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Željko Đurović

University of Belgrade

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Branko Kovačević

University of Belgrade

Aleksandra Marjanović

University of Belgrade

Sanja Vujnović

University of Belgrade

Veljko Papić

University of Belgrade

Goran Kvaščev

University of Belgrade

Srđan T. Mitrović

National Library of Serbia

Predrag R. Tadić

University of Belgrade

Predrag Tadić

University of Belgrade

Sofija Spasojević

Roche (Canada)

Vera Petrović

Technical College of Applied Sciences

Cooperative Institutions

University of Belgrade

Technical College of Applied Sciences

Military Medical Academy

University of Defence

Institut Mihajlo Pupin

Carol I National Defence University

University of Novi Sad

Singidunum University

Sportska Akademija Beograd

Military Technical Institute

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An adaptive filter using neural networks approach

Željko Đurović Branko Kovačević

A new adaptive filter for system state estimation, based on a recurrent neural networks approach, has been proposed in the paper. A general procedure for defining the desired output signal dynamics in the training algorithm, based on the methodology of projecting an identity observer for deterministic dynamic systems, has been developed. An alternative approach for designing the desired output vector, based on a specific three-state track model with position only measurement and physical nature of the state vector components, has been also considered. Results of simulation demonstrating the robustness of the proposed filter, in the sense of its low sensitivity to the imprecise knowledge of noise statistics and the presence of unmodelled dynamics, are included.

Robustness

State vector

Observer (physics)

10.1109/melcon.1998.692476

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Citations (3)

Analysis of one class of neuro-fuzzy regulators

Željko Đurović Branko Kovačević Veljko Papić

The analysis of a class of neuro-fuzzy regulators, called ANFIS (adaptive neuro-fuzzy inherited systems), is presented in the paper. The overview of its structure and the training process is included. One example of nonlinear system is also used to illustrate the feasibility and the limits of this class of regulators.

10.1109/neurel.2002.1057975

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Citations (0)

Robust recursive time series modeling using ARX models with optimal exogenous inputs

Branko Kovačević Željko Đurović

A new method for estimating parameters of ARX time series models, based on the approximate maximum likelihood estimation, named M-estimation, has been considered. Making use of the optimal design of exogenous inputs, the rate of estimates convergence is improved significantly. The convergence of the proposed algorithms is established theoretically using the ordinary differential equation approach. The feasibility of the approach is demonstrated with simulations.

10.1109/icdsp.1997.628511

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Citations (2)

One Realization of an Industrial Device for Machine State Estimation

U. Rakonjac P. Jandric Sanja Vujnović Aleksandra Marjanović Goran Kvaščev

Performing maintenance checks and state detection of machines with rotary actuators in industry is a challenging task which requires expensive and complicated equipment. One of the ways to perform this is using a system based on recording and analysis of sounds the machine makes during operation. This paper describes an approach which uses a simple, compact device based on a commercial microcomputer that aims to entirely replace the state detection system. It is able to record acoustic signals in close proximity to the machine, process them and use a neural network to output the state of the rotary actuator. The testing has been done on real acoustic signals recorded in the thermal power plant Kostolac in Serbia.

Realization (probability)

Micro computer

10.1109/it51528.2021.9390133

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Adaboost algorithm in the frame of predictive maintenance tasks

Predrag Vasilic Sanja Vujnović Nikola Popović Aleksandra Marjanović Željko Đurović

The paper proposes a method for state change detection in rotary machines. The procedure relies on recorded signals spectrogram analysis and features appropriate for texture classification in digital images. Final classification in terms of machine health is performed using Adaboost algorithm. The application of this algorithm is proposed for thermal power plant fan mills whose impact plates are damaged during the coal grinding process. The main goal of the procedure is to detect the amount of wear of the impellers and to determine the appropriate timing for unnecessary maintenance tasks. Real acoustic signals for verification of this algorithm are recorded in thermal power plant Kostolac A1 in a coal grinding subsystem.

AdaBoost

Spectrogram

10.1109/spit.2018.8350846

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Citations (8)

A new approach to Doppler filter adaptation in radar systems

Veljko Papić Željko Đurović Goran Kvaščev Predrag R. Tadić

This paper presents one way to adaptation of Doppler radar filters. Doppler filters use window function in order to estimate the target velocity. The window function length can be adapted depending on estimated target acceleration and estimated signal to noise ratio in the system. Kalman filter is used for estimation of target acceleration. Signal to noise ratio is estimated using a procedure based on parametric methods of spectral analysis. A new adaptive Doppler-Kalman structure has been presented and efficiency of approach to target velocity estimation is proven by computer simulations.

SIGNAL (programming language)

10.1109/telfor.2011.6143644

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Citations (1)

Environmental Impacts On HydroPower Solution Selection

Proceedings of the ... IEEE International Symposium on Electronics and the Environment (2006)

Svetlana Stevović Željko Đurović

Application of modern techniques of synthetic intelligence is also possible in the fields of the environment and sustainable development. This paper is dealing with the modern methods of synthetic intelligence, where the fuzzy expert system is developed and applied in the decision making process

10.1109/isee.2006.1650095

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Citations (1)

Surface crack detection using image processing and support vector machine

Natalija Đorđević Nenad Džamić Željko Đurović

Surface crack detection has proven crucial in the process of inspecting civil engineering structures, as well as in many manufacturing industries that require high-quality products. A large number of methods that deal with this problem are based on computer vision, due to its effectiveness and affordability. In this paper, we present an end-to-end solution that uses the Canny edge detector combined with the Hough transform for feature extraction. With an aim to keep the process intuitive and have fast training and inference, we used SVM (support vector machine) for classification.

Canny edge detector

Hough Transform

Relevance vector machine

10.1109/icetran59631.2023.10192203

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QQ-plot approach to robust Kalman filtering

International Journal of Control (1995)

Željko Đurović Branko Kovačević

Noise distribution arising in certain applications frequently deviates from the assumed gaussian model, often being characterized by heavier tails generating the outliers. Since, in the presence of outliers, the performance of a Kalman filter can be very poor, a statistical approach-named QQ-plot—is suggested to make the Kalman filter more robust. In addition, the first and the second-order moments of noise processes are estimated simultaneously with the system states, using the QQ-plot of the noise samples generated in the 'robustified' Kalman filter algorithm. Results of simulation demonstrating the robustness of the proposed state estimators are also included.

Robustness

10.1080/00207179508921934

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Citations (22)

Comparative Analysis of Different Control Strategies for Electro-hydraulic Servo Systems

Zenodo (CERN European Organization for Nuclear Research) (2009)

Ismail Algelli Sassi Ehtiwesh Željko Đurović

Servomechanism

10.5281/zenodo.1073621

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Citations (6)