Venco Ćorluka

Analysis of some parameters influencing moisture quantity measurements in wheat with NIR technique

Water has an absorption band of four wavelengths, namely 1.2, 1.45, 1.94, and 2.94 micrometers, in the near-infrared light range. When a sample is irradiated with light of the above wavelengths, this sample will absorb light in accordance with its moisture content. As moisture content of wheat increased, reflectance from the wheat sample decreased, which indicates that water is a strong light absorber than a sandy wheat sample. When light hits a sample, several interactions can occur: specular reflectance, diffuse reflectance, absorption, transmittance, refraction and scattering. In this paper we try to find out influence of several interactions on accurate measurement for moisture wheat

Optimal Signal Conditioning in the NIR Moisture Meter

The infrared radiation measurement system in the moisture meter based on the cooled PbS photoconductive detector is designed by the authors and analysed in this paper. It consisted of a preamplifier and a mechanical chopper. The basic noise sources and their influence on this measuring system are studied out. One solution for the maximisation signal to noise ratio based on the theoretical and laboratory practical consideration has also been made. Under the circumstances, the possible accuracy of the mentioned system is founded out by the measurement. The final aim is to develop an optimal optoelectronical measuring system for the infrared moisture meter for practical use but with some specific substances firstly. The overall results can be kept in the numerous variety applications later

Output characteristics analysis of gensets for modeling of an expert system for fault detection purposes

In complex systems, such as military organizations, a large number of technical resources requiring regular maintenance is used. These resources are often exposed to difficult working conditions increasing the probability of a fault occurrence. Fault diagnosis as a part of the maintenance process is often a complex process, which is why expert systems for fault diagnosis are developed. One of the possible systems developed for fault diagnosis on gensets uses the Bayesian network to decide on a fault with the highest probability. For proper system operation, it is important to have a reliable “knowledge base” encompassing results of diagnostic tests. Apart from direct measurements, simulation results are also used in order to obtain diagnostic results. Fault simulations are performed on a model developed using the Matlab Simulink program package.