Support vector machine in machine condition monitoring and fault diagnosis

Support-vector networks

Cortes, C., & Vapnik, V. (1995) · Machine Learning · doi:10.1007/bf00994018 · Cited by 59,421 · see citing works

The Nature of Statistical Learning Theory

Vapnik, V. N. (1995) · doi:10.1007/978-1-4757-2440-0 · Cited by 39,138 · see citing works

Support-Vector Networks

Cortes, C., & Vapnik, V. N. (1995) · Machine Learning · doi:10.1023/a:1022627411411 · Cited by 34,565 · see citing works

Pattern Classification

Seel, N. M. (2012) · Springer eBooks · doi:10.1007/978-1-4419-1428-6_5195 · Cited by 19,525 · see citing works

Neural networks for pattern recognition

Bishop, C. (1994) · Choice Reviews Online · doi:10.5860/choice.31-5500 · Cited by 18,537 · see citing works

A training algorithm for optimal margin classifiers

Boser, B. E., Guyon, I. M., & Vapnik, V. N. (1992) · Proceedings of the fifth annual workshop on Computational learning theory · doi:10.1145/130385.130401 · Cited by 11,992 · see citing works

Pattern Classification

Russell, E. L., Chiang, L. H., & Braatz, R. D. (2000) · Advances in industrial control · doi:10.1007/978-1-4471-0409-4_3 · Cited by 7,938 · see citing works

A comparison of methods for multiclass support vector machines

Hsu, C., & Lin, C. (2002) · IEEE Transactions on Neural Networks · doi:10.1109/72.991427 · Cited by 6,861 · see citing works

Advances in kernel methods: support vector learning

Schölkopf, B., Burges, C. J. C., & Smola, A. J. (1999) · doi:10.5555/299094 · Cited by 5,809 · see citing works

Fast Training of Support Vector Machines Using Sequential Minimal Optimization

Platt, J. C. (1998) · The MIT Press eBooks · doi:10.7551/mitpress/1130.003.0016 · Cited by 5,501 · see citing works

An Introduction to Support Vector Machines

Cristianini, N., & Shawe-Taylor, J. S. (2000) · ePrints Soton (University of Southampton) · Cited by 4,115 · see citing works

The Nature of Statistical Learning Theory

Sain, S. R., & Vapnik, V. N. (1996) · Technometrics · doi:10.2307/1271324 · Cited by 4,097 · see citing works

Decision support systems and intelligent systems

Turban, E., & Aronson, J. E. (1997) · University of Maribor digital library (University of Maribor) · Cited by 2,452 · see citing works

An Introduction to Predictive Maintenance

Mobley, R. K. (2002) · Elsevier eBooks · doi:10.1016/b978-0-7506-7531-4.x5000-3 · Cited by 1,170 · see citing works

Gear fault detection using artificial neural networks and support vector machines with genetic algorithms

Samanta, B. (2003) · Mechanical Systems and Signal Processing · doi:10.1016/s0888-3270(03)00020-7 · Cited by 523 · see citing works

Artificial neural networks and support vector machines with genetic algorithm for bearing fault detection

Samanta, B., Al-Balushi, K. R., & Al-Araimi, S. A. (2003) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2003.09.006 · Cited by 519 · see citing works

Feature selection using Decision Tree and classification through Proximal Support Vector Machine for fault diagnostics of roller bearing

Sugumaran, V., Muralidharan, V., & Ramachandran, K. I. (2006) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2006.05.004 · Cited by 462 · see citing works

Fault diagnosis of rotating machinery based on improved wavelet package transform and SVMs ensemble

Hu, Q., He, Z., Zhang, Z., & Zi, Y. (2006) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2006.01.007 · Cited by 402 · see citing works

A fast iterative nearest point algorithm for support vector machine classifier design

Keerthi, S. S., Shevade, S., Bhattacharyya, C., & Murthy, K. R. K. (2000) · IEEE Transactions on Neural Networks · doi:10.1109/72.822516 · Cited by 382 · see citing works

FAULT DETECTION USING SUPPORT VECTOR MACHINES AND ARTIFICIAL NEURAL NETWORKS, AUGMENTED BY GENETIC ALGORITHMS

Jack, L. B., & Nandi, A. K. (2002) · Mechanical Systems and Signal Processing · doi:10.1006/mssp.2001.1454 · Cited by 376 · see citing works

Combination of independent component analysis and support vector machines for intelligent faults diagnosis of induction motors

Widodo, A., Yang, B., & Han, T. (2006) · Expert Systems with Applications · doi:10.1016/j.eswa.2005.11.031 · Cited by 296 · see citing works

Application of nonlinear feature extraction and support vector machines for fault diagnosis of induction motors

Widodo, A., & Yang, B.-S. (2007) · Expert Systems with Applications · doi:10.1016/j.eswa.2006.04.020 · Cited by 292 · see citing works

ART–KOHONEN neural network for fault diagnosis of rotating machinery

Yang, B., Han, T., & An, J. L. (2003) · Mechanical Systems and Signal Processing · doi:10.1016/s0888-3270(03)00073-6 · Cited by 207 · see citing works

Support vector machines-based fault diagnosis for turbo-pump rotor

Sheng-fa, Y., & Chu, F. (2005) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2005.09.006 · Cited by 207 · see citing works

Tool breakage detection using support vector machine learning in a milling process

Cho, S., ASFOUR, S. S., Onar, A., et al. (2004) · International Journal of Machine Tools and Manufacture · doi:10.1016/j.ijmachtools.2004.08.016 · Cited by 198 · see citing works

Fault diagnosis using support vector machine with an application in sheet metal stamping operations

Ge, M., Du, R., Zhang, G., et al. (2003) · Mechanical Systems and Signal Processing · doi:10.1016/s0888-3270(03)00071-2 · Cited by 166 · see citing works

Condition classification of small reciprocating compressor for refrigerators using artificial neural networks and support vector machines

Yang, B., Hwang, W.-W., Kim, D.-J., & Tan, A. C. C. (2004) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2004.06.002 · Cited by 153 · see citing works

Condition-based maintenance and machine diagnostics

Williams, J. H., Davies, A., & Drake, P. R. (1994) · Chapman & Hall eBooks · Cited by 144 · see citing works

Multiclassification of tool wear with support vector machine by manufacturing loss consideration

Sun, J., Rahman, M., Wong, Y. S., et al. (2004) · International Journal of Machine Tools and Manufacture · doi:10.1016/j.ijmachtools.2004.04.003 · Cited by 117 · see citing works

Thermal error measurement and modelling in machine tools. Part II. Hybrid Bayesian Network—support vector machine model

Ramesh, R., Mannan, M. A., POO, A. N., et al. (2003) · International Journal of Machine Tools and Manufacture · doi:10.1016/s0890-6955(02)00264-x · Cited by 115 · see citing works

Fault diagnosis of rotating machinery based on multi-class support vector machines

Yang, B., Han, T., & Hwang, W.-W. (2005) · Journal of Mechanical Science and Technology · doi:10.1007/bf02916133 · Cited by 113 · see citing works

Practical scheme for fast detection and classification of rolling-element bearing faults using support vector machines

Rojas‐Domínguez, A., & Nandi, A. K. (2005) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2005.05.002 · Cited by 94 · see citing works

An iterative algorithm learning the maximal margin classifier

Franc, V., & Hlaváč, V. (2003) · Pattern Recognition · doi:10.1016/s0031-3203(03)00060-8 · Cited by 92 · see citing works

Case-based reasoning system with Petri nets for induction motor fault diagnosis

Yang, B., Jeong, S. K., Oh, Y., & Tan, A. C. C. (2004) · Expert Systems with Applications · doi:10.1016/j.eswa.2004.02.004 · Cited by 89 · see citing works

Fault diagnosis based on support vector machines with parameter optimisation by artificial immunisation algorithm

Yuan, S., & Chu, F. (2006) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2006.06.006 · Cited by 89 · see citing works

Cavitation detection of butterfly valve using support vector machines

Yang, B., Hwang, W.-W., Ko, M.-H., et al. (2004) · Journal of Sound and Vibration · doi:10.1016/j.jsv.2004.10.033 · Cited by 69 · see citing works

On domain knowledge and feature selection using a support vector machine

Barzilay, O., & Brailovsky, V. L. (1999) · Pattern Recognition Letters · doi:10.1016/s0167-8655(99)00014-8 · Cited by 67 · see citing works

Pump Failure Detection Using Support Vector Data Descriptions

Tax, D. M. J., Ypma, A., & Duin, R. P. W. (1999) · Lecture notes in computer science · doi:10.1007/3-540-48412-4_35 · Cited by 64 · see citing works

Fault diagnosis in HVAC chillers

Choi, K., Namburu, S. M., Azam, M. S., et al. (2005) · IEEE Instrumentation & Measurement Magazine · doi:10.1109/mim.2005.1502443 · Cited by 63 · see citing works

Fault diagnostics of an electrical machine with multiple support vector classifiers

Pöyhönen, S., Negrea, M., Arkkio, A., Hyötyniemi, H., & Koivo, H. N. (2003) · The proceedings of the IEEE Conference on Control Applications/The proceedings of the ... IEEE Conference on Control Applications · doi:10.1109/isic.2002.1157792 · Cited by 47 · see citing works

Application of support vector machine nonlinear classifier to fault diagnoses

Yan, W., & Shao, H. (2003) · World Congress on Intelligent Control and Automation · doi:10.1109/wcica.2002.1020004 · Cited by 46 · see citing works

Support vector approaches for engine knock detection

Rychetsky, M., Ortmann, S., & Glesner, M. (2003) · 2022 International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn.1999.831085 · Cited by 45 · see citing works

TOWARD HELICOPTER GEARBOX DIAGNOSTICS FROM A SMALL NUMBER OF EXAMPLES

Zacksenhouse, M., Braun, S. G., Feldman, M. A., et al. (2000) · Mechanical Systems and Signal Processing · doi:10.1006/mssp.2000.1297 · Cited by 41 · see citing works

Coupling pairwise support vector machines for fault classification

Pöyhönen, S., Arkkio, A., Jover, P., et al. (2004) · Control Engineering Practice · doi:10.1016/j.conengprac.2004.08.002 · Cited by 39 · see citing works

Coupling Pairwise Support Vector Machines for Fault Classification

Pöyhönen, S., Arkkio, A., & Hyötyniemi, H. (2003) · IFAC Proceedings Volumes · doi:10.1016/s1474-6670(17)36567-9 · Cited by 32 · see citing works

Detection and Classification of Rolling-Element Bearing Faults using Support Vector Machines

Rojas‐Domínguez, A., & Nandi, A. K. (2006) · Machine learning for signal processing ... · doi:10.1109/mlsp.2005.1532891 · Cited by 29 · see citing works

The Application of Nonstandard Support Vector Machine in Tool Condition Monitoring System

Sun, J., Hong, G. S., Rahman, M., et al. (2005) · IEEE International Workshop on Electronic Design, Test and Applications (DELTA) · doi:10.1109/delta.2004.10017 · Cited by 26 · see citing works

Support vector machines for fault detection

Batur, C., Zhou, L., & Chan, C.-C. (2003) · Proceedings of the IEEE Conference on Decision & Control, including the Symposium on Adaptive Processes · doi:10.1109/cdc.2002.1184704 · Cited by 21 · see citing works

Fault diagnosis based on support vector machine ensemble

Li, Y., Cal, Y.-Z., Yin, R.-P., et al. (2005) · International Conference on Machine Learning and Cybernetics · doi:10.1109/icmlc.2005.1527514 · Cited by 20 · see citing works

Application of Support Vector Machines in Reciprocating Compressor Valve Fault Diagnosis

Ren, Q., Xiao-jiang, M., & Miao, G. (2005) · Lecture notes in computer science · doi:10.1007/11539117_13 · Cited by 19 · see citing works

Fault Diagnosis System Based on Rough Set Theory and Support Vector Machine

Xu, Y., & Wang, L. (2005) · Lecture notes in computer science · doi:10.1007/11540007_124 · Cited by 17 · see citing works

Induction Machine Rotor Diagnosis Using Support Vector Machines and Rough Set

Fang, R. (2006) · Lecture notes in computer science · doi:10.1007/978-3-540-37275-2_78 · Cited by 12 · see citing works

Support vector machine used to diagnose the fault of rotor broken bars of induction motors

Cao, Z., Jiazhong, F., Hongpingn, C., Guo-guang, H., & Ritchie, E. (2003) · VBN Forskningsportal (Aalborg Universitet) · Cited by 10 · see citing works

Power Plant Boiler Air Preheater Hot Spots Detection System Based on Least Square Support Vector Machines

Han, L., Ding, L., Yu, J., et al. (2004) · Lecture notes in computer science · doi:10.1007/978-3-540-28647-9_98 · Cited by 5 · see citing works

Fuzzy Support Vector Machine and Its Application to Mechanical Condition Monitoring

Zhang, Z., Hu, Q., & He, Z. (2005) · Lecture notes in computer science · doi:10.1007/11427391_150 · Cited by 5 · see citing works

Active Learning of Support Vector Machine for Fault Diagnosis of Bearings

Zhang, Z., Lv, W., & Shen, M. (2006) · Lecture notes in computer science · doi:10.1007/11760191_58 · Cited by 5 · see citing works

Wavelet Support Vector Machine for Machine Faults Classification

(2007) · CRC Press eBooks · doi:10.1201/b12168-64 · Cited by 3 · see citing works

Faults Detection and Classification of Induction Motor using Wavelet Support Vector Machine

Widodo, A., Yang, B., & Lee, S.-M. (2006) · 한국동력기계공학회 학술대회 논문집 · Cited by 1 · see citing works

Applications of machine learning to machine fault diagnosis: A review and roadmap

Lei, Y., Yang, B., Jiang, X., Jia, F., Li, N., & Nandi, A. K. (2020) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2019.106587 · Cited by 2,997 · see citing works

Deep learning and its applications to machine health monitoring

Zhao, R., Yan, R., Chen, Z., Mao, K., Wang, P., & Gao, R. X. (2019) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2018.05.050 · Cited by 2,894 · see citing works

Artificial intelligence for fault diagnosis of rotating machinery: A review

Liu, R., Yang, B., Zio, E., & Chen, X. (2018) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2018.02.016 · Cited by 2,188 · see citing works

Deep neural networks: A promising tool for fault characteristic mining and intelligent diagnosis of rotating machinery with massive data

Jia, F., Lei, Y., Lin, J., Zhou, X., & Lu, N. (2016) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2015.10.025 · Cited by 1,710 · see citing works

Machine learning in manufacturing: Advantages, challenges, and applications

Wuest, T., Weimer, D., Irgens, C., & Thoben, K.-D. (2016) · Production & Manufacturing Research · doi:10.1080/21693277.2016.1192517 · Cited by 1,319 · see citing works

Data-Driven Methods for Predictive Maintenance of Industrial Equipment: A Survey

Zhang, W., Yang, D., & Wang, H. (2019) · IEEE Systems Journal · doi:10.1109/jsyst.2019.2905565 · Cited by 732 · see citing works

Data-driven predictive maintenance planning framework for MEP components based on BIM and IoT using machine learning algorithms

Cheng, J. C. P., Chen, W., Chen, K., & Wang, Q. (2020) · Automation in Construction · doi:10.1016/j.autcon.2020.103087 · Cited by 520 · see citing works

Intelligent prognostics for battery health monitoring based on sample entropy

Widodo, A., Shim, M.-C., Caesarendra, W., & Yang, B.-S. (2011) · Expert Systems with Applications · doi:10.1016/j.eswa.2011.03.063 · Cited by 392 · see citing works

Towards Accountable AI: Hybrid Human-Machine Analyses for Characterizing System Failure

Nushi, B., Kamar, E., & Horvitz, E. (2018) · Proceedings of the AAAI Conference on Human Computation and Crowdsourcing · doi:10.1609/hcomp.v6i1.13337 · Cited by 126 · see citing works

A Digital Twin-Based Approach for the Fault Diagnosis and Health Monitoring of a Complex Satellite System

Shangguan, D., Chen, L., & Ding, J. (2020) · Symmetry · doi:10.3390/sym12081307 · Cited by 94 · see citing works

Machine learning for microalgae detection and utilization

Ning, H., Li, R., & Zhou, T. (2022) · Frontiers in Marine Science · doi:10.3389/fmars.2022.947394 · Cited by 83 · see citing works

Construction of a batch-normalized autoencoder network and its application in mechanical intelligent fault diagnosis

Wang, J., Li, S., Han, B., An, Z., Xin, Y., Qian, W., & Wu, Q. (2019) · Measurement Science and Technology · doi:10.1088/1361-6501/aaf319 · Cited by 61 · see citing works

Machine learning-based cyber threat detection: an approach to malware detection and security with explainable AI insights

Prity, F. S., Islam, M. S., Fahim, E. H., Hossain, M. M., Bhuiyan, S. H., Islam, M. A., & Raquib, M. (2024) · Human-Intelligent Systems Integration · doi:10.1007/s42454-024-00055-7 · Cited by 24 · see citing works

Classification using support vector machines with graded resolution

Wang, L., Liu, B. Y., & Wan, C. (2005) · IEEE International Conference on Granular Computing (GrC) · doi:10.1109/grc.2005.1547374 · Cited by 31 · see citing works

On Multiclass Support Vector Machines: One-Against-Half Approach

(2010) · Cited by 1 · see citing works

[발표논문] 인공신경망과 Support Vector Machine의 기업부도예측 성과 비교-Support Vector Machine의 유용성을 중심으로-

이영찬 (2004) · 한국지능정보시스템학회 학술대회논문집

Smoothing Support Vector Machines for e-Insensitive Regressi

(2006) · doi:10.1109/isda.2006.244 · Cited by 2 · see citing works

재무예측을 위한 Support Vector Machine의 최적화

(2011)