A NOVEL DATA COMPRESSION ALGORITHM USING EMPIRICAL MODE DECOMPOSITION FOR WIRELESS MACHINE MONITORING DATA TRANSMISSION
Monitoring the health of a machine requires a lot of sensory data inputs. Because of the monitored machines that may operate in a hazardous environment or are moveable, wireless transmission becomes the only possible mean for data acquisition. To maintain precision in data acquisition, especially for vibration-based machine fault diagnosis, high sampling rate and large number of sampling points are required. However, the amount of data transmission using wireless mean is limited because of low transmission rate and lengthy transmission time. The solution is to compress the captured sensory data to an allowable number of samples so that the amount of data required to be is small. In this research, a novel data compression algorithm using Empirical Mode Decomposition (EMD) with Differential Pulse Code Modulation (DPCM) was developed. EMD is a new decomposition method used for detecting any instantaneous change in the monitored data. DPCM was mainly applied to compress the voice data by using the embedded linear predictor and quantizer prior to the commencement of transmission. To investigate the effectiveness of EMD combine with DPCM in data compression, vibration signals were collected and tested from machine suffered from misalignment and unbalance as well as normally operating conditions. The results show that the size of data has become much smaller than that of the raw data after applying the above new compression algorithm. The new algorithm also proves the error is negligible when the compressed data has been reconstructed back its original form at the receiver end. With the help of this new algorithm, even the requirement of large data sampling commonly required by vibration-based fault diagnosis can be fulfilled using wireless data communication.
Empirical Mode Decomposition Data Compression Wireless Data Transfer Machine Monitoring
Jeffery C. Chan Peter W. Tse
Smart Asset Laboratory, Department of Manufacturing Engineering and Engineering Management,City University of Hong Kong, Tat Chee Ave., Hong Kong
国际会议
北京
英文
249-259
2008-10-27（万方平台首次上网日期，不代表论文的发表时间）