16results about How to "Reduce engineering risk" patented technology

This invention discloses a vibration damper for an afterburner with an insertion tube, belonging to the design field of afterburners. It includes a vibration damper, a flame stabilizer, and a central cone. The vibration damper is located at the downstream end of the outer bypass channel, closely attached to the inner wall of the afterburner shell, forming a double-wall structure. Cold air from the outer bypass flows through it, cooling the wall surface and absorbing oscillation energy, thus suppressing high-frequency vibrations in the combustion chamber. The flame stabilizer is located in the inner bypass channel, its inner end connected to the central cone. The inner bypass and part of the outer bypass airflow meet here, forming a low-speed recirculation zone, achieving fuel-air mixing and stable ignition. The vibration damper has openings, employing a deep-hole structure with an insertion tube. The insertion tube is placed within a hole in the vibration damper's base, significantly increasing the equivalent neck length of the vibration damper while maintaining the same main plate thickness. This shifts the peak sound absorption frequency towards lower frequencies, improving the vibration damper's absorption capacity for low-frequency oscillation modes in the afterburner.

The utility model relates to long distance big longitudinal slope sand and mudstone interbedded shield fast tunneling key technical field especially relates to a kind of water-rich sand and mudstone interbedded shield machine soil bin intelligent mixing device, solve the problem such as the limited stirring range in soil bin, low mud circulation rate, increase the rubber stick range in soil bin, improve mud circulation rate, including along the soil bin intelligent mixing device of fixed shield machine axial, the soil bin intelligent mixing device is connected with shield machine control system, the soil bin intelligent mixing device includes variable frequency motor, telescopic link, transmission shaft and initiative mixing device;The variable frequency motor is fixed on the back side wall of soil bin, the output of the variable frequency motor is connected the telescopic link, the front end of the telescopic link is connected the transmission shaft, the front end of the transmission shaft is installed with fender, multiple initiative mixing devices are equipped on the front side of the fender;When slag in soil bin is more accumulation, shield machine control system drives telescopic link to lengthen, increase stirring range.

The invention discloses an offshore wind power project soil space variability analysis method. The method comprises the steps that drilling data and CPT data of an offshore wind power project are collected and preprocessed; a mathematical model is established, a correlation function of drilling and CPT is constructed, and distribution characteristics of model parameters are obtained; taking the obtained distribution as initial estimation, and for any to-be-predicted point, obtaining an optimal predicted value of the point in a spatial domain according to the known data points and spatial distribution characteristics of the to-be-predicted point; the prediction result is verified and corrected by using actually measured data obtained in the actual construction process; and a high-precision soil body spatial variability prediction model is obtained through repeated iterative optimization and is used for guiding fan foundation construction scheme formulation, optimization and engineering risk assessment. The method provides data support for the whole wind power plant.

The application discloses a kind of marine engineering steel plate strength detection devices, it is related to marine engineering steel plate strength detection technical field, including data processing module;Data processing module includes contact state analysis unit, steel plate strength analysis unit;Contact state analysis unit carries out analysis to the contact state of indenter and steel plate, obtains the moment when indenter and steel plate contact, the time region between contact moment and current moment is marked as strength detection time zone;Steel plate strength analysis unit carries out state analysis to the strength of steel plate in strength detection time zone and obtains steel plate strength analysis result.The application determines the moment when indenter and steel plate contact and reasonably demarcates strength detection time zone by the contact state analysis unit pressure value operation and comparison mechanism, lays the analysis foundation for subsequent detection, and steel plate strength analysis unit discriminates steel plate quality by index calculation and evaluation process, guarantees the reliability of steel plate quality.

This invention discloses a system for predicting the risk of recurrence after lumbar disc herniation surgery based on domain offset correction, relating to the fields of medical data processing and clinical disease risk prediction technology. The system acquires multimodal clinical and imaging feature vectors and follow-up outcome data from training and independent validation cohorts. It trains a center classifier to quantify and correct for differences in multi-center data distribution, calculates and normalizes the importance weights of each training case, trains a survival analysis base learner based on the processed weights, and performs stacking and ensemble integration. The final deployment model is determined by combining the independent validation case cohort. The final deployment model is then used to infer the risk of recurrence in target patients after lumbar disc herniation surgery, outputting individualized recurrence risk scores, risk stratification, and recurrence-free survival curves. This improves the robustness and reliability of the risk prediction system in cross-center scenarios and is suitable for follow-up management and clinical decision support after lumbar disc herniation surgery.

This invention relates to the field of intelligent control technology for bridge-building machines, specifically to a micro intelligent bridge-building machine system and control method. The system mainly includes diagnosing the target equipment using a fault diagnosis model, outputting the current warning level using an early warning model, and configuring the system to, upon receiving a control signal from a user terminal requesting modification of the first equipment's operating parameters, acquire the user terminal's job level information. Based on the warning level and the user terminal's job level information, it determines whether to proceed with modifying the first equipment's operating parameters. Through this scheme, after a fault warning is issued and the modification of the first equipment's operating parameters is accepted, multiple levels of user terminal information are verified, and encrypted transmission is performed. This significantly prevents malicious tampering and reduces the overall project risk.

The application discloses a diversion tunnel alternating flow staging gate closing water storage structure and method, relates to the technical field of water conservancy and hydropower construction, and comprises a first diversion tunnel, a second diversion tunnel and a three-face stoplog gate, the first diversion tunnel is provided with a first water inlet and a first water outlet at two ends, and is further provided with a third water inlet, the setting height of the third water inlet is higher than that of the first water inlet; the first diversion tunnel is further provided with a first gate slot and a third gate slot, and the first gate slot and the third gate slot are located at the front and rear of the third water inlet respectively; the second diversion tunnel is provided with a second water inlet and a second water outlet at two ends, the setting height of the second water inlet is higher than that of the first water inlet and is lower than that of the third water inlet; the second diversion tunnel is vertically provided with a second gate slot at the second water inlet; and the stoplog gate is formed by parallel and coplanar splicing of a plurality of baffles. The application can solve the problem that the downstream river channel cannot be effectively prevented from being dehydrated and cut off under the premise of ensuring economy and safety.

The application belongs to the technical field of electric power survey design, and discloses an electric power survey design integration method and system for smart grid construction, which comprises the following steps: extracting preset engineering characteristics of existing survey results in a current engineering area, combining current engineering planning condition characteristics to form a sample set; inputting the sample set into a pre-trained graph neural network to output engineering application probability and instability risk score of each survey result, wherein the nodes of the graph neural network correspond to single survey result, and the edges are constructed based on spatial adjacency, engineering correlation or common participation in design relationship; generating design consistency constraints for survey results meeting a preset threshold; and finally checking the compliance of the design scheme and the constraints. The method realizes substantial integration of survey and design, improves design efficiency and quality, and reduces the risk of rework.

The application discloses a water-rich soft rock foundation pit adjacent tunnel stability control method based on artificial intelligence, which comprises the following steps: prior prediction based on a finite element model, monitoring sensor arrangement, construction and training of a neural network model, scheme safety verification, initial decision based on the neural network model, initial grouting scheme execution, real-time monitoring-based cyclic intelligent decision and online incremental learning; training data is generated by establishing a three-dimensional finite element model containing a water-soil coupling mechanism, a neural network model capable of mapping the complex nonlinear relationship between monitoring parameters and optimal grouting schemes is constructed and trained, dynamic decision is made, and the grouting scheme that has passed safety verification is output and the model is continuously optimized; the method realizes the whole-process closed-loop intelligent control from intelligent prediction, real-time decision, safety control to self-optimization, and significantly improves the guarantee capacity and risk control level of the stability of the adjacent tunnel during foundation pit excavation in the water-rich soft rock complex stratum.

This invention provides a sealing structure for building openings, relating to the field of building construction technology. It includes a cross-section enlargement structure installed on the exterior of corner columns; a main beam positioned along the stress direction of the building opening, with both ends connected to the cross-section enlargement structures on two adjacent corner columns; and secondary beams, which are composite beams composed of H-beams and a superstructure plate. The H-beams span between the main beams and are fixedly connected to them, with the superstructure plate covering the H-beams. This invention enhances the load-bearing capacity and deformation resistance of existing corner columns by installing cross-section enlargement structures on their exteriors, thereby improving the stability of the entire sealing structure. The newly added main beams are arranged along the stress direction of the building opening, and the new secondary beams are a combination of H-beams and a superstructure plate. The H-beams provide high-strength load-bearing capacity, while the superstructure plate further distributes the load, thus improving the overall bending stiffness and load-bearing capacity of the sealing structure.

This invention provides a hierarchical collaborative control method and system for a heat pump thermal management system in electric vehicles, relating to the field of electric vehicle thermal management. The method includes: collecting raw operating data and performing preprocessing on the raw operating data; constructing an upper-level state space and a lower-level state space, and setting upper-level action spaces and lower-level action spaces that match each level of state space; vectorizing the upper-level state space, lower-level state space, upper-level action space, and lower-level action space; constructing and training a high-fidelity heat pump thermal management simulation environment model containing upper-level and lower-level strategy modules; obtaining the current upper-level state vector and the current lower-level state vector; and using the trained high-fidelity heat pump thermal management simulation environment model for online inference to obtain actual actuator control commands. This invention can effectively alleviate the long-term and short-term conflict between passenger cabin comfort, battery thermal safety, drive system thermal reliability, and vehicle energy consumption.

The application provides a signal carding method and system for control system reconstruction, which comprises the following steps: obtaining multi-source engineering files of a control system to be reconstructed and extracting signal related information; performing consistency comparison on overlapping information from different files for the same object, and recording inconsistent available information as inconsistent information; integrating available information sets based on the corrected inconsistent information and the information passed by the consistency comparison; analyzing the available information sets based on preset identification rules, reversely identifying a complete signal set for the reconstruction design, and generating corresponding attribute information sets for each signal to form a final I / O list for the reconstruction. Through the establishment of a systematic reverse carding process and signal identification rules for analog / relay systems, the application solves the problems of incomplete, inaccurate and inconsistent signal carding with the state of the art in the in-service reconstruction project, and provides an accurate and reliable data basis for subsequent reconstruction design.

The application discloses a water conservancy and hydropower engineering construction management system and relates to the technical field of water conservancy and hydropower engineering construction. In view of the problems of static management and lagging interference response of the existing system, the system comprises a multi-source data acquisition module, an interference source identification and grade evaluation module, a resource demand prediction module, a resource linkage deployment module and a warning and feedback optimization module, and forms a closed-loop management process. The system improves the accuracy of dynamic interference source identification to more than 92%, shortens the resource deployment response time by 60%, and reduces the engineering safety accident rate by 40%, and is suitable for the management of various water conservancy and hydropower engineering constructions.

This application relates to the field of corrosion assessment model construction technology, specifically to a method and system for constructing an intelligent assessment model for corrosion in subsea pipelines. The method includes: discretizing a concave pipe section into multiple series-connected computational containers based on pipeline elevation characteristics; determining the impact mass of liquid plugs overflowing into the rising pipe section; constructing a scour characteristic index characterizing mechanical scour intensity; using historical detection data to extract the corrosion depth corresponding to the chemical corrosion rate benchmark value, obtaining the erosion wear depth component; performing regression analysis based on the scour characteristic index and the erosion wear depth component to determine the wear conversion factor and establish a mapping relationship between the scour characteristic index and the mechanical scour rate; integrating the chemical corrosion rate benchmark value and the mapping relationship to construct an intelligent assessment model for corrosion in subsea pipelines, used to output the comprehensive corrosion rate of the subsea pipeline based on real-time operating parameters. This allows for accurate early warning of high-risk thinning events in the pipe wall of the rising section, significantly reducing the engineering risk of subsea pipeline perforation and leakage.

The invention discloses a porosity sandstone fault zone closure evaluation method and related equipment, belongs to the technical field of geology, and realizes digitization and refinement of an evaluation process through detailed geological exploration and sampling data acquisition in combination with classified arrangement of physical parameter data and multi-parameter model construction. The method not only improves the accuracy of evaluation, but also enhances the comprehensiveness of evaluation by comprehensively considering a plurality of influence factors. A three-dimensional digital model is used for physical parameter simulation calculation, and visual display and efficient analysis of evaluation results are achieved. The method not only improves the evaluation efficiency, but also enables the evaluation result to have a more scientific basis, and provides powerful support for engineering practices such as oil-gas exploration and underground water development. Through rapid iteration and optimization, the method can flexibly meet the requirements of closure evaluation under different geological conditions, reduces the engineering risk, and guarantees the practicality and reliability of the evaluation result.

The invention discloses a Railway engineering reinforcement cage quality detection method based on Reighting fusion. The method comprises the following steps: calibrating a camera based on Reighting fusion; original images of the railway engineering reinforcement cage are obtained through a camera array and spliced; classifying and marking various types of reinforcing steel bar images in the reinforcing steel bar framework; performing instance segmentation learning based on an artificial intelligence algorithm, and generating a weight file; collecting railway engineering reinforcement cage production and processing image data; reinforcing steel bar framework data in the image are recognized through artificial intelligence; analyzing and extracting steel bar image data, and comparing with design to generate a detection result; and receiving and displaying detection result data through the platform. Geometric information identification is performed on the reinforcement cage based on a deep learning technology, high-precision and high-efficiency non-contact automatic reinforcement cage quality detection is realized through matching with design information, and data accuracy and operation safety are remarkably improved.