Benefits of enhanced techniques combining negentropy, spectral correlation and kurtogram for bearing fault diagnosis

Ugwiri, Moise Avoci; Carratù, Marco; Paciello, Vincenzo; Liguori, Consolatina

doi:10.1016/j.measurement.2021.110013

Cited by 12 publications

(6 citation statements)

References 42 publications

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“…Understanding and analyzing the transfer function in this context allows engineers and researchers to improve drive system performance and efficiency, as well as reduce energy consumption and wear and tear on equipment, which is essential for today's technological and environmental requirements. According to M. A. Ugwiri et al [34], vibration and current characteristics measurements play a vital role in detecting faults in induction motors. Vibration is a sensitive indicator of the machine's condition, enabling the detection of problems in the mechanical part of the engine.…”

Section: Discussionmentioning

confidence: 99%

Diagnostics of Damage to the Rotor of an Induction Machine Using the Method of Instantaneous Power Analysis

Puka,

Bardhi,

Pjetri

et al. 2024

QAJ

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The relevance of the problem under study is that in the modern world, where induction machines are widely used in industry, early detection of rotor damage using the method of instantaneous power analysis is critical to maintaining uninterrupted equipment operation and reducing operating costs. The purpose of this study is to investigate and determine the effectiveness of the method of instantaneous power analysis for diagnosing rotor damage in induction machines to improve their reliability and reduce the risk of production failures. The methods used include the analytical method, classification method, functional method, statistical method, synthesis method. In today’s industry, asynchronous machines play a central role, creating a high demand for their reliable and safe operation. Malfunctions and failures in the operation of these machines can lead to serious downtime and considerable losses that affect the financial position of the company. One method of accurate fault diagnosis is to analyses the theoretical components added to the motor current. The analysis revealed that the locus of the space vector, instantaneous power, and sideband frequencies around the fundamental frequency indicate possible broken rotor cores of an induction machine. These components become key indicators for fault detection in induction machines. Furthermore, the experiments on a three-phase squirrel-cage induction confirmed the theoretical analysis, reinforcing the practical significance of the developed methodology for early diagnosis and improving equipment reliability, as well as reducing maintenance and repair costs. The practical significance lies in the development of a methodology that can be used in the industry for early diagnosis of rotor damage in induction machines, ensuring increased equipment reliability and reduced maintenance and repair costs.

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Section: Discussionmentioning

confidence: 99%

Diagnostics of Damage to the Rotor of an Induction Machine Using the Method of Instantaneous Power Analysis

Puka,

Bardhi,

Pjetri

et al. 2024

QAJ

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show abstract

“…Spectral correlation, as a powerful tool in the field of condition monitoring, has been successfully applied to the fault diagnosis of rolling bearings [21][22][23]. The spectral correlation algorithm yields a two-dimensional plot with spectral and cyclic frequencies as horizontal and vertical axes.…”

Section: Introductionmentioning

confidence: 99%

An improved envelope spectrum via Hoyer index-gram for bearing fault extraction

Tian,

Tang,

Wang

et al. 2024

Meas. Sci. Technol.

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Resonance demodulation is one of the most commonly used methods in rolling bearing fault diagnosis, yet determining the optimal demodulation band has been a significant challenge. The vibration signal from a faulty bearing may include not only periodic fault impulses but also discrete harmonic interferences, random impulses, Gaussian white noise, among others. To enhance fault information and attenuate the impact of interference signals, this paper proposes an Improved Envelope Spectrum via Hoyer Index-gram (IESHoyergram). By utilizing the Hoyer index of the spectrum-related enhanced envelope spectrum as the frequency band filtering criterion, the proposed method extracts periodic impulses while suppressing interference from random impulses and other sources. Moreover, owing to the multilevel segmentation based on the different trend components in the spectral correlation spectrogram, IESHoyergram avoids the shortcomings of traditional segmentation methods. The proposed method is validated through both simulated and experimentally acquired data, demonstrating its capability not only to enhance the characteristics of a single fault but also to separate multiple component faults.

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“…Rolling bearings are one of the crucial components in rotating machinery such as wind turbines and gas turbines, playing a vital role in their overall performance. Their failure can lead to significant mechanical breakdowns and economic losses, and in severe cases, may even jeopardize human safety [1,2]. However, varying operating conditions render the bearing vibration signals non-stationary, thereby complicating the early detection of failures.…”

Section: Introductionmentioning

confidence: 99%

“…Finally, they analyzed gear faults using the squared envelope spectrum. Ugwiri et al [2] presents a novel approach for detecting repetitive transients in rotating machines using the negentropy of signal envelopes and spectral analysis, improving fault diagnosis. By combining timefrequency techniques with thermodynamic principles, it offers a more effective method for identifying and localizing faults.…”

Section: Introductionmentioning

confidence: 99%

Fault feature extraction method based on maximum envelope spectrum PFGI2 and empirical wavelet transform

Tian,

Tang,

Liu

et al. 2024

Meas. Sci. Technol.

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Fast Kurtogram (FK) is an efficient method for processing non-stationary signals, widely recognized by scholars as a rapid and effective approach for fault diagnosis. However, it has limitations in distinguishing between periodic pulse and random interference pulses due to the drawbacks in its frequency band segmentation methods and the inherent shortcomings of the kurtosis index itself. To address this, this paper proposes a fault feature extraction method based on the maximum envelope spectrum power function-based Gini indices (PFGI2) and empirical wavelet transform (EWT). This method, inspired by the concept of Fast Kurtogram, constructs a series of band-pass filters following the principles of empirical wavelet decomposition. It applies envelope spectrum analysis to a series of sub-bands and calculates the PFGI2 value for each, to identify the optimal sub-band. The effectiveness of the proposed method is validated through simulations of vibration signals and experimental data.

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Benefits of enhanced techniques combining negentropy, spectral correlation and kurtogram for bearing fault diagnosis

Cited by 12 publications

References 42 publications

Diagnostics of Damage to the Rotor of an Induction Machine Using the Method of Instantaneous Power Analysis

Diagnostics of Damage to the Rotor of an Induction Machine Using the Method of Instantaneous Power Analysis

An improved envelope spectrum via Hoyer index-gram for bearing fault extraction

Fault feature extraction method based on maximum envelope spectrum PFGI2 and empirical wavelet transform

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