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489results about How to "Improve compromise" patented technology

A low-cost precision casting method for titanium alloy and titanium-aluminum alloy

The invention relates to a method for precisely casting a titanium alloy and a titanium aluminum alloy with low cost, which relates to a method for precisely casting the titanium alloy and the titanium aluminum alloy, and solves the technical problem that cast pieces have low surface quality and internal quality in the conventional method for lowering the cost of precisely casting the titanium alloy and the titanium aluminum alloy by using electrically-fused alumina and silica sol. The method comprises the following steps of: preparing a surface layer binder from zirconium sol, silica sol, a wetting agent JFC, n-octyl alcohol, polyvinyl alcohol and latex; adding calcium carbonate, alumina, titanium dioxide and zirconia to prepare a surface layer coating; preparing a shell surface layer; preparing a shell back layer by a universal method for precisely casting the titanium alloy; dewaxing and sintering to obtain a shell; and casting the titanium alloy or the titanium aluminum alloy by using the shell so as to obtain a titanium alloy cast piece or a titanium aluminum alloy cast piece. Compared with a precise casting method by purely using a zirconium-based binder and a zirconia fireproof material, the method has the advantage that raw material cost is lowered by 30 to 70 percent and the method can be used for civil titanium alloy cast pieces and titanium aluminum alloy cast pieces for common aviation.
Owner:HARBIN SHITAI NEW MATERIAL TECH & DEV

Ant colony algorithm-based high-energy efficiency wireless sensor network routing method

Disclosed in the invention is an ant colony algorithm-based high-energy efficiency wireless sensor network routing method. The method comprises three parts: cluster establishment, transmission in cluster, and transmission between clusters. When a multi-hop relay node is selected, a heuristic ant colony intelligent algorithm is employed to search a multi-hop transmission route; and during the searching process, an expectation importance influence is eliminated and a probability for node selection is completely decided by the link pheromone concentration. And when a local link pheromone is updated, a dump energy minimum value of a collaboration zone node is multiplied by link pheromone increasing degree Q and then the result is divided by transmission energy consumption, thereby completing updating. According to the new pheromone updating method, the dump energy and the transmission energy consumption of the node are scaled appropriately and then are introduced to the link pheromone updating; and when the dump energy of the collaboration zone node at the next hop is increased and the transmission energy consumption is reduced, the node can be selected. Therefore, when the routing method is used, total energy consumption of the network can be reduced; the dump energy of the network nodes can be balanced; and the working life of the network can be prolonged.
Owner:GUILIN UNIV OF ELECTRONIC TECH

Multi-objective optimization method for hybrid active power filter

The invention discloses a multi-objective optimization method for a hybrid active power filter. The method comprises the following steps: analyzing the relationship between all elements of an active leg and a passive leg of the hybrid active power filter and a system impedance, and the coupling relationship between all the elements of the active leg and the passive leg so as to obtain a first class constraint condition; acquiring a performance, cost and loss model of the filter; setting a second class constraint condition according to the specification of the filter; establishing an objective function base on the performance, cost and loss model and combining the first class constraint condition and the second class constraint condition to serve as a constraint condition of the objective function; processing the objective function and the constraint condition thereof to construct a new objective function; and obtaining an optimal solution based on a chaotic algorithm and a multi-objective PSO (Particle Swarm Optimization) algorithm based on Pareto optimal solution. Compared with an optimization algorithm with two objects, the optimization algorithm with three objects formed by establishing a three-dimensional optimization objective function based on the performance, the cost and the loss can enable the optimal solution to obtain a better tradeoff among the three aspects of the performance, the cost and the efficiency.
Owner:CENT SOUTH UNIV
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