492 results about "Computational analysis" patented technology

The embodiment of the invention discloses a life omics research method and device based on artificial intelligence, and the method comprises the steps: carrying out the preprocessing of a project according to the intelligent interaction between a user and a system, and generating standardized data; and meanwhile, carrying out transfer learning on the large language model to construct a life science large language model. And according to the standardized data, decomposing a research target by adopting a life science big language model in cooperation with an intelligent agent, and generating an analysis plan. And based on the analysis plan, the intelligent agent is scheduled through the coordinator, and a hierarchical task is generated. And calling a multi-omics analysis tool by the intelligent agent to calculate and analyze the grading task, and outputting an analysis result. And based on data features, integrating analysis results through an integrated advanced model, and outputting a final report to complete the research of life omics. According to the embodiment of the invention, full-process automation and natural language interaction are realized, the standardization of data analysis and the repeatability of results are ensured, the research efficiency is remarkably improved, and the technical threshold is reduced.

The invention discloses a nondestructive testing method for infrared thermal imaging spatio-temporal information fusion, which relates to the technical field of nondestructive testing and comprises the following steps: establishing a linear laser heat source scanning infrared thermal imaging nondestructive testing system; collecting a dynamic infrared thermal image sequence; and calculating and analyzing dynamic infrared thermal image sequence data, and carrying out data processing on the acquired dynamic infrared thermal image sequence by using an infrared thermal imaging spatio-temporal information fusion post-processing method to obtain a full-field thermal response image with surface crack defects. According to the method, spatio-temporal information can be fused to obtain data with higher resolution, more comprehensive and accurate full-field thermal response characteristics are obtained while the calculation efficiency is improved, the method has better flexibility and wider applicability, and the purpose of nondestructive detection of metal surface defects is achieved.

The invention provides a house waterproof maintenance system based on an intelligent detection and self-repairing technology, and the system comprises an intelligent sensing layer which is used for collecting multi-dimensional physical parameters of building waterproof key nodes in real time; the edge calculation analysis layer is used for performing fusion analysis and risk prediction on the perception data; the dynamic self-repairing execution layer is used for triggering a multi-stage repairing mechanism according to an analysis result; the cloud management layer is used for realizing visual management and control and strategy optimization of the whole system, and relates to the technical field of building waterproofing, the building state is monitored in real time through a multi-mode sensing network, water leakage risk prediction is realized in combination with an edge calculation algorithm, and collaborative repair of a microcapsule repair agent, a shape memory alloy grid and an electrodialysis module is triggered; the system remarkably improves the timeliness and reliability of waterproof maintenance, reduces the manual intervention cost, and is suitable for intelligent maintenance of residential buildings, industrial buildings and historical protection buildings.

The invention, which relates to the technical field of traffic management, discloses an intelligent detection system for a vehicle parking space in a passenger and goods mail fusion station, and the system comprises a multi-mode sensing module which is configured to collect vehicle data information, the collection mode comprises the steps that vehicle data information is collected through an enhanced geomagnetic array, an adjustable video monitoring set, a lateral laser radar and a piezoelectric sensor; and the edge computing node module is configured to integrate an AI chip, the AI chip comprises a vehicle classification model, an abnormal parking detection algorithm and a data fusion engine, and the collected data is computed and analyzed. The edge computing node is integrated with an AI chip, and data are analyzed and processed through a built-in algorithm; the hybrid communication network transmits data through an optical fiber backbone network and a specific redundant link, self-adaptive visual adjustment and intelligent algorithm optimization are performed, the problem of complex vehicle type detection in a passenger and goods mail fusion station is solved, and the parking space utilization rate and the operation efficiency are remarkably improved.

The invention belongs to the technical field of BIM (Building Information Modeling), and particularly relates to a curved surface composite truss design and construction integrated method and device based on the BIM technology. The method comprises the following steps: considering four structural schemes for a building facade, generating a corresponding parameterized structural topology and a three-dimensional structural line model, adding a load, calculating, analyzing and optimizing a cross section, and generating four structural calculation models and building scheme models; the building space effects and the structure force transmission efficiency of the four structure schemes are compared, and the optimal one is selected as an implementation scheme; and forming a full-professional BIM model according to the selected implementation scheme. Building datamation is achieved through the BIM technology, digital delivery of design results is achieved, the link of two-dimensional plotting is reduced, steel structure deepening is further conducted through the BIM model in the construction stage, visual deduction is conducted on key procedures such as steel structure machining, assembling and hoisting, and digital construction is achieved.

The invention discloses an intelligent regulation and control method and system for a dust removal system of an iron and steel enterprise, and the method comprises the following steps: collecting real-time data according to a set frequency, including the operation parameters of each dust production point, the opening degree of a valve, and the operation parameters and exhaust condition parameters of a dust remover, dust conveying equipment and a fan, and dividing the data into operation variables and regulation variables; a hybrid neural network model is constructed, the hybrid neural network model comprises an LSTM-GPT-Neo backbone network, a DenseNet branch network and a meta learning feature fusion correction layer, and the LSTM-GPT-Neo backbone network fuses an LSTM architecture and a GPT-Neo architecture; inputting time sequence data to carry out model training and optimization; and inputting the data into the trained hybrid neural network model for calculation and analysis, and outputting the opening degree of the valve and the optimal operation parameters of the fan. Under the condition that the dust removal efficiency and stability are guaranteed, the electricity utilization cost of the steel plant can be remarkably reduced, and the problem of equipment loss caused by excessive dust emission or excessive air volume due to insufficient air volume is avoided.

The invention relates to the technical field of fault prediction and health management, in particular to a primary and secondary fusion complete ring main unit fault diagnosis method and system. Comprising the following steps: acquiring three-phase instantaneous voltage and current signals in real time, and converting the signals into digital transient data; performing time window preprocessing on the digital transient data, and executing wavelet packet decomposition to generate a transient feature vector; calculating and analyzing the transient feature vector through a transient zero-sequence power direction method and a support vector machine model to generate a local diagnosis result; when the local diagnosis result is that cooperative positioning needs to be started, a transient current similarity coefficient and a transient waveform intensity difference coefficient are calculated based on the digital transient data, and a comprehensive positioning result is generated; determining a fault line according to the comprehensive positioning result, and generating a remote control command; and executing a fault isolation operation based on the remote control command, and executing a PHM process. According to the method, the double local transient diagnosis and the cross-terminal cooperative positioning are deeply fused, so that the high-precision determination of the boundary of the fault section is realized.

The invention discloses an intelligent-based abnormal carbon emission data automatic identification early warning system, which belongs to the technical field of intellectualization and comprises a data acquisition preprocessing module, a high-precision space-time analysis module, an intelligent analysis module, an automatic abnormal identification module, a carbon footprint tracing module, a self-adaptive adjustment module and an intelligent emission prediction module. A carbon emission source and time-space distribution characteristics are accurately positioned through spatial positioning and time sequence analysis of the high-precision time-space analysis module, a spatial distribution diagram is more detailed and accurate through the optimized sensor position and an interpolation algorithm, and time sequence analysis is more accurate through timestamp correction and power spectrum density analysis. The method effectively evaluates the periodic intensity of the signal, analyzes a hidden mode and an association rule in the data through the intelligent analysis module integrating the spatial-temporal characteristics and the related information of the data acquisition and preprocessing module, analyzes the spatial-temporal association between variables through the calculation of a clustering center and the association intensity, and facilitates the discovery of a potential abnormal mode.

The invention discloses a spacecraft space environment safety guarantee system and method based on three-step calculation, and the system comprises two subsystems: a space environment data service subsystem and a three-step calculation and analysis subsystem, and the three-step calculation and analysis subsystem calls data and an algorithm model from the space environment data service subsystem. The space environment safety guarantee analysis based on the three-step calculation is executed; the space environment data service subsystem comprises a metadatabase and a comprehensive database; the metadatabase comprises space environment space-based monitoring data, space environment foundation monitoring data and data from a specified space environment mechanism; the comprehensive database comprises a space environment numerical calculation model library and a spacecraft business application rule algorithm model library; the three-step calculation and analysis subsystem comprises a sun-earth space environment analysis and calculation module, a spacecraft orbit ring layer environment analysis and calculation module and a spacecraft task influence risk assessment and calculation module, and three-step calculation is executed through the three modules.

The invention discloses a character recognition method and system based on a large model and an OCR technology, and relates to the technical field of character recognition, and the method comprises the steps: extracting picture information, carrying out the unified preprocessing, generating a text detection box of a character region through a DBNet lightweight text detection model, and obtaining a text position; quickly identifying characters in the textbox by using a lightweight OCR model to obtain text content, and generating an identification information group; carrying out average value calculation on the confidence coefficient of the lightweight OCR model result, and analyzing the overall confidence coefficient; and for the result with low confidence coefficient, inputting the corresponding identification information group into the multi-modal large model, and carrying out secondary identification. According to the method, the text position set and the text character string sequence are combined into the identification information group, so that the effect of structured storage of detection and identification results is achieved, subsequent information retrieval and multi-modal fusion analysis are facilitated, and the effect of optimizing the subsequent processing efficiency and precision is achieved through the combination of the confidence coefficient screening step.

The invention discloses a tire finite element modeling and multidirectional rigidity optimization method and system based on characteristic lines. The method comprises the following steps: extracting tire section characteristic lines from a three-dimensional digital model; introducing the tire section characteristic line into a finite element analysis environment, generating a three-dimensional tire geometric model by rotationally scanning the characteristic line, and performing grid division on the model; setting tire material attributes, performing zoning setting on the model according to a tire crown, a tire shoulder and a tire side wall, and setting tire thickness based on zoning; applying a constraint boundary condition at the center of the tire, and establishing a contact form of the tread and the ground; a progressive inflation pressure load is applied, the deformation state of the inflated tire is calculated, and longitudinal rigidity, radial rigidity and lateral rigidity calculation and analysis steps are set; the tire elasticity modulus and the cord fabric thickness are used as design variables, and an optimization algorithm is adopted to solve a multi-objective optimization function. The method has the advantages of being simple in modeling method and high in practical operability, the tire modeling threshold can be lowered, and the fund and time cost of refined modeling is reduced.

The invention discloses a water conservancy data acquisition device, and relates to the technical field of Internet of Things, and the device comprises the following steps: dividing a target water area into a plurality of monitoring water areas; performing characteristic factor analysis on each monitored water area to obtain a characteristic factor analysis result; adjusting the installation number and positions of the sensors in the monitored water area according to the characteristic factor analysis result, and obtaining hydrological data monitored in real time; performing edge calculation analysis on the hydrological data monitored in real time to obtain an edge analysis result; performing data synchronization on the edge analysis result and uploading the edge analysis result to a cloud platform to obtain cloud data; performing intelligent analysis on the cloud data to obtain a water area dynamic report; performing risk early warning according to the water area dynamic report; the acquisition device collects and analyzes hydrological data of different water areas by combining real-time data acquisition of a sensor and an edge calculation and analysis method. According to the method, loss and errors of hydrological data are reduced, and consistency, high efficiency, accuracy and timeliness of the hydrological data are enhanced.

The invention discloses a high-formwork optimization design method and system based on BIM and finite element analysis, and the method comprises the steps: S100, building a three-dimensional BIM model of a main body structure, and creating an intelligent parameterization frame body family which is mapped with a main body structure family and has a self-verification function; s200, importing a parameterized family and linking the main body model, generating a plurality of groups of frame body arrangement schemes through spatial topology analysis, and performing a three-dimensional collision test after optimization; s300, setting dynamic boundary constraints and construction loads in stages, and generating a geometric and mechanical integrated data packet; s400, data packet parameters are automatically mapped to finite element software through a plug-in, models are built in stages, multi-working-condition analysis is carried out, if the parameters exceed the limit, frame body parameters are modified, iterative optimization is carried out until the parameters meet the standard, and a result is synchronized to a three-dimensional BIM model; and S500, a construction drawing is automatically generated, and visual disclosure and high formwork monitoring point selection are carried out. According to the method, design, computational analysis and construction application data linkage and closed-loop management from design to construction to monitoring are achieved, and the high formwork design efficiency and safety are improved.

A pressurized water reactor oxidation corrosion product cross-scale nuclear-thermal-material coupling simulation method comprises the following steps: in the first stage, obtaining a supercooled boiling position through mutual loop iteration simulation of a neutronics model and a thermal hydraulic model; and in the second stage, multi-physics field coupling simulation is carried out through an oxidation corrosion product (CRUD) model, a neutronics model and a thermal hydraulic model, and high-resolution simulation under the pressurized water reactor nuclear-thermal-material coupling condition is obtained. According to the method, a scene in which the thickness range of the oxidation corrosion product is 20-200 microns is considered, multi-physical fields such as pressurized water reactor neutron physics, flow heat transfer and oxidation corrosion product deposition are calculated and analyzed, and the complex physical process can be captured more accurately.

The invention discloses a spatio-temporal data visualization index management and application method, and belongs to the field of spatio-temporal data statistical analysis processing. Analyzing a time-space visualization service scene, and determining a statistical calculation rule of the time-space index data; a statistical calculation rule of spatio-temporal index data is configured through a visual interface, structured configuration is generated and stored in a standardized configuration table, an ETL process is automatically generated after the system analyzes the configuration to realize data statistics and circulation, and automatic calculation and timing calculation are supported; the method comprises the following steps: designing a hybrid storage architecture of a standardized index data statistical result, and adopting a relational database and data warehouse dual-mode storage strategy: storing original data and statistical results with small data volume by adopting a relational database; for mass data, the mass data are synchronized to a data warehouse through an ETL process, distributed calculation analysis is executed on a warehouse layer based on index configuration, and an analysis result is persistently stored in a column storage format; transparent access to a heterogeneous storage bottom layer is achieved by constructing a unified access interface layer.

The invention discloses a power distribution network situation deduction method and device based on multi-source data fusion. According to the method, a main and distribution integrated calculation model is established, and a model basis for calculation and analysis is provided for situation deduction; according to the method, data pre-estimation is carried out on equipment which does not acquire real-time measurement and a non-automatic switch state in allusion to the weak condition of power distribution network measurement, and identification and correction are carried out on invariant data based on a pre-estimated value and a real-time measurement value of the equipment, so that multi-source data fusion is realized, and an accurate and complete data basis is provided for situation deduction. According to the invention, based on multi-source data fusion and integrated modeling, panoramic graph model topology active association and power distribution network state real-time sensing are realized, and power flow situation deduction in different application scenes is supported, so that safe, stable and efficient operation of an active power distribution network is effectively supported.

The invention discloses a soft rock TBM jamming risk intelligent prediction method based on numerical mechanism guidance, and the method comprises the following steps: S01, building an extrusion soft rock stratum TBM dynamic tunneling whole process refined numerical simulation model which comprises a TBM cutterhead, a front, middle and tail step shield, soft rock, a segmental lining and a backfill material behind a wall, and simulating an evolution process; s02, systematically calculating and analyzing surrounding rock geological parameters, TBM tunneling parameters, TBM construction parameters and TBM construction parameters, and constructing a machine blocking index numerical value sample library; s03, predicting the large deformation of the soft rock and the extrusion load of the shield, fusing TBM rock-machine interaction multi-source data in actual engineering, and establishing a soft rock TBM jamming risk intelligent prediction model; and S04, evaluating the TBM jamming risk, and verifying the effectiveness of the prevention and control measures. According to the technical scheme, the whole process of dynamic interaction between the TBM and the soft rock can be comprehensively considered; the TBM jamming disaster occurrence mechanism is explained, and the generalization ability of the machine learning method in practical application is improved.

The invention relates to the technical field of casting image data processing, in particular to a casting appearance quality detection method based on machine vision, and the method comprises the steps: determining analysis pixel points in a casting X-ray grayscale image; determining the probability that the analysis pixel point belongs to the pore edge in the color domain according to the difference between the gray value of the analysis pixel point and the gray average value of the thick area or the thin area where the analysis pixel point is located and the gray variance of eight neighborhood pixel points of the analysis pixel point; a plurality of other analysis pixel points are obtained in the texture direction perpendicular to the gradient direction of the analysis pixel points to construct a reference domain of the analysis pixel points, and the probability that the analysis pixel points belong to the pore edge in the spatial domain is calculated; according to the probability that the pixel points belong to the air hole edge in the color domain and the probability that the pixel points belong to the air hole edge in the space domain, the seed points of the watershed algorithm are determined, so that the casting appearance quality detection result is obtained, and the casting quality evaluation accuracy is effectively improved.

Disclosed are systems and methods that provide a decision-intelligence (DI)-based, computerized framework for automatically and dynamically determining a quantity and positioning of APs within a location, for which an optimized WiFi network can be realized. The disclosed framework can operate by determining a floor plan / layout of a location using tracked and analyzed channel metrics from the various WiFi devices in the location. Based upon the computational analysis of such metrics, the framework can identify the ideal spots for signal coverage, detect weak / dead spots for signal coverage, close the coverage hole gaps in the house, and the like. Thus, the network topology of a WiFi network, inclusive of the number of nodes in the topology, as well as the quantity of nodes, can be determined, configured and applied to a location, which can control how a location's network operates.

The invention provides a flying dust management system for composite low-carbon construction. The flying dust management system comprises a multi-source sensing acquisition module, an edge calculation analysis module, a dynamic decision control module, a resource optimization scheduling module and a carbon emission quantitative evaluation module, the multi-source sensing acquisition module completes original data preprocessing and local calibration; the edge calculation and analysis module identifies a main pollution source and generates a concentration distribution thermodynamic diagram; the dynamic decision control module generates an optimal control strategy of the dust suppression equipment; the resource optimization scheduling module optimizes hydroelectric resource distribution, and dynamically schedules fog gun and spray tower equipment combination; and the carbon emission quantitative evaluation module calculates the net carbon emission reduction of the dust suppression measures and generates a low-carbon construction report. According to the invention, turbulence diffusion and fuzzy control are combined to realize predictive dust suppression; double-loop control of edge computing and cloud feedback is adopted, so that communication delay is reduced; and through hydroelectric constraint optimization, the carbon strength of the dust suppression system is reduced.

The invention discloses an unmanned aerial vehicle-mechanical dog cooperative multi-frequency sound wave mine pile cavity monitoring system and method. The system is characterized in that a plurality of receiving sensors are uniformly arranged on the surface of a mine pile in a stoping space; the unmanned aerial vehicle platform and the mechanical dog are arranged in the stoping space; the multi-sensor integration unit comprises a sound wave emission module, an RTK real-time dynamic positioning module, a laser radar module and a visual SLAM module, and the calculation analysis terminal is connected with the mechanical dog, the multi-sensor integration unit and the multiple receiving sensors. The method comprises the following steps: after finishing each ore drawing operation, arranging a plurality of receiving sensors on the surface of an ore heap at the bottom of a stoping space in a rhombic grid manner by adopting a mechanical dog; and the unmanned aerial vehicle platform is controlled to sequentially traverse the arrangement point positions of the receiving sensors, sound wave signals are transmitted, the head wave arrival time, the amplitude attenuation rate and the frequency spectrum gravity center offset are obtained through the receiving sensors, and third-level early warning is carried out. According to the system and the method, the cavity condition in the ore heap can be efficiently and accurately monitored.

The invention relates to the technical field of edge computing, and provides an edge data acquisition and processing device for a power plant unit, which comprises a data receiving module, an edge processing module, a data compression module and a communication module, the data receiving module is used for receiving data input by the access equipment and carrying out frame decoding processing on the data input by the access equipment to obtain data after frame decoding; the edge processing module is used for calculating and analyzing the deframed data to obtain preprocessed data; the data compression module is used for performing data compression processing on the preprocessed data to obtain compressed data; and the communication module is used for transmitting the compressed data to a preset target system. The efficient edge calculation and data compression mechanism not only improves the real-time performance and accuracy of data processing, but also enhances the adaptability of the system to the constantly changing operating environment and technical upgrading requirements of the power plant unit, and provides powerful support for safe operation and stability of the power plant unit.

The present invention relates to the technical field of electrodeposition, and relates to a simulation method for flow field distribution and deposition morphology in ultrafast laser-assisted electrochemical deposition. The steps of the method comprise: constructing, in multiphysics simulation software, a two-dimensional axisymmetric multiphysics coupled field model for heat transfer, solid and fluid heat transfer, tertiary current distribution, and laminar flow; constructing a geometric model of a deposition cell and a substrate, and setting laser properties, material physical parameters, and electrodeposition properties in the multiphysics simulation software; constructing an ultrafast laser heat transfer model on the basis of a two-temperature equation; setting initial and boundary conditions of the ultrafast laser heat transfer model, and constructing an electrodeposition field; coupling the ultrafast laser heat transfer model with the electrodeposition field to construct an ultrafast laser-assisted electrochemical deposition model; delineating a grid; and performing calculation and analysis. In the present invention, ultrafast laser is incorporated to perform multiphysics coupling of a thermal field, a flow field, an electric field, etc., and a two-temperature equation and tertiary current distribution are incorporated to the model, thereby achieving the accuracy and comprehensiveness of prediction models.

The invention relates to the technical field of digital image processing, in particular to a real-time video semantic segmentation system and optimization method fusing an edge size model, and the system comprises an edge end lightweight model belonging to terminal equipment, an edge server large model belonging to an edge server, a dynamic frame distribution module and a self-adaptive cache module. An optical flow change rate and scene complexity are analyzed through edge detection and entropy calculation by a dynamic frame distribution module, then a dynamic distribution strategy is output, the dynamic distribution strategy is formed by processing a low-change frame by a small model and processing a key frame by a large model, a high-confidence segmentation result of the large model is cached by a self-adaptive cache module, and a high-confidence segmentation result of the large model is obtained. The method can be used for reuse of small models in similar scenes so as to reduce calling frequency of large models, flexibly deploy resources of the large models and the small models during operation and solve the real-time performance-precision contradiction in edge computing scenes, and compared with a single model scheme, the method has the advantages that precision is improved, and load is reduced.

The invention belongs to the field of bioinformatics, and relates to a protein post-translational modification prediction method based on multi-modal deep learning. The method comprises the following steps: firstly, performing multi-modal feature extraction by inputting a protein sequence and three-dimensional structure data to obtain a sequence feature vector and a structure feature vector; secondly, carrying out feature fusion by adopting a cross-modal attention mechanism and a self-adaptive gating network; then, combining the fusion features with the disease type information, and performing fine adjustment on the prediction probability through a disease specific coding network; then, using a multi-task learning framework to predict the locus probabilities of various protein post-translational modification types in parallel; finally, feature importance is calculated through a gradient back propagation technology, and a comprehensive report is output in combination with variation influence analysis. According to the method, high-precision and explainable protein post-translational modification prediction with disease perception capability is realized, and an important calculation and analysis tool is provided for revealing a disease molecular mechanism and finding accurate drug targets.

The invention relates to the technical field of large model service tracking, and discloses a large model service chain type calling tracking system and a root cause analysis method, and the method comprises the steps: carrying out the semantic coding of the input and output of a large model, generating a final fingerprint, and carrying out the cross-Span fingerprint inheritance and extension; semantic uncertainty is calculated and analyzed, and the sampling rate is dynamically adjusted; based on sampling data acquired by a sampling rate, fusing a call chain topological structure and a time decay factor, constructing a dynamic space-time atlas, optimizing an atlas index, constructing a multi-dimensional analysis framework, and realizing positioning from surface anomaly to deep root cause in combination with an anomaly propagation contribution degree obtained by calculation; carrying out statistics on distribution parameters of local indexes and carrying out differential privacy processing, and calculating a global threshold value of the distribution parameters and carrying out issuing execution; and based on a final positioning root cause obtained by global threshold analysis, evaluating a root cause repair effect and performing model iteration, and converting historical root cause data into a driving force for system optimization.

A water-mist-penetrating three-wavelength temperature measurement device and method for a high-temperature environment, the device including a housing, a three-waveband beam splitting detection module and a computing unit, the housing provided with an optical aperture, the three-waveband beam splitting detection module arranged in the housing, and including a trichroic prism, three radiation detection assemblies, the trichroic prism able to receive the light signals entering via the optical aperture, and emit radiation signals having different wavelength bands through three emission faces, respectively; the three radiation detection assemblies able to receive radiation signals having different wavelength bands emitted from corresponding emission faces, and convert them into electrical signals, respectively; the computing unit able to receive the electrical signals, and perform calculation and analysis to determine a temperature value of a target to be measured; the method including: temperature measurement data acquisition, data fusion, parameter tuning, and model application.

A portable golf putting green putter multi-parameter intelligent training system is characterized by comprising a support (1) used for installing an electromagnetic induction type sensing device (2) and an electric control element and enabling the whole training system to be convenient to carry and move; the sensing devices (2) are installed on the two supporting legs of the support, and at least two sensing devices (2) are installed on each supporting leg; and the electric control element (3) is used for receiving the signal intensity and the time difference obtained by the sensing device (2), transmitting the signal intensity and the time difference to a computer system (4) in real time in a wired or wireless manner, calculating and analyzing the signal intensity and the time difference, displaying the speed and the angle of the push rod in real time, and comparing the speed and the angle with preset standard values, so that a coach or a practicer can improve the speed and the angle. The utility model has the advantages of simple structure, convenience in carrying, low cost and wide application range.

A deep foundation pit supporting structure design method based on system reliability analysis relates to the technical field of foundation pit structures, and obtains a supporting structure design method with high safety coefficient and low supporting cost through calculation and analysis, and comprises the following steps: S1, obtaining an engineering exploration report and a preliminary design scheme corresponding to a deep foundation pit; s2, determining a value range of a design variable x and statistical characteristics of a random variable y; s3, determining a failure mode of a deep foundation pit support design system according to engineering characteristics of the support corresponding to the deep foundation pit; s4, constructing a limit state function of each failure mode; s5, constructing a system reliability model through the system failure probability of the series system in the step S4, fusing a multi-objective optimization model into the system reliability model, and setting an objective function and a constraint condition; and S6, setting a multi-objective optimization algorithm in the deep foundation pit support design system, calculating the safety and cost of different support structures by using the algorithm, obtaining a Pareto solution set, and obtaining the corresponding deep foundation pit support structure design through comparison and selection.

The invention discloses a method for evaluating the use performance and driving comfort of a bridge after an explosion load effect. The method comprises the following steps: establishing a finite element model of the bridge under the explosion effect, and extracting the residual area of the section of the bridge after the explosion and the elevation of the bridge floor after the explosion; calculating distribution of bridge section damage degree and bridge deck irregularity level; and the traffic capacity of the bridge is evaluated accordingly. For a bridge which can still be used, a result file of a bridge part after explosion is imported, then an axle coupling model after explosion is established, and unevenness after explosion is formed; and extracting the calculated and analyzed vertical acceleration of the vehicle, and calculating the root mean square value of the acceleration to evaluate the driving comfort of the vehicle. According to the method, through coupling evaluation of the damage degree and the bridge floor irregularity level, the composite influence of explosion on the bridge safety and the driving comfort is comprehensively quantified, and the misjudgment risk caused by one-sided evaluation is avoided; and meanwhile, the economic cost is greatly reduced through a simulation analysis and calculation mode, and the safety risk of post-disaster scene survey is avoided.