Drivetrain Gearbox Fault Diagnosis: Vibration- and Current-Based Approaches

Jin, Xiaohang; Cheng, Fangzhou; Peng, Yayu; Wang, Qiao; Qu, Liyan

doi:10.1109/mias.2017.2740470

Cited by 30 publications

(17 citation statements)

References 22 publications

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“…As visible in Table 2, some papers related to this issue are not focused on electric motors, because a different component was the object of CM, but the system is based on an electric motor. Jin et al in 2018 [38] presented the results for a drive train gearbox fault diagnosis and concluded that in vibration signals ghost frequencies are fault sensitive, VS are modulated by shaft rotating frequencies, the fundamental frequency component is dominant in current signals and, at the fundamental frequency, they are modulated by gearbox characteristic frequencies when gear faults appear. Yang in 2015 [39] deduced from the experiments of an automatic condition monitoring for rolling-element bearings-based on vibrations as well as stator current analysis-that vibration analysis had powerful capability in the bearing point and fault severity diagnosis, whereas current analysis showed a moderate capability.…”

Section: Prospective Reviewmentioning

confidence: 99%

“…Hou_2021 [35] Ibarra-Zarate_2019 [42] Amini_2017 [36] Yoshioka_2010 [43] Yoshioka_2009 [44] Khan_2019 [45] Qu_2014 [37] Othman_2016 [46] Yi-Cheng_2016 [47] Bánlaki_2010 [48] Wu_2005 [49] Vibrations and current signals Yang_2015 [39] Jin_2018 [38] Immovilli_2010 [40] Wang_2016 [41] Combined vibration and thermal analysis…”

Section: Vibrations and Acoustic Emissions (Ae) Comparisonmentioning

confidence: 99%

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A Review on Vibration-Based Condition Monitoring of Rotating Machinery

et al. 2022

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Monitoring vibrations in rotating machinery allows effective diagnostics, as abnormal functioning states are related to specific patterns that can be extracted from vibration signals. Extensively studied issues concern the different methodologies used for carrying out the main phases (signal measurements, pre-processing and processing, feature selection, and fault diagnosis) of a malfunction automatic diagnosis. In addition, vibration-based condition monitoring has been applied to a number of different mechanical systems or components. In this review, a systematic study of the works related to the topic was carried out. A preliminary phase involved the analysis of the publication distribution, to understand what was the interest in studying the application of the method to the various rotating machineries, to identify the interest in the investigation of the main phases of the diagnostic process, and to identify the techniques mainly used for each single phase of the process. Subsequently, the different techniques of signal processing, feature selection, and diagnosis are analyzed in detail, highlighting their effectiveness as a function of the investigated aspects and of the results obtained in the various studies. The most significant research trends, as well as the main innovations related to the various phases of vibration-based condition monitoring, emerge from the review, and the conclusions provide hints for future ideas.

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Section: Prospective Reviewmentioning

confidence: 99%

Section: Vibrations and Acoustic Emissions (Ae) Comparisonmentioning

confidence: 99%

A Review on Vibration-Based Condition Monitoring of Rotating Machinery

et al. 2022

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“…From this, it follows that the characteristic frequencies are f m and 2 f m , there being a dc component in f m , 2 f m , 2( f m + f 1 ), etc. According to reference [55], when some type of failure occurs in the multipliers, a new impulse appears in the original spectrum or phase spectrum. For this reason, prior to using the FFT to obtain the spectrum, demodulation is applied (using the HT) to the current signal, demonstrating the effectiveness of this technique in the detection and diagnosis of pinions and broken teeth in the gearbox of a WT.…”

Section: Signal Processing Techniques Applied To Wind Turbine Failurementioning

confidence: 99%

“…By applying this methodology to the SCIG signal, Figure 8 is obtained. For our case, the MATLAB algorithm breaks down the signal into seven IMIs (Figure 8a), and proceeding as in reference [55], the HT of the first IMF is obtained (Figure 8b), to which other techniques can be applied, such as the FFT ( Figure 8c). In this last figure, the components associated with broken bars are much more evident.…”

Section: Appl Sci 2020 10 X For Peer Review 15 Of 29mentioning

confidence: 99%

Fault Detection of Wind Turbine Induction Generators through Current Signals and Various Signal Processing Techniques

et al. 2020

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In the wind industry (WI), a robust and effective maintenance system is essential. To minimize the maintenance cost, a large number of methodologies and mathematical models for predictive maintenance have been developed. Fault detection and diagnosis are carried out by processing and analyzing various types of signals, with the vibration signal predominating. In addition, most of the published proposals for wind turbine (WT) fault detection and diagnosis have used simulations and test benches. Based on previous work, this research report focuses on fault diagnosis, in this case using the electrical signal from an operating WT electric generator and applying various signal analysis and processing techniques to compare the effectiveness of each. The WT used for this research is 20 years old and works with a squirrel-cage induction generator (SCIG) which, according to the wind farm control systems, was fault-free. As a result, it has been possible to verify the feasibility of using the current signal to detect and diagnose faults through spectral analysis (SA) using a fast Fourier transform (FFT), periodogram, spectrogram, and scalogram.

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“…There is a known problem of occupational morbidity of the drivers of dump trucks [1][2][3], which is associated with over-vibration in the workplace. This requires a reduction in time of relay of the driver, but this is often impossible due to the organization of labor in the pit mine.…”

Section: Introductionmentioning

confidence: 99%

Problems of Operational Safety of Dump Trucks in Open Pit Mine

et al. 2019

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One of the risk factors for dump trucks drivers is the over-vibration on various parts and control units. This leads to the formation of high intensity of work. To search for the causes of over-vibration it is proposed to use vibration analysis methods. To search for the causes of over-vibration it is proposed to use vibration analysis methods in time when dump truck is not moving. This allows the escaping the influence of external factors such as like profile of the road, slope, etc. The analysis of the vibrational signal spectrum allows determining the type of defect with a high degree of reliability.

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Drivetrain Gearbox Fault Diagnosis: Vibration- and Current-Based Approaches

Cited by 30 publications

References 22 publications

A Review on Vibration-Based Condition Monitoring of Rotating Machinery

A Review on Vibration-Based Condition Monitoring of Rotating Machinery

Fault Detection of Wind Turbine Induction Generators through Current Signals and Various Signal Processing Techniques

Problems of Operational Safety of Dump Trucks in Open Pit Mine

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