68results about How to "Avoid false negatives" patented technology

The invention discloses a loss diagnosis and health management system and method for a transformer, and belongs to the technical field of intelligent transformers, and the system comprises a thermal fingerprint module which is used for recording a temperature drop curve of each part of the transformer after planned power failure, and obtaining a thermal inertia fingerprint of the transformer based on the fitting of multiple temperature drop curves; the theoretical temperature module is used for calculating the theoretical cold body temperature of each part of the transformer based on the real-time environment temperature and the thermal inertia fingerprint when the transformer runs; the net temperature rise module is used for acquiring the actual temperature value of each part of the transformer and subtracting the corresponding theoretical cold body temperature from the actual temperature value; weak thermal characteristic signals caused by insulation aging and loss abnormity of the transformer can be accurately extracted from strong background noise such as load fluctuation and environment temperature through technologies such as thermal inertia fingerprint construction and net temperature rise separation, early diagnosis of progressive health deterioration is realized, support is provided for intervening potential faults in advance, and the fault diagnosis accuracy is improved. And the passive situation of post-treatment of operation and maintenance is changed.

The invention discloses a wear online identification and compensation control system and method for a high-pressure distribution plunger and barrel assembly, and the system comprises a data collection module which is used for collecting working condition data and state data; a health state dynamic baseline model obtained through offline training is arranged in the data processing module, and the wear level of the plunger and barrel assembly is recognized by calculating the residual error between actual state data and health state data predicted by the model under the current working condition; and the compensation control module is used for generating a self-adaptive compensation control instruction according to the identified wear grade and the current working condition and sending the self-adaptive compensation control instruction to an execution mechanism. According to the method, the dynamic base line synchronous with the real-time working condition is constructed, early weak wear characteristics can be separated from strong working condition interference, the recognition sensitivity and accuracy are improved, the influence of wear on the system performance is actively counteracted through closed-loop adaptive compensation control, the service life of equipment is expected to be prolonged, and the system performance is improved. And technical support is provided for predictive wear monitoring management.

This invention relates to the field of intelligent water control terminal control and electromagnetic compatibility processing technology, and particularly to an anti-interference water control terminal control method and system with abnormal alarm. The method includes: reading raw signals in parallel from water shortage, anti-magnetic, and flow sampling interfaces; processing and mapping these signals into alarm events and writing them into a hardware alarm event set; performing board-level partitioning layout based on the information in the event set to generate a partitioning layout configuration set; configuring decoupling units, laying grounding wires and copper plating, and setting multiple grounding nodes accordingly; assigning power supplies to each detection interface to an analog power path and power supplies to the main control and communication modules to a digital power path, configuring filtering units and isolation nodes; laying grounding copper foil and vias for the crystal oscillator, and configuring metal shielding structures for key modules; reading alarm signals based on the obtained configuration set and encapsulating them into alarm messages, uploading them via Bluetooth or 4G channels, receiving management results, and generating a terminal alarm processing status. This invention improves the anti-interference capability and alarm reliability of the water control terminal through event-driven board-level layout and power supply link isolation.

This invention relates to the field of biomedical detection technology, providing a reagent, kit, and detection method for detecting *Vibrio cholerae* serogroup O139 using loop-mediated isothermal amplification (LAMP). This invention targets the synergistic regulation of the tcpA and hlyA genes in *Vibrio cholerae* serogroup O139, designing LAMP detection primers and establishing a LAMP detection method based on isothermal amplification. These LAMP detection primers or loop primers show promising applications not only against *Vibrio cholerae* serogroup O139 but also against other nosocomial infection bacteria. The LAMP primers for detecting *Vibrio cholerae* serogroup O139 can be used to detect *Vibrio cholerae* serogroup O139 in clinical patients or for outpatient screening. The kit of this invention can effectively and specifically detect single-reaction, single-copy, or higher copies of *Vibrio cholerae* serogroup O139. Compared to the "gold standard" real-time quantitative PCR, the kit of this invention offers higher accuracy and sensitivity, completing the detection within 30 minutes.

This invention provides a method for detecting sensor anomalies in nuclear power plants. The method includes: constructing a principal component analysis model, calculating the Q-statistic, and determining a first threshold; training a Bayesian long short-term memory neural network model and calibrating its prediction interval; calculating a second and third threshold based on the predicted value and uncertainty output by the calibrated model; inputting test data into the two models to obtain the Q-statistic, predicted value, and uncertainty, and comparing them with the corresponding thresholds to obtain three judgment results; and making a final judgment on the three results using a logical judgment table. This invention integrates spatiotemporal characteristics and uncertainty assessment, achieving high-precision and high-reliability sensor anomaly detection with only normal operating data, exhibiting high reliability and robustness.

The application discloses a high-pressure gas particle counter with a laser diode as a light source, which comprises an optical detection unit, a gas path system and a standard particle reference system, wherein the optical detection unit is used for generating laser and dividing the laser into two independent light paths, i.e., a main light path and an auxiliary light path, and is used for irradiating a main detection area and an auxiliary detection area respectively and receiving a particle scattering light signal and converting the particle scattering light signal into an electric signal; the gas path system is used for selectively conveying a high-pressure gas to be measured and a standard particle gas to the main detection area and the auxiliary detection area; the application belongs to the technical field of gas particulate pollution monitoring, and aims to solve the problem that the output light power of a laser diode in the prior art will drift with the increase of working time and the change of temperature, thereby causing the measurement reference to be inaccurate, and achieves the technical effect that a real-time online dynamic calibration mechanism is constructed by introducing an auxiliary reference light path and the standard particle reference system, and the problem of the measurement reference drift caused by factors such as light source aging and temperature drift is effectively overcome.

The application relates to the technical field of automobile transmission shaft production, in particular to a safety management system for automobile transmission shaft production based on big data, which comprises a data acquisition module, which is used for collecting production parameter data, environment parameter data, operator behavior data and quality inspection data of multiple production devices in the automobile transmission shaft production process in real time, and constructing an original safety data set; a big data processing platform, which is in communication connection with the data acquisition module, is used for cleaning, fusing and standardizing the original safety data set, and generating a standardized safety data set; a safety risk research and judgment module, which is connected with the big data processing platform, is used for storing a dynamic safety threshold model, and identifying abnormal states and safety risks in the transmission shaft production process in real time based on the standardized safety data set, and outputting quantitative research and judgment results; the safety risk research and judgment module realizes the whole domain monitoring, hierarchical early warning, millisecond-level emergency shutdown and closed-loop control of the transmission shaft production safety, and significantly improves the response speed and management efficiency.

This invention discloses an anti-theft alarm fastener. By integrating a position detection module, a control module, and an alarm module into the male and female buckles of an existing magnetic fastener, it achieves real-time monitoring of the fastener's connection status and automatic alarm functions upon unauthorized separation. The control module, with its function selection button, allows the fastener to flexibly switch between at least two operating modes: alarm function off or on. This greatly improves the product's practicality and applicability, meeting diverse user needs in different situations. The position detection module uses a magnetic trigger and a Hall sensor element to form a non-contact position detection module, avoiding reliability issues caused by contact oxidation, wear, or poor contact in traditional mechanical switches. Furthermore, the mating structure of the mounting groove and positioning recess improves the accuracy and consistency of detection, effectively avoiding misjudgments or missed alarms due to positional misalignment.

The invention provides a vehicle-mounted highway tunnel brightness real-time monitoring and early warning system, and belongs to the technical field of vehicle driving, and the system comprises a data obtaining module which obtains tunnel brightness test data through a real vehicle driving experiment; the image preprocessing module obtains a tunnel driving image and preprocesses the tunnel driving image to obtain a seven-dimensional spatial-temporal feature vector; the brightness identification monitoring module establishes a tunnel brightness identification model according to the test data and the seven-dimensional spatial-temporal feature vector, and extracts a tunnel brightness value; the threshold generation and early warning module classifies the brightness values by using an improved clustering algorithm to obtain a tunnel dangerous brightness threshold and performs early warning; and the vehicle-mounted integrated module connects the tunnel brightness identification model and the tunnel dangerous brightness threshold to the vehicle to realize real-time monitoring and early warning. The problems that tunnel safety protection is high in deployment threshold and high in cost due to the fact that a professional brightness detection instrument is needed to obtain accurate brightness detection capacity when a vehicle enters and exits a tunnel, and an existing early warning mechanism lacks dynamic environment continuous quantitative evaluation are solved.

The invention discloses an underground water multi-pollutant rapid prediction and diagnosis system, which comprises a multi-parameter sensing and data acquisition module used for acquiring underground water quality parameters in real time; the edge pretreatment unit is used for carrying out edge pretreatment on the underground water quality parameters; the off-line synthetic data engine is used for generating synthetic training data of transient extreme working conditions; the feature engineering processing unit is used for constructing interaction features based on a geochemical mechanism; the AutoML reasoning unit is used for deducing and outputting a pollutant concentration predicted value through a model; and the physical-data dual-drive fault diagnosis module is used for diagnosing the authenticity of pollution according to three-dimensional calculation results of the physical residual calculated by the physical residual calculation unit, the mean square error of the sensor data calculated by the data reconstruction error unit and the difference between the observed value and the predicted value calculated by the statistical test unit. And judging whether to give an alarm according to the diagnosis result. According to the scheme, the specific pollutants can be accurately identified, and the authenticity of pollution can be accurately identified.

The application discloses a kind of rail vehicle pipe joint loosening detection method and system, belong to rail transit vehicle pipe joint detection field;The method comprises: local posture decoupling, detects pipe joint structure features and establishes local coordinate system, estimates local transformation;Marked line skeleton extraction extracts anti-loose mark line candidate area and skeleton, obtains the detected mark line track and template mark line track;Homologous track comparison, according to the boundary division fixed side, active side and cross-seam neighborhood section, template mark line track is mapped into reference mark line track, and the joint deviation feature of the detected mark line track is calculated;Loosening determination output, according to joint deviation feature and registration confidence, calculate loosening risk score, output pipe joint state result.Template image homologous reference, local coordinate system eliminates visual angle deviation, curve topological structure represents anti-loose mark line, distinguishes line drawing non-standard and real loosening, avoids false alarm and miss report, improves detection accuracy and robustness.

The application provides an engineering quality detection data tamper-proofing and abnormal early warning method and system, relates to the technical field of engineering quality detection, and comprises the following steps: obtaining original detection data and tamper-proofing and storing evidence; generating a detection report based on the original data and tamper-proofing and storing evidence; matching a deviation allowable threshold from a dynamic parameter library according to the engineering type, grade and equipment accuracy; comparing the detection report with the original data, comparing the self-inspection data with the sampling inspection data, and obtaining comparison results; constructing a capability portrait based on historical data of a detection institution and performing abnormal scoring by using an unsupervised algorithm; determining an abnormal grade and grading early warning by comprehensively considering the comparison results and the comprehensive abnormal score; and storing evidence by chaining the hash values of the detection report and the original data and generating a verification two-dimensional code. The application realizes multi-source cross verification and can effectively identify data abnormal situations such as inconsistency between report values and original records.

The application relates to the technical field of data processing, and discloses a rain and sewage mixed connection tracing and spatial positioning method for a drainage pipe network of a micro monitoring station network, which comprises the following steps: according to the flow connection relationship of the drainage pipe network and the layout nodes of the micro monitoring station, the upstream confluence pipe network range of each micro monitoring station is defined, and a unique mapping relationship database between each pipe section and the corresponding multi-level monitoring topological sequence thereof is established; water quality and water level data of the monitoring station are acquired, and an analysis time period is intercepted; based on the space-time propagation correlation attribute of the data between the stations, a target monitoring topological sequence currently producing a response is identified in the mapping relationship database; a homomorphic mapping candidate pipe section set corresponding to the sequence is locked, and a pollutant source discharge inversion model of each candidate pipe section is constructed according to the fluid transport and diffusion mechanism of the pipe network; the model is used to calculate the fitting deviation degree of each candidate pipe section source hypothesis to the monitoring data, and the pipe section with the minimum deviation degree is selected as the positioning result.

The invention relates to the technical field of tunnel construction, and provides a machine-rock coupling state detection method and system based on multivariate information perception in order to solve the problem that a dynamic contact state cannot be distinguished in real time at present. The machine-rock coupling state detection method based on multivariate information perception comprises the following steps: acquiring three-dimensional point cloud data of a tunnel face, and constructing a tunnel environment dynamic map and marking key features by combining internal structure information of a rock mass; based on a mechanical arm kinematic model, in combination with a tunnel environment dynamic map and mechanical arm tail end motion state information, a mechanical arm obstacle avoidance path and an optimal tunneling track are planned; the mechanical arm pose offset, the contact stress gradient and the rock mass fracture density in the operation process of the mechanical arm along the mechanical arm obstacle avoidance path and the optimal tunneling track are obtained, and after processing is conducted through the dynamic machine-rock contact recognition model, the classified contact state is obtained, and the rock mass contact trend is predicted; and when the predicted rock mass contact trend is abnormal, the early warning level is determined according to the current classification contact state, and a control instruction is generated, so that motion parameters of the mechanical arm are adjusted in real time, and an emergency protection mechanism is triggered.

The application provides a building fire-fighting early warning system and method, and belongs to the technical field of building fire-fighting safety. The application synchronously collects temperature, smoke concentration and carbon monoxide concentration data in each monitoring area of a building, calculates the deviation degree of sensor sliding window variance and baseline variance, evaluates the reliability index of each sensor in real time and generates adaptive fusion weight, simultaneously detects and isolates the fault sensor through time sequence deviation residual analysis, evaluates the consistency between sensors and generates a correction weight, relies on the dynamic update of the environment baseline based on the exponential weighted moving average, generates a graded early warning threshold for each area and triggers the corresponding response measures. The application effectively improves the robustness of the system under the condition of sensor failure, enhances the fusion accuracy in the multi-sensor conflict scene, realizes the early prediction of the fire spread situation, reduces the false alarm rate while maintaining a high fire detection sensitivity and a short detection response time.

The present application relates to the technical field of battery management, in particular to a lithium battery pack intelligent management system based on multi-modal sensing. It comprises: a multi-modal sensing and fusion unit that collects battery pack operating environment and internal state data in real time, and fuses the operating environment and internal state data through weighted average to generate fused multi-modal data; an intelligent management master unit that predicts battery health state calculation based on cumulative gas production life mapping model, and predicts thermal runaway risk through a long short-term memory network model to generate control instructions, state information and alarm signals; a power execution unit that performs overcharge and overdischarge protection operations on the battery pack based on the control instructions. The present application collects multi-dimensional data such as voltage, current, temperature and gas concentration through a multi-modal sensing module, and extracts key features such as voltage consistency, temperature distribution and current fluctuation by combining statistical analysis and time-frequency transformation methods, thereby achieving comprehensive perception of the battery pack operating state.

The invention relates to the technical field of filling automation control, in particular to a cosmetic filling control method based on a large model knowledge graph, which comprises the following steps: acquiring an actual filling rate to determine a dynamic filling efficiency index, and determining whether the filling efficiency is stable based on the dynamic filling efficiency index. Determining the abnormal level of the filling efficiency in combination with the nitrogen filling response delay; determining that the filling efficiency is reduced due to the fact that moisture absorption raw material components are influenced by environmental factors to change the viscosity of a material body based on the combination of the viscosity-temperature sensitivity coefficient and the actual viscosity of a product and the environmental humidity, and adjusting a temperature set value of a compression area; the actual response time for adjusting the nitrogen flow is obtained to determine a response efficiency index, whether the comprehensive efficiency of nitrogen charging meets the expectation or not is determined based on the response efficiency index, and the calibration delay for determining the abnormal level of the filling efficiency is adjusted. The filling process is regulated and controlled on the basis of the product characteristics of cosmetics needing to be filled and the characteristics of filling equipment.

This invention discloses a method and system for detecting operational faults in wind turbine blades, relating to the field of reinforcement learning technology. The method includes: acquiring multi-source operational data and repair background data corresponding to the surface treatment area of ​​a target wind turbine blade; performing segment-level temporal alignment and region association based on the multi-source operational data and repair background data; constructing a local synchronous monitoring segment corresponding to the surface treatment area; establishing a background constraint compensation mechanism corresponding to the surface treatment area based on the repair background data and the local synchronous monitoring segment; extracting the background state vector and background compensation offset result corresponding to the surface treatment area; and determining the target detection strategy template corresponding to the surface treatment area based on the background state vector from a preset detection strategy template library through a reinforcement learning-driven strategy orchestration mechanism. This invention can improve the accuracy, stability, and adaptability of wind turbine blade operational fault detection under complex repair backgrounds.

The application discloses a constant-temperature workshop temperature and humidity detection system, and relates to the field of intelligent device layout. The technical scheme realizes accurate environment modeling by constructing a three-dimensional space model and a multidimensional database, adopts a phased experimental verification system, scientifically quantifies the spatial relationship between a ventilation control domain and a device influence domain, innovatively uses a data point cloud matching technology to establish a temperature gradient field and a distance attenuation curve, combines device thermal effect analysis and a regional coincidence rate algorithm, realizes intelligent differentiated layout of temperature and humidity sensors, establishes deep integration of physical space modeling, dynamic experimental verification and data-driven decision-making, guarantees result repeatability through a standardized experimental process, optimizes sensor deployment density by using the spatial mapping relationship between the device and the air vent, significantly improves temperature control accuracy while reducing operation and maintenance costs, forms a complete closed loop from data collection, experimental verification to intelligent control, and provides an environment monitoring solution with scientificity and engineering practicability for constant-temperature workshops.

The present application belongs to the technical field of fault detection, and particularly relates to a kind of electric energy metering box connection terminal temperature rise automatic inspection system, including acquisition module, obtains real-time temperature, ambient temperature and load current;Feature extraction module generates thermal state feature vector containing temperature absolute value, temperature rise rate, duration and contact resistance change trend factor;Abnormality discrimination module compares feature vector with adaptively updated dynamic threshold set, and outputs abnormal temperature rise confirmation signal;Execution module determines real abnormality, transient response or unstable state according to contact resistance change trend factor and load current fluctuation rate, and outputs early warning in stages.The present application realizes self-adaptive, multi-dimensional automatic inspection of terminal temperature rise, effectively distinguishes bad contact, overload and harmonic interference and other working conditions, reduces false alarm and missed alarm rate, and improves power distribution network operation safety and intelligent level.

The present application relates to the field of data processing, and more particularly to a kind of based on end-edge-cloud cooperation's electric energy meter fault early warning method and system, method includes: end side gathers voltage, current waveform, short time window is divided to calculate variance and is uploaded to edge node;Edge node constructs self-adapting suppression coefficient according to voltage variance variation and current variance variation, the variance of target window is transiently inhibited, and the variance after inhibition is obtained;Long time window is constructed, and environmental baseline is constructed according to the variance after inhibition, and the independent fluctuation energy of electric energy meter is calculated;Edge node constructs sliding window to real-time independent fluctuation energy, and health deviation index is calculated, and fault is judged according to health deviation index and early warning threshold value.The present application reduces data transmission and storage cost through end-edge-cloud cooperation, eliminates load switching interference, decouples environmental common mode drift, and realizes the precise early warning of electric energy meter hardware degradation.

The application provides a temperature anomaly detection method and device for an electric vehicle battery swap connector, a terminal, a medium and a product, comprising: obtaining current raw data of a plurality of temperature sensors of a plurality of electric vehicle battery swap connectors to be tested and preprocessing to obtain a current multi-channel temperature data set; performing multi-dimensional layered feature extraction on the current multi-channel temperature data set to obtain a current multi-dimensional feature set; inputting the current multi-dimensional feature set into a pre-trained anomaly detection model based on an isolation forest to obtain a current anomaly detection result; based on the current anomaly detection result, performing a double threshold anomaly determination operation to determine an electric vehicle battery swap connector with a temperature anomaly. The multi-dimensional features of the application are comprehensive and can adapt to the actual working scene of the battery swap equipment. In addition, the double threshold anomaly determination of the application avoids false negatives or false positives caused by a single threshold, improving the detection accuracy and reliability.

The application provides a vehicle lamp fault detection system and a vehicle, and relates to the technical field of vehicle lamp control. The system comprises a photosensitive module, a thermosensitive module, an electric signal detection module and a vehicle lamp control module. The photosensitive module is used for detecting a light intensity signal of a target vehicle lamp. The thermosensitive module is used for detecting a temperature signal of the target vehicle lamp. The electric signal detection module is used for detecting an electric signal when the target vehicle lamp is working. The vehicle lamp control module performs fault type detection of the target vehicle lamp based on the light intensity signal, the temperature signal and the electric signal. Through multi-dimensional signal acquisition of the photosensitive module, the thermosensitive module and the electric signal detection module, the application can realize accurate diagnosis of the fault type of the vehicle lamp, break through the limitation of traditional binary detection, can distinguish the fault type of the vehicle lamp, and thus significantly improve the vehicle lamp fault detection effect.

The utility model relates to the technical field of flood control early warning device, and disclose a kind of flood control early warning device of adjustable rainfall threshold, including controller, the outer surface of controller is equipped with fixed link, the upper surface of connecting plate is equipped with alarm lamp, the both sides of fixed link are all set up with sliding slot, the outer surface of fixed link is equipped with the observation mechanism of convenient observation scale line, the lower surface of controller is equipped with the adjustable detection mechanism of height adjustable, the utility model is adjusted detection mechanism by setting, utilize motor drive screw rod and the thread transmission of movable plate, the lifting position of water level sensor can be accurately controlled, according to the actual demand of different installation area, the initial detection height of sensor can be flexibly adjusted, this not only improves the adaptability of device to different terrain, also avoids the false alarm or the false alarm caused by fixed installation height unreasonable, realizes the accurate adjustable of rainfall threshold, improves the reliability and flexibility of flood control early warning.

The invention discloses a driver pressure judgment method and system based on physiological signals. The method comprises the steps that actual values of all physiological indexes of a driver are collected in real time; determining a reference value of each physiological index based on each physiological index of the resting state of the driver; determining the deviation degree of the actual value of each physiological index relative to the reference value; determining an overall pressure index based on the deviation degree of each physiological index; and determining the pressure state of the driver according to the overall pressure index. According to the method, the actual value of each physiological index of the driver is collected in real time, the reference value is determined based on the resting state of the driver, and the deviation degree and the overall pressure index are calculated, so that the pressure state is accurately judged, and the method has the advantages of improving the accuracy and reliability of driver pressure judgment and adapting to individual differences and environmental changes.

The invention relates to an intelligent mountain tunnel gushing water prevention and control system under complex geological conditions, which comprises a coupling sensor module, a detection equipment module, a data transmission module and a central control module, the coupling sensor module is used for acquiring geological physical field data including temperature gradient, fracture opening degree, ground stress, water pressure, fault slip rate and / or pressure wave amplitude; the central control module is used for dynamically identifying a geological scene and an evolution state by receiving geological physical field data from the coupling sensor module, generating a regulation and control instruction based on an identification result, sending the regulation and control instruction to the detection equipment module, and driving the detection equipment module to execute a corresponding detection behavior and an engineering intervention action; the detection equipment module can respond to a regulation and control instruction generated by the central control module and is matched with the coupling sensor module to complete collection and detection of geological physical field evolution data in special scenes of the mountain tunnel, and the special scenes comprise a single scene and a coupling scene.

The application discloses a multiplex PCR primer set for simultaneously detecting multiple symbiotic bacteria and viruses in Bemisia tabaci, comprising the following: a primer pair for detecting TYLCV, the nucleotide sequences of which are shown as SEQ ID NO:1 and SEQ ID NO:2; a primer pair for detecting Rickettsia , the nucleotide sequences of which are shown as SEQ ID NO:3 and SEQ ID NO:4; a primer pair for detecting Cardinium , the nucleotide sequences of which are shown as SEQ ID NO:5 and SEQ ID NO:6; and a primer pair for detecting Hamiltonella , the nucleotide sequences of which are shown as SEQ ID NO:7 and SEQ ID NO:8. The application solves the technical problems of low detection efficiency, large sample consumption, high reagent cost, inconvenient data comparison and poor compatibility of primers in a multiplex PCR system in the prior art.

The invention provides a big data intelligent analysis early warning platform and method for the constructional engineering industry, and belongs to the technical field of building management, and the method specifically comprises the steps: determining the real-time update data of a concerned bidding company, and combining the distribution coincidence condition of the concerned bidding company in different constructional engineering projects to obtain the real-time update data of the concerned bidding company; determining that the prewarning processing strategy of the bidding company needs to be optimized; when the bidding company does not belong to the concerned bidding company, bid-winning project data of the bidding company is determined, and a data processing method of the bidding company is determined in combination with distribution data of associated bidding companies of the bidding company in different bidding projects; according to the invention, the data processing method and the project file are utilized to analyze and process the bidding risk condition between the bidding companies, and the early warning management method is determined according to the analysis data of the bidding risk condition of the bidding companies and the bidding risk identification data of the bidding projects of the bidding companies, so that the identification processing efficiency and reliability of the bidding risk are improved.

The application provides an infrared video monitoring method and system for fire alarm, comprising the following steps: obtaining a thermal infrared image of a specified scene, and determining the fire smoke concentration of the specified scene according to the thermal infrared image; on the basis of obtaining the thermal infrared image, continuously obtaining the thermal infrared image of the specified scene, and monitoring the change of the fire smoke concentration through real-time analysis; periodically and continuously obtaining the thermal infrared image and monitoring the fire smoke concentration, determining whether the fire smoke concentration exceeds a pre-set threshold according to the continuously obtained thermal infrared image and the change of the fire smoke concentration; in the case that there is obvious flame point, triggering the fire alarm, sending an alarm notice to relevant personnel, and recording relevant information; if there is only smoke without obvious flame point, sending a warning notice to relevant personnel to prompt potential fire risk.