Short-Time/-Angle Spectral Analysis for Vibration Monitoring of Bearing Failures under Variable Speed

Sierra-Alonso, Edgar F.; Caicedo-Acosta, Julian; Gutiérrez, Álvaro Ángel Orozco; Riaza, Héctor Fabio Quintero; Castellanos-Domínguez, G.

doi:10.3390/app11083369

Cited by 9 publications

(5 citation statements)

References 35 publications

(34 reference statements)

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“…Moreover, Feng et al [29] and Brusa et al [30] used signal demodulation by envelope analysis to extract characteristic fault frequencies. On the other hand, some authors have used tools such as spectrograms [31,32], kurtograms [33] or bispectra [33,34] to detect the presence of transient events in a signal.…”

Section: Introductionmentioning

confidence: 99%

Bearing Severity Fault Evaluation Using Contour Maps—Case Study

et al. 2021

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Increasing industrial competitiveness has led to an increased global interest in condition monitoring. In this sector, rotating machinery plays an important role, where the bearing is one of the most critical components. Many vibration-based signal treatments are already being used to identify features associated with bearing faults. The information embedded in such features are employed in the construction of health indicators, which allow for evaluation of the current operating status of the machine. In this work, the use of contour maps to represent the diagnosis map of a bearing, used as a health map, is presented for the first time. The results show that the proposed method is promising, allowing for the satisfactory detection and evaluation of the severity of bearing damage. In this initial stage of the research, our results suggest that this method can improve the classification of bearing faults and, therefore, optimise maintenance processes.

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Section: Introductionmentioning

confidence: 99%

Bearing Severity Fault Evaluation Using Contour Maps—Case Study

et al. 2021

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“…This realization of the vibration signal can be described as a sequence of measured samples {x i } n i=1 . The authors in [40,41] designed a special acoustic sensor device for the qualitative research and monitoring of technological equipment.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

Application of Cluster Analysis for Classification of Vibration Signals from Drilling Stand Aggregates

et al. 2023

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Rotary drilling technology with diamond tools is still essential in progressively extracting the earth’s resources. Since investigating the disintegration mechanism in actual conditions is very difficult, the practice must start with laboratory research. Identifying and classifying the drilling stand and its aggregates as objects will contribute to the clarification of certain problems related to streamlining the process, optimizing the working regime, preventing emergencies, and reducing energy and economic demands. For these purposes, the cluster method was designed and applied. Applying the clustering method has a significant place in complex and dynamic processes. Eight vibration signals were measured and processed during the operation of the aggregates, such as the motor, pump, and hydrogenerator, with a sampling frequency of 18 kHz and a time interval of 30 s. Subsequently, 16 symptoms were designed and numerically calculated in the time and frequency domain, creating the symptom vector of the aggregate. The aim of the study and article was the classification of aggregates as objects into recognizable clusters. The results show that the strong symptoms include a measure of variability, variance in the signal, and kurtosis. The weak symptoms are skewness and the moment of the signal spectrum. Visualization in the symptom plane and space proved their influence on cluster formation. According to the cluster analysis results, six to seven clusters presenting the activity of the aggregates were classified. It was found that the boundaries between the clusters were not sharp. As part of the research, the centroids of clusters of aggregates and the distances between them were calculated. Classified clusters can rebuild reference clusters for objects with a similar character in a broader context.

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“…Techniques exploiting classical envelope analysis for detecting bearing faults by utilizing transient signals are present in the literature. In [29], an enhanced envelope analysis is suggested by utilizing spectral kurtosis emphasizing impulsive components. In [30], a general demodulation based on fault instantaneous frequencies acquisition is utilized.…”

Section: Introductionmentioning

confidence: 99%

Comprehensive Diagnosis of Localized Rolling Bearing Faults during Rotating Machine Start-Up via Vibration Envelope Analysis

Ruiz-Sarrio,

Antonino-Daviu,

Martis

2024

Electronics

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The analysis of electrical machine faults during start-up, and variable speed and load conditions offers numerous advantages for fault detection and diagnosis. In this context, diagnosing localized bearing faults through vibration signals remains challenging, particularly in developing physically meaningful, simple, and resampling-free techniques to monitor fault characteristic components throughout machine start-up. This study introduces a straightforward method for qualitatively identifying the time-frequency evolutions of localized bearing faults during the start-up of an inverter-fed machine. The proposed technique utilizes the time-frequency representation of the envelope spectrum, effectively highlighting characteristic fault frequencies during transient operation. The method is tested in an open-source dataset including transient vibration signals. In addition, the work studies the method limitations induced by the mechanical transfer path, when the bearing surroundings are not directly accessible for vibration acquisition. The proposed methodology efficiently identifies incipient localized bearing faults during inverter-fed machine start-up when the fault signature is not highly attenuated.

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Short-Time/-Angle Spectral Analysis for Vibration Monitoring of Bearing Failures under Variable Speed

Cited by 9 publications

References 35 publications

Bearing Severity Fault Evaluation Using Contour Maps—Case Study

Bearing Severity Fault Evaluation Using Contour Maps—Case Study

Application of Cluster Analysis for Classification of Vibration Signals from Drilling Stand Aggregates

Comprehensive Diagnosis of Localized Rolling Bearing Faults during Rotating Machine Start-Up via Vibration Envelope Analysis

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