基于无线声发射传感器系统的活立木含水率 诊断方法研究

水分在活立木的生长代谢过程中起着至关重要的作用，实时准确的含水率测量对于立木培育及林木经营具有关键指导意义。以无损检测活立木树干含水率为主要目标，设计并实现了一套基于无线声发射传感器网络(WASN)的木材含水率诊断系统。首先WASN节点高速采样树干表皮的声发射信号，接着计算其特征参数并无线传输至网关，然后采用最大相关最小冗余(mRMR)判据从中筛选出最优特征组合，并经由麻雀算法优化的支持向量机(SSA-SVM)建立含水率辨识模型，最后即可进行在线实时的长期监测诊断。分别在水杉、杨树、松树和山毛榉四类树种上进行了实测，结果表明，诊断准确率最低为95.5%,所设计WASN完全具备长期部署观测树木蒸腾作用的功能。

Research on diagnosis method of standing wood moisture content based on wireless acoustic emission sensor system

Water content plays a crucial role in the growth and metabolism of standing trees. Real-time and accurate measurement of water content is of key guiding significance for standing tree cultivation and forest management. A wood moisture content diagnosis system based on wireless acoustic emission sensor network (WASN) was designed and implemented for the nondestructive testing of living wood. Firstly, the acoustic emission signals of the trunk epidermis were sampled at high speed by the WASN node, and then the characteristic parameters were calculated and transmitted to the gateway wirelessly. After that, the optimal feature combination was selected by the MRMR criterion, and the water content identification model was established by the support vector machine (SSA-SVM) optimized by the sparrow algorithm. Finally, on-line real-time long-term monitoring and diagnosis can be carried out. The system has been tested on four species of met sequoia, poplar, pine and beech respectively, and the results show that the lowest diagnostic accuracy is 95. 5%. The design of WASN was fully capable of long-term observation of tree transpiration.