针对接收信号强度指示(Received Signal Strength Indication,RSSI)测距定位算法存在定位结果不稳定且精度低的问题,本文分析了一种基于狄克逊检验法滤波RSSI的高斯牛顿定位(Dixon test filter RSSI Gauss-Newton,DF-RSSI-GN)算法。采...针对接收信号强度指示(Received Signal Strength Indication,RSSI)测距定位算法存在定位结果不稳定且精度低的问题,本文分析了一种基于狄克逊检验法滤波RSSI的高斯牛顿定位(Dixon test filter RSSI Gauss-Newton,DF-RSSI-GN)算法。采用狄克逊(Dixon)检验法滤波剔除观测信号异常值使得观测数据偏度降低,根据偏态程度对观测信号进行高斯均值滤波并通过非线性回归模型拟合RSSI衰减模型参数,在目标点坐标求解阶段利用滤波后的观测信号确定不同方向上的权值进行高斯牛顿(Gauss-Newton)迭代定位。实验结果表明,DF-RSSI-GN算法定位平均精度在1.5 m左右,相比RSSI定位算法和最小二乘定位算法,精度提高1倍以上。展开更多
The precise detection of flaw echoes buried in backscattefing noise caused by material microstructure is a problem of great importance in uhrasonic non-destructive testing (NDT). In this work, empirical mode decompo...The precise detection of flaw echoes buried in backscattefing noise caused by material microstructure is a problem of great importance in uhrasonic non-destructive testing (NDT). In this work, empirical mode decomposition (EMD) is proposed to deal with ultrasonic signal. A time-frequency filtering method based on EMD is designed to suppress noise and enhance flaw signals. Simulated results are presented, showing that the proposed method has an excellent performance even for a very low signal-to-noise ratio (SNR). The improvement in flaw detection was experimentally verified using stainless steel pipe sample with artificial flaws.展开更多
文摘针对接收信号强度指示(Received Signal Strength Indication,RSSI)测距定位算法存在定位结果不稳定且精度低的问题,本文分析了一种基于狄克逊检验法滤波RSSI的高斯牛顿定位(Dixon test filter RSSI Gauss-Newton,DF-RSSI-GN)算法。采用狄克逊(Dixon)检验法滤波剔除观测信号异常值使得观测数据偏度降低,根据偏态程度对观测信号进行高斯均值滤波并通过非线性回归模型拟合RSSI衰减模型参数,在目标点坐标求解阶段利用滤波后的观测信号确定不同方向上的权值进行高斯牛顿(Gauss-Newton)迭代定位。实验结果表明,DF-RSSI-GN算法定位平均精度在1.5 m左右,相比RSSI定位算法和最小二乘定位算法,精度提高1倍以上。
文摘The precise detection of flaw echoes buried in backscattefing noise caused by material microstructure is a problem of great importance in uhrasonic non-destructive testing (NDT). In this work, empirical mode decomposition (EMD) is proposed to deal with ultrasonic signal. A time-frequency filtering method based on EMD is designed to suppress noise and enhance flaw signals. Simulated results are presented, showing that the proposed method has an excellent performance even for a very low signal-to-noise ratio (SNR). The improvement in flaw detection was experimentally verified using stainless steel pipe sample with artificial flaws.