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Faults detection in gas turbine using hybrid adaptive network based fuzzy inference systems

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Hadroug N. , Hafaifa A. , Kouzou A. , Chaibet A.

tom Vol. 17, No. 4

3--17

The main aim of the present paper is the implementation of a fault detection strategy to ensure the fault detection in a gas turbine which is presenting a complex system. This strategy is based on an adaptive hybrid neuro fuzzy inference technique which combines the advantages of both techniques of neuron networks and fuzzy logic, where, the objective is to maintain the desired performance of the studied gas turbine system in the presence of faults. On the other side, the representation of fuzzy knowledge in the learning neural networks has to be accurate to provide significant improvements for modeling of the studied system dynamic behavior. The results presented in this paper proves clearly that the proposed detection technique allows the perfect detection of the studied gas turbine malfunctions, furthermore it shows that the use of the proposed technique based on the Adaptive Neuro-Fuzzy Interference System (ANFIS) approach which uses the adaptive learning mechanism of neuron networks and fuzzy inference techniques, can be a promising technique to be applied in several industrial application for faults detection.

Dynamic analysis of three-mass vibratory system with twin crank-slider excitation mechanism

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Korendiy V. , Gursky V. , Krot P. , Kachur O.

tom Vol. 34, nr 2

art. no. 2023226

The paper studies the dynamic behavior of the vibratory sieving conveyor equipped with the twin crank-slider excitation mechanism. The main purpose of this research consists in substantiating the possibilities of implementing the improved drive for providing the controllable vibration parameters of the working member (conveying tray, sieve, etc.) in accordance with the specific technological requirements set for different materials to be sieved and conveyed. In order to reach the goal set above, the following objectives are established: analyzing the design peculiarities of the vibratory sieving conveyor; deriving the mathematical model describing the conveyor’s oscillatory system dynamic behavior; studying the system kinematic, dynamic, and power characteristics. The system motion is described using the Lagrange-d’Alembert principle, and the numerical modeling is carried out in the Mathematica software with the help of the Runge-Kutta methods. The influence of the vibratory system's geometrical parameters on the motion conditions of the conveyor’s working member (conveying tray and sieve) is analyzed.