A5100634275- Machine Fault Diagnosis Techniques
- Gear and Bearing Dynamics Analysis
- Fault Detection and Control Systems
- Engineering Diagnostics and Reliability
- Advanced Algorithms and Applications
- Advanced Sensor and Control Systems
- Industrial Technology and Control Systems
- Robotics and Sensor-Based Localization
- Advanced Measurement and Detection Methods
- Advanced SAR Imaging Techniques
- Optical Systems and Laser Technology
- Infrared Target Detection Methodologies
- Simulation and Modeling Applications
- Tribology and Lubrication Engineering
- Lubricants and Their Additives
- Tribology and Wear Analysis
- Advanced Image and Video Retrieval Techniques
- Advanced Vision and Imaging
- Advanced Computational Techniques and Applications
- Structural Health Monitoring Techniques
- Antenna Design and Optimization
- Traffic control and management
- Evacuation and Crowd Dynamics
- Mechanical stress and fatigue analysis
- Radar Systems and Signal Processing
Shanghai Maritime University
2016-2025
Inner Mongolia Agricultural University
2024
Shanghai University of Engineering Science
2019-2024
Qingdao University
2005-2023
Chongqing University
2016-2023
China Southern Power Grid (China)
2023
Northwestern Polytechnical University
2023
Anhui University of Technology
2021
Lanzhou University of Technology
2017-2021
Liaoning University of Technology
2021
Abstract As a critical and fragile rotary supporting component in mechanical equipment, fault diagnosis of rolling bearing has been hot issue. A technique based on fined-grained multi-scale symbolic entropy whale optimization algorithm-multiclass support vector machine (abbreviated as FGMSE-WOA-MSVM) is proposed this paper. Firstly, the vibration signals are decomposed with fine-grained decomposition, sub-signals at different analysis scales extracted constructed multi-dimension feature...
A rolling bearing fault diagnosis method based on Recursive Quantitative Analysis (RQA) combined with time domain feature extraction and Whale Optimization Algorithm Support Vector Machine (WOA-SVM) is proposed. Firstly, the recurrence graph of vibration signal drawn, nonlinear parameters in Standard Deviation (STD) are extracted by recursive quantitative analysis to generate vectors; after that, order construct optimal support vector machine model, used optimize c g parameters. Finally,...
Rolling bearing is an important rotating support component in mechanical equipment. It very prone to wear, defects, and other faults, which directly affect the reliable operation of Its running condition monitoring fault diagnosis have always been a matter concern engineers researchers. A rolling technique based on multi-domain feature whale optimization algorithm-support vector machine (MDF-WOA-SVM) proposed. Firstly, recursive analysis performed vibration signal features are employed as...
Abstract Due to the doping of considerable noise and impact components in vibration signals quay crane gearboxes, some traditional methods have difficulty uncovering degradation patterns. To accurately extract features from monitoring signals, a feature extraction technique based on static divided symbol sequence entropy is proposed. Based basic scale technique, considering uniformity symbolization standard, takes root mean square health condition signal as basis incorporates coefficient...
Journal Article On the Conditions to Extend Ricci Flow(II) Get access Bing Wang Department of Mathematics, Princeton University, Princeton, NJ 08544, USA Correspondence be sent to: e-mail: bingw@math.princeton.edu Search for other works by this author on: Oxford Academic Google Scholar International Mathematics Research Notices, Volume 2012, Issue 14, Pages 3192–3223, https://doi.org/10.1093/imrn/rnr141 Published: 01 January 2012 history Received: 07 March 2011 Revision received: 12 June Accepted: 27
We address the performance prediction of ordered-statistic constant false alarm rate (OS-CFAR) detector for arbitrarily correlated and possibly nonidentically distributed target echoes in presence nonhomogeneous background. Accounting generalized Swerling-Chi fluctuating model, including well-known Swerling models as special cases, we develop analytic expressions detection probability terms converging series background involving clutter edges isolated point-like interference. At analysis...
In allusion to solve the issue of fault diagnosis for bearing and other rotatory machinery, a technique based on fined-grained multi-scale Kolmogorov entropy whale optimized multi-class support vector machine (abbreviated as FGMKE-WOA-MSVM) is proposed. Firstly, vibration signals are decomposed by fine-grained decomposition, sub-signals at different analysis scales calculated multi-dimension feature vector, which quantitatively characterize complexity signal multi-scales. Aiming problem...
Owing to the superior mechanical and physical properties, metallic glasses (MGs) have attracted tremendous attention as promising candidates for structural functional applications. Unfortunately, ability form uncontrollable glasses, poor stability unpredicted catastrophic failure stemming from disordered structure, Achilles' heel of MGs, severely restrict their large-scale A number phenomenological models, such free volume model, shear transformation zone (STZ) flow unit etc., been proposed,...
The degradation state identification is a key step of the condition based maintenance hydraulic pump. In this paper, spatial information entropy (SIE) as novel feature pump proposed on study permutation (PE) algorithm. fundamental principle SIE introduced and contrasted with PE. Different parameters used in calculation are discussed meaningful conclusion gained. results simulation analysis not only checked rationality but also demonstrated availability superiority adopting feature. Based...
Recent learning-based approaches have achieved impressive results in the field of single-shot camera localization. However, how best to fuse multiple modalities (e.g., image and depth) deal with degraded or missing input are less well studied. In particular, we note that previous towards deep fusion do not perform significantly better than models employing a single modality. We conjecture this is because naive feature space through summation concatenation which take into account different...
Bearings play an important role as the connection between motor and gear. At present, data collected by most bearing datasets are vibration signals in one-dimensional time domain, then convolution or other methods used to analyze signals. In this work, a fault diagnosis method based on continuous wavelet transform scalogram (CWTS) multi-scale convolutional neural network (MS-CNN) is proposed paper. Continuous time-frequency relationship of signal extract frequency information signal, two...
Continuum discretized coupled-channel (CDCC) calculations of total fusion cross sections for reactions induced by the weakly bound nucleus $^{6}\mathrm{Li}$ with targets $^{28}\mathrm{Si}, ^{59}\mathrm{Co}, ^{96}\mathrm{Zr}, ^{198}\mathrm{Pt}$, and $^{209}\mathrm{Bi}$ at energies around Coulomb barrier are presented. In cluster structure frame $^{6}\mathrm{Li}\ensuremath{\rightarrow}\ensuremath{\alpha}+d$, short-range absorption potentials considered interactions between...
Application of computer images processing technology to analyze materials microstructural images, particularly metallographic has received increasing attention. The contain the mesoscopic information on structural relation and components materials. Quantitative analysis these can help correlate structures their performance properties at various levels. There are two challengeable issues necessary be resolved, i.e., automatic segmentation classification different microscopic in images. Since...
We localize the entropy functionals of G. Perelman and generalize his no-local-collapsing theorem pseudo-locality theorem. Our generalization is technically inspired by further development Li-Yau estimate along Ricci flow. It can be used to show Gromov-Hausdorff convergence K\"ahler flow on each minimal projective manifold general type.