基于声速频散谱弛豫特征的油中溶解气体检测方法

针对传统气体检测方法难以满足电力运营部门大范围低成本实时监控油浸式电力设备问题，提出一种利用3个频率点声速测量值获取声速频散谱弛豫特征进行气体监测方法。首先，通过推导有效压缩系数与声弛豫过程理论公式，简化声速频散谱表达式。其次，根据不同频率点声速测量值重建声速频散谱，抽取油浸式电力设备故障气体声速频散谱弛豫声速和弛豫频率。最终，利用弛豫特征定性定量检测气体成分。仿真结果显示重建声速频散谱与实验数据相符，完成了CH₄、CO₂等多种气体检测，为实时在线监测电力设备油中溶解气体成分提供一种低成本、测量简单的声学方法。

Detecting dissolved gas mixtures in electrical equipment oil based on relaxation features of sound speed dispersion

The traditional gas detection method cannot meet the requirements of power department monitoring of oil-immersed electrical equipment at low cost and over a large range. Thus this paper presents a monitoring gas method. It uses the measured sound speed at three frequency points to get sound speed dispersion relaxation characteristics. First, the sound speed dispersion expression is simplified by deducing the theoretical formula of effective compressibility and the acoustic relaxation process. From the measured sound speeds at different frequency points, the sound speed dispersion is reconstructed, and the sound speed dispersion relaxation speed and frequency of the fault gas of oil-immersed electrical equipment are extracted. Finally, the gas composition is identified qualitatively and quantitatively using relaxation characteristics. Simulation results show that the reconstructed sound speed dispersion is consistent with the experimental results, and gas mixtures including CH4 and CO2 are identified. It provides a low-cost acoustic method with simple equipment for online detection of dissolved gas composition from oil-immersed electrical equipment. This work is supported by the National Natural Science Foundation of China (No. 62071189 and No. 62271451).