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EN
This paper describes work aimed at assessing main journal bearing wear in a spark ignition engine using vibration measurements. A large number of tests were run with varying sensor location, engine speed, oil viscosity and bearing wear simulated by machining away material from bearing surfaces. Results show that signal magnitude can be used to characterize bearing operation and wear. Engine speed and oil grade have effects on the signals obtained. In addition it is shown that weak parts of signals can be enhanced with the addition of noise of appropriate level. Random noise was added to vibration signals and noise of an appropriate level enhanced weak parts of accelerometer signals.
EN
In the paper results of single- and double-pulse LIBS (Laser-Induced Breakdown Spectroscopy) measurements in collinear geometry are described. The experiments were performed using a unique self-made Nd:YAG laser operating in the Q-switching regime, where the laser transmission losses are switched. Such a laser allowed for an easy and quick change of the operating mode (one and two pulses), free shaping of the energy ratio of the two pulses (division of the energy of a single pulse into two parts) and a smooth change of the delay time between pulses in the range from 200 ns to 10 μs. To our knowledge, such a laser was used in LIBS measurements for the first time. LIBS experiments revealed strong self-absorption depending on energy ratios carried out in the first and second laser pulse in the double-pulse mode. This was confirmed also by statistical factorial analysis of LIBS spectra. Plasma temperature and LIBS signal enhancement were measured both for energy proportions between the first and the second laser pulse and for the first-to-second-pulse delay.
EN
Active Noise Control (ANC) has become an important field of research in recent decades. Noise Control in industrial environments and conference halls as well as in communication systems has been studied under the title adaptive-active noise cancellation-control (AANCC) and the results of these studies have been used in practical applications. Reducing time dependent noise is one of the ways recommended for speech enhancement. Here we have introduced an artificial neural network called ADALINE as a smart dual microphone active noise control system. This artificial neural network identifies sources of noise and interference during its training phase and adjusts accordingly. In this way the system reduces the input signal noise. Tests and implementations presented here are based on speech in Persian language and cumulative white Gaussian noise and the interference is assumed to be of the cosine type.
PL
Przedstawiono analizę szumów w otoczeniu przemysłowym i w salach konferencyjnych a następnie przedstawiono metody adaptacyjnych metod redukcji szumów. Szczególną uwagę zwrócono na szum zależny od czasu. Zastosowano metodę podwójnego mikrofonu i wykorzystano sieci neuronowe. Sieć identyfikuje źródło szumu i zakłóceń. Metodę sprawdzono doświadczalnie.
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