基于Fractal理论的钻机电控系统随机噪声隔离方法OA

In addressing the issue of the electrical drive system of oil drilling rigs encountering instability in actuator output due to interference from multi-source random noise,a novel approach was proposed.The Fractal theory was utilized to isolate random noise in the drilling rig electrical control system.The presence of composite noise pollution in the frequency,voltage,pulse,and other signals of the frequency converter,attributable to factors such as thyristor and compensation capacitor casting,power supply impedance,and other multi-source random noise,necessitates the employment of fractal theory's nonlinear feature analysis capability.This capability enables the elimination of redundant information present in Gaussian noise,thereby enhancing the signal's low signal-to-noise ratio and improving the recognition rate.Concurrently,in conjunction with Welch analysis of the power spectral density,the fractal dimension parameter was extracted from the local features of the signal to respond to the global trend,thereby achieving effective noise reduction of the signal.Experimental findings demonstrate the efficacy of this method in accurately calculating the fractal dimension of the signal and reducing noise isolation error.