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Fault identification in underwater vehicle thrusters via sliding mode observers

100%

Zuev A. , Zhirabok A. , Filaretov V.

tom Vol. 30, no. 4

679--688

The paper is devoted to the problem of increasing the efficiency of underwater vehicles by using a fault diagnosis system for their thrusters which provides detection, isolation, and identification of minor faults. To address the problem, a two-stage method is proposed. At the first stage, a bank of diagnostic observers is designed to detect and isolate the emerging faults. Each observer in this bank is constructed to be sensitive to some set of faults and insensitive to others. At the second stage, additional observers working in sliding mode are synthesized in order to accurately estimate the error value in the signal obtained from the angular velocity sensor and to estimate deviations of the thruster parameters from their nominal values due to the faults. In contrast to the existing solutions, reduced-order (i.e., lower-dimensional) models of the original system are proposed as a basis to construct sliding mode observers. This approach permits reduction of the complexity of the obtained observers in comparison with the known methods, where full-order observers are constructed. The simulation results show the efficiency and high quality of all synthesized observers. In all cases considered, it was possible to detect typical faults, as well as estimate their values.

Zastosowanie sztucznych sieci neuronowych do identyfikacji uszkodzenia w belkach – badania numeryczne i doświadczalne

100%

Borowiec A. , Ziemiański L.

tom R. 109, z. 8-M

3--13

W pracy przedstawiono zastosowanie sztucznych sieci neuronowych (SSN) do identyfikacji uszkodzenia (położenie, wielkość) w belkach laboratoryjnych. Ocena uszkodzenia belek polega na analizie zmian częstotliwości rezonansowych wywołanych dodatkową zmieniającą położenie masą. Metoda nie wymaga znajomości parametrów modalnych belki nieuszkodzonej.

This paper presents the application of Artificial Neural Networks (ANN) in the identification of damage (location, extent) in simple laboratory beam structure. The assessment of the state of a beams relies on the comparison of the structure eigenfrequencies obtained from the systems with additional masses placed in different nodes without knowledge of the natural frequencies of undamaged structures.

Damage identification using 2-D discrete wavelet transform on extended operational mode shapes

84%

Makki Alamdar M. , Li J. , Samali B.

tom Vol. 15, no. 3

698--710

In this paper a new scheme of damage detection and localisation is presented by implementing frequency response functions (FRFs) of damaged structure only. First damage sensitive shape signals are generated by taking the second order derivatives of the operational mode shapes at each frequency coordinate and then the anti-symmetric extension of each shape signal at the beginning and at the end of the signal is created to avoid boundary distortion phenomenon. In order to highlight the damage influence on shape signals, the shape signals are normalised with respect to the maximum value to adjust the amplitude difference between shape signals at different frequencies. It is illustrated that normalisation of shape signals significantly improves the damage localisation results. After normalising the shape signals, a two-dimensional (2-D) map of all shape signals is created and then is analysed by employing 2-D discrete wavelet transform (DWT). By performing 2-D DWT, three sets of horizontal, vertical and diagonal detailed wavelet coefficients will be obtained. It is demonstrated that amongst these three sets, horizontal detail coefficients are the most sensitive ones to any perturbation in the shape signals due to damage occurrence and, thus, are utilised to localise damage in this study.