This paper presents a portable exhaled breath analyser, developed to detect selected diseases. The set-up employs resistive gas sensors: commercial MEMS sensors and prototype gas sensors made of WO3 gas sensing layers doped with various metal ingredients. The set-up can modulate the gas sensors by applying UV light to induce physical changes of the gas sensing layers. The sensors are placed in a tiny gas chamber of a volume of about 22 ml. Breath samples can be either injected or blown into the gas chamber when an additional pump is used to select the last breath phase. DC resistance and resistance fluctuations of selected sensors using separate channels are recorded by an external data acquisition board. Low-noise amplifiers with a selected gain were used together with a necessary bias circuit. The set-up monitors other atmospheric parameters interacting with the responses of resistive gas sensors (humidity, temperature, atmospheric pressure). The recorded data may be further analysed to determine optimal detection methods.
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.
Varistors are commonly used elements which protect power supply networks against high-voltage surges or lightning. Therefore, quality and endurance of these elements is important to avoid losses when an expensive laboratory equipment would not be protected from random overvoltages. Additionally, excessive leakage currents generate serious costs due to high energy consumption. The paper presents shortly properties of varistors that comprized different ZnO grain types and can have various quality which changes continuously during exploitation (due to exposition to overheating and overvoltage pulses). Therefore, it is important to monitor varistors during their ageing (causing changes within their microstructures). A few methods of varistor property diagnosis were considered and compared with the methods currently applied in laboratory or industry applications. A new measurement (diagnostic) system that can monitor varistors during ageing and can be widely applied in power networks is presented. The proposed system fulfills requirements of the industrial customers which demand various methods for power line protection. The proposed system can be simply developed into a more advanced wireless diagnostic system of long power supply lines.
This paper analyses the effectiveness of determining gas concentrations by using a prototype WO3 resistive gas sensor together with fluctuation enhanced sensing. We have earlier demonstrated that this method can determine the composition of a gas mixture by using only a single sensor. In the present study, we apply Least-Squares Support-Vector-Machine-based (LS-SVM-based) nonlinear regression to determine the gas concentration of each constituent in a mixture. We confirmed that the accuracy of the estimated gas concentration could be significantly improved by applying temperature change and ultraviolet irradiation of the WO3 layer. Fluctuation-enhanced sensing allowed us to predict the concentration of both component gases.
Sensing technology has been developed for detection of gases in some environmental, industrial, medical, and scientific applications. The main tasks of these works is to enhance performance of gas sensors taking into account their different applicability and scenarios of operation. This paper presents the descriptions, comparison and recent progress in some existing gas sensing technologies. Detailed introduction to optical sensing methods is presented. In a general way, other kinds of various sensors, such as catalytic, thermal conductivity, electrochemical, semiconductor and surface acoustic wave ones, are also presented. Furthermore, this paper focuses on performance of the optical method in detecting biomarkers in the exhaled air. There are discussed some examination results of the constructed devices. The devices operated on the basis of enhanced cavity and wavelength modulation spectroscopies. The experimental data used for analyzing applicability of these different sensing technologies in medical screening. Several suggestions related to future development are also discussed.