FPGA-Based Data Acquisition System With Preprocessing of Plasma Signal

Laser diagnostics, particularly the Thomson scattering technique, is one of the methods used to measure the electron temperature of plasma, which is highly contaminated by noise. In this work, novel preprocessing methods with adaptive filters have been proposed to suppress unwanted noise from the plasma signal. Simulations have been carried out on the real data captured in the laser diagnostic laboratory. The hardware architectures of novel preprocessing methods and adaptive filter-based noise cancellation systems to acquire filtered signals to a remote computer for signal monitoring are presented. Moreover, field-programmable gate array (FPGA)-based hardware simulation result for real-time noise cancellation is demonstrated with a developed graphical user interface (GUI). The proposed noise cancellation system occupies 4.09% lookup tables (LUTs) when implemented on the KC705 FPGA board and consumes 2.86-W power when operated at 250-MHz frequency.