Metrology and Measurement Systems 

About: Metrology and Measurement Systems is an academic journal published by De Gruyter Open. The journal publishes majorly in the area(s): Signal & Signal processing. It has an ISSN identifier of 0860-8229. It is also open access. Over the lifetime, 1017 publications have been published receiving 8815 citations. The journal is also known as: Metrologiâ i IzmeritelЬnye Sistemy & M&MS.

Measurement of instantaneous shaft speed by advanced vibration signal processing - Application to wind turbine gearbox

Abstract: Condition monitoring of machines working under non-stationary operations is one of the most challenging problems in maintenance. A wind turbine is an example of such class of machines. One of effective approaches may be to identify operating conditions and investigate their influence on used diagnostic features. Commonly used methods based on measurement of electric current, rotational speed, power and other process variables require additional equipment (sensors, acquisition cards) and software. It is proposed to use advanced signal processing techniques for instantaneous shaft speed recovery from a vibration signal. It may be used instead of extra channels or in parallel as signal verification.

Sensors and Systems for the Detection of Explosive Devices - An Overview

Abstract: The paper pr esents analyses of current research projects connected with explosive material sensors. Sensors are desc ribed assigned to X andrad iation, optical radiation sensors, as well as detectors applied in gas chromatography, electrochemical and chemical sensors. Furthermore, neutron techniques and magnetic resonance devices were analyzed. Special attention was drawn to optoelectronic sensors of explosive devices. Keyw ords: Explosive device sensors, detection of explosive materials.

Frequency and Damping Estimation Methods - An Overview

Abstract: This overview paper presents and compares different methods traditionally used for estimating damped sinusoid parameters. Firstly, direct nonlinear least squares fitting the signal model in the time and frequency domains are described. Next, possible applications of the Hilbert transform for signal demodulation are presented. Then, a wide range of autoregressive modelling methods, valid for da mped sinusoids, are discussed, in which frequency and damping are estimated from calculated signal linear self -prediction coefficients. These methods aim at solving, directly or using least squares, a matrix linear eq uation in which signal or its autocorrelation function samples are used. The Prony, Steiglitz-McBride, Kumaresan-Tu fts, Total Least Squares, Matrix Pencil, YuleWalker and Pisarenko methods are taken into account. Finally, the interpolated discrete Fourier transform is presented with examples of Bertocco, Yoshida, and Agrež algo rithms. The Matlab codes of all the discussed methods are given. The second part of the paper presents sim ulation results, compared with the Cramer-Rao lower bound and commented. All tested methods are compared w ith respect to their accuracy (systematic errors), noise robustness, required signal length, and computational complexity.

Gabor Transform, SPWVD, Gabor-Wigner Transform and Wavelet Transform - Tools For Power Quality Monitoring

Abstract: The one-dimension frequency analysis based on DFT (Discrete FT ) is sufficient in many cases in detecting power disturbances and evaluating power quality (PQ). To illustrate in a more comprehensive manner the character of the signal, time-frequency analyses are p erformed. The most common known time-frequency representations (TFR) are spectrogram (SPEC) and Gabor Transform (GT). However, the method has a relatively low time-frequency resolution. The other TF R: Discreet Dyadic Wavelet Transform (DDWT), Smoothed Pseudo Wigner-Ville Distribution (SPWVD) and new Gabor-Wigner Transform (GWT) are described in the paper. The main features of the transforms, on the basis of testing signals, are presented.