Working process monitoring device

• US 20080127793A1
• Filed: 11/30/2007
• Published: 06/05/2008
• Est. Priority Date: 11/30/2006
• Status: Abandoned Application

• Current Assignee: Panasonic Electric Works Company Limited (Panasonic Holdings Corporation)
• Original Assignee: Asahi Matsushita Electric Works Ltd. (Panasonic Holdings Corporation)
• Inventors: Ikeda, Kazutaka
• Application Number:
  US11/987,441
• Publication Number:
  US 20080127793A1
• Time in Patent Office: Days
• US Class Current: 83/73
• CPC Class Codes: G01H 1/003 of rotating machines G01H1/10 takes precedence
• CPC Class Codes: G05B 19/406 characterised by monitoring or safety G05B19/19 takes precedence
• CPC Class Codes: G05B 2219/33296 ANN for diagnostic, monitoring
• CPC Class Codes: G05B 2219/37435 Vibration of machine
• CPC Class Codes: G05B 2219/43124 Adapt speed as function of material, thickness, depth, volume, width, uniform surface quality
• CPC Class Codes: G05B 2219/45229 Woodworking
• CPC Class Codes: Y10T 83/145 Including means to monitor product
• CPC Class Codes: Y10T 83/159 Including means to compensate tool speed for work-feed variations

Abstract

A working process monitoring device includes: a sensor unit for detecting at least one of vibrations and sound waves produced while processing a workpiece by a working machine rotatably driven by a driving unit; a signal input unit for extracting target signals from an electric signal outputted from the sensor unit; and an amount of characteristics extracting unit for extracting amounts of characteristics including a plurality of parameters from the target signals. Further, the working process monitoring device includes a material inspecting unit for detecting whether a material of a portion of the workpiece currently being processed is normal in quality or not, wherein the material inspecting unit employs a neural network trained by using amounts of characteristics extracted from target signals obtained while processing a workpiece made of a normal quality material.

Claims

1. A working process monitoring device, comprising:

a sensor unit for detecting at least one of vibrations and sound waves produced while processing a workpiece by a working machine rotatably driven by a driving unit;

a signal input unit for extracting target signals from an electric signal outputted from the sensor unit;

an amount of characteristics extracting unit for extracting amounts of characteristics including a plurality of parameters from the target signals; and

a material inspecting unit for detecting whether a material of a portion of the workpiece currently being processed is normal in quality or not, wherein the material inspecting unit employs a neural network trained by using amounts of characteristics extracted from target signals obtained while processing a workpiece made of a normal quality material.

2. The working process monitoring device of claim 1, wherein the workpiece is wood, and the working machine is a cutting device having a saw blade driven by the driving unit, and

wherein the working process monitoring device further comprising a machining terminating unit which terminates machining operation of the workpiece when the material inspecting unit detects that the material of the portion of the workpiece is not normal.

3. The working process monitoring device of claim 2, wherein the saw blade is disposed at the working machine to cut the workpiece across wood grain thereof, and at least one of a cutting speed and a relative feed speed between the workpiece and the saw blade is controllable, and

wherein early wood portions and late wood portions of the workpiece are treated as normal material portions among portions being machined,

the working process monitoring device further comprising a speed control unit which controls at least one of the cutting speed and the feed speed so that an amount of contact per unit time that saw teeth of the saw blade is in contact with the workpiece while cutting the late wood portions is greater than that while cutting the early wood portions.

4. The working process monitoring device of claim 1, wherein the neural network is a competitive learning neural network.