Recently, the TaylorK Kalman filter was proposed for estimating instantaneous oscillating phasors. Its performance was examined through time-domain simulations using the benchmark test signals specified in the IEEE Standard for Synchrophasors for Power Systems. It was discovered that the estimation error level was abruptly reduced by a factor of ten from the second order, mainly because those filters were able to provide instantaneous phasor estimates. In this paper, the frequency response of the zeroth- and second-order filters is established and illustrated. They demonstrate that, for orders greater than or equal to two, the filters are able to form zero flat phase response about the operation frequency and then able to provide instantaneous estimates. By assessing the behavior of the estimates before signals with harmonics, or noise, not contemplated in the signal model, the frequency response method leads us to design more robust filters, referred to as TaylorK Kalman-Fourier, because they incorporate the whole set of harmonics in their multiharmonic signal model. It turns out that the bank of comb filters achieved with K = 0 is equivalent to that of the discrete Fourier transform, with a computational cost of one and a half products per harmonic estimate, which is lower than the FFT cost for more than eight components, and the bank of fence filters obtained with K = 2 is similar to that of the Taylor² Fourier transform but with the advantage of providing estimates devoid of delay and needing only four products per harmonic set of estimates. Due to their instantaneous character, and computational simplicity, those estimates are certainly very useful for real-time harmonic analysis and power system control applications.

The state-transition matrix of the Kth order Taylor approximation to the dynamic phasor and its first derivatives leads to a plurality of state-space representations to approach the bandpass signal model of a power oscillation. With these truncated signal models, the Kalman filter algorithm can be applied to their state vectors in order to find observers able to estimate the dynamic phasor and its first derivatives. The estimates obtained through this technique, from oscillatory signals, are not only instantaneous (no delay) but also synchronous, an important attribute for control applications. They also provide frequency estimates. The new filters reduce the total vector error achieved with the traditional Kalman filter; are much more stable, with settling times five times lower; and improve the phasor estimates of oscillations with frequency offset.

Broken rotor bar (BRB) fault is common in cage rotor induction motors. Motor current signature analysis (MCSA) has been a popular method to detect BRB faults. In the MCSA, the fault signature frequencies for BRB are close to the fundamental frequency. This spectral nearness leads to the requirement of larger observation windows, which inherently increases BRB fault detection time. This paper presents an alternative algorithm to detect BRB faults in induction motors from MCSA using two Taylor-Kalman (TK) filters in cascade with a subsampling scheme. The proposed BRB fault detection approach allows to use the TK filter to estimate lower frequencies with less computational burden in comparison to conventional TK analysis. Experimental analysis shows that nearly accurate estimates and competitive detection time can be achieved by the proposed BRB detection method. The performance of the proposed algorithm has been compared with classical spectral techniques using numerical simulations and records acquired from induction motors under real operating conditions.

This article presents an evaluation of Prony method and its implementation considerations for motor current signal analysis diagnostics in rotor cage induction motors. The broken rotor bar fault signature in current signals is evaluated using Prony method, where its advantages in comparison with fast Fourier transform are presented. The broken rotor bar fault signature could occur during the life cycle operation of induction motors, so that is why an effective early detection estimation technique of this fault could prevent an insulation failure or heavy damage, leaving the motor out of service. First, an overview of cage winding defects in rotor cage induction motors is presented. Next, Prony method and its considerations for the implementation in current signature analysis are described. Then, the performance of Prony method using numerical simulations is evaluated. Lastly, an assessment of Prony method as a tool for current signal analysis diagnostics is performed using a laboratory test system where real signals of an induction motor with broken rotor bar operated with/without a variable frequency drive are analyzed. The summary results of the estimation (amplitudes and frequencies) are presented in the results and discussion section.

This article presents an evaluation of Prony method estimation and its implementation considerations for surge comparison test application in turn insulation diagnostics for three-phase stator windings. Surge testing diagnostics compares recorded surge voltage signals of motor winding, and a diagnostic is then defined with a defined value of EAR (error area ratio), which evaluates the difference between signals to determine a turn insulation diagnostic. First, an overview of surge testing is presented. Next, the Prony method and the considerations for its implementation in surge testing are described. Then, a numerical simulation is used to define a simulated turn fault surge voltage signal, where its parameters can be obtained with Prony method estimation and compared with EAR to evaluate its performance. Lastly, recorded surge test signals from two tested motors are used to validate Prony method estimation application for surge test diagnostics, where twelve recorded surge signals for no-fault and fault conditions were analyzed. The summary results of the surge signals parameter estimation are presented in the results and discussion section.