履带车辆制动器扭振信号瞬时频率特征提取方法研究

履带车辆的制动性能是评判其机动性优劣程度的重要指标之一，发动机引起的扭振在一定程度上会造成制动器制动效果降低，甚至失效。扭振信号常淹没于噪声信号中，因此在分析过程中很难判断所分析的信号是否存在扭振特征。针对上述问题，提出参数优化变分模态分解(VMD)的扭振信号瞬时频率特征提取方法。通过采用粒子群优化算法，以能量熵为适应度函数优化VMD参数，得到最优组合。采用最优参数组合对扭振信号进行降噪和重构，对重构的扭振信号进行零点线性插值，计算两脉冲之间的间隔，得到扭振瞬时转速波动信号。对瞬时转速波动信号进行频谱分析，实现对扭振信号瞬时频率特征提取。惯性载荷扭振实验结果表明：在转子转速为600 r/min、扭振激励频率为50 Hz的条件下，对采样频率为20 480 Hz的位移信号做参数优化VMD能精确提取扭振瞬时频率特征，误差小于1%。

Extraction Method of Instantaneous Frequency Feature of Torsional Vibration Signals of Tracked Vehicle Brake

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 20480Hz) with a rotating speed of 600r/min and a torsional vibration frequency of 50Hz, the parameter-optimized VMD can accurately extract the instantaneous frequency features of torsional vibration, and the error is less than 1%.