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 discloses an amplifier digital pre-distortion device based on a dynamic fuzzy neural network. The amplifier digital pre-distortion device comprises a digital pre-distortion device, a digital analog converter, a broadband quadrature modulator, a power amplifier, an attenuation coupler, a broadband quadrature demodulator, an analog digital converter and a pre-distortion device training module. Dynamic fuzzy neural network pre-distortion processing is conducted on an inputted digital baseband signal through the digital pre-distortion device, coupling, quadrature demodulation and analog digital conversion are conducted on an analog baseband signal outputted by the power amplifier through the attenuation coupler, the broadband quadrature demodulator, the analog digital converter respectively, and then an outputted digital baseband signal is generated. The inputted digital baseband signal and the outputted digital baseband signal are synchronously inputted into the pre-distortion device training module, and the pre-distortion device training module obtains a dynamic fuzzy neural network module parameter after carrying out parameter training through an online self-organized learning algorithm and sends the dynamic fuzzy neural network module parameter to the digital pre-distortion device. The invention further provides an amplifier digital pre-distortion method. By means of the amplifier digital pre-distortion device and method, the advantages of a fuzzy system and the advantages of a neural network are combined, dynamic adjustment can be achieved according to the complexity of a non-linear system, implementation is easy, and the non-linear characteristic and the memory effect of the power amplifier can be well compensated for.

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.

An apparatus and method that compensates for pre-distortion of a power amplifier includes a digital pre-distorter controller which generates a power / phase compensation coefficient, a temperature compensation coefficient and a frequency compensation coefficient, a look-up table which stores the coefficients, a pre-distorter kernel which pre-compensates an input signal based on the temperature compensation coefficient from the look-up table, and a correction filter which compensates an output signal of the kernel based on the frequency compensation coefficient from the look-up table. If desired, an input signal may be pre-distorted based on only one of the temperature and frequency compensation coefficients along with the power / phase compensation coefficient. Nonlinear characteristics of the power amplifier are accurately checked and distortion due to the nonlinear characteristics are compensated for.

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 three-order nonlinear optical telluro composite film and a preparation method thereof. In the method, a Te / TeO2-SiO2 composite film structure formed by TeO2 and / or Te is embedded among SiO2 particles; the film is prepared by an electrochemically induced sol-gel method, the composite film structure has good nonlinear features, and three-order nonlinear optical polarizability Chi (3) reaches more than 10<-8>esu; the Te / TeO2-SiO2 composite film is prepared by an electrochemical method through TeO2-SiO2 transparent composite sol, TeO2 and / or Te is separated out of the soil by virtue of electrochemical induction to form a film with SiO2, thus achieving the purpose of forming the Te / TeO2-SiO2 composite film structure, and realizing simple process; and the Te / TeO2-SiO2 composite film is prepared by a vacuum coating method through TeO2-SiO2 transparent composite sol-gel; and by virtue of temperature control for heat treatment, composition and structure of gel powder is regulated and controlled, thus achieving the purpose of forming the Te / TeO2-SiO2 composite film structure, and having simple and reliable process as well as uniform thickness of film layers.

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 relates to a bearing-typed variable damper used for an automobile suspension, comprising a dual-cylinder oil cylinder with an internal cavity and an external cavity with an upper port consisting of an internal cylinder and an external cylinder sealed by a guider and a sealing seat, a piston arranged in the internal cavity of the oil cylinder and a piston rod connected with the piston, a check valve in the bottom part of the internal cylinder communicated with the internal cavity and the external cavity of the dual-cylinder oil cylinder, a piston check valve arranged on the piston and communicated with an upper cavity and a lower cavity, and a charging connector arranged at the lower part of the external cylinder. The invention is characterized in that the piston check valve is a normal check valve without throttle holes; the side wall at the lower part of the internal cylinder is provided with a compressed damping hole communicated with the internal cavity and the external cavity; a static seal is arranged between the sealing seat and the external cylinder; a high pressure sealing ring is arranged between the sealing seat and the piston rod. The structure of the invention is designed between the normal dual-cylinder damper and an oil-gas spring. Owning to the adopted high pressure sealing structure, the invention has the advantages of bearing static loads, and leading the normal automobile suspension to increase the bearing capability and to have the ideal nonlinear characteristic.

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 super-resolution optical imaging method for forming a small-hole probe based on double-beam transient trepanning. In a scanning microscope imaging system, the cover glass plated with a phase-change material thin film abuts against the surface of a sample, and then two beams focus the cover glass simultaneously to be irradiated onto the sample, one beam is high-power pulseexciting light, and the other beam is low-power probe light. By using the non-linear characteristic of the phase-change material, when the exciting light acts on the phase-change material, the material has a non-linear saturated absorption characteristic, transient small holes are formed in the material, the effective radius of the probe light decreases after the probe light passes through the transient small holes, and the small-hole probe lower than limit is formed; when the material has a non-linear anti-saturated characteristic, differentiation is carried out with a signal under a triggeraction by using a weak optical signal under an unexcited action, the transient small-hole probe lower than the limit can also be formed, point-by-point scanning imaging is realized by using the formed small-hole probe, and super-resolution far-field optical imaging is realized.

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.

The invention belongs to the technical field of spatial traveling wave tube nonlinearity, and particularly relates to a clamping rod adjustment-based spatial traveling wave tube group time delay inhibition method. According to the method, a synchronous deviation of an electron beam and an electromagnetic wave is controlled by adjusting the width n of a rectangular clamping rod of a first interaction section, and a relative phase angle of the first interaction section is enabled to be about 50 degrees, so that the group time delay is greatly inhibited by consuming a small amount of output power, the fluctuation cycle is greatly shortened, and the fluctuation range is greatly narrowed. On the premise of ensuring that the output power meets a user index (>150W) in the whole frequency band range, the group time delay is remarkably inhibited, and the fluctuation range and the fluctuation cycle are remarkably narrowed and shortened; and the method mainly aims at spatial traveling wave tubes used for communication.

The invention relates to a composite broadband filter circuit with an anti-surge voltage. The circuit comprises a piezoresistor circuit, a first-stage LC filter circuit, a second-stage LC filter circuit and a three-stage LC filter circuit. The piezoresistor circuit enables a low-frequency interference signal to be controlled in an allowable range of a device, thereby realizing suppression of a low-frequency surge and an interference signal. The first-stage LC filter circuit is formed by two transient suppression diodes and an LC circuit; and the transient suppression diodes are used for realizing surge voltage suppression so as to realize protection of a back-end circuit and improve the anti-electromagnetic interference capability of the application product. The second-stage LC filter circuit and the three-stage LC filter circuit are used for improving the filter effect further. According to the invention, the filtering function is combined with the anti-surge voltage function; and a high-low frequency filtering circuit with a composite function is formed based on three-stage filter circuits, so that the filtering effect is improved. Moreover, the composite broadband filter circuithas advantages of simple circuit, low cost, fast response time and the like.

The invention discloses a driving servo grid damping device for vibration damping control of a building structure. The driving servo grid damping device for the vibration damping control of the building structure comprises a water box, an acceleration sensor and a control system. The water box comprises a box body, N group grid damping units with N group same structures in the box body, the box body are divided into N+1septums by the N group grid damping units, and the adjacent septums are in communication with each other; the grid damping unit comprises an outer frame, grid blade shafts and driving grid blades, the outer frame is longitudinally installed in the box body, a plurality of grille blade shafts are mounted on the outer frame in a vertical mode, the grille blade shafts are arranged at equal intervals in a linear shape, the driving grid blades are fixedly arranged on the grid blade shafts, the box body is also provided with two water box inlet-outlet valves, the two water boxinlet-outlet valves distribute in a diagonal mode, and the control system is correspondingly connected with the water box inlet-outlet valves and the grid blade shafts. According to the driving servogrid damping device for the vibration damping control of the building structure, the damping of the water box can be adjusted, and the energy dissipation and vibration damping function can be achieved.

The invention discloses an ultra-wideband analog pre-distortion method and device, which comprises a first frequency mixer and a second frequency mixer, wherein the two frequency mixers are respectively connected with a first frequency sweeping local oscillator and a second frequency sweeping local oscillator; the first frequency mixer is connected with a pre-distortion generator; the pre-distortion generator is connected with the second frequency mixer; and the second frequency mixer is connected with a power amplifier. The ultra-wideband analog pre-distortion method comprises a signal frequency conversion step, a pre-distortion signal generation step, a frequency reducing step and a signal counteracting step. According to the scheme, the frequency mixers and the frequency sweeping localoscillators are used for converting an input signal into a radio frequency signal with a fixed frequency; then, the analog pre-distorter is used for generating a pre-distortion signal; finally, the signal is converted to the input frequency through the frequency sweeping local oscillators and the frequency mixers, wherein a distortion signal opposite to the power amplifier is included in the signal at the moment, so that the distortion generated by the power amplifier itself can be counteracted after the signal passes through the power amplifier, and the purpose of improving the linearity of the power amplifier is achieved.

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.

The invention discloses a sliding-mode control method for an electric-hydraulic servo system. The method comprises the steps that a mathematical model of the electric-hydraulic servo system is established, and then a control strategy of a sliding-mode controller is defined after a boundary layer and an approaching law are improved. According to the sliding-mode control method for the electric-hydraulic servo system, the boundary layer and the approaching law are improved, discontinuous terms are eliminated, the distance from a state point to the sliding-mode surface is decreased, the chattering phenomenon of the sliding-mode controller can be weakened, and the approaching speed is increased; the dynamic response characteristic of the system is improved, the tracking performance of the system is improved, the control accuracy of the system is improved, an input waveform can be better restored, and good control performance of the hydraulic servo system is guaranteed. The sliding-mode control method for the electric-hydraulic servo system has the advantages of being high in servo control accuracy, high in robustness, high in response speed, high in stability and the like.

A wheel hub-driven electric vehicle air suspension system with multi-layer additional air chambers, mainly including four air springs with multi-layer additional air chambers in two groups including front suspension system and rear suspension system; each air spring contains A main air chamber and an additional air chamber; the main air chamber is a membrane-type flexible rubber airbag structure, and the additional air chamber is a rigid multi-layer structure; the main air chamber and the additional air chamber are connected by a gas pipeline, and an aperture is set on the gas pipeline Adjustable throttling orifice; the controller of each air spring can independently control the throttling orifice and switch valve at the same time; each air spring is equipped with a sensor for measuring the displacement of the piston, and the displacement sensor is connected to the central controller; The controller is respectively connected with the controller of each air spring. The central controller can keep the suspension performance of the vehicle in an ideal state under different working conditions and road conditions through the combination of the opening and closing state of the additional air chamber switch valve and the control of the throttle orifice aperture.

The invention provides an electroencephalogram grading and prognosis FPGA decoding system based on neural manifold. The system comprises an electroencephalogram acquisition device, an FPGA decoding calculation device, a liquid crystal touchable display screen and a stimulation device. The FPGA decoding calculation device is composed of a manifold extraction subsystem, a cognitive optimization parameter calculation subsystem, an electroencephalogram grading processing subsystem and an electroencephalogram prognosis evaluation processing subsystem which are used for extracting manifolds, calculating stimulation parameters needed for optimizing cognitive functions and conducting grading and prognosis evaluation on electroencephalogram signals respectively. Electroencephalogram grading is carried out, prognosis evaluation is carried out through the change trend of the difference value between the actual neural manifold and the target manifold, the two manifolds, the stimulation parameters and the grading prognosis result are transmitted to a display screen through wires, and the optimal stimulation parameters are transmitted to a stimulation device through a wire for control. According to the system, electroencephalogram automatic grading, prognosis evaluation and brain cognitive function optimization can be achieved.