一种提高开关设备绝缘气体SF6泄漏判定鲁棒性的方法OA
Method for Improving the Robustness of SF6 Leakage Detection in Switchgear Insulation Gas
SF6气体由于其良好的绝缘和灭弧性能,被广泛用于高压电器设备中.在设备长期工作过程中,SF6气体的泄漏在所难免,这可能影响设备的安全运行.目前,SF6气体密度继电器多采用软测量模型进行设计,通过测量气室内SF6气体的温度和压力,并借助特定模型求解得到SF6气体密度.然而,压力传感器在长期使用过程中难免因老化而产生参数漂移,导致测得气体压力误差过大,进而影响该类软测量方法准确性,出现误判或漏判的现象.文中在深入分析常用的贝蒂—布里奇曼模型的基础上,通过线性回归并引入斜率及回归指标,提出了一种鲁棒性更高的SF6气体泄漏判定方法,介绍了其原理及技术实现关键点,并设计仿真实验,验证了该方法的性能.结果表明,该方法相较于传统方法受传感器精度影响较小,对气体泄漏更加敏感.该方法为高性能SF6气体密度继电器的研制提供了一种新思路,具有极高的实际应用价值.
SF6 gas is widely used in high voltage apparatus due to its excellent insulation and arc extinguishing properties.During the long-term operation of the equipment,the leakage of SF6 gas is inevitable,which may affect the safe operation of the equipment.At present,SF6 gas density relays are mostly designed using a soft measurement model,the SF6 gas density is obtained by measuring the temperature and pressure of SF6 gas inside the gas compart-ment and also with help of specific model.However,the parameter drift of pressure sensor in long-term usage of the process is inevitable due to aging,resulting in excessive error of the the measured gas pressure and further affecting the accuracy of this type of soft measurement method as well as occurring the phenomenon of misjudgment or omis-sion.In this paper,based on the in-depth analysis of the commonly used Beattie-Bridgeman model,a more robust SF6 gas leakage state detection method is proposed by applying linear regression and the introduction of slope and regression indexes,its principle and key points of technical implementation are introduced,and the simulation ex-periments are designed to verify the performance of the method.The results show that the method is less affected by the accuracy of the sensor and more sensitive to gas leakage over the traditional method.The method provides a new idea for the development of high-performance SF6 gas density relay and has a high practical application value.
苏旭辉;王志川;方源;李旭旭;张琪;宋科;陈聪;金海勇
国网四川省电力公司阿坝供电公司,四川 阿坝 623299国网四川省电力公司,成都 610041国网四川省电力公司,成都 610041国网四川省电力公司,成都 610041国网四川省电力公司阿坝供电公司,四川 阿坝 623299国网四川省电力公司映秀湾水力发电总厂,四川汶川 624000上海乐研电气有限公司,上海 201802上海乐研电气有限公司,上海 201802
SF6气体高压电器设备设备绝缘泄漏判定鲁棒性
SF6 gashigh-voltage apparatusequipment insulationleakage detectionrobustness
《高压电器》 2026 (3)
29-38,10
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