Acoustic Emission Monitoring of Mechanical Seals Using MUSIC Algorithm Based on Higher Order Statistics

Fan, Yi Bo; Gu, Fengshou; Ball, Andrew

doi:10.4028/www.scientific.net/kem.413-414.811

Cited by 15 publications

(10 citation statements)

References 5 publications

(7 reference statements)

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“…For mechanical seal, the AE occurs when the equipment is distorted, being rubbed or under collision. In order to extract Fan et al have processed the AE signal by multiple signal classification with higher order statistics (HOS-MUSIC) [12] and extracted the information about seal end faces under noisy condition. But in his case, the noise circumstance is artificial, and the paper's focus is not on the state monitoring of the seal end faces.…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

The Contact State Monitoring for Seal End Faces Based on Acoustic Emission Detection

Chen³

et al. 2016

Shock and Vibration

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Monitoring the contact state of seal end faces would help the early warning of the seal failure. In the acoustic emission (AE) detection for mechanical seal, the main difficulty is to reduce the background noise and to classify the dispersed features. To solve these problems and achieve higher detection rates, a new approach based on genetic particle filter with autoregression (AR-GPF) and hypersphere support vector machine (HSSVM) is presented. First, AR model is used to build the dynamic state space (DSS) of the AE signal, and GPF is used for signal filtering. Then, multiple features are extracted, and a classification model based on HSSVM is constructed for state recognition. In this approach, AR-GPF is an excellent time-domain method for noise reduction, and HSSVM has advantage on those dispersed features. Finally experimental data shows that the proposed method can effectively detect the contact state of the seal end faces and has higher accuracy rates than some other existing methods.

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Section: Related Workmentioning

confidence: 99%

“…But for seal, there are very few successful cases. The most major problem of this method is difficult to isolate the seal signal from background noise [10,11], and this makes the existing methods cannot work well in practice [12][13][14].…”

Section: Introductionmentioning

confidence: 99%

The Contact State Monitoring for Seal End Faces Based on Acoustic Emission Detection

Chen³

et al. 2016

Shock and Vibration

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“…By processing the whole sensor array outputs using the MUSIC algorithm, the transfer function and material properties of the structure are not needed [5]. Since the MUSIC algorithm belongs to an eigen-structure and sub-space approach, it can effectively extract the key features of signals received and successfully detect the source signal under a low signal-to-noise ratio [6]. Some developments have been published by applying this method to process the sensor array signals in the structural health monitoring area.…”

Section: Introductionmentioning

confidence: 99%

Multiple Signal Classification-Based Impact Localization in Composite Structures Using Optimized Ensemble Empirical Mode Decomposition

Zhong

Xiang

Chen³

et al. 2018

Applied Sciences

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Multiple signal classification (MUSIC) algorithm-based structural health monitoring technology is a promising method because of its directional scanning ability and easy arrangement of the sensor array. However, in previous MUSIC-based impact location methods, the narrowband signals at a particular central frequency had to be extracted from the wideband Lamb waves induced by each impact using a wavelet transform. Additionally, the specific center frequency had to be obtained after carefully analyzing the impact signal, which is time consuming. Aiming at solving this problem, this paper presents an improved approach that combines the optimized ensemble empirical mode decomposition (EEMD) and two-dimensional multiple signal classification (2D-MUSIC) algorithm for real-time impact localization on composite structures. Firstly, the impact signal at an unknown position is obtained using a unified linear sensor array. Secondly, the fast Hilbert Huang transform (HHT) with an optimized EEMD algorithm is introduced to extract intrinsic mode functions (IMFs) from impact signals. Then, all IMFs in the whole frequency domain are directly used as the input vector of the 2D-MUSIC model separately to locate the impact source. Experimental data collected from a cross-ply glass fiber reinforced composite plate are used to validate the proposed approach. The results show that the use of optimized EEMD and 2D-MUSIC is suitable for real-time impact localization of composite structures.

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“…By combining with piezoelectric (referred as PZT) sensor array, this method is able to improve the signal-to-noise ratio when performing SHM applications for aircraft structures. According to the arrangement of the PZT array, these methods can be roughly divided into two kinds, in which the former kind of damage imaging methods are based on the sparse PZT array, such as delay-and-sum imaging [ 10 , 11 , 12 ], time reversal focusing imaging [ 13 , 14 , 15 , 16 ] and damage probability imaging [ 17 , 18 , 19 , 20 ]; the latter dense PZT array methods include ultrasonic phased array [ 21 , 22 , 23 ] and multi-signal classification [ 24 , 25 , 26 ] etc. These methods mainly concentrate on processing guided wave in time domain, frequency domain or time-frequency domain.…”

Section: Introductionmentioning

confidence: 99%

On-Line Multi-Damage Scanning Spatial-Wavenumber Filter Based Imaging Method for Aircraft Composite Structure

2017

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Structural health monitoring (SHM) of aircraft composite structure is helpful to increase reliability and reduce maintenance costs. Due to the great effectiveness in distinguishing particular guided wave modes and identifying the propagation direction, the spatial-wavenumber filter technique has emerged as an interesting SHM topic. In this paper, a new scanning spatial-wavenumber filter (SSWF) based imaging method for multiple damages is proposed to conduct on-line monitoring of aircraft composite structures. Firstly, an on-line multi-damage SSWF is established, including the fundamental principle of SSWF for multiple damages based on a linear piezoelectric (PZT) sensor array, and a corresponding wavenumber-time imaging mechanism by using the multi-damage scattering signal. Secondly, through combining the on-line multi-damage SSWF and a PZT 2D cross-shaped array, an image-mapping method is proposed to conduct wavenumber synthesis and convert the two wavenumber-time images obtained by the PZT 2D cross-shaped array to an angle-distance image, from which the multiple damages can be directly recognized and located. In the experimental validation, both simulated multi-damage and real multi-damage introduced by repeated impacts are performed on a composite plate structure. The maximum localization error is less than 2 cm, which shows good performance of the multi-damage imaging method. Compared with the existing spatial-wavenumber filter based damage evaluation methods, the proposed method requires no more than the multi-damage scattering signal and can be performed without depending on any wavenumber modeling or measuring. Besides, this method locates multiple damages by imaging instead of the geometric method, which helps to improve the signal-to-noise ratio. Thus, it can be easily applied to on-line multi-damage monitoring of aircraft composite structures.

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Acoustic Emission Monitoring of Mechanical Seals Using MUSIC Algorithm Based on Higher Order Statistics

Cited by 15 publications

References 5 publications

The Contact State Monitoring for Seal End Faces Based on Acoustic Emission Detection

The Contact State Monitoring for Seal End Faces Based on Acoustic Emission Detection

Multiple Signal Classification-Based Impact Localization in Composite Structures Using Optimized Ensemble Empirical Mode Decomposition

On-Line Multi-Damage Scanning Spatial-Wavenumber Filter Based Imaging Method for Aircraft Composite Structure

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