基于信息熵的时频参数优化及内燃机轴承磨损监测

时频分析是单分量调频信号的最优分析工具，但是对于多分量线性调频信号存在比较严重干扰项的影响。为了抑制时频分布交叉项干扰，同时保持一定的时频聚集性，采用时频信息熵优化的方法，对时频分布中的参数进行了优化，给出了参数选择范围，仿真试验表明，该方法提高了时频分布中分辨率。研究结果应用于内燃机轴承磨损状态监测中，提取了故障特征，揭示了内燃机状态变化。

Optimization of time-frequency parameter and its application to monitor bearing wear of internal combustion engine based on information entrop

Time-frequency distribution (TFD) is the best analysis tool for the single-component FM signals, however, it has cross-term interference in the analysis of multi-component LFM signals. For suppressing cross-term interference and keeping some time-frequency local characteristics, parameters of TFD were optimized based on the time-frequency information entropy, and values of some parameters were recommended. Simulation tests showed that the method improved the resolution of TFD. Research results were applied to monitor bearing wear of the internal combustion engine, and fault features were extracted and the state change of internal combustion engine was revealed.