The paper presents experimental works related to contact nonlinearities. The research is focused on effects derived from hysteresis stiffness characteristics and vibro-impacts generated during the relative movement of two surfaces. The modeling of the contact nonlinearities was divided in two parts. First, the parameters of the system were identified based on modal analysis test. Next, the model was created and verified with experimental data. The experimental works were performed on steel samples with prepared contact surfaces. Electromagnetic shaker was used to produce relative motion between surfaces in contact. The response of the system was acquired by noncontact laser vibrometer. Both displacement and velocity of vibration were measured. Additionally, the impedance head measures the force and acceleration. The experimental data were used to validate the created models.
Condition monitoring is an indispensable element related to the operation of rotating machinery. In this article, the monitoring system for the parallel gearbox was proposed. The novelty detection approach is used to develop the condition assessment support system, which requires data collection for a healthy structure. The measured signals were processed to extract quantitative indicators sensitive to the type of damage occurring in this type of structure. The indicator’s values were used for the development of four different novelty detection algorithms. Presented novelty detection models operate on three principles: feature space distance, probability distribution, and input reconstruction. One of the distance-based models is adaptive, adjusting to new data flowing in the form of a stream. The authors test the developed algorithms on experimental and simulation data with a similar distribution, using the training set consisting mainly of samples generated by the simulator. Presented in the article results demonstrate the effectiveness of the trained models on both data sets.
The capabilities of ceramic PZT transducers, allowing for elastic wave excitation in a broad frequency spectrum, made them particularly suitable for the Structural Health Monitoring field. In this paper, the approach to detecting impact damage in composite structures based on harmonic excitation of PZT sensor in the so-called pitch–catch PZT network setup is studied. In particular, the repeatability of damage indication for similar configuration of two independent PZT networks is analyzed, and the possibility of damage indication for different localization of sensing paths between pairs of PZT sensors with respect to damage locations is investigated. The approach allowed for differentiation between paths sensitive to the transmission mode of elastic wave interaction and sensitive reflection mode. In addition, a new universal Bayesian approach to SHM data classification is provided in the paper. The defined Bayesian classifier is based on asymptotic properties of Maximum Likelihood estimators and Principal Component Analysis for orthogonal data transformation. Properties of the defined algorithm are compared to the standard nearest-neighbor classifier based on the acquired experimental data. It was shown in the paper that the proposed approach is characterized by lower false-positive indications in comparison with the nearest-neighbor algorithm.
This study is an experimental research on non-linear effects occurring in vibro-acoustic modulation tests. The work focuses on the analysis of the modulation type. The modulation of the response signal is due to interaction between low- and high-frequency excitation and damage surfaces, which results in the formation of higher harmonics and sidebands. The analysis of the sidebands is an extremely important issue. Their presence may indicate damage in structure. In many cases, the sidebands can be used to determine the damage index. However, not always, the distribution of the sidebands and their evaluation with excitation amplitude allow for an unambiguous interpretation. This may be the result of various damage-related non-linearity sources, which depend on the amplitude of the excitation. Because different types of non-linearities are manifested in different ways, the change in non-linearity type can cause, for example, the disappearance of odd sidebands and/or even harmonics or change in modulation type. To analyse the indicated issues, the sample with prepared contact surfaces was tested in experimental works. Two excitation types, low and high frequencies, are introduced into the structure via electromagnetic shaker and piezoelectric transducer, respectively, to produce contact-related non-linear effects. The contact surfaces are driven to move relative to each other. For a given scenario, the analysis of modulation sidebands is performed based on signal response. The instantaneous frequency approach is used to evaluate modulation type. The results show that the changes in the amplitude of the excitation change the modulation type of response signal. The probable causes of this phenomenon are given.
The paper presents work related to nonlinear system parameters identification. The research is focused on systems with hysteretic stiffness characteristics. The identification procedure is developed with use of artificial neural networks. The presented method assumes two separate clusters of neural networks, which are supported by additional signal processing block. Such approach gives an advantage over the conventional identification methods due to its small restrictions. The validation process considers structural responses in time and frequency domains as well as the restoring force plane of the dynamic structure. First, verification of the identification method is performed on the numerical simulation of the system with hysteretic stiffness. Next, the identification of the real dynamic system with contact-related nonlinearity is carried out. The steel samples with contacting surfaces were used in the experiment. Electromagnetic shaker was used to excite the structure and enforce a relative shear motion between surfaces in contact. The system response was recorded using the Polytec laser vibrometer.
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