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Abstract

This paper deals with the amplitude estimation in the frequency domain of low-level sine waves, i.e. sine waves spanning a small number of quantization steps of an analog-to-digital converter. This is a quite common condition for high-speed low-resolution converters. A digitized sine wave is transformed into the frequency domain through the discrete Fourier transform. The error in the amplitude estimate is treated as a random variable since the offset and the phase of the sine wave are usually unknown. Therefore, the estimate is characterized by its standard deviation. The proposed model evaluates properly such a standard deviation by treating the quantization with a Fourier series approach. On the other hand, it is shown that the conventional noise model of quantization would lead to a large underestimation of the error standard deviation. The effects of measurement parameters, such as the number of samples and a kind of the time window, are also investigated. Finally, a threshold for the additive noise is provided as the boundary for validity of the two quantization models
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Abstract

Power systems that are highly loaded, especially by a stochastic supply of renewables and the presence of storages, require dynamic measurements for their optimal control. Phasor measurement units (PMUs) can be used to capture electrical parameters of a power system. Standards on the PMU dynamic performance have been modified to incorporate their new dynamic mode of operation. This paper examines the PMU dynamic performance and proposes essential algorithms for measurement accuracy verification. Measurements of dynamic input signals, which vary in amplitude or frequency, were taken during automated tests of two PMUs. The test results are presented and expounded with further recommendation for the performance requirements. This paper also presents and examines applied testing procedures with relevance to the specifications of the IEEE Standard for Synchrophasor C37.118.1™-2011 and its amendment C37.118.1a™-2014.
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Abstract

Modern production technology requires new ways of surface examination and a special kind of surface profile parameters. Industrial quality inspection needs to be fast, reliable and inexpensive. In this paper it is shown how stochastic surface examination and its proper parameters could be a solution for many industrial problems not necessarily related with smoothing out a manufactured surface. Burnishing is a modern technology widely used in aircraft and automotive industries to the products as well as to process tools. It gives to the machined surface high smoothness, and good fatigue and wear resistance. Every burnished material behaves in a different manner. Process conditions strongly influence the final properties of any specific product. Optimum burnishing conditions should be preserved for any manufactured product. In this paper we deal with samples made of conventional tool steel – Sverker 21 (X153CrMoV12) and powder metallurgy (P/M) tool steel – Vanadis 6. Complete investigations of product properties are impossible to perform (because of constraints related to their cost, time, or lack of suitable equipment). Looking for a global, all-embracing quality indicator it was found that the correlation function and the frequency analysis of burnished surface give useful information for controlling the manufacturing process and evaluating the product quality. We propose three new indicators of burnishing surface quality. Their properties and usefulness are verified with the laboratory measurement of material samples made of the two mentioned kinds of tool steel.
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