履带车辆制动器扭振信号瞬时频率特征提取方法研究

The braking performance of tracked vehicles is one of the important indicators to evaluate their mobility. Torsional vibration caused by the engine can reduce and even fail the braking effect. Torsional vibration signals are often submerged in noise, and it is difficult to determine whether the signals feature torsional vibration. To solve these problems, a parameter-optimized variational mode decomposition (VMD) method is proposed to extract the instantaneous frequency features of the torsional vibration signals. By using the particle swarm optimization (PSO) algorithm, the energy entropy is used as the fitness function to optimize the VMD parameters, and the optimal combination is obtained. The reconstructed torsional vibration signals are interpolated by zero point linear interpolation, and the interval between the two pulses is calculated to obtain the instantaneous rotational speed fluctuation signal. Finally, the spectrum analysis of the instantaneous rotational speed fluctuation signal is done to extract the instantaneous frequency of the torsional vibration signal. The experimental results of an torsional vibration experiment show that processing the signal (sampling frequency is 20 480 Hz) with a rotating speed of 600 r / min and a torsional vibration frequency of 50 Hz, the parameter-optimized VMD can accurately extract the instantaneous frequency features of torsional vibration, and the error is less than 1% .