Showing papers in "Applied Acoustics in 2022"

TL;DR: In this paper , a feature extraction method of ship-radiated noise signal (S-NS) based on variational mode decomposition (VMD) and slope entropy (SloE) is proposed.

TL;DR: In this paper , a convolutional neural network (CNN) model optimized by particle swarm optimization (PSO) algorithm is constructed based on the standard LeNet, which is applied to identify five common states of a hydraulic piston pump using an acoustic signal.

TL;DR: In this article , a new membrane-type acoustic metamaterial was developed using a recycled cork membrane and fixing to this membrane masses obtained by reusing thumbtacks and buttons.

TL;DR: In this paper , the spatial and temporal distribution characteristics of noise complaints in urban blocks were analyzed to explore the relationship between noise complaint behaviours and The Point of Interest (POI) distribution.

TL;DR: In this article, an intelligent feature selection and classification method for fault diagnosis of WGs under different working conditions was introduced. But the novelty of the study lies in the selection of feature sources and different loading and speed conditions for condition monitoring studies of WG experimentally.

TL;DR: In this article , an intelligent feature selection and classification method for fault diagnosis of WGs under different working conditions was introduced. But the novelty of the study lies in the selection of feature sources and different loading and speed conditions for condition monitoring studies of WG experimentally.

TL;DR: In this paper, the authors investigated the impact of acoustical, building, urban and person-related factors on soundscape dimensions and well-being, and found that perceived dominance of neighbours' noises during relaxation, moderated by noise sensitivity, and the number of people at home were common factors negatively affecting both comfort and wellbeing.

TL;DR: In this paper , the damage characteristics of Carbon Fiber Reinforced Polymer (CFRP) composites, adhesively bonded in a Single Lap Shear (SLS) configuration, are analyzed using Acoustic Emission (AE) data recorded during the test.

TL;DR: In this paper, the damage characteristics are analyzed using Acoustic emission (AE) data recorded during the test, and the most suitable features are selected using a methodology developed based on the Laplacian scores for feature selection.

TL;DR: In this paper , the authors demonstrate the potency of discrete wavelet analysis for fault diagnosis of the planetary gearbox using Artificial Neural Network and Support Vector Machine (SVM) classifiers.

TL;DR: In this article , the authors conducted an online survey with 464 home workers in London during the COVID-19 lockdown to assess the perceived affective quality of indoor soundscapes.

TL;DR: Wang et al. as mentioned in this paper developed a method called Bi-directional deep belief network (Bi-DBN) for fault diagnosis of rolling bearings, which can learn the fault features from the original vibration signals first, and then the reverse generation part synthesizes samples according to the weight sharing by the forward training part.

TL;DR: In this article , a novel approach for identifying impeller defects in the centrifugal pump has been demonstrated by extracting the single-valued neutrosophic cross-entropy (SVNCE) of adaptive chirp mode decomposition (ACMD).

TL;DR: An adaptive channel estimation method based on the improved proportionate normalized least mean squares (IPNLMS) algorithm to reduce the complexity of channel estimation for the OTFS UWA communications system is proposed.

TL;DR: In this article, the authors studied the problem of a muffler with internal extended inlet/outlet tubes with the aim to optimize its geometric design, and proposed an isogeometric BM (IGA-BM) model to solve the muffler problem as an interior 3D Helmholtz acoustic problem.

TL;DR: In this article, a flexible micro-perforated material was fabricated for acoustic application in this study, which is different from the traditional perforated materials whose general impression is rigid, dense and inflexible.

TL;DR: In this article, a membrane-type acoustic metamaterials array with compact magnets (MAMMs array) for acoustic insulation is proposed, where each cell is realized by placing a membrane with a centered magnet in a magnetic field.

TL;DR: In this paper , a membrane-type acoustic metamaterials array with compact magnets (MAMMs array) for acoustic insulation is proposed, where each cell is realized by placing a membrane with a centered magnet in a magnetic field.

TL;DR: Li et al. as discussed by the authors proposed an intelligent fault diagnosis method based on grayscale image (GI) of the vibration signal, a self-supervised learning (SSL) method called deep InfoMax (DIM) and a convolutional neural network (CNN).

TL;DR: The experimental results indicate that, GTSL features can provide objective evaluation of voice diseases with low computational complexity and database dependency.

TL;DR: In this article , the authors proposed a method to optimize the automatic calibration of filters for ultrasound systems to achieve essential performance metrics of signal and image data, which can be used in the development, production, and commercialization of ultrasound systems.

TL;DR: In this article , an approach based on a combined technique of the forward translation, synthesis, back translation, pre-test and a committee approach was selected to maintain content equivalence between source and target languages.

TL;DR: In this article , the authors studied the problem of a muffler with internal extended inlet/outlet tubes with the aim to optimize its geometric design, and proposed an isogeometric BM (IGA-BM) model to solve the muffler problem as an interior 3D Helmholtz acoustic problem.

TL;DR: In this article , an optimization method based on statistical features is proposed to find the optimum sensor placement (OSP) for a wind turbine gearbox considering multi-component faults and an integrated condition monitoring scheme.

TL;DR: In this paper , the authors used a guarded hot plate to measure the absorption coefficient and thermal conductivity of date palm, reed, esparto, olive tree, fig tree, wood sawdust, chicken feathers, and sheep wool.

TL;DR: In this article, an optimization method based on statistical features is proposed to find the optimum sensor placement (OSP) for a wind turbine gearbox considering multi-component faults and an integrated condition monitoring scheme.

TL;DR: In this paper , a rolling bearing fault diagnosis model based on online transfer convolutional neural network (OTCNN) is proposed, which can reduce the training time by half while ensuring the accuracy of it.

TL;DR: In this article, the authors used a guarded hot plate and impedance tube to measure the absorption coefficient and thermal conductivity of date palm, reed, esparto, petiole, chicken feathers, and sheep wool.

TL;DR: Wang et al. as mentioned in this paper proposed an underwater acoustic target multi-attribute correlation perception method based on deep learning, where a group of neurons with learnable wights are designed to extract correlation deep features, which could model the correlation among multiple attributes.

TL;DR: In this paper , a series of hierarchical honeycomb metamaterials with hexagonal and kagome sub-units were analyzed, and the effect of including the fully-filled scatterers in two hierarchical honeycombs types was analyzed, along with the associated generation mechanism.