Use of Acoustic Emission and Pattern Recognition for Crack Detection of a Large Carbide Anvil
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Bin Chen | Yanan Wang | Zhaoli Yan | Bin Chen | Zhaoli Yan | Yanan Wang
[1] Yi Shen,et al. Acoustic emission detection of rail defect based on wavelet transform and Shannon entropy , 2015 .
[2] H Henk Nijmeijer,et al. Broadband planar nearfield acoustic holography based on one-third-octave band analysis , 2014 .
[3] Bin Chen,et al. Fault Detection of Carbide Anvil Based on Hurst Exponent and BP Neural Network , 2013 .
[4] Bin Chen,et al. Acoustic detection of cracks in the anvil of a large-volume cubic high-pressure apparatus. , 2015, The Review of scientific instruments.
[5] Michal Cifra,et al. Influence of non-adherent yeast cells on electrical characteristics of diamond-based field-effect transistors , 2017 .
[6] Ayça Çakmak Pehlivanli,et al. PCA based clustering for brain tumor segmentation of T1w MRI images , 2017, Comput. Methods Programs Biomed..
[7] Huaqing Wang,et al. Study and Application of Acoustic Emission Testing in Fault Diagnosis of Low-Speed Heavy-Duty Gears , 2011, Sensors.
[8] Han Qi. The Criterion for Crack of Tungsten Carbide Anvil Based on Finite Element Method , 2010 .
[9] Carole Lartizien,et al. Converting SVDD scores into probability estimates: Application to outlier detection , 2017, Neurocomputing.
[10] Corinna Cortes,et al. Support-Vector Networks , 1995, Machine Learning.
[11] P. Dhanalakshmi,et al. Classification of audio signals using SVM and RBFNN , 2009, Expert Syst. Appl..
[12] Sazali Yaacob,et al. Classification of speech dysfluencies with MFCC and LPCC features , 2012, Expert Syst. Appl..
[13] Yongliang Xiao,et al. Shot boundary Detection based on supervised locality preserving projections and KNN-SVM classifier , 2010, 2010 2nd International Asia Conference on Informatics in Control, Automation and Robotics (CAR 2010).
[14] Wang Lin-sheng. Voiceprint recognition technology in diamond anvil cell protection , 2013 .
[15] Buket D. Barkana,et al. Voiced/Unvoiced Decision for Speech Signals Based on Zero-Crossing Rate and Energy , 2008, SCSS.
[16] Buyung Kosasih,et al. Acoustic emission-based condition monitoring methods: Review and application for low speed slew bearing , 2016 .
[17] Bibhas Chandra Dhara,et al. Speech/Music Classification Using Occurrence Pattern of ZCR and STE , 2009, 2009 Third International Symposium on Intelligent Information Technology Application.
[18] M. Elforjani,et al. Detecting natural crack initiation and growth in slow speed shafts with the Acoustic Emission technology , 2009 .
[19] Chen Dongdong,et al. An Intelligent System for Eliminating the Suspicious Experiment Data , 2014 .
[20] Masoud Rabiei,et al. Quantitative methods for structural health management using in situ acoustic emission monitoring , 2013 .
[21] Eiji Ito,et al. Theory and Practice – Multianvil Cells and High-Pressure Experimental Methods , 2007 .
[22] David He,et al. Gearbox Tooth Cut Fault Diagnostics Using Acoustic Emission and Vibration Sensors — A Comparative Study , 2014, Sensors.