A divide-and-compress lossless compression scheme for bearing vibration signals in wireless sensor networks

Abstract

Remote rotating machinery condition monitoring system based on wireless sensor networks (WSNs) is an attractive application recently. Bearing is the critical important component in rotating machinery. The bearing vibration-based condition monitoring requires huge amount of vibration data. This is a big challenge to the limited resources of WSNs. So many data compression methods are proposed, but less focus on the lossless compression. In this paper, a novel lossless compression scheme based on divide-and-compress strategy is proposed, which combines the lossy compression into the lossless compression framework to enhance the compression capability. First, the discrete cosine transform is employed in data dividing to split original data into two parts that have different data characteristics. Then, according to the characteristics, several specially designed schemes are exploited for encoding the data. As described in the experimental results, the proposed compression scheme can effectively compress bearing vibration signals without data loss.