JP2020157447A - Detection device, processing device, and program - Google Patents

Abstract

To improve detection accuracy of abnormality of a cutting tool.SOLUTION: A detection device includes a processing part which calculates a fluctuation range per unit time of a load of a motor in a processing device, and a determination part which determines abnormality of a cutting tool of the processing device on the basis of comparison between the fluctuation range and a first threshold.SELECTED DRAWING: Figure 1

Description

Embodiments of the present invention relate to detection devices, processing devices, and programs.

Conventionally, processing devices such as NC (numerical control) compound lathes, NC milling machines, and machining centers are known.

Japanese Unexamined Patent Publication No. 4569494 JP-A-2015-199190

With regard to the above-mentioned processing equipment, it is required to develop a technique for detecting an abnormality of a cutting tool for processing a material with as high accuracy as possible.

The detection device of the embodiment detects an abnormality in the cutting tool of the processing device based on a comparison between the processing unit that calculates the fluctuation range of the motor load of the processing device per unit time and the fluctuation range and the first threshold value. A determination unit for determining is provided.

FIG. 1 is a diagram schematically and exemplary showing the configuration of the processing system of the first embodiment. FIG. 2 is a diagram for explaining a hardware configuration example of the control device of the first embodiment. FIG. 3 is a schematic and exemplary diagram showing the transition of the current flowing through each motor of the first embodiment. FIG. 4 is a diagram showing an example of the transition of the magnitude of the current flowing through the motor that rotates the blade, which is calculated from the output signal of the current sensor of the first embodiment. FIG. 5 is a diagram showing an example of the transition of the fluctuation range of the current flowing through the motor for rotating the blade of the first embodiment per unit time. FIG. 6 is a diagram for explaining an example to be compared with the first embodiment. FIG. 7 is a diagram showing another example of the transition of the magnitude of the current flowing through the motor that rotates the blade, which is calculated from the output signal of the current sensor of the first embodiment. FIG. 8 is a diagram showing another example of the transition of the fluctuation range of the current flowing through the motor for rotating the blade of the first embodiment per unit time. FIG. 9 is a schematic and exemplary diagram showing a time change of vibration during processing of the processing apparatus of the first embodiment. FIG. 10 is a diagram showing a signal obtained by performing the spectral subtraction of the first embodiment on the signal shown in FIG. FIG. 11 is a diagram showing the relationship between the vibration amount and the threshold value of the first embodiment. FIG. 12 is a diagram for explaining a specific example of a signal transmitted / received between the control device and the detection device of the first embodiment. FIG. 13 is a diagram for explaining a hardware configuration example of the monitoring device of the first embodiment. FIG. 14 is a flowchart for explaining an outline of the operation of the detection device according to the first embodiment. FIG. 15 is a flowchart for explaining the operation of acquiring the current fluctuation width of the first embodiment. FIG. 16 is a flowchart for explaining the operation of acquiring the vibration amount of the first embodiment. FIG. 17 is a diagram for explaining a hardware configuration example of the control device of the second embodiment.

(First Embodiment)
FIG. 1 is a diagram schematically and exemplary showing the configuration of the processing system of the first embodiment. The processing system 1 has a configuration in which the detection device 100 is attached to the processing device 200. The processing apparatus 200 is, for example, an NC compound lathe, an NC milling machine, a machining center, or the like.

The processing device 200 includes a plurality of power supplies 201, a plurality of motors 202, and a control device 203. Here, as an example, the processing apparatus 200 includes two power supplies 201a and 201b as a plurality of power supplies 201. Further, the processing apparatus 200 includes two motors 202a and 202b as a plurality of motors 202.

The motor 202a uses the electric power supplied from the power source 201a to rotate the material 300 to be processed. Further, the motor 202b rotates the cutting tool 400 by using the electric power supplied from the power supply 201b.

The control device 203 is, for example, a numerical control device. The control device 203 controls the machining operation based on the machining program. The control of the machining operation specifically includes at least the control of the rotation angle or the rotation speed of the motor 202a and the motor 202b. The control of the machining operation may further include the feed of the material to be machined 300 or the cutting tool 400, the replacement of the cutting tool 400, or the control of any other operation.

The control device 203 has a hardware configuration equivalent to that of a computer capable of executing a program. That is, the control device 203 includes a processor 20, a non-volatile memory 21, and an input / output interface 22, as illustrated in FIG.

The input / output interface 22 is hardware for the control device 203 to communicate with an external device. The input / output interface 22 may communicate with an external device by wire or may communicate wirelessly. Here, each motor 202 and the detection device 100 are connected to the input / output interface 22.

The processor 20 is hardware (circuit) capable of executing a program. The processor 20 is, for example, a CPU (Central Processing Unit).

The non-volatile memory 21 is composed of, for example, a ROM (Read Only Memory), a magnetic disk drive, a flash memory, or a combination thereof. The type of the non-volatile memory 21 is not limited to these. The machining program 23 is stored in the non-volatile memory 21. The processor 20 realizes the control of the machining operation by executing the machining program 23.

For example, the processor 20 calculates a command to each motor 202 based on the instruction described in the machining program 23, and transmits the command obtained by the calculation to each motor 202 via the input / output interface 22. The command is, for example, a position command, a speed command, or other command.

The processing apparatus 200 can create a plurality of parts having the same shape. A series of machining processes for creating one part may be referred to as a machining cycle. The machining cycle includes a plurality of steps. That is, the processing apparatus 200 executes a processing cycle including a plurality of processes for each part. The machining cycle may be composed of one step.

A process is defined, for example, as a combination of a cutting tool and machining conditions. The processing conditions include a feed rate, a rotation speed of the motor 202a, a rotation speed of the motor 202b, and the like.

In the machining program 23, for example, a plurality of instructions for realizing all the steps included in one machining cycle are described.

The machining program 23 further includes a signal output program 24 that outputs a signal according to the progress of machining. The processor 20 outputs the above signal based on the signal output program 24. The signal output by the signal output program 24 will be described later.

The method of creating a plurality of parts by the processing apparatus 200 is not limited to a specific method. In one example, the material 300 to be processed has the shape of a cylinder extending in the axial direction of the motor 202a. When the processing apparatus 200 creates a part from the material 300 to be processed by using the cutting tool 400, the processing apparatus 200 separates the part from the material 300 to be processed. Then, the processing apparatus 200 feeds the remaining portion of the work material 300 toward the cutting tool 400 side, and creates the next part from the fed portion of the work material 300.

The processing apparatus 200 is provided with two current sensors 500 (current sensors 500a and 500b). The current sensor 500a outputs a signal corresponding to the current value supplied to the motor 202a. The current sensor 500b outputs a signal corresponding to the current value supplied from the power supply 201b to the motor 202b.

The current sensor 500a is attached to the power supply 201a or the motor 202a. The current sensor 500b is attached to the power supply 201b or the motor 202b.

Further, the processing apparatus 200 is provided with two vibration sensors 600 (vibration sensors 600a and 600b). The vibration sensor 600a outputs a signal indicating the degree of vibration of the work material 300. The vibration sensor 600b outputs a signal indicating the degree of vibration of the cutting tool 400.

The vibration sensor 600a can be provided at any position as long as the amount corresponding to the degree of vibration of the work material 300 brought about when the work material 300 is processed can be measured. The vibration sensor 600a can be attached to, for example, a casting that rotatably supports the shaft of the work material 300.

Similarly, the vibration sensor 600b can be provided at any position as long as the cutting tool 400 can measure an amount corresponding to the degree of vibration of the cutting tool 400 brought about when the material to be processed 300 is processed. The vibration sensor 600b is attached to, for example, a casting that rotatably supports the shaft of the cutting tool 400.

The type of each vibration sensor 600 is not limited to a specific type. Displacement sensors, velocity sensors, acceleration sensors, or any other type of these sensors may be employed as each vibration sensor 600. That is, the signal output by each vibration sensor 600 as an amount corresponding to the degree of vibration is a displacement amount, a velocity value, an acceleration value, or any other physical quantity of any kind.

When the vibration sensor 600 is provided in the casting for fixing the shaft, the vibration sensor 600 is not easily affected by the oil supplied to the cutting position, the chips generated from the cutting position, or the vibration inherent in the processing apparatus 200. Therefore, the degree of vibration of the corresponding object (work material 300 or cutting tool 400) can be measured with high accuracy.

When the first embodiment is applied to the NC compound lathe, the processing apparatus 200 may include a plurality of sets of a motor 202b, a power supply 201b, and a cutting tool 400. In that case, the current sensor 500b and the vibration sensor 600b may be provided for each motor 202b.

The current sensor 500b does not necessarily have to be provided for each motor 202b. A current sensor 500b may be provided for some of the plurality of motors 202b. Further, the vibration sensor 600b does not necessarily have to be provided for each motor 202b. A vibration sensor 600b may be provided for some of the plurality of motors 202b.

The detection device 100 detects an abnormality in the cutting tool 400. Hereinafter, the outline of the process of detecting the abnormality of the cutting tool 400 by the detection device 100 will be described with reference to specific examples.

Generally, when an abnormality such as breakage occurs in the cutting tool 400, an unusual load is applied to the motor 202. In the first embodiment, the current flowing through the motor 202 is used as an amount indicating the load applied to the motor 202. That is, the detection device 100 detects the abnormality of the cutting tool 400 by monitoring the current flowing through the motor 202.

FIG. 3 is a schematic and exemplary diagram showing the transition of the current flowing through each motor 202 of the first embodiment. The transition is a change over time. The waveform 1000 shows the signal output by the current sensor 500a. Further, the waveform 1001 shows a signal output by the current sensor 500b.

The signal obtained by each current sensor 500 indicates the instantaneous value of the current of the corresponding motor 202. When the motor 202 is an AC motor, the instantaneous value of the current of the motor 202 changes in a substantially sine wave, so that it is difficult to handle it as a signal indicating the magnitude of the current of the motor 202 as it is. The magnitude of the signal transitioning in a substantially sine wave can be represented by an effective value, an average value, an envelope, and the like.

Here, as an example, the magnitude of the current is represented by the average value. Specifically, the detection device 100 executes the calculation of the absolute value and the calculation of the moving average for the output signal of each current sensor 500. As a result, the output signal of each current sensor 500, that is, the signal indicating the instantaneous value of the current is converted into the signal indicating the magnitude of the current.

The method of expressing the magnitude of the current is not limited to the average value. The magnitude of the current may be represented by an effective value, an envelope, or the like.

FIG. 4 is a diagram showing an example of a transition in the magnitude of the current flowing through the motor 202b calculated from the output signal of the current sensor 500b of the first embodiment. The waveform 1002 in this figure shows the transition of the magnitude of the current in the period 2000 shown in FIG.

In the period 2000, so-called step machining is executed in which the material 300 to be machined is cut in a plurality of times. Each of the period 2002, the period 2004, and the period 2006 indicates the period (cutting period) in which the material 300 to be processed is cut by the cutting tool 400. During the period 2000, excluding the period 2002, the period 2004, and the period 2006 (periods 2001, 2003, 2005, 2007), the period during which the motor 202b is rotating but the work material 300 is not cut (air cut). Period) is shown. The rotation speed of the motor 202b is controlled to be constant during the period 2000.

Then, in the example of the waveform 1002 shown in FIG. 4, at the timing t1 of the period 2006, the cutting tool 400 is broken, and the current flowing through the motor 202b is instantaneously increased. That is, a peak of the fluctuation value of the current occurs at the timing t1.

The detection device 100 obtains the fluctuation range of the current per unit time, and compares the fluctuation range of the current per unit time with the threshold value. Thereby, the fluctuation of the electric current indicating the occurrence of the abnormality of the cutting tool 400 and the presence / absence of the period (cutting period) in which the work material 300 is cut by the cutting tool 400 are detected.

Specifically, the detection device 100 first executes resampling at a sampling cycle sufficiently larger than the sampling cycle of the current in order to accurately capture the time fluctuation amount of the magnitude of the current. For example, when the sampling period of the signal indicating the magnitude of the current is about 0.0001 seconds, resampling is executed at a time interval of about 0.1 seconds to 0.5 seconds. The detection device 100 subtracts the minimum value from the maximum value of a predetermined number of consecutive data in the series of data obtained by resampling, and uses the value obtained by the subtraction as the fluctuation range of the current per unit time. The value shown. The fluctuation range of the current per unit time obtained in this way is hereinafter referred to as the current fluctuation range.

Each dot in FIG. 4 indicates a resampling point. The detection device 100, for example, subtracts the minimum value from the maximum value of the three data continuously acquired by resampling, and uses the value obtained by the subtraction as the current in the section in which the three data are acquired. The fluctuation range. The detection device 100 acquires the transition of the current fluctuation width by sequentially executing the current fluctuation width while shifting the start points of the sections one by one. FIG. 5 is a diagram showing the transition of the current fluctuation width obtained by such processing.

The waveform 1004 of FIG. 5 shows the current fluctuation width of each section composed of three consecutive data. As shown in this figure, the current fluctuation range increases at the timing when the current changes significantly. Specifically, peaks are formed at the start and end timings of the cut period (eg, periods 2002, 2004, 2006). At the timing t1 when the cutting tool 400 is broken, a peak larger than the peak observed at the start and end timings of each of the above periods is formed. After the cutting tool 400 is broken, no peak to be observed occurs at the end timing of the cutting period 2006.

The detection device 100 detects the abnormality of the cutting tool 400 based on the comparison between the current fluctuation width and the threshold value Th1. For example, if there is no abnormality in the cutting tool 400, the current fluctuation range is not exceeded, but if an abnormality occurs in the cutting tool 400, a value that exceeds the current fluctuation range is set as the threshold value Th1. That is, a value corresponding to the upper limit of the range in which the peak of the current fluctuation width that occurs when there is no abnormality in the cutting tool 400 can be set as the threshold value Th1.

In the example of FIG. 5, the detection device 100 detects that the current fluctuation width exceeds the threshold value Th1. Then, the detection device 100 determines that an abnormality has occurred in the cutting tool 400.

As a method to be compared with the method of the first embodiment described above, a method of comparing the current flowing through the motor with a predetermined threshold value can be considered. This method is referred to as the method of Comparative Example 1.

According to the method of Comparative Example 1, in a system in which the current flowing through the motor is substantially constant, an abnormality of the cutting tool can be detected with high accuracy. However, the current flowing through the motor may change transiently even if there is no abnormality in the cutting tool. When the method of Comparative Example 1 is applied to a system in which the current flowing through the motor changes transiently, the accuracy of detecting an abnormality in the cutting tool deteriorates.

For example, in FIG. 6, focusing on either the air cut period (periods 2001, 2003, 2005, 2007) or the cut period (periods 2002, 2004, 2006), the rotation speed of the motor 202b is constant even though the rotation speed is constant. , The current flowing through the motor 202b is decreasing with time.

Then, when, for example, Th11 is set as a threshold value in order to detect the peak generated at the timing t1, the current threshold value Th11 even though no abnormality has occurred in the cutting tool 400 in the period 2002 and the period 2004. Exceed. That is, an abnormality is erroneously detected in the period 2002 and the period 2004. Further, when Th12 larger than Th11 is set as a threshold value in order to prevent erroneous detection that the normality of the cutting tool 400 is determined to be abnormal in the period 2002 or 2004, the abnormality of the cutting tool 400 that occurs at the timing t1 is detected. Cannot be detected.

That is, when the method of Comparative Example 1 is applied when the current flowing through the motor changes transiently, the normality of the cutting tool may be erroneously detected as an abnormality, or the abnormality of the cutting tool may be erroneously detected as normal. sell.

In the embodiment, since the fluctuation range of the current flowing through the motor is to be compared with the threshold value, the current caused by the occurrence of an abnormality of the cutting tool 400 while reducing the influence of the transient change of the current flowing through the motor. It is possible to capture the momentary fluctuation of. As a result, when the current flowing through the motor changes transiently, it is possible to suppress the occurrence of erroneous detection in which the normality of the cutting tool is determined to be abnormal and the occurrence of erroneous detection in which the abnormality of the cutting tool is determined to be normal.

As illustrated in FIG. 5, in the embodiment, the threshold Th2 may be used in addition to the threshold Th1. For example, a value that exceeds the current fluctuation range when there is no abnormality in the cutting tool 400, but does not exceed the current fluctuation range after the abnormality occurs in the cutting tool 400 can be set as the threshold value Th2. That is, a value corresponding to the lower limit of the range in which the peak of the current fluctuation width that occurs when there is no abnormality in the cutting tool 400 can be set as the threshold value Th2.

If the machining of the period 2000 is continued with the cutting tool 400 broken, the cutting tool 400 cannot cut into the material to be machined 300, so that the motor 202b is not subjected to the load due to cutting. Therefore, for example, as shown in the waveform 1003 in FIG. 4, the current flowing through the motor 202b shows a transition as if the entire period 2001 to 2007 is an air cut period. That is, the current flowing through the motor 202b does not change significantly in any of the periods 2002, 2004, and 2006 corresponding to the cut period, and changes relatively gently.

The waveform 1005 in FIG. 5 shows the transition of the current fluctuation width calculated based on the transition of the current shown by the waveform 1003 in FIG. From the waveform 1005, when machining is executed with the cutting tool 400 in a normal state, the current fluctuation width exceeds the threshold value Th2 several times, but when machining is executed with the cutting tool 400 broken, the current is generated. It can be read that the fluctuation range never exceeds the threshold value Th2. When the current fluctuation width does not exceed the threshold value Th2 even once in the period 2000, the detection device 100 can determine that the cutting tool 400 has an abnormality.

For example, in a process with a large cutting load, the height of the peak of the current fluctuation width generated at the start timing and the end timing of the cutting period is relatively large, and as a result, these occur when no abnormality occurs in the cutting tool 400. It may be difficult to distinguish between the peak and the peak that occurs when an abnormality occurs in the cutting tool 400.

In that case, the determination using the threshold value Th2 is effective. This is because in the determination using the threshold value Th2, the abnormality is detected depending on the presence or absence of the peak that occurs when the abnormality does not occur in the cutting tool 400.

For example, each waveform shown in FIGS. 4 to 6 described above shows a waveform when a process with a large cutting load is performed. According to the example of the waveform 1004 of FIG. 5, large peaks occur at the start timing and the end timing of the cutting period until the time t1 when the cutting tool 400 breaks, similar to the peak generated when the cutting tool 400 breaks. are doing.

In the example of the waveform 1004, the peak generated at the start timing and the end timing of the cutting period and the peak generated when an abnormality occurs in the cutting tool 400 can be distinguished by the threshold value Th1. However, when the cutting load is further increased, the difference between the peak generated at the start timing and the end timing of the cutting period and the peak generated when an abnormality occurs in the cutting tool 400 becomes smaller, and both are set by the threshold value Th1. Becomes difficult to distinguish.

On the other hand, in a process with a large cutting load, the peaks that occur at the start timing and end timing of the cut period are large. Therefore, if the threshold Th2 is used, the presence or absence of peaks that occur at the start timing and end timing of the cut period. Can be easily detected. The absence of peaks that occur at the start and end timings of the cutting period means that an abnormality has occurred in the cutting tool 400. That is, in the process where the cutting load is large, the abnormality of the cutting tool 400 can be easily detected by using the threshold value Th2.

For example, the waveform 1004 exceeds the threshold Th2 several times, but the waveform 1005 never exceeds the threshold Th2. Therefore, it can be seen that an abnormality has already occurred in the cutting tool 400 during the period in which the waveform 1004 is observed.

Contrary to the case of a process with a large cutting load, in a process with a small cutting load such as when the cutting tool 400 is a small-diameter blade, the peak of the current fluctuation width generated at the start timing and end timing of the cutting period is relatively small. .. Therefore, it may be difficult to detect the presence or absence of a peak that occurs when no abnormality has occurred in the cutting tool 400.

In that case, the determination using the threshold value Th1 is effective. When the height of the peak that occurs when there is no abnormality in the cutting tool 400 is small, the peak that occurs when there is no abnormality in the cutting tool 400 and the peak that occurs when an abnormality occurs in the cutting tool 400 are distinguished. This is because it is easy to do.

FIG. 7 is a diagram showing another example of the transition of the magnitude of the current flowing through the motor 202b calculated from the output signal of the current sensor 500b of the first embodiment. The waveform 1100 shows the transition of the magnitude of the current flowing through the motor 202b when the process with a small cutting load is carried out. Period 2200 and period 2202 are air cut periods, and period 2201 is a cut period in which a step with a small cutting load is carried out.

As shown in FIG. 7, at the start timing and the end timing of the cut period 2201, the fluctuation of the magnitude of the current becomes less noticeable than the case where the cutting load shown in FIG. 4 is large. This is because when the cutting load is small, the difference in load of the motor 202b between the air cut period and the cut period is small.

In the example of FIG. 7, the cutting tool 400 is broken at the timing t3 of the cutting period 2201, and the current flowing through the motor 202b is instantaneously increased. That is, a peak of the fluctuation value of the current occurs at the timing t3.

FIG. 8 is a diagram showing another example of the transition of the fluctuation range of the current flowing through the motor 202b for rotating the blade 400 of the first embodiment per unit time. The waveform 1101 is a waveform showing the transition of the current fluctuation width obtained from the waveform 1100 shown in FIG.

Since the fluctuation of the current is small at the start timing and the end timing of the cut period 2201, according to the waveform 1101, no significant peak is observed at these timings. Therefore, it is very difficult to detect the peaks at the start timing and the end timing of the cut period 2201 using the threshold value Th2. This means that it is difficult to determine an abnormality using the threshold Th2.

On the other hand, at the timing t3, a peak having a large current fluctuation range is generated due to an abnormality generated in the cutting tool 400. Since the peaks at the start timing and end timing of the cutting period 2201 are very small and the peaks that occur when an abnormality occurs in the cutting tool 400 are large, when an abnormality occurs in the cutting tool 400 by using the threshold value Th1. The peak that occurs in can be detected with high accuracy.

As described above, in the embodiment, it is possible to determine the current fluctuation width using two types of threshold values Th1 and Th2. If the current fluctuation width is determined using two types of threshold values Th1 and Th2, it is possible to detect the abnormality of the cutting tool 400 with high accuracy regardless of the cutting load.

In the above description, the detection device 100 determines that an abnormality has occurred in the cutting tool 400 when the current fluctuation width does not exceed the threshold value Th2 even once. The method for determining an abnormality using the threshold value Th2 is not limited to this.

For example, when it is known in advance that the number of times the current fluctuation width exceeds the threshold value Th2 is M times when the cutting tool 400 is normal, the detection device 100 determines the number of times the current fluctuation width exceeds the threshold value Th2. If it is less than N times, it may be determined that an abnormality of the cutting tool 400 has occurred. However, N is an integer of 1 or more and M or less.

In the embodiment, the detection device 100 is configured so that N can be set. When 1 is set as N, it is determined that an abnormality has occurred in the cutting tool 400 when the current fluctuation width never exceeds the threshold value Th2.

In the embodiment, the detection device 100 can detect the abnormality of the cutting tool 400 based on not only the current flowing through the motor 202 but also the vibration. When an abnormality such as breakage occurs in the cutting tool 400, a large impact is generated on the cutting tool 400, the material to be processed 300, or both, and the impact becomes a large vibration and propagates to the surroundings. The detection device 100 measures the degree of this vibration and detects an abnormality of the cutting tool 400 according to the degree of vibration.

FIG. 9 is a schematic and exemplary diagram showing the time change of vibration during processing. The vibration shown in this figure is measured by any of the vibration sensors 600. In this figure, vibration is acceleration.

The waveform 1010 in FIG. 9 shows the signal output from the vibration sensor 600 during the period in which the air cut period 2100, the cut period 2101, and the air cut period 2102 arrive in this order. There is. According to the example shown in this figure, the waveform 1010 contains a large amount of noise over the entire period, and it is difficult to detect an abnormality in the cutting tool 400 as it is.

Therefore, the detection device 100 first executes a filter process for removing a noise component from the output signal (waveform 1010) of the vibration sensor 600. Spectral subtraction is known as a filtering process for removing a noise component. In the embodiment, as an example, spectral subtraction is performed.

Specifically, the detection device 100 obtains a vibration spectrum from the output signal of the vibration sensor 600 during the air cut period (for example, period 2100), and sets the obtained vibration spectrum as a spectrum corresponding to the noise component. The vibration spectrum can be calculated, for example, by Fourier transforming the output signal of the vibration sensor 600. Subsequently, the detection device 100 obtains a vibration spectrum from the detected value of vibration during the cut period (for example, period 2101), and subtracts the spectrum corresponding to the noise component from the obtained vibration spectrum. The detection device 100 restores the spectrum obtained by subtraction into a signal indicating vibration by an inverse Fourier transform or the like. As a result, a signal indicating vibration from which noise components have been removed is obtained.

The method of removing the noise component is not limited to the spectral subtraction. The detection device 100 can remove a noise component from the output signal of the vibration sensor 600 by any method.

Also, the noise component may change over time. Therefore, for example, the detection device 100 acquires a noise component (spectrum corresponding to the noise component) from an air cut period that is close in time to the target cut period. As an example, the detection device 100 acquires a noise component from an air cut period executed up to a predetermined time ago.

FIG. 10 is a diagram showing a signal obtained by performing spectral subtraction on the output signal of the vibration sensor 600 illustrated in FIG. As shown in this figure, in the cut period 2101, the vibration is larger than that in the immediately preceding air cut period 2100. Then, at the timing t2, the cutting tool 400 is broken, and as a result, a particularly large vibration is detected.

The detection device 100 calculates an absolute value for the signal after the noise component has been removed. Then, the detection device 100 detects the occurrence of an abnormality in the cutting tool 400 based on the comparison between the signal obtained by calculating the absolute value and the threshold value. The signal obtained by removing the noise component from the output signal of the vibration sensor 600 and then calculating the absolute value is referred to as the vibration amount.

FIG. 11 is a diagram showing the relationship between the vibration amount and the threshold value. As shown in this figure, thresholds Th3 and Th4 can be used as thresholds for the amount of vibration.

As the threshold value Th3, for example, a value that does not exceed the vibration amount when there is no abnormality in the cutting tool 400 but exceeds the vibration amount when the cutting tool 400 has an abnormality can be set. That is, a value corresponding to the upper limit of the range in which the peaks generated when there is no abnormality in the cutting tool 400 can be set can be set as the threshold value Th3.

The detection device 100 detects that the vibration amount exceeds the threshold value Th3 at the timing t2. Then, the detection device 100 determines that an abnormality has occurred in the cutting tool 400.

Even if the cutting tool 400 does not have an abnormality, the vibration amount may exceed the threshold value Th3 due to the influence of noise. In such a case, according to the above-mentioned determination criteria, erroneous detection that the normality of the cutting tool 400 is determined to be abnormal occurs. In order to prevent erroneous detection in which the normality of the cutting tool 400 is determined to be abnormal due to the influence of noise, the detection device 100 determines the abnormality of the cutting tool 400 based on the number of times the vibration amount exceeds the threshold value Th3. It may be configured.

For example, an integer of 1 or more is preset as P in the detection device 100. Then, when the number of times the vibration amount exceeds the threshold value Th3 exceeds P, the detection device 100 determines that an abnormality of the cutting tool 400 has occurred. Even if the vibration amount exceeds the threshold value Th3, if the number of times the vibration amount exceeds the threshold value Th3 does not exceed P, the condition for determining that the abnormality of the cutting tool 400 has occurred is not satisfied. It is possible to suppress erroneous detection in which the normality of 400 is determined to be abnormal due to the influence of noise.

In the embodiment, the detection device 100 is configured so that P can be set. Note that 0 may be set as P. When 0 is set as P, it is determined that an abnormality has occurred in the cutting tool 400 when the vibration amount exceeds the threshold value Th3 even once.

Further, for example, a value that exceeds the vibration amount when there is no abnormality in the cutting tool 400 but does not exceed the vibration amount after the abnormality occurs in the cutting tool 400 can be set as the threshold value Th4. That is, a value corresponding to the lower limit of the range in which the peak generated when there is no abnormality in the cutting tool 400 can be set can be set as the threshold value Th4.

When the detection device 100 detects that the vibration amount does not exceed the threshold value Th4 even once in a predetermined period (for example, a step including a cutting period), it determines that an abnormality has occurred in the cutting tool 400.

In a situation where an abnormality has occurred in the cutting tool 400, the vibration amount may exceed the threshold value Th4 due to the influence of noise. In such a case, according to the above-mentioned determination criteria, an erroneous detection in which the abnormality of the cutting tool 400 is determined to be normal occurs. In order to prevent erroneous detection in which the abnormality of the cutting tool 400 is determined to be normal due to the influence of noise, the detection device 100 determines the abnormality of the cutting tool 400 based on the number of times the vibration amount exceeds the threshold value Th4. It may be configured.

For example, an integer of 2 or more is set as Q in the detection device 100. Then, the detection device 100 determines that the abnormality of the cutting tool 400 has occurred when the number of times the vibration amount exceeds the threshold value Th4 in a predetermined period is less than Q. Even if the vibration amount exceeds the threshold value Th4 more than once due to the influence of noise, if the number of times the vibration amount exceeds the threshold value Th4 is less than Q times, it is determined that an abnormality of the cutting tool 400 has occurred. Therefore, it is possible to suppress erroneous detection in which the abnormality of the cutting tool 400 is determined to be normal due to the influence of noise.

In the embodiment, the detection device 100 is configured so that Q can be set. 1 may be set as Q. When 1 is set as Q, it is determined that an abnormality has occurred in the cutting tool 400 when it is detected that the vibration amount does not exceed the threshold value Th4 even once in a predetermined period.

As described above, in the embodiment, it is possible to determine the vibration amount by using two types of threshold values Th3 and Th4 as well as the current fluctuation width. This makes it possible to detect the abnormality of the cutting tool 400 with high accuracy regardless of the cutting load.

Hereinafter, in the determination using each of the threshold values Th1 to Th4, the condition for determining that the abnormality of the cutting tool 400 has occurred may be referred to as an abnormal condition. For example, the abnormal condition relating to the threshold value Th1 is that the current fluctuation width exceeds the threshold value Th1. Further, the abnormal condition related to the threshold value Th2 is that the number of times the current fluctuation width exceeds the threshold value Th2 is less than N. Further, the abnormal condition related to the threshold value Th3 is that the number of times the vibration amount exceeds the threshold value Th3 exceeds P. Further, the abnormal condition related to the threshold value Th4 is that the number of times the vibration amount exceeds the threshold value Th4 is less than Q.

Further, in the embodiment, the determination condition can be changed for each process. The judgment conditions will be described later. The detection device 100 can identify each process based on the signal output from the control device 203.

FIG. 12 is a diagram for explaining a specific example of a signal transmitted / received between the control device 203 and the detection device 100. It should be noted that this figure is an exemplary and schematic diagram.

The control device 203 can output a 1-bit machining cycle signal indicating that the machining cycle is being executed / not being executed and a 1-bit process signal indicating that the process is being executed / not being executed.

In the example of this figure, the machining cycle signal is maintained in the asserted state when the machining cycle is being executed, and the machining cycle signal is maintained in the negated state when the machining cycle is not being executed. .. Further, the process signal is maintained in the asserted state when the process is being executed, and the process signal is maintained in the negated state when the process is not being executed.

Then, FIG. 12 shows the state of each signal when the R-th machining cycle and the R + 1-th machining cycle are executed. Each machining cycle includes three steps (steps # 1 to # 3).

By monitoring the process signal and the machining cycle signal, the detection device 100 can recognize which step of the machining cycle is being executed. That is, the detection device 100 can specify each process in each processing cycle.

The detection device 100 can, for example, determine the abnormality of the cutting tool 400 every time each step is completed. Then, each time the machining cycle signal is negated, the detection device 100 creates a report 700 that describes the operating status and the occurrence status of an abnormality, and transmits the report 700 to the management server 3 provided in a remote location or the like. can do.

Further, in the example of FIG. 12, an abnormality of the cutting tool 400 is detected in step # 3 of the R + 1th machining cycle. When the detection device 100 detects an abnormality in the cutting tool 400, the detection device 100 can transmit a stop signal instructing the control device 203 to stop machining. The control device 203 can stop the execution of the machining program 23 in response to receiving the stop signal. As a result, the subsequent processing is not executed, and the spread of damage caused by the abnormality of the cutting tool 400 is prevented.

Further, when the detection device 100 detects an abnormality in the cutting tool 400, the detection device 100 can notify the management server 3 to that effect. The management server 3 can display on a display device (not shown) or the like that an abnormality has occurred in the cutting tool 400.

The management server 3 can receive reports and notifications from the detection devices 100 provided in each of the plurality of processing devices 200, for example. As a result, the management server 3 can centrally manage the state of each processing apparatus 200.

The detection device 100 can automatically update (adjust) the set values of each threshold value (threshold values Th1 to Th4) in order to respond to the progress of wear of the cutting tool 400. When the cutting tool 400 is replaced, the management server 3 can instruct the detection device 100 to reset the set value of each threshold value. Upon receiving the instruction, the detection device 100 resets the set value of each threshold value to the initial value. The update of the set value of each threshold value will be described later.

The explanation is returned to FIG.
The detection device 100 has a driver / signal processing unit 101a, a driver / signal processing unit 101b, an A / D (analog-digital) conversion unit 102, a signal processing unit 103, and a condition setting unit 104 as a configuration for executing the above operation. , A threshold value setting unit 105, a determination unit 106, a storage unit 107, a display unit 108, and a signal IF (interface) unit 109.

The signal IF unit 109 is, for example, an analog circuit. The signal IF unit 109 receives the machining cycle signal and the process signal input from the control device 203, and transmits a stop signal to the control device 203.

The driver / signal processing unit 101a is, for example, an analog circuit. The driver / signal processing unit 101a drives the current sensor 500 to acquire the output signal of the current sensor 500. Then, the driver / signal processing unit 101a executes a predetermined filter processing on the output signal of the current sensor 500. The filter processing executed by the driver / signal processing unit 101a is not limited to a specific processing. The driver / signal processing unit 101a may execute a filter process for attenuating a band unnecessary for the subsequent process. That is, the driver / signal processing unit 101a may include a high-pass filter, a low-pass filter, or a band-pass filter. The driver / signal processing unit 101a may execute signal amplification or the like.

The driver / signal processing unit 101b is, for example, an analog circuit. The driver / signal processing unit 101b drives the vibration sensor 600 to acquire the output signal of the vibration sensor 600. Then, the driver / signal processing unit 101b executes a predetermined filter processing on the output signal of the vibration sensor 600. The filter processing executed by the driver / signal processing unit 101b is not limited to a specific processing. The driver / signal processing unit 101b may execute a filter process for attenuating a band unnecessary for the subsequent process. That is, the driver / signal processing unit 101b may include a high-pass filter, a low-pass filter, or a band-pass filter. The driver / signal processing unit 101b may execute signal amplification or the like.

The A / D conversion unit 102 executes A / D conversion for each signal output from the driver / signal processing unit 101a, the driver / signal processing unit 101b, and the signal IF unit 109.

The signal processing unit 103 executes the calculation of the absolute value and the calculation of the moving average for the output signal of the current sensor 500 output by the A / D conversion unit 102. As a result, the signal processing unit 103 can obtain a signal indicating the magnitude of the current flowing through the motor 202.

Further, the signal processing unit 103 calculates the current fluctuation range from the signal indicating the magnitude of the current flowing through the motor 202. In one example, the signal processing unit 103 executes resampling on a signal indicating the magnitude of the current flowing through the motor 202, and sets the minimum value from the maximum value of the three data continuously acquired by the resampling. Subtract and use the value obtained by subtraction as the current fluctuation width of the section from which the three data were acquired. The signal processing unit 103 sequentially calculates the current fluctuation width while shifting the start point of the section one by one. As a result, the signal processing unit 103 can obtain a signal indicating the current fluctuation range. The method for calculating the current fluctuation width is not limited to this.

Further, the signal processing unit 103 executes a filter process for removing noise components from the output signal of the vibration sensor 600 output by the A / D conversion unit 102. Filtering, in one example, is spectral subtraction. Further, the signal processing unit 103 calculates an absolute value for the signal after executing the spectrum subtraction. As a result, the signal processing unit 103 can obtain a signal indicating the vibration amount.

The signal processing unit 103 is an example of the processing unit of the embodiment.

The processing cycle signal and the process signal are input to the condition setting unit 104 via the signal IF unit 109, and the A / D conversion unit 102, the signal control unit 103, and the threshold value setting are based on these input signals. The unit 105 is controlled. In particular, the condition setting unit 104 identifies the process being executed based on these input signals.

For example, the condition setting unit 104 counts the number of times the process signal is asserted. The condition setting unit 104 resets the count value of the number of times the process signal is asserted when the machining cycle signal is negated. The condition setting unit 104 identifies each process by the count value of the number of times the process signal is asserted. For example, if the count value is "1", the condition setting unit 104 can recognize that the first step in the machining cycle is being executed. If the count value is "2", the condition setting unit 104 can recognize that the penultimate process in the machining cycle is being executed.

The condition setting unit 104 determines the determination condition based on the specific result of the process.

The determination condition includes, for example, the following items (1) to (8).
(1) Whether or not to perform a detection operation based on the current fluctuation range.
(2) Which current sensor 500 output signal is used in the detection operation based on the current fluctuation width. (3) Whether or not to perform a detection operation based on the amount of vibration.
(4) Which vibration sensor 600 output signal is used for the detection operation based on the vibration amount.
(5) Which of the threshold values Th1 and Th2 is used in the detection operation based on the current fluctuation width.
(6) Which of the threshold values Th3 and Th4 is used in the detection operation based on the vibration amount?
(7) Set values of N, P, Q, L (described later).
(8) Signal processing conditions (moving average time, resampling time, etc.).

That is, the condition setting unit 104 can switch the type of determination, the threshold value used for determination, the abnormal condition, the signal processing condition, and the like for each process. For example, the condition setting unit 104 sets a detection operation based on the current fluctuation width using the threshold value Th2 or a detection operation based on the vibration amount using the threshold value Th4 for a process having a large cutting load. Further, the condition setting unit 104 sets a detection operation based on the current fluctuation width using the threshold value Th1 or a detection operation based on the vibration amount using the threshold value Th3 for the process in which the cutting load is small.

Note that (1) to (8) are examples of setting conditions. The setting condition may not include a part of (1) to (8), or may include an item different from (1) to (8).

Further, the condition setting unit 104 may determine to execute both the detection operation based on the current fluctuation width and the detection operation based on the vibration amount. Further, the condition setting unit 104 may determine to execute the detection operation using a plurality of threshold values. In such a case, the abnormality of the cutting tool 400 is detected by the logical operation of the determination result by the plurality of detection operations. The condition setting unit 104 can determine the type of logical operation as one of the determination conditions in the condition setting unit 104. The types of logical operations are, for example, AND operations, or operations, and the like.

The determination conditions for each process are set in advance by the operator, for example. The determination conditions for each process can be set, for example, via the management server 3. The condition setting unit 104 switches the determination condition to be used according to the preset contents.

Further, the condition setting unit 104 may switch the cycle in which the A / D conversion unit 102 digitizes the signal, in other words, the cycle in which the A / D conversion unit 102 outputs the digital signal for each process.

Further, the condition setting unit 104 may switch the moving average time or the resampling time used by the signal control unit 103 for the calculation for each process.

The threshold value setting unit 105 switches the threshold value used for determining the abnormality of the cutting tool 400 among the threshold values Th1 to Th4.

For example, the threshold value setting unit 105 is notified by the condition setting unit 104 of the threshold value to be used in the next process when the process is switched. The threshold value setting unit 105 switches the threshold value based on the notification.

Further, the threshold value setting unit 105 can update the threshold value setting value. For example, when the threshold value Th1 is used in a certain process, the threshold value setting unit 105 uses the threshold value Th1 used in the same process as the plurality of processes executed in the previous machining cycle. Instead of using the set value of No. 1 as it is, the set value of the threshold value Th1 can be newly calculated.

More specifically, the threshold value setting unit 105 records the current fluctuation width, the vibration amount, or both of them calculated by the signal processing unit 103 in the storage unit 107 as past data. Then, the threshold value setting unit 105 calculates a new set value based on the past data.

For example, the threshold value setting unit 105 may use a value obtained by multiplying the current fluctuation width recorded as past data by a coefficient larger than 1 (for example, 1.2) as a setting value of the threshold value Th1. .. The threshold value setting unit 105 may use a value obtained by multiplying the current fluctuation width recorded as past data by a coefficient smaller than 1 (for example, 0.8) as the set value of the threshold value Th2. Further, the threshold value setting unit 105 may use a value obtained by multiplying the vibration amount recorded as past data by a coefficient (for example, 1.2) larger than 1 as the set value of the threshold value Th3. Further, the threshold value setting unit 105 may use a value obtained by multiplying the vibration amount recorded as past data by a coefficient smaller than 1 (for example, 0.8) as the set value of the threshold value Th4.

The above new setting value acquisition method is an example. New setting values can be obtained from past data by any method.

The threshold value setting unit 105 records past data individually for each process. Then, the threshold value setting unit 105 calculates the set value of the threshold value to be used in the next machining cycle individually for each process. For example, the threshold value setting unit 105 calculates the threshold value set value for a certain process by using the past data saved in association with the process.

In one step, the current fluctuation width or the vibration amount changes with time. The relationship between these values, which change over time, and the values stored as historical data is not limited to any particular relationship. For example, the past data may be a representative value calculated from all the values acquired in chronological order. For example, the mean, median, maximum, or minimum can be used as representative values. The representative value is not limited to these. The representative value may be one value selected by an arbitrary method from all the values acquired in chronological order.

In addition, the past data regarding the current fluctuation width is composed of the maximum value and the minimum value of the peak of the current fluctuation width, the maximum value is used as a new set value of the threshold value Th1, and the minimum value is the threshold value Th2. May be used as a new setting for. The historical data on the vibration amount is composed of the maximum value and the minimum value of the peak value of the vibration amount, the maximum value is used as a new setting value of the threshold value Th3, and the minimum value is the new setting value of the threshold value Th4. May be used as.

The timing of updating the threshold setting value is not limited to a specific timing. For example, the threshold value setting unit 105 can update the threshold value set value for each process when the execution of one machining cycle is completed. Alternatively, when the execution of one step is completed, the threshold value setting unit 105 can update the set value of the threshold value used in the next step. Alternatively, the threshold value setting unit 105 may update the threshold value setting value every time a plurality of machining cycles are executed.

Further, the threshold value setting unit 105 can calculate the threshold value setting value using the past data of each of one or more machining cycles. When the past data of a plurality of machining cycles is used, the threshold value setting unit 105 can use the average of the past data of the plurality of machining cycles. That is, the threshold value setting unit 105 obtains the threshold value by multiplying the average of the past data of the plurality of machining cycles by a coefficient. The average may be a simple average or a weighted average. In the case of a weighted average, the weight may be increased as the past data of the machining cycle with a new execution timing.

The cutting tool 400 wears as it is processed. The current flowing through the motor 202 and the generated vibration change as the wear of the cutting tool 400 progresses. Therefore, when the threshold value is fixed, it is determined that an abnormality has occurred in the cutting tool 400 because the fluctuation range or vibration of the current changes due to the wear of the cutting tool 400 even if the cutting tool 400 does not have an abnormality. May occur.

Since the threshold value setting unit 105 changes the threshold value setting value according to the past data, it is possible to appropriately change the threshold value setting value according to the progress of wear of the cutting tool 400. This makes it possible to prevent the occurrence of erroneous determination due to the progress of wear.

The coefficient to be multiplied by the past data may be different for each process, or may be common to a plurality of different processes. The coefficient to be multiplied by the past data may be specified by the condition setting unit 104.

The determination unit 106 determines whether or not an abnormality has occurred in the cutting tool 400 using the conditions determined by the condition setting unit 104. The determination unit 106 uses the threshold value set value calculated by the threshold value setting unit 105 in the determination.

When the determination unit 106 determines that an abnormality has occurred in the cutting tool 400, it can execute various processes. For example, when the determination unit 106 determines that an abnormality has occurred in the cutting tool 400, the determination unit 106 can transmit a stop signal to the control device 203 via the signal IF unit 109. Further, the determination unit 106 can display the display unit 108 to the effect that an abnormality has occurred in the cutting tool 400.

The display unit 108 is a device that notifies the operator of predetermined information. The display unit 108 may be a display device capable of displaying complex information such as text. Further, when it is sufficient to display only the presence or absence of an abnormality, the display unit 108 may be a lamp such as a light emitting diode. The display unit 108 may notify the presence or absence of an abnormality by sound.

It should be noted that whether each component included in the detection device 100 is realized by hardware or software can be arbitrarily selected. FIG. 13 is a diagram for explaining an example of the hardware configuration of the detection device 100.

In the example of FIG. 13, the detection device 100 includes a processor 10, a non-volatile memory 11, an input / output interface 12, a volatile memory 13, and a display device 14.

The input / output interface 12 is hardware for the detection device 100 to communicate with an external device. The input / output interface 12 may communicate with an external device by wire or may communicate wirelessly. Here, the current sensor 500, the vibration sensor 600, and the control device 203 are connected to the input / output interface 12. Further, the input / output interface 12 can execute communication with the management server 3.

The input / output interface 12 includes circuits having the functions of the driver / signal processing unit 101a, the driver / signal processing unit 101b, the A / D conversion unit 102, and the signal IF unit 109.

The non-volatile memory 11 is a memory that can hold data even when the power is off. The non-volatile memory 11 is composed of, for example, a ROM (Read Only Memory), a magnetic disk drive, a flash memory, or a combination thereof. The type of the non-volatile memory 11 is not limited to these. The detection program 110 is stored in the non-volatile memory 11. The detection program 110 is an example of the program of the first embodiment.

The processor 10 is hardware (circuit) capable of executing a program. That is, in the example of FIG. 13, the detection device 100 has a configuration equivalent to that of a computer capable of executing a program. The processor 20 is, for example, a CPU. By executing the detection program 110, the processor 20 realizes functions as, for example, a signal processing unit 103, a condition setting unit 104, a threshold value setting unit 105, and a determination unit 106.

The volatile memory 13 is a memory that can be accessed at high speed. The volatile memory 13 is composed of, for example, a DRAM (Dynamic Random Access Memory), a SRAM (Static Random Access Memory), or a combination thereof. The type of the volatile memory 13 is not limited to these. The volatile memory 13 functions as a buffer area, a cache area, an area in which a program is loaded, an area in which intermediate data for each process is stored, and the like. The storage unit 107 is, for example, a storage area allocated in the volatile memory 13. The storage unit 107 may be provided in the non-volatile memory 11.

The display device 14 is hardware that functions as a display unit 108. The display device 14 is, for example, a liquid crystal display, an organic EL display, a lamp, or the like.

The configuration shown in FIG. 13 is an example. For example, a part or all of the signal processing unit 103, the condition setting unit 104, the threshold value setting unit 105, and the determination unit 106 may be configured by a hardware circuit. Further, some functions (for example, a filter processing function) of the driver / signal processing unit 101a and the driver / signal processing unit 101b may be realized by the processor 10 executing the detection program 110.

Subsequently, the operation of the detection device 100 of the embodiment will be described. FIG. 14 is a flowchart for explaining an outline of the operation of the detection device 100 of the first embodiment.

First, the condition setting unit 104 identifies the next process to be executed based on the machining cycle signal and the process signal (S101). Subsequently, the condition setting unit 104 determines the determination condition to be used in the specified process (S102).

Subsequently, the threshold value setting unit 105 calculates the set value of the threshold value to be used based on the past data (S103). The threshold value used among the threshold values Th1 to Th4 is determined by the processing of S102. The threshold value setting unit 105 calculates a new set value for the threshold value to be used among the threshold values Th1 to Th4.

Subsequently, when the process starts (S104), the detection device 100 executes data acquisition during the execution of the process.

For example, when the condition setting unit 104 determines to perform the detection based on the current fluctuation width and the vibration amount (S105: Yes), the detection device 100 both acquires the current fluctuation width and the vibration amount. Is executed (S106).

When the condition setting unit 104 determines to execute the detection based on the current fluctuation width (S105: No, S107: Yes), the detection device 100 executes the acquisition of the current fluctuation width (S108).

When the condition setting unit 104 determines to execute the detection based on the vibration amount (S107: No), the detection device 100 executes the acquisition of the vibration amount (S109).

Subsequently, when the step is completed (S110), the determination unit 106 determines the acquired data (current fluctuation value, vibration amount, or both) and the threshold value set value set by the threshold value setting unit 105. And, the abnormality determination of the cutting tool 400 based on is executed (S111).

The condition (N, P, Q, or L described later) regarding the number of times the threshold value is exceeded is determined by the condition setting unit 104 and notified to the determination unit 106. In S112, the determination unit 106 determines the abnormality of the cutting tool 400 by using the condition regarding the number of times the threshold value is exceeded, which is determined by the condition setting unit 104 and notified in advance.

When the condition setting unit 104 determines that the detection based on the current fluctuation width and the vibration amount is executed, the determination unit 106 is determined by the condition setting unit 104 for the determination result related to each detection operation. By performing various types of logical operations, it is determined whether or not an abnormality has occurred in the cutting tool 400.

For example, when an or operation is determined as the type of logical operation, the determination unit 106 determines when an abnormal condition is satisfied in either one of the determination based on the current fluctuation width and the determination based on the vibration amount. , It is determined that an abnormality has occurred in the cutting tool 400.

As a result, even if the determination based on the current fluctuation width cannot detect the abnormality of the cutting tool 400, it is possible to detect the abnormality of the cutting tool 400 by the determination based on the vibration amount. Further, even if the determination based on the vibration amount cannot detect the abnormality of the cutting tool 400, it is possible to detect the abnormality of the cutting tool 400 by the determination based on the current fluctuation width. That is, it is possible to prevent the occurrence of erroneous detection in which the abnormality of the cutting tool 400 is determined to be normal.

When the AND operation is determined as the type of the logical operation, the determination unit 106 determines the cutting tool 400 only when the abnormal condition is satisfied in both the determination based on the current fluctuation width and the determination based on the vibration amount. It is determined that an abnormality has occurred.

As a result, when any of the abnormal conditions is satisfied due to data detection error, noise, etc., even though no abnormality has occurred in the cutting tool 400, it is erroneously determined that an abnormality has occurred in the cutting tool 400. Can be prevented.

When it is determined that an abnormality has occurred in the cutting tool 400 by the processing of S112 (S111: there is an abnormality), the determination unit 106 executes a predetermined processing (S112). The predetermined process is not limited to a specific process. For example, the determination unit 106 can transmit a stop signal to the control device 203 via the signal IF unit 109. Alternatively, the determination unit 106 can display the display unit 108 to the effect that an abnormality has occurred in the cutting tool 400.

When it is determined that no abnormality has occurred in the cutting tool 400 (S111: no abnormality), the threshold value setting unit 105 stores the past data in association with the process in the storage unit 107 (S113). Then, the control shifts to S101, and a series of processes related to the next step is executed.

FIG. 15 is a flowchart for explaining the operation of acquiring the current fluctuation width of the first embodiment.

First, the driver / signal processing unit 101a acquires an output signal from the current sensor 500 (S201). The driver / signal processing unit 101a can appropriately perform filter processing and signal amplification that limit the pass band. The A / D conversion unit 102 executes A / D conversion on the signal acquired by the driver / signal processing unit 101a (S202).

Subsequently, the signal processing unit 103 calculates the absolute value of the current detection value with respect to the digital signal obtained by the A / D conversion unit 102 (S203), and further calculates the moving average (S204). As a result, the signal processing unit 103 can obtain a signal indicating the magnitude of the current flowing through the motor 202.

Subsequently, the signal processing unit 103 calculates the current fluctuation range based on the signal obtained by the processing of S204 (S205). Then, the operation of acquiring the current fluctuation width ends.

The execution timing of each process of S203 to S205 can be arbitrarily determined. For example, the processes S203 to S205 may be executed serially each time a digital signal is acquired by S202. Alternatively, the digital signal data acquired by S202 may be stored in, for example, a volatile memory 13, and the processes of S203 to S205 may be collectively executed at the timing when a predetermined number of data are stored. The processes of S201 to S205 are repeatedly executed.

FIG. 16 is a flowchart for explaining the operation of acquiring the vibration amount of the first embodiment.

First, the driver / signal processing unit 101b acquires an output signal from the vibration sensor 600 (S301). The driver / signal processing unit 101b can appropriately perform filter processing and signal amplification that limit the pass band. The A / D conversion unit 102 executes A / D conversion on the signal acquired by the driver / signal processing unit 101b (S302).

Subsequently, the signal processing unit 103 executes spectrum subtraction on the digital signal obtained by the A / D conversion unit 102 (S303). As a result, the signal processing unit 103 can obtain a signal from which the noise component has been removed. As described above, the signal processing unit 103 acquires the output signal of the vibration sensor 600 in advance during the air cut period or the like, and obtains the noise component based on the output signal acquired in advance. In S303, the signal processing unit 103 executes spectrum subtraction using a noise component obtained in advance.

The signal processing unit 103 calculates an absolute value for the signal after executing the spectrum subtraction (S304). As a result, the amount of vibration can be obtained.

The execution timing of each process of S303 to S304 can be arbitrarily determined. For example, the processes S303 to S304 may be executed serially each time a digital signal is acquired by S302. Alternatively, the digital signal data acquired by S302 may be stored in the volatile memory 13 or the like, and the processes of S303 to S304 may be collectively executed at the timing when a predetermined number of data are stored. The processes of S301 to S304 are repeatedly executed until the process is completed.

As described above, according to the first embodiment, the detection device 100 includes a signal processing unit (processing unit) 103 and a determination unit 106. The signal processing unit 103 calculates the current fluctuation range, that is, the fluctuation range of the current flowing through the motor 202 per unit time (for example, S203 to 205 in FIG. 15). The determination unit 106 determines the abnormality of the cutting tool 400 based on the comparison between the fluctuation range of the current flowing through the motor 202 per unit time and the threshold value (threshold value Th1 or threshold value Th2).

Since the fluctuation range of the current flowing through the motor 202 per unit time is adopted as the physical quantity to be compared with the threshold value, even if the current flowing through the motor 202 changes transiently, the transient change is generated. The influence on the judgment can be reduced. As a result, as compared with the case where the method of Comparative Example 1 is adopted, the occurrence of erroneous detection in which the normality of the cutting tool 400 is determined to be abnormal and the occurrence of erroneous detection in which the abnormality of the cutting tool 400 is determined to be normal are suppressed. Can be done. That is, the accuracy of detecting the abnormality of the cutting tool 400 is improved.

Various methods are adopted as the determination method using the threshold value. For example, as described with reference to FIG. 5, the determination unit 106 determines that an abnormality has occurred in the cutting tool 400 when the current fluctuation width exceeds the threshold value Th1.

This makes it possible to detect an abnormality of the cutting tool 400 with high accuracy, especially in a process in which the cutting load is small.

In the above, the determination unit 106 has determined that an abnormality has occurred in the cutting tool 400 when the current fluctuation width exceeds the threshold value Th1. Similar to the determination of the abnormality based on the vibration amount, the detection device 100 may be configured to determine the abnormality of the cutting tool 400 based on the number of times the current fluctuation width exceeds the threshold value Th1.

Specifically, for example, an integer of 0 or more is preset as L in the detection device 100. Then, the detection device 100 may determine that an abnormality of the cutting tool 400 has occurred when the number of times the current fluctuation width exceeds the threshold value Th1 exceeds L.

Further, for example, the determination unit 106 determines that an abnormality of the cutting tool 400 has occurred when the number of times the current fluctuation value exceeds the threshold value Th2 is less than N.

This makes it possible to detect an abnormality of the cutting tool 400 with high accuracy, especially in a process in which a cutting load is large.

The determination unit 106 can carry out both the determination method using the threshold value Th1 and the determination method using the threshold value Th2. That is, the determination unit 106 determines the cutting tool 400 regardless of whether the current fluctuation width exceeds the threshold value Th1 or the number of times the current fluctuation value exceeds the threshold value Th2 is less than N. It is determined that an abnormality has occurred. When the current fluctuation width does not exceed the threshold value Th1 and the number of times the current fluctuation value exceeds the threshold value Th2 is N or more, it is determined that no abnormality has occurred in the cutting tool 400. In this way, by using the determination method using the threshold value Th1 and the determination method using the threshold value Th2 together, it is possible to detect the abnormality of the cutting tool 400 with high accuracy regardless of the cutting load. is there.

Further, the threshold value setting unit 105 records the current fluctuation width acquired in the machining cycle (first machining cycle) in the storage unit 107 as past data (for example, S113 in FIG. 14). Then, the threshold value setting unit 105 calculates the threshold value to be used in the second machining cycle after the first machining cycle based on the current fluctuation value recorded in the storage unit 107 (for example, FIG. 14 S103).

With this configuration, even if the current fluctuation width when no abnormality occurs in the cutting tool 400 fluctuates due to wear of the cutting tool 400, the threshold value used for detecting the abnormality of the cutting tool 400 is set to the progress of wear. It can be changed accordingly. That is, it is possible to suppress erroneous detection in which the normality of the cutting tool 400 is determined to be abnormal and erroneous detection in which the abnormality of the cutting tool 400 is determined to be normal, which may occur due to the progress of wear of the cutting tool 400.

Further, the threshold value setting unit 105 calculates the threshold value set value for each process. As a result, even when a plurality of cutting tools 400 are used as in the NC compound lathe, it is possible to use a different value for each cutting tool 400 as a threshold value. That is, since the threshold value can be adjusted for each cutting tool 400, the accuracy of detecting an abnormality of the cutting tool 400 is further improved.

The threshold value setting unit 105 can switch the threshold value setting value based on the signal (process signal) output from the control device 203 for each process (for example, S101 to S103 in FIG. 14).

In the above description, the current flowing through the motor 202 was measured as an example of the physical quantity corresponding to the load applied to the motor 202. The physical quantity indicating the load applied to the motor 202 is not limited to this. For example, the power consumption of the motor 202 can be measured as a physical quantity corresponding to the load applied to the motor 202. That is, a power sensor may be adopted instead of the current sensor 500. The current sensor 500 is an example of a load sensor that measures the load applied to the motor 202.

Further, the signal processing unit 103 further calculates the amount of vibration at a predetermined position of the processing apparatus 200 (for example, S303 to S304 in FIG. 16). The determination unit 106 determines the abnormality of the cutting tool 400 based on the vibration amount and the threshold value (threshold value Th3, threshold value Th4).

As a result, as compared with the case where the abnormality of the cutting tool 400 is detected only based on the load applied to the motor 202, an erroneous detection that the normality of the cutting tool 400 is determined to be abnormal and an erroneous determination that the abnormality of the cutting tool 400 is normal occurs. It is possible to suppress the occurrence of detection.

Further, the signal processing unit 103 calculates the vibration amount by performing a process of removing a noise component from the output signal of the vibration sensor 600.

This improves the accuracy of the determination based on the vibration amount.

Further, the determination unit 106 determines that an abnormality of the cutting tool 400 has occurred when the number of times the vibration amount exceeds the threshold value Th3 exceeds P.

This makes it possible to detect an abnormality of the cutting tool 400 with high accuracy, especially in a process in which the cutting load is small.

Further, when an integer of 1 or more is set as P, it is possible to suppress erroneous detection in which the normality of the cutting tool 400 is determined to be abnormal due to the influence of noise.

Further, the determination unit 106 determines that an abnormality has occurred in the cutting tool 400 when the number of times the vibration amount exceeds the threshold value Th4 is less than Q.

This makes it possible to detect an abnormality of the cutting tool 400 with high accuracy, especially in a process in which a cutting load is large.

Further, when an integer of 2 or more is set as Q, it is possible to suppress erroneous detection in which an abnormality of the cutting tool 400 is determined to be normal due to the influence of noise.

The detection device 100 can be configured as a system including the current sensor 500. Further, the detection device 100 may be configured as a system including a vibration sensor 600.

Further, in the above, it has been described that the detection device 100 is attached to the processing device 200. The detection device 100 may be included in the processing device 200.

(Second Embodiment)
The function of the detection device 100 described in the first embodiment may be mounted on the control device 203 of the processing device 200. In the second embodiment, the control device 203 to which the function as the detection device 100 is mounted will be described. The control device 203 of the second embodiment is referred to as a control device 203a. The same components as in the first embodiment are given the same names and symbols as in the first embodiment. Then, a detailed description of the same components as in the first embodiment will be omitted.

FIG. 17 is a diagram for explaining a hardware configuration example of the control device 203a of the second embodiment. The control device 203a includes a processor 20a, a non-volatile memory 21a, an input / output interface 22a, a volatile memory 25, and a display device 26.

The input / output interface 22a is hardware for the control device 203a to communicate with an external device. The input / output interface 22a may communicate with an external device by wire or may communicate wirelessly. Here, the motor 202a, the motor 202b, the current sensor 500, and the vibration sensor 600 are connected to the input / output interface 22a.

The input / output interface 22a includes circuits having the functions of the driver / signal processing unit 101a, the driver / signal processing unit 101b, the A / D conversion unit 102, and the signal IF unit 109.

The non-volatile memory 21a is a memory that can hold data even when the power is off. The non-volatile memory 21a is composed of, for example, a ROM, a magnetic disk drive, a flash memory, or a combination thereof. The type of the non-volatile memory 21a is not limited to these. The machining program 23 and the detection program 110a are stored in the non-volatile memory 21a. The detection program 110a is an example of the program of the second embodiment.

The processor 20a is hardware (circuit) capable of executing a program. That is, in the example of FIG. 17, the detection device 100a has a configuration equivalent to that of a computer capable of executing a program. The processor 20a is, for example, a CPU.

The processor 20a realizes the control of the machining operation by executing the machining program 23. For example, the processor 20a calculates a command to each motor 202 based on the instruction described in the machining program 23, and transmits the command obtained by the calculation to each motor 202 via the input / output interface 22.

Further, the processor 20a can internally generate a machining cycle signal and a process signal based on the signal output program 24 included in the machining program 23.

Further, the processor 20a realizes functions as, for example, a signal processing unit 103, a condition setting unit 104, a threshold value setting unit 105, and a determination unit 106 by executing the detection program 110a. The condition setting unit 104 can recognize the process being executed based on the machining cycle signal and the process signal.

The volatile memory 25a is a memory that can be accessed at high speed. The volatile memory 25a is composed of, for example, DRAM, SRAM, or a combination thereof. The type of the volatile memory 25a is not limited to these. The volatile memory 25a functions as a buffer area, a cache area, an area in which a program is loaded, an area in which intermediate data for each process is stored, and the like. The storage unit 107 is, for example, a storage area allocated in the volatile memory 25a. The storage unit 107 may be provided in the non-volatile memory 21a.

The configuration shown in FIG. 17 is an example. For example, a part or all of the signal processing unit 103, the condition setting unit 104, the threshold value setting unit 105, and the determination unit 106 may be configured by a hardware circuit. Further, some functions (for example, a filter processing function) of the driver / signal processing unit 101a and the driver / signal processing unit 101b may be realized by the processor 20a executing the detection program 110.

As described above, the control device 203 (control device 203a) included in the processing device 200 may include a function as the detection device 100.

The detection programs 110 and 110a of the first and second embodiments are provided in advance in the non-volatile memories 11 and 21a of the detection device 100 or the control device 203a. The detection programs 110 and 110a executed by the detection device 100 or the control device 203a are files in an installable format or an executable format, and are a CD (Compact Disc) -ROM (Read Only Memory) or a flexible disk (FD: Flexible). It is configured to be recorded and provided on a computer-readable recording medium such as a Disc), CD-R (Recordable), DVD (Digital Versatile Disk), USB (Universal Serial Bus) memory, or SD (Secure Digital) card. You may.

Further, the detection programs 110 and 110a may be stored on a computer connected to a network such as the Internet and provided by downloading via the network. Further, the detection programs 110 and 110a may be configured to be provided or distributed via a network such as the Internet.

Although some embodiments and modifications of the present invention have been described above, these embodiments and modifications are presented as examples and are not intended to limit the scope of the invention. These novel embodiments and modifications can be implemented in various other embodiments, and various omissions, replacements, and changes can be made without departing from the gist of the invention. These embodiments and modifications thereof are included in the scope and gist of the invention, and are also included in the scope of the invention described in the claims and the equivalent scope thereof.

1 Processing system, 3 Management server, 10,20,20a Processor, 11,21,21a Non-volatile memory, 12,22,22a Input / output interface, 13,25,25a Volatile memory, 14,26 Display device, 23 Processing Program, 24 signal output program, 100, 100a detector, 101a, 101b driver / signal processing unit, 102 A / D conversion unit, 103 signal processing unit (processing unit), 104 condition setting unit, 105 threshold setting unit, 106 Judgment unit, 107 storage unit, 108 display unit, 109 signal IF unit, 110, 110a detection program, 200 processing device, 201, 201a, 201b power supply, 202, 202a, 202b motor, 203, 203a control device, 300 processing Materials, 400 cutting tools, 500, 500a, 500b current sensors, 600, 600a, 600b vibration sensors, 700 reports.

Claims (14)

A processing unit that calculates the fluctuation range of the motor load of the processing equipment per unit time,
A determination unit that determines an abnormality in the cutting tool of the processing apparatus based on a comparison between the fluctuation range and the first threshold value,
A detection device comprising. The first threshold value includes a second threshold value.
The determination unit
When the fluctuation range exceeds the second threshold value, it is determined that an abnormality of the cutting tool has occurred.
The detection device according to claim 1. The first threshold value includes a second threshold value.
The determination unit
When the number of times the fluctuation width exceeds the second threshold value exceeds the first number of times, it is determined that an abnormality of the cutting tool has occurred.
The detection device according to claim 1. The first threshold value includes a third threshold value.
The determination unit
When the number of times the fluctuation range exceeds the third threshold value is less than the second number of times, it is determined that an abnormality of the cutting tool has occurred.
The detection device according to any one of claims 1 to 3. Further equipped with a threshold setting unit and a storage unit,
The threshold value setting unit records the fluctuation range calculated when the first machining cycle is executed in the storage unit, and the second machining cycle executed after the first machining cycle. The first threshold value used in the above is calculated based on the fluctuation range recorded in the storage unit.
The detection device according to any one of claims 1 to 4. The first and second machining cycles include a plurality of steps.
The threshold value setting unit records the fluctuation width in the storage unit for each process, and records the first threshold value for one step of the second processing cycle in the storage unit. Calculated based on the fluctuation range of the one step of the first machining cycle.
The detection device according to claim 5. The processing apparatus outputs a signal each time each process is executed.
The threshold value setting unit switches the first threshold value based on the signal.
The detection device according to claim 6. Further equipped with a current sensor provided in the power supply that supplies current to the motor,
The processing unit acquires the output signal of the current sensor as a load of the motor.
The detection device according to any one of claims 1 to 7. The processing unit further calculates the amount of vibration at a predetermined position of the processing apparatus.
The determination unit further determines an abnormality of the cutting tool of the processing apparatus based on the comparison between the vibration amount and the fourth threshold value.
The detection device according to any one of claims 1 to 8. The fourth threshold value includes a fifth threshold value.
The determination unit
When the number of times the vibration amount exceeds the fifth threshold value exceeds the third number of times, it is determined that an abnormality of the cutting tool has occurred.
The detection device according to claim 9. The fourth threshold value includes a sixth threshold value.
The determination unit
When the number of times the vibration amount exceeds the sixth threshold value is less than the fourth number of times, it is determined that an abnormality of the cutting tool has occurred.
The detection device according to claim 9 or 10. A vibration sensor provided at the predetermined position of the processing apparatus is further provided.
The processing unit acquires the output signal of the vibration sensor and calculates the vibration amount by performing a process of removing a noise component from the acquired output signal.
The detection device according to any one of claims 9 to 11. A motor that rotates the work material or the cutting tool that cuts the work material,
A load sensor that detects the load of the motor and
A processing unit that calculates the fluctuation range of the load per unit time,
A determination unit that determines an abnormality of the cutting tool based on a comparison between the fluctuation width and the threshold value,
A processing device equipped with. On the computer
The procedure for calculating the fluctuation range of the motor load of the processing equipment per unit time, and
A procedure for determining an abnormality in the cutting tool of the processing apparatus based on a comparison between the fluctuation width and the threshold value, and
A program to execute.

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