Monitoring of journal bearing faults based on motor current signature analysis for induction motors

Jung, Junyeong; Yonghyun, Park; Lee, Sang Bin; Cho, Changhee; Kim, Kwon-Hee; Wiedenbrug, E.; Teska, Mike

doi:10.1109/ecce.2015.7309702

Cited by 13 publications

(6 citation statements)

References 15 publications

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“…In the past, several strategies for condition monitoring have been employed to detect defects in electrical machinery. A few of these techniques are outlined here [62][63][64][65][66][67][68][69][70]:…”

Section: Traditional Types Of Condition Monitoringmentioning

confidence: 99%

“…Since vibration analysis can reveal important details regarding the condition of electrical machinery, it is frequently employed in diagnostic settings. To illustrate the variation in the fundamental frequency component as a fault indicator, the authors in [66] utilize vibration signals from healthy and defective bearings to locate particular frequencies on the Fourier transform spectrum, as shown in Figure 9. It is standard procedure to combine conventional approaches with intelligent ones.…”

Section: Vibration Analysismentioning

confidence: 99%

“…The process eral parts: resistance, the angle of phase, current response (CR), frequency respon and comparable impedance, inductance, and ground faults. In the past, several st for condition monitoring have been employed to detect defects in electrical mach few of these techniques are outlined here [62][63][64][65][66][67][68][69][70]:…”

mentioning

confidence: 99%

“…Neighbor finding, k-means, and a back-propagation neural network were all employed in the classification process. Thermal imaging was used in a study in [66] to determine environmental temperatures with positive and accurate measurable outcomes. The authors of [67] suggest using thermal pictures for defect diagnosis and for the application of several smart algorithms for model training.…”

mentioning

confidence: 99%

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State-of-the-Art Techniques for Fault Diagnosis in Electrical Machines: Advancements and Future Directions

Akbar,

Vaimann,

Asad

et al. 2023

Energies

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Electrical machines are prone to various faults and require constant monitoring to ensure safe and dependable functioning. A potential fault in electrical machinery results in unscheduled downtime, necessitating the prompt assessment of any abnormal circumstances in rotating electrical machines. This paper provides an in-depth analysis as well as the most recent trends in the application of condition monitoring and fault detection techniques in the disciplines of electrical machinery. It first investigates the evolution of traditional monitoring techniques, followed by signal-based techniques such as spectrum, vibration, and temperature analysis, and the most recent trends in its signal processing techniques for assessing faults. Then, it investigates and details the implementation and evolution of modern approaches that employ intelligence-based techniques such as neural networks and support vector machines. All these applicable and state-of-art techniques in condition monitoring and fault diagnosis aid in predictive maintenance and identification and have the highly reliable operation of a motor drive system. Furthermore, this paper focuses on the possible transformational impact of electrical machine condition monitoring by thoroughly analyzing each of the monitoring techniques, their corresponding pros and cons, their approaches, and their applicability. It offers strong and useful insights into proactive maintenance measures, improved operating efficiency, and specific recommendations for future applications in the field of diagnostics.

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Section: Traditional Types Of Condition Monitoringmentioning

confidence: 99%

Section: Vibration Analysismentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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State-of-the-Art Techniques for Fault Diagnosis in Electrical Machines: Advancements and Future Directions

Akbar,

Vaimann,

Asad

et al. 2023

Energies

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show abstract

“…This optimization was strictly followed by Kim et al (2007a, 2007b, 2007c), Grisso and Inman (2008), and Panigrahi et al (2009). However, when the research topic is narrowed into damage detection of rotating structures during the operation (Ayes et al, 2005; Brouckaert, 2007; Campbell, 1924; Chen et al, 2012; Dąbrowski et al, 1996; Hardigg and Swarthmore, 1951; Jung et al, 2015; Kending et al, 1990, 1996; Kuzmenko, 1998; Mironov et al, 2016; Robinson, 1972; Shelke et al, 2016; Sieverding and Mathioudakis, 2003; Szczepankowski, 1999; Tandon and Parey, 2006; Twerdochlib et al, 1992; Washburn, 2004; Witos, 2011, 2013; Witos and Szczepanik, 2009; Witos and Wachlaczenko, 2015; Yaghouti et al, 2012; Zablotsky et al, 1969; Zhang, 2013), the conventional transducers and data acquisition hardware seem a little more problematic. Tandon and Parey (2006) proffered monitoring of several parameters—vibration, temperature, driving motor current, wear debris in oil, acoustic emission, shock pulse, and so on—as the most important health parameters of rotary machines to detect any deteriorations in the machine condition.…”

Section: Introductionmentioning

confidence: 99%

Structural health monitoring of rotary aerospace structures based on electromechanical impedance of integrated piezoelectric transducers

Hoshyarmanesh

Abbasi

2018

Journal of Intelligent Material Systems and Structures

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Structural health monitoring of rotary aerospace structures is investigated in this research. A monitoring system is proposed based on the electromechanical impedance spectrum of piezoelectric transducers and a portable transceiver. To investigate the applicability and preliminary results of this method, a turbomachine prototype (laboratory device) is developed, and integrated composite piezoelectric films are deposited on the blades. Next, a self-diagnostic characterization is initially implemented to the piezo-films. Transceiver functionality and accuracy is verified using an Ivium impedance analyzer. The verified measuring path was used in structural health monitoring of pristine and damaged blades at rotational speed of 0 and 1000 r/min. The effects of damage formation and rotational speed on the impedance signature are discussed based on the variations in mechanical impedance using a two-dimensional model. Once damage occurs in a blade at each speed, it results in a frequency shift of the impedance signature at antiresonance peaks compared to the corresponding baseline. The results show a clear frequency shift of existing peaks and the appearance of new peaks as damage grows to a secure minimal detectable size. This achievement confirms the applicability of this method for incipient damage detection on rotary structures prior to any failure.

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A M-EKF fault detection strategy of insulation system for marine current turbine

Wang

Liu

Zhang

et al. 2019

Mechanical Systems and Signal Processing

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Monitoring of journal bearing faults based on motor current signature analysis for induction motors

Cited by 13 publications

References 15 publications

State-of-the-Art Techniques for Fault Diagnosis in Electrical Machines: Advancements and Future Directions

State-of-the-Art Techniques for Fault Diagnosis in Electrical Machines: Advancements and Future Directions

Structural health monitoring of rotary aerospace structures based on electromechanical impedance of integrated piezoelectric transducers

A M-EKF fault detection strategy of insulation system for marine current turbine

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