Chaos theory using density of maxima applied to the diagnosis of three-phase induction motor bearings failure by sound analysis

Lucena-Junior, Jose Anselmo; Lima, Thyago Leite de Vasconcelos; Bruno, Genildo Bandeira; Brito, Alisson V.; Ramos, J. Galvão; Belo, Francisco Antônio; Filho, Abel Cavalcante Lima

doi:10.1016/j.compind.2020.103304

Cited by 27 publications

(16 citation statements)

References 37 publications

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“…Wavelet is a powerful mathematical tool that has been used for decades in the field of signal processing, allowing hybrid time/frequency domain analyses, and has already been tried in the diagnosis of combustion engine failures, obtaining satisfactory results [ 12 , 13 ]. The SAC-DM technique was applied for the first time to diagnose faults in mechanical systems recently with good results [ 2 , 3 ].…”

Section: State Of the Artmentioning

confidence: 99%

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Misfire Detection in Automotive Engines Using a Smartphone through Wavelet and Chaos Analysis

Rodrigues

Brito

Ramos

et al. 2022

Sensors

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Besides the failures that cause accidents, there are the ones responsible for preventing the car’s motion capacity. These failures cause inconveniences to the passengers and expose them to the dangers of the road. Although modern vehicles are equipped with a failure detection system, it does not provide an online approach to the drivers. Third-party devices and skilled labor are necessary to manage the data for failure characterization. One of the most common failures in engines is called misfire, and it happens when the spark is weak or inexistent, compromising the whole set. In this work, two algorithms are compared, based on Wavelet Multiresolution Analysis (WMA) and another using an approach performing signal analysis based on Chaos using the density of maxima (SAC-DM) to identify misfare in a combustion engine of a working automotive vehicle. Experimental tests were carried out in a car to validate the techniques for the engine without failure, with failure in one piston, and with two failed pistons. The results made it possible to obtain the failure diagnosis for 100% of the cases for both WMA and SAC-DM methods, but a shorter time window when using the last one.

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Section: State Of the Artmentioning

confidence: 99%

“…This work proposes a practical model for misfire diagnosis in internal combustion engines through the vibration signal of a smartphone accelerometer comparing two data processing techniques: Wavelet Multiresolution Analysis (WMA) and the SAC-DM (Signal Analysis based on Chaos using Density of Maxima [ 2 , 3 ].…”

Section: Introductionmentioning

confidence: 99%

Misfire Detection in Automotive Engines Using a Smartphone through Wavelet and Chaos Analysis

Rodrigues

Brito

Ramos

et al. 2022

Sensors

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“…Technological applications of the method have also been established in different scenarios of mechatronic engineering (drones and electric motors). The applications include a wide field of study [30][31][32]. For example, in some critical scenarios, mechanical failures can cause operational disasters when using mechanical equipment.…”

Section: Outlook and Conclusionmentioning

confidence: 99%

Mesoscopic Fluctuations: Nuclei, Quantum Dots, and Beyond

et al. 2020

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“…Rotary machines, such as induction motors (IM), have become essential tools for industrial processes due to their low cost and ruggedness [1]. These machines undergo different types of failures associated with the rotor, the stator, or the bearings due to distinct operational circumstances.…”

Section: Introductionmentioning

confidence: 99%

Broken Rotor Bar Detection in Induction Motors through Contrast Estimation

Ferrucho-Alvarez

Martinez-Herrera

Cabal-Yépez

et al. 2021

Sensors

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Induction motors (IM) are key components of any industrial process; hence, it is important to carry out continuous monitoring to detect incipient faults in them in order to avoid interruptions on production lines. Broken rotor bars (BRBs), which are among the most regular and most complex to detect faults, have attracted the attention of many researchers, who are searching for reliable methods to recognize this condition with high certainty. Most proposed techniques in the literature are applied during the IM startup transient, making it necessary to develop more efficient fault detection techniques able to carry out fault identification during the IM steady state. In this work, a novel methodology based on motor current signal analysis and contrast estimation is introduced for BRB detection. It is worth noting that contrast has mainly been used in image processing for analyzing texture, and, to the best of the authors’ knowledge, it has never been used for diagnosing the operative condition of an induction motor. Experimental results from applying the approach put forward validate Unser and Tamura contrast definitions as useful indicators for identifying and classifying an IM operational condition as healthy, one broken bar (1BB), or two broken bars (2BB), with high certainty during its steady state.

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Chaos theory using density of maxima applied to the diagnosis of three-phase induction motor bearings failure by sound analysis

Cited by 27 publications

References 37 publications

Misfire Detection in Automotive Engines Using a Smartphone through Wavelet and Chaos Analysis

Misfire Detection in Automotive Engines Using a Smartphone through Wavelet and Chaos Analysis

Mesoscopic Fluctuations: Nuclei, Quantum Dots, and Beyond

Broken Rotor Bar Detection in Induction Motors through Contrast Estimation

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