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为了解决动态测试系统中,由于电力传感器失调节点定位偏差,产生的测试数据失调现象,提出基于改进关联挖掘算法(Improved Mining Association Algorithm,IMA)及FPGA实现的电力传感器失调节点定位方法,对关联挖掘算法进行了详细的逻辑分析。利用该算法思路获取电力传感器失调节点间的关联规则,基于该关联规则,通过电力传感器失调节点的DV-Hop定位算法,将未知电力传感器失调节点到信标节点间的距离,用网络中节点平均每跳距离和到信标节点间的跳数乘积表示,采用三角定位获取电力传感器失调节点的位置。为了将最佳电力传感器动态定位器运用在在线检测中,在动态定位器的硬件结构中融入了分布式算法,给出了电力传感器动态定位器的高速并行FPGA实现过程。实验结果说明,所提方法进行电力传感器失调节点定位时的执行时间与内存使用量方面均优于传统方法,定位准确率方面比传统方法也有很大提高,有一定的实际应用价值。
In order to solve the imbalance of test data generated by the misalignment of power sensors in dynamic test system, this paper proposes a method to locate the misaligned nodes of power sensors based on Improved Mining Association Algorithm (IMA) and FPGA, Algorithm for a detailed logic analysis. Based on this association rule, DV-Hop localization algorithm of power sensor offset node is used to calculate the distance between unknown node of power sensor and beacon node, and the average of nodes in the network is averaged The distance between each hop and the number of hops to the beacon node is expressed as the location of the power sensor offset node by triangulation. In order to apply the best dynamic sensor of power sensor in on-line detection, a distributed algorithm is incorporated in the hardware structure of dynamic locator, and a high-speed parallel FPGA implementation of dynamic sensor of power sensor is presented. The experimental results show that the proposed method outperforms the traditional method in terms of the execution time and memory usage of the power sensor misalignment node. Compared with the traditional method, the accuracy of the positioning method is also greatly improved, which has certain practical value.