傳統的機械故障診斷，皆是利用麥克風量測聲音，再利用傅立葉進行頻譜分析，這種處理方法非常簡單且有效率，但是由於去除了時間資訊，所以某些訊號特徵並不能完全展現。
以下是車床主軸聲音檔，利用 Enhanced Morlet Transform 進行時頻分析之後，可以發現在 9000 Hz 附近有一個特徵頻率，估計是與軸承轉子數量成倍數關係。
利用傳統傅立葉頻譜圖如下：
若是放大時頻圖：
可以發現 9000 Hz 這個特徵頻率並不是單一一條直線，而是會上下震盪，且在上下緣有細微頻率線，而每條頻率線之間的間隔剛好為轉速。而線的顏色深淺不一，代表強度忽強忽弱，這是 Beat Wave 的關係。
由此可知，時頻分析應用於噪音分析，可以比傳統的傅立葉頻譜擷取出更多資訊。
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陳慶淳 responded on 24 七月 2008 at 10:05 pm #
如果噪音這噪音有轉速的話(間隔),雖然忽強忽弱,但如果將頻率整理(將他整理為有正常頻率的聲波),並將他用於發電的話會不會發會很大的效用??我主要問的是,躁音整頻能用於發電媽??雖然電力很小,但我想做做看這哥數據….,如果知道的話記得回一封E-mail給我憂!!
我是熱愛科學ㄉ高一生~~ 這研究用於科展!!
陳慶淳 responded on 24 七月 2008 at 10:07 pm #
信箱是st86480000@yahoo.com.tw
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