基于多频超声的变压器油质在线监测有效性研究

Research on the effectiveness of transformer oil on-line monitoring based on multi-frequency ultrasonic

为解决变压器传统检测方法中常规试验项目和试验周期的局限性,提出一种基于多频超声的变压器油状态监测的新方法。先利用油化实验的多指标综合分析对选取的变压器油样进行状态等级评定,再采用多频超声设备对待测变压器油发射一束不同频率的超声波,并利用BP神经网络建立超声波接收模块实时得到的各相超声参数(波速,幅频数据,相频数据)和变压器油状态种类的映射关系,验证该多频超声设备能否实时、准确、全面的对变压器绝缘油的状态进行监测。结果显示:BP神经网络可以在超声参数和变压器油状态等级间建立良好的对应关系,利用多频超声设备进行变压器油在线监测是一种行之有效的监测方法。

In order to solve the limitations of current routine test items and test cycles in traditional transformer testing methods,a new method of transformer oil state monitoring based on multi-frequency ultrasonic is proposed in this paper.Firstly,the multi-indicator comprehensive analysis of the results of oiling experiment is carried out to evaluate the status of the selected transformer oil samples,and then,a multi-frequency ultrasonic device is used to transmit the ultrasonic waves of different frequencies to the selected transformer oil,and the ultrasonic receiver module obtained the ultrasonic parameters(wave speed,amplitude-frequency data,and phase-frequency data)in real time.The BP neural network is used to establish the mapping relationship between the ultrasonic spectrum parameters and the state of transformer oil and verify whether the multi-frequency ultrasonic equipment can monitor the status of transformer insulation oil in real time,accurately and comprehensively.The results show that the BP neural network can establish a good correspondence relationship between ultrasonic parameters and transformer oil status levels.The use of multi-frequency ultrasonic equipment for transformer oil online monitoring is an effective method.