基于时、频域自相似性的配电变压器环境噪声识别方法

配电变压器位于开放的嘈杂环境中,环境噪声对基于声音的设备运行状态在线监测具有突出影响.如何识别和剔除含噪声干扰的录音片段,是推进基于声音的配电变压器状态在线监测亟待解决的瓶颈问题.分析指出配电设备正常和异常的运行声音与各种环境噪声在时域和频域上的差异性特征,提出基于时、频域自相似性的配电设备录音数据中含环境噪声片段的识...

Environmental noise recognition method for distribution transformer based on time domain and frequency domain self-similarity

The distribution transformer is located in an open noisy environment, and environmental noise has a prominent impact on the online monitoring of sound-based equipment operating status. How to identify and eliminate recordings containing noise is a bottleneck problem to be solved urgently in the promotion of sound-based online monitoring of the status of distribution transformer. The analysis points out the difference between the normal and abnormal operating sound of power distribution equipment and various kinds of environmental noises in time and frequency domains. The method for identifying environmental noise fragments in the recording data of power distribution equipment based on self-similarity in time and frequency domains is proposed. After the minute-level recording data is divided into frames, the time domain and frequency domain characteristic indexes of each frame are extracted. Whether the recording fragments have self-similarity is judged by clustering, and the recording data containing environmental noise are identified and eliminated. The experimental results show that the proposed method can effectively identify and eliminate the recording segments containing environmental noise, thereby recording data with lower environmental noise content can be obtained, and providing strong support for the subsequent development of sound signal-based status monitoring of distribution transformer.