A Machine Learning Based Methodology for Fault Diagnosis in Rotating Machine

Madhukar, G; Boosi, Shyamala; Adhoni, Zameer Ahmed; Bhaskar, K Aruna; Naik, Ashitha V

doi:10.1109/icicacs57338.2023.10100301

Cited by 3 publications

(3 citation statements)

References 14 publications

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“…Machine failures often occur due to continuous operation and various cyclic loading situations. This process leads to gradual wear of components, which increases the risk of failure [2]. This wear of machine components can be considered normal and is a consequence of machine operation.…”

Section: Introductionmentioning

confidence: 99%

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A Review on Vibration Monitoring Techniques for Predictive Maintenance of Rotating Machinery

Romanssini

Aguirre

Severo

et al. 2023

Eng

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Machine failure in modern industry leads to lost production and reduced competitiveness. Maintenance costs represent between 15% and 60% of the manufacturing cost of the final product, and in heavy industry, these costs can be as high as 50% of the total production cost. Predictive maintenance is an efficient technique to avoid unexpected maintenance stops during production in industry. Vibration measurement is the main non-invasive method for locating and predicting faults in rotating machine components. This paper reviews the techniques and tools used to collect and analyze vibration data, as well as the methods used to interpret and diagnose faults in rotating machinery. The main steps of this technique are discussed, including data acquisition, data transmission, signal processing, and fault detection. Predictive maintenance through vibration analysis is a key strategy for cost reduction and a mandatory application in modern industry.

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Section: Introductionmentioning

confidence: 99%

“…Eng 2023, 4 monitoring, current monitoring, oil and debris monitoring, and corrosion monitoring. Each technique has its proper characteristic of application and use [2][3][4].…”

Section: Introductionmentioning

confidence: 99%

A Review on Vibration Monitoring Techniques for Predictive Maintenance of Rotating Machinery

Romanssini

Aguirre

Severo

et al. 2023

Eng

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“…The vibration signal of BHA is the key to analyzing the real downhole working condition. Also, the measured vibration signals can be used for anomaly detection and fault diagnosis [6][7][8]. The theoretical analysis results have some limitations and cannot reflect the real situation of downhole vibration well [4][5].…”

Section: Introductionmentioning

confidence: 99%

A High-Frequency Measurement Method of Downhole Vibration Signal Based on Compressed Sensing Technology and Its Application in Drilling Tool Failure Analysis

Lyu,

Wang,

Mei

et al. 2023

IEEE Access

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The high-frequency information of downhole vibration can record more specific details about the dynamic response of bottom hole assembly (BHA), which is conducive to analyzing downhole abnormal vibration and diagnosing drilling tool failure. However, high frequency measurements would generate a large amount of data, which is a huge challenge for data storage. To cope with this challenge, this work proposes applying compressive sensing theory to high-frequency measurement of downhole vibration signals and failure analysis of drilling tools. First, three ADCs clocked at different sub-Nyquist frequencies are used to collect and store downhole vibration signals. Then, the stored sparse vibration data is reconstructed into complete vibration signal by an improved OMP signal reconstruction algorithm. The performance of the proposed method has been investigated via a series of experiments by applying simulation and real vibration signals, which show that the proposed method can reconstruct the downhole vibration signal well and significantly reduce the pressure of acquisition and data storage. This method provides a new way to obtain the high-frequency measurement data of downhole vibration, and provides a data basis for further mastering the comprehensive law of downhole vibration, diagnosing abnormal downhole vibration, and drilling tool failure.INDEX TERMS Downhole vibration measurement, Compressed sensing, Drilling tool failure.

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Enhancing Predictive Maintenance in Manufacturing: A CNN-LSTM Hybrid Approach for Reliable Component Failure Prediction

Al-Said,

Findik,

Assanova

et al. 2024

Studies in Systems, Decision and Control

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A Machine Learning Based Methodology for Fault Diagnosis in Rotating Machine

Cited by 3 publications

References 14 publications

A Review on Vibration Monitoring Techniques for Predictive Maintenance of Rotating Machinery

A Review on Vibration Monitoring Techniques for Predictive Maintenance of Rotating Machinery

A High-Frequency Measurement Method of Downhole Vibration Signal Based on Compressed Sensing Technology and Its Application in Drilling Tool Failure Analysis

Enhancing Predictive Maintenance in Manufacturing: A CNN-LSTM Hybrid Approach for Reliable Component Failure Prediction

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