This paper focuses on rolling elements bearing fault detection in induction machines based stator currents analysis. Specifically, it proposes to process the using Hilbert-Huang transform. approach relies two steps: empirical mode decomposition and Hilbert The is used order estimate intrinsic functions (IMFs). These IMFs are assumed be mono-component signals can processed demodulation technique. Afterward, transform compute instantaneous amplitude (IA) frequency (IF) of these IMFs. analysis...

This paper deals with the diagnosis of three-phase electrical machines and focuses on failures that lead to stator-current modulation. To detect a failure, we propose new method based demodulation. By exploiting configuration machines, demonstrate demodulation can be efficiently performed low-complexity multidimensional transforms such as Concordia transform (CT) or principal component analysis (PCA). From practical point view, also prove PCA-based is more attractive than CT. After...

Induction machines are widely used in industrial applications. Safety, reliability, efficiency, and performance major concerns that direct the research activities field of electrical machines. Even though induction machine is very reliable, many failures can occur such as bearing faults, air-gap eccentricity, broken rotor bars. The challenge is, therefore, to detect them at an early stage order prevent breakdowns. In particular, stator current-based condition monitoring extensively...

Blind recognition of communication parameters is a research topic high importance for both military and civilian systems. Numerous studies about carrier frequency estimation, modulation as well channel identification are available in literature. This paper deals with the blind space-time block coding (STBC) scheme used multiple-input-multiple-output (MIMO) Assuming there perfect synchronization at receiver side, this proposes three maximum-likelihood (ML)-based approaches STBC...

The main objective of this paper is to detect faults in induction machines using a condition monitoring architecture based on stator current measurements. Two types fault are considered: bearing and broken rotor bars faults. proposed high-resolution spectral analysis techniques also known as subspace techniques. These frequency estimation allow separate components including frequencies close the fundamental one. correspond sensitive frequencies. Once estimated, their corresponding amplitudes...

Motor current signature analysis (MCSA) is a well-proven technique for electrical and mechanical faults detection in induction motors. The appearance of stator components or increase magnitude some at characteristic frequencies indicates motor fault condition. In this paper, we propose new MCSA detector based on matched subspace technique. proposed consists three steps. First, the influence fundamental supply frequency removed from signal using an interference cancellation oblique...

The blind recognition of communication parameters is a key research issue for commercial and military systems. results numerous investigations about symbol timing estimation, modulation as well identification the number transmitters have been reported in literature. But, to our knowledge, none them dealt with Space-Time Block Codes (STBC) used multiple transmitter communications. In order blindly recognize STBC wireless communication, this paper proposes method based on space-time...

This paper describes a new blind channel estimation algorithm for Space-Time Block Coded (STBC) systems.The proposed method exploits the statistical independence of sources before space-time encoding.The matrix is estimated by minimizing kurtosis-based cost function after Zero-Forcing equalization.In contrast to subspace or Second-Order Statistics (SOS) approaches, more general since it can be employed class linear STBCs including Spatial Multiplexing, Orthogonal, quasi-Orthogonal and...

To reduce the cost of wind energy, minimization and prediction maintenance operations in turbine is key importance. In variable speed generator, advanced signal processing tools are required to detect diagnose generator faults from stator current. a fault non-stationary conditions, previous studies have investigated use time-frequency techniques such as Spectrogram, Wavelet transform, Wigner-Ville representation Hilbert-Huang transform. this paper, these presented compared for broken-rotor...

Wind energy conversion systems have become a focal point in the research of renewable sources. In order to make wind turbines as competitive classical electric power stations, it is important reduce operational and maintenance costs. The most efficient way reducing these costs would be continuously monitor condition systems. This allows for early detection degradation generator health, facilitating proactive response, minimizing downtime, maximizing productivity. paper provides then an...

This paper deals with the diagnosis of Wind Turbines based on generator current analysis. It provides a comparative study between traditional signal processing methods, such as periodograms, more sophisticated approaches. Performances these techniques are assessed through simulation experiments and compared for several types fault, including air-gap eccentricities, broken rotor bars bearing damages.

Fault detection in squirrel cage induction machines based on stator current spectrum has been widely investigated. Several high resolution spectral estimation techniques have developed and used to detect machine abnormal operating conditions. In this paper, a modified version of MUSIC algorithm the faults characteristic frequencies. This method estimate spectrum. Then, an amplitude estimator proposed fault indicator derived for severity measurement. Simulated data issued from coupled...

In this paper, new frequency and phasor estimators are presented. These based on the maximum-likelihood technique exploit multidimensional nature of electrical signals. To minimize likelihood function, we present an optimization algorithm Newton-Raphson technique. While performance Fourier-based significantly degrades when window length is not equal to a multiple fundamental half-period, proposed perform well regardless length. Simulation results show that clearly outperform discrete-time...

Several studies have demonstrated that induction machine faults introduce phase and/or amplitude modulation of the stator currents. Hence, demodulation currents is high interest for machines detection and diagnosis. The techniques can be classified into mono-dimensional multi-dimensional approaches. include synchronous demodulator, Hilbert transform, Teager energy operator other approaches Concordia transform Principal Component Analysis. Once has been performed, demodulated signals are...

In this paper, the problem of frequency and phasor estimation in three-phase systems is considered. Three-phase electrical signals are composed three components that can be jointly exploited to improve performance. To exploit property, most existing algorithms based on a linear preprocessing called Clarke transform. we investigate more general situation where obtained from semi-orthogonal This encompasses several strategies such as single-phase estimator, optimal Clarke-based estimator. For...

In this paper, a new technique for power quality disturbance classification is proposed. It focuses on voltage sags and swells that are first preclassified into four classes depend the number of nonzero symmetrical components can contain different types sag swell. Using estimated component values, we afterward classify corresponding or swell signature. study, show preclassification be reformulated as pure model order selection problem. To solve problem, propose two preclassifiers based...

This paper investigates a new fault detection method for induction machines diagnosis. The proposed is based on hypothesis testing. decision made between two hypotheses: the machine healthy and faulty. generalized likelihood ratio test used to address this issue with unknown signal noise parameters. To implement detector, parameters are replaced by their estimates. Specifically, four estimations required, which model order, frequency, phase, amplitude estimations. order obtained using...

This paper focuses on the estimation of instantaneous amplitude, phase, and unbalance parameters in three-phase power systems. Due to particular structure systems, we demonstrate that maximum-likelihood estimates (MLEs) unknown have simple closed-form expressions can be easily implemented without matrix algebra libraries. We also derive analyze Cramer-Rao Bounds (CRBs) for considered problem. The performance proposed approach is evaluated using synthetic signals compliant with IEEE Standard...

Wind energy conversion systems (WECS) have become a focal point in the research of renewable sources. In order to make wind turbine reliable and competitive, it is important reduce operational maintenance costs. The most efficient way relies on condition monitoring fault diagnostics. This paper proposes new detector based amplitude demodulation three-phase stator current. Simulations show that this low-complexity method well suited for stationary or non-stationary behavior.