近年來由於高科技工業之密集發展，對於供電品質要求日益提昇，然卻由於非線性負載之急遽增加，致使電力公司供電品質大受影響，因此如何辨識異常電力擾動訊號，以維持穩定供電品質，已躍為電力研究中之重要工作。基於此，本論文研擬嵌入近似熵演算法於訊號偵測，同時應用現場可規劃邏輯閘陣列完成整體電力品質擾動之偵測，而由於近似熵估測技術具有判斷資料相似度之特點，因此本文期能因而提升擾動訊號之檢測能力，同時藉由硬體描述語言將其實現於FPGA晶片，可大幅提昇擾動訊號之檢測能力。同時為求驗證本文所提方法之實用價值，並進行實體電路之研製，並將所實作之電路經由電壓擾動模擬訊號，予以審慎驗證，所得之測試結果，應可協助佐證本文所應用之方法於訊號檢測之可行性及實用參考價值。

Following the fast development of high-tech industry, electric power quality has emerged as a very important concern. Yet, because of the increasing utilization of non-linear loads, the level of power quality is significantly affected. It is, therefore, crucial to devote to electric power quality studies nowadays. This paper was hence aimed at the embedment of the approximate entropy method in the signal detection algorithm. Moreover, the hardware realization of field-programmable gate array (FPGA) of this paper was also completed in anticipation of further improving the detection capability of power system disturbances. This method was motivated due to the signal-regularity justification capability exhibited by the approximate entropy such that when the algorithm was realized by the FPGA, the overall detection performance can be highly improved. To validate the effectiveness of this approach, the proposed method was tested through several scenarios of disturbances. Test results help confirm the feasibility and practical value of the method applied.

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