Generally, turbine blade vibration can be divided into asynchronous vibration and synchronous vibration. Comparing to parameters identification of asynchronous vibration, that of the synchronous vibration is more difficult and needs more sensors. The applicability of the synchronous identification method is more stringent than that of asynchronous identification method. A new method is presented to identify the blade synchronous vibration parameters based on the blade tip-timing (BTT) method and previous achievements in this region. Here, the parameters, such as the frequency of harmonic resonance center, blade vibration amplitude and the initial phase, are obtained by the nonlinear least square fitting algorithm based on relationships between the rotation speed and the blade tip displacement. We call this way as sweep frequency fitting (SFF) method. As the blade is operated at a constant speed that is near the frequency of resonance center, the blade vibration displacement can be obtained by the sensors at different positions, so the blade synchronous vibration Engine Order (EO) can be obtained by the global autoregressive with instrumental variables (GARIV) method. Furthermore the Campbell diagram of blade synchronous vibration can be plotted by the parameters obtained by GARIV method and SFF method. In the experimental study, the parameter identification of blade synchronous vibration is completed and the Campbell diagram of blade vibration is accurately plotted under the excitation of six magnets. Meanwhile, the experimental study and analysis on the harmonic vibration of blade with different numbers of excitation are carried out. The relative deviation of the dynamic frequency of blade between the experimental result and simulation result is less than 1%.
A parameters identification method of the equivalent circuit model of the supercapacitor cell module based on segmentation optimization