AI-Based Welding Quality Detection
Alzayed, Abdul Aziz (2021)
Alzayed, Abdul Aziz
2021
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2021082517119
https://urn.fi/URN:NBN:fi:amk-2021082517119
Tiivistelmä
Artificial Intelligence (A.I.) is a multidisciplinary field whose goal is to automate activities that presently require human intelligence. Recent successes in A.I. include computerized medical diagnosticians and systems that automatically customize hardware to particular user requirements. The major problem areas addressed in A.I. can be summarized as Perception, Manipulation, Reasoning, Communication, and Learning. Perception is concerned with building models of the physical world from sensory input (visual, audio, etc.).
Many occupations nowadays need a professional person to check their products, and one of them is metal welding. After welding a professional person needed to check visually the quality of welding, if it has a good shape or no, and then the professional gives a report if the welding has been accepted or not.
With AI based solution one can make this procedure faster and the developed solution should improve itself each time one adds something new to its knowledge.
This study focuses on an AI image classification solution to check the welding quality, how it works to fulfil the function and the accuracy using the .Net environment (ASP.NET, MVC, ML.NET, Console App, .NET Framework), jQuery, JavaScript, Bootstrap.
The study went through many challenges in terms of collecting images, collecting references, and examining the results of images analysis, and the results were successful and correct in the cases that have been used.
Many occupations nowadays need a professional person to check their products, and one of them is metal welding. After welding a professional person needed to check visually the quality of welding, if it has a good shape or no, and then the professional gives a report if the welding has been accepted or not.
With AI based solution one can make this procedure faster and the developed solution should improve itself each time one adds something new to its knowledge.
This study focuses on an AI image classification solution to check the welding quality, how it works to fulfil the function and the accuracy using the .Net environment (ASP.NET, MVC, ML.NET, Console App, .NET Framework), jQuery, JavaScript, Bootstrap.
The study went through many challenges in terms of collecting images, collecting references, and examining the results of images analysis, and the results were successful and correct in the cases that have been used.