Noise & Vibration Worldwide

In recent times, nonlinear ultrasonic inspection has become a very reliable technique to characterize micro-scale cracks and small-scale delaminations. In this paper, an analytical framework is developed for the orthotropic composite plate to calculate the variation of relative acoustic nonlinearity parameter, a quantitative measurement of nonlinearity at the delamination region. The analytical investigation is justified with numerical and experimental research using a carbon fiber-reinforced polymer (CFRP) plate with three delaminations. Two incident waves are used for excitation, out of which the first wave frequency is varied as local defect resonance (LDR) frequency (f_d), subharmonic LDR frequency (2f_d), second-order superharmonic LDR frequency (f_d/2), and third-order superharmonic LDR frequency (f_d/3) while the second incident wave is taken as a single periodic frequency. Different delamination sizes, positions, and depths were used to understand the second-order relative acoustic nonlinearity parameter (β₂) with other LDR frequencies as well as its harmonics. It has been observed from analytical, numerical, and experimental results that the relative acoustic nonlinearity parameter is maximum at LDR frequencies. It increases in case of surface level delaminations.

In rotating machinery, rolling elements are the key members of the rolling element bearing (REB), which has tremendous application in automobiles, aerospace, ships, machinery apparatuses, and many more industrial sectors. Bearings are a significant source of various non-linear parameters which strongly affect the whole system. In the last two decades, tremendous research and approaches have been developed, considering the different parameters and faultiness for the proper understanding of the system’s non-linear behavior. This research paper summarizes the literature review on bearing fault diagnosis with localized and distributed defects for rolling element bearings with various non-linear parameters. Artificially-generated defects on the bearing races provides the vibration analysis of the system. These factors like radial clearance, unbalanced force, preload, misalignment, etc. are also considered defects in bearings. Moreover, the literature highlights some significant gaps that should be examined for future research in the condition monitoring of the mechanism.

Tuned-mass-dampers are extensively used in physical systems in order to reduce the dynamic response of the primary structures. The damping in a tuned-mass-damper system plays a significant role. In many engineering systems, we see damping is hysteretic in nature. Tuned-mass systems with nonlinear hysteretic damping are mathematically challenging. In this paper, tuned mass systems with rate-independent hysteresis are studied. In particular, first we study tuned mass systems with the famous Bouc-Wen model, and then we study tuned mass systems with the Bouc-Wen model and a recently developed scalar hysteresis model in parallel. Numerical approaches are used to study the dynamic responses of the systems. The sine sweep responses show two resonance peaks. The sine sweep responses indicate the amplitude versus frequency of the systems. The numerical results obtained for two different hysteretic dampers are compared.

This paper aimed to examine the impact of the COVID-19 lockdown in Algeria on the soundscapes’ components throughout the cafe terraces in coastal cities. The methodology is based on a laboratory qualitative approach established and divided into two stages. And the monitoring of sound recordings through twenty-one cafe terraces inside the coastal city of Azzaba in Algeria was conducted before and after the lockdown of whole the country due to the COVID-19 pandemic. Using the McNemar’s test on the first stage, results suggest that the lockdown measures in Algeria affect the soundscape components of the cafe terraces, specifically the predominance of the anthrophonical sounds over the natural sound components. The predominance of traffic sounds on the soundscapes after the lockdown period does not reflect an increase in noise level, whereas the soundscapes through the cafe terraces during the two periods were similar, and showed as less noisy by the semantic difference analysis evaluation, of the second stage. The factors of the principal component analysis suggest that the soundscapes of the cafe terraces reflect the main patterns of the acoustics design in the public spaces, such as functions (relaxation and communication), space-time for the two factors of the soundscapes of the period before the lockdown, and by relaxation, space and time for the three factors of those of the period after lockdown. Otherwise, the Marginal Homogeneity Test shows that there are significant differences in the assessment of the soundscapes of the cafe terraces during the two periods, which were only associated to the functions. Findings suggest that additional long-term research is needed to preserve and improve the cultural soundscapes among the urban spaces to ensure the acoustic comfort of the occupants and preserve their health.

Vibration control and trajectory tracking for nonlinear aeroelastic system of 2D airfoil of wind turbine subjected to flap-wise vibration and independent pitch motion, are investigated based on hydraulic pitch control and adaptive iterative learning (AIL) control. The aeroelastic system is simplified by an external slubber, the host material of which is a composite material with shape memory alloy (SMA) wires embedded in. The independent pitch motion is driven by two-way-rack cylinder and hydraulic servo valve. The control of divergent unstable motions is implemented by tracking the vibrations of the preset displacements. The control law of AIL algorithm combines iterative algorithm and proportional-derivative (PD) control. The control parameters of PD controller are adjusted by proportional-derivative control based on single neuron (PDC/SN) algorithm. Based on the convergence analysis of the iterative algorithm, the tracking results (including position tracking and speed tracking) of the iterative process are shown, and the convergence of the absolute values of the relative errors during tracking is verified. The experiment based on process control and a refined OPC Technology verifies the feasibility of the engineering application of the proposed algorithm in nonlinear aeroelasticity. The consistency between the real-time dynamic tracking process shown on the experimental panel and the theoretical tracking process illustrated by simulation verifies the effectiveness of the control algorithm for engineering application. The research implication for the design of current turbine manufacturers is that it provides a design idea of blade buffer based on smart materials, and an implementation idea for the engineering application of adaptive AIL algorithm.

Over recent decades, ambiguous ground vibration induced by blasting operation can cause extensive damage to structures, lives and fields in and around mine premises. As a consequence, it is indispensable to measure the ambiguous ground vibration intensity levels for assessing and reduce their perilous impact. In this investigation, estimation and evaluation of blast-induced ground vibration in terms of peak particle velocity (PPV) through the ensemble machine learning intelligent algorithms were carried out. One hundred and 21 experimental and blasting events were monitored to collect the real-time field data in Mine-A, India. The collected data was randomly split into training and testing to generate models. Eight input parameters include number of holes, burden, spacing, hole diameter, hole depth, top stemming, maximum explosive charge per delay and the distance were selected for development of ensemble machine learning algorithms. An eXtreme gradient boosting (XGBoost) and random forest (RF) ensemble model, Decision Tree were developed to assess the PPV levels. In addition to that, four empirical predictor models proposed by the US Bureau of Mines, Langefors–Kihlstrom, Central Mining Research Institute, and Bureau of Indian Standards were applied to derive a relation between PPV and its influencing parameters. The accuracy and efficiency of developed models can be determined by performance evaluation metrics chosen as the coefficient of determination (R²), and root mean square error (RMSE). Among all models, yielded results evidence that the Decision Tree ensemble model with the R² of 0.9549, and RMSE of 0.0444 was more precise optimum model to assess the PPV. Besides, a sensitivity analysis method was applied in this current study to know the role of the input parameters in estimating PPV. The determined results inferred that burden, number of holes and top stemming are more influenced parameters on the intensity of PPV levels.