Volterra级数与神经网络的光纤传感器网络故障诊断

Fault diagnosis of optical fiber sensor network with Volterra series and neural network

故障诊断准确性直接影响光纤传感器网络的应用价值,为了改善光纤传感器网络故障的诊断性能,本文提出了一种Volterra级数和神经网络的光纤传感器网络故障诊断方法。首先采用Volterra级数提取光纤传感器故障的信号特征,然后采用神经网络中的相关向量机对光纤传感器特征进行学习,建立光纤传感器故障诊断识别器,最后通过具体光纤传感器网络对其性能进行仿真测试。结果表明,本文方法能够分析光纤传感器网络的故障特征,较好完成了光纤传感器网络的故障诊断,而且结果要优于其他光纤传感器故障诊断方法。

Fault diagnosis accuracy directly affects the application value of optical fiber sensor network. In order to improve the performance of optical fiber sensor network fault diagnosis, this paper proposed a fault diagnosis method for optical fiber sensor networks with Volterra series and neural network. Volterra series is used to extract signal character-- istics of fiber optic sensor fault, and relevance vector the optical fiber sensor, and the fault diagnosis model machine in neural network is used to study the characteristics of of the optical fiber sensor is established, finally, the simulation test is carried out by some optical fiber sensor network data. The results show that the method in this paper can be used to analyze the fault characteristics and can complete the fault diagnosis of the optical fiber sensor network, and the results are better than other optical fiber sensor fault diagnosis method.