Topic · Mechanical Failure Analysis and Simulation

Most cited papers in Mechanical Failure Analysis and Simulation

Mechanical Failure Analysis and Simulation

What are the most cited papers in Mechanical Failure Analysis and Simulation?

The most cited paper in Mechanical Failure Analysis and Simulation is "A Hybrid Prognostics Approach for Estimating Remaining Useful Life of Rolling Element Bearings" (Biao Wang, Yaguo Lei, Naipeng Li et al., 2018), with 1,903 citations. Next come "Prognostics and health management design for rotary machinery systems—Reviews, methodology and applications" (1,587) and "Determination of layer-specific mechanical properties of human coronary arteries with nonatherosclerotic intimal thickening and related constitutive modeling" (984).

Published TypeAccessCitations

Showing 50 of 100 papers. Every paper with more than 173 citations is listed.

Most cited papers, sortable by citations and release date
#	Paper
1	A Hybrid Prognostics Approach for Estimating Remaining Useful Life of Rolling Element Bearings Biao Wang, Yaguo Lei, Naipeng Li et al. · IEEE Transactions on Reliability	14 Dec 2018	1,903
2	Prognostics and health management design for rotary machinery systems—Reviews, methodology and applications Jay K. Lee, Fangji Wu, Wenyu Zhao et al. · Mechanical Systems and Signal Processing	29 Aug 2013	1,587
3	Determination of layer-specific mechanical properties of human coronary arteries with nonatherosclerotic intimal thickening and related constitutive modeling Gerhard A. Holzapfel, Gerhard Sommer, Christian T. Gasser et al. · American Journal of Physiology-Heart and Circulatory Physiology	8 Jul 2005	984
4	Multiscale Convolutional Neural Networks for Fault Diagnosis of Wind Turbine Gearbox Guoqian Jiang, Haibo He, Jun Yan et al. · IEEE Transactions on Industrial Electronics Open access	14 Jun 2018	889
5	An intelligent fault diagnosis approach based on transfer learning from laboratory bearings to locomotive bearings Bin Yang, Yaguo Lei, Feng Ling Jia et al. · Mechanical Systems and Signal Processing	3 Jan 2019	881
6	Automotive tribology overview of current advances and challenges for the future Simon C. Tung, Michael L. McMillan · Tribology International	12 May 2004	667
7	The Use of β Titanium Alloys in the Aerospace Industry Rodney R. Boyer, Robert D. Briggs · Journal of Materials Engineering and Performance	Dec 2005	574
8	Failure of Materials in Mechanical Design Jack A. Collins, Charles O. Smith · Journal of Mechanical Design	Jul 1982	567
9	Remaining useful life predictions for turbofan engine degradation using semi-supervised deep architecture André Listou Ellefsen, Emil Bjørlykhaug, Vilmar Æsøy et al. · Reliability Engineering & System Safety Open access	26 Nov 2018	519
10	Aluminium in Innovative Light-Weight Car Design Jürgen Hirsch · MATERIALS TRANSACTIONS Open access	2011	509
11	Roles of microstructure in fatigue crack initiation Kwai S. Chan · International Journal of Fatigue	15 Oct 2009	509
12	A novel method for intelligent fault diagnosis of rolling bearings using ensemble deep auto-encoders Haidong Shao, Hongkai Jiang, Ying Lin et al. · Mechanical Systems and Signal Processing	20 Oct 2017	464
13	Prognostics and Health Management: A Review of Vibration Based Bearing and Gear Health Indicators Dong Wang, Kwok‐Leung Tsui, Qiang Miao · IEEE Access Open access	20 Nov 2017	456
14	Common failures in gas turbine blades Tim J. Carter · Engineering Failure Analysis	15 Dec 2004	456
15	Adhesive bonding of aircraft structures Andrew J. Higgins · International Journal of Adhesion and Adhesives	2000	442
16	A Damage Function and Associated Failure Equations for Predicting Hold Time and Frequency Effects in Elevated Temperature, Low Cycle Fatigue Warren J. Ostergren · Journal of Testing and Evaluation	Sep 1976	427
17	Course of SN-curves especially in the high-cycle fatigue regime with regard to component design and safety Cetin Morris Sonsino · International Journal of Fatigue	27 Jan 2007	416
18	Deep separable convolutional network for remaining useful life prediction of machinery Biao Wang, Yaguo Lei, Naipeng Li et al. · Mechanical Systems and Signal Processing	12 Sep 2019	411
19	Intelligent fault diagnosis of rolling bearings based on normalized CNN considering data imbalance and variable working conditions Bo Zhao, Xianmin Zhang, Hai Li et al. · Knowledge-Based Systems	27 Apr 2020	387
20	A novel deep learning method based on attention mechanism for bearing remaining useful life prediction Yuanhang Chen, Gaoliang Peng, Zhiyu Zhu et al. · Applied Soft Computing	5 Nov 2019	387
21	THE THEORY OF STRESS CORROSION CRACKING IN ALLOYS J.C. Scully · Anti-Corrosion Manual	Sep 1972	382
22	Gearbox condition monitoring in wind turbines: A review Jack P. Salameh, Sébastien Cauët, Erik Etien et al. · Mechanical Systems and Signal Processing	12 Apr 2018	374
23	A convolutional neural network based on a capsule network with strong generalization for bearing fault diagnosis Zhiyu Zhu, Gaoliang Peng, Yuanhang Chen et al. · Neurocomputing	26 Sep 2018	357
24	Low cycle fatigue behavior of inconel 718 at 298 K and 823 K D. Fournier, André Pineau · Metallurgical Transactions A	Jul 1977	336
25	Predicting Remaining Useful Life of Rolling Bearings Based on Deep Feature Representation and Transfer Learning Wentao Mao, Jianliang He, Ming Jian Zuo · IEEE Transactions on Instrumentation and Measurement	25 May 2019	333
26	Novel Joint Transfer Network for Unsupervised Bearing Fault Diagnosis From Simulation Domain to Experimental Domain Yiming Xiao, Haidong Shao, Song-Yu Han et al. · IEEE/ASME Transactions on Mechatronics	6 Jun 2022	331
27	Planetary gearbox fault diagnosis using bidirectional-convolutional LSTM networks Junchuan Shi, Dikang Peng, Zhongxiao Peng et al. · Mechanical Systems and Signal Processing	18 May 2021	320
28	Review and Prospects for Current Studies on Very High Cycle Fatigue of Metallic Materials for Machine Structural Use Tatsuo Sakai · Journal of Solid Mechanics and Materials Engineering Open access	2009	319
29	Fault diagnosis for wind turbine planetary gearboxes via demodulation analysis based on ensemble empirical mode decomposition and energy separation Zhipeng Feng, Ming Xuan Liang, Zhang Yi et al. · Renewable Energy	14 May 2012	318
30	Bearing Fault Diagnosis Method Based on Deep Convolutional Neural Network and Random Forest Ensemble Learning Gaowei Xu, Min Liu, Zhuofu Jiang et al. · Sensors Open access	3 Mar 2019	315
31	Transgranular Stress Corrosion Cracking of High-Pressure Pipelines in Contact with Solutions of Near Neutral pH R. N. Parkins, W. K. Blanchard, Burke S. Delanty · CORROSION	May 1994	313
32	An improved similarity-based prognostic algorithm for RUL estimation using an RNN autoencoder scheme Wennian Yu, Il Yong Kim, Chris Mechefske · Reliability Engineering & System Safety	16 Mar 2020	300
33	A Two-Stage Approach for the Remaining Useful Life Prediction of Bearings Using Deep Neural Networks Min Xia, Teng Li, Tongxin Shu et al. · IEEE Transactions on Industrial Informatics	4 Sep 2018	296
34	Joining Technologies for Automotive Battery Systems Manufacturing Abhishek Das, Dezhi Li, David M. Williams et al. · World Electric Vehicle Journal Open access	5 Jul 2018	293
35	Dislocation behavior in fatigue Doris Kuhlmann‐Wilsdorf, Campbell Laird · Materials Science and Engineering	Feb 1977	292
36	Principles and practices of adhesive bonded structural joints and repairs Maxwell Davis, David A. Bond · International Journal of Adhesion and Adhesives	Apr 1999	291
37	Influence of microstructure on high-cycle fatigue of Ti-6Al-4V: Bimodal vs. lamellar structures Ravi K. Nalla, Robert O. Ritchie, Brad L. Boyce et al. · Metallurgical and Materials Transactions A	Mar 2002	290
38	A Hybrid Generalization Network for Intelligent Fault Diagnosis of Rotating Machinery Under Unseen Working Conditions Te Han, Yan‐Fu Li, Min Qian · IEEE Transactions on Instrumentation and Measurement	2021	289
39	Metal-matrix composites in the automotive industry: Opportunities and challenges John E. Allison, Gerald S. Cole · JOM	1993	283
40	Meta-learning for few-shot bearing fault diagnosis under complex working conditions Chuanjiang Li, Shaobo Li, Ansi Zhang et al. · Neurocomputing	29 Jan 2021	275
41	Stacked Multilevel-Denoising Autoencoders: A New Representation Learning Approach for Wind Turbine Gearbox Fault Diagnosis Guoqian Jiang, Haibo He, Ping Xie et al. · IEEE Transactions on Instrumentation and Measurement Open access	23 May 2017	270
42	Gated Dual Attention Unit Neural Networks for Remaining Useful Life Prediction of Rolling Bearings Yi Qin, Dingliang Chen, Sheng Xiang et al. · IEEE Transactions on Industrial Informatics	2 Jun 2020	268
43	A fault information-guided variational mode decomposition (FIVMD) method for rolling element bearings diagnosis Qing Ni, Jinchen Ji, Ke Feng et al. · Mechanical Systems and Signal Processing	14 Jul 2021	265
44	A Directed Acyclic Graph Network Combined With CNN and LSTM for Remaining Useful Life Prediction Jialin Li, Xueyi Li, David He · IEEE Access Open access	2019	257
45	Effects of pitting corrosion on the fatigue behavior of aluminum alloy 7075-T6: modeling and experimental studies Krishnan K. Sankaran, Raúl Pérez-Arévalo, Kumar V. Jata · Materials Science and Engineering A	2001	257
46	XJTU-SY Rolling Element Bearing Accelerated Life Test Datasets: A Tutorial Lei Yaguo, HAN Tianyu, Biao Wang et al. · Journal of Mechanical Engineering Open access	2019	255
47	Intelligent fault diagnosis method of planetary gearboxes based on convolution neural network and discrete wavelet transform Renxiang Chen, Xin Huang, Lixia Yang et al. · Computers in Industry	2 Jan 2019	254
48	A review on deep learning in planetary gearbox health state recognition: methods, applications, and dataset publication Dongdong Liu, Lingli Cui, Weidong Cheng · Measurement Science and Technology Open access	24 Aug 2023	252
49	Wind turbine high-speed shaft bearings health prognosis through a spectral Kurtosis-derived indices and SVR Lotfi Saïdi, Jaouher Ben Ali, Eric R. Bechhoefer et al. · Applied Acoustics	11 Jan 2017	252
50	Deformation and failure mechanisms of 18650 battery cells under axial compression Juner Zhu, Xiaowei Zhang, Elham Sahraei et al. · Journal of Power Sources	29 Oct 2016	251

Citations are OpenAlex's own counts, from its 2026-09-23 snapshot, so the ranking can differ from Google Scholar or Web of Science. A paper is listed for a field when OpenAlex files it under one of the field's topics; retracted papers and papers whose citation count cannot be traced to citing works are left out, and a preprint and the article it became are shown once. Release dates are OpenAlex's: where a source gave only a month or a year, that is what is shown. How the lists are chosen.