Blade tip timing (BTT) technique has become a promising way of online damage diagnosis for compressor and turbine blades by monitoring their vibrations. However, there are some disadvantages in previous algorithms for BTT signals, including not high precision, strict sensor layout, signal bandwidth limit, and weak anti-noise ability. To solve these problems, a novel interpolation method for wideband signal reconstruction (IWSR) is presented. Simulations are conducted using a lumped parameter model, which shows that IWSR reconstructs noiseless signals with overall errors mainly below 1%, and identifies the exact frequencies of 5 dB noise signals. In addition, the results validate its signal separation function and verify that its sensor layout is almost arbitrary, and its maximum allowable bandwidth is half the product of sensor number and rotational frequency. Experimental results demonstrate its effectiveness in frequency identification. In conclusion, IWSR provides precise information for real-time blade damage diagnosis, which benefits turbomachinery safety.

叶片尖端正时（BTT）技术已经成为通过监视压缩机和涡轮机叶片的振动进行在线损伤诊断的有前途的方法。但是，以前的BTT信号算法存在一些缺点，包括精度不高，传感器布局严格，信号带宽限制和抗噪能力差。为了解决这些问题，提出了一种新颖的宽带信号重建插值方法。使用集总参数模型进行仿真，该模型表明IWSR重构的无噪声信号的总体误差主要在1％以下，并确定5 dB噪声信号的确切频率。此外，结果验证了其信号分离功能，并验证了其传感器布局几乎是任意的，其最大允许带宽是传感器数量和旋转频率的乘积的一半。实验结果证明了其在频率识别中的有效性。总之，IWSR为实时叶片损坏诊断提供了精确的信息，这有利于涡轮机械的安全性。