基于正弦结构元素的自适应Top-Hat变换及发电机特征振动信号增强检测

Self-Adapted Top-Hat Transformation Based on Sine-Structure Element and Its Application in Enhanced Characteristic Vibration Signal Detection of Generator

提出了一种基于正弦结构元素的自适应改进Top-Hat变换方法,并将其应用至发电机定子特征振动信号的增强检测中。该方法通过嵌套遍历循环确定使特征振动信号频率成分能量占比最大的最优结构元素幅值和长度,结合自互补Top-Hat变换来实现对发电机特征振动信号的增强检测。动模实验机组MJF-30-6定子匝间短路的实测信号处理结果表明,该文所提方法能够同时提取和增强定子的2倍频、4倍频和6倍频这3个特征振动信号,给故障的识别和诊断提供了方便,具备参考价值和积极意义。

An improved self-adapted Top-Hat transformation method based on sine-structure element was proposed to enhance the characteristic vibration signal detection of generator. This method firstly obtained the optimal amplitude and length of the structure element, so that the energy proportion of the characteristic components can be maximal. Then the optimal structure element was used to carry out the self-complementary Top-Hat transformation for the enhanced characteristic vibration signal detection of generator. Verifications taken on the stator vibration signal of the MJF-30-6 type fault simulating generator with a stator interturn short circuit fault indicate that, the proposed method is qualified to extract and enhance all of the three characteristic stator vibration components respectively at 2f, 4f, and 6f （f is the electrical frequency）. This method is probably to offer more convenience for the fault diagnosis of generator and therefore has reference value and active meaning.