By researching the data quality problem in the monitoring and diagnosis system （MDS） , the method of detecting non-condition data based on the development trend of equipment condition is proposed, and three requirem...By researching the data quality problem in the monitoring and diagnosis system （MDS） , the method of detecting non-condition data based on the development trend of equipment condition is proposed, and three requirements of criteria for detecting non-condition data： dynamic, syntheses and simplicity are discussed. According to the general mode of data management in MDS, a data quality assurance system （DQAS） comprising data quality monitoring, data quality diagnosis, detection criteria adjusting and artificial confirmation is set up. A route inspection system called MTREE realizes the DQAS. Aiming at vibration data of route inspection, two detecting criteria are made. One is the quality monitoring parameter, which is found through combining and optimizing some fundamental parameters by genetic programming （GP）. The other is the quality diagnosis criterion, i. e. pseudo distance of Spectral-Energy-Vector （SEV） named Adjacent J-divergence, which indicates the variation degree of adjacent data＇s spectral energy distribution. Results show that DQAS, including these two criteria, is effective to improve the data quality of MDS.展开更多
基金This paper is supported by National Natural Science Foundation of China under Grant No.50335030
文摘By researching the data quality problem in the monitoring and diagnosis system （MDS） , the method of detecting non-condition data based on the development trend of equipment condition is proposed, and three requirements of criteria for detecting non-condition data： dynamic, syntheses and simplicity are discussed. According to the general mode of data management in MDS, a data quality assurance system （DQAS） comprising data quality monitoring, data quality diagnosis, detection criteria adjusting and artificial confirmation is set up. A route inspection system called MTREE realizes the DQAS. Aiming at vibration data of route inspection, two detecting criteria are made. One is the quality monitoring parameter, which is found through combining and optimizing some fundamental parameters by genetic programming （GP）. The other is the quality diagnosis criterion, i. e. pseudo distance of Spectral-Energy-Vector （SEV） named Adjacent J-divergence, which indicates the variation degree of adjacent data＇s spectral energy distribution. Results show that DQAS, including these two criteria, is effective to improve the data quality of MDS.
