Study of surface roughness by acoustic signal obtained from piezoelectric electret sensors in milling machine with CNC

Основний зміст сторінки статті

Maksym Shykhalieiev
Vadim Medvedev

Анотація

Nowadays, quality requirements in industry is an important issue. Study of surfaces machined with milling machine tools with computer numerical control by acoustic signal is informative method of monitoring of machining in industry. Also, studying of machining parameters and surface quality can be applied in different methods of machining metals, for example in abrasive waterjet cutting [1]. Quality of surfaces is important for machines and details.

In this research acoustic signal was measured by two piezoelectric sensors with thin electret plate to find out how surface roughness correlate with it. Electret material have dielectric properties and have high resistance to cutting fluids and coolants. It is important, because cutting of metals in experiment have been done in condition of machining with coolants. Electret microphone circuit shown on fig. 1. Acoustic signal obtained from electret microphone is characterized by frequency (Hz) and decibels relative to full scale (dBFS). Studying of this parameters compared with g-code and operation on machine tool allows to correlate acoustic signal with characteristics of finished surfaces.

The experiment was done on HAAS VF-2 machining center with support of ISO 6983 G-code. Two main operations were milling of planar and cylindrical surfaces and drilling of holes. Total of 5 parts with same drawings were machined. Each part was machined with one fixture outfit. Finished detail is shown in fig. 2. Material of workpiece was Duralumin D16 GOST 4784-97. Dimensions of the workpiece was L´H´B = 130´80´25mm. Cutting tools used in research was mill Ø10 with length of cutting part 20mm and spiral drill Ø12 with length of cutting part 70mm. Table 1 demonstrate the cutting parameters of the experiment.

Conclusion. As result of research study of correlation between acoustic signal and surface roughness was done. Acoustic spectrogram with fast furrier transform of machining was obtained and analyzed.

Блок інформації про статтю

Номер
Розділ
Технологія машинобудування
Біографія автора

Maksym Shykhalieiev, КПІ ім. Ігоря Сікорського

Механіко-машинобудівельний Інститут, Кафедра технології машинобудування, Аспірант

Посилання

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