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Inicio  /  Aerospace  /  Vol: 7 Par: 6 (2020)  /  Artículo
ARTÍCULO
TITULO

A Nonlinear Ultrasonic Modulation Method for Crack Detection in Turbine Blades

Frank Mevissen and Michele Meo    

Resumen

In modern gas turbines, efforts are being made to improve efficiency even further. This is achieved primarily by increasing the generated pressure ratio in the compressor and by increasing the turbine inlet temperature. This leads to enormous loads on the components in the hot gas region in the turbine. As a result, non-destructive testing and structural health monitoring (SHM) processes are becoming increasingly important to gas turbine manufacturers. Initial cracks in the turbine blades must be identified before catastrophic events occur. A proven method is the linear ultrasound method. By monitoring the amplitude and phase fluctuations of the input signal, structural integrity of the components can be detected. However, closed cracks or small cracks cannot be easily detected due to a low impedance mismatch with the surrounding materials. By contrast, nonlinear ultrasound methods have shown that damages can be identified at an early stage by monitoring new signal components such as sub- and higher harmonics of the fundamental frequency in the frequency spectrum. These are generated by distortion of the elastic waveform due to damage/nonlinearity of the material. In this paper, new global nonlinear parameters were derived that result from the dual excitation of two different ultrasound frequencies. These nonlinear features were used to assess the presence of cracks as well as their qualitative sizes. The proposed approach was tested on several samples and turbine blades with artificial and real defects. The results were compared to samples without failure. Numerical simulations were conducted to investigate nonlinear elastic interaction of the stress waves with the damage regions. The results show a clear trend of nonlinear parameters changing as a function of the crack size, demonstrating the capability of the proposed approach to detect in-service cracks.