CAJ | 학술논문

准确提取振动信号的特征，是滚动轴承故障检测的关键问题，为此提出一种基于S能量谱特征提取的故障诊断方法。该方法对振动信号进行S变换，得到时频矩阵，并构建S能量谱，对S能量谱进行奇异值分解（Singular Value Decomposition，SVD）分析，得到能够反映S能量谱特征的奇异值，利用变量预测模型（Variable Predictive Model based Class Discriminate，VPMCD）方法，通过建立特征值之间的内在关系，构建故障识别模型。将所提方法应用于滚动轴承故障检测，实验结果表明，S能量谱特征提取轴承故障诊断方法具有较高的正判率。
준학제취진동신호적특정，시곤동축승고장검측적관건문제，위차제출일충기우S능량보특정제취적고장진단방법。해방법대진동신호진행S변환，득도시빈구진，병구건S능량보，대S능량보진행기이치분해（Singular Value Decomposition，SVD）분석，득도능구반영S능량보특정적기이치，이용변량예측모형（Variable Predictive Model based Class Discriminate，VPMCD）방법，통과건립특정치지간적내재관계，구건고장식별모형。장소제방법응용우곤동축승고장검측，실험결과표명，S능량보특정제취축승고장진단방법구유교고적정판솔。
To accurately extract the features of vibration signal is essential in detecting rolling bearing fault. Therefore, a method named feature extraction based on S energy spectrum is brought up in this paper. By performing S transform on the vibration signals, time-frequency matrix is obtained and S energy spectrum is constructed. S energy spectrum is decom-posed into singular values that can reflect the energy distribution and analyses with the help of Singular Value Decomposi-tion(SVD). Through utilizing the Variable Predictive Model based Class Discriminate(VPMCD)and comparing the interrelation among singular value vectors of S energy spectrum, the fault identification model is constructed. The experi-mental results prove that the proposed method applied to the bearing fault diagnosis acquires a better correction rate.