基于小波分析的图书馆电子阅览设备故障检测方法

针对图书馆电子阅览设备在长时间运行时受到其他设备干扰的影响,导致设备故障的检测性能变差,以提高图书馆电子阅览设备故障的检测性能为目的,提出了基于小波分析的图书馆电子阅览设备故障检测方法。利用小波分析法将电子阅览设备故障信号与干扰信号分离,采集到无干扰的故障信号,对采集到的电子阅览设备故障信号进行预处理,得到梅尔倒谱系数分析结果,利用动态时间规整函数识别了图书馆电子阅览设备故障,在BP神经网络的基础上,引入小波函数作为小波神经网络的传递函数,根据小波神经网络的结构,计算了小波神经网络隐含层的输出,构建了小波神经网络,最后通过设计电子阅览设备故障检测算法,实现了图书馆电子阅览设备故障的检测。实验结果表明,基于小波分析的图书馆电子阅览设备故障检测方法不仅可以提高故障检测速率,还可以提高检测准确率,从而电子阅览设备故障的检测性能大大提高。

Fault detection method of library electronic reading equipment based on wavelet analysis

In order to improve the performance of the electronic library equipment,the fault detection method based on wavelet analysis is proposed.The fault signal of electronic reading equipment is separated from interference signal by wavelet analysis,and the non-interference fault signal is collected.After preprocessing the fault signal of electronic reading equipment,the result of Mel cepstrum coefficient analysis is obtained.The fault of library electronic reading equipment is identified by using dynamic time warping function.On the basis of BP neural network,wavelet function is introduced on the basis of BP neural network,wavelet function is introduced as the transfer function of wavelet neural netwark.The output of hidden layer of wavelet neural network is calculated to construct wavelet neural network,and finally the fault detection of library electronic reading equipment is realized by designing fault detection algorithm of electronic reading equipment.The experimental results show that the fault detection method based on wavelet analysis can not only improve the fault detection rate,but also improve the detection accuracy,so the fault detection performance of electronic reading equipment is greatly improved.