针对水电机组锥管进人门螺栓松动故障定位问题,提出了基于射频识别(radio frequency identification,RFID)的无源无线水电机组锥管进人门螺栓松动故障定位改进虚拟参考消除(virtual reference elimination,VIRE)算法。首先,确定超高频R...针对水电机组锥管进人门螺栓松动故障定位问题,提出了基于射频识别(radio frequency identification,RFID)的无源无线水电机组锥管进人门螺栓松动故障定位改进虚拟参考消除(virtual reference elimination,VIRE)算法。首先,确定超高频RFID读写器下所有螺栓松动故障辨识节点内标签的接收信号强度指示(received signal strength indicator,RSSI)值;然后,采用样条插值法插入虚拟标签,计算出虚拟螺栓松动故障辨识节点内标签的RSSI值;最后,采用动态阈值(threshold,Th)使最邻近螺栓松动故障辨识节点内标签数接近最优值,求出待测螺栓松动故障辨识节点内标签的定位坐标并记录,选择几组数据取平均值作为最终结果。结果表明,改进VIRE算法的平均定位误差相对于基于动态有源RFID校准的位置识别(location identification based on dynamic active RFID calibration,LANDMARC)算法、传统VIRE算法分别降低了98.72%、25.27%。该研究成果可以满足复杂环境下的水电机组锥管进人门螺栓松动故障定位需要。展开更多
The most common location algorithms based on received signal strength （RSS） are location identification based on dynamic active radio frequency identification （LANDMARC） and virtual reference elimination （VIRE）....The most common location algorithms based on received signal strength （RSS） are location identification based on dynamic active radio frequency identification （LANDMARC） and virtual reference elimination （VIRE）. However, both the original algorithms suffer from some drawbacks. In this paper, several aspects of the two original algorithms have been modified to reduce the positioning errors. Firstly, Lagrange interpolation has been used instead of linear interpolation. Secondly, adaptive threshold has been introduced in the new algorithm. Thirdly, insert virtual reference tags to improve the location accuracy of the boundary of the sensing area. Finally, combine LANDMARC with VIRE to absorb both advantages. Compared with the original algorithms, on average, simulated results show that the modified algorithms can improve the location performance efficiently and achieve the goal of accurate positioning in indoor environment.展开更多
文摘针对水电机组锥管进人门螺栓松动故障定位问题,提出了基于射频识别(radio frequency identification,RFID)的无源无线水电机组锥管进人门螺栓松动故障定位改进虚拟参考消除(virtual reference elimination,VIRE)算法。首先,确定超高频RFID读写器下所有螺栓松动故障辨识节点内标签的接收信号强度指示(received signal strength indicator,RSSI)值;然后,采用样条插值法插入虚拟标签,计算出虚拟螺栓松动故障辨识节点内标签的RSSI值;最后,采用动态阈值(threshold,Th)使最邻近螺栓松动故障辨识节点内标签数接近最优值,求出待测螺栓松动故障辨识节点内标签的定位坐标并记录,选择几组数据取平均值作为最终结果。结果表明,改进VIRE算法的平均定位误差相对于基于动态有源RFID校准的位置识别(location identification based on dynamic active RFID calibration,LANDMARC)算法、传统VIRE算法分别降低了98.72%、25.27%。该研究成果可以满足复杂环境下的水电机组锥管进人门螺栓松动故障定位需要。
基金supported by the National Natural Science Foundation of China (61003237)
文摘The most common location algorithms based on received signal strength （RSS） are location identification based on dynamic active radio frequency identification （LANDMARC） and virtual reference elimination （VIRE）. However, both the original algorithms suffer from some drawbacks. In this paper, several aspects of the two original algorithms have been modified to reduce the positioning errors. Firstly, Lagrange interpolation has been used instead of linear interpolation. Secondly, adaptive threshold has been introduced in the new algorithm. Thirdly, insert virtual reference tags to improve the location accuracy of the boundary of the sensing area. Finally, combine LANDMARC with VIRE to absorb both advantages. Compared with the original algorithms, on average, simulated results show that the modified algorithms can improve the location performance efficiently and achieve the goal of accurate positioning in indoor environment.
