Dielectric loss angle is one of the effective means of estimating the insulation performance of high voltage electrical equipment. Accurate extraction of harmonic voltage and current signals is the key to the detection of dielectric loss angle. Based on improved ITD algorithm and the Least Square (LS) method, in this paper we proposed a detection method for dielectric loss angle. Above all, extract the harmonic voltage and current signals by using improved ITD. Then obtain the phase of harmonic voltage and current by using the LS method to achieve high-precision detection of dielectric loss angle. The improved ITD-LS method is validated by simulation. When the true value of dielectric loss angle, frequency fluctuations of fundamental voltage, and the three harmonic ratio change, the DC component proportion, sampling points change, respectively. Finally, the simulation results demonstrate the feasibility and effectiveness of the proposed method.

This paper proposed a normalized, automatically adaptive stochastic resonance Sub-Synchronous Resonance (SSR) detection method. In reality, the purpose is to detect the SSR early signals quickly and accurately. Based on stochastic resonance theory, the paper is for the signal's greater frequency and small amplitude characteristics. The steps of the method are (a) make the stochastic resonance equation do normalization transformation; (b) realize the large parameter signal detection; (c) adjust the parameter automatically adaptively; (d) get the optimal value of the output signal-to-noise ratio. The simulation results show that this method is easy to implement and has good antinoise and a wide range of advantageous detection frequency.

A new method was proposed based on permutation entropy toward detection to the instantaneous voltage disturbances signal. At first, it used the CEEMD to decompose the signals to get the Intrinsic Mode Function (IMF) components, and then figured out the permutation entropy of each IMF component to test the randomness to estimate whether the IMF component is an abnormal signal. Afterwards, refactoring the normal IMF components to get the de-noised signals of the instantaneous voltage disturbances, it can be preferable to persist the disturbance characteristics of the disturbance signal; permutation entropy curve can get mutations of power quality at the beginning and ending of the perturbation moment. The results of simulation show that the method has advantages such as antinoise ability, small waveform distortion, and exact extraction of disturbance characteristics; it can be applied in de-noising and location of the instantaneous voltage disturbances.

This paper puts forward a new method based on Ensemble Empirical Mode Decomposition (EEMD) and Kernel Independent Component Analysis (KICA) for de-noising to extract the Partial Discharge (PD) signals against narrow-band noise. At first, this method used EEMD to decompose the detection signal to get Intrinsic Mode Function (IMF) components which would be the inputs of KICA algorithm, then KICA could extract PD from the detection signal. The method is introduced to separate the PD signals against the narrow-band interferences of multifrequency and multiamplitude. The method can alleviate the mixing mode phenomenon in detection of PD and have a better detection result. It also has advantages such as the antinoise ability and small waveform distortion. The proceeding result of simulation model and signal from field test pro---+ves its effectiveness.

Jane harmonic detection technology is an important content of power system harmonic governance, the paper proposes an improved ITD method combined with singular value difference spectrum of fast high precision detection. By improving the ITD method it can directly according to measured data with feature information contain system parameter identification. First, using singular value different spectrum system order, and then using ITD improved directly on the noise signal accurately detect the actual frequency of each harmonic, using the Least square method (further Squares, LS) on the amplitude of harmonic component between accurate detection. Improve ITD method with SSI method of covariance matrix (Toeplitz) as the input data, and overcoming the data processing method is not accurate, the error of the parameter identification precision is improved. Compared with the method of SSI, improved ITD method accuracy does not decrease, at the same time shortens the calculation time. Simulation results show that the method calculating speed, high precision, strong ability to resist noise, verify the feasibility and effectiveness of the proposed method.

There exists a variety of oscillation modes in the Sub-Synchronous Resonance (SSR). The trend of its development cannot be judged by the existing detection methods. This paper presents a stability diagram and the matrix based beam SSR new method for vibration modal identification. This method does not need to explicitly use SSR, and the mechanism of directly using the test data is identified. First, it is established by the method of stable figure order number in the system. Then use the matrix of precise frequency method detection system. According to the characteristics of the sub-synchronous oscillation frequency, modal identification, analysis of sub-synchronous oscillation frequency, amplitude and attenuation factor, simulation experiments show that the method has high precision, strong noise resistance, accurate predictions of SSR development tendency, and verify the effectiveness of the method feasibility.