Abstract

The paper is devoted to problem of analysis, identification and prediction of the presence of damages, which above a certain level may present a serious threat to the engineering (vibrating) structures such as different technical systems and devices, including nuclear reactors etc in result of the operational, environmental conditions, including the emergency accidents. For the first time we present and apply a novel computational approach to modelling, analysis (further prediction) of a chaotic behaviour of structural dynamic properties of the engineering structures, based on earlier developed chaos-geometric and vibration blind source monitoring approach. In the concrete realization the novel approach includes a combined group of blind source monitoring , non-linear analysis and chaos theory methods such as a correlation integral approach, average mutual information, surrogate data, false nearest neighbours algorithms, the Lyapunov’s exponents and Kolmogorov entropy analysis, nonlinear prediction models etc. As illustration we present the results of the numerical investigation of a chaotic elements in dynamical parameter time series for the experimental cantilever beam (the forcing and environmental conditions are imitated by the damaged structure, the variable temperature and availability of the pink-noise force). Using numerical time series analysis results, we list thedata on the topological and dynamical invariants, namely, the correlation, embedding, Kaplan-Yorke dimensions, the Lyapunov’s exponents and Kolmogorov entropy etc and consider a construction of the engineering structures (including nuclear reactors) damage detection prediction model. Under an influence of the operational, environmental conditions, including the emergency incidents (accidents) during the operation of the nuclear reactor vessel it is more than probable development (growth) of damages (defects) that existed initially, as well as the emergence of new defects and their further development (growth). In this case technical application of vibration diagnostics technologies and further analysis within the presented approach could be very useful together with available probabilistic models for assessing the safety of nuclear reactors.

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