Accession Number:

ADA347671

Title:

Intelligent Tool Condition Monitoring in Milling Operation

Descriptive Note:

Corporate Author:

SOUTHAMPTON INST (UNITED KINGDOM) SYSTEMS ENGINEERING FACULTY

Personal Author(s):

Report Date:

1998-01-01

Pagination or Media Count:

10.0

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.

Subject Categories:

  • Manufacturing and Industrial Engineering and Control of Production Systems
  • Machinery and Tools

Distribution Statement:

APPROVED FOR PUBLIC RELEASE