Amplitude and Frequency Estimation of Exponentially Decaying Sinusoids

Tomar, Shikha; Sumathi, P.

doi:10.1109/tim.2017.2755998

Cited by 25 publications

(6 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…One of the main features of MCSA is the rotor analysis [20]. Broken rotor bar, static eccentricity and dynamic eccentricity are the three basic types of motor issues that can be analyzed using the MCSA method.…”

Section: Fig 3 Mcsa Data Collection Process When Monitoring the Induction Motormentioning

confidence: 99%

Analysis of Induction Motor Performance Using Motor Current Signature Analysis Technique

Syahputra

Purwanto

Wiyagi

et al. 2021

JET

View full text Add to dashboard Cite

This paper discusses the analysis of the performance of an induction motor using the motor current signature analysis (MCSA) technique. Induction motor is a type of electric machine that is widely used in industry. One of the industries that utilize induction motors is a steam power plant (SPP). The role of induction motors is very vital in SPP operations. Therefore, it is necessary to monitor the performance, stability, and efficiency to anticipate disturbances that can cause damage or decrease the life of the induction motor. MCSA is a reliable technique that can be used to analyze damage to an induction motor. In this technique, the induction motor current signal is detected using a current transducer. The signal is then passed on to the signal conditioning and then into the data acquisition device. The important signal data is analyzed in adequate computer equipment. The results of this analysis determine the condition of the induction motor, whether it is normal or damaged. In this research, a case study was carried out at the Rembang steam power plant, Central Java, Indonesia. The results of the analysis of several induction motors show that most of them are in normal conditions and are still feasible to operate.

show abstract

Section: Fig 3 Mcsa Data Collection Process When Monitoring the Induction Motormentioning

confidence: 99%

Analysis of Induction Motor Performance Using Motor Current Signature Analysis Technique

Syahputra

Purwanto

Wiyagi

et al. 2021

JET

View full text Add to dashboard Cite

show abstract

“…Sums of sinusoidal signals having arbitrary frequencies are common signals in information-based systems. Besides being multi-purpose signals used in communication channels, they are used as test signals in measurement systems [1]- [3] and for system identification purposes [4]. They are employed to measure material properties in electrochemical impedance spectroscopy [5] and to characterize the stateof-health of rechargeable batteries [6].…”

Section: Introductionmentioning

confidence: 99%

Measurement of the Parameters of Multiple Sinusoids Based on Binary Data

Carbone

Angelis

Santoni

et al. 2021

IEEE Trans. Instrum. Meas.

View full text Add to dashboard Cite

This paper introduces a novel procedure for quick estimation of the parameters of a sum of sinusoidal signals based on one-bit measurements. Amplitude, phases and, frequencies of the signal components are assumed unknown, as well as the threshold level of the comparator used to produce measurement results. To provide enough information at the one-bit quantizer input, a sinewave is assumed to dither one of the two comparator's inputs. To ease the procedure's application, only the peak-to-peak amplitude of this dither signal is assumed known. Theoretical, simulation-based and experimental results validate the presented approach.

show abstract

“…Widespread used renewable and sustainable energy sources bring modern power systems electromechanical oscillations, synchronous, and subsynchronous oscillations [1][2][3][4][5][6]. The low-frequency oscillations (LFO) may result in unstable and unsecure operation of power systems, so the real-time identification of frequency, amplitude, and damping factor are still essential in recent years [7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

“…A type of methods to estimate the parameters of EDS signals are based on integration, such as a method combining Hankel singular value decomposition (HSVD) with the extended complex Kalman filter (ECKF) [2], an algorithm employing the DFT coefficients around the peaks of the components [3], a moving window discrete Fourier transform filter (MWDFT) in cooperation with a frequency-locked loop [8], and two novel interpolation iterative estimators based on DFT coefficients [10]. In these integral methods, the large computation restrains the online identification in a more wider engineering.…”

Section: Introductionmentioning

confidence: 99%

A Robust Direct Parameter Identification of Exponentially Damped Low-Frequency Oscillation in Power Systems

et al. 2020

View full text Add to dashboard Cite

Low-frequency oscillations in power systems can be modeled as an exponentially damped sinusoid (EDS) signal. Its frequency, damping factor, and amplitude are identified by the robust algorithm proposed in this paper. Under the condition of no noise, the exponentially convergent property of the proposed identification is proved by the use of time scale change, variable transformation, slow integral manifold, averaging method, and Lyapunov stability theorem in sequence. Under the condition of bounded additive noise, the antinoise performance of the identification of each parameter is investigated by the perturbed system theorem and error synthesis principle. The robustness of the proposed method is embodied in the following aspects: the exponential convergence for EDS signal with a wide range of frequency, especially with a rather low frequency; the boundary values of identification errors resulting from high-frequency sinusoidal noise of both frequency and damping factor can be adjusted by tuning the design parameters; and the different effects of the four design parameters on tracking performance and antinoise performance of each parameter identification. Simulation results demonstrate the performance of the algorithm and validate the conclusions.

show abstract

Amplitude and Frequency Estimation of Exponentially Decaying Sinusoids

Cited by 25 publications

References 23 publications

Analysis of Induction Motor Performance Using Motor Current Signature Analysis Technique

Analysis of Induction Motor Performance Using Motor Current Signature Analysis Technique

Measurement of the Parameters of Multiple Sinusoids Based on Binary Data

A Robust Direct Parameter Identification of Exponentially Damped Low-Frequency Oscillation in Power Systems

Contact Info

Product

Resources

About