300W Wind Turbine Model Fault Diagnosis and Speed Control Simulation
Simulink implementation of fault diagnosis and speed control for a 300W wind turbine model with detailed code analysis and control algorithm explanations
MATLAB Implementation of Dempster-Shafer Evidence Theory
MATLAB implementation of DS evidence theory - a crucial data mining framework for fault diagnosis applications with comprehensive algorithmic descriptions
Comprehensive MATLAB Function Suite for Fault Diagnosis
A self-developed comprehensive MATLAB function collection for fault diagnosis featuring statistical methods, time-domain analysis, time-series techniques, spectral analysis with power spectral density functions, and wavelet analysis methods. Each algorithm includes detailed implementation comments and usage guidelines.
SVM Currently Primarily Applied in Fault Diagnosis
Support Vector Machine (SVM) is widely used in fault diagnosis due to its effectiveness in addressing nonlinear problems and handling small sample datasets.
MATLAB Algorithms for Multifractal Spectrum and Box-Counting Dimension Calculation
Development and enhancement of multifractal spectrum algorithms and box-counting dimension calculation methods using MATLAB software, applicable for mechanical equipment fault diagnosis and feature extraction. These implementations provide valuable insights for applying fractal theory to diagnostic systems, featuring optimized code structure with efficient matrix operations and custom functions for partition-based analysis.
Latest Time-Frequency Analysis Techniques
Advanced time-frequency analysis techniques featuring multiple LMD algorithms and implementation programs for fault diagnosis applications.
EEMD and EMD: Advanced Fault Diagnosis Methods for Signal Extraction and Analysis
EEMD and EMD: Novel fault diagnosis techniques for effective signal extraction and accurate fault identification, featuring enhanced implementation with adaptive decomposition algorithms and code-based applications.
Artificial Intelligence - Neural Networks - Fault Diagnosis Classification Program
AI-powered neural network system for automated fault diagnosis and classification using machine learning algorithms
MATLAB Implementation of Wavelet Analysis for Signal Processing
A comprehensive MATLAB program for wavelet analysis-based signal processing designed for fault diagnosis applications, featuring data preprocessing, multi-resolution analysis, and diagnostic visualization capabilities.
Particle Swarm Optimization for BP Neural Network Weight Tuning
Using Particle Swarm Optimization to optimize BP neural network weights, the trained neural network is applied to fault diagnosis for pattern recognition, achieving faster convergence compared to standard BP neural networks