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Amazon Echo Dot: The Ultimate User Guide to Amazon Echo Dot 2nd Generation for Beginners

為了解決bose soundlink mini 的問題，作者Howard, Andrew 這樣論述：

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麥克風陣列結合波束成型理論進行聲源定位及應用聲學攝影機於加工系統之振噪分析

為了解決bose soundlink mini 的問題，作者蘇紫茵 這樣論述：

就像人有兩個耳朵一樣，多個感測器組成陣列後可以進行聲源定位。此技術應用廣泛，從早期用於軍事科技，到現代智慧聲控裝置或輔助工業噪音檢測，皆能見到其蹤影，亦是一項發展已久的技術，研究者也努力從陣列排列方式或演算法優化追求提升定位精準度及運算速度。本研究首先將聲音感測器以直線的方式排列建立一維等間距線性陣列系統，並使用波束成型演算法進行聲源定位，進而建構完整的自動聲源追蹤系統；接著為了追蹤空間中的聲源位置，以一維陣列系統為基礎建立二維的聲源定位陣列，利用不同的排列形式設計各種陣列幾何的配置，並探討對應的聲源辨識能力與解析度，進而找出最佳的陣列排序方式；接著將二維陣列系統與工業相機結合，建立出可視化

的聲場量測系統，並設計靜止、二維移動和三維空間移動的聲源實驗，測試此系統的靈敏度與定位能力；最後將本系統與三維數位影像相關法（digital image correlation，DIC）結合可精準定位聲源的三維空間位置，並將分析結果與市售的聲學攝影機相互比對以驗證本系統之可行性。另一部份則是將聲源定位應用於振噪分析的實例研究，與傳統量測工具相互搭配，針對內藏式主軸、馬達加工系統與機械手臂三種不同加工系統進行量測，將運轉訊號分離出環境背景噪音、電子元件噪音與運轉機械噪音並分項討論，也從異常訊號特徵推論結構有零件鬆動、基座不穩等問題，並成功使用聲學攝影機找到發出異音的缺陷軸承；最後則將聲學攝影機拍

攝結果相互比較，討論聲源定位技術於實例應用的可行性。