Görüntü İşleme Algoritmalarına Dayalı Olarak Manyetik Parçacık Test Görüntülerinde Kusur Tespitinin Araştırılması

Year 2023, Volume: 23 Issue: 1, 115 - 122, 01.03.2023

Volkan Sözeri , Orhan Keskin , Coşkun Harmanşah , İlkay Kozak , Esma Nur Kibar

https://doi.org/10.35414/akufemubid.1173473

Abstract

Otomotiv, havacılık ve savunma sanayi sektörleri başta olmak üzere birçok sektörde kullanılan kritik parçaların hata tespitleri tahribatsız muayene testleri ile yapılmaktadır. Tahribatsız Muayene (TM) yöntemleri ile kritik parçaların maksimum güvenilirliği ve kalitesi, hızlı ve uygun maliyetli bir şekilde elde edilir. Manyetik parçacık testi (MT), ferromanyetik malzemelerdeki yüzey ve yüzey altı çatlaklarını tespit etmek için yaygın olarak kullanılmaktadır. Ayrıca, üretim aşamasında ve hizmetin bir noktasında tüm kritik çelik parçaların denetlendiği endüstriyel uygulamalarda da önemli bir kullanıma sahiptir. Bu çalışmada, operatöre MT deneyleri ile alınan görüntülerdeki kusurları belirlemede yardımcı olmak için seçilen görüntü işleme algoritmaları ile sistematik bir yaklaşım önerilmiştir. MT (Manyetik Parçacık Testi) deneyleri ile alınan görüntüler yazılıma aktarılmış ve önerilen yöntemlerle analiz edilmiştir. Elde edilen sonuçların referans test bloğundaki yapay kusurlarla uyumlu olduğu gözlemlenmiştir. Deneysel çalışmalar, önerilen yöntemin operatöre çatlakların yorumlanmasında önemli katkılar sağlayabileceğini göstermiştir. M2GLD algoritması referans bloktaki 6 kusurun tamamını, K Ortalama Kümeleme algoritması ise 5’ini tespit edebilmiştir.

Keywords

Tahribatsız Muayene, Manyetik Parçacık Testi, Görüntü İşleme Algoritmaları, Çatlak Tespiti

Thanks

Ege Üniversitesi Havacılık Meslek Yüksekokulu Öğretim Görevlisi Alperen Doğru’ ya NDT Laboratuvarında yapılan test çalışmalarındaki katkılarından dolayı teşekkür ederiz.

Investigation of Crack Detection in Magnetic Particle Testing Images Based on Image Process Algorithms

Abstract

Flaw detection of critical parts used in many sectors, especially in the automotive, aerospace and defense industry sectors, is made by Nondestructive Testing (NDT) techniques. Maximum reliability and quality of critical parts are achieved quickly and cost-effectively with NDT methods. Magnetic Particle Inspection (MPI) is widely used to detect surface and subsurface cracks in ferromagnetic materials. It also has important use in industrial applications where all critical steel parts are inspected during the production phase and at some point in service. In this study, a systematic approach is proposed with selected image processing algorithms to assist the operator in identifying defects in images taken by MPI experiments. Images taken with MPI experiments were transferred to the software and analyzed with the suggested methods. It was observed that the obtained results were compatible with the artifacts in the reference test block. Experimental studies have shown that the proposed method can provide important contributions to the operator in the interpretation of cracks. The M2GLD algorithm was able to detect all 6 defects in the reference block, while the K Mean Clustering algorithm was able to detect 5 of them.

Keywords

Nondestructive Testing, Magnetic Particle Testing, Image Processing Algorithm, Crack Detection

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