Early fault detection and real-time condition monitoring systems have become quite significant for today's modern industrial systems. In a high volume of manufacturing facilities, fleets equipment are expected to operate uninterrupted days or weeks. Any unplanned interruptions uptime could jeopardize manufacturers' cycle time, capacity, and, most significantly, credibility their customers. With the help smart technologies, companies started develop integrate classification where end-to-end...

In this work, Empirical Mode Decomposition (EMD) is applied to the problem of Direction Arrival (DoA) estimation as a preprocessing method. The stage consists separate denoising rows array data matrix where each row corresponds output particular sensor. chosen algorithm an iterative interval-thresholding variant EMD. After stage, MUSIC construct EMD-enhanced spatial spectrum. proposed EMD-based scheme based on principles wavelet-thresholding, thus it comparable wavelet-based matrix. results...

A novel scattering center extraction algorithm based on data extrapolation and continuous parameter genetic (CGA)-based CLEAN is presented. The frequency domain extrapolated using AR modeling to obtain high resolved range profiles then initial estimates of centers obtained from the peaks these are used increase convergence rate algorithm. Simulation results show that proposed method requires less computation time compared classical evolutionary programming approaches it has resolution...

In this work, a novel scattering center extraction method using genetic algorithm based CLEAN is proposed. Initial values for optimization parameters are estimated from the power spectra of measured data Fourier transform. The proposed reduces computational time compared to existing evolutionary programming (EP) approaches.

In this work, we propose a new diagonal loading approach to improve the robustness of standard Capon beamformer. For purpose, array is analyzed using spatial autoregressive modeling. The proposed regularization method order-recursive, which allows definition Levinson-like algorithm. This eliminates need invert regularized covariance matrix, essential for all types beamformers. diagonal-loading involves two parameters, thereby increasing compared one-parameter approaches.

In this study the advantage of using Web 2.0 applications in terms increasing student attention and enthusiasm will be emphasized by presenting example community service activities which were supported blog usage.

In this work, we consider the spectral estimation of gapped data encountered in inverse synthetic aperture radar (ISAR) imaging. For missing data, propose use Least-Square Lattice (LSL) Filters. The proposed method consists interpolating rows two-dimensional backscattered where each row corresponds to target from a specific aspect angle. IFFT processing yields enhanced estimate interpolated data. To demonstrate effectiveness algorithm, numerical results based on simulated are presented.

In this work we propose an approach for the direction of arrival (DOA) estimation problem which increases performance subspace algorithms . The is based on extrapolation data matrix using autoregressive model. proposed method, AR coefficients are calculated least square lattice (LSL) structure. low signal to noise levels steming from LSL structure enable a more efficient modeling subspaces. Via simulations, it shown that enhanced compared non-extrapolated and other extrapolated methods...

Radar images, range profiles and scattering centers are used as feature parameters in radar target classification applications. Scattering center parameters, when enable an efficient compression of space compared to classical methods based on images profiles. A method for the estimation via cancellation side lobes is CLEAN algorithm. In this work, model Prony, MUSIC, ESPRIT evolutionary applied centers. hybrid proposed which improves convergence CLEAN. estimated by aforementioned classified...