49results about How to "Good nonlinear characteristics" patented technology

Disclosed is a spherical hinge class rubber elastic element rigidity varying method and a spherical hinge class rubber elastic element; the combination mode of the multi-segment spherical hinge class rubber elastic bodies is adopted; the non-linear properties of the segments of the spherical hinge rubber elastic bodies are different; the spherical hinge class rubber elastic elements with different non-linear properties are combined on a spindle to realize the variation of the rigidity of the whole spherical hinge class rubber elastic element in different situations and radial directions, so as to realize the varying rigidity purpose. The spherical hinge class rubber elastic element comprises a metal spindle, a metal outer sleeve , an elastic rubber body and a metal inner sleeve; the elastic rubber body, the metal outer sleeve and the metal inner sleeve are integrated to a whole through vulcanization; the metal inner sleeve is nested on the metal spindle; the spherical hinge class rubber elastic element rigidity varying method and the spherical hinge class rubber elastic element have the advantages that the spherical hinge class rubber elastic element is the combined structure of a mutually-independent three-segment elastic body; the whole spherical hinge class rubber elastic rubber is composed of three independent parts, including a metal outer sleeve, an elastic rubber body, a metal inner sleeve; the elastic bodies are axially combined on the spindle to construct a whole.

The invention provides a method for changing the stiffness of spherical-hinge type rubber elastic elements, and a spherical-hinge type rubber elastic element. The method comprises the following steps: a four-piece mode of combining the spherical-hinge type rubber elastomers is adopted; two elements which are opposite are taken as one group, so as to form two mutually perpendicular groups of spherical-hinge type rubber elastomers; by changing the structures of the two groups of spherical-hinge type rubber elastomers in the perpendicular direction, the stiffness properties of the two groups of spherical-hinge type rubber elastomers are different; and by adjusting the structures of the two groups of spherical-hinge type rubber elastomers, the stiffness of the spherical-hinge type rubber elastomers is changed, so as to meet the requirement on different stiffness in every direction. In the two mutually perpendicular groups of spherical-hinge type rubber elastomers, a rubber elastic elastomer in one direction and a metal housing are integrally vulcanized together with no gap, and a certain gap is reserved between the rubber elastic elastomer in the other direction and the metal housing.

The invention relates to the technology of information system safety engineering, in particular to an integral nonlinear mapping-based hash function constructing method. The method comprises the following steps of: (1) filling information; (2) setting a group of initial vectors and parameters; (3) performing non-linear segmental code word expansion of message packets; (4) using a coupling mapping system model to make the parallel mode blending iterative operation, and realizing the blending and dispersion of the expanded code words and the link variables; and (5) outputting a variable length hash. The hash function constructing method is mainly used in fields of digital certificates, electric signatures, password protection, digital integrity verification and the like, adopts the nonlinear segmental type code word expansion technology, speeds up the nonlinear dispersion degree of the code words, combines the integral nonlinear mapping and a logic function and has relative ideal blending and dispersing characteristics; the parallel iterative structure is used in the compression function of the method, so that the high-speed parallel realization of software and hardware can be realized conveniently; and the constructing method has high operating efficiency, and the hash function is easily modified, supplemented and maintained.

This invention relates to a control gap used in protecting neutral points of transformers including a fixed gap, a control gap and its control loop and a capacitance equalizing loop, in which, the fixed gap is serial to the control gap, one end of the fixed gap is connected to the neutral point and one end of the control gap is connected to the earth, the control gap is controlled by the control loop to trigger actions, the capacitance equalizing loop is parallel at both ends of the fixed gap and control gap for bleeding, the equalizing capacitor parallel to the control gap is composed of a serial equalizing capacitor with small capacitance value and high voltage endurance and a measuring capacitor with great capacitance and low voltage endurance providing input signals for the control loop. This invention jointly uses an arrester often used for transformer neutral point to protect the neutral point including: impacted by thunder and operation, the arrester operates to limit over voltage of the neutral point, when the point insulated line-frequency over voltage is threatened in the system, the control gap breaks through it to discharge to protect the insulation of the point and the arrester.

The invention discloses an SDN flow prediction method based on RBF neural network, belonging to the technical field of wireless communication network. The SDN traffic prediction algorithm based on theRBF neural network provided by the invention has excellent non-linear characteristics, is particularly suitable for processing highly non-linear system, and is trained by studying historical data records, so that a properly trained neural network has the ability of inducing all data. Secondly, the RBF neural network has a flexible and effective way of learning. Compared with other neural networks, the structure of RBF neural network is simpler and the learning speed is faster. Therefore, the RBF neural network can predict the complex and changeable network traffic more accurately. The invention utilizes POX and Mininet to simulate the proposed algorithm, and the simulation results show that the proposed algorithm can accurately predict the SDN traffic change trend, and has better prediction performance and lower prediction error.

The invention discloses a combined type all-metal steel wire rope vibration isolator which is easy to disassemble, has various types of vibration isolation units with strong replaceability, variable rigidity and variable damping, reduces vibration quickly, has a simple structure and is convenient to install and maintain. The combined type steel wire rope vibration isolator mainly comprises a basic vibration isolating unit, an expandable vibration isolating unit and a buckle. The units are connected together through bolts. The vibration isolator has the characteristics of strong vibration isolation and reduction capacity in any direction, large damping, strong impact resistance capacity, good broadband vibration absorbing performance, obvious nonlinear characteristics, various combination modes and the like, is convenient to assemble and disassemble, convenient to package and easy to maintain and is suitable for mass production and single-piece character assembly. So the vibration isolator is widely applied in the fields of vibration reduction, vibration isolation and impact resistance of machinery and instruments under dynamic load.

The invention discloses an overhead crane neural network modeling method based on an RNA genetic algorithm of a hairpin mutation operation, and belongs to the field of intelligent modeling. An overhead crane is a highly non-linear under-actuated complicated system, and the establishment of a high-precision overhead crane system model is a crucial foundation for achieving the purpose of effective control. The invention, for the problem in overhead crane modeling precision, provides overhead crane nonlinear regression models based on a position and an angle of an RBF (Radial Basis Function) neural network. Under the inspiration of a hairpin structure, the RNA genetic algorithm of the hairpin mutation operation is abstracted, and the RBF center of the RBF neural network for the position and the swing angle of the overhead crane is optimized by running the RNA genetic algorithm of the hairpin mutation operation, so that a neural network model of the overhead crane is obtained. The modeling method has the characteristic of high modeling precision, and is also suitable for modeling other complicated nonlinear systems.

The invention belongs to the space travelling wave tube non-linear technology field and particularly relates to a space travelling wave tube group delay inhibition method based on helix internal diameter adjustment. According to the method, synchronization deviation of an electron beam and electromagnetic waves is controlled through adjusting an internal diameter Ra of a first interaction segment helix to make a relative phase angle of a first interaction segment to be about -50 DEG, so group delay is substantially inhibited at the cost of a little of output power, a fluctuation period is substantially reduced, and fluctuation amplitude is substantially reduced. The method is advantaged in that a synchronization degree of the electromagnetic waves and the electron beam is improved, a clustering state of the electron beam is further substantially improved, the group delay is remarkably inhibited after optimization, the fluctuation amplitude and the fluctuation period are substantially reduced, and the method is mainly applicable to space travelling wave tubes for communication.

The invention discloses an inflatable vibration damper, which consists of an inflatable rubber bag, a metal mounting component and a gas charging connector component. The mounting component and the gas charging connector component are vulcanized as a whole by the inflatable rubber bag through means of vulcanization technique and the shape of the mounting component is matched with a device requiring vibration damping. The vibration damper has the advantages of wide application field, strong overloading resistance, compact structure, adjustable rigidity and the like and is applicable to occasions needing stable, accurate and precise dynamic systems, such as the vibration damping of a field testing device.

The invention discloses a heavy oil pyrolysis process modeling method based on a chaotic DNA genetic algorithm. In the invention, the DNA genetic algorithm and chaotic optimization calculating are fused; chaotic optimization calculating is performed on an individual with poor performance in the framework of the DNA genetic algorithm; the characteristic that the global search capability of the DNAgenetic algorithm is high is reserved and simultaneously the weakness that a local search capability is poor is improved; and the method has a good application and development prospect. The DNA genetic algorithm is applied to the parameter estimation of the reaction kinetic model of a heavy oil pyrolysis process. A result shows that a heavy oil pyrolysis process model can well reflect the nonlinear characteristic of an actual system.

The invention discloses a bridge crane modeling method adopting a hairpin mutation operation RNA genetic algorithm and belongs to the field of intelligent modeling. A bridge crane is a highly nonlinear complicated system, and building a high-precision bridge crane system model is a fatal basis for the purpose of effectively control. For high bridge crane modeling precision, a bridge crane nonlinear regression model based on the position and the angle of an RBF nerve network. Under inspiration of a hairpin structure, the hairpin mutation operation RNA genetic algorithm is abstracted and applied to optimize the radial basis function center of the bridge crane RBF nerve network so as to obtain a nerve network model of the bridge crane. The bridge crane modeling method has the characteristic of high modeling precision and is also suitable for modeling other complicated nonlinear systems.

A nonvolatile resistive switching memory (ReRAM) device having no selection device is provided. The ReRAM device includes a lower electrode that is formed on on a substrate; a metal oxide layer that is formed on the lower electrode, the metal oxide layer having a resistive switching characteristic; an upper electrode that is formed on the metal oxide layer; and a tunnel barrier oxide film that is formed between the lower electrode and the metal oxide layer, thereby forming a double oxide film structure, the tunnel barrier oxide film being made of a material, a band energy gap and a conduction band offset of which are lower than those of the metal oxide layer, and which does not cause interface switching.