A review on empirical mode decomposition in fault diagnosis of rotating machinery

Lei, Yaguo; Lin, Jing; He, Zhengjia; Zuo, Ming J.

doi:10.1016/j.ymssp.2012.09.015

Cited by 1,499 publications

(740 citation statements)

References 158 publications

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“…It seems that one of the emerging methods for transient signal processing is the empirical modal decomposition (EMD) [6]. The EMD method has focused considerable attention and has been indexed recently for power system fault detection and analysis [12][13].…”

Section: Eemd-based Voltage Sag Detection Techniquementioning

confidence: 99%

“…EEMD is mainly a signal processing technique to extract distinctive features; namely intrinsic mode functions (IMFs). Feature selection requires a series of calculations based on statistics such as maxima, minima, singular value, standard deviation, and mean [6]. The instantaneous power will be used as the electrical quantity for voltage sag detection.…”

Section: Introductionmentioning

confidence: 99%

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A smart grid voltage sag detector using an EEMD-based approach

Benbouzid

2013

2013 International Electric Machines &Amp; Drives Conference

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Abstract-Smart grids have become a focal point in renewable energy source researches. Sustainability and viability of distributed grids are highly dependent on the reduction of the operational and maintenance costs. The most efficient way of reducing these costs would be to continuously monitor the condition of these systems. This allows for early detection of the power quality degeneration, and facilitating a proactive response, prevent a fault ride-through the renewable energy conversion system, minimizing downtime, and maximizing productivity.This paper provides then the assessment of an advanced signal processing technique (demodulation tool) using the instantaneous power for voltage sags detection in smart grids.Index Terms-Smart grid, voltage sag detection, power quality (PQ), ensemble empirical mode decomposition (EEMD).

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Section: Eemd-based Voltage Sag Detection Techniquementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A smart grid voltage sag detector using an EEMD-based approach

Benbouzid

2013

2013 International Electric Machines &Amp; Drives Conference

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“…Rolling element bearings (REB) are widely used and the running health condition of the REB is of great importance to the operating stability and safety of the related machinery [1]. Therefore, study on the theory and method of the REB fault diagnosis has always been a hotspot in this research area.…”

Section: Introductionmentioning

confidence: 99%

Shock Pulse Index and Its Application in the Fault Diagnosis of Rolling Element Bearings

Sun¹,

Yuhe²,

Lin³

2017

Preprint

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Properties of time domain parameters of the vibration signal have been extensively studied for the fault diagnosis of rolling element bearings (REB). Parameters like kurtosis and Envelope Harmonic-to-Noise Ratio are most widely applied in this field and some important progress has been made. However, since only one-sided information is contained in these parameters respectively, problems still exist in practice when the signals collected are of complicated structure and/or contaminated by strong background noises. A new parameter, named Shock pulse index (SPI), is proposed in this paper. It integrates the mutual advantage of both parameters above and can help effectively identify fault related impulse components under the interference of strong background noises, unrelated harmonic components and random impulses. The SPI optimizes the parameters of Maximum Correlated Kurtosis Deconvolution (MCKD), which is used to filter the signals under consideration. Finally, the interested transient information contained in the filtered signal can be highlighted through demodulation with Teager Energy Operator (TEO). Fault related impulse components can therefore be extracted accurately. Simulations and experiment analyses verify the effectiveness and correctness of the SPI.

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“…However, owing to the thermal, electrical and mechanical stresses, mechanical failures are unavoidable in induction motors [2]. The need to increase reliability against possible faults has attracted considerable interest in fault diagnosis of induction motors in recent years [3,4]. The main aim of a condition monitoring system is to detect incipient faults before a potentially harmful machine failure occurs since a faulty motor means a reduction on production, a cost increase and a hazard to people and machinery [5,6].…”

Section: Introductionmentioning

confidence: 99%