scholarly journals Measured and simulated examination of the propagation paths of structure‐borne sound using the structural intensity for fibre reinforced injection moulded thermoplastic parts

PAMM ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Dennis Netzband ◽  
Andreas Ujma ◽  
Elmar Moritzer
2021 ◽  
Vol 13 (5) ◽  
pp. 890
Author(s):  
Aleksandra Nina ◽  
Milan Radovanović ◽  
Luka Č. Popović

Atmospheric properties have a significant influence on electromagnetic (EM) waves, including the propagation of EM signals used for remote sensing. For this reason, changes in the received amplitudes and phases of these signals can be used for the detection of the atmospheric disturbances and, consequently, for their investigation. Some of the most important sources of the temporal and space variations in the atmospheric parameters come from the outer space. Although the solar radiation dominates in these processes, radiation coming out of the solar system also can induces enough intensive disturbance in the atmosphere to provide deflections in the EM signal propagation paths. The aim of this issue is to present the latest research linking events and processes in outer space with changes in the propagation of the satellite and ground-based signals used in remote sensing.


2021 ◽  
Vol 262 ◽  
pp. 113631
Author(s):  
Pasquale Junior Capasso ◽  
Giuseppe Petrone ◽  
Nikolai Kleinfeller ◽  
Sergio De Rosa ◽  
Christian Adams

2021 ◽  
pp. 1-10
Author(s):  
Chien-Cheng Leea ◽  
Zhongjian Gao ◽  
Xiu-Chi Huanga

This paper proposes a Wi-Fi-based indoor human detection system using a deep convolutional neural network. The system detects different human states in various situations, including different environments and propagation paths. The main improvements proposed by the system is that there is no cameras overhead and no sensors are mounted. This system captures useful amplitude information from the channel state information and converts this information into an image-like two-dimensional matrix. Next, the two-dimensional matrix is used as an input to a deep convolutional neural network (CNN) to distinguish human states. In this work, a deep residual network (ResNet) architecture is used to perform human state classification with hierarchical topological feature extraction. Several combinations of datasets for different environments and propagation paths are used in this study. ResNet’s powerful inference simplifies feature extraction and improves the accuracy of human state classification. The experimental results show that the fine-tuned ResNet-18 model has good performance in indoor human detection, including people not present, people still, and people moving. Compared with traditional machine learning using handcrafted features, this method is simple and effective.


Radio Science ◽  
1977 ◽  
Vol 12 (3) ◽  
pp. 435-440 ◽  
Author(s):  
D. C. Cox ◽  
H. W. Arnold ◽  
A. J. Rustako

Author(s):  
X. Yin ◽  
G. Steinbock ◽  
G. E. Kirkelund ◽  
T. Pedersen ◽  
P. Blattnig ◽  
...  

2015 ◽  
Vol 12 (03) ◽  
pp. 1550013 ◽  
Author(s):  
Siu-Siu Guo ◽  
Dongfang Wang ◽  
Zishun Liu

The concept of structural intensity (SI) is extended to the random domain by introducing a physical quantity denominated random structural intensity (RSI). This quantity is formulated for mechanical systems whose dynamical responses are stochastic due to random excitations. In order to fully characterize the stochastic behavior of a system under random loadings, it is imperative to obtain the probability density function (PDF) of RSI. Based on the elastic theory and the definition of SI, RSI is expressed as functions of system responses. In general, the PDF of system responses is governed by Fokker–Planck–Kolmogorov (FPK) equation under the assumption that random dynamic loadings are idealized as white noise excitations. Therefore, the PDF of RSI is derived with the joint PDF of system responses. In the present study, four demonstrating cases of beams and plates under separately concentrated and uniform random loadings are studied to investigate the properties of RSI. Stationary and non-stationary PDFs of RSI at arbitrary section of beam and plate are obtained. Numerical results show that the PDF of RSI is transient at early stage of stationary loading and then converges to the exact stationary ones as time increases. With the obtained PDFs of RSI, energy transmission path over the beam and plate can be determined, which is guided from the locations with lower probabilities of RSI to the ones with higher probabilities of RSI. Furthermore, virtual energy flow sinks on the plate and beam can be found, which are identified by the locations with the maximum probabilities of RSI.


2003 ◽  
Vol 9 (10) ◽  
pp. 1189-1199 ◽  
Author(s):  
Nirmal Kumar Mandal ◽  
Roslan Abd. Rahman ◽  
M. Salman Leong

The structural intensity technique is usually used to estimate vibration power flow in structures. This method is used to determine vibration power flow in thin naturally orthotropic plates. The bending wave is considered to find general vibration power transmission in the frequency domain that is not approximated by far field conditions. This intensity formulation defines power flow per unit width of the plates (W m−1) similar to that of the conventional idea. Power flow estimation is formulated using cross-spectra of field signals, facilitating the use of a fast Fourier transform analyzer.


2020 ◽  
Author(s):  
Victor U. J. Nwankwo ◽  
Jean-Pierre Raulin ◽  
Dra. Emilia Correia ◽  
William F. Denig ◽  
Olanike Akinola ◽  
...  

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