2018
DOI: 10.1051/matecconf/201819015008
|View full text |Cite
|
Sign up to set email alerts
|

Fast Quality Inspection of Micro Cold Formed Parts using Telecentric Digital Holographic Microscopy

Abstract: Quality inspection is an integral part of the production process and often part of the quality management agreements between manufacturer and customer. Especially when it comes to safety-relevant parts, i.e. in the automobile or medical industry, often a 100% quality inspection is mandatory. Here, we present a solution comprised of a digital holographic measurement system, as well as fast algorithms for geometric evaluation and surface defect detection that paves the way for the inspection of metallic micro cu… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1

Citation Types

0
2
0

Year Published

2020
2020
2021
2021

Publication Types

Select...
2

Relationship

2
0

Authors

Journals

citations
Cited by 2 publications
(2 citation statements)
references
References 25 publications
0
2
0
Order By: Relevance
“…In our systems, we use optical fibers to transport illumination and reference waves in order to achieve maximum flexibility. If refocusing is necessary, it is useful to employ a telecentric microscope objective in order to avoid depth-dependent magnification [25]. The reference wave and the illumination are provided by an optical fiber.…”
Section: Rapid Holographic Shape Measurement Of Micro Partsmentioning
confidence: 99%
“…In our systems, we use optical fibers to transport illumination and reference waves in order to achieve maximum flexibility. If refocusing is necessary, it is useful to employ a telecentric microscope objective in order to avoid depth-dependent magnification [25]. The reference wave and the illumination are provided by an optical fiber.…”
Section: Rapid Holographic Shape Measurement Of Micro Partsmentioning
confidence: 99%
“…Furthermore, it has to be possible to run it in real-time on a low-weight and low-power hardware system. A promising candidate for the development of such algorithms are convolutional neural networks (CNN) as they have consistently found success in a variety of image processing tasks ranging from image classification [6] to image segmentation and have hence also been successfully applied to surface inspection tasks [7][8][9]. However, CNNs require suitable hardware to achieve real-time performance.…”
Section: Introductionmentioning
confidence: 99%