基于多传感器数据融合的漏磁信号采集与处理

Magnetic flux leakage signal acquisition and processing based on multi-sensor data fusion

漏磁检测以其高信噪比、高灵敏度和高检测效率,在无损检测中得到了广泛应用。随着科学技术的发展,传统的信号处理方法越来越不适应现代工业的需要,提出一种基于多传感器数据融合技术的漏磁信号处理方法。采用小波去噪的方法,并利用径向基函数(RBF)神经网络的数据融合技术对缺陷信号进行检测处理。仿真结果表明,采用这种方法可以有效提高系统的检测能力和信号精度。

Magnetic flux leakage testing method is widely applied for high signal-to-noise ,high sensitivity and detection efficiency in nondestructive testing. According to development of Science and technology, traditional signal processing method modern industry＇ need. So this article introduces a magnetic flux leakage signal process method based on muhi-sensor data fusion technology. With the wavelet denoising algorithm, the flaw signal is detected by data fusion technology of radial basis function （RBF） neural network. The results show that it improves the detection ability and the precision of the signal.