates the abnormality of the tool which concerns on Example 3 of this invention with cutting force data.

  The present invention measures the cutting force measured by a processing machine and the current value / power value of a motor that drives the cutting tool, and analyzes the change of these values with a detection algorithm that can detect tool wear with a desired wear width. Thus, tool abnormalities are predicted to control the processing conditions or the operation of the processing machine.

  In particular, paying attention to the high correlation between the wear width of the tool and the drive signal for driving the spindle that drives the tool, the magnitude of the amplitude of the current value is obtained from the data obtained by measuring the current value for driving the spindle. By analyzing the features using an analysis technique based on pattern recognition, tool wear can be detected with a desired wear width.

  In the present invention, the degree of progress of wear from the change in the ratio of normal data in the measured data from the data obtained by measuring the cutting force measured by the processing machine and the current value / power value of the motor driving the cutting tool. It is intended to provide a processing method that follows the progress of wear.

  That is, the present invention relates to a processing device for cutting a work material, a main shaft for rotating a tool for processing the work material, a measuring device for measuring a signal of the main shaft, and a normal signal storage unit for storing a normal signal. The signal processing unit that processes the measurement signal and normal signal, which are signals measured in the target processing, and the output signal processed by the signal processing unit are counted and counted. And a processing machine command section for controlling the processing machine when the threshold value is exceeded and the threshold value is set based on the processing result of the normal signal and measurement signal after the integration processing. Is.

  Hereinafter, examples will be described with reference to the drawings. Components having the same function are denoted by the same reference symbols throughout the drawings for describing the embodiments, and the repetitive description thereof is omitted in principle. However, the present invention is not construed as being limited to the description of the embodiments below. Those skilled in the art will readily understand that the specific configuration can be changed without departing from the spirit or the spirit of the present invention.

In this embodiment, an example of a machining apparatus that predicts an abnormality of a tool by a current value or a power value will be described.
FIG. 1 is a block diagram illustrating a configuration and signal flow of a machining apparatus 100 having a function of predicting tool abnormality according to the present embodiment. The machining apparatus 100 that predicts tool abnormality according to the present embodiment includes a machining apparatus body 13, a calculation unit 14 that calculates measurement data and outputs a control command for the machining machine, and normal data storage that stores normal data. A unit 12 and an input unit 15 for inputting settings of the processing apparatus are provided.

  In the processing apparatus main body 13, the cutting tool 1 is fixed by the main shaft 3, and the main shaft 3 is rotated by the main shaft motor 5 to process the workpiece 2 into a desired shape. At this time, the voltage value and the current value that the servo amplifier 6 inputs to the spindle motor 5 are controlled by a command from the NC device 7 in which the NC program is stored. Thereby, the spindle motor 5 is rotated at the rotational speed as commanded.

  Here, the example which measures the electric current value or electric power value of a processing machine is demonstrated. As the measurement signal for machining, the voltage value and the current value obtained between the servo amplifier 6 and the spindle motor 5 are measured by the measuring device 8 of the calculation unit 14. At this time, a voltage sensor or a current sensor may be used for the measurement.

  From the measurement signal measured by the measuring device 8, a signal processing unit 9 extracts a waveform for every fixed time, and performs a specified prior signal processing on the extracted waveform. At this time, the prior signal processing method may be performed by a noise removal filter such as a low-pass filter, a high-pass filter, a band-pass filter, or a moving average filter.

  On the other hand, the normal signal is output from the normal data storage unit 12. In the normal data storage unit 12, the voltage value and current value obtained between the servo amplifier 6 and the spindle motor 5 are measured by the measuring device 8 of the calculation unit 14 when the workpiece 2 is machined while the cutting tool 1 is in a normal state. The stored signal is stored. At this time, the normal state may use data when the first pass in which tool wear has not progressed on the cutting tool 1 is processed.

  The normal signal output from the normal data storage unit 12 and input to the signal processing unit 9 is extracted with a waveform for every fixed time having the same interval as the measurement signal, and is subjected to prior signal processing as necessary.

  The measurement signal and the normal signal processed by the signal processing unit 9 are statistically processed and integrated and calculated by the integration processing unit 10 and converted into a count number using the progress of tool wear as an index.

  Subsequently, the processing machine command unit 11 sets a threshold value based on the normal signal processed by the integration processing unit 10. When the output value of the measurement signal processed by the integration processing unit 10 exceeds this threshold value, a command to execute the operation method of the processing apparatus body 13 specified by the input unit 15 is sent to the NC device 7 of the processing apparatus body 13. Put out. The command at this time may be tool change, machining condition adjustment, or tool evacuation.

  FIG. 2 shows an example of the cutting tool 1 and FIG. 3 shows an example of tool wear of the cutting tool 1. In the cutting tool 1, the workpiece 2 is processed at the cutting edge 20 portion. Although the cutting edge 20 is not worn in a new state before machining, the tool wear 21 progresses on the side of the flank 23 of the tool cutting edge 20 as machining progresses. If the wear width 22 of the flank 23 increases at this time, machining abnormalities such as an increase in cutting force, generation of machining vibration, deterioration of machining accuracy, and tool breakage occur. Therefore, it is necessary to control the processing apparatus main body 13 by detecting the progress of the wear width 22 of the flank 23 before the processing abnormality occurs.

  FIG. 4 is an example of a flowchart showing an operation flow of the processing apparatus 100 that predicts an abnormality of the cutting tool 1. First, in step S30, conditions are input. The input conditions include machining data controlled by the NC device 7, a control method of the servo amplifier 6, a signal processing method in the arithmetic unit 14, and the like.

  When the input of the conditions is completed, processing of the measurement object is started in step S31. Simultaneously with the start of machining, a signal for driving the spindle 3 of the machine is measured by the measuring device 8 in step S32. The signals to be measured at this time are the current value and power value output from the servo amplifier 6 that controls the drive motor 5 connected to the main shaft 3, the acceleration directly obtained from the main shaft 3, and the cutting force. Next, in step S33, the signal processing unit 9 extracts a waveform for every predetermined time from the measurement signal output from the measurement device 8, and performs pre-signal processing as necessary. At the same time, normal data is input from the normal data storage unit 12 from step S39.

  Next, in step S34, the integration processing unit 10 integrates the signal waveform subjected to the processing specified by the signal processing unit 9, and in step S35, a threshold is set based on the normal signal processing result. Next, the processing result of the measurement signal and the threshold value are compared and evaluated in step S36. If the processing result of the measurement signal exceeds the threshold value (greater than or equal to the threshold value), it is determined that it is a sign that a tool abnormality has occurred. Proceeding to step S37, the processing machine body 13 is controlled.

  Here, specific examples of control of the processing machine main body 13 executed in step S37 include exchanging the cutting tool 1, adjusting the processing conditions set by the NC device 7, or retracting the cutting tool 1. .

  When the control ends, the process ends in step S38. If it is determined in step 36 that the processing result of the measurement signal is less than the threshold value, it is determined that there is no abnormality in the cutting tool 1, the process returns to step S31, and the machining is continued.

  FIG. 5 is a graph of the measurement signal 50 measured by the measurement device 8 and taking the current value as an example. In this example, a groove having a width of 6 mm and a depth of 2 mm is machined under the conditions of a cutting speed of 450 m / min and a single blade feed of 0.1 mm / tooth. The horizontal axis represents time [s], and the vertical axis represents the current value [A] in the spindle 3 of the machining apparatus measured from between the spindle motor 5 and the servo amplifier 6.

  In the signal waveform shown in FIG. 5, since the spindle 3 has already been measured from the rotating state, the current value in the idling state occurs from 0 to 6 seconds, and from around 6 seconds. The cutting tool 1 comes into contact with the work material 2 and machining is started. When machining starts, a load is generated on the main shaft 3, and control for rotating the main shaft motor 5 at a constant rotational speed works from the servo amplifier 6, so that the current value detected by the measuring device 8 increases. FIG. 5 is an example of a measurement signal 50 of the current value detected by the measurement device 8 when the tool wear has advanced by about 0.2 mm.

  6 shows current values detected by the measuring device 8 when machining with a new cutting tool 1 in which tool wear has not progressed under the same machining conditions as in FIG. 5 accumulated in the normal data storage unit 12. Signal. For example, the signal at this time may be a normal signal. Alternatively, in the measurement device 8, a signal when the first cutting with the new cutting tool 1 is performed may be a normal signal.

  In the signal waveform shown in FIG. 5, it can be seen that the cutting force is increased and the current value is increased because the workpiece 2 is processed in a state in which the wear of the cutting tool 1 has progressed. On the other hand, the normal signal shown in FIG. 6 has a sharp cutting edge so that the work material is sharp and the cutting force can be kept low. Therefore, the current value in the signal waveform 60 of the normal signal is the signal waveform 50 in FIG. It can be seen that the current value is low.

  FIG. 7 is a graph illustrating a state where the signal processing unit 9 extracts a measurement signal for a predetermined time. Here, a case where data 71 at intervals of 0.5 seconds is extracted from the measurement signal 70 and a normal signal (not shown) is taken as an example. The time interval for extracting this data may be arbitrarily set by the input unit 15. However, it is necessary to set it sufficiently short with respect to the machining time for one pass.

  FIG. 8 shows the measurement signal 71 for 0.5 seconds extracted in FIG. In this graph, sample lines 40 parallel to the time axis of the waveform are set for the interval and the number specified in the amplitude direction. The interval and the number of the sample lines 40 may be arbitrarily set by the input unit 15. However, with respect to the amplitude interval of the waveform, it is necessary to have an interval and the number of the waveforms that are accommodated. For example, FIG. 8 shows an example in which n sample lines from sample line 1 to sample line n are set at equal intervals in the range of current values from 0A to 30A.

  FIG. 9 illustrates a case where the measurement signal 71 shown in FIG. 8 is processed by the sample line 3 as a representative. In the sample line 3, there is a portion that intersects the waveform of the measurement signal 71, and the number of intersections is defined as an intersection count 41. In addition, the length of the sample line 3 from when the waveform of the measurement signal 71 intersects the sample line 3 and the waveform of the measurement signal 71 once becomes larger than the sample line 3 until the next intersection comes, that is, the sample line 3. Is a count amount 42 that is equal to or smaller than the current value of the waveform of the measurement signal 71. Here, in the case of the sample line 3, the value of the intersection count 41 is 18, and the count amount 42 is 0.09 since it is 0.09 seconds.

Here, since there are sample lines from 1 to n, n intersection counts 41 and count amounts 42 are obtained from the graph of FIG. A crossing count 41 on the sample line n is set to X _1n and a count amount 42 is set to X _2n, and a vector X composed of the crossing count 41 and the count amount 42 is created.

  Next, in order to normalize each matrix element, a normalization matrix Z is calculated.

となる。

It becomes.

  Next, a correlation matrix R is defined. Since there are two types of variables, the intersection count number 41 and the count amount 42, the variable is created with a 2 × 2 square matrix.

  Next, a count data amount D is obtained in order to characterize the waveform so that a processing abnormality can be predicted.

Here, R ⁻¹ represents an inverse matrix of the correlation matrix R, and Z ^T represents a transposed matrix of the normalization matrix Z. As a result, the count data amount D for 0.5 seconds extracted by the signal processing unit 9 can be obtained.

  FIG. 10 shows the count data amount every 0.5 seconds in the measurement signal evaluation time interval of 5 seconds. The horizontal axis indicates time, and the vertical axis indicates the count data amount D on a logarithmic scale. FIG. 11 shows a graph of normal signals in the same range. A normal signal having a small signal amplitude shown in FIG. 11 has a small count data amount D. On the other hand, the measurement signal having a large amplitude shown in FIG.

  Next, integration processing is performed in the integration processing unit 10 in order to determine the graph area of the count data amount D of each of the obtained measurement signal and normal signal. Here, as an example, description will be made with the data of the evaluation time interval of 5 seconds previously obtained in FIGS. 10 and 11. Data obtained by integrating the measurement signal shown in FIG. 10 is defined as a measurement data amount, and data obtained by integrating the normal signal shown in FIG. 11 is defined as a normal data amount.

  In order to obtain the ratio of the normal data amount included in the measurement data amount, a value obtained by dividing the normal data amount by the measurement data amount is defined as a normal data ratio S. The normal data ratio S is obtained by the following formula.

  FIG. 12 is a graph showing the relationship between the tool wear width and the normal data ratio S. The graph data may be stored in the normal data storage unit 12.

  When the cutting tool 1 is an end mill or the like shown in FIGS. 2 and 3, generally, when the wear width 22 of the tool becomes 0.2 to 0.4 mm, a sign of machining abnormality starts and it is time to replace the tool. For this reason, the threshold value may be set at a level where the wear width 22 is 0.2 to 0.4 mm. For example, the tool wear width for controlling machining is set to 0.2 mm. Here, from the graph of FIG. 12, about 50% of the normal data ratio S may be set as the threshold value.

  In this example, since the count data amount is obtained every 5 seconds, the comparison with the threshold is performed every 5 seconds, and when the threshold is exceeded, the processing machine is controlled in step S37. When the control based on the normal data ratio S and the threshold value is performed in a shorter cycle, the data extracted in FIG. 7 may be shortened. Alternatively, the evaluation time of the count data amount in FIGS. 10 and 11 may be shortened. These settings may be set by the input unit 15.

  FIG. 13 shows an example of the input unit 15. Data input from the input unit 15 is input to the calculation unit 14 and the normal data storage unit 12 to control the processing apparatus body 13.

  In the input unit 15, the material of the work material, the type of tool, the program, the path, and the processing conditions are input in the processing data input unit 50. Next, the processing control method input unit 51 selects a control method for the processing machine. Here, an example of selecting from tool change, tool retraction, and machining condition adjustment is shown.

  Next, in the signal processing method input unit 52, signal processing conditions to be calculated by the calculation unit 14 are input. Here, the pre-processing method implemented by the signal processing unit 9, the processing time interval set by the signal processing unit 9 and the integration processing unit 10, the evaluation time interval set by the integration processing unit 10, and the sample set by the integration processing unit 10 An example of inputting the number of lines is shown.

  FIG. 14A shows an example of the display screen 520 of the signal processing method input unit 52. On the display screen 520 of the signal processing method input unit 52, a screen for selecting the pre-processing method 521, the processing time interval 522, the evaluation time interval 523, and the number of sample lines 524 is displayed. When the pre-processing method 521 is selected on this screen, a specific processing method 5211 of the pre-processing method is displayed on the pre-processing method selection screen 5210 as shown in FIG. 14B, and one of them is selected on the screen. By clicking with the mouse, the pre-processing is executed by the selected processing method.

  The example using the current value has been described above, but the power value may be processed similarly. The unit of the parameter is changed from the current value [A] to the power value [W], and the rest is the same as in the first embodiment.

  According to the present embodiment, since the tool can be processed to the wear state before abnormal processing occurs, the use period of each tool is improved, and the processing lead time is shortened by reducing the number of tool exchanges and the number of tools used is reduced. Effects such as tool cost reduction can be obtained. For example, when a cutting tool having a tool diameter of 300 mm and a cutting number of 20 blades and a groove width of 7 mm and a groove length of 4000 mm are repeatedly performed on a carbon steel work material, the application of this embodiment reduces the tool cost by about 50%. The processing time can be reduced by about 20%.

  Next, an embodiment of a processing apparatus 1500 that predicts an abnormality of the cutting tool 1 using acceleration data will be described with reference to FIG.

  In the machining apparatus main body 131, an acceleration sensor 301 is installed on the main shaft 3, and the acceleration during machining is measured. By measuring the acceleration, vibration during processing can be evaluated. As the tool wear 22 of the cutting tool 1 progresses, the cutting force increases, and the vibration during processing also increases. Therefore, the abnormality of the cutting tool 1 can be evaluated by acceleration. The acceleration data is input to the measuring device 81 of the calculation unit 141. Subsequent processing methods of the signal processing unit 91, the integration processing unit 101, and the processing machine command unit 111 are changed from the current value [A] to the acceleration [G] as the parameter unit including the normal data storage unit 121 and the input unit 151. Other than that, the processing method is the same as that described in the first embodiment.

  Next, an example of a processing apparatus 1600 that predicts an abnormality of the cutting tool 1 using cutting force data will be described with reference to FIG.

  In the processing apparatus main body 132, a force sensor 303 is provided on a table 302 in the processing apparatus. The work material 2 is fixed on the force sensor 303. The cutting force during processing is measured by the force sensor 303. When the tool wear 22 of the cutting tool 1 progresses, the cutting force increases, so that it is possible to predict tool abnormality during processing. The cutting force data is input to the measuring device 82. Subsequent processing methods of the signal processing unit 92, the integration processing unit 102, and the processing machine command unit 112 are such that the unit of parameters is changed from the current value [A] to the cutting force [N] including the normal data storage unit 122 and the input unit 152. Instead, it is the same as the processing method described in the first embodiment. Here, a strain gauge or a load cell may be used as the force sensor.

  As described above, according to the present invention, in the processing method for cutting a work material, the main shaft holding a tool for processing the work material is rotated in the drive unit of the processing apparatus main body, and the main shaft is rotated. The signal obtained from the measurement unit is measured by the measurement unit, and the signal obtained when the main shaft is operating normally among the signals obtained from the main shaft is stored in the normal signal storage unit and is obtained by measurement by the measurement unit. The measurement signal and the normal signal stored in the normal signal storage unit are processed by the signal processing unit at predetermined time intervals for a predetermined time, and the measurement signal and the normal signal are processed by the signal processing unit by the predetermined signal. The integration processing unit integrates the result of processing at predetermined time intervals for the time of, and the processing apparatus main body is controlled by a command signal from the processing machine command unit based on the result of integration processing by the integration processing unit. In what That.

  In addition, this invention is not limited to an above-described Example, Various modifications are included. For example, the above-described embodiments have been described in detail for easy understanding of the present invention, and are not necessarily limited to those having all the configurations described. Further, a part of the configuration of one embodiment can be replaced with the configuration of another embodiment, and the configuration of another embodiment can be added to the configuration of one embodiment. Further, it is possible to add, delete, and replace other configurations for a part of the configuration of each embodiment.

  DESCRIPTION OF SYMBOLS 3 ... Main shaft 5 ... Main shaft motor 6 ... Servo amplifier 8, 81, 82 ... Measuring apparatus 9, 91, 92 ... Signal processing part 10, 101, 102 ... Integration processing part 11, 111, 112 ... Processing machine command part 12, 121 122, normal data storage unit 14, 141, 142 ... control unit 13, 131, 132 ... processing apparatus main body 100, 1500, 1600 ... processing apparatus.

Claims (7)

A processing device for cutting a work material,
A processing apparatus main body comprising a main shaft for holding a tool for processing a work material and a drive unit for rotationally driving the main shaft;
A measurement unit that measures a signal obtained from the spindle that is rotationally driven by the drive unit of the processing apparatus body;
A normal signal storage unit for storing a signal obtained when the spindle is operating normally among signals obtained from the spindle;
A signal processing unit that extracts and processes the measurement signal obtained by measurement by the measurement unit and the normal signal stored in the normal signal storage unit for a predetermined time interval at predetermined time intervals;
An integration processing unit that integrates a result obtained by processing the measurement signal and the normal signal by the predetermined time interval for each predetermined time interval in the signal processing unit;
A processing apparatus comprising: a processing machine command unit that controls the processing apparatus main body based on a result of integration processing by the integration processing unit.   The processing apparatus according to claim 1, wherein the measurement unit measures a current value, power value, acceleration, or cutting force signal obtained from the spindle that is rotationally driven by the drive unit of the processing apparatus body. The processing apparatus characterized by performing.   The processing apparatus according to claim 1, wherein the integration processing unit is configured to integrate an integration value of a signal obtained by processing the measurement signal by the signal processing unit and a signal obtained by processing the normal signal. And a ratio of the integral value of the signal obtained by processing the normal signal included in the integral value of the signal obtained by processing the measurement signal.   The processing device according to claim 1, wherein the processing machine command unit is a signal obtained by processing the normal signal included in an integral value of a signal obtained by processing the measurement signal by the integration processing unit. A processing apparatus for controlling a processing machine when a ratio of an integral value of a value exceeds a preset threshold value.   The processing apparatus according to claim 1, wherein the signal processing unit designates a signal waveform of a signal obtained by extracting the measurement signal and the normal signal for a predetermined time interval at predetermined time intervals in a waveform amplitude direction. A plurality of sample lines are set at the intervals, and the number of times each of the set sample lines intersects the waveform of the output signal is counted, and the waveform of the output signal crosses the sample line and becomes larger than the sample line. A processing apparatus for measuring a count time and performing a statistical process on the number of times counted and the time when the waveform of the output signal is larger than the sample line to obtain a count data amount.   The processing apparatus according to claim 5, wherein the integration processing unit integrates the count data amount obtained by processing in the signal processing unit for each predetermined time interval, thereby integrating the measurement signal on the time axis. And a normal signal data amount, and a ratio of the normal signal data amount included in the measurement signal data amount is obtained.   6. The processing apparatus according to claim 5, wherein the processing machine command unit includes the normal signal included in a data amount of the measurement signal obtained by processing the measurement signal and the normal signal by the integration processing unit. A processing apparatus that controls a processing machine when a ratio of a data amount exceeds a preset threshold value.

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