A5103275090- Machine Fault Diagnosis Techniques
- Gear and Bearing Dynamics Analysis
- Structural Health Monitoring Techniques
- Structural Integrity and Reliability Analysis
- Magnetic Properties and Applications
- Non-Destructive Testing Techniques
- Face and Expression Recognition
- Power Quality and Harmonics
- Welding Techniques and Residual Stresses
- Advanced Adaptive Filtering Techniques
- Advanced Algorithms and Applications
- Advanced Electrical Measurement Techniques
- Advanced Sensor and Control Systems
Foshan University
2019-2021
Hunan University of Science and Technology
2019-2020
This article proposes a novel data-driven adaptive decomposition method named broadband mode (BMD) for analyzing complex signals containing components, such as square and sawtooth signals. For effective with “sharp corners,” an unavoidable error occurs when applying former methods, variational (VMD) ensemble empirical (EEMD), due to the Gibbs phenomenon interpolation of extreme points. Therefore, we propose BMD separating modes, narrowband noise in nonstationary signal. First, associative...
Bearing fault is the major of rotating machinery, in order to better identify bearing, multi-layer kernel learning methods based on local tangent space alignment (LTSA) and support vector machine (SVM) are proposed. In this method, supervised embedded into improved algorithm, realize feature extraction new data processing for equipment signal, then correctly classify faults by non-linear machine. The experiment result roller bearing diagnosis shows that SILTSA-SVM method has effect related methods.
There are two difficulties in the remaining useful life prediction of rolling bearings. First, vibration signals always interfered by noise signals. Second, some extracted features include useless information which may decrease accuracy. In order to solve problems above, corresponding methods employed this article. adaptive sparsest narrow-band decomposition is utilized for extracting degradation from noise. Compared with commonly used empirical mode method, including mixture and boundary...
A lot of adaptive signal decomposition methods have been applied for nonstationary DPMIG electrical signals as they are always affected by noise. Recently, to solve the problems former caused Gibbs phenomenon and calculation extremas when dealing with broadband such square sawtooth "sharp corners", mode (BMD) method was proposed application algorithm showed a good performance. The main idea BMD is searching in associative dictionary contains both narrowband using regulated differential...
The application of photovoltaic power is becoming more and extensive presently, when the existing time-frequency analysis methods are used to analyze mutation signals such as transient rise fall, cornered signal will produce Gibbs phenomenon leads errors. Thus, Broadband Mode Decomposition (BMD) method proposed. main idea BMD search in associated dictionary that contains wideband narrowband signals. However, algorithm may treat several components, applied a interfered by strong noise,...
A novel adaptive signal decomposition algorithm, broadband mode (BMD), is proposed for analyzing nonstationary signals. Unavoidable error will occur when applying former time-frequency methods to signals, which caused by Gibbs phenomenon and the calculation of extrema. To overcome that problem, BMD searching in associative dictionary contains both narrowband The procedure method as follows: First, collected datasets are analyzed composite multiscale fuzzy entropies (CMFEs) obtained effective...
Adaptive sparsest narrow-band decomposition is the most sparse solution to search for signals in over-complete dictionary library containing intrinsic mode functions, which transform signal into an optimization problem, but calculation accuracy must be improved case of strong noise interference. Therefore, combination with algorithm complementary ensemble empirical decomposition, a new method adaptive obtained. In white opposite paired symbol added target reduce reconstruction error and...
A vibration signal analysis system introduced by this paper adopts hybrid programming of Matlab and Delphi, using data file for agency to achieve communication. The procedure is written turned into the independent executable under environment Matlab, which called Delphi. combined languages matlab delphi with comprehensive utilization powerful numerical calculation processing function exploitation capability shortens period developing software greatly, saves development costs fully embodies...