Rolling element bearing defect detection using the generalized synchrosqueezing transform guided by time–frequency ridge enhancement

Healthy rolling element bearings are vital guarantees for safe operation of the rotating machinery. Time–frequency (TF) signal analysis is an effective tool to detect bearing defects under time-varying shaft speed condition. However, it is a challenging work dealing with defective characteristic frequency and rotation frequency simultaneously without a tachometer. For this reason, a technique using the generalized synchrosqueezing transform (GST) guided by enhanced TF ridge extraction is suggested to detect the existence of the bearing defects. The low frequency band and the resonance band are first chopped from the Fourier spectrum of the bearing vibration measurements. The TF information of the lower band component and the resonance band envelope are represented using short-time Fourier transform, where the TF ridge are extracted by harmonic summation search and ridge candidate fusion operations. The inverse of the extracted TF ridge is subsequently used to guide the GST mapping the chirped TF representation to the constant one. The rectified TF pictures are then synchrosqueezed as sharper spectra where the rotation frequency and the defective characteristic frequency can be identified, respectively. Both simulated and experimental signals were used to evaluate the present technique. The results validate the effectiveness of the suggested technique for the bearing defect detection.     

A multi-objective problem based on fuzzy inference with application to parametric design of an electrophotographic system

This paper proposes a systematic approach to conduct system-level optimal parametric design for a class of electrophotographic systems. A conventional monochrome laser printer serves as the platform for verification of the proposed optimal design approach. Besides performance, we incorporate two other practical indices, i.e., cost and energy consumption, into design objectives and formulate a multi-objective optimization problem. A fuzzy inference system is established to provide the nonlinear or linguistic mapping between the decision variables and the design objectives. For comparative purpose, the problem is solved using both single-objective and multi-objective optimization algorithms. Note that the proposed approach is also applicable to other complex systems.     

Periodical concentration of surface plasmon polaritons by wave interference in metallic film with nanocavity array

Metallic thin films with nanocavity arrays provide ideal platforms for plasmonics, non-linear optics, surface chemistry and corresponding applications. A general understanding of electromagnetic (EM) field distributions is needed for further creation, manipulation and designation of near-field enhancements. Herein, we study the distribution of plasmonic hot spots over Ag thin films with triangular nanocavities in hexagonal arrays with a variable of lattice parameters. We propose that the concentration and interference of surface plasmon polaritons (SPP) dominates the distribution of plasmonic hot spots. The localized surface plasmonic resonance (LSPR) at nanocavities excites SPPs to propagate on the thin film, whose concentration and interference lead to an extremely strong near-field enhancement at the surface of the thin film, the location of which can also be termed as plasmonic hot spot. For this model, the calculation results of the physical formula are in excellent agreements with both the experimental results and the electrodynamic simulations with 3D finite element method (FEM). Moreover, the plasmonic hot spots distribute periodically within the nanocavity arrays, determined by the geometric symmetry of the array as well as with the polarization state of the incident field. The periodicity of plasmonic hot spots on flat surface illustrates a new way to concentrate SPPs in an extendable area, which has potential applications in localized non-linear optics, sensing, plasmonic logical circuit and optical computing.     

Novel clock synchronization algorithm of parametric difference for parallel and distributed simulations

Clock synchronization is crucial in distributed simulation applications (DSAs). Traditional synchronization methods are mainly based on computers’ physical clocks and have network delays. Consequently, the clock jumps easily, and the stability of the algorithm is less than excellent. Furthermore, a new class of DSAs with flexible and dynamically assembled simulation components to optimize the performance of clock clusters is emerging. To remedy the problems, we propose a novel logic parametric difference clock (PDC), which is recursively constructed by an alterable parametric difference frequency (PDF) and its counter. We also develop a simple and efficient synchronization algorithm of parametric difference (SAPD), in which the indeterminate network delay is considered in the PDF, and the PDC counter is used as the synchronous symbol. Compared with existing typical algorithms, the SAPD has the predominant advantages of convergence, stability, and precision for DSAs in local area networks.     

Finite element analysis of the effect of coefficient of friction on the drawability

Drawability is a term commonly used to describe the ease with which the metal can be drawn into the cups. The various measures of drawability are limit drawing ratio and the limit strains which are influenced by the parameters like tooling configurations, blank configurations, material properties, and forming conditions. Generally the drawability is limited by tearing of the cup at the punch corners. Friction plays an important role in deciding drawability in such a situation. In this work, the effect of coefficient of friction on limit drawing ratio and the limit strains are studied using an explicit finite element code LSDYNA. The model is validated by comparing force obtained by the existing experimental setup with the one obtained in simulation. The limit strains obtained from the simulation are verified by the analytical equations developed using vortex theory. The results are tallying within 0.17–8.29% error.     

Properties of Co0.5Ni0.5Fe2O4/carbon nanotubes/polyimide nanocomposites for microwave absorption

High-temperature microwave absorbing materials are of great interest due to their ability to withstand high temperatures. Multi-walled carbon nanotubes (MWNTs) were surface modified by Ar plasma and Co_0.5Ni_0.5Fe₂O₄ nanoparticles were doped onto the surface of the MWNTs by a chemical co-precipitation method. Co_0.5Ni_0.5Fe₂O₄/MWNTs powders were then added to polyimide to prepare nanocomposites for microwave absorption. After plasma modification, the surface of the MWNTs produced carboxyl groups, which are beneficial for interfacial bonding between the MWNTs and PI. The glass transition temperature of the nanocomposites was 261 °C and their thermostability was preserved up to 500 °C. The maximum reflection loss (RL) value of nanocomposites containing 0.75 wt% modified MWNTs was ?24.37 dB and the frequency range where the RL value was less than ?10 dB was 5.1 GHz from 7.8 to 12.9 GHz.     

Synthesis and characterization of a Keggin-type V(V)-substituted isopolytungstate, (n-C3H7)5[H4VW11O40]

A new V(V)-substituted isopolytungstate, (n-C₃H₇)₅[H₄VW₁₁O₄₀], with Keggin structure was synthesized in an acidic aqueous–CH₃CN solution and characterized by elemental analysis, FT-IR, Raman, ¹H NMR, and cyclic voltammetry.     

A novel route to produce BaTiO3 glass-ceramics with nanosized cubic BaTiO3 phase precipitating for high energy-storage applications

To meet requirements of miniaturization devices in high pulsed power technology, super dielectric energy storage performance, such as high dielectric breakdown strength (DBS), large energy storage density with high power density, is extremely important in dielectric materials. However, for BaTiO₃ based ceramics and glass ceramics, there is still a critical challenge to achieve high DBS and large energy storage density. Herein, a novel route was proposed to precipitate nanocrystals with cubic BaTiO₃ phase from glass matrix, which can elevate dielectric constant and meanwhile maintain high DBS compared to parent glass. A high recoverable energy storage density of ∼ 3.66 J cm⁻³ at 1000 kV cm⁻¹ and high discharge energy density of ∼3.57 J cm⁻³ with good thermal stability and ultra-high peak power density of ∼ 910 MW cm⁻³ can be achieved in BaTiO₃ glass ceramic, which implies this type of glass ceramics is suitable for high pulsed power technology application.     

Neural network guidance based on pursuit-evasion games with enhanced performance

This paper addresses a neural network guidance based on pursuit-evasion games, and performance enhancing methods for it. Two-dimensional pursuit-evasion games solved by the gradient-based method are considered. The neural network guidance law employs the range, range rate, line-of-sight rate, and heading error as its input variables. Additional pattern selection methods and a hybrid guidance method are proposed for the sake of the interception performance enhancement. Numerical simulations are accompanied for the verification of the neural network approximation, and of the improved interception performance by the proposed methods. Moreover, all proposed guidance laws are compared with proportional navigation.