Neural Network for Pulsed Ultrasonic Vibration Control of Electrical Equipment

A. Bychkov, L. Slavutskii, Elena Vladimirovna Slavutskaya
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引用次数: 7

Abstract

The technique based on contactless pulsed ultrasonic control of electrical equipment's low frequency vibrations is proposed. Experimental laboratory measurements were carried out under conditions when the frequency of ultrasonic probing pulses is comparable to the vibrations frequency of the controlled object's surface (fractions of Hz). In this case, it is proposed to use the simplest artificial neural network (ANN) with back error propagation to estimate the vibrations frequency in the ultrasonic sensing data processing. ANN training was carried out by numerical simulation of ultrasonic signals scattered on the vibrating surface, and then ANN was used to estimate the frequency of vibrations from experimental data. It is shown that at the frequency of ultrasonic sounding in 3-4 pulses for the vibrations period, the use of ANN allows to ensure the accuracy of determining the unsteady vibrations frequency not less than units of percent.
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电气设备脉冲超声振动控制的神经网络
提出了一种基于非接触脉冲超声控制电气设备低频振动的技术。实验实验室测量是在超声探测脉冲的频率与被控物体表面的振动频率(赫兹的分数)相当的条件下进行的。针对这种情况,提出了在超声传感数据处理中,使用最简单的带反向误差传播的人工神经网络(ANN)来估计振动频率。通过对分散在振动表面的超声信号进行数值模拟,进行人工神经网络训练,然后利用实验数据估计振动频率。结果表明,在振动周期内超声探测频率为3-4个脉冲时,使用人工神经网络可以保证确定非定常振动频率的精度不小于百分之一。
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