High Sensitive Methods for Health Monitoring of Compressor Blades and Fatigue Detection

Abstract

The diagnostic and research aspects of compressor blade fatigue detection have been elaborated in the paper. The real maintenance and overhaul problems and characteristic of different modes of metal blade fatigue (LCF, HCF, and VHCF) have been presented. The polycrystalline defects and impurities influencing the fatigue, along with their related surface finish techniques, are taken into account. The three experimental methods of structural health assessment are considered. The metal magnetic memory (MMM), experimental modal analysis (EMA) and tip timing (TTM) methods provide information on the damage of diagnosed objects, for example, compressor blades. Early damage symptoms, that is, magnetic and modal properties of material strengthening and weakening phases (change of local dislocation density and grain diameter, increase of structural and magnetic anisotropy), have been described. It has been proven that the shape of resonance characteristic gives abilities to determine if fatigue or a blade crack is concerned. The capabilities of the methods for steel and titanium alloy blades have been illustrated in examples from active and passive experiments. In the conclusion, the MMM, EMA, and TTM have been verified, and the potential for reliable diagnosis of the compressor blades using this method has been confirmed.