Smart Cutting Tools Used in the Processing of Aluminum Alloys

The processing of aluminum alloys in optimal conditions is a problem that has not yet been fully resolved. The research carried out so far has proposed various intelligent tools, but which cannot be used in the presence of cooling-lubricating fluids. The objective of the research carried out in the paper was to design intelligent tools that would allow a control of the vibrations of the tool tip and to determine a better roughness of the processed surfaces. The designed intelligent tools can be used successfully in the processing of aluminum alloys, not being sensitive to coolants-lubricants. In the research, the processing by longitudinal turning of a semi-finished product with a diameter Ø = 55 mm of aluminum alloy A2024-T3510 was considered. Two constructive variants of smart tools were designed, realized, and used, and the obtained results were compared with those registered for the tools in the classic constructive variant. The analysis of vibrations that occur during the cutting process was performed using the following methods: Fast Fourier Transform (FFT); Short-Time Fourier-Transformation (STFT); the analysis of signal of vibrations. A vibration analysis was also performed by modeling using the Finite Element Method (FEM). In the last part of the research, an analysis of the roughness of the processed surfaces, was carried out and a series of diagrams were drawn regarding curved profiles; filtered profiles; Abbott–Firestone curve. Research has shown that the use of smart tools in the proposed construction variants is a solution that can be used in very good conditions for processing aluminum alloys, in the presence of cooling-lubrication fluids.

Improving the Performance of Steel Machining Processes through Cutting by Vibration Control

Machining processes through cutting are accompanied by dynamic phenomena that influence the quality of the processed surfaces. Thus, this research aimed to design, make, and use a tool with optimal functional geometry, which allowed a reduction of the dynamic phenomena that occur in the cutting process. In order to carry out the research, the process of cutting by front turning with transversal advance was taken into account. Additionally, semi-finished products with a diameter of Ø = 150 mm made of C45 steel were chosen for processing (1.0503). The manufacturing processes were performed with the help of two tools: a cutting tool, the classic construction version, and another that was the improved construction version. In the first stage of the research, an analysis was made of the vibrations that appear in the cutting process when using the two types of tools. Vibration analysis considered the following: use of the Fast Fourier Transform (FFT) method, application of the Short-Time Fourier-Transformation (STFT) method, and observation of the acceleration of vibrations recorded during processing. After the vibration analysis, the roughness of the surfaces was measured and the parameter Ra was taken into account, but a series of diagrams were also drawn regarding the curved profiles, filtered profiles, and Abbott–Firestone curve. The research showed that use of the tool that is the improved constructive variant allows accentuated reduction of vibrations correlated with an improvement of the quality of the processed surfaces.

Investigation of a Signal Demodulation Method based on Wavelet Transformation for OFDR to Enhance Its Distributed Sensing Performance

Optical fiber distributed sensing that is based on optical frequency domain reflectometer (OFDR) is a promising technology for achieving a highest spatial resolution downwards to several millimeters. An OFDR signal demodulation method that is based on Morlet wavelet transformation (WT) is demonstrated in detail to improve the resolution of distributed sensing physical quantity under a high spatial resolution, aiming at the trade-off between spatial and spectrum resolution. The spectrum resolution, spatial interval of the measured gauges, and spatial resolution can be manually controlled by adjusting the wavelet parameters. The experimental results that were achieved by the wavelet transformation (WT) method are compared with these by short time Fourier transformation (STFT) method and they indicate that significant improvements, such as strain resolution of 1 με, spatial resolution of 5 mm, average repeatability of 4.3 με, and stability of 7.3 με within one hour, have been achieved. The advantages of this method are high spatial and spectral resolution, robust, and applicability with current OFDR systems.

IN-PROCESS MONITORING AND ANALYSIS OF DYNAMIC DISTURBANCES IN BORING AND TREPANNING ASSOCIATION (BTA) DEEP DRILLING

This paper presents an approach to monitor the dynamic disturbances of a BTA (boring and trepanning association) deep drilling system. High length to diameter ratios are the key characteristic of deep drilling processes compared to conventional drilling applications. Since length to diameter ratios of up to 150 for slender tool-boring-bar assemblies are common, the deep drilling process is sensitive to dynamic disturbances such as chatter and whirling vibrations. Whirling vibrations usually effect the shape of the hole and cause holes with several lobes. To gain a deeper understanding of the dynamic state of the process, a sensor application has been developed and was tested in practice. Experimental investigations on BTA deep drilling with continuous multi-sensory monitoring were conducted. The used setup allowed the determination of the frequencies of chatter and whirling vibrations during the cutting process by analysing the logged data using a continuous short-time Fourier transformation (STFT).