Digital Signal Processing

Solar photovoltaic (PV) systems are increasingly recognized as crucial sustainable energy sources with diverse applications. Their implementation leverages rapid advancements in material engineering, communication systems, and computational intelligence tools. This paper focuses on mathematical methods for signal analysis, including multichannel signal processing, optimization methods, and feature evaluation, to monitor PV systems with panels situated in a specific coordinate system.

This paper is a novel digital signal processing software of the advanced conversion of text-to-speech synthesis technology, which has been available as a range of hardware products for more than ten years, to software. It was initially created as a replacement for character cell terminals and telephony applications, but it is now also used to give people who are visually impaired access to information. With a digital formant synthesizer used to mimic the human vocal tract, text-to-speech quality is very high in both understandability and naturalness.

The objective of this dataset is the fault diagnosis in diesel engines to assist the predictive maintenance, through the analysis of the variation of the pressure curves inside the cylinders and the torsional vibration response of the crankshaft. Hence a fault simulation model based on a zero-dimensional thermodynamic model was developed. The adopted feature vectors were chosen from the thermodynamic model and obtained from processing signals as pressure and temperature inside the cylinder, as well as, torsional vibration of the engine’s flywheel.