Теория размерностей и моделирование температуры на границе раздела стружка–инструмент при точении SS304 на основе искусственных нейронных сетей

Abstract

Introduction. During machining, the resulting temperature has a wider and more critical impact on machining performance. During machining, the power consumption is mainly converted into heat near the cutting edge of the tool. Almost all the work performed during plastic deformation turns into heat. Researchers have put a lot of effort into measuring the cutting temperature during machining, as it significantly affects tool life and overall machining performance. The purpose of the work: to investigate the temperature of the chip-tool interface, taking into account the influence of cutting parameters and the type of tool coating during SS304 turning. The chip-tool interface temperature is measured by changing the cutting speed and feed with a constant cutting depth for uncoated and PVD single-layer TiAlN and multi-layer TiN/TiAlN coated carbide tools. In addition, an attempt is made to develop a model for predicting the temperature of the chip-tool interface using dimensional analysis and ANN simulating to better understand the process. The methods of investigation. Experiments are carried out with varying the cutting speed (140-260 m/min), feed (0.08-0.2 mm/rev) and a constant cutting depth of 1 mm. The chip-tool interface temperature is measured using the tool-work thermocouple principle. The Calibration Setup is designed to establish the relationship between the produced electromotive force (EMF) and the cutting temperature during machining. Statistical dimensional analysis and artificial neural network models have been developed to predict the temperature of the chip-tool interface. Tangential cutting force and chip attributes such as chip width and thickness are also measured depending on the cutting conditions, which is a prerequisite for dimensional analysis simulation. Results and Discussion. A tool made of TiAlN carbide with PVD coating had a lower temperature at the chip-tool interface than a tool with TiN/TiAlN coating. It has been observed that the chip-tool interface temperature increases prominently with the cutting speed, followed by the chip cross-sectional area and the specific cutting pressure. However, a lower cutting force was observed when using a carbide tool with a multi-layer TiN/TiAlN coating, which can be attributed to a lower coefficient of friction created by the front surface of this tool for flowing chips. On the other hand, the greatest cutting force was observed in uncoated carbide tools. It was noticed that the developed models allow predicting the temperature of the chip-tool interface with an absolute error of 5%. However, the lowest average absolute error of 0.78% was observed with the ANN model and, therefore, can be reliably used to predict the chip-tool interface temperature during SS304 turning.