213 results about "Stress index" patented technology

The invention provides a time sequence fusion and health state prediction method and system for multi-dimensional physiological data, and relates to the technical field of electrical digital data processing.The method includes the steps that high-precision sensing equipment and a parameter calibration model are adopted to calibrate data, time synchronization and error compensation are achieved through a weighted fusion algorithm, and the accuracy of physiological parameters is improved; meanwhile, a fatigue index and a pressure index are corrected in real time by using a closed-loop feedback mechanism, and a comprehensive state index is generated based on an evaluation result for further analysis and prediction; the change trend of the comprehensive state index is predicted through a machine learning technology, and a targeted dynamic rehabilitation scheme including training intensity optimization, diet adjustment, rest cycle planning and the like is provided in combination with physiological data of the user; and a timing feedback mechanism is established, so that the user can obtain health state change and adjustment suggestions in real time, thereby improving scientificity and timeliness of a rehabilitation scheme, remarkably optimizing the rehabilitation effect and efficiency, and realizing intelligent health management at the same time.

The invention provides a psychological analysis method and system based on multi-modal features, and relates to the technical field of psychological assessment. The method comprises the following steps: synchronously obtaining voice data, video data, text data and physiological signal data of a user; respectively denoising the data to obtain each piece of denoised modal data; performing feature extraction on each modal data to obtain each modal feature; mapping each modal feature vector to a unified semantic space through an attention weighting mechanism to generate a fusion feature matrix; a trained psychological analysis model is adopted to perform multi-task learning on the fusion feature matrix, and emotion classification, pressure indexes and psychological health risk scores are synchronously output; and updating model parameters of the psychoanalysis model through an online incremental learning mechanism based on the real-time feedback data of the user and the newly added sample. Through accurate data denoising, efficient feature extraction and flexible model optimization, comprehensive and accurate analysis of the psychological state of the user is realized.

The invention discloses a stress detection method and system applied to a high-pier bridge supporting structure, and relates to the technical field of bridge supporting structure stress detection. According to the stress detection method applied to the high-pier bridge supporting structure, for each bridge supporting column in the high-pier bridge supporting structure, supporting state data is obtained, an initial stress index is analyzed and corrected, a stress comprehensive correction index of the high-pier bridge supporting structure is obtained, judgment and analysis are conducted on the stress comprehensive correction index and a preset stress evaluation interval, and therefore the stress detection accuracy of the high-pier bridge supporting structure is improved. According to the method, the real-time data of each supporting column are obtained and are dynamically corrected in combination with various environmental factors, and the initial stress index of the supporting column is corrected according to changes of local displacement, local strain and load after each time of monitoring, so that the real-time performance and accuracy of stress evaluation are ensured; the accurate correction mechanism can be used for analyzing different stress states of each support column and reflecting the dynamic change of the structure in time.

The invention provides a deep coal seam roadway surrounding rock stability intelligent early warning method, and relates to the technical field of coal mine dynamic disaster prevention and control. According to the intelligent early warning method for the stability of the surrounding rock of the deep coal seam roadway, a basic sample library is constructed through a dynamic and static combined loading rock test; synchronously collecting field surrounding rock static stress and micro-seismic data and carrying out time sequence polymerization; constructing an equivalent dynamic and static combined stress index based on a dynamic and static load superposition principle, and forming a seismic-force coupling feature vector; establishing an LSTM early warning model, adopting a transfer learning strategy, pre-training by using laboratory data, and then performing fine tuning by using field data; inputting the real-time feature vector into a model and outputting an instability probability; and verifying and correcting the probability based on actual deformation data of the surrounding rock, and applying a missing report sample to online incremental updating of the model. According to the method, the dynamic and static load coupling effect is quantified, the difficulty of small sample training is overcome, and accurate and self-adaptive early warning of the deep roadway surrounding rock instability risk is realized through a physical feedback closed-loop correction mechanism.

The invention discloses a feed additive ratio control method and system based on environmental perception. The method comprises the steps that breeding environment, feed characteristics, equipment operation and animal physiological parameters are collected, and a high-quality parameter set is generated after preprocessing; calculating an environment stress index based on a multi-factor data fusion algorithm and analyzing a change trend; combining historical and current data, using time sequence prediction and a machine learning algorithm to predict additive requirements and generating an optimal proportioning strategy; a control instruction is generated according to the strategy, and the additive conveying and spraying process is regulated and controlled; and a matching strategy and control parameters are corrected in real time through closed-loop feedback, so that accurate regulation and control are realized. The device can dynamically adapt to environmental changes, reduce animal stress, and improve mixing uniformity and nutrition retention effect.

The invention relates to the technical field of livestock breeding, in particular to an intelligent feed optimal proportioning method based on pig herd nutrition analysis, which comprises the following steps: S1, collecting stress index data of a pig herd; s2, analyzing the stress level and the stress source of the swinery; s3, dynamically adjusting nutritional requirement parameters according to the stress level and the stress source, and determining nutrients needing to be adjusted under different stress conditions; s4, making corresponding stress mitigation measures based on the stress source and the stress intensity; s5, generating an optimal feed formula meeting the nutritional requirements of the swinery under the stress condition; and S6, converting the optimal feed formula into a production instruction, and sending the production instruction to feed production equipment. By dynamically adjusting the nutritional requirements of the swinery under different stress conditions and combining intelligent feed production equipment, precise feed formula optimization and efficient production are achieved, the feed utilization rate and the swinery health level are improved, and meanwhile the breeding cost is reduced.

The invention relates to the field of ropeway monitoring, and discloses a roundabout ropeway stress monitoring and early warning method and a roundabout ropeway stress monitoring and early warning system which are used for solving the problem that when a ropeway built in a high-altitude area is monitored, obtained stress data are inaccurate due to regional special environmental factors. Sensors are arranged at cableway cable monitoring points, stress data, load data and image data of all the monitoring points are collected in real time, an initial cableway stress index is obtained through comprehensive analysis and calculation, environment data of the environment where the cableway is located are collected, and adjustment factors are obtained through evaluation according to the environment data; the method comprises the following steps: calculating to obtain an actual cableway stress index according to an initial cableway stress index and an adjustment factor, dynamically adjusting a stress safety threshold according to the adjustment factor to obtain an actual stress safety threshold, and carrying out early warning and reminding according to the actual cableway stress index and the actual stress safety threshold, thereby effectively improving the accuracy of monitoring data. And the cableway safety is improved.

The invention discloses a vegetation vulnerability constraint estimation method and system under dry-heat composite stress. The vegetation vulnerability constraint estimation method comprises the following steps: 1, acquiring observed vegetation total primary productivity data, meteorological data and similar meteorological data of each lattice point in a global climate mode; 2, determining a standardized rainfall evapotranspiration index time scale of each lattice point and determining dominant stress types of different lattice points in growing seasons; 3, respectively constructing two-dimensional Copula models of corresponding dominant stress and total primary productivity, and determining a stress threshold value corresponding to induced vegetation loss; 4, calculating future estimation of dominant stress based on a climate mode, and constructing an emergence constraint model; 5, correcting a future estimated mean value and uncertainty of the dry heat stress index based on the emergence constraint relation; and 6, inputting the corrected mean value and uncertainty range of the future dry heat stress indexes into a Copula model, and calculating a corresponding loss probability. According to the method, the response difference of different vegetation ecosystems to dry heat stress is considered while the prediction accuracy of the drought heat waves and the compound events thereof is improved.

The invention relates to a method, a device and equipment for analyzing in-situ formation fracture porosity of mixed rock. Comprising the steps of obtaining original data of a plurality of layers in a target block; taking out a first rock core sample from each layer of the target block, and performing experimental analysis on the first rock core sample of each layer to determine a target layer; taking out a second core sample from the target horizon, and performing a triaxial compression test on the second core sample to obtain a stress index; according to the original data and the stress index, the stratum fracture porosity of the target layer is calculated, the stratum fracture porosity is used for guiding workers to evaluate the real underground in-situ fracture porosity of the reservoir, and therefore an oil and gas reservoir exploitation plan of the target layer is made. The stratum fracture porosity calculated by the method represents the fracture porosity of the target horizon in the target block and represents in-situ characteristics in the stratum, so that the accuracy of reservoir evaluation is improved. A worker can formulate an oil and gas reservoir exploitation plan according to the formation fracture porosity, and the oil and gas reservoir yield is improved.

The invention discloses a quality monitoring system and method for insulation side expansion sleeve production, and relates to the field of pipe quality monitoring. The method comprises the steps that S1, ultrasonic wall thickness, infrared temperature, capacitance signals and process parameters are collected; S2, the signals are normalized to generate enhanced signals, and local gradient anomaly indexes are calculated; s3, a flaring stress index is calculated according to the thickness value deviation and the technological parameters; s4, calculating coupling unevenness based on a local gradient anomaly index; s5, calculating a comprehensive quality factor according to the local gradient anomaly index, the flaring stress index, the coupling unevenness and the process parameter deviation; s6, generating an anomaly identifier based on the comprehensive quality factor dynamic deviation rate and adaptive threshold detection anomaly; s7, mapping the time sequence characteristic corresponding to the abnormal identifier to a space coordinate to output defect distribution information; and S8, according to the defect distribution information, generating process parameter adjustment quantity and feeding back to a control system.

The invention discloses a printed circuit board defect online full-automatic detection method and system based on data analysis, relates to the technical field of printed circuit board performance testing, and realizes comprehensive evaluation of circuit board performance through steps 1 to 4. By configuring a test system and setting test conditions, accurate installation and debugging of each test module are ensured; a power supply stability index Dyw, a power supply switching fault-tolerant index Qhrc, a thermal stress index Ryl, a mechanical stress index Mvz, an electromagnetic compatibility index Jrx, a resource contention index Zyzq and a self-repairing index Xfz are calculated, a comprehensive evaluation index Pc is obtained through associated calculation, performance evaluation is carried out, and whether the circuit board is qualified or not is effectively judged. And when the comprehensive evaluation index Pc is lower than a first performance threshold value X, generating a performance disqualification label, and performing in-depth grading evaluation through a second multi-stage evaluation module, thereby promoting identification of specific performance defects.

The invention discloses a mental stress assessment and intelligent dredging method and system, and belongs to the technical field of digital medical treatment and health informatics. Multi-modal physiological signals are continuously collected through the wearable device, medical diagnosis level pressure state evaluation is carried out based on the personalized physiological baseline, and personalized pressure indexes and levels are generated; secondly, when it is diagnosed that the pressure level exceeds the standard, the system serves as an intelligent decision support system, the environment and schedule information after privacy protection processing is fused, and an optimal grooming action is dynamically selected from a predefined intervention action library and executed; finally, the system serves as a continuous learning system, the intervention efficiency is evaluated in real time according to feedback data of the pressure index after execution, the decision model is updated, and collaborative self-optimization of the diagnosis strategy and the intervention strategy is achieved. According to the method, medical diagnosis, personalized treatment decision and adaptive learning are integrated, and the systematicness, accuracy and intelligent level of mental stress related health problem management are improved.

A method for diagnosing regional moisture conditions based on evaporative stress oscillation patterns is presented. [Solution] The method includes the following steps: Step 1: acquiring data; Step 2: calculating the time series of the evaporative stress index; Step 3: calculating the evolution rate of the evaporative stress index; Step 4: determining the oscillation patterns of the evaporative stress index; Step 5: calculating the frequency or duration of each oscillation pattern; and Step 6: diagnosing the evaporative stress-driven pattern and regional moisture status. The method of the present invention effectively solves the problem of information leakage and failure to reflect the transition mechanism of the stress state due to smoothing of the long-term series in the process of diagnosing the current regional moisture status, and provides solid theoretical and technical support for the diagnosis and evaluation of the evaporative stress-driven pattern and regional moisture status.

The invention relates to the technical field of stress testing, in particular to a VCSEL epitaxial wafer stress distribution monitoring method and system. The method comprises the following steps: acquiring a PL spectrum of each measurement point and a peak wavelength of the PL spectrum, and decomposing the PL spectrum into polarization components along a first crystal orientation and a second crystal orientation; obtaining the initial polarization orthogonality of the measurement point based on the peak intensity of the polarization component; obtaining a reference wavelength of the VCSEL epitaxial wafer, and calculating a thermally induced wavelength drift factor of a measurement point; based on the thermally induced wavelength drift factor and a set maximum saturation value, thermally induced polarization artifacts of the measurement points are calculated, the thermally induced polarization artifacts are in positive correlation with the thermally induced wavelength drift factor, and the maximum saturation value is taken as an upper limit; subtracting the thermally induced polarization artifact from the initial polarization orthogonality to obtain a pure stress index; the pure stress indexes are mapped to the corresponding coordinates, the stress distribution diagram of the VCSEL epitaxial wafer is obtained, and the accuracy of the stress distribution monitoring result of the VCSEL epitaxial wafer is effectively improved.

The invention relates to a cascade reservoir flood control capacity collaborative optimization method and system based on a dynamic game, and belongs to the technical field of hydropower station group flood control regulation and storage. Comprising the following steps: collecting a historical water level sequence, upstream flood discharge flow, drainage basin rainfall confluence data, radar flow measurement data, dam body stress indexes and dynamic correlation parameters of a cascade reservoir group, inputting the collected data into a space-time risk field model, and constructing a space-time risk field; constructing a game model based on the space-time risk field, taking an upstream reservoir as a leader to formulate a reservoir capacity allocation strategy, taking a downstream reservoir as a follower to dynamically adjust a flood discharge scheme according to the leader strategy, and coordinating a flood control target and an economic target through a time-varying game weight; solving the game model by adopting an improved distributed ADMM optimization algorithm to generate a scheduling instruction, and verifying the legality of the scheduling instruction through a block chain smart contract; and pre-executing the scheduling instruction in the digital twin simulation platform, dynamically calibrating the mapping parameters of the physical reservoir and the virtual mirror image through reinforcement learning, generating a final scheduling instruction, and issuing and executing the scheduling instruction.

The invention relates to the technical field of human resource management, in particular to a human resource management system and method based on a block chain. The method comprises the following steps: firstly, dividing personnel into a plurality of talent unit groups based on functions, professions and levels, performing quantitative evaluation from two dimensions of talent loss risk and post influence degree, and setting evaluation factors such as work satisfaction, occupational development opportunities, work pressure indexes and team relationship scores, so as to obtain evaluation results of the talent loss risk and the post influence degree; calculating a demission tendency index in combination with an analytic hierarchy process; generating an early warning signal based on the evaluation result; and finally, performing credible storage on the whole-process data by utilizing a block chain technology. According to the method, the conversion from passive statistics to active early warning is realized, the evaluation granularity is optimized by introducing the talent unit group, the accuracy of risk identification is improved, and the credibility of data is ensured by using the block chain technology.

A method for assessing a state of stress of an individual when the individual is contacting a receiving surface of a device comprising a pressure sensor comprising a plurality of elemental gauges, each elemental gauge having a gauge factor of at least 10, the method comprising acquiring and digitizing each signal delivered by each elemental gauges of the pressure sensor each signal comprising a pseudo-periodic part, exploring the signal and detecting patterns corresponding to heartbeats, measuring an Inter-Beat interval and recording in a heartbeat timestamped file each Inter-Beat Interval, from the heartbeat timestamped file computing at least 3 stress indices and categorizing the state of stress of the individual based on the at least three indices and a stress assessment program implementing a trained algorithm, among an increasing stress, a decreasing stress and a neutral state.

The invention relates to the technical field of steel structure installation quality detection, and discloses an intelligent detection system for detecting steel structure installation quality and a detection method thereof, and the system comprises a multi-dimensional acquisition module and an intelligent analysis module. The system obtains detection data of all components and all joints through a multi-dimensional acquisition module, classifies the detection data to form a data set, an intelligent analysis module analyzes the dimensional deviation and the material quality of each component according to a structure data set, generates a deviation index, dynamically compares a BIM model, and sends the BIM model to the intelligent analysis module according to an installation data set. The method analyzes the stress distribution state of the steel structure and the installation quality of each connection position, generates a stress index and a defect index, discovers potential structure safety hazards in advance, accurately positions the connection positions with problems, is high in comprehensive detection precision, and evaluates the dimensional deviation degree, the material quality and the steel structure stress distribution state of each assembly. And the corresponding management suggestions are output, so that the intelligent management and installation quality is good.

The invention relates to the technical field of biomedical signal processing, in particular to a pulse signal-based stress index calculation method, which comprises the following steps of: acquiring a pulse signal of an individual in real time by utilizing pulse signal acquisition equipment, preprocessing the acquired pulse signal, removing useless information and noise in the pulse signal, and calculating the stress index of the individual according to the useless information and noise. Extracting characteristic parameters related to the stress state from the preprocessed pulse signals, constructing a stress index calculation model based on the extracted characteristic parameters, and accurately mapping the characteristic parameters into stress index values through the stress index calculation model; the pulse signal is collected and processed in real time, the stress index value can be rapidly calculated, and the method has the advantage of being high in real-time performance.

The invention provides a post evaluation simulation method based on virtual reality, and relates to the technical field of virtual reality, and the method comprises the steps: calculating a real-time cognitive load pressure index and an emotion state parameter of a student; obtaining a fault evolution speed parameter and a complexity parameter used for adjusting the fault evolution process; inputting the fault evolution speed parameter and the complexity parameter into an intelligent fault chain generation system, and generating a cascade fault situation conforming to the physical law of the power system through a graph neural network model; in a high-precision simulation environment of a digital twin platform of a power system, students are guided to execute simulation operation based on a cascade fault situation, and multi-dimensional behavior data are collected and recorded; the multi-dimensional behavior data comprises operation time sequence data, operation path deviation data and decision delay data; and inputting the multi-dimensional behavior data into a multi-dimensional human factor engineering evaluation system, and processing the multi-dimensional behavior data through a human factor analysis model to obtain a post evaluation result of the student. According to the embodiment of the invention, the accuracy of post evaluation can be improved.

The present invention discloses a stress detection method and system for a high pier bridge support structure, which relates to the technical field of stress detection of bridge support structures. The stress detection method for a high pier bridge support structure respectively obtains support state data for each bridge support column in the high pier bridge support structure, analyzes the initial stress index and performs correction processing to obtain the stress comprehensive correction index of the high pier bridge support structure, and makes a judgment and analysis with a preset stress evaluation interval. The present invention dynamically corrects by obtaining the real-time data of each support column and combining various environmental factors. The initial stress index of the support column will be corrected according to the changes in local displacement, local strain and load after each monitoring, ensuring the real-time and accuracy of stress evaluation. This precise correction mechanism can analyze the different stress states of each support column and timely reflect the dynamic changes of the structure.

The invention provides a Tibetan chicken intensive breeding health monitoring and early warning method and system, and relates to the technical field of computers, and the method comprises the steps: obtaining the three-dimensional motion and interval time sequence data of a Tibetan chicken flock in a breeding house, and the original chirp audio time sequence data; performing motion mode analysis according to the three-dimensional motion and the interval time sequence data to obtain a vector field sequence; carrying out stress level inference according to the vector field sequence to obtain a group recessive stress index; according to the group implicit stress index and the original chirp audio time sequence data, performing model construction to obtain a chirp-stress association model; acquiring real-time chirp audio data, and inputting the real-time chirp audio data into the chirp-stress correlation model for health state critical point prediction to obtain an instability precursor signal; and performing graded early warning according to the instability precursor signal to obtain a health early warning grade. According to the invention, prediction and early warning of health risks caused by group stress of the Tibetan chickens in an intensive breeding environment are realized.

The invention provides a remote data acquisition and analysis method and system for a baby stroller, and the method comprises the steps: synchronously acquiring environmental stimulation and passenger physiological reaction data through multiple modules on the baby stroller, locally processing the environmental data into cumulative stress indexes, and processing the physiological data such as sound production into state classification labels. And when the passenger has negative stress states such as crying, screaming and the like, the system automatically packs the accumulated stress index sequence in the previous period of time to form a stress event data packet. And the data packet and baseline data in a normal state are transmitted to a remote server together, and a specific environment mode causing the negative stress of the passenger is identified through comparative analysis. According to the method, through event-triggered data acquisition and comparative analysis, specific external factors causing discomfort of infants can be accurately identified and understood.

The invention discloses a method for evaluating the sealing performance of a pipe joint, and the method avoids the defect that the visual inspection of tiny seepage is easy to omit through building the relation between a leakage rate value and an actual leakage phenomenon. Based on a numerical calculation method, the time period and the cost waste of physical verification are saved, the sealing performance can be pre-judged during product design by adopting the method, and the stress index and the sealing contact width index of main structure parameter design are reversely solved according to the sealing performance index; and traceability can be carried out when a leakage fault is sent, a weak link of contact pressure is found, and guidance is brought to improvement of sealing performance.

The invention relates to the field of deep coal bed gas development and reservoir reconstruction engineering, in particular to a compressibility evaluation method for a deep coal bed gas reservoir containing dirt band. The invention discloses a method for evaluating compressibility of a deep coal bed gas reservoir containing dirt band. The method comprises the following steps: obtaining a normalized coal rock brittleness index, a normalized coal body structure index, a normalized fracture toughness index, a normalized ground stress heterogeneity index, a normalized dirt band and coal rock layer stress difference index, a normalized fracture surface density index and a normalized mechanical specific energy index; converting the data into dimensionless numerical values, and unifying the value range to an interval of [0, 1]; and performing hierarchical weight assignment by using a triangular fuzzy analytic hierarchy process to form a deep coal rock compressibility index, and establishing an evaluation standard according to the deep coal rock compressibility index. According to the method, a theoretical basis is provided for optimal decision-making of the on-site deep composite coal rock reservoir fracturing transformation horizon.

The invention discloses a self-adaptive regulation and control method and system for an in-cabin environment driven by vital signs of a wounded person, and relates to the technical field of crossing of medical equipment and environment control. According to the self-adaptive regulation and control method and system for the in-cabin environment driven by the vital signs of the wounded person, a four-dimensional data acquisition system composed of physiology, environment, medical intervention and space-time scenes is built; the method comprises the following steps: synchronously acquiring multi-dimensional vital signs including brain electricity, skin electricity and other nerve and stress indexes, an in-cabin dynamic environment including detailed parameters such as airflow velocity and particulate matter concentration, external medical operation covering drug dosage and equipment working parameters, and transfer scene data including altitude change and bumping intensity; the limitation that only single environment or physiological data is acquired in the prior art is solved; when a craniocerebral injury wounded person is transported in an air transport mode, the system can be combined with the altitude change rate and the electroencephalogram alpha wave power, the blood oxygen lowering risk can be pre-judged 10 minutes in advance, and the problem that misjudgment is conducted only through current data traditionally is avoided.

The invention relates to the technical field of health data processing, in particular to a multi-modal health data processing method and device and a storage medium, and the method comprises the steps: collecting vital sign data, motion data and biochemical index data; dividing a multi-scale time window based on the vital sign data, the exercise data and the biochemical index data, and dividing user data types according to the vital sign data, the exercise data and the biochemical index data in the multi-scale time window; screening a positive sample and a negative sample based on the user data type, the vital sign data, the motion data and the biochemical index data, and performing feature coding analysis to obtain a joint feature vector; constructing a branch decision tree based on the joint feature vector; and analyzing a pressure index trend according to the vital sign data and the biochemical index data so as to update the branch decision tree. According to the invention, accurate abnormal early warning of the multi-modal health data is realized.

The invention provides a roadway surrounding rock stability judgment method and a classified supporting method, and relates to the technical field of soil layer or rock drilling and mine safety. The method comprises the following steps: S1, determining roadway surrounding rock stability influence factors; s2, dividing a rock mass strength index, a surrounding rock stress index, a surrounding rock integrity index, a roadway size index, a coal pillar ruler habit index, a water spraying index and the like; s3, determining a roof strength stress coefficient, a roof integrity coefficient and a side loosening coefficient; s4, performing field investigation or testing to obtain a classification index value, and determining an index threshold value through a fuzzy clustering method; s5, determining classification of non-impact roadways and impact dangerous roadways according to the roadway impact dangerousness and the impact danger index; and S6, determining a roadway support mode according to the roadway surrounding rock stability classification. According to the method, more comprehensive influence factors are considered, parameters are more convenient to obtain, values of factors required by field test classification indexes are facilitated, and scientific support of roadway surrounding rocks is achieved.

The invention provides a bridge supporting column stress measurement method based on structure collaborative stress analysis, and belongs to the technical field of stress measurement, and the method comprises the steps: collecting the stress, strain and displacement data of each bridge supporting column in real time; calculating a local stress index of each bridge support column based on the collected real-time data; according to the connection relation between the bridge overall structure parameters and the bridge supporting columns, a structure collaborative stress model is established; calculating a cooperative stress correction index of each bridge support column; and comparing the cooperative stress correction index with the dynamic stress evaluation interval, performing trend analysis in combination with historical data and environmental factors, judging whether a structural risk exists or not, and sending out an early warning signal when the structural risk exceeds a threshold value. According to the method, a structure collaborative stress analysis mechanism is introduced, the influence of the overall stress state of the bridge on a single bridge supporting column is comprehensively considered, key structure risk points can be recognized more accurately, and the reliability and early warning capacity of bridge safety monitoring are improved.

The invention provides a multi-factor coupling asphalt accelerated aging simulation method and system, and relates to the technical field of road engineering. The method comprises the following steps: at the beginning of simulation, performing multi-factor coupling asphalt aging environment simulation through an aging test box; acquiring set parameters of the multi-factor coupling asphalt aging environment simulation; determining an aging stress index according to the set parameters; obtaining the operation time of the aging test box; determining equivalent aging time according to the aging stress index and the operation time; when the simulation is finished, obtaining aging parameters of the asphalt through a dynamic shear rheometer and a penetrometer; determining an aging degree deviation according to the aging parameter; and determining whether to adjust the set parameters according to the aging degree deviation. According to the invention, the aging rate can be dynamically adjusted according to the aging stress index, and the set parameters can be dynamically adjusted according to the aging degree deviation so as to optimize the simulation condition and improve the accuracy and reliability of simulation.