Compressed Sensing-Based Order Analysis for Blade Tip Timing Signals Measured at Varying Rotational Speed

Suiyu Chen,Guoji Shen,Yongmin Yang,Haifeng Hu,Fengjiao Guan,Faming Yang,Fabio Rizzo

doi:10.1155/2020/8328345

Abstract

Monitoring the vibrations of high-speed rotating blades is significant to the security of turbomachineries. Blade tip timing (BTT) is considered as a promising technique for detecting blade vibrations without contact online. However, extracting blade vibration characteristics accurately from undersampled BTT signals measured at varying rotational speed (VRS) has become a big challenge. The existing two methods for this issue are restricted within the order bandwidth limitation and require prior information and precise sensor installation angles, which is often unpractical. To overcome these difficulties, a compressed sensing-based order analysis (CSOA) method was proposed. Its feasibility comes from the sparsity of BTT vibration signals in the order domain. The mathematical model for the proposed method was built, and the optimizing principles for sensor number and sensor arrangement were given. Simulated and experimental results verified the feasibility and advantages of the proposed method that it could extract order spectrum accurately from BTT vibration signals measured at VRS without the drawbacks in the existing two methods.

Highlights

Since the BTT signals measured at VRS have sparsity in the order domain, this paper proposed an order analysis method to obtain the order spectrum of BTT vibration signals at VRS based on Compressed sensing (CS) theory
This paper proposed a compressed sensing-based order analysis (CSOA) method for BTT signals measured at VRS, which has good advantages over the existing methods
Simulations and experiments were performed to demonstrate the advantages and validity of the CSOA method. e main results are summarized as follows: (1) e order spectrum of undersampled BTT vibration signals measured at VRS can be accurately obtained through the proposed CSOA method

Summary

Introduction

High-speed rotating blades are critical components in turbomachinery, such as gas turbine engines and aircraft engines [1]. ey often suffer from multifrequency vibrations resulted from various exciting forces, including centrifugal force, aerodynamic force, and impact force. ese vibrations reduce the service life of the blades and may lead to cracks and even fractures, resulting in catastrophic accidents [2]. Zhan et al [17] proposed an interpolation algorithm to reconstruct blade vibration signals measured by uniformly arranged sensors, which made compensation for the effects of VRS This method required strictly precise sensor installation angles and prior information, including central frequency and signal bandwidth. Compared to the existing methods for BTT vibration signals at VRS in [17, 18], the proposed method has three major advantages: firstly, it requires no prior information of the central engine order and order bandwidth of signals; secondly, it is still feasible to the signals exceeding the order bandwidth limitation as stated in [18]; and thirdly, it allows considerable installation angle errors.

BTT Mechanism

CSOA Method

Parameter Optimization

Numerical Simulations

Experiments

Conclusions