583results about How to "Simple calculation" patented technology

The invention provides a method for quickly establishing a three-dimensional near-seafloor speed model in a shallow sea area; the method comprises the following steps of extracting initial informationand extracting a common-center-point gather; calculating the slope of the initial travel time in the common-center-point gather; judging whether a shot point is located in the seawater layer or not,and if yes, correcting the shot point to the seafloor; calculating the speed and the depth of inflection points corresponding to respective offset distances; performing linear interpolation on the speed at each depth to obtain a one-dimensional speed model of the common center point; after all the common-center point domain gathers are processed, adopting the linear interpolation method, calculating the speed values of the rest grid points by utilizing the one-dimensional speed model of all common center points, and a speed model is output. By adoption of the method for quickly establishing the three-dimensional near-seafloor speed model in the shallow sea area, the influence of the seawater layer on ray propagation is overcome, and the influence of multiple excitation receiving modes on an inversion result is eliminated, and the problem that the conventional method needs to carry out multi-ray tracing forward modeling is avoided.

The invention discloses a cable fault positioning method and system based on reflected wave decomposition and kurtosis sorting, and aims to solve the problem that a cable fault is difficult to detect under a low impedance change rate. The method comprises the steps of transmitting an incident excitation signal to a cable to obtain a first reflection signal in the cable; an improved VMD algorithm is adopted for decomposition to obtain K IMF components, and the IMF with the maximum kurtosis is selected as a second reflection signal; acquiring a time-frequency distribution curve of the second reflected signal by using short-time Fourier transform and frequency spectrum redistribution technologies; and constructing a two-dimensional energy-time curve by extracting an energy value and time under the frequency of the maximum energy amplitude point, and determining a fault position. The system is composed of an incident excitation module, a decomposition module, an STFT-RSP module and a fault positioning output module, and the positioning method is achieved. According to the method, the limitation of a traditional spread spectrum time domain reflection positioning method in cable fault detection is effectively overcome, and an efficient and accurate instructive technology is provided for cable fault positioning and detection.

The invention relates to the field of short-term load prediction and power dispatching control of a power system, in particular to an energy output optimization dispatching method and system considering a random source load virtual power plant, and designs a virtual power plant double-layer optimization dispatching model. The lower-layer model constructs a user load prediction model of an improved Transform, and then a renewable energy output model is established by using a scene generation method; the upper layer model takes the power generation cost minimization of the wind-light storage and combustion virtual power plant as a target, considers constraint conditions such as gas turbine output power, ramp rate, energy storage charging and discharging power, electricity storage quantity and power balance, and proposes a single guide target function comparison algorithm considering random source load to carry out optimization solution on a virtual power plant optimization scheduling target function; and planning and deciding the output of each energy source in the next 24 hours. Experiments show that the new energy consumption level can be remarkably improved under the random source load condition, and better economic benefits are obtained while stable operation of a power distribution system is promoted.

The invention provides a method for intelligently predicting the strength of a filling body by combining color and pore structure characteristics, and relates to the technical field of mine filling, the method comprises the following steps: firstly, selecting a filling material for mine production, making an experimental scheme on the basis of the actual proportion of mine production, and preparing and maintaining the filling body; then obtaining a color characteristic value, a pore structure characteristic value and a uniaxial compressive strength value of the filling body; and processing the color characteristic value, the pore structure characteristic value and the uniaxial compressive strength value, establishing a data set, constructing an initial strength prediction model, and performing evaluation and optimization to obtain an optimal strength prediction model.

The invention discloses a three-dimensional finite element simulation method for a complex slope excavation unloading process, which comprises the following steps of: 1) constructing a three-dimensional model of a complex slope, and establishing a finite element grid; 2) inputting boundary conditions of the model and material parameter information of each stratum; 3) calculating and simulating an initial stress field of the slope before excavation; (4) according to the initial stress field, the unloading load of the slope excavation part is calculated; (5) finite element calculation is conducted on stress deformation of the excavated slope; according to the method, the high-precision three-dimensional finite element model is established, various material parameters and actual boundary conditions are combined, the stress change and the unloading effect of the slope in the excavation process are simulated, the stress redistribution in the unloading process is accurately reproduced, the prediction precision of local instability and stress concentration areas is improved, and the prediction accuracy of the slope is improved. Therefore, a scientific basis is provided for safety assessment of slope excavation.

The invention relates to the technical field of air traffic management, in particular to an unmanned aerial vehicle conflict-free route planning method and system applied to a low-altitude airspace, and the method comprises the steps: obtaining the starting point and terminal point information of the flight of an unmanned aerial vehicle in an airspace unit when detecting that a new unmanned aerial vehicle enters the airspace unit; acquiring information about whether the grids of the airspace units have conflicts or not; obtaining reachable grids and feasible grids of the unmanned aerial vehicle; obtaining alternative nodes based on the feasible grids of the unmanned aerial vehicle; based on the alternative nodes, a preset constraint condition and the power consumption, obtaining a directed weighted graph; a path in the directed weighted graph represents a conflict-free track; searching the directed weighted graph by adopting an A-star algorithm to obtain an optimal conflict-free track, and controlling the unmanned aerial vehicle to execute the optimal conflict-free track; according to the invention, the optimal conflict-free flight path of the unmanned aerial vehicle can be efficiently and rapidly planned.

The present invention relates to the technical field of distribution network planning and construction, and discloses a power balancing method for power system source-grid-load-storage coordination, including the following steps: S10: superimpose total load, the total load includes conventional load and electric energy substitution load, perform superimposition calculation on them, adopt a method combining natural growth and special load when predicting electric energy substitution load, and fit the total load curve after the total load is superimposed; S20: net load curve; S30: curve after natural peak shaving; S40: curve after grid side peak regulation; S50, balance curve; S60, power demand. The present invention establishes a clear and highly operable power balancing process for new power system source-grid-load-storage coordination, clarifies the relationship between the source-grid-load-storage interaction after a large number of new energy sources are connected to the power grid, and can improve the utilization efficiency of the power grid on the basis of ensuring the security of the power grid while fully absorbing a large number of new energy sources.

The invention relates to a traditional Chinese medicine tongue diagnosis auxiliary diagnosis method and system fusing multiple characteristics of a tongue body, and belongs to the technical field of medical information and health data processing. Firstly, a BlendMask network is utilized to carry out tongue segmentation model training, an obtained tongue segmentation model is utilized to complete data segmentation, tongue shape analysis is carried out on a segmented tongue data set, whether the shape is normal or not is judged by calculating a tongue skew index, and a data set with the normal shape is utilized to input a feature extraction network to carry out classification training. And classifying the tongue body image by using a tongue body identification and classification model, carrying out further regional tongue color analysis on the tongue body with abnormal tongue color, and outputting the comprehensive health state of the patient by combining the tongue body form skew feature, the tongue body identification and classification and the regional tongue color analysis. According to the invention, comprehensive analysis is carried out from the aspects of tongue body morphology, color and regional tongue color, the accuracy of tongue diagnosis analysis is improved, and efficient diagnosis of organs is realized.

The invention relates to an enterprise park meteorological fire risk assessment method based on an adaptive random forest model, and the method comprises the steps: building a risk assessment model and a visual early warning platform, enabling the risk assessment model to collect alarm data, meteorological data, enterprise data and park division data, and forming a risk assessment data set, and integrating internal characteristics and external data of the park into a data set, inputting new data into the self-adaptive random forest model by means of a real-time data flow technology, updating and evaluating a fire risk index value of the park in real time, and optimizing a model decision tree to automatically adjust a risk evaluation model and adapt to changes of environment and operation. Accurate early warning information is provided for a visual early warning platform, the risk level of the park is displayed in real time, and a risk alarm is given out in time.

The invention discloses a joint beam forming optimization method for an RIS auxiliary low-altitude communication system. The problem of performance bottleneck caused by interaction of active beam forming and passive beam forming is solved by adopting a genetic algorithm based on a dynamic adaptive theory. Aiming at the limitation of a standard optimization method, a hybrid strategy of genetic algorithm optimization and a full-connection neural network is explored, and intelligent collaborative setting of system parameters is realized. Simulation results show that the hybrid algorithm not only simplifies the calculation process to obtain the optimal network parameters, but also effectively optimizes the system structure by dynamically adjusting the RIS reflection configuration. On the basis, the signal transmission quality is improved, interference is reduced, and it is guaranteed that the RIS-assisted low-altitude unmanned aerial vehicle intelligent communication system stably and efficiently operates in a complex wireless transmission environment.

The invention discloses a degradation conversion rate calculation method and system based on an epoxy resin alcoholysis model, and belongs to the technical field of thermosetting epoxy resin degradation and recovery. The method comprises the following steps: pouring epoxy resin to cure and mold, carrying out an epoxy resin alcoholysis degradation experiment at different temperatures, and recording degradation conversion rates at different moments; constructing an epoxy resin geometric model, and analyzing to obtain a degradation conversion rate differential expression containing reaction rate constants and geometric parameters; solving the differential equation to obtain a reaction rate constant, and fitting by using an Arrhenius formula to obtain degradation activation energy; analyzing a transesterification process of the epoxy resin and the alcohol solvent and a diffusion process of the alcohol solvent in the epoxy resin, and establishing a degradation conversion rate expression which does not contain geometric dimension parameters; and substituting degradation reaction activation energy, and fitting to determine a degradation conversion rate expression which does not contain geometric dimension parameters. The invention aims to provide a reference for the degradation process analysis of the large-size epoxy resin with a complex shape.

The invention discloses a junction temperature estimation method and device for a power semiconductor and a vehicle, and the method comprises the steps: obtaining the loss, temperature rise data and environment temperature of the power semiconductor in an electric period, the temperature rise data comprises temperature rise values of the temperatures of the power semiconductor under different operation conditions relative to the environment temperature; determining thermal impedance according to the loss and temperature rise data; and determining the junction temperature according to the loss, the thermal impedance and the environment temperature. According to the method, the load rate of the vehicle-mounted software can be reduced, additional hardware does not need to be added, so that test resources are simple, the accuracy is high, the practicability is high, the junction temperature calculation efficiency is improved, and the calculation time is saved.

The invention provides a vehicle transverse motion control method and a vehicle transverse motion control system. The vehicle transverse motion control method comprises the steps that a feedback rotation angle is calculated based on an LQR algorithm; calculating a feed-forward rotation angle based on preview tracking control; and adding the feedback rotation angle and the feedforward rotation angle to obtain a front wheel rotation angle original value which is used for participating in vehicle transverse motion control. Through the configuration, on one hand, the advantages of simple calculation and less calculation resource occupation of the LQR algorithm and the preview tracking control algorithm can be played, and on the other hand, the control effect can be effectively improved by combining the calculation results of the LQR algorithm and the preview tracking control algorithm. The vehicle transverse motion control system is hardware for operating the control method. Both of the two can solve the problem that in the prior art, a vehicle transverse movement online control method cannot meet the requirements of actual application scenes.

The invention discloses a vehicle visual relay tracking method based on spatial-temporal feature fusion, and belongs to the technical field of intelligent traffic. After a multi-target tracking trajectory of each camera on a road is obtained, the method comprises the following steps: establishing a camera space-time constraint based on a topological relation between the cameras and the road, performing trajectory compatibility judgment based on the camera space-time constraint, and filtering out incompatible trajectory pairs; modeling the trajectory of the target vehicle into a graph, and calculating the similarity of compatible trajectory pairs based on a graph convolutional neural network; based on the trajectory similarity, the multi-camera trajectory association problem is decomposed, hierarchical clustering is performed on the trajectory by using a heap data structure, and the global association trajectory of each target vehicle is obtained step by step. According to the method, the efficiency and accuracy of track association are improved, the calculation efficiency is optimized, and vehicle tracking in a complex scene and under multiple cameras can be dealt with.

The invention discloses a model predictive control-based train formation distributed cooperative control method, which comprises the following steps of: acquiring a train tracking speed running curve, train speed limiting information and a train running resistance coefficient, and establishing a train formation model; according to a preset model predictive control algorithm, in a set predictive control time domain, according to a train formation model, a control target and constraint conditions, state variables of positions and running speeds of all trains in a train formation and control variables of control forces of all the trains in the train formation are used to predict the train formation according to state variables of the positions and running speeds of all the trains in the train formation. Respectively generating optimization control problems of the leading train and the following train in the train formation; and based on a synchronization theory, solving an optimization control problem of each train to obtain a control force of each train in the formation, and inputting the control force into a train operation control system to realize distributed control of each train in the train formation. The method is based on a model predictive control algorithm, uses a synchronization theory, and reduces the use of computing resources and communication resources in practice.

The invention relates to a lightweight electrical equipment multi-target detection method and system, and the method comprises the steps: collecting multi-angle images of different types of electrical equipment, obtaining an experiment data set, constructing a Ghostnet lightweight network structure, introducing a CBAM attention mechanism and an SPPFCSPC convolution structure to improve a YOLOv8 model, and obtaining a multi-target detection model based on the improved YOLOv8 model. And training, verifying and evaluating the multi-target detection model based on the improved YOLOv8 model to obtain a multi-target detection optimal model for electrical equipment multi-target detection. According to the method and the system, the model complexity and the calculation amount can be reduced while the detection precision is ensured, and an effective solution is provided for multi-target identification detection of lightweight electrical equipment.

The invention discloses a quantitative characterization method for the roughness degree of a high-speed remote landslide motion path, and belongs to the technical field of geological disasters, and the method comprises the steps: firstly obtaining remote sensing image data of a target landslide, DEM digital elevation data of the target landslide and landslide boundary data of the target landslide, and obtaining elevation data of the motion path of the target landslide through processing; carrying out detrending to obtain elevation data of the landslide motion path microtopography; and according to the elevation data of the landslide motion path microtopography, performing calculation based on a joint contour line fractal dimension calculation method to obtain the fractal dimension of the target landslide motion path after detrending, and performing calculation to obtain the path roughness coefficient of the target landslide. According to the method, the calculation process is simple, the application range is wide, the roughness degree of the high-speed remote landslide motion path can be quantified under different spatial scales, the influence of the microtopography in the landslide motion process is fully revealed, and more comprehensive roughness characterization is provided.

The invention relates to the technical field of automatic driving, and provides an intersection steering decision-making method and decision-making device. According to the method, target obstacle information of a moving object is obtained, the conflict time of the moving object and a target obstacle is determined, and a revenue function is constructed based on the conflict time, the self-vehicle decision probability of the moving object to the target obstacle and the decision probability of the target obstacle. Solving the revenue function to obtain a first target self-vehicle decision probability when the revenue function reaches a balance point, determining a convergence decision by using the first target self-vehicle decision probability, determining that the decision type of the convergence decision is different from the current decision type of the moving object, performing feasibility judgment and enhancement judgment on decision type conversion operation, according to the method, the intersection turning decision is made by combining the game and the rule, the more accurate decision result can be provided by dynamically adapting to the environment change through the game, the calculated amount is simplified by utilizing the constraint of the rule, the decision efficiency is greatly improved on the basis of not obviously reducing the decision quality, and the decision-making efficiency is improved. And thus, the road condition steering decision making efficiency is improved.

The invention discloses a distribution network reactive power support capability evaluation method and system considering uncertainty new energy output, and belongs to the technical field of power grid power generation dispatching, and the method comprises the steps: constructing a distribution network reactive power deviation index considering active and reactive power coupling, and fusing the index into a distribution network reactive power support capability evaluation calculation process; constructing reactive power reserve models of various traditional energy sources and uncertain new energy sources, wherein the reactive power reserve models comprise a generator set, a capacitor bank, wind power generation, photovoltaic power generation, energy storage, a flexible load and an electric vehicle; constructing a typical scene set which comprehensively considers the output of all the models; constructing a distribution network reactive power support capability calculation model considering the uncertainty new energy output; and solving by adopting a genetic algorithm to obtain the reactive power support capability of the distribution network. According to the method, multiple types of reactive power resources on the power distribution side are fully transferred, the reactive power reserve potential evaluation model for the active power distribution network individuals is established, and quantitative evaluation of the reactive power voltage supporting capacity of the power distribution network is achieved.

The invention discloses a carrier rocket application-oriented adaptive augmented controller frequency domain analysis method, which comprises the following steps of: further simplifying a nonlinear damping module of an improved AAC controller to obtain a frequency domain model of the AAC controller, inputting a sine characteristic signal into the frequency domain model to obtain an analytical solution of an output value of the AAC controller, and removing high-order harmonics from the analytical solution to obtain a frequency domain model of the AAC controller. Obtaining an output signal with the same frequency band as the input signal; frequency domain response of an integrator at a low frequency band is used as an integral filter to simplify an output signal, and a linear part of a result is used as a frequency domain analysis model of the AAC controller; the precision and the application range of the AAC controller frequency domain analysis model are evaluated through a frequency sweep test, and the application range of the AAC controller is given; the obtained AAC controller frequency domain analysis model is integrated into a carrier rocket control model, and the frequency domain margin of a carrier rocket control system is improved at high frequency and low frequency by adjusting control parameters.

The invention relates to a transformer substation flood prevention case text classification method and device, equipment and a medium, belongs to the field of natural language processing text classification, and is used for carrying out multi-label classification on transformer substation flood prevention case texts to be predicted based on a completely trained improved BERT model to obtain disaster cause labels of the flood prevention case texts. The improved BERT model comprises an embedded layer, an encoder layer, a TextCNN (Convolutional Neural Network) layer and a Seq2Seq layer; the transformer substation flood prevention case text classification method comprises the steps of extracting a text vector of a to-be-predicted transformer substation flood prevention case text based on an embedded layer, and compressing the text vector by adopting a lightweight strategy; extracting global semantic features of the compressed text vector based on an encoder layer; performing feature extraction on the global semantic features based on a TextCNN layer to obtain feature vectors; the feature vector is coded and decoded based on the Seq2Seq layer, the disaster-causing cause label of the flood prevention case text is obtained, the overall classification performance is enhanced, and the accuracy of the single cause label is improved.

The invention provides a bad root cause analysis method and system based on a comprehensive analysis framework, and relates to the technical field of bad root cause analysis, and the method comprises the steps: obtaining bad data and processing process data; performing comprehensive analysis on the bad data and the processing process data according to the comprehensive analysis framework so as to position intermediate link factors related to the bad product; performing root cause positioning analysis on the processing process data according to the bad data so as to preliminarily position a root cause station and root cause machine equipment; root cause positioning analysis is carried out on the processing process data according to the intermediate link factors related to the bad products so as to further position root cause machine equipment; and performing fusion judgment on the root cause site and the root cause machine equipment which are preliminarily positioned and the root cause machine equipment which is further positioned to obtain a comprehensive root cause positioning result. The root cause positioning of the processing equipment is carried out based on the comprehensive analysis framework, and the problem that comprehensive analysis and judgment cannot be realized due to isolation between different bad root cause analysis means is solved.

The invention discloses an overhead transmission line engineering construction carbon emission calculation method based on a full life cycle method. The calculation method comprises the following steps: S1, selecting GB / T 51366-2019 Building Carbon Emission Calculation Standard as an overhead transmission line carbon emission calculation criterion; s2, combining calculation standards, selecting a full life cycle method as a theoretical basis, and taking a carbon emission factor method as a main calculation method to carry out combined calculation; s3, carbon emission factors of electric energy, fossil fuel, mechanical equipment and building materials are compared in detail, and finally a carbon emission factor list suitable for overhead transmission line engineering construction is established; according to the method, the carbon emission is divided into three key stages, namely vehicle transportation, a construction process and building material use, on the basis of a full life cycle method, the complexity of analysis of main components and the overall structure of the overhead transmission line is simplified, the calculation workload and the calculation cost are reduced, and the method has wide applicability.

The invention belongs to the technical field of magnetic particle imaging, particularly relates to a time sequence magnetic nanoparticle imaging device and method for detecting nerve response activity, and aims to solve the problems that the sensitivity of magnetic particle signal detection is not high, a large coil assembly is needed for achieving high magnetic field intensity, the calculation amount is large, and the calculation mode is complex. According to the device, a signal generator outputs a voltage signal, amplifies the voltage signal and then accesses a selection coil and a driving coil; the two selection coils are arranged in a Maxwell configuration and have the same axis; the driving coils are arranged at intervals of 90 degrees from top to bottom, from left to right and from front to back by taking the FFR as the center; the excitation coil, the receiving coil and the selection coil are coaxial; and the high-pass filter filters the signal received by the receiving coil and imports the signal into a computer through a signal acquisition card for time sequence fMPI image sequence reconstruction. According to the invention, the magnetic particle signal detection sensitivity is improved, the volume of the coil assembly is reduced, the calculation complexity and the calculation amount are simplified, and the magnetic particle imaging robustness is improved.

The invention discloses a tunnel stratum grouting reinforcement design method considering a vertical jacking construction load, and belongs to the technical field of underground tunnel engineering. The prediction method comprises the steps that the value range of the grout injection rate beta is determined, the value range of the thickness D of a grouting reinforcement ring is determined, the design range of the grouting reinforcement ring is determined, and the range of the grouting reinforcement ring and the value range of grouting pressure P are further determined; according to the foundation bearing capacity requirements of a grouting reinforcement ring and an undisturbed stratum and the maximum floating displacement threshold value of local segments caused by the grouting lifting effect, a theoretical basis is provided for design of the range and thickness D of the grouting reinforcement ring, the grout injection rate beta and the grout pressure P, and control over design parameters of the grouting reinforcement ring is achieved; the theory based on the method is more reasonable, the calculation process is simple, and the method can be used for tunnel stratum grouting reinforcement design in actual vertical jacking construction.

The invention discloses a cable production quality detection method and system, and the method comprises the steps: obtaining a cable insulation layer surface image with qualified production quality, generating an image fingerprint, and storing the image fingerprint in a qualified cable database; after insulation injection molding of the current cable is completed, shooting an image of a cable insulation layer once every s second through three camera devices surrounding the cable; performing image compression and graying processing on the three shot cable insulation layer images at different angles, then performing discrete cosine Fourier transform, generating a transformation coefficient matrix, and then taking out a sub-matrix as a low-frequency domain matrix; generating a binary sequence through the low-frequency domain matrix and converting a hexadecimal character string; image fingerprints are obtained from a qualified cable database, the Hamming distance is calculated through the image fingerprints and hexadecimal character strings, and whether surface defects of the insulating layer occur or not is judged. According to the method, automatic quality monitoring in the cable production process is achieved, high detection accuracy is achieved under the condition that the detection speed is guaranteed, and the calculation process is simple.

The invention discloses a pressure sensor temperature compensation method combining polynomial fitting and a neural network algorithm, and belongs to the technical field of sensors, and the method comprises the following steps: collecting output data of a pressure sensor in a wide temperature and pressure range, carrying out the cleaning and normalization processing of the collected data, and removing abnormal values; according to the collected data, polynomial fitting is carried out by using a least square method and the like, initial compensation is carried out on the original data, and a pressure value after initial compensation is calculated; constructing a neural network structure, training the neural network by using the preliminarily compensated data, and adjusting the weight and bias of the neural network to minimize the error between the output of the neural network and the actual pressure value; a temperature value measured in real time and a sensor output value are input into a trained system, primary processing is carried out through a polynomial fitting model, then a result is input into a neural network, and the neural network outputs a final pressure value after temperature compensation.

The invention discloses a secret key following transmission system and method based on dynamic window encryption, and the system comprises a transmitting end which is configured to obtain a chaotic initial value and an original signal to be transmitted; processing the chaotic initial value through a public key encryption module and a first constellation mapping module to obtain encryption key information; the original signal is processed by a bit stream encryption module, a second constellation mapping module and a symbol encryption module to obtain encrypted information, the bit stream encryption module realizes bit stream encryption by using a disturbance sequence generated by a chaotic initial value, and the symbol encryption module realizes symbol-level scrambling by using a'dynamic window structure '; superposing the encrypted information and the encrypted key information by using a power division multiplexing module to obtain to-be-transmitted composite information; the composite information is converted into a time domain signal through fast inverse Fourier transform (IFFT), and signal transmission is carried out through a channel; and dual improvement of communication safety and communication efficiency is realized.

The invention relates to the technical field of waste gas treatment, and discloses a method for calculating contribution coefficients of different pore diameters to VOCs (volatile organic compounds) adsorption capacity under different partial pressures, which comprises the following steps of: using two or more porous materials with concentrated pore diameter distribution as model adsorption materials; the change trend of the VOCs adsorption isotherm in different pressure areas is associated with the pore size of the material to obtain a regularity equation that the critical pore size of filling type adsorption and covering type adsorption changes along with pressure under corresponding adsorption conditions. According to the critical pore channel size equation and in combination with an influence rule of pore size difference and partial pressure change on a VOCs adsorption isotherm, contribution coefficients of different pore sizes in the adsorbent on filling type adsorption and covering type adsorption of VOCs adsorption and a regularity equation of the change along with the partial pressure are obtained respectively. The method can effectively guide the type selection of the adsorbent, and provides a reference basis for the development of efficient adsorption materials and technologies.

The invention relates to a novel noise reduction device aiming at the noise problem in a subway shield tunnel and an evaluation method of the novel noise reduction device. The device is a honeycomb-multilayer composite sound energy absorption device based on a honeycomb structure, the device is composed of a multilayer honeycomb energy absorption pad structure, the reflection frequency of noise entering the absorption pad is greatly increased, and the laying condition of shield tunnel bent duct pieces can be adapted through unitized honeycomb holes. And meanwhile, a vehicle-track-infrastructure vibration noise analysis model containing a fluid domain is established as an evaluation method, so that the noise reduction performance of the device can be evaluated and verified. According to the honeycomb-multilayer composite sound energy absorption device, the porous material with an excellent sound absorption effect is adopted, so that the honeycomb-multilayer composite sound energy absorption device has independent noise reduction capability in structure and material, the composite noise reduction capability is more excellent, the established evaluation method can be suitable for device performance modulation of various scenes, and the evaluation method is suitable for popularization and application. And the method has relatively high universality.