本文致力於在低信噪比的雜訊環境下，僅使用一個感測器的情況下仍能獲得較好的電纜局部放電（Partial discharge，PD）定位效果的研究。因此，基於單端感測器且適用於低信噪比雜訊環境下PD定位的改進相位差法被使用。同時，為提高改進相位差法在低信噪比雜訊環境下的定位準確度，一種結合高階統計量（High-order statistics，HOS）標準與廣義交叉校驗（General cross-validation，GCV）閾值的新型快速濾波演算法被提出來處理PD到達脈衝信號。最後，為避免使用脈衝峰值檢測法檢測到純雜訊的峰值而引起定位誤判，制定了純雜訊信號與包含雜訊的PD信號的區分策略。經過一系列模擬實驗，可得到以下結論：
1. 脈衝峰值檢測法檢測到的PD到達脈衝波形初至時刻幾乎可等同於真實的PD到達脈衝波形初至時刻，因而其應用於改進相位差法的PD定位的結果非常準確。
2. 相比於HOS標準濾波演算法和GCV閾值濾波演算法，本文所提出的新型濾波演算法能夠有效消除雜訊，更好地還原PD信號到達脈衝波形。
3. 同樣使用新型濾波演算法進行濾波定位的條件下，改進相位差法能在-10dB和-15dB的低信噪比雜訊環境中，實現比時域反射（Time domain reflectometry，TDR）法更準確的PD定位。
4. 制定的區分策略使用一個區分閾值來判別純雜訊信號與包含雜訊的PD信號，其判別效果優異，這充分說明了區分策略的有效性。

This thesis aims to use only one sensor to achieve better PD location of power cables in the low signal-to-noise ratio (SNR) noise environment. Therefore, an improved phase difference (IPD) method based on one sensor is used, which is suitable for PD location in the low SNR noise environment. In order to enhance the accuracy of the IPD method in the noise environment, a new denoising algorithm combining high-order statistics (HOS) criterion and generalized cross-validation (GCV) thresholding is proposed to process PD signals. Finally, a discriminant strategy is developed to avoid misjudgment of PD location when peaks of pure noise signals are detected using pulse peak detection. Through simulation experiments, the following conclusions can be obtained:
1. The arrival time of the PD pulse detected by the pulse peak detection method is almost equal to the actual arrival time of the PD pulse, which makes the result of the PD location very accurate.
2. Comparing with the HOS criterion denoising algorithm and the GCV thresholding denoising algorithm, the proposed denoising algorithm in this paper can better reduce the interference of noise on PD signals, and helps the IPD method obtain higher location accuracy.
3. Based on the same use of the proposed denoising algorithm, the IPD method can achieve more accurate PD location than the TDR method in a noisy environment with SNR of -10dB and -15dB.
4. The discriminant strategy proposed in this paper perfectly separates the pure noise signal from the noisy PD signal, which fully proves the effectiveness of the discriminant strategy.

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