Published November 1, 2018 | Version v1
Journal article

A survey of machine vision-based monitoring methods for abnormalities in molds

  • 1. School of Mechanical Engineering, Beijing Institute of Technology, Beijing (China)

Description

Anomaly monitoring in the mold is a mean to ensure its efficient and stable operation. At present, there are many methods for detecting abnormalities in molds, such as tonnage or strain signal analysis, ultrasonic or magnetostatic detection, and machine vision inspection. This paper compares the advantages and disadvantages of the above methods, lists the existing abnormalities of machine vision mold monitoring methods, and the two major problems (illumination changes and camera vibration) in the process of monitoring solutions are summarized. At the end, the paper summarizes and analyzes the development direction and key points of this field. (paper)

Availability note (English)

Available from http://dx.doi.org/10.1088/1757-899X/439/3/032086

Additional details

Publishing Information

Journal Title
IOP Conference Series. Materials Science and Engineering (Online)
Journal Volume
439
Journal Issue
3
Journal Page Range
[7 p.]
ISSN
1757-899X

Conference

Title
International Conference on Advanced Electronic Materials, Computers and Materials Engineering
Acronym
AEMCME 2018
Dates
14-16 Sep 2018
Place
Singapore (Singapore)

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
52100222
Subject category
S47: OTHER INSTRUMENTATION; S42: ENGINEERING;
Resource subtype / Literary indicator
Conference
Descriptors DEI
CAMERAS; ILLUMINANCE; MONITORING; SIGNALS; STATIC MAGNETIC FIELDS; ULTRASONIC WAVES
Descriptors DEC
MAGNETIC FIELDS; SOUND WAVES