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31 results about "Nonlinear excitation" patented technology
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Method for calculating DC (direct current) magnetic bias dynamic leakage inductance of transformer
The invention relates to a method for calculating DC (direct current) magnetic bias dynamic leakage inductance of a transformer. The method is characterized in that: the method comprises a dynamic parameter calculation step based on a transient field-circuit coupling model, and a dynamic leakage inductance calculation step based on transient field-circuit coupling; the method can establish a three-dimensional finite element magnetic field model of the transformer and solve the model to fully reflect the accuracy of magnetic field calculation under nonlinear excitation of the transformer; and the method can calculate dynamic inductance parameters according to the energy perturbation principle, calculate a transient current by combining with four-order Range-Kuttle method, and then calculate the dynamic leakage inductance based on a T-shaped equivalent circuit of the transformer. In comparison with the existing harmonic calculation method, the method provided by the invention can calculate the dynamic leakage inductance by considering the transient changes of equivalent parameters of magnetic field and circuit of the transformer and the relationship between the parameters under different DC perturbations on the basis of field-circuit coupling. Accordingly, the method provided by the invention has higher adaptability, and higher actual application value.
Owner:NORTHEAST DIANLI UNIVERSITY
Nonlinear dynamics calculation method for gear pair
ActiveCN108052760AImprove calculation accuracySimulate the realGeometric CADSpecial data processing applicationsFeedback effectEngineering
The invention discloses a nonlinear dynamics calculation method for a gear pair. The method comprises the steps that the feedback effect of vibration displacement to the dynamic contact condition of agear surface of the gear pair in the actual running process is considered, and the nonlinear excitation of the dynamic meshing rigidity and dynamic comprehensive meshing errors is calculated. Dynamiccontact analysis of the gear pair and a system dynamics solution process are combined, and an excitation-response-feedback loop-locked calculation process of the system is achieved. According to themethod, the nonlinear dynamics phenomenon of the gear pair due to parameters such as gear surface errors and shape correction can be acquired, the dynamics behavior of the system in the dynamic contract process can be more truly simulated, and the calculation accuracy of dynamics is improved.
Owner:CHANGAN UNIV
An identity recognition method based on a dual-channel convolutional neural network
ActiveCN109409297AImprove accuracyEasy to identifyNeural architecturesMultiple biometrics useNerve networkIdentity recognition
The invention discloses an identity recognition method based on a dual-channel convolutional neural network, and the method comprises the steps: carrying out the training of a neural network and the identity recognition, carrying out the comprehensive training and recognition through employing two time synchronization images: a face image and a whole body posture image, avoiding the cheating of asingle factor, and achieving the high anti-interference capability and high recognition accuracy. According to the method, feature data of two channels are connected in a weighted mode through a fullconnection layer, image feature data are obtained through a plurality of convolution layers and a pooling layer, finally the classification probability is obtained through a classifier, and the maximum probability is extracted to be compared with a set threshold value to determine the recognition result. Through multiple times of convolution feature map extraction, nonlinear excitation and poolingdimension reduction processing, the dual-channel convolutional neural network control data is more flexible, and the abstraction capability and the learning capability are stronger, thereby having abetter identification effect.
Owner:咪付(广西)网络技术有限公司
Main and auxiliary integrated fault locating method and system based on gradient descent algorithm
ActiveCN109782124AIncrease flexibilityImprove fault toleranceFault locationInformation technology support systemGrid faultDescent algorithm
The invention discloses a main and auxiliary integrated fault locating method and system based on a gradient descent algorithm. In the fault locating method, the fault locating of a main and auxiliaryintegrated network model is realized based on the gradient descent algorithm, and meanwhile, based on the above method, a fault locating system composed of a data acquisition module, an analysis module and an accuracy evaluation module is constructed. The method is verified by an IEEE standard 33-node topology example. The example is to simulate the grid fault, calculate and preprocess multi-dimensional data measured by each node through the data acquisition module, establish a multi-layer neural network by using a neural network gradient descent algorithm idea, select an appropriate excitation function for nonlinear excitation, optimize the accuracy of model locating based on the gradient descent algorithm, and provide a fault branch locating result in a fault locating calculation module. The example simulation shows that the branch where the fault occurs can be located with high accuracy. The fault locating method effectively locates the branch of a grid where the fault occurs, provides an effective decision basis for the operation and repair of the grid, and reduces the economic losses.
Owner:JIANGSU ELECTRIC POWER CO +1
An unmanned driving path selection method based on multi-sensor cooperation
PendingCN109886152AEasy to identifyFine surrounding informationForecastingCharacter and pattern recognitionPattern perceptionImage prediction
The invention discloses an unmanned driving path selection method based on multi-sensor cooperation, which comprises the following steps of arranging a multi-cooperation sensor and a high-sensitivitycamera around a vehicle body, performing sensor distribution adjustment and replacement according to the importance of different positions of the vehicle body in driving recognition, and obtaining allbasic information around the vehicle body; analyzing the coverage and redundancy of a sensor to obtain the driving condition of an automobile, and taking an image captured by a high-sensitivity camera as the input of a full convolutional neural network; performing nonlinear mapping on the data in an encoding stage by using a full convolutional neural network; in the decoding stage, adopting the nonlinear excitation, achieving the rough segmentation of an image through an image prediction channel, using an Adam algorithm, and optimizing the hyper-parameters, reasoning a road and finally obtaining a road segmentation model; and on the basis of the segmented roads, improving the recognition precision in combination with the comprehensive perception of a driving route segmentation model in the convolutional neural network, thereby realizing the high-precision route planning.
Owner:TIANJIN UNIV
Three-phase transformer electromagnetic transient low-and-medium frequency modeling method and system
ActiveCN107958125AImprove calculation accuracySolve complexitySpecial data processing applicationsLow voltageMagnetic reluctance
The invention discloses a three-phase transformer electromagnetic transient low-and-medium frequency modeling method. The method comprises the steps of selecting iron core joints as magnetic circuit division points of a transformer model, and partitioning a transformer; building a magnetic circuit equivalent model according to magnetic conductive features of materials inside the transformer of allpartitioned areas and the spatial distribution of all parts of the transformer; conducting classifying according to physical properties represented by all magnetic resistance elements, establishing acircuit model according to relevant parameters and electromagnetic duality principles of the elements and conducting simplifying according to a topological connection relation; adopting a dynamic loss model according to loss characteristics of magnetic conductive materials of the transformer to simulate the loss of a transformer iron core; combining the circuit model and the dynamic loss model, wherein the combined model is used for simulating nonlinear excitation and loss features of the transformer iron core; calculating the parameters of the circuit part of the transformer, and adopting alinear transformer model for simulation; connecting the combined model for representing the transformer iron core transient characteristics to the low-voltage side of the linear transformer model; calculating the parameters of the transformer.
Owner:CHINA ELECTRIC POWER RES INST +1
Microbubble synergistic dynamic experiment system based on double frequency superimposed ultrasonic pulse in viscoelastic medium and microbubble synergistic dynamic experiment method based on double frequency superimposed ultrasonic pulse in viscoelastic medium
ActiveCN110243454AImprove efficiencyImprove securitySubsonic/sonic/ultrasonic wave measurementDesign optimisation/simulationDynamic methodCavitation
The invention discloses a microbubble synergistic dynamic experiment system based on a double frequency superimposed ultrasonic pulse in a viscoelastic medium and a microbubble synergistic dynamic experiment method based on the double frequency superimposed ultrasonic pulse in the viscoelastic medium. The experiment method comprises the following steps 1) according to an actual waveform of a focal region sound field measured by a hydrophone, setting KZK equation parameters and establishing a microbubble nonlinear excitation waveform; 2) constructing a HIFU synergistic model according to viscoelasticity of a biological tissue and vibration characteristics of the microbubble in compressible fluid; 3) establishing a microbubble synergistic dynamic method based on double frequency superimposition; 4) in combination with simulation results of steps above, determining a HIFU waveform phase, sound pressure and frequency parameters to perform a thermal ablation or tissue damage experiment. According to the system and the method provided by the invention, the dynamic characteristics of the microbubble in the biological tissue are used fully to design the sound wave waveform and the phase parameter, maximum vibration of the microbubble is triggered at a focal region, a cavitation effect is enhanced, and safety and efficiency of HIFU thermal ablation and tissue damage are improved.
Owner:XI AN JIAOTONG UNIV
Motor non-linear excitation control device based on DSP chip
InactiveCN1545203AGuaranteed safe operationEasy to adjustAdaptive controlGenerator control by field variationMicrocontrollerDigital signal processing
The invention is a DSP-based machine nonlinear excitation control device, and its character: it uses machine control special DSP chip as CPU and PLD as auxiliary processor, and consists of AC sampling circuit, CPU, pulse amplifying circuit, controlled silicon power circuit and switching quantity control circuit. It uses high-performance DSP chip to implement multiple generator excitation control laws of multiple generators relying mainly on nonlinear control and can largely enhance the speed and precision of excitation control, reduce control delay, making the whole system of excitation control have very good adjusting performance and reliability, enhancing network stability, assuring safety working of generator, reducing large-area power failure rate, and it is a new-generation generator excitation auto-control device with a huge market prospect.
Owner:中国石化集团天津石油化工公司 +1
Optical microimaging device and method based on line scanning temporal-spatial focusing
InactiveCN109799602ASuppresses signal crosstalkHas a deep penetration depthMicroscopesProcess studyHigh temporal resolution
An embodiment of the invention provides an optical microimaging device and method based on line scanning temporal-spatial focusing. The device comprises a laser transmitting module, a line scanning module, an optical microscopic module, a synchronous filtering module and a reconstruction module, the laser transmitting module generates nonlinear excitation pulse light, the line scanning module acquires angular dispersion and deflection angle of the excitation pulse light and enables the excitation pulse light to scan a sample, the optical microscopic module forms a focusing line focusing on twodimensions like space and time at the same time in the sample to excite the sample on the basis of nonlinear optical effect to generate a transmitting light signal; the synchronous filtering module detects the transmitting light signal of the sample and filters the transmitting light signal, and the reconstruction module performs two-dimension reconstruction according to the transmitting light signal detected by the synchronous filtering module to acquire a reconstruction image of the sample. The optical microimaging device can effectively inhibit signal crosstalk caused by stray light, has the advantages of wide field of view, high spatial resolution, high temporal resolution and high penetration depth and can provide rich information for biological dynamic process study and disease diagnosis basis.
Owner:TSINGHUA UNIV
Method and system for testing nonlinearity degree of closed-loop feedback circuit of fiber-optic gyroscope
ActiveCN109029412ARealize closed-loop testingImprove accuracySagnac effect gyrometersDigital signal processingFiber
The invention provides a method and a system for testing the nonlinearity degree of a closed-loop feedback circuit of a fiber-optic gyroscope. The method comprises the steps that a digital signal processing chip generates a modulation voltage signal, and the modulation voltage signal is output to a Y waveguide phase modulator through a digital-to-analog converter and a modulation wave driving circuit, wherein the modulation voltage signal is a superposed signal of a nonlinear excitation modulation wave signal and a fixed step wave signal; the Y waveguide phase modulator is used for convertingthe modulation voltage signal into a modulation phase signal to obtain a modulation phase difference; a photoelectric detector detects the modulation phase difference, and the modulation phase difference is output to the digital signal processing chip through a preamplifier and an analog-to-digital converter; the digital signal processing chip calculates and outputs a first demodulation value according to the modulation phase difference; and a determination module determines the nonlinear degree of a modulation coefficient of the closed-loop feedback circuit according to the first demodulationvalue. The closed-loop test of the fiber-optic gyroscope is realized, so that the accuracy of the nonlinearity test of the feedback circuit is improved.
Owner:HENGYANG ZHIGU TECH DEV CO LTD
Decoupling modeling method for dynamic response analysis of high-speed railway pantograph-catenary coupling system
ActiveCN110362786AReduce dimensionalityReduce sensitivitySustainable transportationComplex mathematical operationsContact networkEngineering
The invention discloses a decoupling modeling method for dynamic response analysis of a high-speed railway pantograph-catenary coupling system. The method comprises the steps of contact network modelestablishment, pantograph model establishment, pantograph-catenary system coupling space model establishment, pantograph-catenary system decoupling space model establishment, nonlinear excitation linearization processing, exponential matrix fine algorithm and the like. A non-coupling motion equation of the high-speed pantograph-catenary system is established, an exponential matrix fine algorithm is adopted to obtain accurate expression of an equation homogeneous term solution, a linearization method is adopted to obtain linearization expression of a non-homogeneous excitation term, and therefore rapid and accurate simulation of kinetic analysis of the high-speed pantograph-catenary system is achieved. By applying the method provided by the invention, the sensitivity of high-speed pantograph-catenary system model simulation to the simulation step length can be effectively reduced, the calculated amount is reduced, the simulation time consumption is shortened, and the method has certainpracticability.
Owner:SOUTHWEST JIAOTONG UNIV
Ultrahigh-resolution nonlinear fluorescence excitation microscopic system based on Bragg diffraction crystals
The invention discloses an ultrahigh-resolution nonlinear fluorescence excitation microscopic system based on Bragg diffraction crystals, and relates to the field of laser detection. The system is combined with a nonlinear optical technology and a stimulated emission depletion microtechnique, infrared lasers with long wave lengths are adopted as a multiphoton excitation light source, a continuous laser beam is adopted as a depletion light source, the excitation light source is used for exciting fluorescent molecules, stimulated emission depletion light quenches fluorescence on the periphery of an excitation light spot focus, and the nonlinear optical microscopic system can break through the light wave diffraction limit. The Bragg diffraction crystals are introduced, the repetition frequency of femtosecond lasers is reduced below 4 MHz, and the fluorescence quantum yield of the fluorescent molecules is obviously improved. Meanwhile, the continuous stimulated emission depletion light is modulated into synchronization pulse lasers with the repetition frequency equal to that of the femtosecond lasers by the Bragg diffraction crystals, and on the basis of simplifying the device, the energy of incident light is reduced, and photobleaching on samples is reduced.
Owner:TIANJIN UNIV
Low-complexity convolutional neural network based on symbol random calculation
PendingCN110555519AAvoid calculation errorsImprove throughputNeural architecturesPhysical realisationCalculation errorStochastic computing
The invention discloses a low-complexity convolutional neural network based on symbol random calculation. The system comprises a symbol random calculation module and an efficient convolution layer, apooling layer and a nonlinear excitation layer which are constructed based on the symbol random calculation module, the symbol random calculation module comprises a forward conversion module and a backward conversion module, the efficient convolution layer comprises a random processing unit and a random adder matrix, and the pooling layer is connected to the output end of the efficient convolutionlayer. According to the invention, a special sign bit is introduced; symbol random calculation is formed, the problem that the traditional random calculation can only represent positive numbers is solved; the calculation error caused by scaling coding is avoided, a novel parallel fast convolutional neural network architecture is provided based on the random calculation mode, the throughput rateof random convolution is increased while the hardware consumption is reduced, and the delay of random convolution calculation is reduced to a certain extent.
Owner:SOUTHEAST UNIV
Method and system for detecting looseness of bolt joints based on nonlinear excitation characteristics
The invention discloses a bolt joint part looseness detecting method and system based on a nonlinear shock excitation feature. The method comprises the following steps: carrying out simulated modal analysis on a three-dimensional model of a test piece, and determining the arrangement positions of a vibration exciter and a sensor of a local part of a bolt joint part; arranging the vibration exciterand the sensor according to the determined arrangement positions of the vibration exciter and the sensor, and determining a vibration excitement parameter of the vibrator exciter according to the simulated modal analysis result of the three-dimensional model; maintaining the vibration excitement parameter unchanged, carrying out preliminary experiment on the same kind of test pieces to obtain a corresponding relation between a bolt pretightening force and a high harmonic scaling factor, and generating a relation data base; and carrying out test on a test piece to be tested to obtain a high harmonic scaling factor, querying the relation data base, determining the bolt pretightening force of the test piece to be tested, and judging whether the bolt joint part of the test piece to be testedis loosen or not according to the bolt pretightening force of the test piece to be tested. The method has the advantages of wide applicability, flexibility and convenience in use, high sensitivity andthe like, implements nondestructive detection, and is suitable for actual production.
Owner:TSINGHUA UNIV
Extreme learning machine face dimension reduction method based on discriminant shared neighborhood preservation
PendingCN114596603AEliminates the process of bonding and fixingReduce processing stepsCharacter and pattern recognitionNeural architecturesLearning machineCharacteristic space
The invention discloses an extreme learning machine face dimension reduction method based on discriminant shared neighborhood preservation. The method comprises the following steps: S1, image preprocessing: performing scale normalization processing on a face image acquired by a face image acquisition module; s2, an input layer: inputting a face feature X subjected to scale normalization processing; s3, a hidden layer: selecting a nonlinear excitation function, randomly and nonlinearly mapping the single-sample face feature X to an N-dimensional feature space, and transforming to obtain a feature H (X); s4, outputting a layer: fixing a feature H (X); and S5, a sample data storing the face sample data t subjected to dimension reduction processing. The invention provides an SGRD-ELM algorithm. The SGRD-ELM not only considers the category information of the sample, but also pays attention to mining the shared neighbor information of any two sample points, and under the condition that the dimension of the sample data is reduced to 64 dimensions, the human face recognition rate is averagely improved by 10%-14% compared with that of an LLE method, and the human face recognition rate is averagely improved by 6%-8% compared with that of a US-ELM method.
Owner:GUANGDONG POLYTECHNIC NORMAL UNIV
CVT power frequency simulation model and simulation method for intermediate transformer under overexcitation working condition
PendingCN112668168AImprove simulation accuracyDesign optimisation/simulationPower oscillations reduction/preventionElectrical resistance and conductanceComputational physics
The invention discloses a CVT power frequency simulation model and simulation method for an intermediate transformer under an overexcitation condition. The model comprises a capacitance voltage division unit, a compensation reactor, the intermediate transformer and a ferromagnetic resonance suppression unit. According to the CVT power frequency simulation model and simulation method under the over-excitation working condition of the intermediate transformer, a CVT intermediate transformer model with physical significance is constructed according to the electromagnetic dual principle, and model parameters comprise primary side and secondary side winding resistors R's1 and Rs2, leakage reactance L's, nonlinear excitation reactance L'm1 and Lm2 of two excitation branches and parallel resistors R'm1 and Rm2. The model is provided with two excitation branches which are in one-to-one correspondence with the whole CVT structure, and accurate simulation of saturation difference of the intermediate transformer iron core under an over-excitation working condition can be realized.
Owner:ELECTRIC POWER RES INST OF GUANGDONG POWER GRID
Apparatus and methods for optical neural networks
ActiveCN109477938BNeural architecturesOptical bistable devicesComputational physicsOptical neural network
The present invention provides an optical neural network constructed based on photonic integrated circuits to perform neuromorphic computing. In optical neural networks, matrix multiplication is implemented using one or more optical interferometric units that can apply arbitrary weighted matrix multiplications to an array of input optical signals. Nonlinear excitation is achieved through optical nonlinear units, which can be based on nonlinear optical effects such as saturable absorption. These calculations are implemented optically, resulting in high computational speed with low power consumption in optical neural networks.
Owner:MASSACHUSETTS INST OF TECH
Underwater target sonar detection method based on CNN
ActiveCN112731410AEliminate side lobe effectsHigh precisionCharacter and pattern recognitionNeural architecturesSonarData set
The invention discloses an underwater target sonar detection method based on a CNN. The method specifically comprises the following steps of: S1, carrying out 360-degree sonar data collection on an underwater target through an active sonar technology to obtain original sonar data; S2, preprocessing the original sonar data to obtain a sonar image; S3, expanding the sonar image to obtain a sonar image data set, and dividing the sonar image data set into a training set and a test set; S4, training a CNN network model by using the training set; and S5, inputting the test set into the trained CNN model for testing to obtain a detection and recognition result. According to the method, a convolutional neural network with a single convolutional layer is adopted, a nonlinear excitation function Sigmoid is used during model training and is replaced with Softplus during actual testing, so that the signal intensity of the detection target is better displayed on the basis of simplified training.
Owner:SHANGHAI UNIV
Active damping device of solid rocket engine
PendingCN114856867AImprove stabilityImprove anti-disturbance abilitySustainable transportationRocket engine plantsCombustion chamberInsulation layer
The invention discloses an active damping device for a solid rocket engine, which comprises a test engine main body and an engine supporting structure, and the engine supporting structure supports the test engine main body; the main body of the test engine is a projectile body, the shell is of a porous sandwich layer structure and sequentially comprises an outer shell layer, a porous structure layer and an inner shell layer from outside to inside, and a heat insulation layer and a propellant are arranged in the inner shell layer; according to the engine supporting structure, one end of a sliding rail is connected with triangular leaning iron and installed on a base; one end of the thrust frame is connected with the triangular leaning iron, and the other end is connected with the front sealing head; the limiting stopper and the rear hanging bracket are connected with the sliding rail through the sliding block, one end of the spraying pipe of the shell is hung on the rear hanging bracket, and the limiting stopper is located between the thrust frame and the rear hanging bracket. Combustion chamber pressure and structural vibration caused by nonlinear excitation of an engine in a free trajectory can be weakened to a great extent, and the stability of the engine is enhanced.
Owner:HARBIN ENG UNIV
A CNN-based sonar detection method for underwater targets
ActiveCN112731410BEliminate side lobe effectsHigh precisionCharacter and pattern recognitionNeural architecturesData setTarget signal
Owner:SHANGHAI UNIV
Vibration testing device and method for thin-walled structural parts based on piezoelectric ceramic vibrator
ActiveCN103528782BEfficient collectionStable linear excitation signalSubsonic/sonic/ultrasonic wave measurementUsing wave/particle radiation meansModal testingLinear relationship
Owner:NORTHEASTERN UNIV LIAONING
A method and system for testing the nonlinearity of a fiber optic gyroscope closed-loop feedback loop
ActiveCN109029412BRealize closed-loop testingImprove accuracySagnac effect gyrometersDigital signal processingClosed loop feedback
Owner:HENGYANG ZHIGU TECH DEV CO LTD
Information generation method, device and apparatus based on fuzzy neural network
ActiveCN111353576ASolve the defect of inaccurate linear matchingAddress subjectivityWebsite content managementNeural architecturesPrincipal component analysisEngineering
The embodiment of the invention provides an information generation method, device and apparatus based on a fuzzy neural network, and the method comprises the steps: carrying out principal component analysis of an obtained dimension parameter, and determining a feature parameter; smoothing the characteristic parameters according to a nonlinear excitation function, and determining service parameterscorresponding to the characteristic parameters; processing the service parameters by using a fuzzy mapping principle to generate to-be-recommended information; and establishing a mapping relationshipbetween the to-be-recommended information and the feature parameters so as to generate recommendation information. The characteristic parameters are determined by using the principal component analysis method, and the fuzzy neural network is constructed by using the nonlinear excitation function, so that the service information suitable for the user is calculated and output according to the characteristic parameters, the neural network is constructed by using the fuzzy mapping principle, and the problem of inaccurate linear matching of a single user label for massive user data at present is solved. The purpose of reducing the labor cost can be achieved while the accuracy and efficiency of information recommendation are achieved.
Owner:SHANXI CHINA MOBILE COMM CORP +1
A method of identity recognition based on dual-channel convolutional neural network
ActiveCN109409297BAvoid Single Factor DeceptionImprove anti-interference abilityNeural architecturesMultiple biometrics useIdentity recognitionDimensionality reduction
The invention discloses an identity recognition method based on a dual-channel convolutional neural network, which includes training the neural network and identity recognition steps, using two time-synchronized images of a face image and a body posture image for comprehensive training and recognition, avoiding a single factor Deception has strong anti-interference ability and high recognition accuracy; the method of the present invention weights the feature data of two channels through a fully connected layer, and obtains image features through multiple convolutional layers and pooling layers Finally, the classification probability is obtained by the classifier, and the maximum probability is extracted to compare with the set threshold to determine the recognition result. After multiple convolutions to extract feature maps, nonlinear excitation and pooling dimensionality reduction processing, the dual-channel convolutional neural network control data is more flexible, and the abstraction ability and learning ability are stronger, thus having a better recognition effect.
Owner:咪付(广西)网络技术有限公司
Method for calculating DC (direct current) magnetic bias dynamic leakage inductance of transformer
Owner:NORTHEAST DIANLI UNIVERSITY
Microbubble synergistic dynamics experiment system and method based on dual-frequency superimposed ultrasonic pulses in viscoelastic media
ActiveCN110243454BSevere vibrationEfficient damageSubsonic/sonic/ultrasonic wave measurementDesign optimisation/simulationCavitationSound pressure
Owner:XI AN JIAOTONG UNIV
A method and system for modeling a three-phase transformer electromagnetic transient mid-low frequency model
ActiveCN107958125BImprove calculation accuracySolve the problem of heavy dependenceComputer aided designSpecial data processing applicationsTransformerHemt circuits
Owner:CHINA ELECTRIC POWER RES INST +1
A Point Layout Method of Angular Velocity Nonlinear Excitation Controller
InactiveCN104135018BThe layout problem involvesFully reflect the dynamic characteristicsPower oscillations reduction/preventionSpecial data processing applicationsWater turbineAngular velocity
Owner:SOUTHEAST UNIV +3
A Nonlinear Dynamic Calculation Method for Gear Pairs
ActiveCN108052760BImprove calculation accuracySimulate the realGeometric CADSpecial data processing applicationsGear wheelEngineering
Owner:CHANGAN UNIV
Damage threshold calculation method of laser cavity surface
PendingCN111353224ADesign optimisation/simulationCAD numerical modellingErbium lasersNonlinear excitation
The invention belongs to the field of semiconductor lasers. At present, the research on the influence of laser defects on the laser performance mainly focuses on the spectral characteristic analysis after the laser damage occurs; the change of the free electron density in the laser cavity surface material is not microscopically analyzed from the perspective of physics; the invention provides a method for calculating a damage threshold of a laser cavity surface. The incident laser irradiates the lower cavity film to generate photoionization, collision ionization and free electron attenuation; the damage threshold value of the laser cavity surface is analyzed and calculated by calculating the critical free electron density of the laser cavity surface, the influence rule of cavity surface material nonlinear excitation on free electrons is theoretically analyzed, and a theoretical model for calculating the cavity surface laser-induced damage threshold value is established.
Owner:TAIYUAN UNIV OF TECH
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