31 results about "Nonlinear excitation" patented technology

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.

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.

The invention discloses a CNN-based sonar detection method for an underwater target, which specifically includes the following steps: S1: collecting 360° sonar data of the underwater target through active sonar technology to obtain original sonar data; S2: analyzing the original sonar Preprocessing the 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: using the training set to CNN The network model is trained; S5: Input the test set into the trained CNN model for testing to obtain detection and recognition results. The present invention adopts a convolutional neural network with a single-layer convolution layer, uses a non-linear excitation function Sigmoid when training the model, and replaces it with Softplus when actually testing, and better displays the signal strength of the detection target on the basis of simplified training.

The invention belongs to the technical field of vibration test, in particular to a thin-walled structure part vibration test device and a method based on a piezoelectric ceramic vibration exciter. The device comprises a signal generator, a piezoelectric ceramic drive power supply, a piezoelectric ceramic vibration exciter, a feedback attenuator, a laser vibration meter, a data acquisition analyzer and an upper computer. The method comprises the steps of performing modality test on a thin-walled structure part, determining a linear relationship between excitation voltage and critical excitation frequency of the signal generator and calibrating an excitation force of the piezoelectric ceramic vibration exciter based on a cantilever theory. According to the device and the method, an excitation signal can be effectively acquired; the magnitude of the excitation force when the piezoelectric ceramic vibration exciter excites the structure part is defined; the stable designated excitation force and the linear excitation signal of the excitation frequency can be generated; influencing factors of non-linear piezoelectric ceramic excitation are effectively eliminated; the piezoelectric ceramic vibration exciter is adopted to realize high-frequency vibration excitation; additional mass is low; and the device is convenient to use.

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.

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.

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.

The present invention discloses a dual -frequency superposition micro -foam -efficient dynamic experimental system and method in a dual -frequency superposition. The experimental method includes: 1) The actual waveform of the coke area measured according to the water hearing device, set the KZK equation parameterNon -linear incentive waveforms; 2) Construct HIFU efficiency models according to the vibration characteristics of the viscosity and micro -bubbles in the biological tissue and micro bubbles in compressed fluids;The simulation results of the steps determine the HIFU waveform phase, sound pressure, and frequency parameters for thermal ablation or tissue damage experiments.The present invention makes full use of the dynamic characteristics of micro -bubbles in biological tissues, designing sound wave -shaped and phase parameters, causing the maximum vibration of micro -bubbles in the coke area, enhancing the effect of emptiness, and improving the safety and efficiency of HIFU thermal melt and tissue damage.Essence

The invention discloses a method for modeling a three-phase transformer electromagnetic transient medium-low frequency model: select the iron core joint as the magnetic circuit subpoint of the transformer model, and divide the transformer into partitions; According to the spatial distribution of each component, establish the equivalent model of the magnetic circuit; classify according to the physical properties represented by each magnetoresistive element, build a circuit model according to the relevant parameters of the element and the principle of electromagnetic duality, and simplify it according to the topological connection relationship; according to the transformer The loss characteristics of the magnetic material, using the dynamic loss model to simulate the transformer core loss; combining the circuit model and the dynamic loss model, the obtained combination model is used to simulate the nonlinear excitation and loss characteristics of the transformer core; calculate some parameters of the transformer circuit, and The linear transformer model is used for simulation; the combined model representing the transient characteristics of the transformer core is connected to the low-voltage side of the linear transformer model; the parameters of the transformer are calculated.

The invention provides a distribution method for angular speed non-linear excitation controllers. An electric power system which the distribution method is used for comprises a generator set, loads and an electric power network, the generator set further comprises generators, an excitation system, a water turbine and a speed regulating system of the water turbine, linearization equations of the generator set, the loads and the electric power network are respectively built, then a linearization equation of the whole system is built, the damping ratio is calculated through a state matrix of the linearization equation of the whole system, and the optimum distribution positions of the angular speed non-linear excitation controllers are determined. The control effect of the angular speed non-linear excitation controllers with the determined optimum distribution positions is brought into full play, the capacity for suppressing oscillation of the system is improved, and the distribution method for the angular speed non-linear excitation controllers has high practical value at the level of electric power system planning.

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.