Non-contact passive sensing of acoustic emission signal using the air-coupled transducer

Acoustic emission signal analysis for crane slewing bearing with no defect under different conditions

Industrial Electronics and Engineering ◽

10.2495/iciee140661 ◽

2014 ◽

Author(s):

Yang Jiao ◽

Shang Meng ◽

Guanghai Li

Keyword(s):

Acoustic Emission ◽

Acoustic Emission Signal ◽

Signal Analysis ◽

Slewing Bearing ◽

Emission Signal

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Research of the cold resistance of metals by indentation with registration of an acoustic emission signal

10.36652/0042-4633-2020-8-61-64 ◽

2020 ◽

pp. 61-64

Author(s):

Yu.G. Kabaldin ◽

A.A. Khlybov ◽

M.S. Anosov ◽

D.A. Shatagin

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Acoustic Emission ◽

Acoustic Emission Signal ◽

Low Temperatures ◽

Cold Resistance ◽

Emission Signal ◽

Impact Bending ◽

Artificial Neural

The study of metals in impact bending and indentation is considered. A bench is developed for assessing the character of failure on the example of 45 steel at low temperatures using the classification of acoustic emission signal pulses and a trained artificial neural network. The results of fractographic studies of samples on impact bending correlate well with the results of pulse recognition in the acoustic emission signal. Keywords acoustic emission, classification, artificial neural network, low temperature, character of failure, hardness. [email protected]

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Bearing remaining useful life prediction under starved lubricating condition using time domain acoustic emission signal processing

Expert Systems with Applications ◽

10.1016/j.eswa.2020.114391 ◽

2021 ◽

Vol 168 ◽

pp. 114391

Author(s):

Mohsen Motahari-Nezhad ◽

Seyed Mohammad Jafari

Keyword(s):

Signal Processing ◽

Acoustic Emission ◽

Time Domain ◽

Acoustic Emission Signal ◽

Life Prediction ◽

Remaining Useful Life ◽

Emission Signal ◽

Useful Life

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Laser cladding state recognition and crack defect diagnosis by acoustic emission signal and neural network

Optics & Laser Technology ◽

10.1016/j.optlastec.2021.107161 ◽

2021 ◽

Vol 142 ◽

pp. 107161

Author(s):

Kaiqiang Li ◽

Tao Li ◽

Min Ma ◽

Dong Wang ◽

Weiwei Deng ◽

...

Keyword(s):

Neural Network ◽

Acoustic Emission ◽

Laser Cladding ◽

Acoustic Emission Signal ◽

State Recognition ◽

Emission Signal ◽

Defect Diagnosis ◽

Crack Defect

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Insulator Defect Detection Based on Ultraviolet Imaging and Acoustic Emission Signal

2020 IEEE 3rd Student Conference on Electrical Machines and Systems (SCEMS) ◽

10.1109/scems48876.2020.9352424 ◽

2020 ◽

Author(s):

Ming Li ◽

Yugang Jing ◽

Lei Zhang ◽

Xinmei Li ◽

Guilin Huang ◽

...

Keyword(s):

Acoustic Emission ◽

Defect Detection ◽

Acoustic Emission Signal ◽

Emission Signal

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Acoustic emission signal characteristics of maraging steel 250 pressure vessel during a hydraulic qualification test

Nondestructive Testing And Evaluation ◽

10.1080/10589759.2021.1909013 ◽

2021 ◽

pp. 1-15

Author(s):

Gowri Shankar Wuriti ◽

Somnath Chattopadhyaya ◽

Tessy Thomas

Keyword(s):

Acoustic Emission ◽

Maraging Steel ◽

Pressure Vessel ◽

Acoustic Emission Signal ◽

Qualification Test ◽

Emission Signal ◽

Signal Characteristics

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Spatial correlation-based characterization of acoustic emission signal-cloud in a granite sample by a cube clustering approach

International Journal of Mining Science and Technology ◽

10.1016/j.ijmst.2021.05.008 ◽

2021 ◽

Author(s):

Dongjie Xue ◽

Zepeng Zhang ◽

Cheng Chen ◽

Jie Zhou ◽

Lan Lu ◽

...

Keyword(s):

Acoustic Emission ◽

Spatial Correlation ◽

Acoustic Emission Signal ◽

Granite Sample ◽

Emission Signal ◽

Clustering Approach

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Relating acoustic emission signal parameters to the strength of fibres used in the manufacture of polymeric composites

Ultrasonics ◽

10.1016/0041-624x(95)00017-w ◽

1995 ◽

Vol 33 (2) ◽

pp. 123-131 ◽

Cited By ~ 13

Author(s):

E.U. Okoroafor ◽

R. Hill

Keyword(s):

Acoustic Emission ◽

Acoustic Emission Signal ◽

Polymeric Composites ◽

Emission Signal ◽

Signal Parameters

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Application of independent component analysis in metal corrosion acoustic emission signal processing

2012 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering ◽

10.1109/icqr2mse.2012.6246316 ◽

2012 ◽

Cited By ~ 2

Author(s):

Yang Cheng ◽

Nengjun Yang ◽

Xiaolin Yang ◽

Yufeng Wu

Keyword(s):

Signal Processing ◽

Acoustic Emission ◽

Independent Component Analysis ◽

Acoustic Emission Signal ◽

Component Analysis ◽

Independent Component ◽

Metal Corrosion ◽

Emission Signal

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Experiment on Surface Roughness and Acoustic Emission Signal in Infeed Period of Cylindrical Plunge Grinding

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.690-693.2442 ◽

2013 ◽

Vol 690-693 ◽

pp. 2442-2445 ◽

Cited By ~ 1

Author(s):

Hao Lin Li ◽

Hao Yang Cao ◽

Chen Jiang

Keyword(s):

Surface Roughness ◽

Acoustic Emission ◽

Acoustic Emission Signal ◽

Feed Rate ◽

Grinding Process ◽

Experiment Research ◽

Plunge Grinding ◽

Emission Signal ◽

Ae Signal ◽

Ae Signals

This work presents an experiment research on Acoustic emission (AE) signal and the surface roughness of cylindrical plunge grinding with the different infeed time. The changed infeed time of grinding process is researched as an important parameter to compare AE signals and surface roughnesses with the different infeed time in the grinding process. The experiment results show the AE signal is increased by the increased feed rate. In the infeed period of the grinding process, the surface roughness is increased at first, and then is decreased.

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