CNC Freze Tezgahının Bulanık Tabanlı Takım Aşınma Takibi

Year 2022, , 248 - 256, 30.08.2022

İsmet Gücüyener

https://doi.org/10.53433/yyufbed.1067638

Abstract

Talaşlı imalat sistemlerinde kesici takım aşınması, hassas imalat süreçlerinde hatalara neden olur. Hatalı üretim de işlenen hammadde israfına ve boşuna harcanan zaman kaybına neden olur. Takım aşınmasının sürekli izlenmesi ve aşınma değerinin tolerans değerinin dışına çıkması durumunda otomatik uyarı verilmesi bu sorunları çözecektir. Titreşim değerleri ve motorların çektiği güçler, üretim sırasında kesici takım aşınmasının temassız izlenmesinde önemli ipuçları sağlar. Bu çalışmada düşük maliyetli sensörlerin kullanımı ve uygulanan bulanık karar mekanizması sayesinde kesici takım durumu yüzde 90,17 doğrulukla çevrimiçi olarak tespit edilebilmiştir. İş mili motorunun çektiği gücün RMS değeri, fiber optik sensör çıkış voltajının ortalama değeri ve seçilen fiber optik sensör çıkış dalgacık dönüşümlerinin ortalama değerleri tasarlanan sistemin girdileridir. Sistemin çıktısı, bulanık karar mekanizması tarafından tahmin edilen kesici takım aşınma değeridir.

Keywords

Bulanık mantık, CNC freze, Fiber optik sensor, Wavelet dönüşümü

Fuzzy Based Tool Wear Monitoring of the CNC Milling Machine

Abstract

In machining systems, cutting tool wear causes errors in precision manufacturing processes. It causes a waste of raw material processed in faulty production and a waste of time spent in vain. Continuous monitoring of tool wear and generating an automatic warning in case the wear value falls outside the tolerance value will resolve these issues. Vibration values and the powers drawn by the motors provide important clues in the non-contact monitoring of cutting tool wear during production. In this study, thanks to the use of low-cost sensors and the applied fuzzy decision mechanism , the cutting tool status could be detected online with an accuracy of 90.17 percent. The RMS value of the power drawn by the spindle motor, average value of fiber optic sensor output voltage, and the average values of selected fiber optic sensor output wavelet transformations are the inputs of the designed system. The output of the system is the cutting tool wear value estimated by the fuzzy decision mechanism.

Keywords

CNC milling machine, Fiber optic sensor, Fuzzy inference, Wavelet transform

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