Abstract: The traditional fixed frequency range detection method is difficult to effectively capture fault characteristics due to redundant frequency band division, which weakens the sensitivity, speed, and positioning accuracy of detection. In response to the above issues, this study proposes an intelligent detection method for interturn short circuit faults in synchronous generator rotor windings based on wavelet packet entropy.Firstly, wavelet packet decomposition technology is used to decompose the interturn short circuit signal into different frequency bands,and morphological filtering is used to effectively reduce noise and improve signal quality. Then, the entropy theory is introduced to calculate the sample entropy, multiscale entropy, and wavelet packet energy spectrum relative entropy of each frequency band signal, screen out the frequency bands with significant entropy changes, effectively eliminate redundant frequency bands, accurately extract fault features, and significantly enhance the sensitivity of detection. Combining convolutional neural networks to classify extracted features and achieve intelligent fault detection.Experimental verification shows that compared to traditional methods, this method exhibits significant advantages in improving fault detection sensitivity, accelerating detection processes, and ensuring accurate fault localization. It provides an efficient and reliable solution for synchronous generator rotor winding fault diagnosis, effectively overcoming the limitations of traditional methods.
Key words: wavelet packet decomposition; entropy calculation; synchronous generator; interturn short circuit; fault detection
參考文獻(xiàn)
[1] 黃楊森. 基于 MSET 的汽輪發(fā)電機(jī)轉(zhuǎn)子繞組匝間短路故障診斷[J]. 發(fā)電設(shè)備，2024，38(3) ：182-188.
[2] 孫浩， 劉馳程， 傅裕， 等. 基于行波理論的檢測(cè)技術(shù)在轉(zhuǎn)子繞組故障診斷中的應(yīng)用[J] . 電工技術(shù)，2022(9) ：43-45.
[3] 譚尚仁，楊增杰，高境，等. 重復(fù)脈沖法在凸極轉(zhuǎn)子繞組匝間短路檢測(cè)中的應(yīng)用探索[J] . 水力發(fā)電，2024，50(6) ：72-78.
[4] 付強(qiáng). 基于 XALO-SVM 的同步電機(jī)轉(zhuǎn)子繞組匝間短路故障診斷方法[J] . 黑龍江科技大學(xué)學(xué)報(bào)，2024，34(1) ：125-131.
[5] 徐俊元，胡磊，王曉劍，等. 基于 PCC-SVM 的發(fā)電機(jī)轉(zhuǎn)子匝間短路在線監(jiān)測(cè)法[J]. 大電機(jī)技術(shù)，2023(6)：35-41.
[6] 馮宇哲，李衛(wèi)軍，楊立川.660 MW 發(fā)電機(jī)轉(zhuǎn)子繞組匝間短路故障檢測(cè)與處理[J]. 電工電氣，2023(7) ：46-50.
[7] 潘劍南，李浩良. 一起基于重復(fù)脈沖法的發(fā)電機(jī)轉(zhuǎn)子繞組匝間短路故障分析[J] . 黑龍江電力，2022，44(5) ：402-406.
[8] 王云峰，冀順林. 一起發(fā)電機(jī)轉(zhuǎn)子繞組動(dòng)態(tài)匝間短路故障的診斷與分析[J]. 電工技術(shù)，2021(17) ：170-172.
[9] 鄧方雄，楊東，劉敏，等. 大型水輪發(fā)電機(jī)轉(zhuǎn)子匝間短路在線監(jiān)測(cè)研究[J] . 設(shè)備管理與維修，2021(11) ：27-28.
[10] 李俊卿，李斯璇，陳雅婷，等. 一種基于 CGAN-CNN 的同步電機(jī)轉(zhuǎn)子繞組匝間短路故障診斷方法[J]. 電力自動(dòng)化設(shè)備，2021，41(8) ：169-174.
