Pressure fluctuation signal analysis of pump based on ensemble empirical mode decomposition method

AbstractPressure fluctuations, which are inevitable in the operation of pumps, have a strong non-stationary characteristic and contain a great deal of important information representing the operation conditions. With an axial-flow pump as an example, a new method for time-frequency analysis based on the ensemble empirical mode decomposition (EEMD) method is proposed for research on the characteristics of pressure fluctuations. First, the pressure fluctuation signals are preprocessed with the empirical mode decomposition (EMD) method, and intrinsic mode functions (IMFs) are extracted. Second, the EEMD method is used to extract more precise decomposition results, and the number of iterations is determined according to the number of IMFs produced by the EMD method. Third, correlation coefficients between IMFs produced by the EMD and EEMD methods and the original signal are calculated, and the most sensitive IMFs are chosen to analyze the frequency spectrum. Finally, the operation conditions of the pump are identified with the frequency features. The results show that, compared with the EMD method, the EEMD method can improve the time-frequency resolution and extract main vibration components from pressure fluctuation signals

3D Positioning Algorithm Design for RIS-aided mmWave Systems

In this paper, we investigate a three-dimensional (3D) positioning algorithm for a millimeter wave (mmWave) system, where the reconfigurable intelligent surfaces (RIS) are leveraged to enhance the positioning performance of mobile users (MUs). We propose a two-stage weight least square (TSWLS) algorithm to obtain the closed-form solution of the MU's position. In the first stage, we construct the pseudolinear equations based on the angle of arrival (AOA) and the time difference of arrival (TDOA) estimation at the RISs, then we obtain a preliminary estimation by solving these equations using the iterative weight least square (WLS) method. Based on the preliminary estimation in the first stage, a new set of pseudolinear equations are obtained, and a finer estimation is obtained by solving the equations using the WLS method in the second stage. By combining the estimation of both stages, the final estimation of the MU's position is obtained. Further, we study the theoretical bias of the proposed algorithm by considering the estimation error in both stages. Simulation results demonstrate the superiority of the proposed positioning algorithm. Furthermore, it is also shown that the proposed algorithm still have good positioning performance with low SNR.Comment: Keywords: Reconfigurable intelligent surface (RIS), intelligent reflecting surface (IRS

Particle bonding mechanism in CGDS-a three-dimensional approach

Abstract: Cold gas dynamics spray (CGDS) is a surface coating process using highly accelerated particles to form the surface coating by high speed impact of the particles. In the CGDS process, metal particles of generally 1-50 μm diameter is carried by a gas stream in high pressure (typically 20-30 atm) through a DE Laval type nozzle to achieve supersonic flying so as to impact on the substrate. Typically, the impact velocity ranges between 300 and 1200 m/s in the CGDS process. When the particle gains its critical velocity, the minimum in-flight speed at which it can deposit, adiabatic shear instabilities will occur. Herein, to ascertain the critical velocities of different particle sizes on the bonding efficiency in CGDS process, three-dimensional numerical simulations of single particle deposition process were performed. In the CGDS process, one of the most important parameters which determine the bonding strength with the substrate is particle impact temperature. Bonding will occur when the particle’s impacting velocity surpass the critical velocity, at which the interface can achieve 60 % of melting temperature of particle material (Ref 1). Therefore, critical velocity should be a main parameter on the coating quality. The particle critical velocity is determined not only by its size, but also by its material properties. This study numerically investigate the critical velocity for the particle deposition process in CGDS. In the present numerical analysis, copper (Cu) was chosen as particle material and aluminum (Al) as substrate material for this study. The impacting velocities were selected between 300 m/s and 800 m/s increasing in steps of 100 m/s. The simulation result reveals temporal and spatial interfacial temperature distribution and deformation between particle(s) and substrate. Finally, comparison is carried out between the computed results and experimental data

Early postoperative interventions in the prevention and management of thyroidectomy scars

Thyroidectomy scars, located on the exposed site, can cause distress in patients. Owing to the cosmetic importance of thyroidectomy scars, many studies have been conducted on its prevention and treatment. Scar formation factors mainly include inflammatory cell infiltration, angiogenesis, fibroblast proliferation, secretion of cytokines such as transforming growth factor (TGF)-β1, and mechanical tension on the wound edges. Anti-scar methods including topical anti-scar agents, skin tension-bearing devices, and local injections of botulinum toxin, as well as lasers and phototherapies, that target these scar formation factors have been developed. However, current studies remain fragmented, and there is a lack of a comprehensive evaluation of the impacts of these anti-scar methods on treating thyroidectomy scars. Early intervention is a crucial but often neglected key to control hyperplastic thyroidectomy scars. Therefore, we review the currently adopted early postoperative strategies for thyroidectomy scar reduction, aiming to illustrate the mechanism of these anti-scar methods and provide flexible and comprehensive treatment selections for clinical physicians to deal with thyroidectomy scars

PP-012 Novel blaCTX-M-79 gene from community isolates in association with ISEcp1 in Shenyang, China

Digitalitzat per Artypla

RIS-Position and Orientation Estimation in MIMO-OFDM Systems with Practical Scatterers

In this paper, we investigate the problem of estimating the position and the angle of rotation of a mobile station (MS) in a millimeter wave (mmWave) multiple-input-multiple-output (MIMO) system aided by a reconfigurable intelligent surface (RIS). The virtual line-of-sight (VLoS) link created by the RIS and the non-line-of-sight (NLoS) links that originate from scatterers in the considered environment are utilized to facilitate the estimation. A two-step positioning scheme is exploited, where the channel parameters are first acquired, and the position-related parameters are then estimated. The channel parameters are obtained through a coarser and a subsequent finer estimation processes. As for the coarse estimation, the distributed compressed sensing orthogonal simultaneous matching pursuit (DCS-SOMP) algorithm, the maximum likelihood (ML) algorithm, and the discrete Fourier transform (DFT) are utilized to separately estimate the channel parameters. The obtained channel parameters are then jointly refined by using the space-alternating generalized expectation maximization (SAGE) algorithm, which circumvents the high-dimensional optimization issue of ML estimation. Departing from the estimated channel parameters, the positioning-related parameters are estimated. The performance of estimating the channel-related and position-related parameters is theoretically quantified by using the Cramer-Rao lower bound (CRLB). Simulation results demonstrate the superior performance of the proposed positioning algorithms.Comment: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl

Quasispecies distribution of Eigen model

We study sharp peak landscapes (SPL) of Eigen model from a new perspective about how the quasispecies distribute in the sequence space. To analyze the distribution more carefully, we bring forth two tools. One tool is the variance of Hamming distance of the sequences at a given generation. It not only offers us a different avenue for accurately locating the error threshold and illustrates how the configuration of the distribution varies with copying fidelity $q$ in the sequence space, but also divides the copying fidelity into three distinct regimes. The other tool is the similarity network of a certain Hamming distance $d_{0}$, by which we can get a visual and in-depth result about how the sequences distribute. We find that there are several local optima around the center (global optimum) in the distribution of the sequences reproduced near the threshold. Furthermore, it is interesting that the distribution of clustering coefficient $C(k)$ follows lognormal distribution and the curve of clustering coefficient $C$ of the network versus $d_{0}$ appears as linear behavior near the threshold.Comment: 13 pages, 6 figure