Application of the STFT for Detection of the Rotor Unbalance of a Servo-Drive System with an Elastic Interconnection

Ewert, Pawel; Wicher, Bartłomiej; Pajchrowski, Tomasz

doi:10.3390/electronics13020441

Electronics

2024

DOI: 10.3390/electronics13020441

|View full text |Cite

Application of the STFT for Detection of the Rotor Unbalance of a Servo-Drive System with an Elastic Interconnection

Pawel Ewert,

Bartłomiej Wicher,

Tomasz Pajchrowski

Abstract: The article focuses on the use of short-time Fourier transform (STFT) to detect the unbalance of a drive with a flexible connection between the driving machine and the load. The authors present the unbalance model and justify, through subsequent experiments, why the STFT-based approach is appropriate. The effectiveness of the presented method of analyzing signals from acceleration sensors was confirmed experimentally by designing an artificial neural network for detecting the unbalance.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article2

Relationship

Self Cite0

Independent2

Authors

Journals

Cited by 2 publications

References 54 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Sensorless Detection of Mechanical Unbalance in Servodrive with Elastic Coupling

Ewert,

Pajchrowski,

Wicher

2024

Energies

View full text Add to dashboard Cite

The article focusses on detecting the unbalance of a mechanical component in the electric drive system of a two-mass servomechanism with a permanent magnet synchronous motor (PMSM), which is connected to the load via a long, flexible shaft. In the example analysed, the degree of unbalance was determined using the reference current signal from the speed controller of the field-orientated control (FOC) system. The authors presented a two-mass model with an unbalanced mechanical system. The short-time Fourier transform (STFT) transform was used to analyse the symptoms of unbalance, and an artificial neural network multi-layer perceptron (MLP) was used for system state inference. The effectiveness of the presented analysis, based on the reference current signal from the sensor embedded in the control system, was experimentally confirmed.

show abstract

Sensorless Detection of Mechanical Unbalance in Servodrive with Elastic Coupling

Ewert,

Pajchrowski,

Wicher

2024

Energies

View full text Add to dashboard Cite

show abstract

Advanced Data Augmentation Techniques for Enhanced Fault Diagnosis in Industrial Centrifugal Pumps

Kim,

Kareem,

Domingo

et al. 2024

JSAN

View full text Add to dashboard Cite

This study presents an advanced data augmentation framework to enhance fault diagnostics in industrial centrifugal pumps using vibration data. The proposed framework addresses the challenge of insufficient defect data in industrial settings by integrating traditional augmentation techniques, such as Gaussian noise (GN) and signal stretching (SS), with advanced models, including Long Short-Term Memory (LSTM) networks, Autoencoders (AE), and Generative Adversarial Networks (GANs). Our approach significantly improves the robustness and accuracy of machine learning (ML) models for fault detection and classification. Key findings demonstrate a marked reduction in false positives and a substantial increase in fault detection rates, particularly in complex operational scenarios where traditional statistical methods may fall short. The experimental results underscore the effectiveness of combining these augmentation techniques, achieving up to a 30% improvement in fault detection accuracy and a 25% reduction in false positives compared to baseline models. These improvements highlight the practical value of the proposed framework in ensuring reliable operation and the predictive maintenance of centrifugal pumps in diverse industrial environments.

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Application of the STFT for Detection of the Rotor Unbalance of a Servo-Drive System with an Elastic Interconnection

Cited by 2 publications

References 54 publications

Sensorless Detection of Mechanical Unbalance in Servodrive with Elastic Coupling

Sensorless Detection of Mechanical Unbalance in Servodrive with Elastic Coupling

Advanced Data Augmentation Techniques for Enhanced Fault Diagnosis in Industrial Centrifugal Pumps

Contact Info

Product

Resources

About