Metrology and Measurement Systems

The spin-lattice (T1) relaxation rates of materials depend on the strength of the external magnetic field in which the relaxation occurs. This T1 dispersion has been suggested to offer a means to discriminate between healthy and cancerous tissue by performing magnetic resonance imaging (MRI) at low magnetic fields. In prepolarized ultra-low-field (ULF) MRI, spin precession is detected in fields of the order of 10-100 μT. To increase the signal strength, the sample is first magnetized with a relatively strong polarizing field. Typically, the polarizing field is kept constant during the polarization period. However, in ULF MRI, the polarizing-field strength can be easily varied to produce a desired time course. This paper describes how a novel variation of the polarizing-field strength and duration can optimize the contrast between two types of tissue having different T1 relaxation dispersions. In addition, NMR experiments showing that the principle works in practice are presented. The described procedure may become a key component for a promising new approach of MRI at ultra-low fields

In this paper, some issues of building a reliable, distributed measurement system for monitoring of water quality in reservoir Lake Dobczyckie are presented. The system is based on a measurement station that has the shape of a floating buoy which is supposed to be at anchor on the reservoir. Wireless data transmission problems that were encountered during the development of the buoy, modeling a radio link, and measurements of actual signal strength on the reservoir are discussed. A mathematical approach to procedures of early situation assessment was conducted, and specialized procedures were designed for measurement stations of the system. It is also discussed how such computations can improve a qualitative assessment of system performance in terms of real-time messaging

The analysis of the autocorrelation function of a noise signal in a limited band of a microwave frequency range is described in the paper. On the basis of this analysis the static characteristic of the detector for object movement was found. The measurement results for the correlation function of noise signals are shown and the application of such solution in a noise radar for the precise determination of distance variations and the velocity of these changes is presented in the paper. The construction, working principle and measurement results for through-thewall noise radar demonstrator have been presented in the paper. A broadband noise signal in microwave S frequency band has been chosen, for high sensitivity getting. The broadband noise signal together with correlation receiver provides high sensitivity and moderate range for low transmitted power level. The experimental results obtained from 2.6-3.6 GHz noise-like waveform for the signal of a breathing human are presented. Conclusions and future plans for application of the presented detection technique in broadband noise radars conclude the paper

The wavelet transform has been successfully used in the area of power quality analysis. There are many published papers with methods for power quality disturbance classification or harmonics measurement, which use wavelet transform. However, the properties of the wavelet transform can drastically vary from the choice of the wavelet. In this paper we analyze the influence of the choice of the wavelet to the accuracy of the power quality classification method and to high frequency harmonics measurements. Additionally to the well known wavelet filters we introduce near perfect reconstruction filter banks. The simulation results indicate that these filter banks are a good choice for classification of power quality disturbances, especially in the presence of noise and for high frequency harmonics measurements

A measurement system for 256-channel in vitro recordings of brain tissue electrophysiological activity is presented in the paper. The system consists of the brain tissue life support system, Microelectrode Array (MEA), conditioning Application Specific Integrated Circuits (ASIC’s) for signals conditioning, Digitizer and PC application for measurement data presentation and storage. The life support system keeps brain tissue samples in appropriately saturated artificial cerebrospinal fluid at a very stable temperature. The MEA consists of two hundred and fifty-six 40 μm diameter tip-shaped electrodes. The ASIC’s performs amplification and filtering of the 256-field and action potential signals. The Digitizer performs simultaneous data acquisition from 256 channels 14 kS/s sample rate and 12-bit resolution. The resulting byte stream is transmitted to the PC via USB (Universal Serial Bus). Preliminary tests confirm that the system is capable of keeping the extracted brain tissue active (hippocampal formation slices) and simultaneously to record action potentials, as well as local theta field potentials with very small amplitudes from multiple neurons

Samples of CdTe single crystals which are used as radiation detectors were periodically measured during a long time interval with different values of an applied voltage. The samples were also periodically exposed during long time periods to high temperatures of 390 K and to rapid changes of temperature from 300 K to 390 K. After 1.5 years of measurements we observed ageing of the samples which resulted in deterioration of their transport characteristics. The resistance of the samples increased significantly and current-voltage characteristics were unstable in time. Noise spectroscopy showed that low frequency noise can be used for detection of CdTe sample ageing as its spectral density increases significantly comparing to the 1/f noise of a high quality sample

The paper presents the equalization problem of non-linear phase response of digital IIR type filters. An improved analytical method of designing a low-order equalizer is presented. The proposed approach is compared with the original method. The genetic algorithm is presented as an iterative method of optimization. The vector and matrix representation of the all-pass equalizer are shown and introduced to the algorithm. The results are compared with the analytical method. In this paper we have also proposed the use of an aging factor and setting the initial population of the genetic algorithm around the solution provided by the analytical methodology

The agglomeration of particles is a process that modifies the physical properties of a product originally manufactured as a powder. During milk powder agglomeration of fluidized bed, resulting agglomerates are sufficiently porous to improve the solubility of the final product but, at the same time, their rigidity decreases and agglomerates can be destroyed during packing. The porosity and rigidity properties depend on both the volume and shape characteristics of the agglomerates. This paper presents a three-dimensional reconstruction technique based on a laser displacement sensor (LDS) applied to characterize milk agglomerates. This technique allows three-dimensional scanning to estimate particle volume and extract shape parameters such as: sphericity, elongation and flatness ratio, shape factor and aspect ratio. This technique was implemented using a mechatronic device with two degrees of freedom. The device is composed of an angular positioning system to rotate the agglomerate and a linear positioning system to displace the LDS. Experimental result allows agglomerates classification according to shape parameters

Mobile devices have become an integral part of our life and provide dozens of useful services to their users. However, usability of mobile devices is hindered by battery lifetime. Energy conservation can extend battery lifetime, however, any energy management policy requires accurate prediction of energy consumption, which is impossible without reliable energy measurement and estimation methods and tools. We present an analysis of the energy measurement methodologies and describe the implementations of the internal (profiling) software (proprietary, custom) and external software-based (Java API, Sensor API, GSM AT) energy measurement methodologies. The methods are applied to measure energy consumption on a variety of mobile devices (laptop PC, PDA, smart phone). A case study of measuring energy consumption on a mobile computer using 3DMark06 benchmarking software is presented

The proper interaction of bone tissue - the natural porous biomaterial - with a porous coated intra-osseous implant is conditioned, among others, by the implant porous coating poroaccessibility for bone tissue adaptive ingrowth. The poroaccessibility is the ability of implant porous coating outer layer to accommodate the ingrowing bone tissue filling in its pore space and effective new formed bone mineralizing in the pores to form a biomechanically functional bone-implant fixation. The functional features of the microtopography of intra-osseous implant porous surfaces together with the porosity of pore space of the outer layer of the porous coating are called by bioengineers the porostructural-osteoconductive properties of the porous coated implant. The properties are crucial for successful adaptive bone tissue ingrowth and further long-term (secondary) biomechanical stability of the boneimplant interface. The poroaccessibility of intra-osseous implants porous coating outer layers is characterized by - the introduced in our previous papers - set of stereometric parameters of poroaccessibility: the effective volumetric porosity fVef, the index of the porous coating space capacity VPM, the representative surface porosity fSrep, the representative pore size pSrep, the representative angle of the poroaccessibility Wrep and the bone-implant interface adhesive surface enlargement index y. Presented in this paper, an original method of evaluation of the porostructural-osteoconductive properties of intra-osseous implant porous coatings outer layer by means of the parameters of poroaccessibility was preliminary verified during experimental tests performed on the representative examples of porous coated femoral stems and acetabular cups of various hip endoprostheses. The computer-aided stereometric evaluation of the microstructure of implant porous coatings outer layer can be now realized by the authoring application software PoroAccess_1.0 elaborated in our research team in Java programming language

Rapid development of computing and visualisation systems has resulted in an unprecedented capability to display, in real time, realistic computer-generated worlds. Advanced techniques, including three-dimensional (3D) projection, supplemented by multi-channel surround sound, create immersive environments whose applications range from entertainment to military to scientific. One of the most advanced virtual reality systems are CAVE-type systems, in which the user is surrounded by projection screens. Knowledge of the screen material scattering properties, which depend on projection geometry and wavelength, is mandatory for proper design of these systems. In this paper this problem is addressed by introducing a scattering distribution function, creating a dedicated measurement setup and investigating the properties of selected materials used for rear projection screens. Based on the obtained results it can be concluded that the choice of the screen material has substantial impact on the performance of the system

Enhanced Traffic Management System (ETMS) stores all the information gathered by the Federal Aviation Administration (FAA) from aircraft flying in the US airspace. The data stored from each flight includes the 4D trajectory (latitude, longitude, altitude and timestamp), radar data and flight plan information. Unfortunately, there is a data quality problem in the vertical channel and the altitude component of the trajectories contains some isolated samples in which a wrong value was stored. Overall, the data is generally accurate and it was found that only 0.3% of the altitude values were incorrect, however the impact of these erroneous data in some analyses could be important, motivating the development of a filtering procedure. The approach developed for filtering ETMS altitude data includes some specific algorithms for problems found in this particular dataset, and a novel filter to correct isolated bad samples (named Despeckle filter). As a result, all altitude errors were eliminated in 99.7% of the flights affected by noise, while preserving the original values of the samples without bad data. The algorithm presented in this paper attains better results than standard filters such as the median filter, and it could be applied to any signal affected by noise in the form of spikes

This paper presents a low-cost and smart measurement system to acquire and analyze mechanical motion parameters. The measurement system integrates several measuring nodes that include one or more triaxial accelerometers, a temperature sensor, a data acquisition unit and a wireless communication unit. Particular attention was dedicated to measurement system accuracy and compensation of measurement errors caused by power supply voltage variations, by temperature variations and by accelerometers’ misalignments. Mathematical relationships for error compensation were derived and software routines for measurement system configuration, data acquisition, data processing, and self-testing purposes were developed. The paper includes several simulation and experimental results obtained from an assembled prototype based on a crank-piston mechanism

This paper shows the result of work of the Institute of Micromechanics and Photonics at Warsaw University of Technology and the Length and Angle Division of Central Office of Measures (GUM) [1] in building an automatic multiwavelength interferometric system with extended measurement range for calibration of long (up to 1 m) gauge blocks. The design of a full working setup with environmental condition control and monitoring systems, as well as image analysis software, is presented. For length deviation determination the phase fraction approach is proposed and described. To confirm that the system is capable of calibrating gauge blocks with assumed accuracy, a comparison between the results of 300 mm length gauge block measurement obtained by using other systems from the Central Office of Measures is made. Statistical analysis proved that the system can be used for high precision measurements with assumed standard uncertainty (125 nm for a length of 1 m). Finally the comparison between our results obtained for a long gauge block set (600 mm to 1000 mm long) and previous calibrations made by the Physikalisch-Technische Bundesanstalt (PTB) [2] is shown

In the paper a method using active thermography and a neural algorithm for material defect characterization is presented. Experimental investigations are conducted with the stepped heating method, so-called time-resolved infrared radiometry, for the test specimen made of a material with low thermal diffusivity. The results of the experimental investigations were used in simulations of artificial neural networks. Simulations are performed for three datasets representing three stages of the heating process occurring in the investigated sample. In this work, the simulation research aimed to determine the accuracy of defect depth estimation with the use of the mentioned algorithm is descibed

Electrocatalytic gas sensors belong to the family of electrochemical solid state sensors. Their responses are acquired in the form of I-V plots as a result of application of cyclic voltammetry technique. In order to obtain information about the type of measured gas the multivariate data analysis and pattern classification techniques can be employed. However, there is a lack of information in literature about application of such techniques in case of standalone chemical sensors which are able to recognize more than one volatile compound. In this article we present the results of application of these techniques to the determination from a single electrocatalytic gas sensor of single concentrations of nitrogen dioxide, ammonia, sulfur dioxide and hydrogen sulfide. Two types of classifiers were evaluated, i.e. linear Partial Least Squares Discriminant Analysis (PLS-DA) and nonlinear Support Vector Machine (SVM). The efficiency of using PLS-DA and SVM methods are shown on both the raw voltammetric sensor responses and pre-processed responses using normalization and auto-scaling

Open-Path Fourier Transform Infrared OP-FTIR spectrometers are commonly used for the measurement of atmospheric pollutants and of gases in industrial processes. Spectral interpretation for the determination of gas concentrations is based on the HITRAN database line-by-line modeling method. This article describes algorithms used to model gas spectra and to determine gas concentration under variable temperatures. Integration of individual rotational lines has been used to reduce the impact of spectrometer functions on the comparison of both measured and synthetic modeled spectra. Carbon monoxide was used as an example. A new algorithm for gas concentration retrieval consisting of two ensemble methods is proposed. The first method uses an ensemble of local models based on linear and non-linear PLS (partial least square) regression algorithms, while the second is an ensemble of a calibration set built for different temperatures. It is possible to combine these methods to decrease the number of regression models in the first ensemble. These individual models are appropriate for specific measurement conditions specified by the ensemble of the calibration set. Model selection is based on comparison of gas spectra with values determined from each local model