{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,25]],"date-time":"2026-06-25T11:31:29Z","timestamp":1782387089944,"version":"3.54.5"},"reference-count":28,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2023,3,20]],"date-time":"2023-03-20T00:00:00Z","timestamp":1679270400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Science and technology projects of State Grid Corporation of China","award":["SGZJDKO0ZTJS2200242"],"award-info":[{"award-number":["SGZJDKO0ZTJS2200242"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>A transformer\u2019s acoustic signal contains rich information. The acoustic signal can be divided into a transient acoustic signal and a steady-state acoustic signal under different operating conditions. In this paper, the vibration mechanism is analyzed, and the acoustic feature is mined based on the transformer end pad falling defect to realize defect identification. Firstly, a quality\u2013spring\u2013damping model is established to analyze the vibration modes and development patterns of the defect. Secondly, short-time Fourier transform is applied to the voiceprint signals, and the time\u2013frequency spectrum is compressed and perceived using Mel filter banks. Thirdly, the time-series spectrum entropy feature extraction algorithm is introduced into the stability calculation, and the algorithm is verified by comparing it with simulated experimental samples. Finally, stability calculations are performed on the voiceprint signal data collected from 162 transformers operating in the field, and the stability distribution is statistically analyzed. The time-series spectrum entropy stability warning threshold is given, and the application value of the threshold is demonstrated by comparing it with actual fault cases.<\/jats:p>","DOI":"10.3390\/s23063258","type":"journal-article","created":{"date-parts":[[2023,3,20]],"date-time":"2023-03-20T03:30:31Z","timestamp":1679283031000},"page":"3258","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Defect Identification Method for Transformer End Pad Falling Based on Acoustic Stability Feature Analysis"],"prefix":"10.3390","volume":"23","author":[{"given":"Shuai","family":"Han","sequence":"first","affiliation":[{"name":"China Electric Power Research Institute, Beijing 100192, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bowen","family":"Wang","sequence":"additional","affiliation":[{"name":"State Grid Zhejiang Electric Power Research Institute, Hangzhou 310014, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sizhuo","family":"Liao","sequence":"additional","affiliation":[{"name":"China Electric Power Research Institute, Beijing 100192, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fei","family":"Gao","sequence":"additional","affiliation":[{"name":"China Electric Power Research Institute, Beijing 100192, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mo","family":"Chen","sequence":"additional","affiliation":[{"name":"China Electric Power Research Institute, Beijing 100192, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,3,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"670","DOI":"10.1109\/TPWRD.2012.2185955","article-title":"Diagnosis of technical condition of power transformers based on the analysis of vibroacoustic signals measured in transient operating conditions","volume":"27","author":"Borucki","year":"2012","journal-title":"IEEE Trans. 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