102results about How to "Realize early warning" patented technology

The invention provides a lithium ion battery health state evaluation method, system and device and a medium, and belongs to the technical field of battery health management and life prediction.The method comprises the steps that voltage and current time sequence data in the battery charging and discharging process are synchronously collected, and the discharging capacity is calculated; three key area proportion features are extracted based on the above, a cycle feature sequence of the battery is compressed into a fixed length, and health state dichotomy labeling is carried out according to a capacity attenuation threshold value; training a CNN classification model by using the marked source domain data, wherein the CNN classification model is used for carrying out real-time and online health state classification on the target domain battery; and for the target domain battery data classified as rapid degradation, further performing high-precision residual life prediction by combining an LSTM model and RBF-MMD. The problems that an existing method is poor in generalization, early warning lags behind and is difficult to deploy in an embedded platform are effectively solved, and cross-battery and cross-working-condition early-stage, accurate and real-time life prediction is achieved.

This invention discloses an intelligent early warning system and method for railway line patrol safety based on edge computing, involving intelligent safety early warning in the railway transportation field, enabling real-time controllable emergency measures to minimize the negative impact of incidents. The edge computing-based intelligent early warning system for railway line patrol safety includes: a cloud platform for an intelligent patrol system along the railway line, network infrastructure units for the intelligent patrol system along the railway line, on-site edge intelligent early warning devices and traffic control units, and IoT video sensing infrastructure units. This invention aims to deploy edge computers to continuously analyze 24-hour video streams from surveillance cameras at key locations along the railway line, process data in real-time, reduce latency, promptly identify abnormal events, take temporary emergency measures as quickly as possible, and rapidly report abnormal events, effectively shortening response time, significantly improving the efficiency of handling abnormal events in railway transportation, enhancing the accuracy of emergency measures, and ensuring railway line safety.

The application discloses a new energy electric drive system of a novel green intelligent carrying frame, which comprises a multi-source energy supply module, an intelligent driving module, an energy efficiency control module, an energy recovery module and a communication interaction module.The multi-source energy supply module is used for supplying energy under different working conditions for the carrying frame.The intelligent driving module is used for driving walking mechanisms arranged on both sides of the carrying frame.The energy efficiency control module is used for generating a dynamic energy consumption adjustment decision by using an energy consumption optimization algorithm and sending the decision to the multi-source energy supply module and the intelligent driving module.The energy recovery module is used for monitoring the running state of the carrying frame in real time to start an energy recovery process and output electric energy to the multi-source energy supply module.The communication interaction module is used for establishing an information transmission channel between the intelligent driving module, the energy efficiency control module and a warehouse intelligent scheduling system.The novel green intelligent carrying frame has the remarkable effects that the green environmental protection, energy utilization efficiency and intelligent operation capacity of the carrying frame are remarkably improved through multi-element new energy collaborative power supply, full-working-condition high-efficiency driving, intelligent energy efficiency control and precise energy recovery.

The application relates to the technical field of equipment health management, and discloses a battery replacement cabinet fault prediction and health management method and system. The method comprises the following steps: acquiring an original temperature sequence, an original humidity sequence, a battery module number and a battery replacement cabinet position number, performing abnormal value correction to obtain a corrected temperature sequence and a corrected humidity sequence; performing abnormal fluctuation point screening according to the corrected temperature sequence and the corrected humidity sequence to generate an abnormality judgment record; removing interference according to the abnormality judgment record to obtain a refined feature set; performing abnormal risk analysis according to the refined feature set to obtain an overheating risk report; generating an intervention instruction according to the overheating risk report to obtain an initial execution scheme; driving operation is performed according to the initial execution scheme to obtain an equipment operation log; and performing reliability evaluation according to the equipment operation log to obtain a reliability evaluation conclusion. The method can realize early warning and health management of battery replacement cabinet faults.

The invention provides an end sealing and cooling structure for a plunger. The end sealing and cooling structure for the plunger comprises a sealing sleeve and the plunger arranged on the core portion of the sealing sleeve in a penetrating mode. A threaded sleeve, a water jacket, a three-stage sealing structure and a guide sleeve are sequentially arranged between the plunger and the sealing sleeve; annular cooling flow channels are formed between the water jacket and the plunger and between the water jacket and the sealing sleeve respectively. The annular cooling flow channels are communicated with a cooling medium inlet and a cooling medium outlet in the sealing sleeve. A pressure detection device is arranged on the quick-change connector at the cooling medium outlet; the three-stage sealing structure comprises three UN sealing rings and three supporting rings, and the UN sealing rings and the supporting rings are arranged at intervals; an annular groove is formed in the UN sealing ring, an annular protrusion is arranged on the supporting ring, and the annular protrusion is connected with the annular groove in an inserted mode. The problems that an existing sealing structure is prone to failure in the high-temperature and high-pressure environment, and sealing failure cannot be found in time are solved.

This invention belongs to the field of space laser communication and deep space exploration technology, and discloses an integrated detection device for space laser communication monitoring and interaction. The device includes a main body, on which are integrated a solar panel, a navigation imaging device, a communication antenna, a communication receiver, a radar, a landing support, and functional components for communication monitoring, environmental perception, and interactive operation. This invention forms a closed-loop system through electrical, signal, and mechanical connections, enabling simultaneous execution of multiple tasks, significantly improving the device's space operation efficiency, reducing the load pressure on space launch vehicles, and adapting to the space constraints of on-orbit operations. The communication antenna and receiver achieve bidirectional signal interaction through a high-speed laser communication module and are linked with the navigation imaging device and environmental sensors to ensure stable transmission and status monitoring of laser communication signals, which is beneficial for practical applications and operations.

The application provides a production method of high-corrosion-resistance and high-strength galvanized steel strand, relates to the technical field of hot-dip plating, and comprises the following steps: collecting hot-dip plating related characteristic parameters and setting basic hot-dip plating time; pre-processing the hot-dip plating related characteristic parameters and outputting a hot-dip plating calibration coefficient; establishing a coupling formula and obtaining a hot-dip plating calibration time; collecting strength interference characteristic parameters; based on the collected strength interference characteristic parameters and the obtained actual hot-dip plating required time, calculating a tensile strength prediction score of the produced galvanized steel strand, and determining the eligibility of the galvanized steel strand prepared under the current working condition parameters. The application calculates a most suitable galvanizing time, ensures that the zinc layer is fully penetrated, and avoids excessive reaction to cause the steel strand to be brittle. Meanwhile, the application can predict whether the tensile strength of the finished product is qualified before production, realizes dynamic optimization, early warning and self-learning in the whole process, and effectively reduces the waste product rate.

This application relates to the field of waterproof and thermal insulation building technology, specifically disclosing a monitorable and early warning type waterproof and thermal insulation wall, its construction method, and monitoring and early warning method. A monitorable and early warning type waterproof and thermal insulation wall comprises multiple prefabricated wall sections, each including: a concrete substrate; a sealed cavity; two steel meshes; a channel; and a pressure measuring device. The method includes: by installing a pressure measuring device within the channel, the air pressure values ​​of sealed cavities A and B within the concrete wall can be monitored in real-time over a long period. An alarm threshold is set; when the air pressure value changes to reach the threshold, the early warning device sends an early warning notification. By monitoring pressure changes, the waterproof and thermal insulation performance of the concrete wall is monitored, achieving long-term monitoring and early warning of the wall's waterproof and thermal insulation performance.

The present application relates to the photovoltaic power station operation and maintenance technical field, propose a kind of photovoltaic power collection line fault diagnosis method and system based on big data analysis.The monitoring point is laid along the line and feature extraction is carried out in time window unit, the spatial fine perception of photovoltaic power collection line operation state is realized.On this basis, double model parallel processing architecture is used, i.e.current window feature vector is used to realize real-time accurate identification of fault type through classification model, while time series formed by historical and current feature vectors is used to realize early quantitative prediction of fault development trend and remaining life, so that fault diagnosis is promoted from traditional post-judgment to early warning.Further, the identification result and prediction result of each monitoring point are uniformly input into reasoning engine for comprehensive analysis and cause tracing, and the complete technical closed loop from data output to decision generation is realized.

This disclosure provides a method for early warning of safety and environmental protection for large-scale industrial solid waste stockpiles based on digital twins. The method includes: acquiring the stockpile state variables within the target stockpile and constructing a comprehensive stockpile state set with a unified time reference based on these variables. Based on the comprehensive stockpile state set, a dual-state mapping structure is constructed in the digital twin space to obtain a dual-state digital twin stockpile model. The dual-state digital twin stockpile model is used to analyze the target stockpile area to identify its mechanical state characteristics and determine the critical instability pre-state based on these characteristics. The critical instability pre-state is used to determine whether the target stockpile area is in a critical state of mechanical degradation. When the target stockpile area is in a critical state of mechanical degradation, safety and environmental protection early warning information is output, enabling early warning of instability and pollution risks in high-moisture-content fine-particle solid waste stockpiles, thus improving the reliability and timeliness of safety and environmental protection risk assessment.

The application discloses a building cross-subsystem data sharing and dynamic permission allocation method based on Internet of Things, and relates to the technical field of building cross-subsystem data processing. Specifically, the analysis of the analysis timeliness and analysis processing capacity of building cross-subsystem data in the sharing process is carried out, the analysis result is used as a benchmark to quantize the adaptation of permission allocation, the analysis capacity is adapted to dynamic load and permission decision, the data quality and communication state are matched, the timeliness and resource utilization efficiency of permission allocation in the building scene are balanced, and therefore, the accuracy of the permission allocation result is improved.

The application discloses an abnormal working condition identification and control method and system of an electric valve station, and the method comprises the following steps: collecting a working condition signal set of a low-voltage switch cabinet of the electric valve station and / or an auxiliary signal set of a control cabinet of the electric valve station; identifying the working condition of the electric valve station based on the working condition signal set and / or the auxiliary signal set, and triggering an abnormal working condition alarm signal and a passivation control signal if the working condition is identified as abnormal. The application realizes identification, early warning and passivation control of various electric valve failure modes based on the working condition signal set of the low-voltage switch cabinet of the electric valve station and the auxiliary signal set of the control cabinet of the electric valve station, provides an effective supplement for the failure diagnosis function of the electric valve, and can improve the reliability of the process system of an enterprise and reduce industrial accident losses based on the flexible combination of various electric valve failure divisions.

The invention discloses an anti-rollover emergency braking device for a motorcycle and a control method of the anti-rollover emergency braking device. The anti-rollover emergency braking device comprises a gyroscope module, a vehicle speed obtaining module, a controller, a gear motor, an electromagnetic band-type brake device, a motor driving module and an air bag module. The gyroscope module provides three-axis acceleration and angular velocity data; the controller obtains the real-time inclination angle of the motorcycle through attitude calculation according to the three-axis acceleration and rotation angular velocity data, the real-time inclination angle is compared with a preset threshold value in real time, when the inclination angle reaches or exceeds the preset threshold value, braking is triggered, and the controller generates control signals and outputs the control signals to the motor driving module, the electromagnetic band-type brake device and the air bag module; the motor driving module drives the gear motor to operate according to the control signal and cooperates with the electromagnetic band-type brake device to realize emergency braking; and the airbag modules are synchronously started and unfolded. The tilting state of the motorcycle can be detected in real time, when the rollover risk is recognized, the motorcycle is quickly stopped, a safety protection mechanism is released, and therefore impact damage to the human body is reduced.

The application relates to an international public opinion event information dissemination and control system based on artificial intelligence, and relates to the field of social communication science. The system can monitor, identify, analyze, track and effectively control the information dissemination in international public opinion events in real time. The system uses natural language processing (NLP), machine learning (ML), deep learning (DL) and other artificial intelligence technologies to deeply mine and understand massive cross-language and cross-platform data, thereby realizing accurate identification of public opinion events, intelligent analysis of dissemination paths, early warning and intervention of negative information, and guidance and amplification of positive information. The system aims to improve the control efficiency and accuracy of international public opinion events, maintain social stability, and provide decision support and action basis for relevant departments.

The embodiment of the application discloses a mountain road trap active detection method and system based on sound wave reflection, the method comprises the following steps: collecting the echo signal of the multi-path propagation of the multi-band detection sound wave in the to-be-detected mountain road area through a microphone array, and scoring the propagation path according to a path credibility scoring mechanism; if it is determined that the trigger condition is met, it is determined that the to-be-detected mountain road area has a trap, and a risk early warning is carried out; if it is determined that the trigger condition is not met, the second feature data and the first feature data are input into a pre-trained machine learning model, and the trap category of the to-be-detected mountain road area is determined according to the machine learning model. The system has a second-level response capability, greatly improves the safety, realizes full-process automation, reduces manual intervention, and greatly improves the mountain road inspection efficiency.

The application provides an SCR multi-level coupling failure recognition method and system based on remote OBD, and belongs to the technical field of automobile aftertreatment system fault diagnosis. The method comprises the following steps: collecting vehicle remote OBD mandatory data through a data acquisition and working condition screening module, performing effective working condition screening, and eliminating invalid data; based on the effective working condition data, calculating a carrier failure index CFI and performing carrier deterioration trend prediction, calculating a liquid level failure index LFI, and calculating an OBD failure index OFI; inputting the CFI, LFI and OFI into a multi-factor fusion decision module for fusion decision, outputting a comprehensive failure index SFI and determining a failure level and a root cause; the modules are communicatively connected to form a closed-loop feedback mechanism, and the output results of any module are fed back to other related modules to adjust calculation parameters, fault recognition and failure chain tracing. The scheme improves the accuracy, real-time performance, forward-looking performance and robustness of SCR failure recognition.

The utility model discloses a coal mine tunnel fault passing rapid supporting device which comprises bases distributed at the bottoms of the two sides of a tunnel, single-cylinder hydraulic props are fixedly arranged on the bases, a supporting top plate is fixedly arranged at the upper ends of the single-cylinder hydraulic props, and a supporting side plate is hinged to the end, close to the side face of the tunnel, of the supporting top plate. One end of the support top plate is hinged to the support top plate, the other end of the support top plate is hinged to an extension top plate, the other end of the extension top plate is internally connected with a butt joint plate in an inserted mode, the butt joint plate is used for butt joint to achieve closing, and a pressure monitoring mechanism is arranged on the upper surface of the support top plate. The pressure sensor collects roof pressure data in real time, and the roof pressure data is analyzed and processed by the controller to achieve real-time monitoring and early warning of the roof pressure. Meanwhile, the extension top plate is matched with the butt joint plate, the extension top plate is driven to turn over through the second hydraulic push rod, the position of the butt joint plate is adjusted through the fastening bolt, roadway top plates with different widths can be flexibly adapted, and fully-closed supporting is achieved.

The invention discloses a concrete pump pipe fixing system and an assembling and monitoring method thereof. The system comprises a vertical fixing device, a bent pipe fixing device, a horizontal fixing device and a monitoring and control system. The assembling method comprises the following steps of positioning and paying off, installing the vertical fixing device, installing the bent pipe fixing device, installing the horizontal fixing device, installing the pipeline, and clamping and fixing. The monitoring method comprises five main steps of system initialization, data acquisition, edge calculation processing, cloud analysis and early warning, and decision support and feedback. According to the invention, lossless installation, intelligent monitoring, active early warning and predictive maintenance are realized, the construction safety is remarkably improved, the service life of equipment is remarkably prolonged, and the management efficiency is remarkably improved.

This invention discloses a remote monitoring method and system for flammable and explosive gases based on big data. It acquires raw datasets collected in real time from multiple sensors; preprocesses the raw datasets using a denoising algorithm, and obtains a first multi-parameter dataset through normalization; generates a second fusion feature set based on the first multi-parameter dataset; if the parameter values ​​of the second fusion feature set exceed a preset threshold, a classification model is used to identify gas leak events, and a diffusion model is combined to generate leak probability and range data; the leak probability and range data are compressed and encoded, and the transmission frequency and data packet size are dynamically adjusted according to network status parameters to form a stable transmission stream; the stable transmission stream is decoded at the monitoring center, and a dynamic visualization interface is generated using a visualization engine; the system reliability is judged based on the interface parameters to determine whether it meets preset standards. This invention achieves real-time monitoring, intelligent identification, and early warning of gas leaks.

The application relates to the technical field of medical safety, in particular to a patient violence behavior detection method and system based on an intelligent bracelet, which comprises a data acquisition module, a behavior analysis module, an abnormality judgment module and a prewarning execution module. The physiological and motion signals of a patient are collected in real time through multidimensional sensors, a behavior characteristic matrix is generated, a matching degree index is calculated, a violence tendency is analyzed and judged in combination with a threshold interval and time continuity, and graded prewarning and multi-channel notification are realized. The application can significantly improve the recognition accuracy of complex behavior patterns, reduce misjudgment and false positives, ensure that medical staff can respond in time, improve the safety management efficiency, simplify the medical management process, and provide a reliable solution for the whole-process automatic detection and prewarning of patient violence behavior.

The application discloses a biological age evaluation method and system based on multi-modal clinical data, wherein the evaluation method comprises the following steps: step 1, data acquisition and multi-modal construction; step 2, data preprocessing and feature expression; step 3, reference population construction and feature screening; step 4, biological age prediction model training and verification; step 5, biological age acceleration index calculation; and step 6, standardization and risk assessment output. By fusing heart ultrasound examination data and blood biomarker data, the application realizes comprehensive characterization of the aging state of an individual, further calculates a biological age acceleration index, and uses the biological age acceleration index for cardiovascular disease risk assessment, so as to solve the problems that a single-modal biological age model in the prior art cannot comprehensively depict the aging process and cannot simultaneously reflect changes in organ function and changes in systemic physiological state.

The present application relates to the technical field of livestock data processing, in particular to a livestock and veterinary breeding data analysis system, which comprises: a state transition analysis module collects data of the breeding cycle of female livestock, integrates the data of all female livestock to construct a transition probability matrix, predicts the future state transition path of female livestock according to the transition probability matrix, and generates a female livestock state transition evaluation result. In the present application, by analyzing the data of each state of the breeding cycle of female livestock, the state change path of female livestock at different stages is determined, accurate prediction and quantitative evaluation of the state in the breeding cycle are realized, and the formulation of the breeding plan is more accurate. By evaluating the residence time and transition trend of each stage, the best breeding time is predicted, and the overall breeding efficiency is improved. Based on the similarity analysis of behavior data such as activity frequency, body temperature and number of reproductions, individual female livestock is divided into different behavior groups, and more targeted reproduction management strategies are formulated for different groups.

The present application relates to the technical field of scraper conveyor, and particularly relates to a chain breakage fault pre-judgment device and method of a scraper conveyor and the scraper conveyor, the device comprising: a controller, a first plug plate and a first magnetic sensor fixed to the first plug plate; a conveying groove of the scraper conveyor is provided with a first opening, the first plug plate is inserted into the first opening and located at a side of the chain close to a chain channel, and the first magnetic sensor is fixed to the first plug plate and opposite to one side of the chain; in the process of running of the chain of the scraper conveyor, the first magnetic sensor collects a first magnetic characteristic signal of a chain link passing through the first magnetic sensor; the controller is connected with the first magnetic sensor, the damage state of the chain link is analyzed according to the first magnetic characteristic signal, and whether the chain link is a chain breakage fault risk point is pre-judged based on the damage state. In this way, the present application pre-judges the chain damage of the scraper conveyor in advance, so as to realize the early warning and preventive maintenance of the chain breakage fault, and the operation reliability and safety of the scraper conveyor are improved.

The invention discloses a drill string sticking early warning method and device, electronic equipment and a storage medium. The method comprises the steps that the average torque and the maximum torque of a drill column in the drilling process are obtained in real time, and the torque difference value between the average torque and the maximum torque is determined; determining a first friction resistance coefficient corresponding to the average torque and a second friction resistance coefficient corresponding to the maximum torque according to a pre-established theoretical model about the torque and friction resistance coefficients of the drill string; and according to the torque difference value, the first friction resistance coefficient and the second friction resistance coefficient, early warning is conducted on sticking of the drill column in the drilling process according to the change trend of the torque difference value, the first friction resistance coefficient and the second friction resistance coefficient within the preset time. The torque difference value, the first friction resistance coefficient and the second friction resistance coefficient are determined through the average torque and the maximum torque which are obtained in real time, real-time monitoring of the change trend of the torque difference value, the first friction resistance coefficient and the second friction resistance coefficient within the preset time is achieved, and then early warning of possible drill column sticking accidents is achieved. Operation cost can be reduced, and potential safety hazards are avoided.

The invention discloses a wind turbine generator gearbox state monitoring and fault early warning method and system. The method comprises the following steps: defining a key part of a gearbox of a wind turbine generator as a flexible body, and constructing a multi-body dynamic model based on the flexible body; the multi-body dynamics model receives input multi-source time sequence data, then performs feature extraction and multi-index fault early warning algorithm processing, and outputs signal abnormal information for the current multi-source time sequence data; the signal abnormal information is gearbox fault data; constructing a mixed data set guided by a physical mechanism and performing data enhancement; and inputting a spatial-temporal feature coding fault diagnosis model based on the enhanced mixed data set, and then outputting a health index. According to the intelligent early warning system for the wind turbine generator gearbox, through the technical innovation of making up for data missing through modeling simulation, improving diagnosis precision through an intelligent algorithm and guaranteeing real-time early warning through edge calculation, a set of intelligent early warning system for the wind turbine generator gearbox which is high in precision, low in time delay and strong in generalization is successfully constructed.

The application relates to the technical field of water resource protection, and particularly discloses a device for constructing an ecological barrier in a surface-underground water interaction zone, which comprises a barrier construction pool; a purification pool is arranged on one side of the inside of the barrier construction pool; an aeration pool is arranged on the middle side of the inside of the barrier construction pool; a wetland pool is arranged on the other side of the inside of the barrier construction pool; a purification mechanism is jointly arranged between the inner walls on the two sides of the wetland pool; and a plurality of interception mechanisms are embeddedly arranged on one end of the barrier construction pool; the purification pool, the aeration pool and the wetland pool can sequentially perform biological degradation, aeration decomposition and plant purification treatment on surface water, so that the surface water flowing into the interaction zone is comprehensively purified; the plurality of planting mechanisms in the wetland pool can utilize the biological degradation capacity of aquatic plants to absorb and transform pollutants in the surface water, improve the water quality, and further avoid the pollutants contained in the surface water from penetrating into the underground water along with the water flow to pollute the underground water.

This invention discloses a method and system for identifying crop pests based on visual recognition, belonging to the field of pest identification technology. A crop pest identification system based on visual recognition includes a crop visual processing module and a crop pest identification module. This invention constructs a multi-source information collaborative judgment mechanism by integrating visual image features, volatile gas concentrations, and environmental parameters, effectively distinguishing between physiological abnormalities and pathogenic diseases, reducing misjudgments and missed judgments caused by environmental interference, and significantly improving the accuracy and reliability of identification results. By combining gas sensor data to analyze crop respiration characteristics and maturity status, it can identify crop physiological abnormalities before visual symptoms appear, achieving early detection and warning of pests. Dynamically adjusting the identification threshold and sensitivity according to different growth stages supports targeted prevention and control decisions, improving the timeliness of prevention and control.

The invention relates to the field of violation monitoring, in particular to violation behavior monitoring equipment and method based on dual prevention. The technical problems that in the prior art, a violation behavior monitoring method lacks a prediction analysis and risk prevention and control mechanism, so that the early warning capability and the prevention and control effect of a monitoring system are limited, and a passive response mode is mostly adopted, that is, the violation behavior can be found and recorded only after the violation behavior occurs, and early warning and prevention cannot be performed in advance are solved; according to the technical scheme, the violation behavior monitoring equipment based on dual prevention comprises a high-definition camera, a mounting rack and a central processing unit; according to the invention, by introducing a risk assessment mechanism, quantitative assessment is carried out on the properties and consequences of the violation behaviors, the hazard level of the violation behaviors is determined, a scientific basis is provided for subsequent treatment measures, potential risk behaviors are predicted through a machine learning algorithm, early warning and prevention and control are realized, and occurrence of the violation behaviors and accumulation of potential risks are effectively reduced.

The invention relates to the field of fishery data fusion, and discloses an offshore fishery data resource assessment method combined with multi-source heterogeneous data fusion, which comprises the following steps of: performing data preprocessing, data space-time matching and data heterogeneous fusion on offshore fishery related multi-source data to obtain fused offshore fishery related data; and carrying out data analysis on the fused offshore fishery related data, and evaluating resource states of different positions in a sea area by combining a fishery resource evaluation model so as to realize early warning of offshore fishery data resources. According to the method, excessive fishing, population structure degradation and ecological chain collapse can be avoided, and overall management of related resource data of Xian'an offshore fishery in different dimensions is realized.

The application belongs to the technical field of electric data processing, and particularly relates to a multi-measuring piece linkage aircraft structure state early warning method, wherein each strain gauge is classified according to data characteristics; based on the classification result, at least one classification correlation method is applied to determine a three-level alarm position; based on the result of the three-level alarm position, a space or structure correlation rule is applied to determine a two-level alarm position; based on the result of the two-level alarm position, clustering determination is performed in a key area of the structure to determine a one-level alarm position; the application overcomes the problem of difficult positioning of a weak position after abnormal strain data recognition, realizes monitoring and early warning of a structure dangerous position, and effectively supports command and decision making on a test site.