최소 단어 이상 선택하여야 합니다.
최대 10 단어까지만 선택 가능합니다.
다음과 같은 기능을 한번의 로그인으로 사용 할 수 있습니다.
NTIS 바로가기IEEE transactions on instrumentation and measurement, v.69 no.6 pt.2, 2020년, pp.3334 - 3347
Sohaib, Muhammad (School of Electrical, Electronics and Computer Engineering, University of Ulsan, Ulsan, South Korea) , Kim, Jong-Myon (School of IT Convergence, University of Ulsan, Ulsan, South Korea)
This article proposes a fault diagnosis (FD) method that is based on bispectrum analysis and a convolutional neural network (CNN) to identify bearing faults under inconsistent working conditions, such as high shaft speed variations with cracks of multiple scales and compound faults. First, the bispe...
A Wideband Vibration Sensor 2018
Seeded Fault Test Data 2018
arXiv 1609 04747 An overview of gradient descent optimization algorithms ruder 2016
Deep Learning goodfellow 2016 1
Smart Struct Syst A novel approach to damage localisation based on bispectral analysis and neural network civera 2017 20 669
Nikias, C.L., Raghuveer, M.R.. Bispectrum estimation: A digital signal processing framework. Proceedings of the IEEE, vol.75, no.7, 869-891.
arXiv 1412 6980 Adam: A method for stochastic optimization kingma 2014
Proc Adv Neural Inf Process Syst Identifying and attacking the saddle point problem in high-dimensional non-convex optimization dauphin 2014 2933
Hasan, Md Junayed, Islam, M.M. Manjurul, Kim, Jong-Myon. Acoustic spectral imaging and transfer learning for reliable bearing fault diagnosis under variable speed conditions. Measurement : journal of the International Measurement Confederation, vol.138, 620-631.
He, D., Ruoyu Li, Junda Zhu. Plastic Bearing Fault Diagnosis Based on a Two-Step Data Mining Approach. IEEE transactions on industrial electronics : a publication of the IEEE Industrial Electronics Society, vol.60, no.8, 3429-3440.
Bangalore, Pramod, Tjernberg, Lina Bertling. An Artificial Neural Network Approach for Early Fault Detection of Gearbox Bearings. IEEE transactions on smart grid, vol.6, no.2, 980-987.
Xiang Gong, Wei Qiao. Bearing Fault Diagnosis for Direct-Drive Wind Turbines via Current-Demodulated Signals. IEEE transactions on industrial electronics : a publication of the IEEE Industrial Electronics Society, vol.60, no.8, 3419-3428.
Khan, Sheraz Ali, Kim, Jong-Myon. Rotational speed invariant fault diagnosis in bearings using vibration signal imaging and local binary patterns. The Journal of the Acoustical Society of America, vol.139, no.4, EL100-EL104.
Liu, Ruonan, Yang, Boyuan, Zio, Enrico, Chen, Xuefeng. Artificial intelligence for fault diagnosis of rotating machinery: A review. Mechanical systems and signal processing, vol.108, 33-47.
Asia–Pacific J Multidisciplinary Res Vibration feature extraction and analysis for fault diagnosis of rotating machinery—A literature survey riaz 2017 5 103
Myeongsu Kang, Islam, Md Rashedul, Jaeyoung Kim, Jong-Myon Kim, Pecht, Michael. A Hybrid Feature Selection Scheme for Reducing Diagnostic Performance Deterioration Caused by Outliers in Data-Driven Diagnostics. IEEE transactions on industrial electronics : a publication of the IEEE Industrial Electronics Society, vol.63, no.5, 3299-3310.
Dubey, Rahul, Agrawal, Dheeraj. Bearing fault classification using ANN-based Hilbert footprint analysis. IET science, measurement & technology, vol.9, no.8, 1016-1022.
Ren, Likun, Lv, Weimin, Jiang, ShiWei, Xiao, Yang. Fault Diagnosis Using a Joint Model Based on Sparse Representation and SVM. IEEE transactions on instrumentation and measurement, vol.65, no.10, 2313-2320.
Saini, Manish Kumar, Aggarwal, Akanksha. Detection and diagnosis of induction motor bearing faults using multiwavelet transform and naive Bayes classifier. International transactions on electrical energy systems, vol.28, no.8, e2577-.
Xu, Gaowei, Liu, Min, Jiang, Zhuofu, Shen, Weiming, Huang, Chenxi. Online Fault Diagnosis Method Based on Transfer Convolutional Neural Networks. IEEE transactions on instrumentation and measurement, vol.69, no.2, 509-520.
Zavaliagkos, G., Zhao, Y., Schwartz, R., Makhoul, J.. A hybrid segmental neural net/hidden Markov model system for continuous speech recognition. IEEE transactions on speech and audio processing : a publication of the IEEE Signal Processing Society, vol.2, no.1, 151-160.
Sun, Jiedi, Yan, Changhong, Wen, Jiangtao. Intelligent Bearing Fault Diagnosis Method Combining Compressed Data Acquisition and Deep Learning. IEEE transactions on instrumentation and measurement, vol.67, no.1, 185-195.
Yong Zhang, Peng Li, Yingyezhe Jin, Yoonsuck Choe. A Digital Liquid State Machine With Biologically Inspired Learning and Its Application to Speech Recognition. IEEE transactions on neural networks and learning systems, vol.26, no.11, 2635-2649.
Zhang, Xiaochen, Jiang, Dongxiang, Han, Te, Wang, Nanfei, Yang, Wenguang, Yang, Yizhou. Rotating Machinery Fault Diagnosis for Imbalanced Data Based on Fast Clustering Algorithm and Support Vector Machine. Journal of sensors, vol.2017, 1-15.
Sameen, Sara, Sharjeel, Muhammad, Nawab, Rao Muhammad Adeel, Rayson, Paul, Muneer, Iqra. Measuring Short Text Reuse for the Urdu Language. IEEE access : practical research, open solutions, vol.6, 7412-7421.
Soualhi, Abdenour, Medjaher, Kamal, Zerhouni, Noureddine. Bearing Health Monitoring Based on Hilbert–Huang Transform, Support Vector Machine, and Regression. IEEE transactions on instrumentation and measurement, vol.64, no.1, 52-62.
Song, Liuyang, Wang, Huaqing, Chen, Peng. Vibration-Based Intelligent Fault Diagnosis for Roller Bearings in Low-Speed Rotating Machinery. IEEE transactions on instrumentation and measurement, vol.67, no.8, 1887-1899.
Van Opbroek, Annegreet, Achterberg, Hakim C., Vernooij, Meike W., De Bruijne, Marleen. Transfer Learning for Image Segmentation by Combining Image Weighting and Kernel Learning. IEEE transactions on medical imaging, vol.38, no.1, 213-224.
Qingbo He, Haiyue Song, Xiaoxi Ding. Sparse Signal Reconstruction Based on Time–Frequency Manifold for Rolling Element Bearing Fault Signature Enhancement. IEEE transactions on instrumentation and measurement, vol.65, no.2, 482-491.
Harmouche, Jinane, Delpha, Claude, Diallo, Demba. Improved Fault Diagnosis of Ball Bearings Based on the Global Spectrum of Vibration Signals. IEEE transactions on energy conversion, vol.30, no.1, 376-383.
Wang, Ziwei, Zhang, Qinghua, Xiong, Jianbin, Xiao, Ming, Sun, Guoxi, He, Jun. Fault Diagnosis of a Rolling Bearing Using Wavelet Packet Denoising and Random Forests. IEEE sensors journal, vol.17, no.17, 5581-5588.
Guo, X., Chen, L., Shen, C.. Hierarchical adaptive deep convolution neural network and its application to bearing fault diagnosis. Measurement : journal of the International Measurement Confederation, vol.93, 490-502.
Khan, Sheraz Ali, Kim, Jong-Myon. Automated Bearing Fault Diagnosis Using 2D Analysis of Vibration Acceleration Signals under Variable Speed Conditions. Shock and vibration, vol.2016, ARTN 8729572-.
Sohaib, Muhammad, Kim, Cheol-Hong, Kim, Jong-Myon. A Hybrid Feature Model and Deep-Learning-Based Bearing Fault Diagnosis. Sensors, vol.17, no.12, 2876-.
Ahmad, Kashif, Mekhalfi, Mohamed Lamine, Conci, Nicola, Melgani, Farid, Natale, Francesco De. Ensemble of Deep Models for Event Recognition. ACM transactions on multimedia computing communications and applications, vol.14, no.2, 1-20.
Amar, Muhammad, Gondal, Iqbal, Wilson, Campbell. Vibration Spectrum Imaging: A Novel Bearing Fault Classification Approach. IEEE transactions on industrial electronics : a publication of the IEEE Industrial Electronics Society, vol.62, no.1, 494-502.
Appana, Dileep K., Prosvirin, Alexander, Kim, Jong-Myon. Reliable fault diagnosis of bearings with varying rotational speeds using envelope spectrum and convolution neural networks. Soft computing : a fusion of foundations, methodologies and applications, vol.22, no.20, 6719-6729.
Lu, C., Wang, Z.Y., Qin, W.L., Ma, J.. Fault diagnosis of rotary machinery components using a stacked denoising autoencoder-based health state identification. Signal processing : the official publication of the European Association for Signal Processing (EURASIP), vol.130, 377-388.
Kang, Gaoqiang, Gao, Shibin, Yu, Long, Zhang, Dongkai. Deep Architecture for High-Speed Railway Insulator Surface Defect Detection: Denoising Autoencoder With Multitask Learning. IEEE transactions on instrumentation and measurement, vol.68, no.8, 2679-2690.
*원문 PDF 파일 및 링크정보가 존재하지 않을 경우 KISTI DDS 시스템에서 제공하는 원문복사서비스를 사용할 수 있습니다.
※ AI-Helper는 부적절한 답변을 할 수 있습니다.