The paper presents results of the localization of main noise sources in the industrial plant. Identification of main noise sources was made with an acoustic camera using Beamforming Method. Parallel to the measurements by means of the acoustic camera, sound level measurements on the main noise sources have been performed. Based on the calculations, prediction regarding the noise emission at residential buildings located near to the plant has been determined. Acoustic noise maps have been performed with LEQ Professional software, which includes the 3D geometry of the buildings inside the plant. It has been established that, after introduction of noise reduction measures in the plant, the noise levels at the observation points in the residential area meets the limit values.

Entrapped gases, solidification shrinkage and non-metallic compound formation are main sources of porosity in aluminium alloy castings. Porosity is detrimental to the mechanical properties of these castings; therefore, its reduction is pursued. Rotary degassing is the method mostly employed in industry to remove dissolved gases from aluminium melts, reducing porosity formation during solidification of the cast part. Recently, ultrasonic degassing has emerged as a promising alternative thanks to a lower dross formation and higher energy efficiency. This work aims to evaluate the efficiency of the ultrasonic degasser and compare it to a conventional rotary degassing technique applied to an AlSi10Mg alloy. Degassing efficiency was evaluated employing the reduced pressure test (RPT), where samples solidified under reduced pressure conditions are analysed. Factors affecting RPT were considered and temperature parameters for the test were established. The influence of ultrasonic degassing process parameters, such as degassing treatment duration and purging gas flow rate were studied, as well as treated aluminium volume and oxide content. Finally, ultrasonic degassing process was contrasted to a conventional rotary degassing technique, comparing their efficiency.

Conductivity measurements of distilled water and some electrolytic solution due to the SO2 and CO2 absorption have been performed in the laboratory and on the site. CO2, has been found to cause a decrease in the conductivity of alkaline solutions and an increase in that of CaCO3, and MgCO3, aqueous suspensions. The importance of the direct SO2 absorption was proved to be limited to the zones of extremely high concentrations of this gas in the ambient air.

Performance of standard Direction of Arrival (DOA) estimation techniques degraded under real-time signal conditions. The classical algorithms are Multiple Signal Classification (MUSIC), and Estimation of Signal Parameters via Rotational Invariance Technique (ESPRIT). There are many signal conditions hamper on its performance, such as closely spaced and coherent signals caused due to the multipath propagations of signals results in a decrease of the signal to noise ratio (SNR) of the received signal. In this paper, a novel DOA estimation technique named CW-PCA MUSIC is proposed using Principal Component Analysis (PCA) to threshold the nearby correlated wavelet coefficients of Dual-Tree Complex Wavelet transform (DTCWT) for denoising the signals before applying to MUSIC algorithm. The proposed technique improves the detection performance under closely spaced, and coherent signals with relatively low SNR conditions. Also, this method requires fewer snapshots, and less antenna array elements compared with standard MUSIC and wavelet-based DOA estimation algorithms.