Application of Wavelet Fractal Dimension Estimation in Dividing Flood Stages for Three Gorges Reservoir
Abstract Limit water level control improves water resources utilization efficiency without reducing flood control standard, while the premise is to divide the discharge series into a number of different flood stages. Db4 is selected as wavelet base, based on Mallat algorithm, put forward the model of wavelet dimension estimation method and calculated the fractal dimension of floods at the Yichang station, got the flood periods of Three Gorges reservoir. The results indicate that the method of wavelet dimension estimation can obtain the same result as traditional methods, and it has the merit of simplicity and stability. As a feasible and effective tool, the wavelet dimension estimation method is recommended in the applications of dividing flood periods.
Application of system clustering method to dividing flood season of reservoir
A multi-factors system clustering method based on the fuzzy similarity matrix is put forward herein with the study made on the actual problem of dividing the flood season of the control catchment(basin) of reservoir, which avoids the lopsidedness caused by using single factor method used ever before. Taking Luanhe River basin as an example, six factors describing the characteristics of both the rainfall and the runoff are chose to calculate the similarity coefficients between the factors in order to compose a fuzzy similarity matrix, and then an analytical calculation is made on the division of the flood season for the basin concerned through the system clustering method, of which the results show that the method is more reasonable in practice.
Fully Integrated Bidirectional CMOS-MEMS Flow Sensor With Low Power Pulse Operation
Leveraging More-than-Moore technology, we demonstrate an integrated CMOS MEMS flow sensor via a very compact system on chip (SoC) that can sense the bidirectional N2 gas flow. Our SoC features a very low-noise instrumentation amplifier that is implemented on a CMOS wafer and serves as a readout integrated circuit for a thermoresistive micro-calorimetric flow sensor which is fabricated on a MEMS wafer. A compact heterogeneous integration is achieved by combining the two wafers via the proprietary InvenSense AlN process. The measured sensitivity of our CMOS MEMS flow sensor is 98 mV/sccm which is three times better than the state-of-the-art counterpart. The flow range measured by our SoC is from −26 to 26 m/s (from −50 to 50 sccm). Moreover, the pulsed heater operation makes this proposed SoC flow sensor a very low power (<9 mW) and, thus, a promising candidate for the Internet-of-Things applications in smart home/green buildings.