MACHINE LEARNING DEVICE, CNC DEVICE AND MACHINE LEARNING METHOD FOR DETECTING INDICATION OF OCCURRENCE OF CHATTER IN TOOL FOR MACHINE TOOL
First Claim
1. A machine learning device for detecting an indication of an occurrence of chatter in a tool for a machine tool, comprising:
- a state observation unit which observes at least one state variable of a vibration of the machine tool itself, a vibration of a building in which the machine tool is installed, an audible sound, an acoustic emission and a motor control current value of the machine tool, in addition to a vibration of the tool; and
a learning unit which generates a learning model based on the state variable observed by the state observation unit.
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Abstract
A machine learning device for detecting an indication of an occurrence of chatter in a tool for a machine tool, includes a state observation unit which observes at least one state variable of a vibration of the machine tool itself, a vibration of a building in which the machine tool is installed, an audible sound, an acoustic emission and a motor control current value of the machine tool, in addition to a vibration of the tool; and a learning unit which generates a learning model based on the state variable observed by the state observation unit.
20 Citations
13 Claims
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1. A machine learning device for detecting an indication of an occurrence of chatter in a tool for a machine tool, comprising:
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a state observation unit which observes at least one state variable of a vibration of the machine tool itself, a vibration of a building in which the machine tool is installed, an audible sound, an acoustic emission and a motor control current value of the machine tool, in addition to a vibration of the tool; and a learning unit which generates a learning model based on the state variable observed by the state observation unit.
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2. The machine learning device according to claim 1, wherein the learning unit generates the learning model by performing unsupervised learning based on the state variable during normal operation in which no chatter occurs in a specific machining block.
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3. The machine learning device according to claim 2, wherein
the learning unit generates and outputs a normal score during the normal operation in which no chatter occurs in the specific machining block, and an abnormal score when there is an indication of the occurrence of chatter in the machining block, and the machine learning device further comprises: an output utilization unit which determines whether a score based on the state variable of the machining block corresponds to the normal score or the abnormal score, in order to detect an indication of the occurrence of chatter in the tool for the machine tool.
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4. The machine learning device according to claim 1, further comprising a neural network.
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5. The machine learning device according to claim 1, wherein the machine learning device is connectable to at least one different machine learning device and exchanges or shares the learning model generated by the learning unit of the machine learning device with the at least one different machine learning device in a mutual manner.
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6. The machine learning device according to claim 1, wherein
the machine tool includes: -
a vibration sensor which detects the vibration of the machine tool itself and provided in a holder or bit of the tool; and at least one of an audible sound sensor which detects the audible sound, and an acoustic emission sensor which detects the acoustic emission.
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7. The machine learning device according to claim 1, wherein the machine tool includes a vibration sensor which detects the vibration of the building in which the machine tool is installed.
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8. The machine learning device according to claim 1, wherein the machine tool includes a current sensor which detects a motor control current value of the machine tool.
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9. The machine learning device according to claim 8, wherein the current sensor is provided in a motor amplifier for driving a motor of the machine tool.
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10. A CNC device comprising a learning circuit which constitutes the machine learning device according to claim 1, and wherein the CNC device controls the machine tool.
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11. The CNC device according to claim 10, further comprising:
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a determination circuit which compares a score outputted from the learning circuit with a certain determination reference value to make a determination; and a CPU which outputs a stop signal to the machine tool based on a determination result from the determination circuit.
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12. The CNC device according to claim 11, wherein the CPU outputs a warning signal to a host management system based on the determination result from the determination circuit.
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13. A machine learning method for detecting an indication of an occurrence of chatter in a tool for a machine tool, comprising:
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observing at least one state variable of a vibration of the machine tool itself, a vibration of a building in which the machine tool is installed, an audible sound, an acoustic emission and a motor control current value of the machine tool, in addition to a vibration of the tool; and generating a learning model by unsupervised learning based on the observed state variable.
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Specification