研究生: |
鄭永文 Yung-Wen, Cheng |
---|---|
論文名稱: |
應用語音技術於鬆動元件質量估測 Using Speech Technique for the Mass Estimation of Loose Parts |
指導教授: | 林強 |
口試委員: | |
學位類別: |
碩士 Master |
系所名稱: |
原子科學院 - 工程與系統科學系 Department of Engineering and System Science |
論文出版年: | 2007 |
畢業學年度: | 95 |
語文別: | 中文 |
論文頁數: | 62 |
中文關鍵詞: | 鬆動元件 、頻率比值 、梅爾倒頻譜係數 、線性識別分析法 |
外文關鍵詞: | loose parts, frequency ratio, Mel-scale frequency cepstral coefficients, linear discriminant analysis |
相關次數: | 點閱:2 下載:0 |
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核電廠的「鬆動元件監測系統」(Loose Parts Monitoring System)是監測核反應器或蒸汽產生器內的鬆動元件產生撞擊時,記錄其訊號並對工作人員發出警報,以防止危及核能電廠運轉的安全,因此系統最重要的功能便是估測鬆動元件的位置與質量。
本研究發展演算法來分辨撞擊訊號與非撞擊訊號及估測鬆動元件的質量,除使用包含頻譜特性的「頻率比值」作為質量估測的第一個特徵外,另外將語音辨識技術取得的「梅爾倒頻譜係數」,利用「線性識別分析法」的降維方式取得第二個特徵:「撞擊特徵」和「質量特徵」。利用頻率比值和撞擊特徵可將撞擊訊號和泵啟動訊號辨別分開;利用頻率比值和質量特徵可以將撞擊訊號質量大致區分成較輕(一磅以下)與較重(兩磅以上)兩類。
The Loose Parts Monitoring System is a system to monitor the loose parts in the reactor vessel and the steam generator of the nuclear power plant. When loose parts impact the container wall, the system will record the signal and turn on the alarm so that the operator can take actions to protect the nuclear power plant. Therefore, the most important capability of the system is to estimate the mass and location of loose parts.
This research developed the methodology which can estimate the mass of loose part and recognize the impact signal and non-impact signal. The first feature of mass estimation is frequency ratio (FR) which contains the characteristic of the spectrum. In addition, linear discriminant analysis(LDA)is adopted to extract the second feature:“impact feature” and “mass feature” from Mel-scale frequency cepstral coefficients(MFCC)which is the important feature used for speaker recognition. Utilizing both of frequency ratio and impact feature can distinguish between impact signal and RHR pump start-up signal. Utilizing both of frequency ratio and mass feature can separate the mass of impact signal into two parts:light mass (less than one pound)or heavy mass(more than two pounds).
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