An improved mistuning identification and dynamic strain prediction method for rotating blades with application of blade tip timing technology

Blade tip timing (BTT) is the most effective technique for vibration monitoring of rotating blades. The research of dynamic characteristics and forced responses of the blisk is crucial to the matters of blade vibration with far-reaching significance. The general mistuning identification techniques require experimental tests and numerical solutions of the whole bladed disk. Since the feature of the BTT technique can identify the modal properties of blades, this paper proposed a blade natural frequency deviation-based mistuning identification method, which achieves the mistuning quantitative evaluation and the model online update of mistuned blisk. Numerical analysis and experimental investigations prove that the improved mistuning identification method can reach accurate and reasonable results, especially in the mode dominated by blade vibration. Furthermore, based on the three assumptions of the fundamental mistuning model (FMM), an additional condition was defined: The mode strain energy proportions of the blade in the isolated modal family can be believed identical. This study revealed the relationship between blade strain and blade vibration, and an improved dynamic strain prediction method for the implementation of non-contact measurement of blade strain was proposed. The numerical analysis shows the prediction error of dynamic strain is less than 3%. Two experimental tests reported that the prediction results of dynamic strain are consistent with the FMM and BTT-based non-contact dynamic stress measurement (FB-NDSM) method, and the maximum error of prediction results is less than 2% about a FB-NDSM method reference, which is acceptable in practical applications. Improved mistuning identification and dynamic strain prediction method with the application of BTT technology are attractive for the dynamic characteristic study and health management of the bladed disk, which significantly promotes the application of BTT technology in blade vibration monitoring of large-scale rotating machinery.