In order to make the analog fault classification more accurate, we present a method based on the Support Vector Machines Classifier (SVC) with wavelet packet decomposition (WPD) as a preprocessor. In this paper, the conventional one-against-rest SVC is resorted to perform a multi-class classification task because this classifier is simple in terms of training and testing. However, this SVC needs all decision functions to classify the query sample. In our study, this classifier is improved to make the fault classification task more fast and efficient. Also, in order to reduce the size of the feature samples, the wavelet packet analysis is employed. In our investigations, the wavelet analysis can be used as a tool of feature extractor or noise filter and this preprocessor can improve the fault classification resolution of the analog circuits. Moreover, our investigation illustrates that the SVC can be applicable to the domain of analog fault classification and this novel classifier can be viewed as an alternative for the back-propagation (BP) neural network classifier.
Raman spectrometers are devices which enable fast and non-contact identification of examined chemicals. These devices utilize the Raman phenomenon to identify unknown and often illicit chemicals (e.g. drugs, explosives) without the necessity of their preparation. Now, Raman devices can be portable and therefore can be more widely used to improve security at public places. Unfortunately, Raman spectra measurements is a challenge due to noise and interferences present outside the laboratories. The design of a portable Raman spectrometer developed at the Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology is presented. The paper outlines sources of interferences present in Raman spectra measurements and signal processing techniques required to reduce their influence (e.g. background removal, spectra smoothing). Finally, the selected algorithms for automated chemicals classification are presented. The algorithms compare the measured Raman spectra with a reference spectra library to identify the sample. Detection efficiency of these algorithms is discussed and directions of further research are outlined.
In the paper a method for correction of heating non-homogeneity applied in defect detection with the use of active thermography is presented. In the method an approximation of thermal background with second- and third-order surfaces was used, what made it possible to remove partially the background. In the paper the simulation results obtained with the abovementioned method are presented. An analysis of the influence of correction of heating non-homogeneity on the effectiveness of defect detection is also carried out. The simulations are carried out for thermograms obtained on the basis of experiments on a test sample with simulated defects, made of a material of low thermal diffusivity.
Digital holography (DH) which is the technology of acquiring and processing measurement data via a CCD camera is spreading to industrial applications, finds wide employment in engineering problems of testing and investigation. In this paper, a simple digital holographic system, comprising a He-Ne laser source, CCD camera and analyzing software, is used for testing surface flatness and detecting the presence of a propagating crack on the surface plane and the effect of the crack on the neighborhood. Phase variations across the surfaces planes are extracted to represent the surface deviation from a reference plane. The analysis methods differ according to the interference fringes in the recorded holograms. Both fringe tracking and Fourier transform with phase unwrapping methods are used in the interpretation of interferometric fringe patterns.
The paper presents a spectral formulation of surface profile irregularity in a wideband frequency range for roughness, waviness and shape components along the measured length. A unique distribution of roughness and waviness components is proposed, according to the nature of their origination in the course of machining with tools of defined cutting edge, as distinct from standard filtration in measurements of surface irregularities. Differences resulting from both formulations are outlined as well as the method of determining the frequency of component separation for surface roughness and waviness.
The paper presents the results of investigation on a prototype sensor for measurement of benzaldehyde in air. Sensitivity and limit of quantification of the sensor were determined for different internal electrolytes using square wave voltammetry (SWV) as the detection technique. The working and counter electrodes were made of platinum. Ionic liquids 1-hexyl, 3-methylimidazolium chloride, 1-hexyl, 3-methylimidazolium bis (trifluoro-methanesulfonyl) imide and 1-butyl, 3-methylimidazolium tricyanomethan constituted the internal electrolyte. A polydimethylsiloxane (PDMS) membrane separated the gaseous medium from the electrolyte.
The paper contains an overview of ethical issues related to technoscience, followed by a more detailed presentation of ethical aspects of measurement-based experimentation, publishing peer-reviewing practices. The need for increased sensitivity of scientists to this kind of issues is justified by the evolution of research institutions in the postmodern era.
Local geometric deviations of free-form surfaces are determined as normal deviations of measurement points from the nominal surface. Different sources of errors in the manufacturing process result in deviations of different character, deterministic and random. The different nature of geometric deviations may be the basis for decomposing the random and deterministic components in order to compute deterministic geometric deviations and further to introduce corrections to the processing program. Local geometric deviations constitute a spatial process. The article suggests applying the methods of spatial statistics to research on geometric deviations of free-form surfaces in order to test the existence of spatial autocorrelation. Identifying spatial correlation of measurement data proves the existence of a systematic, repetitive processing error. In such a case, the spatial modelling methods may be applied to fitting a surface regression model representing the deterministic deviations. The first step in model diagnosing is to examine the model residuals for the probability distribution and then the existence of spatial autocorrelation.
Worldwide Interoperability for Microwave Access (WiMAX), based on the IEEE 802.16 standards, is a technology that offers low cost mobile broadband access to multimedia and internet applications for operators and end-users. Similarly to cellular phone or other Radio Frequency devices, WiMAX has to be considered as a possible source of electromagnetic pollution and so monitoring its emission could be necessary to verify compliance with the applicable emission limits. Generally, the monitoring of the electromagnetic pollution is performed by means of a suitable measurement chain constituted by an antenna connected to a traditional spectrum analyzer. The use of this kind of device to measure the power of digital modulated noise-like signals, such as WiMAX, requires to use proper measurement methods and to carefully set many instrument parameters to obtain reliable measurement results, otherwise a significant underestimate or overestimate of the human exposure can be obtained.
In this framework, this paper investigates the feasibility of using the traditional spectrum analyzer to perform the electromagnetic pollution measurements due to WiMAX devices. A large experimental campaign is carried out to identify the most proper measurement method and spectrum analyzer settings able to warrant reliable measurements.
The problem of management of memory in a signal processor has been discussed on the example of time parameters measurement system of transient signals. General rules of memory management and allocation in TMS320C6713 DSK have been described.
Telemedicine is one of the most innovative and promising applications of technology in contemporary medicine. Telemedical systems, a sort of distributed measurement systems, are used for continuous or periodic monitoring of human vital signals in the environment of living. This approach has several advantages in comparison to traditional medical care: e.g. patients experience fewer hospitalizations, emergency room visits, lost time from work, the costs of treatment are reduced, and the quality of life is improved. Currently, chronic respiratory diseases comprise one of the most serious public health problems. Simultaneously patients suffering from these diseases are well suitable for home monitoring. This paper describes the design and technical realization of a telemedical system that has been developed as a platform suitable for monitoring patients with chronic pulmonary diseases and fitted to Polish conditions. The paper focuses on the system's architecture, included medical tests, adopted hardware and software, and preliminary internal evaluation. The performed tests demonstrated good overall performance of the system. At present further work goes on to put it into practice.
Journal | Publisher | ISSN |
IOP Publishing | 0026-1394 | |
IEEE | 0018-9456 | |
Elsevier | 0263-2241 | |
IOP Publishing | 0957-0233 | |
Metrology and Measurement Systems | PAS | 0860-8229 |
IOP Publishing | 0034-6748 | |
IEEE | 1557-9948 | |
IET | 1751-8822 | |
SISSA, IOP Publishing | 1748-0221 | |
Walter de Gruyter | 1335-8871 | |
IEEE | 1094-6969 | |
Bulletin of the Polish Academy of Sciences: Technical Sciences | PAS | 2300-1917 |
PAS | 1896-3757 | |
IEEE | 1558-1748 | |
MDPI | 1424-8220 |