南方电网技术2025，Vol.19Issue(1)：30-40,11.DOI:10.13648/j.cnki.issn1674-0629.2025.01.004
基于改进MFCC-OCSVM和贝叶斯优化BiGRU的GIS异常工况声纹识别算法
Voiceprint Recognition Algorithm for GIS Anomalous Conditions Based on Improved MFCC-OCSVM and Bayesian Optimized BiGRU
摘要
Abstract
To accurately identify abnormal conditions in gas insulated switchgear(GIS)equipment,a voiceprint recognition algorithm is proposed based on weighted Mel frequency cestrum coefficient-one class support vector machine(MFCC-OCSVM)and Bayesian optimized bidirectional gate recurrent unit(BiGRU).Firstly,weighted extractions of voiceprint data are performed using MFCC based on the F-statistic,highlighting important features and reducing the influence of noise.Subsequently,OCSVM is utilized to detect anomalies and remove anomalous values from the weighted features to improve data quality.To address the issue of sample imbalance,synthetic minority over-sampling technique(SMOTE)is employed to balance voiceprint samples.Finally,voiceprint recognition is carried out using a BiGRU model based on Bayesian optimization.Taking a certain GIS equipment as an example,sound samples from 20 different operating conditions are collected and compared with various classical classification models.The results demonstrate that the proposed algorithm achieves the highest average recognition accuracy of 92.8%,resulting in improve-ments of 30.1%,14.7%and 11.5%compared to adaptive boosting,Naïve Bayes,and linear discriminate analysis,respectively.Ablation study further assesses and validates the practical effects and performance impacts of each process in the proposed algorithm.Research results provide an efficient technical approach for voiceprint recognition of anomalous conditions in GIS.关键词
GIS设备/梅尔频谱倒谱系数/单类支持向量机/双向门控循环单元/声纹识别/贝叶斯优化Key words
gas insulated switchgear(GIS)equipment/Mel frequency cestrum coefficient(MFCC)/one-class support vector machine(OCSVM)/bidirectional gate recurrent unit(BiGRU)/voiceprint recognition/Bayesian optimization分类
信息技术与安全科学引用本文复制引用
庄小亮,李乾坤,刘紫罡,张禄亮,季天瑶,张长虹..基于改进MFCC-OCSVM和贝叶斯优化BiGRU的GIS异常工况声纹识别算法[J].南方电网技术,2025,19(1):30-40,11.基金项目
国家自然科学基金资助项目(52077081) （52077081）
中国南方电网有限责任公司科技项目(CGYKJXM20220069).Supported by the National Science Foundation of China(52077081) （CGYKJXM20220069）
the Science and Technology Project of China Southern Power Grid Co.,Ltd.(CGYKJXM20220069). （CGYKJXM20220069）
