Substation Noise Separation Method
A technology of noise separation and substation, applied in the direction of electrical digital data processing, measurement of ultrasonic/sonic/infrasonic, special data processing applications, etc., can solve the problem that there are no separate measurement of three kinds of noise
Active Publication Date: 2017-06-30
SHANGHAI ADVANCED RES INST CHINESE ACADEMY OF SCI
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The three kinds of noise have different noise sources and exist in the substation at the same time. At present, there is no method to measure the three kinds of noise separately
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[0051] The embodiments of the present invention will be described in further detail below in conjunction with the accompanying drawings, but the present embodiments are not intended to limit the present invention, and any similar structures and similar changes of the present invention should be included in the protection scope of the present invention.
[0052] Such as figure 1 As shown, a substation noise separation method provided by the embodiment of the present invention is characterized in that the specific steps are as follows:
[0053] 1) Use a microphone to pick up the noise of the high-voltage substation at a sampling rate of 65536 Hz. The noise of the high-voltage substation includes corona noise, body noise, and fan noise. The signal model is:
[0054] s(n)=c(n)+b(n)+e(n)
[0055]
[0056] w 0 =2πf 0 / f s
[0057] Among them, s(n) is high-voltage substation noise, c(n) is corona noise, b(n) is body noise, e(n) is fan noise, w 0 is the frequency in the digit...
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The invention provides a transformer substation noise separation method and relates to the technical field of audio processing. The technical purpose that three types of noise of a high-voltage transformer substation is independently measured is achieved. The method includes the steps that firstly, multilayer wavelet transformation is conducted on noise of the high-voltage transformer substation, so that six groups of wavelet coefficients are acquired; then, after the low-frequency wavelet coefficients pass a passband comb filter, wavelet inverse transformation is conducted, and therefore body noise is separated; meanwhile, after the low-frequency wavelet coefficients pass a stop band comb filter, wavelet inverse transformation is conducted on the low-frequency wavelet coefficients and other five groups of wavelet coefficients, and mixed signals containing corona noise and fan noise are acquired; then the corona noise is detected through the high-frequency wavelet coefficients, a fan noise power spectrum is estimated in a period without the corona noise, a corona noise power spectrum is estimated in a period with the corona noise, time domain signals are reconstructed through the estimated fan noise power spectrum and the estimated corona noise power spectrum, and therefore the fan noise and the corona noise are separated. The method is suitable for processing noise signals of large high-voltage alternating current and direct current transformer substations.
Description
technical field [0001] The invention relates to audio processing technology, in particular to a technology of a substation noise separation method. Background technique [0002] In the power transmission system, under the same rated power condition, the higher the transmission voltage, the smaller the corresponding transmission current, so the energy loss of the line is smaller. Therefore, high-voltage and ultra-high-voltage transmission lines are the key development direction of power construction at present and in the future. In a high-voltage power transmission system, an ultra-high electric field will be generated near the wire to cause ionization of the nearby air, and discharge will occur, and the air discharge will produce a "squeak" sound, forming corona noise. At the same time, due to the periodic change of the voltage, the charged particles near the wire move periodically under the action of the electric field, and the motion cycle is the same as the AC cycle. In ...
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IPC IPC(8): G06F19/00G01H17/00
Inventor 彭任华郑成诗杨鹤飞李晓东
Owner SHANGHAI ADVANCED RES INST CHINESE ACADEMY OF SCI