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10.29007/b1th ◽  
2022 ◽  
Author(s):  
Cong Hoa Vu ◽  
Ngoc Thien Ban Dang

Today, freight is an extremely important industry for the world we are living. Fast transportation, large volume...will optimize the cost, time and effort. Besides, ensuring the products safety is a matter of concern. During transporting, it is inevitable that the vibration caused by the engine, rough road surface...the cargo inside can be damaged. Automobile industries have prime importance to vibration testing. Sine vibration testing is performed when we have been given with only one frequency at given time instant. Trend to perform random vibration testing has been increased in recent times. As random vibration considers all excited frequencies in defined spectrum at known interval of time, it gives real-time data of vibration severities. The vibration severity is expressed in terms of Power Spectral Density (PSD). KLT box is an industrial stacking container conforming to the VDA 4500 standard that was defined by German Association of the Automotive Industry (VDA) for the automotive industry. The aim of this paper is study about random vibration and power spectral density analysis, how it can be used to predict the impact of hash road to the KLT box on container / truck during transportation. Finite element model is developed in ANSYS, modal analysis and random vibration analysis were done.


Sensors ◽  
2022 ◽  
Vol 22 (2) ◽  
pp. 593
Author(s):  
Ekaterina Babich ◽  
Sergey Scherbak ◽  
Ekaterina Lubyankina ◽  
Valentina Zhurikhina ◽  
Andrey Lipovskii

The problem of optimizing the topography of metal structures allowing Surface Enhanced Raman Scattering (SERS) sensing is considered. We developed a model, which randomly distributes hemispheroidal particles over a given area of the glass substrate and estimates SERS capabilities of the obtained structures. We applied Power Spectral Density (PSD) analysis to modeled structures and to atomic force microscope images widely used in SERS metal island films and metal dendrites. The comparison of measured and calculated SERS signals from differing characteristics structures with the results of PSD analysis of these structures has shown that this approach allows simple identification and choosing a structure topography, which is capable of providing the maximal enhancement of Raman signal within a given set of structures of the same type placed on the substrate.


2022 ◽  
Author(s):  
Daichi Kitahara ◽  
Hiroki Kuroda ◽  
Akira Hirabayashi ◽  
Eiichi Yoshikawa ◽  
Hiroshi Kikuchi ◽  
...  

<div>We propose nonlinear beamforming for phased array weather radars (PAWRs). Conventional beamforming is linear in the sense that a backscattered signal arriving from each elevation is reconstructed by a weighted sum of received signals, which can be seen as a linear transform for the received signals. For distributed targets such as raindrops, however, the number of scatterers is significantly large, differently from the case of point targets that are standard targets in array signal processing. Thus, the spatial resolution of the conventional linear beamforming is limited. To improve the spatial resolution, we exploit two characteristics of a periodogram of each backscattered signal from the distributed targets. The periodogram is a series of the powers of the discrete Fourier transform (DFT) coefficients of each backscattered signal and utilized as a nonparametric estimate of the power spectral density. Since each power spectral density is proportional to the Doppler frequency distribution, (i) major components of the periodogram are concentrated in the vicinity of the mean Doppler frequency, and (ii) frequency indices of the major components are similar between adjacent elevations. These are expressed as group-sparsities of the DFT coefficient matrix of the backscattered signals, and we propose to reconstruct the signals through convex optimization exploiting the group-sparsities. We consider two optimization problems. One problem roughly evaluates the group-sparsities and is relatively easy to solve. The other evaluates the group-sparsities more accurately, but requires more time to solve. Both problems are solved with the alternating direction method of multipliers including nonlinear mappings. Simulations using synthetic and real-world PAWR data show that the proposed method dramatically improves the spatial resolution.</div>


2022 ◽  
Vol 12 (1) ◽  
Author(s):  
Dongwan Kim ◽  
Mark Harfouche ◽  
Huolei Wang ◽  
Christos T. Santis ◽  
Yaakov Vilenchik ◽  
...  

AbstractWe have recently introduced a new semiconductor laser design which is based on an extreme, 99%, reduction of the laser mode absorption losses. In previous reports, we showed that this was achieved by a laser mode design which confines the great majority of the modal energy (> 99%) in a low-loss Silicon guiding layer rather than in highly-doped, thus lossy, III–V p$${}^+$$ + and n$${}^+$$ + layers, which is the case with traditional III–V lasers. The resulting reduced electron-field interaction was shown to lead to a commensurate reduction of the spontaneous emission rate by the excited conduction band electrons into the laser mode and thus to a reduction of the frequency noise spectral density of the laser field often characterized by the Schawlow–Townes linewidth. In this paper, we demonstrate theoretically and present experimental evidence of yet another major beneficial consequence of the new laser design: a near total elimination of the contribution of amplitude-phase coupling (the Henry $$\alpha $$ α parameter) to the frequency noise at “high” frequencies. This is due to an order of magnitude lowering of the relaxation resonance frequency of the laser. Here, we show that the practical elimination of this coupling enables yet another order of magnitude reduction of the frequency noise at high frequencies, resulting in a quantum-limited frequency noise spectral density of 130 Hz$$^2$$ 2 /Hz (linewidth of 0.4 kHz) for frequencies beyond the relaxation resonance frequency 680 MHz. This development is of key importance in the development of semiconductor lasers with higher coherence, particularly in the context of integrated photonics with a small laser footprint without requiring any sort of external cavity.


Author(s):  
Wissam Dehina ◽  
Mohamed Boumehraz ◽  
Wissam Dehina ◽  
Frédéric Kratz

Purpose The purpose of this paper is to propose applications of advanced signal-processing techniques for the diagnosis and detection of rotor fault in an induction machine. Two techniques are used: spectral analysis techniques and time frequency techniques for the diagnosis of an electrical machine. One is based on the power spectral density estimation techniques, such as periodogram and Welch periodogram. The second method is based on Hilbert transform (HT) to extract the envelope for the stator current. Then, this signal is processed via discrete wavelet transform (DWT) for determining the faulty components in the spectrum of the stator current envelope and identifying the eigenvalues of energies (HDWT). Design/methodology/approach First, this paper focused on theoretical development and a comparative study of these signal-processing techniques, which are based on the periodogram, Welch periodogram, HT and the DWT to extract the envelope for the stator current; it is used to compute the energy stored in each decomposition level obtained by the stator current envelope (HDWT). Moreover, the Welch periodogram is applied to obtain the envelope spectrum. Findings The simulation obtained and the experimental validation results of the proposed methods through MATLAB environment show the effectiveness of the proposed approaches with a good accuracy by power spectral density estimation techniques (periodogram and Welch periodogram). Moreover, the faults are manifested through the appearance of new frequencies components, as well as the envelope for the stator current (HT and DWT). This approach is effective for non-stationary and stationary signal to extract useful information for the detection of broken bar fault. Originality/value The current paper proposes a new diagnosis method for the detection and characterization of broken rotor bars defects early; it is founded primarily on theoretical development, and the comparison is based on the power spectral density technique (periodogram and Welch periodogram) and the computation of the energy stored in each decomposition level (precisely the HT and DWT). Moreover, the Welch periodogram is applied to obtain the envelope spectrum. The main advantages of the proposed techniques increase their reliability and availability.


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