Power quality analysis technology for Uninterruptible Power Supply(UPS)system
In response to the shortcomings of low accuracy,poor real-time performance,and high cost in the current UPS power quality detection process,a UPS power quality detection and recognition algorithm is proposed based on the VMD-SAE-1DCNN model.For the nonlinear and non-stationary characteristics of electric energy signals,the variational modal algorithm is used to decompose the original signal to obtain the intrinsic modal signal.At the same time,the sparse Auto Encoder is used to extract the characteristics of the intrinsic mode signal,and the multi-layer one-dimensional Convolutional Neural Network model is established to train the characteristics,which improves the operation efficiency.The experimental test results show that the proposed algorithm has the best iteration times and running time in the comparison algorithm,with a classification accuracy of over 97%,fully proving the effectiveness of the proposed algorithm improvement.
UPSvariational modal algorithmSparse Auto EncoderConvolutional Neural Networkpower quality analysis
万方数据
维普
