16results about How to "Meet engineering needs" patented technology

The invention provides an epoxy modified cement-based material, the epoxy modified cement-based material comprises an organic phase structure and inorganic crystals, and the inorganic crystals are radially distributed on the surface of the organic phase structure; the organic phase structure is a spherical or sphere-like structure with the diameter of 3-15 microns; the inorganic crystal is of a needle-shaped, rod-shaped or sheet-shaped structure with the length being 0.3-3 microns and the diameter being 0.05-0.5 microns. The epoxy modified cement-based material disclosed by the invention shows good adhesion and dispersion resistance under water or in a humid environment, can realize rapid underwater construction, and keeps stable performance for a long time under harsh conditions such as a marine environment and a humid environment; the engineering requirements of multiple fields such as building structure repairing, underwater repairing, rapid first-aid repair, ocean protection and road and bridge engineering are met, and the integration of high strength, high toughness, strong interface bonding and long-acting durability is realized.

The application discloses a Transformer oil well production prediction method and device based on gating constraints and Kalman filtering, and a medium, which comprises the following steps: first, obtaining oil well historical production data and preprocessing; then, using a mutual information method to screen input features related to target production, and constructing conditional gating constraint features representing the opening and closing states of the oil well; then, inputting the processed time sequence samples into a Transformer prediction model to obtain initial prediction results of the oil well production; then, performing state constraint on the initial prediction results according to the conditional gating constraint features, and performing causal recursive residual correction on the prediction results of subsequent time based on the current time prediction residual by using Kalman filtering to obtain final prediction results; further, performing grid search on Kalman filtering parameters Q and R for optimization, and determining the optimal parameter range by combining a heat map. The application can effectively reduce the prediction error, and improve the accuracy, stability and robustness of the oil well production prediction.

This invention discloses a fast quasi-peak detector simulation method for EMI receivers based on pulse detection coefficient fitting, comprising: acquiring the amplitude result of the target signal after processing by a peak detector; establishing a quasi-peak response model and determining the pulse detection coefficients; calculating the quasi-peak detection result corresponding to the target signal using the mathematical mapping relationship between quasi-peak voltage and peak voltage; and using the quasi-peak detection result as a fast predictive output to replace the time constant integration of traditional quasi-peak detection circuits for electromagnetic interference assessment. This invention is beneficial for the electromagnetic compatibility design of power electronic equipment and solves the problems of electromagnetic compatibility array testing time and cost.

The invention belongs to the technical field of fluid mechanical engineering, and particularly relates to a centrifugal pump and turbine dual-mode shaft power calculation method based on mechanical energy and internal energy analysis. Performing three-dimensional flow field calculation based on the pump mode system mass flow; calculating the specific mechanical energy difference between the outlet boundary and the inlet boundary of the pump mode system; calculating the specific internal energy difference between the outlet boundary and the inlet boundary; calculating pump mode shaft power of the centrifugal pump; determining a turbine mode system of the centrifugal pump; three-dimensional flow field calculation is executed based on the turbine mode system mass flow; calculating the specific mechanical energy difference between the inlet boundary and the outlet boundary of the turbine mode system; calculating the specific internal energy difference between the outlet boundary and the inlet boundary; calculating the turbine mode shaft power of the centrifugal pump; through collaborative analysis of mechanical energy and internal energy, the structure and operation characteristics of the pump and turbine dual mode of the centrifugal pump are adapted, and the technical blank of quantitative shaft power calculation under the pump and turbine dual mode of the centrifugal pump is made up from the perspective of system energy dissipation and conservation.

The application discloses a permafrost region railway track roadbed reinforcing and temperature controlling structure, method and storage medium, and the roadbed reinforcing and temperature controlling structure comprises, from top to bottom, a steel rail, a sleeper, a subgrade surface layer, a subgrade bottom layer and an embankment; a transverse ventilation pipe is arranged below the embankment; a plurality of gravel piles are arranged at the bottom of the transverse ventilation pipe; the pile body of the gravel pile is a porous structure formed by gravel filling and is communicated with the transverse ventilation pipe; the gravel pile at the soft soil foundation layer is wrapped by an economical geogrid; the gravel pile at the future maximum soft layer and the safety reserve layer is wrapped by a high-strength geogrid; and the gravel pile at the permafrost layer is not wrapped. The application adopts the composite wrapped gravel pile reinforcing structure to reinforce the foundation based on the degradation position of the permafrost, simultaneously reduces the deep soil temperature through the temperature controlling structure, maintains the stability of the permafrost layer, and improves the stability of the reinforcement.

This invention provides a modular inertia disk-type inertia torque adjustment mechanism. Through standard module units with calibrated inertia values ​​and a conical sleeve-type quick-locking mechanism, it achieves precise quantification and rapid assembly / disassembly of inertia, solving the problems of cumbersome operation, low accuracy, and poor repeatability associated with existing manual steel plate addition / reduction methods. By utilizing the target torque-angular acceleration conversion algorithm and greedy combination optimization algorithm built into the inertia matching controller, it can automatically output the optimal module configuration scheme without manual calculation, improving testing efficiency and accuracy. Furthermore, through the safety verification function of dynamic torque and motion range prediction, it can provide early warning of risks exceeding mechanical limits, avoiding equipment damage and safety hazards. This invention, while retaining the compact structure and high reliability of the original inertia disk assembly, significantly improves the intelligence level and ease of operation of inertia torque adjustment, meeting the engineering requirements of dynamic load simulation for high-precision servo mechanisms.

The invention provides a face recognition method based on point cloud data and RGB image sequential verification, and the method comprises the following steps: collecting two types of data at the same time, completing the face detection and cutting of an RGB image, combining histogram equalization and illumination compensation, extracting unitized features, comparing the unitized features with a feature library, and carrying out the confidence calibration. And according to the first upper threshold value and the first lower threshold value, primary judgment of passing, re-verification or refusal is made. After the RGB image passes verification, selecting a point cloud corresponding to a human face region, executing voxel downsampling, counting abnormal point removal and normal estimation, calculating local geometric description, performing robust registration, and constructing a single geometric similarity index based on a median absolute deviation of a point-to-surface residual error and quantile statistics; and outputting passing, re-checking or refusing according to the second upper threshold value and the second lower threshold value. Only when the two stages pass, an identity conclusion and confidence information are given; and when any stage is not passed or re-verification is not passed, outputting a rejection result or triggering a warning or auxiliary verification.

This invention discloses a design method for steel fiber reinforced concrete (SFR) materials based on multiple performance requirements, comprising: acquiring raw data of SFR parameters and performance, and determining a training dataset; training an initial convolutional neural network (CNN) model based on the training dataset to obtain a CNN performance prediction model; constructing a virtual function of SFR performance as the objective function using the CNN performance prediction module; obtaining the constraints of the basic performance parameters corresponding to the objective function; optimizing the concrete mix proportion for the objective function under each constraint using a genetic algorithm, selecting the optimal solution that meets the preset performance indicators, and determining the optimal solution set; and using the TOPSIS method to select the optimal solution set to obtain the optimal design scheme for SFR materials. This invention is beneficial for improving the various performance characteristics of SFRs, avoiding raw material waste, and achieving sustainable development of building materials.

The utility model discloses an HTCC-based differential line pair inner equal-length structure. Comprising a routing of a P-end differential line on a first wiring layer, a routing of an N-end differential line on the first wiring layer, a routing of the P-end differential line on a transition layer, a routing of the N-end differential line on the transition layer, a routing of the P-end differential line on a second wiring layer, a routing of the N-end differential line on the second wiring layer, and a via hole of a differential transmission line from the first wiring layer to the transition layer, and the differential transmission line passes through a via hole, a differential transmission line input end bonding pad and a differential transmission line output end bonding pad from the transition layer to the second wiring layer. The structure provided by the utility model has three significant advantages: firstly, the space required for wiring can be greatly reduced; secondly, a transmission path is scientifically optimized, so that the signal transmission distance is effectively shortened; and finally, high quality and stability of signal transmission are powerfully ensured by means of a symmetrical and equal-length ingenious design.

This invention discloses a coupling method for aerodynamics and vehicle dynamics applicable to high-speed trains, relating to the interdisciplinary field of aerodynamics and vehicle dynamics. The method includes: establishing separate aerodynamic and vehicle dynamic models for the high-speed train; exchanging data between the two models using a dual-time-step time-progression method, improving computational time accuracy, step size, and stability. While comprehensively considering the interaction between the high-speed train and its surrounding flow field, the influence of track irregularities, and tunnel effects, a multi-region mesh generation method is adopted, improving the quality and efficiency of mesh generation. Furthermore, the overlapping mesh method avoids mesh reconstruction problems. Simultaneously, the use of six-degree-of-freedom motion velocity to reflect the attitude changes of the high-speed train simplifies the coupling steps. The entire process saves time on mesh generation, calculating the displacement of mesh nodes around the train, mesh reconstruction, and computational iterations, enabling the coupling method to be implemented quickly and on a large scale.

The application discloses the technical field of plastic and additive identification, and relates to a plastic and additive identification method based on a bimodal multi-task neural network, which comprises the following steps: collecting plastic samples with known plastic base materials and additive contents; acquiring mid-infrared hyperspectral data and X-ray fluorescence spectral data of the samples based on a mid-infrared hyperspectral camera and a handheld X-ray fluorescence spectrometer; obtaining the plastic base material type, the additive type and the additive dose of the samples based on sample formulations or chemical analysis results; and determining the type and regression label of the plastic base material type, the additive type and the additive dose. The application is based on the natural complementarity of mid-infrared spectra and X-ray fluorescence spectra in the aspects of molecular structure information and element composition information, and is oriented towards the spectral characteristics of the plastic-additive system. The target identification model can improve the analysis capability for complex waste plastic systems carrying multiple additives, and has outstanding uniqueness and engineering application value.

The invention relates to the technical field of steel rolling, in particular to an ultra-strong steel thick plate online width measurement method based on monochromatic visible light irradiation sensitization, which comprises the following steps: step 1, conveying a steel thick plate along a roller way; 2, four monochromatic parallel light sources are used for obliquely irradiating the corresponding edges on the two sides of the conveying direction of the thick steel plate correspondingly; obtaining projection image data of the corresponding edges according to the projection area generated on each photosensitive plate; step 3, according to the projection image data of the four edges, respectively establishing an equation of each edge; 4, the length of two diagonal lines of the cross section of the thick steel plate is obtained; step 5, obtaining a first plate width value AC and a second plate width value BD of the steel thick plate; and 6, calculating the final plate width value of the steel thick plate. According to the method, a long-distance linear regression method is adopted, the bulging area occurring during rolling of the steel thick plate can be avoided, the width size of the super-strong steel thick plate in the rolling process is measured in real time, and measurement data are provided for automatic production control.

The application provides a deep-sea light-weight ring-stiffened cylindrical shell strength design method, which specifically comprises the following steps: (1) establishing a geometric model of the ring-stiffened cylindrical shell under external static water pressure; (2) performing stress analysis on the geometric model to obtain a cylindrical shell deflection curve expression containing unknown parameters; (3) confirming the boundary conditions of the geometric model and solving the unknown parameters in the cylindrical shell deflection curve expression according to the boundary conditions, substituting into the cylindrical shell deflection curve expression, thereby obtaining a complete deflection curve analytical expression, calculating stress values at different positions of the shell body based on the deflection curve analytical expression, and performing strength design on the structure according to the geometric parameters of the ring-stiffened cylindrical shell structure. The application has reasonable concept, the elastic boundary condition is used at the rib, the new boundary condition can better describe the constraint condition of the ribbed cylindrical shell at the rib and shell connection according to the material characteristics, and can be used for ring-stiffened cylindrical shell structures of different materials, and is more universal and accurate.

The application discloses a data-driven runner blade surface static stress neural network prediction method, which comprises the following steps: establishing a full-flow passage model of a Francis turbine unit, performing grid division on the model, importing the grid corresponding to a working condition point into a numerical simulation software, and obtaining runner blade surface pressure data; establishing a water turbine unit shaft system model, performing non-structural grid division on the model, inputting the runner blade surface pressure data into an interface between a fluid domain and a solid domain, obtaining runner blade surface static stress data and corresponding three-dimensional coordinates, and dividing the static stress data into a training set and a test set; training a prediction model by using the three-dimensional coordinates, water head and opening degree corresponding to the training set, inputting the three-dimensional coordinates, water head and opening degree of the working condition point into the trained prediction model, and obtaining runner blade surface static stress under the working condition point. The application can correctly reflect the static stress distribution trend of the blade under all working conditions and has high precision.

The present application relates to a space perspective method, comprising: S1, obtaining prior information of a space target; S2, deploying a perspective satellite system loaded with a cruising robot relative to the space target, wherein the cruising robot is loaded with a perspective load; S3, the cruising robot performs a space perspective task on the space target according to the prior information. The present application can realize high-precision and close-range internal structure perspective detection of a target in a space dimension.

The application discloses a preparation method of MICP combined with molasses reinforced calcareous sand. The preparation method comprises the following steps: activating and culturing mineralization bacteria, preparing a molasses culture medium by using waste molasses, inoculating the activated mineralization bacteria liquid on the molasses culture medium, and after the OD600 value of the mineralization bacteria in the molasses culture medium is between 1.0 and 1.5, injecting the molasses culture medium containing the mineralization bacteria into the calcareous sand for reinforcement, so that the reinforced calcareous sand is obtained. The preparation method of the MICP combined with molasses reinforced calcareous sand disclosed by the application directly uses waste molasses as a carbon source to culture mineralization bacteria, greatly reduces the preparation cost, and is green and environment-friendly in the preparation process; by adding sugarcane residue with a proper proportion and length in the waste molasses, the viscous sugar silk and the sugarcane residue are uniformly distributed in the reinforced calcareous sand, so that the generation amount of the microbial-induced calcium carbonate crystal is improved, and the prepared calcareous sand has more excellent reinforcement effect, and the unconfined compressive strength can reach 2 MPa at most.