Detection method for low-frequency non-stationary signals

Abstract

The invention relates to a detection method for low-frequency non-stationary signals. The detection method comprises the following steps: S100, determining a center frequency; S200, determining the bandwidth of a main lobe; S300, determining a sidelobe bandwidth; S400, adjusting a phase shift coefficient; S500, transferring a function; S600, determining amplitude/phase frequency characteristics; S700, if the phase requirement is met, entering the step S800, otherwise, returning to the step S400; and S800, ending. The method has the beneficial effects that the problems that inter-harmonics in a target frequency band are difficult to extract and interference is difficult to eliminate can be effectively solved, the 75-125Hz low-frequency inter-harmonics are well extracted through simulation and experimental verification of the detection algorithm, the extraction precision can exceed 50%, the extraction precision of second harmonics is up to more than 90%, the interference signal can be attenuated to below 1% (the amplitude can be suppressed to be close to 0), and the correctness and effectiveness of the detection algorithm are fully verified.

Description

technical field [0001] The invention relates to a detection method for low-frequency non-stationary signals. Background technique [0002] In recent years, with the widespread application of nonlinear power electronic equipment, the harmonic content in the power grid has increased sharply, which brings convenience but also causes serious pollution to the power system, threatening the safety of the power grid and electrical equipment. Aiming at the harmonic problems in high-power impact loads in the industry, experts and scholars at home and abroad have been looking for effective solutions. After a long period of extensive research, the filtering effect of single-frequency harmonics has achieved remarkable results. However, there are few studies on the low-frequency interharmonics (mainly the second harmonic and interharmonics) near the fundamental wave, and there are few effective methods to solve the low-frequency harmonics of continuous spectrum in the existing research. ...

AI Technical Summary

Problems solved by technology

As the main detection method used by the active power filter (APF) in the industry, the instantaneous reactive power theory is to extract the fundamental wave signal quickly and effectively, and then subtract it from the power grid signal to obtain the compensation signal, because it is sensitive to fixed frequency signals. The extraction effect is remarkable and is widely used, but it cannot effectively detect low-frequency interharmonics

Although the PR detection algorithm can effectively extract single-frequency interference signals, it cannot meet the requirements of rapid real-time detection for multiple groups of interharmonic signals of different frequencies.

The harmonic detection method based on ANN can effectively extract the harmonics between the continuum, but the reasonable value of the learning rate in the design process has always been difficult to break through. If the value is too large, it will affect the dynamic performance and stability of the system. Small and will affect the detection accuracy due to insufficient learning

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