Metrology and Measurement Systems

Spectrometry, especially spectrophotometry, is getting more and more often the method of choice not only in laboratory analysis of (bio)chemical substances, but also in the off-laboratory identification and testing of physical properties of various products, in particular - of various organic mixtures including food products and ingredients. Specialised spectrophotometers, called spectrophotometric analysers, are designed for such applications. This paper is on the state of the art in the domain of data processing in spectrophotometric analysers of food (including beverages). The following issues are covered: methodological background of food analysis, physical and metrological principles of spectrophotometry, the role of measurement data processing in spectrophotometry. General considerations are illustrated with examples, predominantly related to wine and olive oil analysis.

Products of Gaussian noises often emerge as the result of non-linear detection techniques or as parasitic effects, and their proper handling is important in many practical applications, including fluctuation-enhanced sensing, indoor air or environmental quality monitoring, etc. We use Rice’s random phase oscillator formalism to calculate the power density spectra variance for the product of two Gaussian band-limited white noises with zero-mean and the same bandwidth W. The ensuing noise spectrum is found to decrease linearly from zero frequency to 2W, and it is zero for frequencies greater than 2W. Analogous calculations performed for the square of a single Gaussian noise confirm earlier results. The spectrum at non-zero frequencies, and the variance of the square of a noise, is amplified by a factor two as a consequence of correlation effects between frequency products. Our analytic results are corroborated by computer simulations.

The article presents an application of Prony’s method with some known components in the analysis of electric power quality. Modifications of the Prony algorithm broaden the scope of method application. Modification of the filter of known components enables more accurate analysis of the parameters of unknown components and components with known or assumed frequencies. This article presents a comparison of the results of analyses conducted with the proposed algorithm for simulated and real signals and the results obtained by means of a commercial electric power quality testing device, operating in class A and using the Fourier transform. The proposed method enables to estimate the levels of the harmonic components, the frequency of the fundamental signal and real parameters of the interharmonic components, which are grouped and averaged in the contemporary monitoring equipment. Knowledge of the individual parameters of the interharmonics has considerable diagnostic importance while removing causes of incorrect operation affecting sensitive equipment in some electric power systems. Additionally, the algorithm is capable of analyzing exponentially damped components and finds its application in analysis of disturbances, for example, transient oscillations.

This paper derives analytical formulas for the systematic errors of the linear interpolated DFT (LIDFT) method when used to estimating multifrequency signal parameters and verifies this analysis using Monte-Carlo simulations. The analysis is performed on the version of the LIDFT method based on optimal approximation of the unit circle by a polygon using a pair of windows. The analytical formulas derived here take the systematic errors in the estimation of amplitude and frequency of component oscillations in the multifrequency signal as the sum of basic errors and the errors caused by each of the component oscillations. Additional formulas are also included to analyze particular quantities such as a signal consisting of two complex oscillations, and the analyses are verified using Monte-Carlo simulations.

In this paper, we investigate the implementation schemes of a single-scale wavelet transform processor using magnetostatic surface wave (MSSW) devices. There are three implementation schemes: the interdigital transducer, the meander line transducer and the grating transducer. Because the interdigital transducer has excellent properties, namely, good frequency characteristic and low insertion loss, we use the interdigital transducer as the implementation scheme of a single-scale wavelet transform processor using MSSW device.

In the paper, we also present the solutions to the three key problems: the direct coupling between the input transducer and the output transducer, the insertion loss, and the loss characteristics of the gyromagnetic film having an influence on the wavelet transform processor. There are two methods of reducing the direct coupling between the input transducer and the output transducer: increasing the distance between the input transducer and the output transducer, and placing a metal “wall” between the input transducer and the output transducer. There also are two methods of reducing the insertion loss of a single-scale wavelet transform processor using a MSSW device for scale: the appropriate thickness of the yttrium iron garnet (YIG) film and the uniform magnetic field.The smaller the ferromagnetic resonance linewidth of the gyromagnetic film , the smaller the magnetostatic wave propagation loss.

Estimating the fundamental frequency and harmonic parameters is basic for signal modelling in a power supply system. Differing from the existing parameter estimation algorithms either in power quality monitoring or in harmonic compensation, the proposed algorithm enables a simultaneous estimation of the fundamental frequency, the amplitudes and phases of harmonic waves. A pure sinusoid is obtained from an input multiharmonic input signal by finite-impulse-response (FIR) comb filters. Proposed algorithm is based on the use of partial derivatives of the processed signal and the weighted estimation procedure to estimate the fundamental frequency, the amplitude and the phase of a multi-sinusoidal signal. The proposed algorithm can be applied in signal reconstruction, spectral estimation, system identification, as well as in other important signal processing problems. The simulation results verify the effectiveness of the proposed algorithm.

At the Kielce University of Technology a new concept of accurate measurements of sphericity deviations of machine parts has been developed. The concept is based upon measurement of roundness profiles in many clearly defined cross-sections of the workpiece. Measurements are performed with the use of typical radial measuring instrument equipped with a unit allowing accurate positioning of the ball. The developed concept required finding a solution to numerous problems relating to the principle of the radial measurement. One of the problems to be solved was matching of measured roundness profiles. The paper presents an outline of the developed concept of sphericity measurement, a mathematical model of profile matching and results of the verification of the model.

Wind turbines are nowadays one of the most promising energy sources. Every year, the amount of energy produced from the wind grows steadily. Investors demand turbine manufacturers to produce bigger, more efficient and robust units. These requirements resulted in fast development of condition-monitoring methods. However, significant sizes and varying operational conditions can make diagnostics of the wind turbines very challenging.

The paper shows the case study of a wind turbine that had suffered a serious rolling element bearing (REB) fault. The authors compare several methods for early detection of symptoms of the failure. The paper compares standard methods based on spectral analysis and a number of novel methods based on narrowband envelope analysis, kurtosis and cyclostationarity approach.

The very important problem of proper configuration of the methods is addressed as well. It is well known that every method requires setting of several parameters. In the industrial practice, configuration should be as standard and simple as possible. The paper discusses configuration parameters of investigated methods and their sensitivity to configuration uncertainties

This paper presents a method of using a sensor with uniform Bragg grating with appropriately generated zone chirp. The presented method can be used for measuring two physical quantities, namely strain and temperature. By providing the same temperature sensitivity and different sensitivity to strain of two parts of a sensor, and experimental measurement of qualities of the proposed system and its calibration (experimental determination of sensitivity), verification of the results obtained from laboratory tests and the possibility of its practical implementation has been confirmed. The sensor grating was placed in such a way that its half was in the zone of a variable value of axial strain caused by changes of the cross-section of the sample. The other half, however, was in the zone of a constant cross-section of the sample and of constant value of strain, caused by the force stretching the sample. The obtained errors of non-linearity of processing characteristics for measuring strain and temperature of the proposed system were 2.7% and 1.5% respectively, while coefficients of sensitivity to strain and temperature were 0.77 x 10-6 m/e and 4.13 x 10-12 m/K respectively. The maximum differences between the values obtained from the indirect measurement and the set values were 110 μe for strain and 3.8°C for temperature, for a strain of 2500 μe and a temperature of 40°C.

Embedding cardiac system sensing devices in wheelchairs is both necessary and attractive. Elders, diabetics, or stroke victims are a substantial group needing permanent cardiac monitoring, without restriction of their already limited mobility. A set of sensing devices was embedded in a wheelchair to monitor the user without his awareness and intervention. A dual-wavelength reflection photoplethysmogram (PPG), and a ballistocardiogram (BCG) based on MEMS accelerometers and on electromechanical film sensors are output b