Published November 1, 2018
| Version v1
Journal article
A survey of machine vision-based monitoring methods for abnormalities in molds
Creators
- 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/439/3/032086Additional details
Identifiers
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