The pressure fluctuation characteristics in a Francis hydro-turbine running at partial flow conditions were studied based on the chaotic dynamic methods. Firstly, the experimental data of pressure fluctuations in the draft tube at various flow conditions was de-noised using lifting wavelet transformation, then, for the de-noised signals, their spectrum distribution on the frequency domain, the energy variation and the energy partition accounting for the total energy was calculated. Hereby, for the flow conditions ranging from no cavitation to severe cavitation, the chaos dynamic features of fluctuation signals were analyzed, including the temporal-frequency distribution, phase trajectory, Lyapunov exponent and Poincaré map etc. It is revealed that, the main energy of pressure fluctuations in the draft tube locates at low-frequency region. As the cavitation grows, the amplitude of power spectrum at frequency domain becomes larger. For all the flow conditions, all the maximal Lyapunov exponents are larger than zero, and they increase with the cavitation level. Therefore, it is believed that there indeed exist the chaotic attractors in the pressure fluctuation signals for a hydro-turbine.
A novel cascaded charge-sharing technique is presented in content-addressable memories (CAMs), which not only effectively reduces the match-line (ML) power by using a pre-select circuit, but also realizes a high search speed. Pre-layout simulation results show a 75.9% energy-delay-product (EDP) reduction of the MLs over the traditional precharge-high ML scheme and 41.3% over the segmented ML method. Based on this technique, a test-chip of 64-word × 144-bit ternary CAM (TCAM) is implemented using a 0.18-μm 1.8-V CMOS process, achieving an 1.0 ns search delay and 4.81 fJ/bit/search for the MLs. 相似文献
