A new methodology for determining the operating strategies for bio-chemical, wastewater treatment plants was proposed. The method is based on Monte Carlo (MC) simulations and the expected utility theory in order to deal with the analysis of choices among risky operating strategies with multi-dimensional outcomes. The motivation is given by a case study using an anaerobic digestion model (ADM) adapted for multiple co-substrates. It is shown how the multi-criteria analyses' computational complexity can be reduced within an approximation based on Gaussian-process regression and how a reliability map can be built for a bio-process model under uncertainty and multiplicity. In our uncertainty-analyses case study, the reliability map shows the probability of a biogas-production collapse for a given set of substrates mixture input loads. Results of this research were published in the most important journal (it has the highest impact factor) in the field of Water Resources.
COBISS.SI-ID: 26152231
In the paper we propose a novel approach to the diagnosis of gearboxes in presumably non-stationary and unknown operating conditions. The approach makes use of information indices based on Rényi entropy derived from coefficients of the wavelet packet transform of measured vibration records. These indices quantify some statistical properties of instantaneous power of the generated vibration that are largely unaffected by changes in the operating conditions. The analysis is based on probability density of the envelope of a sum of sinusoidal signals with random amplitude and phase. Such an approach requires no a priori information about the operating conditions and no prior data describing physical characteristics of the monitored drive. The fault detection capabilities of the proposed feature set are demonstrated on a two-stage gearbox operating under different rotational speeds and loads with various seeded mechanical faults.
COBISS.SI-ID: 25765159
Using gold plated electrodes, inserted into the rat’s head above the dura of the left and right parietal cortex, we recorded EEG during deep and shallow anesthesia with either pentobarbital (PB) or ketamine-xylazine (KX). Time series were then analyzed using wavelet transforms and the spectral power was determined within 7 frequency intervals (S1, S2, δ, θ, α, β in γ). We show specific changes for both anesthetics indicating that during deep anesthesia PB reduces high and low frequency activity (0.2–35 Hz) and enhances coupling, while KX reduces low frequency activity (0.005 to 0.2 Hz) and enhances coupling between frequency waves α, β and γ. Our results, using two anesthetics known to block different ion channels, provide an insight into brain dynamics and could have wide implications in creating biomarkers for detecting various neurophysiological modifications, such as in Alzheimer and Parkinson’s disease.
COBISS.SI-ID: 29971417
This study explores two issues in the transition from mp-MPC theory to the implementation of an industrial controller: offset-free output-feedback tracking, and controller tuning based on local linear analysis of the closed-loop system. It is shown that the disturbance-estimation based offset-free tracking schemes involving an observer/estimator, known from on-line MPC, are also applicable in mp-MPC. Further, that a "joint"-scheme, in which the MPC controller integrates the functions of constrained dynamic control and offset-free tracking without using a separate target calculator, may be efficiently used for control of small-scale multivariable processes with redundant control inputs. Such schemes facilitate tuning for efficient disturbance rejection and robustness using local linear analysis, which was found to be extremely valuable tuning tool. An experimental case study on a two-input single-output system for pressure control in the vacuum chamber of a wire annealer is presented.
COBISS.SI-ID: 25808423
In cooperation with the researchers of Technical University of Catalonia, Barcelona, Spain, we tested the knowledge discovery procedure that includes both prior expert knowledge and interpretation oriented tools to extract the behavior of a process. Special emphasis is made on the interest of developing postprocessing tools for clustering methods which can help expert to understand the meaning of the clusters and bridge the important existing gap between data mining and effective decision support. A proposal for automatic construction of traffic light panels is presented trying to mimic the real process that the analyst performs to manually build them. The proposed knowledge discovery procedure was applied on the data measured in Domžale-Kamnik WWTP.
COBISS.SI-ID: 25969191