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Machine Vision Inspection of the Lapping Process in the Production of Mass Impregnated High Voltage Cables
Blekinge Institute of Technology.
Blekinge Institute of Technology.
2018 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Background. Mass impregnated high voltage cables are used in, for example, submarine electric power transmission. One of the production steps of such cables is the lapping process in which several hundred layers of special purpose paper are wrapped around the conductor of the cable. It is important for the mechanical and electrical properties of the finished cable that the paper is applied correctly, however there currently exists no reliable way of continuously ensuring that the paper is applied correctly.

Objective. The objective of this thesis is to develop a prototype of a cost-effective machine vision system which monitors the lapping process and detects and records any errors that may occur during the process; with an accuracy of at least one tenth of a millimetre.

Methods. The requirements of the system are specified and suitable hardware is identified. Using a method where the images are projected down to one axis as well as other signal processing methods, the errors are measured. Experiments are performed where the accuracy and performance of the system is tested in a controlled environment.

Results. The results show that the system is able to detect and measure errors accurately down to one tenth of a millimetre while operating at a frame rate of 40 frames per second. The hardware cost of the system is less than €200.

Conclusions. A cost-effective machine vision system capable of performing measurements accurate down to one tenth of a millimetre can be implemented using the inexpensive Raspberry Pi 3 and Raspberry Pi Camera Module V2. Th

Place, publisher, year, edition, pages
2018. , p. 86
Keywords [en]
Computer Vision, Edge Extraction, Industrial Metrology, Projection Profile, Peak Detection
National Category
Computer Systems
Identifiers
URN: urn:nbn:se:bth-16707OAI: oai:DiVA.org:bth-16707DiVA, id: diva2:1230268
External cooperation
NKT HV Cables AB
Subject / course
Degree Project in Master of Science in Engineering 30.0
Educational program
PAACI Master of Science in Game and Software Engineering
Presentation
2018-05-31, 10:00 (English)
Supervisors
Examiners
Available from: 2018-07-04 Created: 2018-07-03 Last updated: 2018-07-04Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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Output format
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