134 results about "Nonlinear parameters" patented technology

The invention relates to the technical field of injection molding process control, and discloses an injection molding parameter self-learning collaborative regulation and control system which is characterized in that multi-source parameters such as temperature and pressure are acquired in real time through a data acquisition module, and the multi-source parameters are mapped to a low-dimensional manifold space through a dynamic manifold construction module to decouple a nonlinear coupling relationship; the chaos synchronization control module suppresses external disturbance based on master-slave system design, and the distributed optimization module realizes multi-target real-time decision by adopting a split Bregman algorithm; the execution module converts the optimization instruction into a control signal and triggers closed-loop feedback; and the federated learning architecture realizes cross-device strategy migration by extracting continuous homology features of a manifold space and combining a Hausdorff distance and homeomorphic mapping, and drives a global model to update. According to the invention, the technical problems of difficult dynamic regulation and control of nonlinear parameters, insufficient real-time performance of multi-constraint optimization, low cross-scene repeated parameter adjustment efficiency and lack of self-adaptability of long-term process drift in the injection molding process are solved.

The invention discloses an unmanned aerial vehicle flight path planning method based on an improved star-graffiti algorithm, and belongs to the field of unmanned aerial vehicle flight path planning. The invention relates to a method for carrying out flight path planning on a single task executed by an unmanned aerial vehicle. Firstly, a starting point, a target point position and a threat area range are determined; establishing a route planning cost model based on path cost, angle cost, height cost, speed cost and threat cost; optimizing the established cost model, on the basis of a basic individual algorithm, updating the position of the population by adopting an updating formula with nonlinear parameters hybridized with the individual algorithm, and embedding an elite selection method to improve the optimizing capability; and when an iteration upper limit is reached, obtaining an optimal individual position, namely an optimal track, and realizing track planning. According to the invention, optimization of the algorithm is realized, the calculation result is more flexible and simpler, and premature convergence is avoided.

The invention relates to the technical field of aero-engines, and discloses a dry friction damper multi-target robust optimization method considering multi-source uncertainty, and the method specifically comprises the following steps: 1, quantifying the uncertainty parameters of a dry friction damper; step 2, performing hyper-Latin cube (LHS) sampling on value ranges of geometric parameters and contact parameters caused by abrasion to obtain parameter combination sampling capable of expressing global characteristics in a global sample space; 3, calculating a corresponding nonlinear dynamic response by using a multi-dimensional harmonic balance method (MHBM) by using the nonlinear parameters obtained by sampling; by means of the mode of synchronously optimizing key design parameters of the friction-damping system, the optimal robustness design of the friction-damping system is allowed to be carried out under parameter uncertainty with the purpose of vibration reduction, the damping effect of the dry friction damper is improved, the Pareto optimal solution of the neural network is solved through the genetic algorithm, and the optimal stability of the friction-damping system is improved. Therefore, the multi-objective optimization is realized and the calculation efficiency is improved.

The invention provides an ultrasonic nonlinear static parameter monitoring method for creep damage of a high-temperature alloy component, and particularly relates to the technical field of material monitoring. The method comprises the following steps: S1, arranging an ultrasonic probe; s2, determining the emission frequency of the excitation end; s3, respectively calculating an incident angle and an emergent angle of the signal; s4, exciting fundamental frequency ultrasonic waves; s5, receiving the signal and uploading the collected signal to a cloud processing system; s6, carrying out fast Fourier transform and calculating a nonlinear parameter of a static component; s7, establishing a linear relation with creep time, and constructing a creep damage linear quantitative model; s8, calculating a static component nonlinear parameter of the healthy sample; and S9, completing quantitative analysis of the damage by using nonlinear parameters. The method solves the problems that a traditional nonlinear ultrasonic method depends on second harmonic nonlinear parameters, phase velocity matching conditions in the middle and later periods are seriously damaged, response shows a nonlinear trend, unique creep time cannot be determined according to the parameters, and then the unique damage state cannot be determined.

The invention relates to the technical field of wireless communication, and discloses a digital pre-distortion method for improving the linearity of a power amplifier in a phased array system, which comprises the following steps of: 1, acquiring a nonlinear parameter of the power amplifier under a dynamic load in real time, the nonlinear parameters comprise an input signal amplitude-phase characteristic, a temperature parameter and a quantum tunneling current parameter; 2, generating a pre-distortion compensation signal based on the nonlinear parameter, wherein the pre-distortion compensation signal comprises a quantum phase compensation item and a dynamic phase change compensation item; and step 3, superposing the pre-distortion compensation signal to an original input signal to generate a pre-distortion modulation signal. The linearity of the power amplifier is improved by introducing the quantum phase compensation item and the dynamic phase change compensation item, nonlinear parameters are accurately obtained in real time in a dynamic load environment, and the precision of pre-distortion compensation is improved.

The invention relates to the technical field of radio-frequency signal processing, and discloses a 5G radio-frequency signal amplification method and system, and the method comprises the steps: decomposing an obtained radio-frequency signal into a high-frequency sub-band and a low-frequency sub-band through a multilayer wavelet packet, judging whether the radio-frequency signal is sparse in a wavelet packet domain, and carrying out the sparse reconstruction of an LI norm minimization problem if the radio-frequency signal is sparse; obtaining feature data of each sub-band, extracting a nonlinear transfer function of each sub-band through a CNN-GRU network, and carrying out transfer learning pre-training and dynamic adaptation updating; on the basis of dynamic adaptation update ending, layered memory polynomial calculation and layered model joint output construction, layered model parameter optimization is converted into a least square problem to obtain an error compensation function, and resource allocation is dynamically adjusted according to the peak-to-average power ratio of an input signal; and based on power amplifier state data, holographic sensing is performed on nonlinear parameters of the device through a fusion model, and dynamic changes of the device are compensated through multi-stage calibration and calibration delay is controlled.

The invention relates to the technical field of image signal processing, and discloses an agent-free ISP hyper-parameter high-speed optimization method and system, and the method comprises the following steps: collecting RAW data through a sensor, carrying out the black level correction, and initializing the ISP register parameter mapping; a multi-dimensional state vector is constructed by combining the coded image and the parameters, and the master and slave agents generate discrete adjustment amounts in parallel; after a register is updated through nonlinear quantization, a composite reward is calculated based on target detection and image quality, and data is stored and network parameters are updated through a priority experience pool; the system comprises a sensor module, an ISP hardware processing unit, a master-slave agent decision module, a reward calculation module, a register mapping module and an experience playback module. According to the method, hardware-in-the-loop and deep reinforcement learning are combined, and the problems of proxy model distortion, response lag, high data dependence and parameter mutation are solved through master-slave agent parallel decision, a self-supervision reward mechanism and nonlinear parameter mapping.

The invention discloses a finite element simulation method for motion of a magnetically-driven spiral micro-robot in a fluid environment, and belongs to the technical field of finite element simulation. According to the method, a micro-robot model containing a streamline head and a spiral empennage and a fluid environment are constructed through COMSOL software, a peristaltic flow module and a multi-body dynamics module are integrated through the fluid-solid coupling technology, and a fluid-solid coupling transient motion equation is established. The motion characteristics of the micro-robot driven by a rotating magnetic field are accurately simulated by setting material nonlinear parameters, dynamic self-adaptive grid division and a non-uniform step size solving strategy. A rigid domain motion equation and an open boundary condition are innovatively introduced, speed and acceleration probes are combined for real-time monitoring, and the flow field vortex effect caused by spiral propulsion is captured. According to the method, the simulation error is controlled within 5%, the motion trail prediction precision is remarkably improved, a reliable simulation platform is provided for micro-robot structure optimization and magnetic control strategy design, the experiment cost is reduced, and the research and development period is shortened.

The invention belongs to the technical field of crossing of high polymer materials and artificial intelligence, and discloses a method for optimizing the proportion of a nano-composite flame-retardant master batch in engineering plastic based on machine learning. The method is used for solving the problems that a traditional experience trial and error method is low in efficiency in multi-target performance collaborative optimization, high-dimensional nonlinear parameter space search is difficult, and microscopic coupling effect modeling is missing. According to the method, a multi-dimensional input feature set containing material composition and process parameters is constructed, six key performance indexes are combined to form training data, a mixed model formed by cascading a multi-layer perceptron and Gaussian process regression is trained, an improved non-dominated sorting genetic algorithm (NSGA-II) is adopted for multi-target global optimization, and an optimal ratio meeting preset constraints is obtained. The method is an industrial internet technology system service, and solves the technical problem that multi-target performance is difficult to collaboratively optimize due to the fact that a traditional experience trial-and-error method cannot perform modeling and searching on a high-dimensional nonlinear parameter space of a nano-composite flame-retardant system.

The invention belongs to the technical field of ultrasonic imaging, and particularly relates to an ultrasonic nonlinear parameter imaging method and system, a medium and a program product. The method comprises the following steps: calculating a fundamental signal and a harmonic signal based on an ultrasonic echo RF signal; extracting the amplitude of the fundamental wave signal and the amplitude of the harmonic wave signal, and calculating to obtain a fundamental wave amplitude ratio and a harmonic wave amplitude ratio; calculating an initial value of a nonlinear coefficient according to a ratio of the fundamental wave amplitude ratio to the harmonic wave amplitude ratio, and estimating a value range of the nonlinear coefficient by using a Newton iteration method; and generating an ultrasonic image based on the value range of the nonlinear coefficient. In the ultrasonic non-linear parameter imaging process, a method for solving a non-linear coefficient by adopting a Newton iteration method is further disclosed, so that the dynamic range of the estimated non-linear coefficient value is expanded, the distinguishing between normal tissues and focus tissues in an obtained ultrasonic image is more obvious, and the sensitivity is higher.

The invention discloses a non-linear ultrasound-based soft package battery internal tiny foreign matter imaging method, which belongs to the field of power battery manufacturing, and comprises the following steps: exciting and receiving non-linear ultrasound on the surface of a soft package battery by using a non-linear ultrasound measurement system, and extracting a non-linear ultrasound time domain signal carrying foreign matter information; performing C scanning on the soft package battery by adopting a three-degree-of-freedom motion platform, and obtaining acoustic nonlinear parameters and spatial distribution of the acoustic nonlinear parameters based on the position of a focused ultrasonic transducer, the nonlinear ultrasonic time domain signal and the frequency spectrum; performing normalization processing on the acoustic nonlinear parameters, and constructing a function relationship between the normalized acoustic nonlinear parameters and different foreign matters; and inverting the size and the position of the foreign matter based on the function relationship between the normalized acoustic nonlinear parameter and different foreign matters and the spatial distribution of the acoustic nonlinear parameter.

Aspects relate to signaling relating to a non-linearity model for power amplifier circuitry of a transmitting device. The power amplifier circuitry may apply digital pre-distortion (DPD) to a signal prior to amplification and transmission of the signal. A receiving device may apply digital post-distortion (DPoD) to a signal received from the transmitting device where the DPoD is based on the non-linearity model. The transmitting device may send to the receiving device non-linearity parameters for the non-linearity model.

The invention relates to a direct current furnace machine-furnace coordination system dynamic modeling method suitable for a wet condition. Based on the law of mass conservation and energy conservation, a lumped parameter method is adopted to construct a dynamic model comprising a coal pulverizing system, a coal economizer-water wall system, a water storage tank system, a superheater system and a steam turbine system; identifying parameters are optimized step by step by only utilizing unit variable load dynamic operation data and combining with the mechanism constraint that the heat absorption capacity of a working medium is monotonically increased along with the coal quantity as fired: static parameters are determined through dynamic data regression, nonlinear parameters are optimized based on a preset water-cooled wall outlet flow and dryness function structure, and the heat absorption capacity of the working medium is calculated. And finally, identifying dynamic parameters step by step by adopting an immune genetic algorithm. The dynamic characteristics and the physical consistency of the established model are verified through open-loop simulation, and the technical problems that dynamic description of the water level of the water storage tank is missing and the modeling precision is low under the wet working condition are solved.

The invention discloses a sine frequency modulation harmonic error compensation method based on Bessel function modulation characteristics, and relates to the technical field of sine frequency modulation nonlinear parameter compensation and high-precision measurement of target absolute distance based on multi-wavelength interference. The problem that the constant phase demodulation precision is insufficient due to the fact that carrier harmonic waves, accompanying amplitude modulation and modulation depth errors cannot be effectively suppressed due to laser modulation nonlinearity in existing sine frequency modulation distance measurement is solved. According to the method, after sine frequency modulation interference signals are collected, high-pass filtering is carried out to remove low-frequency components, Hilbert transform is carried out to remove envelope suppression associated amplitude modulation, window function frequency mixing is carried out to extract modulation depth, a matched carrier containing second harmonics is constructed, and frequency modulation harmonic parameter optimization is achieved through baseband amplitude maximization. And finally, carrying out orthogonal demodulation on the compensated interference signal to obtain a high-precision constant phase. The method is suitable for high-precision multi-wavelength interference ranging, precision displacement measurement and optical metering systems.

The invention provides a gap nonlinear control surface flutter wind tunnel test system and method based on steering engine excitation. The system comprises a wind tunnel test section, a test object and a parameter-adjustable excitation mechanism outside a wind tunnel field, wherein the parameter-adjustable excitation mechanism is composed of a transverse clamping mechanism, a longitudinal supporting mechanism, an excitation system and an angle sensor. The excitation system comprises a steering engine, a steering engine rocker arm and a connecting rod, one end of a spring rod is fixed to the longitudinal supporting mechanism, and the other end is in clearance fit with the connecting rod. By adjusting the effective length of the spring rod, the fit clearance and the excitation of the steering engine, the clearance nonlinear rigidity applied to the test control surface can be changed. In a wind tunnel test, an angle sensor is used for collecting rudder shaft rotation angular displacement response in real time, excitation-response characteristic testing before and after flutter occurs is achieved, and the influence rule of gap nonlinear parameters on rudder surface dynamic characteristics is effectively studied. The test principle is simple, and a new way is provided for excitation-response characteristic measurement of the full-motion control surface under different gap nonlinear rigidities.

The invention discloses a composite material storage life prediction method based on variable transformation and a genetic algorithm, and relates to the technical field of composite material performance evaluation and life prediction, and the method comprises the steps: obtaining performance degradation data at different temperatures through an accelerated aging test, and building a semi-empirical performance degradation model; specific variable transformation is introduced, a nonlinear optimization problem is converted into a linear regression problem, partial model parameters are rapidly solved by adopting a least square method, and meanwhile, key nonlinear parameters are globally optimized by using a genetic algorithm, so that the defect that a traditional method is easy to fall into local optimum is overcome. And establishing a temperature-service life relationship by combining with an archenius model, and realizing storage life prediction at normal temperature. The method also integrates sensitivity analysis and uncertainty quantification functions, and provides reliability evaluation for a prediction result. The method fully considers the influence of the environment temperature, meets the requirement of efficient prediction, and improves the precision and stability of life prediction.

The invention discloses a test method and device for measuring nonlinearity of a phase modulator, and belongs to the technical field of measurement, the device comprises a laser source, a polarization controller, a beam splitter, the phase modulator, a coupler, a photoelectric detector, a microwave source I, an acousto-optic frequency shifter, a microwave amplitude phase detection module and a microwave source II; the laser source is used for outputting a fixed-frequency optical signal to the polarization controller; the polarization controller is used for compensating the polarization state of the optical signal; the beam splitter is used for equally dividing an optical signal into two paths, the first path of optical signal is transmitted to the phase modulator, and the second path of optical signal is transmitted to the acousto-optic frequency shifter; by means of the mode, the problem that the phase modulator directly enters the photoelectric detector, photoelectric conversion cannot be conducted, and nonlinear parameters cannot be detected is solved.

The invention discloses a battery off-line and on-line hybrid modeling method and device, a storage medium and a product. The method comprises the following steps: constructing a state dependent model of a battery; determining a state vector according to the state parameter of the battery; taking the state vector as input, and determining a function type coefficient of the state dependent model; converting the state-dependent model into a nonlinear least square model; according to the obtained battery measurement data, performing offline optimization on parameters of the nonlinear least square model by adopting an optimization algorithm to obtain all parameters, and further obtaining a battery offline model; and keeping the non-linear parameters of the battery offline model unchanged, and updating the linear parameters in the battery offline model online according to the real-time measurement data of the battery so as to obtain a real-time updated state dependent model. According to the method, high-precision modeling of the lithium ion battery is realized on the premise of ensuring real-time performance.

The invention discloses a nano-scale displacement real-time compensation measurement method and system based on double-frequency laser interference, and belongs to the technical field of precision measurement. In order to solve the problems that three error sources of environmental drift, periodic nonlinear error and dynamic vibration are mutually coupled and have high real-time requirements in dual-frequency laser interference measurement, a multi-source error unified state space model including measured displacement, an air refractive index parameter, a nonlinear error parameter and a vibration disturbance quantity is constructed. A high-dimensional state vector is divided into a displacement-refractive index group and a nonlinear parameter group by adopting an extended Kalman filter of a grouping updating strategy, the displacement-refractive index group and the nonlinear parameter group are alternately updated in an assembly line parallel mode, nonlinear parameters are identified in real time in combination with an online recursive least square algorithm, and the state of the filter is corrected through a state coupling injection mechanism. Real-time compensation with the end-to-end delay smaller than 80 microseconds is achieved, the displacement measurement residual error is controlled within + / -0.3 nm under the composite disturbance condition, and the method is suitable for precise assembly of intelligent glasses optical assemblies.

The invention provides an underwater robot adaptive control method and device, electronic equipment and a medium, and the method comprises the steps: determining a first posture prediction model of an underwater robot according to a dynamic model of the underwater robot; identifying a to-be-identified parameter of the first attitude prediction model according to the motion data; determining a first attitude of the underwater robot according to the first attitude prediction model, the identification parameters and the motion data; predicting a second attitude of the underwater robot at a second moment according to the first attitude and a control algorithm to obtain a prediction result; determining a control algorithm of the underwater robot according to the first attitude and nonlinear parameters of the underwater robot; according to the control algorithm, a control instruction for the underwater robot is determined, and self-adaptive control over the underwater robot is completed according to the control instruction. The method has the beneficial effect that the accurate adaptive control of the underwater unmanned aerial vehicle is realized.

The invention discloses a phase-control multi-channel nonlinear ultrasonic nondestructive testing system and method based on phase reversal excitation, and the method comprises the steps: generating multi-channel phase reversal waveform data and a control instruction by an upper computer, carrying out the nonlinear parameter extraction of a received digital signal, and calculating a nondestructive testing result; the phase-control high-energy fundamental frequency ultrasonic excitation module suppresses a fundamental frequency signal for the electric signal with the phase reversal waveform, enhances the harmonic amplitude, and performs delay excitation to realize fixed-point focusing; the transmitting transducer array and the receiving transducer array convert the electric signal and the acoustic signal; the multi-path double-band-pass filter is used for carrying out fundamental wave suppression, harmonic wave enhancement and clutter filtering to enhance a nonlinear effect and improve a signal-to-noise ratio; and the phase-controlled ultrasonic acquisition module is used for filtering, amplifying and sampling the multi-channel feedback electric signal and converting the multi-channel feedback electric signal into a digital signal. The method has the multi-channel nonlinear ultrasonic evaluation capability, can realize multi-channel phase reversal waveform excitation, has the ultrasonic fixed-point focusing capability, and remarkably improves the nonlinear effect detection result, so that the detection result is more accurate.

This model parameter estimation device comprises a state quantity calculator to calculate state quantities indicating a state of a target system with respect to a measured value of an input on the basis of a state equation obtained by assigning values to nonlinear parameters for a model that represents the target system using the nonlinear parameters and linear parameters, and time-series data of the input and an output of the target system, a linear parameter estimator to estimate the linear parameters that minimize an error between the measured value of the output and an estimated value of the output calculated on the basis of the model, the state quantities, and the measured value of the input, and a nonlinear parameter updater to repeatedly update the values of the nonlinear parameters so as to make the minimized error to be small until a convergence condition is satisfied.

The present invention discloses a method and device for measuring the nonlinearity of an electro-optical modulator, belonging to the technical field of photoelectric device measurement, and includes the following steps: inputting an optical signal output by a laser source into an electro-optical modulator to be measured; the optical signal passes through an electro-optical modulator to be measured, and outputs a modulated optical signal; the modulated optical signal enters a standard photodetector operating in a linear region, and a large-signal response item of the electro-optical modulator to be measured is obtained at different input electrical signal powers; an electrical signal is output to the electrical signal output end of the electro-optical modulator to be measured via a small-signal disturbance source, and a small-signal response item of the electro-optical modulator to be measured is obtained at different input electrical signal powers. By combining the large-signal response item and the small-signal response item, the complete nonlinear parameters of the electro-optical modulator to be measured at the input electrical signal power are obtained; and further, the complete nonlinear parameters of the electro-optical modulator to be measured at different frequencies are obtained. The present invention can achieve high-precision measurement of the nonlinearity of electro-optical modulators.

This invention belongs to the field of ultrasound imaging technology, specifically relating to an ultrasound nonlinear parameter imaging method, system, medium, and program product. The method includes: calculating a fundamental wave signal and harmonic signals based on ultrasound echo RF signals; extracting the amplitudes of the fundamental wave signal and the harmonic signals, and calculating the fundamental wave amplitude ratio and harmonic amplitude ratio; calculating an initial value of the nonlinear coefficient based on the ratio between the fundamental wave amplitude ratio and the harmonic amplitude ratio, and estimating the range of values ​​for the nonlinear coefficient using Newton's iteration method; and generating an ultrasound image based on the range of values ​​for the nonlinear coefficient. In the process of ultrasound nonlinear parameter imaging, a method for solving the nonlinear coefficient using Newton's iteration method is further disclosed, thereby expanding the dynamic range of the estimated nonlinear coefficient values, resulting in a clearer distinction between normal tissue and lesion tissue in the obtained ultrasound image, and higher sensitivity.

The invention relates to a method for influence of dislocation dipole defects in an aluminum matrix on acoustic parameters, belongs to the technical field of discrete solution, and provides a novel molecular dynamics simulation method for researching ultrasonic sound velocity, sound attenuation and acoustic nonlinear parameter change on the basis of two dislocation dipole structures. The method specifically comprises the following steps: controlling the type and the number of dislocation dipoles in an aluminum matrix, carrying out atomic scale acoustic simulation on dislocation dipole models of different types and numbers by adopting a phase inversion technology, extracting sound velocity by adopting a cross correlation method, extracting sound attenuation by adopting a Hilbert transformation method and extracting acoustic nonlinear parameters by adopting an FFT method aiming at four-phase signals; and precise extraction of acoustic parameters is realized. And determining the contribution of the dislocation defect to the acoustic parameters based on the relationship fitting of the three acoustic parameters and the dislocation defect, thereby realizing the prediction from the acoustic parameters to defect characteristics.

The application relates to the technical field of wireless communication, and discloses a digital predistortion method for improving the linearity of a power amplifier in a phased array system, which comprises the following steps: step one, acquiring nonlinear parameters of a power amplifier under dynamic load in real time, wherein the nonlinear parameters comprise input signal amplitude and phase characteristics, temperature parameters and quantum tunneling current parameters; step two, generating a predistortion compensation signal based on the nonlinear parameters, wherein the predistortion compensation signal comprises a quantum phase compensation term and a dynamic phase change compensation term; and step three, superimposing the predistortion compensation signal to an original input signal to generate a predistortion modulation signal. The application improves the linearity of the power amplifier by introducing the quantum phase compensation term and the dynamic phase change compensation term, and improves the accuracy of predistortion compensation by accurately acquiring the nonlinear parameters in real time under the dynamic load environment.

The invention provides a semi-parameter clustering method for screening scrapped lithium ion batteries in electric vehicles, and relates to the technical field of roadbed stability evaluation in seasonal frozen soil regions. Linear parameters, including voltage change data, internal resistance change data and nonlinear parameters, of the batteries in charge and discharge cycles are collected; comprising a discharge curve and temperature change data, and dominant trend and recessive complex characteristics of battery performance are comprehensively obtained; secondly, regression fitting is adopted for linear parameters to extract degradation trend feature data, semi-parameter modeling is adopted for nonlinear parameters to extract complex feature data, and the degradation trend feature data and the complex feature data are combined to form comprehensive feature data; and finally, based on the comprehensive feature data, establishing a clustering model cooperatively by using K-Means + + and DBSCAN algorithms, and accurately classifying the batteries into normal batteries, degraded batteries and scrapped batteries by processing the problems of non-uniform data distribution, fuzzy category boundary and the like.

The application discloses a bearing stress state measurement method based on a resonance attenuation method and related devices, and the bearing-main shaft system is loaded in the mode of electromagnetic loading. The resonance attenuation method in the nonlinear parameter identification method is used to obtain an attenuation response curve, and the instantaneous frequency and envelope amplitude are obtained based on a transient time-frequency signal analysis method, and then the main curve is identified from the measured bearing-main shaft system. A quasi-static model of the bearing is established to obtain the mapping relationship between the bearing stress state and the nonlinear non-time-varying stiffness, and the external loading state of the bearing is effectively and accurately detected through multiple tests on the nonlinear stiffness of the bearing system in the actual operation process. The application is suitable for multiple types of assembled angular contact ball bearings and is suitable for accurate measurement of the bearing stress state.

The present invention discloses a method for identifying nonlinear parameters of structural clearances. First, a mathematical model of the structural clearance nonlinear system is established; then, the frequency response function of the system under sinusoidal sweep excitation is obtained through the input-output response of the system; in the frequency response function, a pair of symmetric displacement points exist at any displacement response amplitude to define the same displacement frequency response function. By defining the real and imaginary parts of the displacement frequency response function through the symmetric displacement FRF points at each given displacement response amplitude, the natural frequency of the system related to the displacement response amplitude can be obtained; then, the expression of the nonlinear equivalent stiffness of the system is extracted through the simulation analysis of the model, and the equivalent stiffness curve of the system is further obtained through the model simulation data; finally, based on the particle swarm algorithm, the clearance characteristic parameters are obtained by curve fitting according to the equivalent stiffness expression obtained by integration and the equivalent stiffness curve obtained by model simulation; the present invention can identify the clearance nonlinear parameters more quickly and accurately globally.

The method for monitoring the resonant capacitor state of the medium-voltage direct-current LLC resonant converter comprises the following steps: closing the switch tube S 11 ~S 41 of the full-bridge at the initial moment when the LLC resonant converter is stopped, then turning on the switch tube S 31 and S 41 after the closing process lasts for 500 ns, forming a discharge loop of a resonant cavity independent of the latter stage, then collecting the time sequence data of the resonant current in the resonant cavity, and estimating the resonant capacitor by using a nonlinear parameter identification algorithm, wherein the estimation is sequentially performed by encoding, initializing the population, calculating the individual fitness, selecting the cross variation evolution, and iterative optimization, finally searching for the optimal resonant current estimation value, and calculating the resonant capacitor estimation value based on the corresponding resonant frequency and resonant inductance. The present application estimates the resonant capacitor value based on the discharge curve of the limited sampling data, has low cost and high reliability, and the present application estimates the parameters by using the nonlinear parameter identification algorithm, and has high estimation accuracy.