Versatile visual inspection tool for the manufacturing process

Panagiotis Liatsis, Peter E. Wellstead, Martin B. Zarrop, Terry Prendergast

Research output: Contribution to conferencePaperpeer-review

5 Scopus citations

Abstract

The dynamically changing nature and the complex behaviour of processes in manufacturing cells dictate the need for lean, agile and flexible manufacturing systems. This research describes a versatile, intelligent vision system capable of performing a variety of tasks for the manufacturing process. The key features of the system are reconfigurability, adaptation, and real-time performance. It is based on higher-order neural networks (HONNs), whose structure is designed using a priori information related to the expected relationships between input pixels. The incorporation of prior information is the reason that HONNs demonstrate invariance to certain geometric distortions. An input representation scheme known as coarse coding was used to represent the fine resolution image with a set of offset, overlaying coarse resolution images. The performance of the system is examined in three real-world application areas, i.e. the classification of screws, the classification of rivets, and finally the detection of flaws in axisymmetric engineering parts.

Original languageBritish English
Pages1505-1510
Number of pages6
StatePublished - 1994
EventProceedings of the 1994 IEEE Conference on Control Applications. Part 3 (of 3) - Glasgow, UK
Duration: 24 Aug 199426 Aug 1994

Conference

ConferenceProceedings of the 1994 IEEE Conference on Control Applications. Part 3 (of 3)
CityGlasgow, UK
Period24/08/9426/08/94

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