机械振动无线传感器网络大量数据传输发射功率优化控制方法  

Transmit power optimization control method for a mechanical vibration wireless sensor network with a lot of transmission data

作　　者：朱亮亮 汤宝平[1] 黄艺 邓蕾[1] ZHU Liangliang;TANG Baoping;HUANG Yi;DENG Lei(State Key Lab of Mechanical Transmission,Chongqing University,Chongqing 400030,China)

机构地区：[1]重庆大学机械传动国家重点实验室,重庆400030

出　　处：《振动与冲击》2020年第17期275-280,共6页Journal of Vibration and Shock

基　　金：国家自然科学基金(51675067,51775065)。

摘　　要：针对机械振动无线传感器网络采集节点采用最大发射功率传输大量数据导致传输能耗高的问题,提出了一种机械振动无线传感器网络大量数据传输发射功率优化控制方法。首先通过统计试验确定链路质量指示(Link Quality Indicator,LQI)与丢包重传率、节点发射功率与传输单个数据包所需能耗的离散关系,以及节点发射功率与LQI的数学模型的类型;然后使用最小二乘法对离散数据进行拟合,构建节点发射功率与传输能耗的关系模型;最后,根据该模型优化得出最小能耗对应的发射功率,在每次传输数据前节点只需发送极少量数据包便可重新优化计算发射功率并更新。试验结果表明,所提的优化控制方法能随工作环境的变化保证优化控制发射功率,降低机械振动无线传感器网络传输能耗。Aiming at the problem of a mechanical vibration wireless sensor network’s collection node using the maximum transmit power to transmit a lot of data and cause high transmission energy consumption,a transmit power optimization control method for this network was proposed.Firstly,statistical tests were conducted to determine discrete relations among link quality indicator(LQI),packet loss retransmission rate,node transmit power and energy consumption required to transmit a single data packet,as well as mathematical model types of node transmit power and LQI.Then,the least squares method was used to fit these discrete data,and construct the relation model between node transmit power and transmission energy consumption.Finally,this relation model was optimized to obtain the transmit power corresponding to the minimum power consumption.Thus,before each time to transmit data,the collection node only needed to transmit a very small number of data packets,and then the model was used to reoptimize and update the transmit power.Test results showed that the proposed method can optimally control the transmit power to reduce the transmission energy consumption of mechanical vibration wireless sensor network.

关 键 词：机械振动监测 无线传感器网络(WSNs) 发射功率 链路质量指示(LQI) 丢包重传率 传输能耗 

分 类 号：TP274.2[自动化与计算机技术—检测技术与自动化装置] TP393.1[自动化与计算机技术—控制科学与工程]