`
`l.
`
`A
`
`device
`
`for
`
`overall machine
`
`tool monitoring
`
`comprising:
`
`a signal
`
`input unit
`
`to which a target signal which is
`
`an electric signal
`
`representing' vibrations generated from
`
`the machine tool is inputted;
`
`a first and a second characteristics extracting units
`
`for
`
`extracting an
`
`amount
`
`of
`
`characteristics
`
`having
`
`a
`
`10
`
`plurality of parameters from the target signal;
`
`a first and a second neural networks for classifying
`
`the amount of characteristics extracted by the respective
`
`characteristics extracting units into categories; and
`
`a
`
`determination unit
`
`for
`
`determining
`
`an overall
`
`15
`
`anomaly in the machine tool by using a classification result
`
`from each of the neural networks,
`
`wherein the
`
`first neural network classifies,
`
`into
`
`normal and abnormal categories, an amount of characteristics
`
`extracted from a target signal generated when the machine
`
`20
`
`tool is racing prior to machining a workpiece, and
`
`wherein the second neural network classifies,
`
`into
`
`normal
`
`and
`
`abnormal
`
`categories,
`
`the
`
`amounts
`
`of
`
`characteristics extracted from a
`
`target
`
`signal generated
`
`while the machine tool is machining the workpiece, and
`
`25
`
`wherein the determination unit determines whether or
`
`not
`
`the anomaly exists before the machine tool machines the
`
`.19_
`
`
`
`workpiece
`
`and while
`
`the machine
`
`tool
`
`is machining the
`
`workpiece,
`
`and whether or not
`
`there is a
`
`fault
`
`in the
`
`machine tool, based on the classification results from the
`
`first
`
`and the
`
`second neural networks, deviation history
`
`between weight coefficients of neurons in an output
`
`layer
`
`included in the first neural network and the amounts of
`
`characteristics
`
`extracted by
`
`the
`
`first
`
`characteristics
`
`extracting unit,
`
`and deviation history between weight
`
`coefficients of neurons in an output
`
`layer included in the
`
`10
`
`second neural network and the amounts of characteristics
`
`extracted by the second characteristics extracting unit.
`
`2.
`
`The device
`
`for overall machine
`
`tool monitoring of
`
`claim 1,
`
`the target signal
`
`is output of a vibration sensor
`
`15
`
`attached to the machine tool.
`
`3.
`
`The device
`
`for overall machine
`
`tool monitoring of
`
`claim 1, wherein the first characteristics extracting unit
`
`extracts.frequency components
`
`from the target signal,
`
`and
`
`20
`
`the
`
`second
`
`characteristics
`
`extracting unit
`
`extracts
`
`a
`
`frequency component of an envelop from the target signal.
`
`4.
`
`The device
`
`for overall machine
`
`tool monitoring of
`
`claim 1, wherein the first and the second neural networks
`
`25
`
`are competitive learning neural networks.
`
`-20-
`
`
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