Możliwości oraz obszar zastosowań małogabarytowego spektrometru DLP NIRScan Nano do błyskawicznych pomiarów spektralnych

Zmodyfikowana wersja minispektrometru typu DPL NIR Scan została testowo zastosowana w laboratoriach oraz w warunkach mobilnych do analizy różnych materiałów. Jako testowa została wybrana seria obiektów badawczych w postaci głównie obiektów organicznych. Metoda pomiarowa i zastosowane urządzenie z powodzeniem może być zastosowane również do badania różnorodnych cienkowarstwowych materiałów półprzewodnikowych, ze względu na zakres pomiarowy. Badania wstępne już wykonane na innych obiektach, w tym z grupy materiałów stosowanych w elektronice, m.in. filmów półprzewodnikowych i nanokompozytowych, rokuje perspektywistyczność poszerzenia grupy obiektów pomiarowych też i na materiały z tej grupy. Za pomocą urządzenia można tworzyć bazy danych pomiarowych, które później mogą być wykorzystywane do diagnostyki badanych obiektów, w tym zmian w dziedzinie czasu lub na etapach obróbki technologicznej.A modified version of the DPL NIR Scan type mini-spectrometer was tested in laboratories and in mobile conditions for the analysis of various materials. A series of research objects in the form of mainly organic objects was chosen as the testing probes. The measuring method and the device used can also be successfully used for testing various thin-film semiconductor materials, due to the measuring range. Preliminary tests already performed on other objects, including from the group of materials used in electronics, among others semiconductor and nanocomposite films, promising the prospect of expanding the group of measurement objects also for materials from this group. Using the device, it is possible to create measurement databases that can later be used to diagnose the examined objects, including changes in the time domain or at the stages of technological processing

Application of Artificial Neural Networks in Analysis of Time-Variable Optical Reflectance Spectra in Digital Light Projection Spectroscopy

This article undertakes the subject matter of applying artificial neural networks to analyze optical reflectance spectra of objects exhibiting a change of optical properties in the domain of time. A compact Digital Light Projection NIRscan Nano Evaluation Module spectrometer was used to record spectra. Due to the miniature spectrometer’s size and its simplicity of measurement, it can be used to conduct tests outside of a laboratory. A series of plant-derived objects were used as test subjects with rapidly changing optical properties in the presented research cycle. The application of artificial neural networks made it possible to determine the aging time of plants with a relatively low mean squared error, reaching 0.56 h for the Levenberg–Marquardt backpropagation training method. The results of the other ten training methods for artificial neural networks have been included in the paper

Monitoring Time-Non-Stable Surfaces Using Mobile NIR DLP Spectroscopy

In recent years, Near Infrared (NIR) spectroscopy has increased in popularity and usage for different purposes, including the detection of particular substances, evaluation of food quality, etc. Usually, mobile handheld NIR spectroscopy devices are used on the surfaces of different materials, very often organic ones. The features of these materials change as they age, leading to changes in their spectra. The ageing process often occurs only slowly, i.e., corresponding reflection spectra can be analyzed each hour or at an even longer interval. This paper undertakes the problem of analyzing surfaces of non-stable, rapidly changing materials such as waxes or adhesive materials. To obtain their characteristic spectra, NIR spectroscopy using a Digital Light Projection (DLP) spectrometer was used. Based on earlier experiences and the current state of the art, Artificial Neural Networks (ANNs) were used to process spectral sequences to proceed with an enormous value of spectra gathered during measurements

Monitoring Time-Non-Stable Surfaces Using Mobile NIR DLP Spectroscopy

In recent years, Near Infrared (NIR) spectroscopy has increased in popularity and usage for different purposes, including the detection of particular substances, evaluation of food quality, etc. Usually, mobile handheld NIR spectroscopy devices are used on the surfaces of different materials, very often organic ones. The features of these materials change as they age, leading to changes in their spectra. The ageing process often occurs only slowly, i.e., corresponding reflection spectra can be analyzed each hour or at an even longer interval. This paper undertakes the problem of analyzing surfaces of non-stable, rapidly changing materials such as waxes or adhesive materials. To obtain their characteristic spectra, NIR spectroscopy using a Digital Light Projection (DLP) spectrometer was used. Based on earlier experiences and the current state of the art, Artificial Neural Networks (ANNs) were used to process spectral sequences to proceed with an enormous value of spectra gathered during measurements

Diagnostics on the Basis of the Frequency-Temperature Dependences of the Loss Angle Tangent of Heavily Moistured Oil-Impregnated Pressboard

The aim of this study was to perform precision measurements of the frequency-temperature dependences of the loss angle tangent of the liquid-solid composite with the FDS Dirana meter. The composite consisted of heavily moistered oil-impregnated pressboard. The moisturization of the pressboard occurred in a manner as close as possible to the process of wetting the insulation in power transformers to a moisture content of (5.0 ± 0.2) wt. %. This value of moisture content was chosen because exceeding this value can lead to transformer failure. The measuring temperature range was from 293.15 K (20 °C) to 333.15 K (60 °C), with a step of 8 K. The measuring frequency range was 0.0001 Hz to 5000 Hz. It was observed that the shape of the frequency dependence of the loss angle tangent for a moisture content of 5.0 wt. % does not depend on the value of the measuring temperature. An increase in temperature leads to a shift of the waveforms into the higher frequency region. This is associated with a decrease in the relaxation time, and its value depends on the activation energy. It was found that a good fit of the waveforms, simulated by Dirana, to the actual tgδ waveforms obtained at temperatures between 293.15 K (20 °C) and 333.15 K (60 °C) requires the introduction of temperatures, higher than the actual insulation temperatures, into the program. It was found that estimating the moisture content for different temperatures using Dirana soft-ware for insulating an oil-impregnated pressboard produced large discrepancies from the actual content. Better results were obtained after an adjustment requiring manual temperature correction towards higher, compared to measured, temperatures. The moisture content estimated after correction by the Dirana meter ranges from of 4.5 wt. % to 5.7 wt. % and increases almost linearly with increasing measuring temperature. The average moisture content estimated by the Dirana meter for all measuring temperatures is 5.1 wt. % and is close to the actual content (5.0 ± 0.2) wt. %. The uncertainty of the estimate is ±0.43 wt. % and is more than twice as high as the true value

Diagnostics on the Basis of the Frequency-Temperature Dependences of the Loss Angle Tangent of Heavily Moistured Oil-Impregnated Pressboard

The aim of this study was to perform precision measurements of the frequency-temperature dependences of the loss angle tangent of the liquid-solid composite with the FDS Dirana meter. The composite consisted of heavily moistered oil-impregnated pressboard. The moisturization of the pressboard occurred in a manner as close as possible to the process of wetting the insulation in power transformers to a moisture content of (5.0 ± 0.2) wt. %. This value of moisture content was chosen because exceeding this value can lead to transformer failure. The measuring temperature range was from 293.15 K (20 °C) to 333.15 K (60 °C), with a step of 8 K. The measuring frequency range was 0.0001 Hz to 5000 Hz. It was observed that the shape of the frequency dependence of the loss angle tangent for a moisture content of 5.0 wt. % does not depend on the value of the measuring temperature. An increase in temperature leads to a shift of the waveforms into the higher frequency region. This is associated with a decrease in the relaxation time, and its value depends on the activation energy. It was found that a good fit of the waveforms, simulated by Dirana, to the actual tgδ waveforms obtained at temperatures between 293.15 K (20 °C) and 333.15 K (60 °C) requires the introduction of temperatures, higher than the actual insulation temperatures, into the program. It was found that estimating the moisture content for different temperatures using Dirana soft-ware for insulating an oil-impregnated pressboard produced large discrepancies from the actual content. Better results were obtained after an adjustment requiring manual temperature correction towards higher, compared to measured, temperatures. The moisture content estimated after correction by the Dirana meter ranges from of 4.5 wt. % to 5.7 wt. % and increases almost linearly with increasing measuring temperature. The average moisture content estimated by the Dirana meter for all measuring temperatures is 5.1 wt. % and is close to the actual content (5.0 ± 0.2) wt. %. The uncertainty of the estimate is ±0.43 wt. % and is more than twice as high as the true value

Cooperation in the Area of Improving Education in Energy Efficiency – the TEMPUS Project “ENERGY”

Many of EU and non-EU States of Europe do not have sufficient amount of their own energy resources. Therefore, they are interested in more effective usage of thermal and electrical energy in order to lower costs for the purchased gas and oil products. Acquisition of energy saving technologies, including renewable sources of energy, is a prerequisite for achieving this goal

Analysis of Perovskite Solar Cell Degradation over Time Using NIR Spectroscopy—A Novel Approach

In recent years, there has been a dynamic development of photovoltaic materials based on perovskite structures. Solar cells based on perovskite materials are characterised by a relatively high price/performance ratio. Achieving stability at elevated temperatures has remained one of the greatest challenges in the perovskite solar cell research community. However, significant progress in this field has been made by utilising different compositional engineering routes for the fabrication of perovskite semiconductors such as triple cation-based perovskite structures. In this work, a new approach for the rapid analysis of the changes occurring in time in perovskite structures was developed. We implemented a quick and inexpensive method of estimating the ageing of perovskite structures based on an express diagnosis of light reflection in the near-infrared region. The possibility of using optical reflectance in the NIR range (900–1700 nm) to observe the ageing of perovskite structures over time was investigated, and changes in optical reflectance spectra of original perovskite solar cell structures during one month after PSC production were monitored. The ratio of characteristic pikes in the reflection spectra was determined, and statistical analysis by the two-dimensional correlation spectroscopy (2D-COS) method was performed. This method allowed correctly detecting critical points in thermal ageing over time