As the electrical entity boundary installed at both ends of the high voltage direct current(HVDC)transmission line has the ability to block high-frequency components

the start voltage caused by the external fault changes gently and amplitude is small; the start voltage caused by the line fault changes steeply when amplitude is large and the time-domain waveform is shown shaking violently. Principal component analysis(PCA)is used to extract time domain features of pole fault voltage and project the time domain features on to PCA space and form cluster point clusterings of external fault and line fault constituting cPC1 and cPC2 coordinates. Hence the characterization and distinction of external fault and internal line fault. After fault

the Euclidean distance between the projection values of fault data mapped to PCA space and the cluster centers of PCA identification element is used to distinguish internal and external faults adaptively. The large number of measured data tests show that this method has the ability to interfere without lightning disturbance

samples dithering

harmonic interference and other factors

while improving the protection performance of traveling wave protection with du/dt as the core. And if the historical fault data is reusable to increase PCA cluster point clusterings

PCA fault identification element can continue to improve. This work is supported by National Natural Science Foundation of China(No. 51267009)and National Natural Science Foundation of China-Yunnan(No. U1202233).