Diesel-Engine-Fault-Diagnosis

DOA估计常用算法，包括：music算法，卡尔曼滤波算法，自适应梯度算法，空间平滑算法，改进的空间平滑算法。(DOA estimation algorithm used, including: music algorithm, Kalman filter algorithm, adaptive gradient algorithm, spatial smoothing algorithm, the improved spatial smoothing algorithm.)

tempalte matchin progrma used

说明：  针对“BreastCancer”数据集，作为对比，第一次对特征集直接进行SVM分类，第二次使用粒子群算法进行特征选择后再进行SVM分类。并且对比和分析了两次分类的结果。(For "BreastCancer" data set, as a comparison, the first time the feature set is directly classified by SVM, and the second time the feature set is selected by particle swarm optimization before SVM classification. The results of the two classifications are compared and analyzed.)

说明：  有关图形图像的相关资料及matlab源码(For information and graphic images matlab source)

说明：  The model used for creating the reference voltage is shown in Fig. 4. First, photovoltaic output current (Ipv) and output voltage (Vpv) are passed through a first order low pass filter with a magnitude of G = 1 and a time constant of T = 0.01 seconds in order to filter out the high frequency components or harmonics from these signals as shown in Fig. 5 and Fig. 6. The filtered current and voltage signals (Ipv_F and Vpv_F) are then fed into the MPPT control block that uses the Incremental Conductance Tracking Algorithm. An algorithm that is based on the fact the slope of the PV array power curve shown in Fig. 7 is zero at the Maximum Power Point (MPP), positive on the left of the MPP, and negative on the right. The MPP can thus be tracked by comparing the instantaneous conductance (I/V) to the incremental conductance (∆ I/∆ V) [11] as in (1):

关于matlab中仿真器fis的源代码，自己设计的。(About fis code soures)

This implements Lie-derivative based complete observability analysis for relative localization using equabilent relative measurement model.

实现了蚁群算法求解TSP问题。注释详细 function[R_best,L_best,L_ave,Shortest_Route,Shortest_Length]=ACATSP(C,NC_max,m,Alpha,Beta,Rho,Q) ------------------------------------------------------------------------- 主要符号说明 C n个城市的坐标，n×2的矩阵 NC_max最大迭代次数 m蚂蚁个数 Alpha表征信息素重要程度的参数 Beta表征启发式因子重要程度的参数 Rho信息素蒸发系数 Q信息素增加强度系数 R_best各代最佳路线 L_best各代最佳路线的长度 ========================================================================= (Ant Colony Algorithm for the realization of the TSP problem. Notes the detailed function [R_best, L_best, L_ave, Shortest_Route, Shortest_Length] = ACATSP (C, NC_max, m, Alpha, Beta, Rho, Q) ------------------------------------------------------------------- The main symbol------ C n that cities coordinates, n × 2 matrix NC_max the largest number of iterations m the number of Alpha ant pheromones characterized the importance of the parameters Beta factor heuristic importance of characterization of the parameters Rho evaporation coefficient of pheromone pheromone Q increase in intensity coefficient R_best best route generations generations L_best the length of the best route ====== ================================================== =================)

MCA算法源程序，可用于稀疏分解，信号分类，图像修复，信号还原(MCA algorithm source code can be used for sparse decomposition, signal classification, image restoration, signal reduction)

nous intéressons à la détection et à la localisation de défauts dans des systèmes dynamiques en combinant simultanément l’analyse en composantes principales et la transformée en ondelettes. Ce procédé d’analyse et de traitement, connu souvent sous le nom de MSPCA, permet à la fois l’extraction de la corrélation entre les différents capteurs (approche ACP) et le calcul de l’auto corrélation pour chaque capteur (approche ondelette).