{"title":"High compression ratio algorithm for power quality signals","authors":"R. E. Dapper, A. Susin, S. Bampi, C. Crovato","doi":"10.1109/ISIE.2015.7281664","DOIUrl":null,"url":null,"abstract":"This paper presents a compression algorithm for power quality (PQ) signals, which does not separate the signal into stationary and transient components. The proposed algorithm is composed of a number of different compression techniques which are combined to improve both compression ratio and total computing time. This method is based on a sequence of three phases. The first phase transforms the signal to the frequency domain using the FFT algorithm. In a second phase the signal is approximated by a polynomial approximation algorithm, which is finally compressed by a lossless compression algorithm. The proposed method is characterized by high compression ratio and low computational cost, making its implementation suitable for embedded systems.","PeriodicalId":377110,"journal":{"name":"2015 IEEE 24th International Symposium on Industrial Electronics (ISIE)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE 24th International Symposium on Industrial Electronics (ISIE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISIE.2015.7281664","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
This paper presents a compression algorithm for power quality (PQ) signals, which does not separate the signal into stationary and transient components. The proposed algorithm is composed of a number of different compression techniques which are combined to improve both compression ratio and total computing time. This method is based on a sequence of three phases. The first phase transforms the signal to the frequency domain using the FFT algorithm. In a second phase the signal is approximated by a polynomial approximation algorithm, which is finally compressed by a lossless compression algorithm. The proposed method is characterized by high compression ratio and low computational cost, making its implementation suitable for embedded systems.