Frequency Optimization of Ultrasonic Welding System with Gradient Descent Method Gradient Descent Metodu ile Ultrasonik Kaynak Sisteminin Frekans Optimizasyonu


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Teke M., Kalinbacoglu A., DURAN F., ÖZARSLAN YATAK M.

El-Cezeri Journal of Science and Engineering, cilt.10, sa.1, ss.46-56, 2023 (Scopus) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 10 Sayı: 1
  • Basım Tarihi: 2023
  • Doi Numarası: 10.31202/ecjse.1132660
  • Dergi Adı: El-Cezeri Journal of Science and Engineering
  • Derginin Tarandığı İndeksler: Scopus
  • Sayfa Sayıları: ss.46-56
  • Anahtar Kelimeler: Frequency optimization, Gradient descent algorithm, Ultrasonic welding
  • Gazi Üniversitesi Adresli: Evet

Özet

Ultrasonic welding, with its entry into the friction welding group, is preferred in many sectors as a joining method in today's industry. In this way, the materials to be welded are joined without the need for filler material. Since there is no filling material during welding, toxic gases and wastes do not come out, so it has a more environmentally friendly structure than other sources. In addition to producing maximum power at the resonance operating frequency, disturbing noise also occurs. Optimum welding form occurs during resonance operation. Therefore, frequency shift occurs according to the size and mechanical properties of the welded materials. The resonant frequency must be captured during welding to prevent this shift. In this study, a new methodology has been developed to determine the resonance frequency of ultrasonic welding machines to increase the system's efficiency. This variable resonance frequency value, which needs to be re-determined when the load changes, is determined online with the gradient descent algorithm during the welding process. Simulation studies were carried out in Matlab/Simulink environment. Two different resonance frequencies with a maximum random variation of 5% and 20% were used. As a result, 5% changing resonance frequency within 150 ms and 20% varying resonance frequency within 250 ms were obtained with the Gradient Descent algorithm.