Araştırma Makalesi
BibTex RIS Kaynak Göster

Detecting Manufacturing Defects on Printed Circuit Boards Using Metamaterial-Based Circular Microstrip Patch Antenna

Yıl 2024, Cilt: 5 Sayı: 2, 65 - 74, 30.08.2024
https://doi.org/10.52795/mateca.1475763

Öz

In this study, a microstrip circular patch antenna is designed having a metamaterial-based (MTM) ground plane to detect manufacturing defects of short circuits and open circuits on printed circuit boards (PCB). In that regard, PCB specimens of FR-4 as the substrate and copper microstrip lines as the conductive wiring lines are designed and manufactured. Five vertical copper lines printed side by side on the top of the substrate are used to demonstrate the working mechanism of the designed antenna sensor. Two different defect scenarios of open and short circuits with controlled locations are studied to determine variations in the return loss data of the proposed structure. MTM cell structures with cross lines enclosed by an octagon ring are periodically placed as part of the ground plane of the proposed antenna to obtain higher sensitivity of the designed and manufactured sensor. Antenna return loss behaviors in terms of the locations of the faults are employed to prepare a database to detect not only the presence of the faults but also determine their locations. Since the samples to be measured are not irreversibly damaged during the testing process, the proposed design can be considered a non-destructive measurement method to provide information about the type and location of defects with real-time measurement data.

Kaynakça

  • W. Jillek, W. Yung, Embedded components in printed circuit boards: a processing technology review. International Journal of Advanced Manufacturing Technologies, 25: 350–360, 2005.
  • A.C. Marques, J.-M. Cabrera, C.F. Malfatti, Printed circuit boards: A review on the perspective of sustainability, Journal of Environmental Management, 131: 298-306, 2013.
  • K.P. Anoop, N.S. Sarath, V.V. Sasi Kumar, A review of PCB defect detection using image processing, International Journal of Engineering and Innovative Technology 4(11): 188-192, 2015.
  • H. Rau, C-H. Wu, Automatic optical inspection for detecting defects on printed circuit board inner layers, The International Journal of Advanced Manufacturing Technology, 25: 940-946, 2005.
  • W. Dai, A. Mujeeb, M. Erdt, A. Sourin, Soldering defect detection in automatic optical inspection, Advanced Engineering Informatics, 43: 101004, 2020.
  • N. Asadizanjani, S. Shahbazmohamadi, M. Tehranipoor, D. Forte, Non-destructive pcb reverse engineering using x-ray micro computed tomography, International Symposium for Testing and Failure Analysis (ISTFA), 1-5 November 2015, Oregon, USA.
  • Y. Zhou, M. Yuan, J. Zhang, G. Ding, S. Qin. Review of vision-based defect detection research and its perspectives for printed circuit board, Journal of Manufacturing Systems, 70: 557-578, 2023.
  • G. Mahalingam, K. M. Gay, K. Ricanek. Pcb-metal: A pcb image dataset for advanced computer vision machine learning component analysis, 16th International Conference on Machine Vision Applications (MVA), 27-31 May 2019, Tokyo, Japan.
  • J. Schmitt, J. Bönig, T. Borggräfe, G. Beitinger, J. Deuse. Predictive model-based quality inspection using machine learning and edge cloud computing, Advanced Engineering Informatics, 45: 101101, 2020.
  • C.A. Balanis, Antenna theory analysis and design, 3rd Ed., John Wiley & Sons, New Jersey, 2005.
  • V.G. Veselago, The electrodynamics of substances with simultaneously negative values of ε and μ, Soviet Physics Uspekhi, 10, 509-514, 1968.
  • V. Kaya, İ. Akgül, Detection of defects in printed circuit boards with machine learning and deep learning algorithms, European Journal of Science and Technology, 41: 183-186, 2022.

Metamalzeme Tabanlı Dairesel Mikroşerit Yama Anteni Kullanılarak Baskılı Devre Kartlarındaki Üretim Hatalarının Tespiti

Yıl 2024, Cilt: 5 Sayı: 2, 65 - 74, 30.08.2024
https://doi.org/10.52795/mateca.1475763

Öz

Bu çalışmada, baskılı devre kartları (PCB) üzerindeki kısa devre ve açık devrelerden kaynaklanan imalat hatalarını tespit etmek için metamalzeme tabanlı (MTM) yer düzlemine sahip bir mikroşerit dairesel yama anteni tasarlanmıştır. Bu bağlamda altlık olarak FR-4 PCB numuneleri ve iletken kablolama hatları olarak bakır mikroşerit hatları tasarlanıp üretilmektedir. Alt tabakanın üst kısmında yan yana basılmış beş dikey bakır çizgi, tasarlanan anten sensörünün çalışma mekanizmasını göstermek için kullanılmıştır. Önerilen yapının geri dönüş kaybı verilerindeki değişiklikleri belirlemek için konumları kontrollü açık ve kısa devrelerden oluşan iki farklı arıza senaryosu incelenmiştir. Tasarlanan ve üretilen sensörün daha yüksek hassasiyetini elde etmek için, sekizgen bir halka ile çevrelenmiş çapraz çizgili MTM hücre yapıları, önerilen antenin yer düzleminin bir parçası olarak periyodik olarak yerleştirilmektedir. Arızaların konumlarına göre anten geri dönüş kaybı davranışları, arızaların sadece varlığını tespit etmekle kalmayıp aynı zamanda konumlarını da tespit etmek için bir veri tabanı hazırlamak amacıyla kullanılmıştır. Ölçülecek numuneler test sürecinde geri dönülemez bir hasara uğramadığından, önerilen tasarım, gerçek zamanlı ölçüm verileriyle kusurların türü ve konumu hakkında bilgi sağlayan, tahribatsız bir ölçüm yöntemi olarak değerlendirilebilir.

Kaynakça

  • W. Jillek, W. Yung, Embedded components in printed circuit boards: a processing technology review. International Journal of Advanced Manufacturing Technologies, 25: 350–360, 2005.
  • A.C. Marques, J.-M. Cabrera, C.F. Malfatti, Printed circuit boards: A review on the perspective of sustainability, Journal of Environmental Management, 131: 298-306, 2013.
  • K.P. Anoop, N.S. Sarath, V.V. Sasi Kumar, A review of PCB defect detection using image processing, International Journal of Engineering and Innovative Technology 4(11): 188-192, 2015.
  • H. Rau, C-H. Wu, Automatic optical inspection for detecting defects on printed circuit board inner layers, The International Journal of Advanced Manufacturing Technology, 25: 940-946, 2005.
  • W. Dai, A. Mujeeb, M. Erdt, A. Sourin, Soldering defect detection in automatic optical inspection, Advanced Engineering Informatics, 43: 101004, 2020.
  • N. Asadizanjani, S. Shahbazmohamadi, M. Tehranipoor, D. Forte, Non-destructive pcb reverse engineering using x-ray micro computed tomography, International Symposium for Testing and Failure Analysis (ISTFA), 1-5 November 2015, Oregon, USA.
  • Y. Zhou, M. Yuan, J. Zhang, G. Ding, S. Qin. Review of vision-based defect detection research and its perspectives for printed circuit board, Journal of Manufacturing Systems, 70: 557-578, 2023.
  • G. Mahalingam, K. M. Gay, K. Ricanek. Pcb-metal: A pcb image dataset for advanced computer vision machine learning component analysis, 16th International Conference on Machine Vision Applications (MVA), 27-31 May 2019, Tokyo, Japan.
  • J. Schmitt, J. Bönig, T. Borggräfe, G. Beitinger, J. Deuse. Predictive model-based quality inspection using machine learning and edge cloud computing, Advanced Engineering Informatics, 45: 101101, 2020.
  • C.A. Balanis, Antenna theory analysis and design, 3rd Ed., John Wiley & Sons, New Jersey, 2005.
  • V.G. Veselago, The electrodynamics of substances with simultaneously negative values of ε and μ, Soviet Physics Uspekhi, 10, 509-514, 1968.
  • V. Kaya, İ. Akgül, Detection of defects in printed circuit boards with machine learning and deep learning algorithms, European Journal of Science and Technology, 41: 183-186, 2022.
Toplam 12 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Modelleme ve Simülasyon
Bölüm Araştırma Makaleleri
Yazarlar

Sultan Suheyla Bakir 0009-0009-6963-0610

Asaf Behzat Sahin Bu kişi benim 0000-0001-9759-8448

Erken Görünüm Tarihi 23 Ağustos 2024
Yayımlanma Tarihi 30 Ağustos 2024
Gönderilme Tarihi 30 Nisan 2024
Kabul Tarihi 25 Haziran 2024
Yayımlandığı Sayı Yıl 2024 Cilt: 5 Sayı: 2

Kaynak Göster

APA Bakir, S. S., & Sahin, A. B. (2024). Detecting Manufacturing Defects on Printed Circuit Boards Using Metamaterial-Based Circular Microstrip Patch Antenna. İmalat Teknolojileri Ve Uygulamaları, 5(2), 65-74. https://doi.org/10.52795/mateca.1475763
AMA Bakir SS, Sahin AB. Detecting Manufacturing Defects on Printed Circuit Boards Using Metamaterial-Based Circular Microstrip Patch Antenna. MATECA. Ağustos 2024;5(2):65-74. doi:10.52795/mateca.1475763
Chicago Bakir, Sultan Suheyla, ve Asaf Behzat Sahin. “Detecting Manufacturing Defects on Printed Circuit Boards Using Metamaterial-Based Circular Microstrip Patch Antenna”. İmalat Teknolojileri Ve Uygulamaları 5, sy. 2 (Ağustos 2024): 65-74. https://doi.org/10.52795/mateca.1475763.
EndNote Bakir SS, Sahin AB (01 Ağustos 2024) Detecting Manufacturing Defects on Printed Circuit Boards Using Metamaterial-Based Circular Microstrip Patch Antenna. İmalat Teknolojileri ve Uygulamaları 5 2 65–74.
IEEE S. S. Bakir ve A. B. Sahin, “Detecting Manufacturing Defects on Printed Circuit Boards Using Metamaterial-Based Circular Microstrip Patch Antenna”, MATECA, c. 5, sy. 2, ss. 65–74, 2024, doi: 10.52795/mateca.1475763.
ISNAD Bakir, Sultan Suheyla - Sahin, Asaf Behzat. “Detecting Manufacturing Defects on Printed Circuit Boards Using Metamaterial-Based Circular Microstrip Patch Antenna”. İmalat Teknolojileri ve Uygulamaları 5/2 (Ağustos 2024), 65-74. https://doi.org/10.52795/mateca.1475763.
JAMA Bakir SS, Sahin AB. Detecting Manufacturing Defects on Printed Circuit Boards Using Metamaterial-Based Circular Microstrip Patch Antenna. MATECA. 2024;5:65–74.
MLA Bakir, Sultan Suheyla ve Asaf Behzat Sahin. “Detecting Manufacturing Defects on Printed Circuit Boards Using Metamaterial-Based Circular Microstrip Patch Antenna”. İmalat Teknolojileri Ve Uygulamaları, c. 5, sy. 2, 2024, ss. 65-74, doi:10.52795/mateca.1475763.
Vancouver Bakir SS, Sahin AB. Detecting Manufacturing Defects on Printed Circuit Boards Using Metamaterial-Based Circular Microstrip Patch Antenna. MATECA. 2024;5(2):65-74.