基于任意传感器排布的叶尖定时信号压缩感知辨识方法

基于叶片振动和叶尖计时系统的特点,推导了任意传感器角度分布下叶片振动响应的分布规律,并基于叶尖定时信号频域的稀疏性,探究了压缩感知方法在叶尖定时信号的重构和倍频辨识上的应用。通过同步信号和非同步信号的大量数值实验,分析了包括信号重构误差、传感器数量、旋转周期数、频率分辨率和信噪比等因素对辨识效果的影响,提出了压缩感知重构叶尖定时信号的基本方法和步骤。进一步将压缩感知方法应用于某型号涡扇发动机钛合金宽弦风扇叶片有限元仿真获得的振动响应数据重构,验证了该方法的有效性。结果表明:在加入了叶尖测点位置误差和30 dB随机噪声的前提下,在80%、90%和100%三种转速工况下均清晰辨识出幅值较大的激励倍频。基于任意传感器角度分布的压缩感知方法对叶尖定时信号辨识效果较好。

Compressive sensing identification method of blade tip timing signals based on arbitrary sensor arrangement

Based on the characteristics of blade vibration and tip timing system, the regulation of blade vibration response under arbitrary sensor angle distribution was studied. Based on the sparsity in frequency domain of tip timing signal, the application of compressive sensing method in reconstruction of blade tip timing signal and mode identification was explored. Through a large number of numerical experiments of synchronous and non-synchronous signals, the influences of signal reconstruction errors, number of sensors, number of sampling cycles, frequency resolution and signal to noise ratio on the identification effect were analyzed, and the basic methods and steps of the compressive sensing method to reconstruct the timing signal of blade tip were determined. Finally, the method was applied to the reconstruction of vibration response data of a titanium alloy wide chord fan blade from the finite element simulation. The results show that the excitations with large amplitudes can be accurately identified under three rotating speed conditions of 80%, 90% and 100% with blade tip position error and 30 dB noise signals. The compressive sensing method based on arbitrary sensor angle distribution is effective in identifying the timing signal of blade tip and has value of engineering application and promotion.