Power quality disturbance classification method of twin support vector machine based on ITD decomposition and sparrow optimization

The invention discloses a power quality disturbance classification method of a twin support vector machine based on ITD decomposition and sparrow optimization, and the method comprises the following four steps: 1, collecting different types of power quality disturbance signals containing interference by using power quality monitoring equipment; step 2, processing the acquired power quality disturbance signal by adopting ITD decomposition to obtain a series of inherent rotation components (PRC), and screening out effective PRC components by utilizing entropy and hyper entropy of a cloud model; 3, respectively calculating the fuzzy entropy and the energy entropy of the effective PRC component, and sequentially arranging the fuzzy entropy and the energy entropy obtained by calculation to form a feature matrix; 4, dividing the extracted feature data into a test group and a training group, inputting data of the training group into a twinborn support vector machine (TWSVM), searching an optimized ...