Microseismic monitoring is widely applied in dams, mines, and various fields of underground engineering. The number of sensors in microseismic monitoring systems is usually very large, which will result in a huge amount of data being produced if the Nyquist sampling theorem is used to acquire microseismic signals. To reduce the data storage costs and accelerate the transmission speed, we propose a distributed compressed sensing (CS) scheme for microseismic monitoring signals in this paper. The distributed compressed sensing scheme begins when it detects the first break time in the microseismic signal. The data recoding of the first break time is coded and transmitted together with the measured values of CS. Depending on the correlations between the microseismic signals, the first break time of the signals are aligned to that of the reference signal. Furthermore, we make use of the distributed CS to reduce the amount of data to be transmitted and to increase the reconstruction accuracy. Simulation results show that, compared with the sampling scheme based on the Nyquist sampling theorem, the independent CS scheme or the traditional distributed CS scheme, our proposed scheme improves the accuracy in the first break time detection and the reconstruction accuracy, and the scheme reduces the energy consumption at the same time.
In order to effectively solve the ecological problem of global desertification, and aimed at the inadequate existing desertification combating technologies, Solidworks modeling software was used to design a people-oriented, light weight, and portable linear sand-barrier paving machine. Besides, Altium Designer software was used to draw the PCB board circuit diagram of corresponding functions to achieve a flow-line operating mode of the equipment from storing straw, to making furrows, then to feeding materials, and finally to pressing straw. Lastly, ANSYS software was used to make the finite-element analysis of key parts and components, and their feasibility was verified, with the final experimental results meeting paving requirements. The design of the cart proactively responds to the philosophy for protecting the ecological environment that "lucid waters and lush mountains are invaluable assets", a philosophy that is conducive to meeting the ever-growing needs of the people for a good life, and is of vitally practical significance for promoting regional economic coordination, sustainable development, and ecological conservation.
Two layer compatible control framework is an effective method to solve the conflicting multi-objective control problem, however, which should overcome the difficulties---direct multi-objective optimization, be assuring of the realization of the multiple objectives selecting from the first layer and online optimization. Multi-objective genetic algorithm (MOGA) is adopted as the optimization tool. To assure the objectives realization from the first layer, a different optimization performance index was designed and a selection function was added in to reflect the control system requirement. Integrated with the predictive control theory, online iterative genetic algorithm (IGA) was proposed and solved the optimizationspeedproblem. The predictive control dynamic process error and energy consumption were taken as the two objectives to illuminate the compatible predictive control algorithm (CPCA).
Large-area silicon nanowire arrays are prepared successfully with mixed AgNO3 and HF solution by EMD method at normal temperature and pressure. It has been proved the best equality of silicon nanowires can be obtained at the concentration ratio of 0.02 mol/l: 5mol/l for AgNO3 and HF and 1h reaction time. The influence of nano metal particles on the growth, the wire diameter, the distribution and the array of silicon nanowires are analyzed. Experimental results show the distribution and wire diameter of silicon nanowires can be controlled effectively by nano metal particles deposited on silicon wafers, and the equality of silicon nanowires with nano Au particles are better than those with nano Pt particles. The reaction mechanism of preparing large-area silicon nanowire arrays is analyzed as the result of the deoxidization of Ag+ and the removal of the oxidized Si solution by reacting with HF.
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