This paper presents and analyzes a method for short-circuit fault detection in a permanent-magnet synchronous motor (PMSM). The study includes steady-state condition and speed transients in motor operation. The stator current is decomposed by empirical mode decomposition (EMD), which generates a set of intrinsic mode functions (IMFs). Quadratic time-frequency (TF) distributions such as smoothed pseudo-Wigner-Ville and Zhao-Atlas-Marks are applied on the more significant IMFs for fault detection. Simulations and experimental laboratory tests validate the algorithms and demonstrate that this kind of TF analysis can be applied to detect and identify short-circuit failures in PMSM.

This paper presents a study of the permanent magnet synchronous machine (PMSM) running under bearing damage. To carry out the study a two-dimensional (2-D) Finite Element Analysis (FEA) is used. Stator current induced harmonics for fault condition were investigated. Advanced signal analysis by means of continuous and discrete wavelet transforms was performed. Simulation were carried out and compared with experimental.

Estimating nitrogen (N) concentration in situ is fundamental for managing the fertilization of the sugarcane crop. The purpose of this work was to develop estimation models that explain how N varies over time as a function of three spectral data transformations in two stages (plant cane and first ratoon) under variable rates of N application. A randomized complete-block experimental design was applied, with four levels of N fertilization: 0, 80, 160, and 240 kg N ha−1. Six sampling events were carried out during the rapid growth stage, where the canopy reflectance spectra with a hyperspectral sensor were measured, and tissue samples for N determination in plant cane and first ratoon were taken, from 60 days after emergence (DAE) and 60 days after harvest (DAH), respectively, until days 210 DAE and 210 DAH. To build the models, partial least squares regression analysis was used and was trained by three transformations of the spectral data: (i) average reflectance spectrum (R), (ii) multiple scatter correction and Savitzky-Golay filter MSC-SG) reflectance spectrum, and (iii) calculated vegetation indices (VIs).

This paper presents and analyzes short circuit failures for Permanent Magnet Synchronous Motor (PMSM). The study includes stable condition and speed transients in simulation and realistic experimental conditions. The stator current is analyzed by the empirical mode decomposition (EMD) method, which will generate a collection of intrinsic mode functions (IMF). Finally, the Hilbert-Huang transform (HHT) is used to compute the instantaneous frequencies resulting from the IMFs obtained from the stator currents. Moreover, the IMF 1 and IMF 2 have been analyzed by means of Wigner Ville distribution (WVD). Experimental laboratory results validate the analysis and demonstrate that this kind of time-frequency analysis can be applied to detect and identify short circuit failures in synchronous machines.

In this paper and its companion paper [14], the problem of cooperative source seeking by a formation of mobile agents is considered. Each agent is equipped with position and signal strength measurement sensors; their task is to find the maximum of the scalar field. Agents exchange information with neighboring agents through a communication network. In the first part of this couple of papers, a distributed gradient estimation for each agent and a decentralized navigation controller for single- and double-integrator models are presented. When the signal measurements are corrupted by noise, distributed consensus filters are used in order to estimate the gradient direction. The strategy is based on both a gradient estimating algorithm and a formation controller. Stability conditions are provided. Numerical simulations illustrate the effectiveness of the proposed control law. Part two extends this approach to general linear time-invariant models.

In this paper and its companion paper [16], the problem of cooperative source seeking by a formation of mobile agents is considered. Each agent is equipped with position and signal strength measurement sensors; their task is to find the maximum of the scalar field. Agents exchange information with neighboring agents through a communication network. In the first paper, a distributed gradient estimation for each agent and a decentralized navigation controller for single- and double-integrator models are presented. In this paper, that approach is extended to general linear time-invariant (LTI) models. Our approach is verified using formation flight simulation for quad-rotor helicopters and stability conditions are provided.