基于DCS的多轴承振动信号重构算法研究

A Study on Reconstruction Algorithm of Multi-Bearing Vibration Signal Based on DCS

针对轴承状态监测中多传感器会产生大量数据,给数据存储、传输和处理带来困难的问题,提出一种适用于多轴承振动信号的分布式压缩感知重构算法。通过引入离散余弦变换,实现了轴承振动信号在变换域的稀疏化;通过基于TSBL的重构算法,实现了多轴承振动信号的联合重构。实验利用机械故障模拟器产生的多传感加速度振动信号对提出的算法进行了分析。结果表明:提出的基于分布式压缩感知技术的联合重构算法能以更少数据重构原始信号,进一步提升了重构性能,解决了轴承状态监测中多传感器数据采集造成的问题。

As the multi-sensor generate large amounts of data in bearing condition monitoring,which present difficulties in data storage,transmission and processing,this paper proposes a distributed compression sensing reconstruction algorithm suitable for multi-bearing vibration signals.By introducing discrete cosine transform,the bearing vibration signal was sparse in the transform domain,and joint reconstruction of bearing vibration signals was realized by the distributed compression reconstruction algorithm based on TSBL.The proposed algorithm was analyzed by using the multi-sensing acceleration vibration signal produced by the mechanical fault simulator.The results show that the distributed joint reconstruction algorithm proposed in this paper can reconstruct original signals with less data,achieve better reconstruction performance,and solve the problem of multi-sensor data acquisition in bearing condition monitoring.