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AE detection of crack signal in tank shell using the multi-sensors with adaptive weighted fusion method

机译:自适应加权融合方法的多传感器声发射检测罐壳裂纹信号

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In order to detect the crack accurately and make full use of the information from multi-sensors, this paper proposes a detection method based on the adaptive weighted fusion method and Kalman filter method for tank crack detection. The fusion method of four sensors is deduced, and the simulation with noise interference is utilized to analyze the effectiveness of the proposed method. An experiment is implemented to obtain the signals with noise interference from four sensors. The proposed method is used to obtain the weight of each sensor, the signals from four sensors are fused by the calculated weights, and then Kalman filter method is employed to remove the noise. Compared to the method with only Kalman filter method, the proposed method with adaptive weighted fusion has a higher signal noise ratio which is 9.89dB. The result shows that the proposed method can make full use of multi-sensor information and has a better noise suppression.
机译:为了准确地检测裂纹并充分利用多传感器的信息,提出了一种基于自适应加权融合法和卡尔曼滤波法的坦克裂纹检测方法。推导了四个传感器的融合方法,并通过噪声干扰仿真分析了该方法的有效性。进行了一个实验,以从四个传感器获得具有噪声干扰的信号。提出的方法用于获得每个传感器的权重,将四个传感器的信号与计算出的权重融合,然后采用卡尔曼滤波方法去除噪声。与仅采用卡尔曼滤波的方法相比,所提出的自适应加权融合方法具有更高的信号噪声比,为9.89dB。结果表明,该方法可以充分利用多传感器信息,具有较好的噪声抑制效果。

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