| Summary: | Some important information pertaining to blade fault is thought to be concealed in highly unsteady casing vibration. This paper explores suitable methods to best reconstruct blade related signals from raw casing vibration, which could be used for diagnosis of blade fault. The feasibility of translation invariant wavelet transform and cycle spinning (TIWT-CS) technique in reconstruction of these signals is investigated in this paper. Subsequently, a new parameter for blade fault diagnosis, namely, the energy profile of blade signal (EPBS), is formulated. Experimental results show that TIWT-CS method effectively retained blade related signals, while other unwanted signals such as system noises and aerodynamic induced vibration are reasonably suppressed. EPBS provides an indication of the condition of blade faults in rotor system, whereby the exact position and the quantity of faulty blades, as well as the root cause of blade fault, can be identified. In comparison, the energy profile plots using unfiltered casing vibration were found to be highly unstable and therefore provides inconsistent results for diagnosis of blade fault.
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