A study of the effect of contaminant particles in lubricants using wear debris and vibration condition monitoring techniques

Peng, Zhongxiao; Kessissoglou, Nicole; Cox, Monica Farmer

doi:10.1016/j.wear.2004.11.020

Cited by 107 publications

(59 citation statements)

References 5 publications

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“…The width of the coil line is 100 m with 100 m line space and the thickness is 35 m. The debris is over the sensor. The debris is gathered in the oil and can be calculated as a metal ball [13]. So the shape of the debris is set as a ball whoes diameter is 150 m. The coil is covered with medium and its size is 9000 m×9000 m×9350 m (length×width×height).…”

Section: Model Establishment and Parameters Selectionmentioning

confidence: 99%

Research on the Detection of Metal Debris with Microplane Inductance Sensor

Liu

Zhang

Yude

et al. 2013

Advances in Mechanical Engineering

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The debris detection system is simulated and analyzed with the software of Maxwell 14 in this paper. The magnetic induction intensity and the magnetic density of the detection system with metal debris are simulated. The static experimental system is designed to measure the inductance caused by different metal debris. The simulation and experimental result indicate that the nonferromagnetic metal debris reduces the inductance of microplane inductance sensor and that ferromagnetic metal debris increases the inductance of microplane sensor. The detection of metal debris with microplane sensor is feasibly proved by the research. This paper provides a model for detecting the debris with a plane eddy current sensor and a case for the 3D simulation of the eddy current. This work may have some significance for improving the efficiency of the plane eddy current sensor.

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Section: Model Establishment and Parameters Selectionmentioning

confidence: 99%

Research on the Detection of Metal Debris with Microplane Inductance Sensor

Liu

Zhang

Yude

et al. 2013

Advances in Mechanical Engineering

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“…Troyer and Williamson (1999) concluded that correlation between the oil and vibration analysis techniques is generally good for both bearing and gear tooth fracture faults. Peng et al (2005) studied the effect of particles in gearbox lubricants, using WDA and vibration CM techniques, and investigated the correlation between them. Ebersbach et al (2006) investigated effectiveness of combining vibration anal-ysis and WDA techniques on gearboxes.…”

Section: Fluid Parametersmentioning

confidence: 99%

Review on Approaches for Condition Based Maintenance in Applications with Induction Machines located Offshore

Cibulka¹,

Ebbesen²,

Hovland³

et al. 2012

MIC

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This paper presents a review of different approaches for Condition Based Maintenance (CBM) of induction machines and drive trains in offshore applications. The paper contains an overview of common failure modes, monitoring techniques, approaches for diagnostics, and an overview of typical maintenance actions. Although many papers have been written in this area before, this paper puts an emphasis on recent developments and limits the scope to induction machines and drive trains applied in applications located offshore.

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“…This makes grease or oil monitoring unsuitable for wheelset bearing fault detection. The attenuation of transient elastic waves generated by a bearing fault restricts wide application of acoustic emission techniques in bearing fault detection [2]. Hotbox detection is commonly used in practice.…”

Section: Introductionmentioning

confidence: 99%

Fault Detection of High-Speed Train Wheelset Bearing Based on Impulse-Envelope Manifold

Zhuang

Ding

Tan

et al. 2017

Shock and Vibration

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A novel fault detection method employing the impulse-envelope manifold is proposed in this paper which is based on the combination of convolution sparse representation (CSR) and Hilbert transform manifold learning. The impulses with different sparse characteristics are extracted by the CSR with different penalty parameters. The impulse-envelope space is constructed through Hilbert transform on the extracted impulses. The manifold based on impulse-envelope space (impulse-envelope manifold) is executed to learn the low-dimensionality intrinsic envelope of vibration signals for fault detection. The analyzed results based on simulations, experimental tests, and practical applications show that (1) the impulse-envelope manifold with both isometric mapping (Isomap) and locally linear coordination (LLC) can be successfully used to extract the intrinsic envelope of the impulses where local tangent space analysis (LTSA) fails to perform and (2) the impulse-envelope manifold with Isomap outperforms those with LLC in terms of strengthening envelopes and the number of extracted harmonics. The proposed impulse-envelope manifold with Isomap is superior in extracting the intrinsic envelope, strengthening the amplitude of intrinsic envelope spectra, and enlarging the harmonic number of fault-characteristic frequency. The proposed technique is highly suitable for extracting intrinsic envelopes for bearing fault detection.

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A study of the effect of contaminant particles in lubricants using wear debris and vibration condition monitoring techniques

Cited by 107 publications

References 5 publications

Research on the Detection of Metal Debris with Microplane Inductance Sensor

Research on the Detection of Metal Debris with Microplane Inductance Sensor

Review on Approaches for Condition Based Maintenance in Applications with Induction Machines located Offshore

Fault Detection of High-Speed Train Wheelset Bearing Based on Impulse-Envelope Manifold

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