机械振动 WSNs 子带峰值自适应量化融合编解码方法
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TP393. 1 TH17

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国家自然科学基金(52275087)项目资助


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

    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。

    Abstract:

    To address the problems of large amount of data transmission and low efficiency when transmitting vibration data in mechanical vibration wireless sensor network of intelligent operation and maintenance, this article proposes a subband peak adaptive quantization fusion codec method. First, the edge device performed discrete cosine transform on the original data to ensure the energy concentration of the subbands. Then, the outliers in the sub-band DCT coefficients are extracted, and quantified by the subband peak adaptive quantization method to reduce the data distortion. Finally, byte fusion and bit fusion methods are used to concatenate and fuse different quantified data to reduce data redundancy. The proposed method is compared with other data compression methods to evaluate the performance. The experimental results show that the proposed method can effectively realize the fusion and compression of multi-sensor vibration data in mechanical vibration wireless sensor networks with limited channel resources. When eight sensors collect and transmit at the same time, the data 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% .

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朱柯宇,汤宝平,付 豪,汤恒行,何 灏.机械振动 WSNs 子带峰值自适应量化融合编解码方法[J].仪器仪表学报,2023,44(4):296-303

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  • 在线发布日期: 2023-07-12
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