6 results about "Statistical energy analysis" patented technology

The invention discloses an FEM-SEA hybrid calculation method and device for full-frequency-domain NVH simulation analysis and a storage medium, and belongs to the field of computer aided design. The method comprises the following steps: calculating the modal density n (f) of a to-be-analyzed structure in a target frequency band; the frequency domain type (low frequency, intermediate frequency or high frequency) is automatically judged based on the value of a modal density criterion n (f) delta f; and according to a judgment result, a finite element method module, a statistical energy analysis method module or an FEM-SEA hybrid analysis module is automatically selected and called for simulation calculation. Wherein the FEM-SEA hybrid analysis is based on the direct mixing field reciprocity theorem, and accurate coupling between the deterministic subsystem and the statistical subsystem is realized by constructing an overall dynamic stiffness matrix Dtot, calculating an energy conversion coefficient and solving an energy balance equation. According to the method, full-frequency-domain automatic analysis of NVH simulation from low frequency to high frequency is achieved, dependence of method selection on artificial experience is avoided, and the precision and efficiency of medium-frequency band analysis are remarkably improved.

The application relates to a method and system for defining an effective analysis frequency band of an engineering structure, important parameters of statistical energy analysis of a target system are selected and ranges are defined, including a modal number, a modal overlap factor, a normalized attenuation factor and coupling strength; dimension analysis is carried out in combination with vibration characteristics and boundary conditions of the target system, dimensionless parameters corresponding to the important parameters are obtained, including a dimensionless wave number, a shape parameter, a damping loss factor and a Poisson ratio, according to a corresponding relationship between the dimensionless parameters and the important parameters, an effective diagram of statistical energy analysis of each subsystem is constructed to describe the distribution of the important parameters in the dimensionless parameter space; the effective diagram of statistical energy analysis is analyzed to obtain a dimensionless wave number value range of each subsystem, and then the effective frequency band of the target system is obtained in combination with a coupling relationship. The application has the advantages of rapidness, directness, accuracy and the like, and is helpful to improving the prediction accuracy of high-frequency dynamic response of an engineering structure.

The invention relates to the technical field of tire structure optimization, in particular to an automobile tire NVH (Noise Vibration and Harshness) performance structure collaborative optimization method and a tire. Performing feature extraction on the data set to obtain a feature parameter matrix representing a transmission relation between structural vibration and noise; inputting the matrix into a coupling model constructed by finite element analysis, statistical energy analysis and neural network prediction, and outputting a prediction result set; processing the result set by adopting a multi-objective optimization algorithm, synchronously adjusting a plurality of design variables such as tread rubber layer thickness distribution, a support rubber stiffness curve, a cap ply winding track and carcass damping distribution, and generating an optimal parameter combination meeting multiple performance constraints; and performing virtual verification on the parameter combination through a digital twin platform, and inputting the verified parameters into an intelligent manufacturing system to complete tire forming. The technical problems of large noise and strong vibration caused by lack of collaborative optimization of tire structure design and NVH (Noise Vibration and Harshness) performance are solved.

The invention belongs to the technical field of motor noise prediction, and particularly provides a permanent magnet synchronous motor statistical energy analysis and noise prediction method based on stator orthotropy. The method comprises the following steps: carrying out subsystem division on a motor structure, considering orthotropic characteristics of a stator and a winding, establishing an anisotropic cylindrical shell model, and deriving an analytical expression of a coupling loss factor between subsystems based on a first-order shear deformation theory; taking the electromagnetic force as input power, and constructing a statistical energy analysis model in combination with the internal loss factor; the average vibration energy of each subsystem is solved and obtained, the radiation sound power and the sound pressure level are calculated by combining a sound radiation efficiency model, and rapid and accurate prediction of the medium-high frequency vibration noise of the motor under the working conditions of the constant rotating speed and the variable speed is achieved. According to the method, effective estimation of the high-frequency noise of the motor can be realized in a design stage, and the problems that a traditional numerical method is large in calculation amount and an analytical method is not suitable for high-frequency statistical characteristics are solved.

The present disclosure provides an aircraft acoustic structure parameter simulation design method, electronic equipment and medium, the method comprises: obtaining the independent variable parameters of the simulation design of the aircraft acoustic structure, the independent variable parameters include the wallboard structure parameters of the aircraft wallboard and the acoustic parameters of the sound-absorbing material inside the aircraft interior panel; the independent variable parameters are loaded as input conditions to the statistical energy analysis (SEA) model of the simulation software; a plurality of numerical simulation operations are carried out through the SEA model to obtain simulation results of sound quality parameters corresponding to different independent variable parameters; based on a preset sound quality target screening strategy, the simulation results are screened to obtain target independent variable parameters that meet the sound quality target requirements. The present disclosure upgrades the acoustic evaluation dimension, optimizes the wallboard structure parameters and the sound-absorbing material parameters jointly, thereby realizing cabin noise control and improving noise subjective comfort.

The application discloses a ship sonar self-noise prediction method and system based on statistical energy analysis, and the method comprises the following steps: constructing a sonar self-noise statistical energy analysis prediction model according to ship drawing materials, constructing an external auxiliary acoustic cavity by locally refining a sonar array and a load area; determining the vibration acceleration level load of the connecting position, the mechanical noise source sound source level load and the like based on the external auxiliary acoustic cavity, and simultaneously determining the shell plate structure and the acoustic cavity loss factor; establishing a shell plate material structure microscopic acoustic analysis model to calculate material acoustic parameters; according to the passive sonar working frequency range, the statistical energy analysis method is used to perform ship sonar self-noise prediction analysis on the aforementioned load to obtain sonar cabin external self-noise prediction values; and the material acoustic parameters are used to calculate the sonar cabin internal sound pressure level, and the sonar cabin internal self-noise prediction values are calculated in the form of 1 / 3 octave. The method can effectively improve the efficiency and precision of ship sonar self-noise prediction.