2364 results about "Structural safety" patented technology

The invention relates to the technical field of bridge structure safety monitoring and maintenance, and discloses a road bridge real-time monitoring and maintenance system based on intelligent perception, which comprises a data acquisition module used for acquiring multi-dimensional data of a bridge operation state through a deployed multi-source sensor, the multi-source sensor comprises a vibration sensor, a strain sensor, a temperature and humidity sensor and image acquisition equipment; the data preprocessing module is used for carrying out cleaning, synchronization and feature extraction on the collected multi-dimensional data to obtain dynamic features, environment features and visual features; and a data fusion module. According to the method, the comprehensiveness and accuracy of bridge monitoring are improved through multi-source data fusion, the reliability of an evaluation result is ensured in combination with physical constraint optimization, health trend prediction and early warning functions are realized based on a time sequence model, scientific decision support is provided for bridge maintenance, and the monitoring and management efficiency is improved.

The invention discloses a bolt looseness online monitoring method and system, and the method comprises the steps: collecting an original data set containing a vibration signal of bolt connection, temperature gradient data and structural stress distribution through a multi-mode sensor array, and carrying out the time-space alignment and frequency domain decomposition processing of the original data set, obtaining a multi-dimensional feature matrix of the bolt nodes; based on the multi-dimensional feature matrix, a graph neural network model is adopted to carry out bolt looseness probability calculation, and a real-time looseness probability value of each bolt is output; generating a risk level map based on time evolution according to the real-time loosening probability value; and the risk level map is mapped in real time through a three-dimensional visual interface, and when it is detected that the bolt loosening risk level exceeds a preset threshold value, an early warning message is generated and uploaded to an operation and maintenance platform, and closed-loop monitoring response is completed. According to the embodiment of the invention, accurate assessment, dynamic prediction and visual early warning of the loosening risk can be realized, and the intelligent level of structure safety monitoring is improved.

The invention discloses a wind turbine generator hoisting construction tower drum operation system and a construction method thereof, and relates to the technical field of intelligent control. The problems that in the prior art, a static tension balance mechanism cannot restrain bending moment abrupt change, steel-concrete interface stress concentration causes microcrack propagation, the wave dynamic load compensation capacity is insufficient, and dynamic rigidity attenuation early warning is lacked are solved. Comprising a dynamic load prediction module, a multi-mode vibration suppression module, an offset compensation module and a digital twinborn decision module, a hoisting load is solved in real time through a multi-physics field coupling model and an improved time sequence deep learning algorithm, and interface crack propagation is suppressed in combination with traveling wave offset control and sweep frequency vibration. An improved Morison equation is adopted to drive a two-stage hydraulic servo to compensate a wave dynamic load, and a digital twin closed-loop correction mechanism is constructed based on a 5G URLLC protocol; the tower drum hoisting precision, the structural safety and the operation reliability under the complex working condition are remarkably improved.

The invention discloses a wharf armor block quality detection method, and belongs to the technical field of concrete structure detection.The method comprises the steps that a surface model is constructed through a movable three-dimensional laser scanning device, and a high-risk defect area is recognized; performing encryption scanning and impact echo detection in the high-risk area by adopting a frequency-adjustable dual-mode flaw detection device to generate a three-dimensional defect distribution diagram; a core sample is drilled in the defect area for compressive strength testing, and the material performance is analyzed in combination with a non-contact infrared spectrum; and establishing a dynamic evaluation model, calculating a safety coefficient by integrating surface defects, internal defects and material discreteness data, and generating a three-dimensional visual report. The problems that a traditional detection method is low in efficiency, insufficient in internal defect positioning precision, one-sided in material performance evaluation and the like are solved, full-dimensional detection from the surface to the interior and from the macroscopic level to the microscopic level is achieved through a multi-source data fusion and closed-loop feedback mechanism, and the reliability of structural safety evaluation and the scientificity of maintenance decision are remarkably improved.

The invention relates to the field of building structure safety detection, and discloses a building structure anti-seismic performance monitoring method and system. The method comprises the following steps: acquiring multi-source response data such as acceleration, displacement, strain and inclination angle; obtaining a structure standard response based on wavelet denoising and standardization processing; adopting a multi-order modal recognition algorithm to extract structural dynamic characteristic parameters; performing structural damage evaluation based on the modal change index, and combining the yield strength, the load index and the displacement margin to calculate the residual bearing capacity of the structure; and finally, outputting an anti-seismic grade early warning signal. The system comprises a structure response acquisition module, a modal identification and damage evaluation module and a residual bearing capacity calculation and early warning module. According to the method, real-time quantitative analysis of the performance of the structure under the earthquake or load effect can be achieved, the evaluation precision is high, the applicability is high, and the wide engineering popularization value is achieved.

The invention specifically relates to the technical field of big data analysis, and discloses a water conservancy gate multi-parameter cooperative intelligent monitoring system, which comprises a multi-parameter acquisition module, a multi-parameter processing module, a comprehensive analysis module, an intelligent decision module, an operation and maintenance early warning module and a man-machine interaction module, the multi-parameter processing module is used for calculating flood control and discharge indexes, structure safety indexes and equipment health indexes; the comprehensive analysis module is used for judging gate risk levels; the intelligent decision-making module is used for generating an optimal gate scheduling scheme; the operation and maintenance early warning module is used for constructing a multi-level early warning mechanism; according to the method, parameter coverage is comprehensive, a gate digital twinborn model and a gate opening comprehensive evaluation model are constructed, the gate risk level is evaluated, an optimization strategy is dynamically adjusted through an intelligent decision module, the accuracy of gate risk judgment is improved, and the self-adaptive capacity of the system is improved.

The invention discloses a digital intelligent management method and system for hydraulic engineering construction, particularly relates to the technical field of hydraulic engineering construction management, and is used for solving the problems of regulation lag and insufficient environmental disturbance adaptability of an existing method under the action of multi-physics field coupling. According to the method, a concrete three-dimensional temperature field model is established, initial regulation and control parameters are generated, and a heat conductivity coefficient under the seepage influence is corrected based on space-time relevance of pore water pressure and temperature data; the constraint boundary is dynamically adjusted in combination with the construction progress and the material strength curve, a cooling water pipe coordinated regulation and control matrix is constructed, and target flow instructions of space differentiation are generated through the included angle between the distance and the water flow direction; setting a lag time threshold and optimizing an execution time sequence according to the thermal inertia parameter, splitting the threshold and allocating a weight coefficient when the environmental wind speed suddenly changes, and finally updating the model parameter and the regulation and control instruction; accurate temperature control response and abnormal heat conduction suppression under multi-field coupling are achieved, and the structural safety and construction efficiency under complex working conditions are improved.

The invention discloses a road bridge design method and system based on a BIM real scene model, and relates to the technical field of constructional engineering information, and the method comprises the steps: a BIM model carries out multi-objective optimization through a quantum annealing algorithm in combination with a bridge-crossing topology library, synchronously optimizes topological connectivity, structural stress and energy consumption indexes, generates a parameterized component, and feeds back the parameterized component to the BIM model; the model of the BIM model is loaded and optimized based on augmented reality equipment, the model is superposed to a reality scene through space anchoring, and the BIM model is corrected in combination with a conflict monitoring engine and a knowledge graph; the corrected BIM model is deployed to edge computer equipment, a dynamic deviation thermodynamic diagram is generated by scanning a construction surface, a lofting robot is driven to execute coordinate dotting, and meanwhile construction error data is transmitted back; according to the method, the problem that a global optimal solution is difficult to find when a traditional optimization algorithm is used for processing a complex multi-target problem is solved by utilizing an advanced quantum computing technology, and the economical efficiency and the structural safety of bridge design are greatly improved.

The invention relates to the technical field of bridge digital twinborn platform construction, and particularly discloses a Unity 3D bridge digital twinborn platform construction method integrated with a Midaas-Civil calculation function, and the method carries out the real-time monitoring and evaluation of a bridge through a digital twinborn technology, thereby improving the structural safety and maintenance efficiency of the bridge. The method comprises the following steps: acquiring stress distribution data of a bridge in real time through bridge monitoring equipment, and analyzing a stress concentration area in a digital twin platform; a crack propagation rate and a stress gradient change value are extracted, a comprehensive feature vector is constructed, the current state of the bridge is evaluated by using a machine learning model, and a high-risk area is identified according to an evaluation result; the maintenance strategy of the bridge is dynamically optimized by predicting the future crack expansion trend and stress distribution change of the low-risk area; and on the basis of a risk assessment result, a resource optimization allocation model is constructed, optimal allocation and dynamic adjustment of bridge maintenance resources are realized, and accurate implementation of a maintenance strategy is ensured.

The invention discloses a system and a method for predicting the fatigue life of a flange by utilizing ultrasonic flaw detection, and belongs to the field of artificial intelligence. Comprising an aggressive frequency domain spot feature extraction module, a microdefect enhancement recognition module, an acoustic echo database training module, a damage accumulation-stress wave mapping model construction module, an active echo disturbance injection module, a fatigue life progressive prediction module, a real-time feedback closed-loop control module and a multi-scale self-checking redundancy mechanism module. Spot feature extraction and defect identification share high-frequency phase data to generate a focusing map, and registration with historical defect features is carried out in a database; the mapping model constructs a stress-damage relation according to the stress concentration coefficient and the frequency domain characteristics; the disturbance injection module applies directional excitation to potential fatigue points, and the prediction module constructs a life evolution curve based on response; the feedback control module fits and corrects the database and the disturbance strategy; the self-checking mechanism improves the prediction robustness and self-adaptability through waveform deviation and mismatch correction. The beneficial effects are that the structure safety and the service life management intelligence are improved.

The invention relates to the technical field of structure health monitoring, and discloses an underground pipe gallery structure corrosion monitoring and evaluation method based on optical fiber sensing, which comprises the following steps: constructing a composite optical fiber sensing structure which comprises a Fe-C alloy coated optical fiber and a long-period grating, synchronously monitoring the chemical component change and the structural mechanical state of the corrosion product through the photoluminescence spectrum characteristic peak displacement and the strain distribution cloud picture; measuring deviation caused by coating layer loss is dynamically corrected in combination with the change rate of the environment refractive index; a reference grating is embedded to eliminate temperature drift interference, and iron ion in-situ deposition is triggered to realize sensing interface self-repairing. According to the invention, through a multi-physical-quantity cooperative sensing and self-adaptive compensation mechanism, the problems of signal interruption and the like caused by difficult decoupling of chemical-mechanical parameters and film coating failure in traditional monitoring are avoided, the long-term stable monitoring capability of a corrosion process in a complex environment is remarkably improved, and high-precision data support is provided for safety assessment of an underground pipe gallery structure.

The invention relates to the technical field of crack detection, in particular to a building crack intelligent detection and prediction method based on multi-modal data fusion, which comprises the following steps: constructing a multi-source heterogeneous data set including an image data set, a thermal imaging data set and a vibration data set; simulating complex environment interference through a GAN (Generative Adversarial Network), and dynamically enhancing image training data; designing a double-branch multi-mode fusion network, and extracting the edge and texture features of the crack; designing a multi-modal fusion branch, and carrying out feature alignment and weighted fusion on vision, thermal imaging and vibration data; and based on a long short-term memory network LSTM and a structural mechanics model, a crack trend prediction module is developed, and early warning is provided for building structure safety. According to the method, intelligent monitoring and early warning of building structure safety are realized by constructing a multi-source heterogeneous data set, enhancing image training data through a GAN, extracting features by using a double-branch multi-mode fusion network, predicting a crack trend based on an LSTM and a structural mechanical model, and finally integrating system deployment.

The invention relates to the technical field of unmanned aerial vehicle inspection, in particular to an intelligent unmanned aerial vehicle bridge slope crack detection and early warning system, which comprises an unmanned aerial vehicle cruise unit and a detection and early warning management unit, and is characterized in that the unmanned aerial vehicle cruise unit is used for performing autonomous flight inspection on a bridge slope in a target area according to a preset period; the visible light image, the infrared thermal imaging and the three-dimensional laser point cloud data of the target area are synchronously obtained; the detection and early warning management unit is used for processing the image data acquired by the unmanned aerial vehicle cruise unit in real time through a pre-trained crack intelligent analysis algorithm, extracting geometric features and thermodynamic features of the crack, constructing a time sequence model to predict a crack expansion trend and a structure safety risk level, and outputting the crack expansion trend and the structure safety risk level. A multi-level early warning signal is generated based on the risk level and is pushed to the maintenance terminal; the geometrical characteristics comprise crack depth and strike angle, and the thermodynamic characteristics comprise abnormal temperature gradient distribution. The problems of long detection period, high cost and terrain limitation in the prior art are solved.

The invention relates to the technical field of structure inspection, in particular to a bridge pier underwater structure inspection system based on an unmanned underwater robot, which comprises an inspection period adjustment module, an anomaly recognition module, an automatic supplementary shooting module, a damage evaluation module and a bridge pier anomaly evaluation module. According to the invention, bridge pier underwater structure inspection is executed through the unmanned underwater robot, the inspection period is dynamically adjusted according to the traffic flow, fine management of inspection work is realized, the inspection frequency can be adjusted according to actual use conditions and external influence factors, potential structure problems are effectively prevented and found, and the inspection efficiency is improved. The damage area can be quickly and accurately calibrated by image acquisition and automatic anomaly recognition performed by the unmanned robot, supplementary shooting is performed when necessary, the image quality is improved, the data reliability is ensured, and the influence of damage on the structural safety can be accurately evaluated by comparing the positions and overlap ratios of the damage area and the key bearing area of the bridge pier, so that the safety of the bridge pier is improved. And a scientific basis is provided for maintenance decision.

The invention relates to the technical field of building curtain wall keel structure design, and discloses a curtain wall keel structure intelligent optimization design method, which comprises the following steps: firstly, obtaining geometric parameters, load distribution data and material performance indexes, and verifying the geometric parameters, the load distribution data and the material performance indexes; analyzing the verified data to generate multi-dimensional structure characteristic parameters, and constructing a structure optimization reference model; keel structure data are verified in real time according to the model, and abnormal matching of node displacement and stress distribution is quantitatively evaluated; according to a verification result, generating a structural anomaly index to judge a design defect; and when defects exist, optimization design schemes including keel section adjustment, node reinforcement and the like are automatically generated and sequenced. According to the method, multiple factors are comprehensively considered, multi-objective optimization is achieved, the curtain wall keel structure design quality and efficiency can be improved, the structure safety is guaranteed, and the cost is reduced.

The invention discloses a fabricated building curtain wall assembly control system and method in the technical field of building industrialization. The method comprises the steps that building curtain wall assembly data are obtained; respectively inputting the building curtain wall assembly data into the module adaptation degree calculation model, the dynamic load distribution calculation model and the connection efficiency evaluation function calculation model to obtain an adaptation degree coefficient, a dynamic load value and a connection efficiency index; performing dynamic adaptation on the curtain wall unit and the building main body structure based on the adaptation degree coefficient; performing real-time positioning deviation compensation in the installation process based on the dynamic load value; and performing quantitative control on the connection node strength and the overall load distribution based on the connection efficiency index. Compared with the limitation of geometric accuracy and structure safety separation control in the traditional process, the scheme synchronously completes curved surface matching degree improvement and aerodynamic performance optimization in the curtain wall unit installation process, and the industrial pain point that modeling accuracy and wind resistance of a special-shaped curtain wall are difficult to consider at the same time is fundamentally solved.

The invention discloses a power monitoring regulation and control system and method used in the operation process of a ship lock miter gate, and relates to the technical field of ship locks. The method comprises the following steps: firstly, monitoring the vibration state of each structural member of the ship lock miter gate, calculating a rigidity evaluation value of the ship lock miter gate, adjusting an electric control signal of a proportioning pump according to the rigidity evaluation value, and optimizing the non-deformability of a gate body structure; secondly, the dynamic stress of the door body is monitored, the dynamic stress safety evaluation value of the ship lock miter gate is obtained, the output frequency of the motor is adjusted through the frequency converter, and structural overload can be avoided; and finally, the back pull rod prestress monitoring and adjusting module adjusts the prestress of the back pull rod in combination with the vibration state, the dynamic stress and other characteristic data, so that the stability and the structural safety of the door body are kept. Structural damage caused by excessive vibration or stress overload can be avoided, the service life of equipment is prolonged, and stable operation of a ship lock system is ensured.

The invention provides a quick physical examination method for a brick-concrete building structure based on multi-modal tight coupling SLAM, and the method comprises the steps: introducing a laser residual error, a visual residual error, a thermal image residual error and an IMU (Inertial Measurement Unit) pre-integration residual error into a factor graph, and constructing a real-time positioning and mapping frame which can still achieve high precision and stronger robustness in a weak illumination and texture missing scene. In the mapping process, the system synchronously operates crack width and temperature difference double-threshold identification and wall slope rate evaluation, and risk identification and marking of dangerous cracks and inclined walls are completed in real time. According to the method, a three-dimensional building model with a semantic standard is generated, an integrated closed-loop process integrating'multi-modal perception, high-precision mapping, crack and inclination risk judgment and instant output early warning 'is formed, and the high-timeliness and high-precision structural examination requirements of'risk judgment by scanning' on old brick-concrete buildings are met. The method is suitable for scenes such as city updating, dangerous building general survey and rural self-built house structure safety monitoring, and the efficiency and reliability of building rapid screening are remarkably improved.

The invention discloses an overhead layer climbing frame wall-attached support steel truss stand column safety monitoring system fused with big data analysis, relates to the technical field of construction monitoring, and is used for solving the problem of recognition misjudgment caused by construction disturbance. According to construction behavior control signals, behavior labels are extracted, a semantic mapping relation between construction behaviors and structure responses is constructed, a behavior-driven data set is generated, a disturbance change trend is extracted through node response tensor and time difference analysis, the behavior labels are fused to construct a structure state vector, and a structure behavior distribution model is established. Analyzing the deviation degree between the current state and the model response, identifying the propagation path of the anomaly in space by combining a structure layout diagram, extracting a high-risk abnormal block mass region by adopting a diagram clustering method, analyzing the structural state change and construction behavior of the abnormal region, triggering different monitoring response strategies, and obtaining a high-risk abnormal block mass region; the structural risk identification and control in the construction process are realized, and the structural safety monitoring efficiency in the floor construction stage is improved.

The invention relates to the technical field of structural health monitoring and geotechnical engineering, and discloses a breakwater foundation settlement direction real-time monitoring and early warning system and method, and the system comprises a data collection module which is used for obtaining the measurement data of at least one sensor disposed on a breakwater and a foundation of the breakwater in real time; the storage module is used for storing a preset physics-based reduced-order model, and the reduced-order model represents the overall deformation rule of the breakwater and the foundation system through a group of core deformation modes; and the processing module is connected with the data acquisition module and the storage module, and the processing module comprises a data assimilation module which is used for fusing the measurement data and the order reduction model in real time. By arranging the deformation field reconstruction module, the problem that only discrete point information can be obtained through traditional monitoring is effectively solved, real-time and high-precision expansion from sparse measurement to a continuous overall deformation field is achieved, and a more visual and reliable basis is provided for comprehensively evaluating the safety state of a structure.

The invention discloses a BIM-based hoisting construction supervision optimization management system. The system comprises a sensing layer which collects multi-source heterogeneous data in real time; according to the decision-making layer, a bottom layer utilizes an incremental RRT # algorithm to generate candidate paths meeting crane kinematics constraints, a distributed Q-learning framework is embedded in an upper layer, all cranes serve as independent agents, collaborative learning is carried out through a shared experience pool, a path planning strategy is dynamically optimized according to environment sensing data and construction progress requirements, and a path planning strategy is established. Meanwhile, a fuzzy sliding mode control algorithm is developed to be combined with an LSTM-Transformer crane cart and trolley walking speed, a hook crane cart and trolley walking speed, a hook lifting speed and a steel wire rope disturbance prediction model to calculate crane motion compensation parameters, and an optimal control instruction is generated in advance based on predicted crane moving walking and lifting data; the execution layer is used for issuing the instruction generated by the decision-making layer to construction equipment; and the optimization layer is used for constructing a BIM model and feeding back an equipment execution result and structure safety monitoring data to the decision-making layer.

The invention relates to the technical field of civil engineering structure safety monitoring and aircraft image detection, and discloses a safety quantification nondestructive monitoring method and system based on an aircraft concrete structure, and the method comprises the steps: constructing a multi-target path optimization model, and generating a track point sequence; the aircraft collects an image and calculates an image reliability score; identifying crack and spalling defects by using a deep learning model; calculating a structure risk index SFI based on a partial least squares regression model; a monitoring report is generated and uploaded to the cloud. The technical problem that in the prior art, the safety quantitative evaluation based on the in-flight image structure cannot be realized by depending on a manual inspection or static image recognition mode, especially under the conditions of a special-shaped curved surface structure, shielding of a complex area or violent illumination change is solved. Due to the fact that three-dimensional path optimization, an image reliability scoring mechanism and AI defect recognition are fused, intelligent recognition of structure surface covering and crack peeling is achieved, and the automation degree of concrete structure monitoring is improved.

The invention discloses a temperature effect monitoring method and system for a metal roof, particularly relates to the technical field of building structure health monitoring, and is used for solving the problems of decoupling of temperature monitoring data and structural mechanical response, failure of a static early warning threshold and the like in the prior art. Acquiring three-dimensional temperature field data through a distributed temperature sensing network, and extracting a temperature gradient characteristic value from the three-dimensional temperature field data; a piezoelectric film sensor is used for collecting constraint point micro-vibration signals, and dynamic constraint reaction force spectrum characteristic values are extracted through signal transformation and manifold learning; establishing a temperature gradient and mechanical characteristic coupling model to generate a temperature stress evaluation value; dynamically adjusting an early warning threshold range according to the environmental parameters; when the evaluation value exceeds a threshold value, a structure safety early warning signal is output; multi-physical field coupling analysis of temperature field distribution and structural response is achieved, an environment-adaptive dynamic early warning mechanism is constructed, and the accuracy and reliability of metal roof temperature effect monitoring are remarkably improved.

The invention discloses a multi-parameter collaborative optimization design method for lateral impact resistance of a honeycomb sandwich panel battery pack, and relates to the technical field of structural safety and lightweight design of new energy automobile battery packs. An existing battery pack generally has the defects of insufficient light weight, limited energy absorption efficiency and lack of multi-parameter collaborative optimization with an upper box body, a lower box body and a stiffening beam in impact resistance research. Therefore, according to the honeycomb sandwich panel battery pack lateral impact resistance multi-parameter collaborative optimization design and parameter calculation method, a honeycomb sandwich panel finite element model is established, performance parameters are obtained, an optimal energy absorption combination is screened, then a battery pack box body finite element model is established, and multiple design variables are set; and constructing a function relationship between variables and responses by utilizing an agent model, and carrying out multi-objective optimization by combining an NSGA-II algorithm to finally obtain an optimal design parameter meeting a safety threshold and carrying out simulation verification. The method is suitable for battery pack anti-impact protection design work of the electric automobile under the lateral collision working condition.

The invention provides an automatic evolution method and system for a building design parameterization data driven scheme, and relates to the field of building design, and the method comprises the steps: firstly obtaining a building design parameterization basic data set containing building function requirements, structural safety, spatial layout, environment adaptation and other parameters; the method comprises the following steps: generating an architectural design parameter dynamic constraint model by using a parameter constraint dynamic iterator, generating an initial scheme through a parameterization scheme intelligent evolution model, starting a scheme iteration evolution closed-loop process to obtain an intermediate scheme, and finally screening out a target architectural design evolution scheme and outputting related parameterization process associated data. Automatic and intelligent generation and optimization of the building design scheme are realized.

The invention provides a house structure safety detection method and system based on multi-modal sensing fusion, and relates to the technical field of house structure safety detection. The method comprises the following steps: acquiring multi-modal sensing data such as vibration, acoustic emission and temperature of a key part of a house structure; performing noise reduction, normalization processing and time sequence alignment on the data; extracting dynamic response features and environmental response features; calculating a dynamic stress index (DSI) and a composite stability factor (CSF); generating a real-time safety score of the house structure based on a multi-modal data fusion algorithm; judging whether potential safety hazards exist or not according to the safety score; after the hidden danger is confirmed, alarm information is generated and pushed to a user terminal. Through multi-modal data fusion, the safety of the house structure can be accurately evaluated, real-time monitoring and early warning are provided, and the long-term stability and safety of the house structure are enhanced.

The invention discloses a digital modeling steel structure multi-dimensional collaborative optimization design method and system, belongs to the technical field of steel structure design, and aims to solve the problems that multi-dimensional comprehensive consideration and automatic optimization tools are lacked, and complex multi-objective optimization requirements are difficult to quickly respond. Comprising the steps of establishing a full-parameterized digital model containing construction process parameters and environmental protection indexes, constructing a multi-objective evaluation system of structural safety, economical efficiency, construction feasibility and environmental influence, performing automatic optimization by adopting an improved multi-objective evolutionary algorithm, selecting 10 groups of candidate schemes, generating a visual interface, supporting human-computer interaction decision, and generating an optimization report. According to the method, multi-dimensional collaborative optimization is realized by constructing a multi-target evaluation system of structural safety, economy, construction feasibility and environmental influence, construction process parameters and environmental protection indexes are integrated through the digital modeling unit, it is ensured that factors of all parties are comprehensively considered in design decision, and the design efficiency is remarkably improved.

The invention relates to the technical field of data processing, and discloses a three-section combined structure design method and system for an ultrahigh wind power generation tower. The method comprises the following steps: analyzing wind speed distribution data through a wind load-structural dynamics-material mechanics coupling algorithm to obtain rigidity distribution functions and frequency avoidance constraints of three functional partitions, performing multi-objective optimization on a lower truss section to obtain geometric parameter configuration, performing fluid-solid coupling vibration control design on a middle multi-edge transition section, and performing multi-functional partition design on the middle multi-edge transition section. And aeroelastic instability prevention and control design is carried out on the upper cylindrical section, integrated dynamic coordination processing is carried out on the three-section structure, multi-working-condition verification is carried out through a large eddy simulation-finite element coupling verification algorithm, and target design parameters are obtained. The wind power tower drum solves the technical problems that the existing wind power tower drum technology cannot break through the limitation of the 360-meter super height and cannot meet the requirements of structural safety, economical efficiency and constructability at the same time.

The invention discloses a steel reinforced concrete member full-period management method based on industrial big data. The method comprises the steps that a member model is established through BIM modeling software, an easily-buckling area is screened in combination with finite element buckling analysis, a buckling monitoring point is arranged on the surface of an analysis plate body, and a plate body monitoring point is arranged on the splicing edge; extracting model coordinate data to generate processing parameters, and guiding plate cutting and monitoring point position marking; actual coordinates of all monitoring point positions in the profile steel component are obtained through laser scanning and compared with model coordinates, and reworking is triggered if errors exceed the limit; constructing a neural network model, inputting various parameters related to analysis of plate body buckling to obtain a predicted buckling monitoring point out-of-plane displacement value, and judging compliance; according to the method, the problems of low efficiency, error accumulation and lack of full-period closed-loop management of a traditional method are solved, the machining precision and the structural safety of the steel reinforced concrete member are remarkably improved, and the hardware cost and the detection time consumption are reduced.

The invention discloses a dynamic response regulation and control and vibration reduction system and method for a floating type photovoltaic platform in the technical field of offshore new energy equipment, and aims to improve the anti-wave stability and structural safety of the platform under complex sea conditions. The system comprises a platform main body, a monitoring unit, a response analysis and early warning unit and a regulation and control execution unit, the monitoring unit is arranged on the platform main body and is used for collecting real-time sea condition data; the response analysis and early warning unit is in communication connection with the monitoring unit and is used for performing response analysis on the real-time sea condition data and sending an early warning signal to the regulation and control execution unit when the abnormal working condition of the platform main body is identified; and the regulation and control execution unit is used for carrying out regulation and control and vibration reduction on the platform main body according to the received early warning signal. According to the method, the assembly fatigue can be obviously relieved, the cable damage probability is reduced, the service life of the platform is prolonged, and good engineering adaptability and intelligent expansion potential are achieved.