There is a global challenge in demand and need of electricity. Whenever a serious fault occurs, it affects the productivity of any power plant. So many indicators have been identified in real-time fault diagnosis of steam turbine which is extremely important in a functioning power plant. Detection of fault and early rectification requires a real time intelligent fault diagnostic system. This paper considers seven types of very slowly happening and accumulating physical phenomena which will ultimately lead to deterioration in turbine performance. Based on the acquired domain knowledge, an online intelligent diagnostic analyzer for turbine performance degradation is designed in this paper by using a VLSI based methodology written in Verilog code and simulated using a simulator (Modelsim Altera 6.4a). This system can be easily implemented on to FPGA which enables the identification of the root causes for turbine performance degradation. The simulation results show that the developed real-time fault diagnostic system is accurate, high percentile with less time consuming, cost effective, and easy to apply and user friendly. 
Implementation of VLSI model as a tool in diagnostics of slowly varying process parameters which affect the performance of steam turbine