Intelligent Tool Condition Monitoring in Milling Operation

Abstract

One of the most important features of the modern machining system in an "unmanned" factory is to change tools that have been subjected to wear and damage. An integrated system composed of multi-sensors, signal processing device and intelligent decision making plans is a necessary requirement for automatic manufacturing process. An intelligent tool wear monitoring system for milling operation will be introduced in this report. The system is equipped with four kinds of sensors, signal transforming and collecting apparatus and microcomputer. A unique ANN (artificial neural network) driven fuzzy pattern recognition algorithm has been developed from this research. It can fuse the information from multiple sensors and has strong learning and noise suppression ability. This lead to successful tool wear classification under a range of machining conditions.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1998
Accession Number
ADA347671

Entities

People

  • A. D. Hope
  • G. A. King
  • Pan Fu

Tags

Communities of Interest

  • Sensors

DTIC Thesaurus Topics

  • Acoustic Emissions
  • Algorithms
  • Computers
  • Energy Consumption
  • Feature Extraction
  • Frequency
  • Frequency Domain
  • Fuzzy Sets
  • Machine Tools
  • Neural Networks
  • Pattern Recognition
  • Sensor Fusion
  • Signal Processing
  • Standards
  • Systems Engineering
  • Tools
  • Vibration

Fields of Study

  • Engineering

Readers

  • Artificial Intelligence
  • Metallurgy
  • Sensor Fusion and Tracking Systems.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - Neural Networks
  • Autonomy