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US 10,496,055 B2Granted
Machine learning device, CNC device and machine learning method for detecting indication of occurrence of chatter in tool for machine tool
AssigneeFanuc Corporation
InventorsTakahiko Matsushima, Yoshito Miyazaki
Life of this patent
Estimating the term…
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.
Claims11
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 state variables including a vibration of the machine tool itself, at least one of a vibration of a building in which the machine tool is installed, an audible sound, and an acoustic emission, and a motor control current value of the machine tool;
- and
- a learning unit which generates a learning model based on the state variables observed by the state observation unit, wherein
- the learning unit
- generates the learning model by performing unsupervised learning based on the state variables during normal operation in which no chatter occurs in a specific machining block, and
- 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 variables 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.
6 more elements
A CNC device, comprising:
- a learning circuit which constitutes a machine learning device for detecting an indication of an occurrence of chatter in a tool for a machine tool, wherein the machine learning device includes
- a state observation unit which observes state variables including a vibration of the machine tool itself, at least one of a vibration of a building in which the machine tool is installed, an audible sound, and an acoustic emission, and a motor control current value of the machine tool;
- and
- a learning unit which generates a learning model based on the state variables observed by the state observation unit, wherein the learning unit
- generates the learning model by performing unsupervised learning based on the state variables during normal operation in which no chatter occurs in a specific machining block, and
- 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
- an output utilization unit which determines whether a score based on the state variables 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, and
- wherein the CNC device controls the machine tool.
6 more elements
A machine learning method for detecting an indication of an occurrence of chatter in a tool for a machine tool, comprising:
- observing state variables including a vibration of the machine tool itself, at least one of a vibration of a building in which the machine tool is installed, an audible sound and an acoustic emission, and a motor control current value of the machine tool;
- and
- generating a learning model by unsupervised learning based on the observed state variables, wherein
- the generating the learning model includes
- generating the learning model by performing unsupervised learning based on the state variables during normal operation in which no chatter occurs in a specific machining block, and
- generating and outputting 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 method further comprises:
- determining whether a score based on the state variables 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.
6 more elements
Dependencies are inferred from the claim text.