Abstract
Crack localization in running rotors is very important and full of challenges for machinery operation and maintenance. Characteristic deflection shapes or their derivatives based methods seem to be promising for crack localization in rotors. Despite the substantial advantages, several critical issues still need to be addressed to enhance the efficiency of this kind of method for practical applications. Two problems are considered in this work: 1. How to localize single or multiple cracks accurately avoiding the interference of commonly existing steps without baseline information on pristine rotors; 2. How to improve the crack localization performance under a noisy environment. To circumvent the issues, a novel baseline-free adaptive crack localization method is proposed based on data fusion of multiscale super-harmonic characteristic deflection shapes (SCDSs). In this method, crack induced asymmetry and nonlinearity of crack breathing are utilized to simultaneously eliminate the interference from the steps without a reference model. To enhance the noise robustness, the multiscale representations of SCDSs are made in Gaussian multiscale space, and Teager energy operator is applied to the multiscale SCDSs to amplify the crack induced singularities and construct the multiscale Teager super-harmonic characteristic deflection shapes (TSCDSs). Moreover, fractal dimension is designed as an evaluator to select the proper multiscale TSCDSs for data fusion adaptively. Then, a new damage index is derived for crack localization by Dempster-Shafer’s (D-S) evidence fusion of the adaptively selected multiscale TSCDSs. Finally, the feasibility and the effectiveness are verified by both numerical and experimental investigations.
Highlights
Crack monitoring and diagnosis in rotors based on vibration signals has been widely investigated and is an important field in the structural health monitoring (SHM) of rotating machines
The proposed super-harmonic characteristic deflection shapes (SCDSs) is a spatial shape of multi-sensor signals at a super-harmonic frequency which can be extracted by using frequency domain decomposition (FDD) [36,41]
The multiscale SCDSs are calculated by Gaussian multiscale analysis (GMA)
Summary
Crack monitoring and diagnosis in rotors based on vibration signals has been widely investigated and is an important field in the structural health monitoring (SHM) of rotating machines. As for crack localization in rotors, it is of great importance for the maintenance of rotating machines, fewer studies have been carried out and it is still difficult to apply in Sensors 2020, 20, 5693; doi:10.3390/s20195693 www.mdpi.com/journal/sensors. This work aims at developing a crack localization method for rotors containing commonly existing steps under operating and noisy conditions. As the natural frequencies are global parameters, reference models are required to provide more spatial information for the natural frequency-based methods. For the mode shape-based method, it contains enough spatial information and has been applied in stationery structures successfully, but it is difficult to obtain mode shapes for rotors under operating conditions
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