CAJ | 학술논문

频率切片小波变换（Frequency Slice Wavelet Transform，FSWT）是一种新的时频分析方法，信号中的噪声会降低FSWT分析的频率分辨率。为了提高分析精度，提出了基于形态滤波和时延自相关的时频切片分析方法，并成功应用到轴承故障诊断中。该方法首先采用多结构元素差值形态滤波和时延自相关方法对信号进行降噪，采用FSWT分解降噪后的轴承振动信号，然后根据轴承故障特征频率选择时间频率切片区间，进行细化分析来提取故障特征。仿真信号与轴承故障振动信号的分析验证了该方法的有效性。
빈솔절편소파변환（Frequency Slice Wavelet Transform，FSWT）시일충신적시빈분석방법，신호중적조성회강저FSWT분석적빈솔분변솔。위료제고분석정도，제출료기우형태려파화시연자상관적시빈절편분석방법，병성공응용도축승고장진단중。해방법수선채용다결구원소차치형태려파화시연자상관방법대신호진행강조，채용FSWT분해강조후적축승진동신호，연후근거축승고장특정빈솔선택시간빈솔절편구간，진행세화분석래제취고장특정。방진신호여축승고장진동신호적분석험증료해방법적유효성。
Frequency slice wavelet transformation (FSWT)is a new time-frequency analysis method,and the noise in a signal reduces frequency resolution of FSWT.In order to improve the analysis accuracy,a FSWT method based on morphological filtering and time-delayed autocorrelation was proposed and applied to diagnose bearing faults successfully. With this method,the multi-structure element difference morphological filtering method and the time-delayed autocorrelation method were used to reduce the noise of a bearing vibration signal,and the denoised signal was decomposed by applying FSWT,then time and frequency slice intervals were selected for the detailed analysis to extract fault characteristics according to the bearing fault characteristic frequencies.Simulation signal analysis and bearing fault vibration signals analysis demonstrated the effectiveness of the method.