机械振动 WSNs 子带峰值自适应量化融合编解码方法

针对智能运维机械振动无线传感器网络多传感器传输振动数据时面临传输数据量大及传输效率低的问题,本文提出一种子带峰值自适应量化融合编解码方法。首先,传感器节点对原始数据进行离散余弦变换以确保子带能量集中;然后提取出子带DCT系数中的离群值,并用子带峰值自适应量化方法对其进行量化以减少数据失真;最后,用字节融合与比特融合方法将多传感器的量化数据进行融合拼接以减少数据冗余。将提出的方法与其他数据压缩方法进行对比以验证本文方法的性能。实验结果表明,该方法在8个节点同时采集传输的机械振动无线传感器网络中,数据压缩比为8.335时,重构信噪比为20.486 3 dB,节省37.2%的传输时间,可以有效实现信道资源受限的机械振动无线传感器网络多传感器振动数据的融合压缩。

A subband peak adaptive quantization fusion codec method for wireless sensor networks

To address the problems of large amount of data transmission and low efficiency when transmitting vibration data in mechanicalvibration wireless sensor network of intelligent operation and maintenance, this article proposes a subband peak adaptive quantization fusioncodec method. First, the edge device performed discrete cosine transform on the original data to ensure the energy concentration of thesubbands. Then, the outliers in the sub-band DCT coefficients are extracted, and quantified by the subband peak adaptive quantizationmethod to reduce the data distortion. Finally, byte fusion and bit fusion methods are used to concatenate and fuse different quantified datato reduce data redundancy. The proposed method is compared with other data compression methods to evaluate the performance. Theexperimental results show that the proposed method can effectively realize the fusion and compression of multi-sensor vibration data inmechanical vibration wireless sensor networks with limited channel resources. When eight sensors collect and transmit at the same time, thedata compression ratio is 8. 335, the reconstructed signal to noise ratio is 20. 486 3 dB, and the transmission time is reduced by 37. 2% .