Wyniki wyszukiwania - BazTech

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A novelty detection approach to monitoring of epicyclic gearbox health

Dworakowski Z., Dziedziech K., Jabłoński A.

Metrology and Measurement Systems

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2018

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Vol. 25, nr 3

459--473

EN

Reliable monitoring for detection of damage in epicyclic gearboxes is a serious concern for all industries in which these gearboxes operate in a harsh environment and in variable operational conditions. In this paper, autonomous multidimensional novelty detection algorithms are used to estimate the gearbox’ health state based on vectors of features calculated from the vibration signal. The authors examine various feature vectors, various sources of data and many different damage scenarios in order to compare novel detection algorithms based on three different principles of operation: a distance in the feature space, a probability distribution, and an ANN (artificial neural network)-based model reconstruction approach. In order to compensate for non-deterministic results of training of neural networks, which may lead to different network performance, the ensemble technique is used to combine responses from several networks. The methods are tested in a series of practical experiments involving implanting a damage in industrial epicyclic gearboxes, and acquisition of data at variable speed conditions.

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An Approach to Damage Detection in the Aircraft Structure with the Use of Integrated Sensors – The Symost Project

Dragan K., Dziendzikowski M., Leski A., Dworakowski Z., Uhl T.

Fatigue of Aircraft Structures

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2012

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Iss. 4

10--16

EN

This paper presents an approach to damage growth monitoring and early damage detection in the structure of PZL – 130 ORLIK TC II turbo-prop military trainer aft using the statistical models elaborated by the Polish Air Force Institute of Technology (AFIT) and the network of the sensors attached to the structure. Drawing on the previous experiences of the AFIT and AGH in structural health monitoring, the present research will deploy an array of the PZT sensors in the structure of the PZL -130 Orlik TC II aircraft. The aircraft has just started Full Scale Fatigue Test (FSFT) that will continue up to 2013. The FSFT of the structure is necessary as a consequence of the structure modification and the change of the maintenance system - the transition to Condition Based Maintenance. In this paper, a novel approach to the monitoring of the aircraft hot-spots will be presented. Special attention will be paid to the preliminary results of the statistical models that provide an automated tool to infer about the presence of damage and its size. In particular, the effectiveness of the selected signal characteristics will be assessed using dimensional reduction methods (PCA) and the so-called averaged damage indices will be delivered. Moreover, the results of the signal classification based on the neural network will be presented alongside the numerical model of the wave propagation. The work contains selected information about the project scope and the results achieved at the preliminary stage of the project.

3

Vision data employed for crack detection and localization

Kohut P., Holak K., Dworakowski Z., Uhl T.

Diagnostyka

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2012

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nr 3(63)

35-41

EN

Nowadays, non-contact measurement systems have found application in the Structural Health Monitoring of civil engineering structures for the detection, localization and assessment of damage. In the field of static deflection measurement, the vision based techniques have become more popular. The deflection curve obtained by image processing and analysis methods can be analyzed in order to detect and localize the change of the curvature, which implies the appearance of a crack. In this paper, the vision based deflection measurement system is discussed. The deflection of beam-like structures is computed by means of digital image correlation. The damage detection and localization is based on the irregularity detection by means of analyzing the deflection curve. A new approach and some selected methods for damage detection and localization will be highlighted and their results obtained in the laboratory setup will be presented and discussed.