In Situ Detection of Turbine Blade Vibration and Prevention
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Turbine blades are the most critical components in any power plant. Failure in even one rogue blade out of hundreds of blades fixed on the rotor leads to colossal damage to the machine. Statistics have shown that low-pressure turbine blades in steam power plants are generally more susceptible to failure compared to high- or intermediate-pressure blades. The mechanism of failures is different in each case and is generally very complex. As a result, a large number of blade failures are not fully understood. Two primary forces acting on the blades are the steady centrifugal force due to rotation and the fluctuating steam bending force. In view of no direct access to monitor the health of the blades through vibration or other means, indirect method using non-contacting probes have been attempted and some are in use in special cases. Largely these methods are expensive and intrusive in nature. They involve placing of sensors in the narrow space inside the turbine casing, routing special signal cables with sealing arrangement and involves difficulties in analyzing shot duration signals from each rotating blades. Unless a diagnostic technique is made simple to implement and whose reliability is proven, power plants will not find it attractive to invest on upgrade for safe operation of the machine. This article is about an innovative method of detecting the presence of blade vibration in operating turbine through vibration signal analysis and prevention through process control. The method is based on vibration analysis of the turbine casing. The casing vibration includes signals associated with the blades of different stages called as blade passing frequency (BPF). When the rotating blades vibrate, the analysis of changes in the BPF is a novel way of diagnosing blade vibrations. Signals captured from operating plants have been analyzed and blade vibrations have been detected and verified with Campbell diagram. Laboratory experiments were carried out on a rotating fan to demonstrate robustness of the diagnostics tool for turbine blades.
KeywordsTurbine blades LP casing Vibration Accelerometer Signal analysis Blade passing frequency
The authors would like to acknowledge the support and assistantce provided by their colleagues in the Vibration Laboratory of BARC, Mumbai, India, for this analytic research.
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