[1]王 刚,彭彦卿,庄志坚,等.基于无刷直流电机电流的断路器手车梅花触头对中度诊断方法[J].高压电器,2020,56(03):46-53.[doi:10.13296/j.1001-1609.hva.2020.03.007]
 WANG Gang,PENG Yanqing,ZHUANG Zhijian,et al.Method to Diagnose the Concentricity of Tulip Contacts of a Medium Voltage Circuit Breaker Handcart Based on the Armature Current of a BLDCM[J].High Voltage Apparatus,2020,56(03):46-53.[doi:10.13296/j.1001-1609.hva.2020.03.007]
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基于无刷直流电机电流的断路器手车梅花触头对中度诊断方法()
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《高压电器》[ISSN:1001-1609/CN:61-11271/TM]

卷:
第56卷
期数:
2020年03期
页码:
46-53
栏目:
研究与分析
出版日期:
2020-03-15

文章信息/Info

Title:
Method to Diagnose the Concentricity of Tulip Contacts of a Medium Voltage Circuit Breaker Handcart Based on the Armature Current of a BLDCM
作者:
王 刚1 彭彦卿1 庄志坚2  孙利杰1 熊逸伟3
(1. 厦门理工学院电气工程与自动化学院, 福建 厦门 361024; 2. ABB(中国)有限公司中压产品技术中心, 福建 厦门 361101; 3. 国网娄底供电公司, 湖南 娄底 417000)
Author(s):
WANG Gang1 PENG Yanqing1 ZHUANG Zhijian2 SUN Lijie1 XIONG Yiwei3
(1. School of Engineering and Automation, Xiamen University of Technology, Fujian Xiamen 361024, China; 2. ABB (China) Co., Ltd. Power Product Medium Voltage Technology Center, Fujian Xiamen 361101, China; 3. State Grid Loudi Power Supply Company, Hunan Loudi 417000, China)
关键词:
断路器手车 无刷直流电机电枢电流 梅花触头与静触头对中度 高斯拟合 BP神经网络
Keywords:
circuit breaker handcart armature current of a brushless DC motor concentricity between tulip contacts and static contacts Gauss fitting BP neural network
DOI:
10.13296/j.1001-1609.hva.2020.03.007
摘要:
目前,市场上可抽出式高压开关柜无法确认断路器手车梅花触头与静触头的对中度是否良好。文中提出了以无刷直流电机作为底盘车驱动电机,利用电枢电流数据实现手车梅花触头和静触头对中度诊断的方法。首先,为确定电枢电流的影响因素,分析无刷直流电机数学模型并仿真验证;利用具有不同偏心距离的静触头代替试验台原静触头,模拟不同程度的对中偏差;其次,以均值滤波和高斯拟合处理啮入阶段曲线,提取拟合函数参数A、xmax和啮入阶段电流均值为曲线特征,训练BP神经网络模型用于对中度诊断;最后,采集新数据,对所述方法进行试验验证。结果表明,所述方法对手车梅花触头和静触头对中度识别精度高。该方法为断路器手车梅花触头对中度诊断提供了一种思路。
Abstract:
At present, there is no method for high voltage withdrawable switchgears to determine whether the concentricity of the tulip contacts of a circuit breaker handcart is good. This paper used a brushless DC motor as the driving motor for the circuit breaker handcart, and a method to diagnosis the concentricity of the tulip contacts of a medium voltage circuit breaker handcart was proposed. First of all, the mathematic model of the brushless DC motor was analyzed to determine the influencing factor of armature current. Static contacts with different eccentric distances were used to replace the original static contacts of the test bed to simulate different degrees of center deviation. Secondly, the current curves were processed by mean filter and Gauss fitting, and the parameter of the fitting function including A, xmax and the mean current of the meshing stage were extracted as the curves characteristics. The characteristics was used to train a BP neural network which was used to diagnosis the concentricity of tulip contacts. Finally, more data was sampled to test the method. It has been proved that the method was able to recognize different degrees of center deviation, and the method is high accuracy. It can provide a new idea to diagnosis the concentricity of tulip contacts of a medium voltage circuit breaker handcart.

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备注/Memo

备注/Memo:
收稿日期:2019-11-24; 修回日期:2020-01-28 基金项目:福建省自然科学基金资助项目(2019J01867)。 Project Supported by Fuijian Provincial Natural Science Foundation(2019J01867).王 刚(1990—),男,硕士研究生,研究方向为电器智能化技术及其应用。 彭彦卿(1966—),女,教授,硕士研究生导师,博士,研究方向为智能控制、复杂系统的建模与优化、电力电子与电力传动。 庄志坚(1986—),男,高级工程师,硕士,研究方向为智能中压断路器。 孙利杰(1994—),男,硕士研究生,研究方向为电器智能化技术及其应用。 熊逸伟(1991—),男,工程师,本科,研究方向为高电压设备健康诊断。
更新日期/Last Update: 2020-03-15