Speed Estimation During the Starting Transient of Induction Motors

Meira, Matias; Bossio, Guillermo R.; Verucchi, Carlos; Ruschetti, Cristian; Bossio, José

doi:10.1109/tim.2020.3010039

Cited by 9 publications

(3 citation statements)

References 25 publications

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“…Therefore, filtering the signal to be studied is a good practice. Comb filters and multi-rate filters are the most common frequency-domain filters for removing harmonic interference [ 23 ].…”

Section: The Theory Of the Proposed Techniquementioning

confidence: 99%

“…In [ 19 ], flux estimation is employed to identify parameters that are independent of the speed of the observer’s output. In [ 23 ], model-based solutions are used to obtain accurate estimations in the high-speed range—an operation region where speed estimation is particularly challenging. The performance of the observers, and therefore the speed estimation in steady- and transient-states, is enhanced by speed estimation algorithms that are less susceptible to multi-parameter perturbations [ 24 ].…”

Section: Introductionmentioning

confidence: 99%

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Speed Estimation of Six-Phase Induction Motors, Using the Rotor Slot Harmonics

Laadjal

Bento

Antunes

et al. 2022

Sensors

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Multiphase machines have recently been promoted as a viable alternative to traditional three-phase machines. Most experts are looking for strategies to estimate the rotation speed of such complex systems, since speed data are required for high-performance control purposes. Traditionally, electromechanical sensors were used to detect the rotor speed of electric motors. These devices are extremely accurate, but they are also delicate and costly to deploy. New speed estimating algorithms must be created for these situations. This paper looks at how to estimate rotor speed in symmetrical six-phase induction motors (IMs) using a novel strategy for rotor speed estimation based on the Short Time Fourier Transform (STFT) method. The technique is based on tracking the frequencies of the rotor slot harmonics (RSH) seen in most squirrel-cage IM stator currents, thus assuring a broad range of applications. To monitor the RSH, the STFT employs a sliding window to perform the discrete Fourier transform technique, making it more suitable for online use with noisy and nonstationary signals. Experimental tests demonstrate the effectiveness of the suggested approach.

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Section: The Theory Of the Proposed Techniquementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Speed Estimation of Six-Phase Induction Motors, Using the Rotor Slot Harmonics

Laadjal

Bento

Antunes

et al. 2022

Sensors

View full text Add to dashboard Cite

show abstract

“…Other studies focused on the acquisition and analysis of motor currents for fault diagnosis purposes [20], and are also used to estimate the rotor speed [21][22][23]. The current of the stator is sampled and analysed to detect harmonic components that depend on the rotor speed.…”

Section: Introductionmentioning

confidence: 99%

Measurement of the Speed of Induction Motors Based on Vibration with a Smartphone

et al. 2022

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Induction motors are key pieces of equipment in today’s society, powering a variety of industrial drives and home appliances. The induction motor speed is often used to monitor the performance of all kinds of industrial drives. For example, in the industrial field, the motor speed is very often used to determine the efficiency and mechanical load of motors. In this work, a new simple, low-cost, and nonintrusive procedure is proposed for infield measurement of induction motors speed, which is based on the spectral analysis of the vibration signal of the motors. The motor vibration signal is first acquired using the accelerometers integrated into a basic phone. The acquired signal is then treated by a MATLAB-based algorithm, which can determine the motor speed by identifying the mechanical frequency of the rotor shaft from the harmonic content of the vibration signal. In this way, it is shown that the mechanical frequency corresponding to the speed of rotation of the motors can be acquired by means of the embedded accelerometers of a common smartphone, avoiding the acquisition and installation of external accelerometers. To the authors’ knowledge, this could be the first time that a smartphone has been proposed as a practical means of measuring the speed of a motor by analysing its vibration. Experimental results from an extensive set of tests, including the supply of the motor from a frequency converter, show that the speed can always be measured with a relative error of less than 0.15%.

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