Aiming at the problem that human breathing and heartbeat signals are difficult to detect in a low signal-to-clutter environment,this paper proposes a signal processing method that combines differential evolution algor...
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Aiming at the problem that human breathing and heartbeat signals are difficult to detect in a low signal-to-clutter environment,this paper proposes a signal processing method that combines differential evolution algorithm and variationalmodaldecomposition *** order to achieve non-contact detection of vital signs,this paper uses ultra-wideband radar to collect the signal reflected by the human body,and suppresses the interference of the background signal by removing the background of the signal,and then extracts the signal reflected by the human chest in the fast time *** that,according to the frequency range of breathing and heartbeat signals,low-pass filter and band-pass filter are used to filter useless *** at the problem that the variational modal decomposition algorithm needs to manually adjust parameters in advance,this paper takes the maximum effective frequency band energy ratio as the objective function,and uses differential evolution algorithm to automatically search for the best parameter combination of variationalmodaldecomposition,which reduces the workload of parameter ***,variationalmodaldecomposition by the best parameter combination is used again to decompose the signal,and the breathing and heartbeat signals are reconstructed from the decomposed modal *** show that the method proposed in this paper can measure the human body's respiratory rate and heartbeat rate with high accuracy.
This paper is concerned with the development of improved multi-strategy MPA-VMD method and its application in pipeline leakage detection. Aiming at the shortcomings of the marine predator algorithm (MPA) itself, which...
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This paper is concerned with the development of improved multi-strategy MPA-VMD method and its application in pipeline leakage detection. Aiming at the shortcomings of the marine predator algorithm (MPA) itself, which has a slow convergence speed and is easy to fall into local optimum, an improved MPA is proposed and used to find two important parameters in variational mode decomposition (VMD), and then dynamic entropy is used to select effective modes. In the initial stage of the population, a good point set strategy is adopted to enhance the search accuracy by increasing the diversity of the initial population;in the search process, a nonlinear convergence factor and the Cauchy distribution are introduced to optimize the predator step size to enhance the global search ability of the algorithm. The ability of the algorithm is enhanced to jump out of the local optimum, and the convergence speed of the algorithm is further improved;the effective mode after VMD is selected by the method of symbolic dynamic entropy. The experimental results show that compared with MPA-VMD, grey wolf optimization-VMD and particle swarm optimization-VMD methods, the devised method has improved signal-to-noise ratio, reduced mean square error and mean absolute error, and has better denoising effect.
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