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 by the hardware. Tests were conduced on twenty one subjects, for an immobility scenario. Additional recordings were made for helped propulsion over a tiled floor course, with good results in keeping track of acceleration BCG and PPG. A treadmill was also used for tests, providing a smooth floor and constant speed and inclination. The PPG and acceleration BCG could be continuously monitored in all the tests. The developed system proves to be a good solution to monitor cardiac activity of wheelchair users even during motion.

Nowadays the “gold clinical standard” of hemodynamics diagnostic and cardiac output measurements is pulmonary artery catheterization by means of the Swan-Ganz catheter and thermodilution. The method itself is sensitive to numerous disturbances which cause inaccurate results. One of the well-known disadvantages of thermodilution is the overestimation of results at low values of cardiac output. This effect may concern the limited slew rate of the thermoelement mounted at the tip of the catheter. In this paper the relationship between the dynamic response of the thermoelement and the uncertainty of cardiac output measurements by means of thermodilution has been investigated theoretically and experimentally.

Gas-liquid flows abound in a great variety of industrial processes. Correct recognition of the regimes of a gasliquid flow is one of the most formidable challenges in multiphase flow measurement. Here we put forward a novel approach to the classification of gas-liquid flow patterns. In this method a flow-pattern map is constructed based on the average energy of intrinsic mode function and the volumetric void fraction of gas-liquid mixture. The intrinsic mode function is extracted from the pressure fluctuation across a bluff body using the empirical mode decomposition technique. Experiments adopting air and water as the working fluids are conducted in the bubble, plug, slug, and annular flow patterns at ambient temperature and atmospheric pressure. Verification tests indicate that the identification rate of the flow-pattern map developed exceeds 90%. This approach is appropriate for the gas-liquid flow pattern identification in practical applications.

In this paper a concept of finite impulse response (FIR) narrow band-stop (notch) filter with non-zero initial conditions, based on infinite impulse response (IIR) prototype filter, is proposed. The filter described in this paper is used to suppress power line noise from ECG signals. In order to reduce the transient response of the proposed FIR notch filter, optimal initial conditions for the filter have been determined. The algorithm for finding the length of the initial conditions vector is presented. The proposed values of the length of initial conditions vector, for several ECG signals and interfering frequencies, are calculated. The proposed filters are tested using various ECG signals. Computer simulations demonstrate that the proposed FIR filters outperform traditional FIR filters with initial conditions set to zero.

Modern control and measurement systems are equipped with interfaces to operate in local area networks and are typically intended to perform complicated data processing and control algorithms. The authors propose a digital system for rapid prototyping of target application devices. The concept solution separates the processing and control section from the hardware interface and user interface section. Both sections constitute independent ARM-based controllers interconnected via a direct USB link. Popular libraries can be used and low-level procedures developed, which enhances the system’s economic viability. A test unit developed for the purpose of the study was built around a SoC ARM7 microsystem and an off-the-shelf palmtop device. It demonstrated a continuous data stream transfer capability up to 150 kB per second, which was sufficient to monitor the performance of an electricity line.

The correlation of data contained in a series of signal sample values makes the estimation of the statistical characteristics describing such a random sample difficult. The positive correlation of data increases the arithmetic mean variance in relation to the series of uncorrelated results. If the normalized autocorrelation function of the positively correlated observations and their variance are known, then the effect of the correlation can be taken into consideration in the estimation process computationally. A significant hindrance to the assessment of the estimation process appears when the autocorrelation function is unknown. This study describes an application of the conditional averaging of the positively correlated data with the Gaussian distribution for the assessment of the correlation of an observation series, and the determination of the standard uncertainty of the arithmetic mean. The method presented here can be particularly useful for high values of correlation (when the value of the normalized autocorrelation function is higher than 0.5), and for the number of data higher than 50. In the paper the results of theoretical research are presented, as well as those of the selected experiments of the processing and analysis of physical signals.

An optical measurement method of radial displacement of a ring sample during its expansion with velocity of the order 172 m/s and estimation technique of plastic flow stress of a ring material on basis of the obtained experimental data are presented in the work. To measure the ring motion during the expansion process, the Phantom v12 digital high-speed camera was applied, whereas the specialized TEMA Automotive software was used to analyze the obtained movies. Application of the above-mentioned tools and the developed measuring procedure of the ring motion recording allowed to obtain reliable experimental data and calculation results of plastic flow stress of a copper ring with satisfactory accuracy.

The article describes an application for calibration of a stereovision camera setup constructed for the needs of an electronic travel aid for the blind. The application can be used to calibrate any stereovision system consisting of two DirectShow compatible cameras using a reference checkerboard of known dimensions. A method for experimental verification of the correctness of the calibration is also presented. The developed software is intended for calibration of mobile stereovision systems that focus mainly on obstacle detection.

While the Slope Fault Model method can solve the soft-fault diagnosis problem in linear analog circuit effectively, the challenging tolerance problem is still unsolved. In this paper, a proposed Normal Quotient Distribution approach was combined with the Slope Fault Model to handle the tolerances problem in soft-fault diagnosis for analog circuit. Firstly, the principle of the Slope Fault Model is presented, and the huge computation of traditional Slope Fault Characteristic set was reduced greatly by the elimination of superfluous features. Several typical tolerance handling methods on the ground of the Slope Fault Model were compared. Then, the approximating distribution function of the Slope Fault Characteristic was deduced and sufficient conditions were given to improve the approximation accuracy. The monotonous and continuous mapping between Normal Quotient Distribution and standard normal distribution was proved. Thus the estimation formulas about the ranges of the Slope Fault Characteristic were deduced. After that, a new test-nodes selection algorithm based on the reduced Slope Fault Characteristic ranges set was designed. Finally, two numerical experiments were done to illustrate the proposed approach and demonstrate its effectiveness.