Fiber-optic interferometric sensor for dynamic impact measurement of transport trucks

Ground vibrations are commonly observed by using a standard seismic station equipped with speed seismometers or acceleration seismometers. The seismometers include three mechanical vibrating systems (sensors) and the primary output is the wave pattern of recording velocity or acceleration of the material point oscillation. An alternative new method how it is possible to realize seismic measurements is using of the fiber-optic interferometric sensors. These interferometers are well-known for their ability to make high-precision measurements of optical path difference or changes that may be induced by a refractive index change in the interferometer or a physical displacement. The paper presents a comparison of the results of the standard seismic measurement by using seismic station and of the fiber-optic interferometric sensor. As a source of dynamic load, truck transport was chosen. When trucks passing through unevenness on the road (due to the road damage, the transition area of the bridge etc.), it generates vibrations that are transmitted to the subsoil and can adversely affect the surrounding building objects. Data comparison of the subsoil dynamic response obtained during both approaches of measurements is present in the amplitude and primary in the frequency domain.Web of Science42463

Design of a new method for detection of occupancy in the smart home using an FBG sensor

This article introduces a new way of using a fibre Bragg grating (FBG) sensor for detecting the presence and number of occupants in the monitored space in a smart home (SH). CO2 sensors are used to determine the CO2 concentration of the monitored rooms in an SH. CO2 sensors can also be used for occupancy recognition of the monitored spaces in SH. To determine the presence of occupants in the monitored rooms of the SH, the newly devised method of CO2 prediction, by means of an artificial neural network (ANN) with a scaled conjugate gradient (SCG) algorithm using measurements of typical operational technical quantities (indoor temperature, relative humidity indoor and CO2 concentration in the SH) is used. The goal of the experiments is to verify the possibility of using the FBG sensor in order to unambiguously detect the number of occupants in the selected room (R104) and, at the same time, to harness the newly proposed method of CO2 prediction with ANN SCG for recognition of the SH occupancy status and the SH spatial location (rooms R104, R203, and R204) of an occupant. The designed experiments will verify the possibility of using a minimum number of sensors for measuring the non-electric quantities of indoor temperature and indoor relative humidity and the possibility of monitoring the presence of occupants in the SH using CO2 prediction by means of the ANN SCG method with ANN learning for the data obtained from only one room (R203). The prediction accuracy exceeded 90% in certain experiments. The uniqueness and innovativeness of the described solution lie in the integrated multidisciplinary application of technological procedures (the BACnet technology control SH, FBG sensors) and mathematical methods (ANN prediction with SCG algorithm, the adaptive filtration with an LMS algorithm) employed for the recognition of number persons and occupancy recognition of selected monitored rooms of SH.Web of Science202art. no. 39

Effect of selected luminescent layers on CCT, CRI, and response times

Phosphors have been used as wavelength converters in illumination for many years. When it is excited with blue light, the frequently used yttrium aluminium garnet doped with cerium (YAG:Ce) phosphor converts a part of blue light to a wideband yellow light, resulting in the generated light having a white color. By combining an appropriate concentration of the YAG:Ce phosphor and blue excitant light, white light of a desired correlated color temperature (CCT) can be obtained. However, this type of illumination has a lower color rendering index value (CRI). In an attempt to improve the CRI value, we mixed the YAG:Ce phosphor with europium-doped calcium sulfide phosphor (CaS:Eu), which resulted in a considerably increased CRI value. This article examines an experiment with luminescent layers consisting of a mixture of selected phosphors and polydimethylsiloxane (PDMS). Different thicknesses in these layers were achieved by changing the speed of rotation during their accumulation onto laboratory glass using the method of spin coating. The spectral characteristics of these luminescent layers as they were excited with blue light emitting diode (LED) and laser diode (LD) were then determined. A suitable combination of the YAG:Ce phosphor with a phosphor containing europium, as it was excited with a blue LED, yielded a source of white light with a CRI value of greater than 85. The response time in the tested luminescent layers to a rectangular excitant impulse (generated by a signal generator and transmitted by LD) was also measured in order to examine their potential use in visible light communications (VLC).Web of Science1213art. no. 209

Fiber-optic breath sensors: A comparison study

The paper presents a comparative study of three fiber optic sensors based on the fiber Bragg grating (FBG). The basic monitored parameter is the respiratory rate of the human body. Fiber-optic sensors are immune to electromagnetic interference (EMI). This fact singles them out as ideal for use in magnetic resonance environments (typically in MRI -magnetic resonance imaging) as a prediction of hyperventilation states in patients. These patient conditions arise as a result of the closed tunnel environment in MR scanners. The results (10 volunteers with written consent) were compared with the results using the conventional respiratory belt (RB) in a laboratory environment and processed using the objective Bland-Altman (B-A) method.Web of Science40635

Methods of power line interference elimination in EMG signals

Electromyogram (EMG) recordings are often corrupted by the wide range of artifacts, which one of them is power line interference (PLI). The study focuses on some of the well-known signal processing approaches used to eliminate or attenuate PLI from EMG signal. The results are compared using signal-to-noise ratio (SNR), correlation coefficients and Bland-Altman analysis for each tested method: notch filter, adaptive noise canceller (ANC) and wavelet transform (WT). Thus, the power of the remaining noise and shape of the output signal are analysed. The results show that the ANC method gives the best output SNR and lowest shape distortion compared to the other methods.Web of Science40706

Encapsulation of FBG sensor into the PDMS and its effect on spectral and temperature characteristics

Fiber Bragg Grating (FBG) is the most distributed type of fiber-optic sensors. FBGs are primarily sensitive to the effects of temperature and deformation. By employing different transformation techniques, it is possible to use FBG to monitor any physical quantity. To use them as parts of sensor applications, it is essential to encapsulate FBGs to achieve their maximum protection against external effects and damage. Another reason to encapsulate is increasing of sensitivity to the measured quantity. Polydimethylsiloxane (PDMS) encapsulation appears to be an interesting alternative due to convenient temperature and flexibility of the elastomer. This article describes an experimental proposal of FBG PDMS encapsulation process, also providing an analysis of the FBG spectral characteristics and temperature sensitivity, both influenced by high temperature and the process of polydimethylsiloxane curing itself. As for the PDMS type, Sylgard 184 was employed. Encapsulation consisted of several steps: allocation of FBG to PDMS in its liquid state, curing PDMS at the temperature of 80°C ± 5 %, and a 50-minute relaxation necessary to stabilize a Bragg wavelength. A broadband light source and an optical spectrum analyzer were both used to monitor the parameters during the processes of curing and relaxation. Presented results imply that such a method of encapsulation does not have any influence on the structure or functionality of the FBG. At the same time, a fourfold increase of temperature sensitivity was monitored when compared to a bare FBG

On the FEM solution of a coupled contact—two-phase Stefan problem in thermo-elasticity. Coercive case

AbstractIn the paper a semi-implicit discretization in time of the weak formulation of the coupled signorini type contact—two-phase Stefan Problem is numerically analyzed. The problem leads to coupled elliptic variational inequalities, which are approximated by the FEM

The design of an indirect method for the human presence monitoring in the intelligent building

This article describes the design and verification of the indirect method of predicting the course of CO2 concentration (ppm) from the measured temperature variables Tindoor (degrees C) and the relative humidity rH(indoor) (%) and the temperature T-outdoor (degrees C) using the Artificial Neural Network (ANN) with the Bayesian Regulation Method (BRM) for monitoring the presence of people in the individual premises in the Intelligent Administrative Building (IAB) using the PI System SW Tool (PI-Plant Information enterprise information system). The CA (Correlation Analysis), the MSE (Root Mean Squared Error) and the DTW (Dynamic Time Warping) criteria were used to verify and classify the results obtained. Within the proposed method, the LMS adaptive filter algorithm was used to remove the noise of the resulting predicted course. In order to verify the method, two long-term experiments were performed, specifically from February 1 to February 28, 2015, from June 1 to June 28, 2015 and from February 8 to February 14, 2015. For the best results of the trained ANN BRM within the prediction of CO2, the correlation coefficient R for the proposed method was up to 92%. The verification of the proposed method confirmed the possibility to use the presence of people of the monitored IAB premises for monitoring. The designed indirect method of CO2 prediction has potential for reducing the investment and operating costs of the IAB in relation to the reduction of the number of implemented sensors in the IAB within the process of management of operational and technical functions in the IAB. The article also describes the design and implementation of the FEIVISUAL visualization application for mobile devices, which monitors the technological processes in the IAB. This application is optimized for Android devices and is platform independent. The application requires implementation of an application server that communicates with the data server and the application developed. The data of the application developed is obtained from the data storage of the PI System via a PI Web REST API (Application Programming Integration) client.Web of Science8art. no. 2

Analysis of the applicability of singlemode optical fibers for measurement of deformation with distributed systems BOTDR

Distributed optical fiber sensors allow monitoring physical effects across the whole cable. The paper presents results obtained from the performed tests and shows that single mode fibers can provide analyses of the deformation changes, when distributed optical systems BOTDR used. We used standard optical fiber G.652.D with primary and secondary protected layers and specialized cable SMC-V4 designed for this purpose. The aim was to compare the deformation sensitivity and determine which fiber types are the best to use. We deformed the fiber in the longitudinal and transverse directions and mechanically stressed in orthogonal directions to find how to localize optical fibers. They could be deployed in real use. For achieving optimal results of mechanical changes and acting forces, sensor fibers have to be located carefully

A weather forecast model accuracy analysis and ECMWF enhancement proposal by neural network

This paper presents a neural network approach for weather forecast improvement. Predicted parameters, such as air temperature or precipitation, play a crucial role not only in the transportation sector but they also influence people's everyday activities. Numerical weather models require real measured data for the correct forecast run. This data is obtained from automatic weather stations by intelligent sensors. Sensor data collection and its processing is a necessity for finding the optimal weather conditions estimation. The European Centre for Medium-Range Weather Forecasts (ECMWF) model serves as the main base for medium-range predictions among the European countries. This model is capable of providing forecast up to 10 days with horizontal resolution of 9 km. Although ECMWF is currently the global weather system with the highest horizontal resolution, this resolution is still two times worse than the one offered by limited area (regional) numeric models (e.g., ALADIN that is used in many European and north African countries). They use global forecasting model and sensor-based weather monitoring network as the input parameters (global atmospheric situation at regional model geographic boundaries, description of atmospheric condition in numerical form), and because the analysed area is much smaller (typically one country), computing power allows them to use even higher resolution for key meteorological parameters prediction. However, the forecast data obtained from regional models are available only for a specific country, and end-users cannot find them all in one place. Furthermore, not all members provide open access to these data. Since the ECMWF model is commercial, several web services offer it free of charge. Additionally, because this model delivers forecast prediction for the whole of Europe (and for the whole world, too), this attitude is more user-friendly and attractive for potential customers. Therefore, the proposed novel hybrid method based on machine learning is capable of increasing ECMWF forecast outputs accuracy to the same level as limited area models provide, and it can deliver a more accurate forecast in real-time.Web of Science1923art. no. 514