357results about How to "Resolve interference" patented technology

The invention discloses a solid state disk data reading method and system, a storage medium and a program product, and the method comprises the steps: calculating a temperature change rate and a temperature accumulation effect coefficient of a to-be-read data block according to a current temperature value and a historical temperature record; dividing the physical page address into a plurality of subintervals, and determining a loss level; calculating an initial reading voltage threshold value; compensating the initial reading voltage threshold value to obtain a target reading voltage threshold value; performing parallel reading on the to-be-read data block by adopting the target reading voltage threshold value to obtain original reading data; performing crosstalk correction on the original read data to obtain corrected data; when the reliability verification result of the corrected data of any subinterval is lower than a preset threshold value, error correction processing is carried out; and updating the loss level of the sub-interval according to the verification result of the reliability verification, and re-dividing the sub-interval of the data block to be read. The data reading delay is reduced, and the performance of the solid state disk in a scene of frequently reading small files is improved.

The invention relates to the technical field of fault detection for a wireless communication network, and discloses a fault detection method for the wireless communication network. By collecting data of base station signal strength, network delay, data packet loss rate and user equipment signal quality, the problem of insufficient fault detection caused by a single index is solved. Through multi-dimensional data acquisition, the system can comprehensively evaluate network performance, the fault detection accuracy is improved, and different fault types can be effectively identified especially in a complex fault mode. By storing the data according to the time sequence, the problem of time sequence chaos is avoided, and accurate detection of time-varying faults is ensured. The comprehensive data vector generated by each time of sampling comprises a plurality of network performance indexes, so that the fault detection and positioning capability is improved. Abnormal values are eliminated through data preprocessing, the data quality is ensured, an accurate basis is provided for subsequent analysis, and the reliability of a detection result is ensured.

The invention provides a pesticide residue detection method and device combined with mass spectrometry, and relates to the technical field of pesticide residue detection.The method comprises the steps that a sample image is recognized, and a sample type and sample morphology characteristics are determined; matching and determining a pretreatment process and a sample interference matrix; detecting according to a pretreatment process; inputting the sample type, the sample morphology characteristics and the detection data set into a pesticide component analysis channel for identification, and outputting a pesticide residue component set; and performing interference correction on the plurality of pesticide concentrations according to the experimental equipment attribute characteristics, the interference matrix type set and the matrix content set, outputting a plurality of corrected pesticide concentrations, and generating a pesticide residue detection report. The technical problem that the accuracy and reliability of pesticide residue detection are poor due to the fact that matrix interference of different types of products cannot be handled in a traditional method can be solved, the interference problem of pesticide residue detection under a complex matrix can be effectively solved, and the accuracy and reliability of pesticide residue detection are remarkably improved.

The invention provides a sick juvenile fish identification method based on an improved YOLOv10 model, and the method comprises the steps: collecting a fish image in a water area as a to-be-detected image, and carrying out the preprocessing of the to-be-detected image, and obtaining an image data set; the method comprises the following steps: constructing a YOLOv10-UDFishNet model; the image data set is input into the YOLOv10-UFFishNet model, the YOLOv10-UFFishNet model is trained through the image data set, and the trained YOLOv10-UFFishNet model is obtained; and inputting a fish image in a water area to be detected into the trained YOLOv10-UFFishNet model to obtain a fish detection result and position information of a fish individual target. According to the method, the sick juvenile fish in the turbid underwater environment can be accurately and efficiently identified.

The invention relates to the technical field of spine deformation recognition, in particular to a spine deformation recognition method and system based on image recognition, and the method comprises the following steps: S1, data collection and preprocessing: obtaining multi-view and multi-time-point spine image data of the spine of a patient; s2, soft tissue shielding correction: automatically identifying and correcting interference of the soft tissue on the spine image data; s3, dynamic change prediction of the spine: performing dynamic change prediction on the spine image data subjected to soft tissue shielding correction; and S4, deformation judgment and result output: judging the deformation condition, the deformation type and the severity of the spine, and generating a visual report containing the spine deformation condition and future change prediction. According to the method, the noise in the image is effectively removed, the definition of the spine structure is enhanced, and meanwhile, the interference problem of soft tissue on the spine image is solved.

The invention provides an adaptive CFAR detection method based on scene classification, and the method comprises the steps: carrying out the scene classification of an input SAR image through employing a K-means clustering algorithm, carrying out the target detection of a pure sea area obtained through classification through employing VI-CFAR, and carrying out the CFAR detection of a coastal area through employing a significance model. According to the method, the problems that a traditional CFAR algorithm is high in false alarm rate and unstable in detection performance in port and land complex backgrounds are effectively solved, detection parameters are optimized according to the complexity of different scene backgrounds, and therefore it is ensured that the CFAR algorithm can still maintain the constant false alarm rate in the sea clutter background, and the robustness of target detection is remarkably improved. The ocean area and the land area in the image are effectively distinguished, and the land area is shielded. According to the technical scheme, the problem that a traditional CFAR detection algorithm is interfered by a complex land background when detecting ships on the sea surface is solved.

The invention discloses a substation unmanned aerial vehicle middle and low altitude automatic flight patrol safety management and control method, and relates to the technical field of intelligent operation and maintenance of power system equipment, and the method comprises the steps: setting a plurality of micro radar signal sources in a substation, and testing the signal intensity of a wireless communication system; dividing an interference area through the three-dimensional model of the transformer substation, recording the coordinates of the area causing the abnormity of the unmanned aerial vehicle equipment, and setting the area as a flight forbidden area; and generating an unmanned aerial vehicle flight path based on the transformer substation three-dimensional model, and setting a corresponding flight height and an electrified equipment distance according to different voltage class sites. According to the invention, double-AP module distributed deployment and multi-direction obstacle avoidance module configuration are adopted, so that the reliability of a communication link and the flight safety are guaranteed; based on interference area identification and differentiated parameter setting of a three-dimensional model, a precise control mechanism for different voltage levels is established, and the reliability and operation efficiency of automatic inspection of the unmanned aerial vehicle are improved.

The invention discloses a coal seam working face floor detection and analysis method, and relates to the technical field of detection and analysis. Potential change conditions of different positions and different elevations are observed through a parallel electrical method instrument, resistivity distribution conditions of different depths in a working face and a bottom plate of the working face can be obtained through three-dimensional electrical method inversion, and the resistivity distribution conditions provide technical support for objective and accurate geological interpretation. The hydrogeological condition of the working face floor rock stratum can be better understood, so that an important reference basis is provided for safe mining; the thermal effect and the electromagnetic effect existing in the environment are evaluated and corrected, so that the deviation of the measured conductivity value can be accurately corrected, and the accuracy and the reliability of conductivity measurement data are improved; and inputting the corrected conductivity value SR (xi, yi, zi) of each grid point into a three-dimensional model, and marking to construct a conductivity three-dimensional model, so as to visually display the electrical property distribution information of the underground medium.

The invention discloses a sensing signal transmission method and device, equipment, a medium and a product. The method is applied to first equipment and comprises the following steps: acquiring a first sensing signal and a target prefix length; intercepting a cyclic prefix signal with a target cyclic prefix length from the first sensing signal; splicing the cyclic prefix signal and the first sensing signal to obtain a second sensing signal, the second sensing signal occupying a plurality of OFDM symbols; and sending a second sensing signal to a second device, so that the second device obtains the target cyclic prefix length, and splitting a cyclic prefix signal of the target cyclic prefix length from the second sensing signal to obtain a first sensing signal. By adjusting the length of the cyclic prefix signal, the device can sense a long-distance target, the problem of inter-symbol interference is solved, the sensing performance is improved, and the sensing coverage distance can be effectively improved.

The invention relates to the technical field of electrical digital data processing, and discloses a lightweight-based multi-modal data enhancement method, which comprises the following steps: acquiring a multi-modal feature tensor; extracting a vector orthogonal projection scalar and determining the novelty; updating the global covariance matrix when the novelty is greater than a redundancy threshold, and maintaining the global covariance matrix in a register state when the novelty is not greater than the redundancy threshold; extracting a main diagonal variance component to determine a differential modulation coefficient; calculating a second-order moment manifold projection operator according to the global covariance matrix, and calibrating the operator by using a differential modulation coefficient; the calibrated operator is used for carrying out orthogonal projection on random noise to generate a structured disturbance vector, the structured disturbance vector is superposed to a multi-modal feature tensor to output enhanced features, a novelty judgment mechanism is used for restraining statistical deviation caused by steady-state redundant data, computing resource occupation is reduced, and it is ensured that semantic alignment between modals is maintained in enhanced feature distribution.

The invention provides a parameter efficient fine tuning method based on a hybrid expert system, and an image segmentation method and device. The method comprises the following steps: based on an improved sensitivity constraint function and a low-rank matrix constraint function in a self-adaptive low-rank adaptation module; obtaining a target low-rank matrix corresponding to a to-be-trained model parameter of a to-be-trained network layer in the pre-trained segmentation model; obtaining an output result of the to-be-trained network layer according to the target low-rank matrix, a routing decision value of the hybrid expert system and the sample image; according to a segmentation loss value between an image segmentation result corresponding to an output result of the to-be-trained network layer and an image segmentation label of the sample image, and an equilibrium loss value corresponding to each expert module in the hybrid expert system, obtaining a target loss value of the pre-trained segmentation model; and according to the target loss value, performing parameter efficient fine tuning on the to-be-trained model parameter iteration to obtain an image segmentation model. According to the method, the robustness is improved, the inter-task interference is reduced, and the task processing performance is improved.

The invention discloses an internet of things-oriented federated learning anti-poisoning attack method. The method comprises the following steps of S1, initializing an internet of things federated learning system; s2, performing mask processing on the privacy data of the Internet of Things participants; s3, the cluster server collects mask data provided by all the Internet of Things participants and aggregates the mask data; and S4, identifying malicious poisoning participants of the Internet of Things through robust clustering. According to the method, an advanced machine learning algorithm and a privacy protection technology are introduced, a more effective anti-poisoning protection measure is provided for the Internet of Things system, the security and robustness of the Internet of Things system are remarkably improved through successful application of the method, and an important guarantee is provided for coping with potential hostile attacks and data tampering.

The invention provides a display panel and a display device, and relates to the technical field of display, pixel driving lines and data lines are electrically connected with pixel driving circuits respectively and are used for transmitting control signals and data signals to the pixel driving circuits respectively; the shift register circuit is used for transmitting control signals to the pixel driving lines, and the gating circuit is used for transmitting data signals to the data lines. The shifting register circuit comprises a plurality of cascaded shifting registers, namely a plurality of cascaded first shifting registers and a second shifting register cascaded with the first shifting registers, and the first shifting registers are located in the area where the pixel driving circuit array is located. The second shifting register is located on the side, facing the edge of the display panel, of the pixel driving circuit array, and the gating circuit is located between the pixel driving circuit array and the second shifting register. Therefore, the signal interference between the shift register circuit and the data line can be reduced, and the display accuracy of a display product can be improved.

According to the information superposition method of the intelligent perception information in the virtual space provided by the embodiment of the invention, a data layering mechanism based on an importance weight is established by evaluating the information integrity and association degree of multi-source data such as images, temperatures and sounds. A hierarchical display buffer area is adopted to realize hierarchical management of information, and an interlayer visual effect is optimized in combination with marginal definition evaluation and a fuzzy processing technology. Intelligent superposition of multi-layer data is realized through contrast enhancement and transparency control, and a display refreshing strategy is dynamically adjusted based on data timeliness. According to the method, the problems of disordered display and visual interference when a traditional superposition scheme processes multi-dimensional perception information are effectively solved, and the information display quality in the virtual space is improved.

The invention discloses a vernier sensitization vacuum pressure sensor based on optical fiber end face interference, and relates to the technical field of film sensors. The problem of low measurement precision caused by electromagnetic interference of a traditional capacitive film pressure sensor is solved. An interference cavity formed between the lower end face of the center optical fiber of the separated vernier assembly and the pressure sensing diaphragm serves as a sensing cavity for pressure detection, the sensing cavity (an optical fiber Fabry-Perot structure) formed by the pressure sensing diaphragm and the center optical fiber is adopted to replace a capacitor structure, optical waves are used for measurement, electric signals are not transmitted in the optical fiber, and the measurement precision is high. Therefore, the cable has excellent anti-electromagnetic interference and long-distance transmission capabilities. The pressure sensor is mainly used for pressure measurement.

The invention discloses an auxiliary switch driving device for an operating mechanism and a high-voltage circuit breaker. The auxiliary switch driving device comprises a bearing assembly; the transmission assembly is arranged on the bearing assembly, one end of the transmission assembly is externally connected with power output equipment, and the other end of the transmission assembly is movably connected with a guide assembly located at the bottom of the bearing assembly; the supporting assembly is mounted at the end part of the guide assembly and is used for connecting an auxiliary switch; under the driving of the power output equipment, the transmission assembly drives the guide assembly to move and pushes the supporting assembly to enable the auxiliary switch to rotate at the same time, so that signals of the auxiliary switch are changed. The switching angle of the auxiliary switch is accurately calculated according to the requirement for switching positions through position signals, the supporting assembly can push the rotating shaft of the auxiliary switch to rotate by different angles through cooperation of the guiding assembly and the supporting assembly in the auxiliary switch driving device, and therefore the requirement for sending different position signals can be met; accurate transmission of position signals can be achieved, and misoperation of other devices is avoided.

The invention provides a magnetic field observation method and system suitable for carrying out high-density deployment, and relates to the technical field of data processing, and the method comprises the steps: obtaining observation planning data, determining the number, interval and position distribution of observation nodes, setting a plurality of observation nodes to designated positions in a target region, magnetic field data in a target area is collected through observation nodes, preliminary screening is performed on the collected data according to background noise generated by equipment characteristics, secondary screening is performed according to spatial distribution characteristics among the observation nodes, and the observation data of different observation nodes are aggregated according to spatial position association rules. Performing cross validation on data consistency among observation nodes of the target area, performing optimization through a precision improvement algorithm to obtain a magnetic field distribution model, identifying a magnetic field abnormal area, performing multi-level detailed analysis on abnormal area data, and generating a magnetic field distribution result and abnormal characteristic data of the target area; the magnetic field observation precision is improved.

The invention discloses an adaptive filtering response method and system of a VHF frequency band, relates to the field of VHF frequency band signal processing, effectively solves the problems of signal interference and multipath effect in VHF frequency band communication through the adaptive filtering response method, and combines a delay detection algorithm and an adaptive filtering algorithm through time domain and frequency domain analysis, so as to realize the adaptive filtering response of the VHF frequency band. Accurate separation of the reflection path signal and the main path signal is realized. Furthermore, interference of reflection path signals is eliminated through a phase offset mechanism, and the transmission quality of the signals is remarkably improved.

The invention discloses a salient target detection method based on boundary guidance of depth map generation and RGB image fusion. The salient target detection method is specifically implemented according to the following steps: step 1, constructing a data set and an encoder; 2, constructing a depth map generation and RGB fusion module based on an attention mechanism; step 3, constructing a boundary feature guidance module based on a self-supervision mode; and step 4, constructing a double-branch feature fusion module based on progressive fusion. According to the method, a multi-modal fusion strategy and self-supervised edge feature guidance are adopted to perform feature enhancement, in order to effectively generate a depth image and remove noise, a depth image generation technology based on Depth Anything is adopted, a self-supervised edge feature module is designed to extract edge feature information, and the edge feature information is extracted by using the self-supervised edge feature module. Noise and artifacts in the generated depth image are effectively eliminated through the process.

The utility model relates to the technical field of drinking water supplies, and discloses an elastic cover type double-drinking vacuum cup which comprises a cup body, a cup cover assembly detachably covering the upper end of the cup body through threads, a first straw assembly and a second straw assembly, the first straw assembly and the second straw assembly are installed on the cup cover assembly, and the cup cover assembly comprises a base, a direct drinking turning cover and a straw turning cover. A direct drinking opening and a straw inserting opening which are communicated with the interior of the cup body are formed in the base, a first buckle is arranged on the direct drinking turning cover, a sliding plate is arranged in the base, a second buckle is arranged on the sliding plate, a first switch is installed on the base, a lock catch is arranged on the straw turning cover, a second switch is arranged on the direct drinking turning cover, and a spring bolt is arranged on the second switch; according to the utility model, a user can directly drink water through the direct drinking port or drink water through the straw under the condition that the cup cover is not taken down according to water drinking habits or requirements, the operation is convenient, the interference of the straw on direct drinking water drinking actions can be effectively avoided, the turning cover can be conveniently opened for drinking water by single-hand operation, and a switch key can be effectively prevented from being touched by mistake.

The invention discloses a device and a method for automatically measuring individual egg laying performance of family small-group caged geese, and the device comprises an egg laying detection device, a code spraying area device, a weighing area device, a combined goose cage, an egg detection module matched with the combined goose cage, a code spraying module, an information storage module, an information analysis module and a corresponding detection algorithm. Egg laying detection, egg laying performance detection, egg laying collection and other related work are carried out through a region division algorithm, a target persistence counting algorithm, an egg goose matching algorithm and an event triggering algorithm, the problems that resource space is wasted, independent cage culture facilities are high in cost and management cost are effectively solved, and the automation degree is greatly improved.

The invention relates to the technical field of current measurement, in particular to a multi-range current measurement circuit. The multi-level current measuring circuit comprises multi-level current measuring branches, the multi-level current measuring branches work in parallel, the first-level current measuring branch is connected to a TP point, current to be measured flows through the TP point and flows to the multi-level current measuring branches from the TP point, and the current to be measured is decomposed into parallel current of the multi-level current measuring branches to be measured respectively. The first-stage current measurement branch is continuously in a starting state and bears measurement of the minimum current gear, and the measurement voltage of the first-stage current measurement branch serves as a control signal to control starting or stopping of shunting work of all the rear-stage current measurement branches; the parallel connection of each stage of current measurement branch is smoothly connected from small to large from a zero current state, and the parallel quit of each stage of current measurement branch is smoothly quit from large to small to the zero current state. According to the invention, the problems of switch shift current abrupt change and sampling resistor voltage drop in the current measurement technology are solved.

The invention relates to the technical field of underground pipe network damage diagnosis, in particular to an underground pipe network damage diagnosis and analysis system based on an SAR satellite technology. The method comprises the following steps: firstly, collecting an SAR image of a target area of an urban underground pipe network, processing imaging data by adopting differential interference, calculating earth surface deformation and generating two-dimensional earth surface deformation data; then performing three-dimensional scanning on the deformation area by adopting LiDAR measurement to generate three-dimensional terrain point cloud data; performing spatial fusion analysis on the two-dimensional surface deformation data and the three-dimensional topographic point cloud data to obtain three-dimensional surface deformation data of a deformation area, and obtaining damage diagnosis information of the underground pipe network in combination with basic data of the underground pipe network; by combining the sensing data of the deformation area, the accuracy and efficiency of underground pipe network damage diagnosis are improved. The deformation rate and accumulated deformation are calculated through the time sequence InSAR technology, prediction and early warning of potential damage are achieved, and the method is suitable for large-range long-term monitoring of the urban underground pipe network.

The invention discloses a metamorphic rock surface porosity analysis and evaluation method, device, equipment and medium, and relates to the technical field of petroleum logging reservoir evaluation, and the method comprises the steps: preprocessing a rock debris sample, scanning the preprocessed rock debris sample, and obtaining a rock debris sample image; performing identification detection on mineral and background color edges in the rock debris sample image and rock debris gap image segmentation to obtain rock debris particles, and determining the total area of the particles; performing threshold truncation on the rock debris particles by adopting a threshold segmentation method, calculating pore areas in the rock debris particles, identifying cracks in the rock debris particles by adopting a maximum likelihood method, calculating crack areas in the rock debris particles, and calculating pore and crack areas by utilizing the pore areas and the crack areas; and calculating the surface porosity based on the total particle area and the pore and crack area, and analyzing and evaluating the imaging logging crack interpretation result and the surface porosity to obtain an analysis and evaluation result. The metamorphic rock surface porosity analysis and evaluation accuracy and efficiency can be improved, and metamorphic rock surface porosity analysis and evaluation complexity can be reduced.

The invention relates to a trace methane detection device and a detection method thereof, the trace methane detection device comprises: a sampling detection gas circuit formed by sequentially connecting a gas inlet, a three-way solenoid valve I, a quantitative tube, a sampling pump, a three-way solenoid valve II, a trace methane sensor and a gas outlet; the gas phase separation gas circuit comprises a constant flow pump and a chromatographic separation pipe which are connected between other ports of the three-way electromagnetic valve I and the three-way electromagnetic valve II, and the three-way electromagnetic valve I, the quantitative pipe, the three-way electromagnetic valve II, the constant flow pump and the chromatographic separation pipe form the gas phase separation gas circuit; and the signal processing and analyzing module is in signal connection with the trace methane sensor and is used for processing a detection signal of the trace methane sensor to obtain the methane concentration. According to the trace methane detection device and the detection method thereof, the to-be-detected gas sample is separated through the chromatographic separation tube, and the high-sensitivity gas sensor is used for detecting the gas concentration, so that the strong anti-interference performance brought by gas separation in a gas chromatographic analysis method is reserved, and the high-sensitivity detection capability of the gas sensor is combined.

The invention discloses a multi-terminal communication system based on Internet of Things, which relates to the technical field of communication, and comprises a terminal access module, a data management module, a network management module, a communication protocol stack and a user management module, the data management module, the network management module and the user management module are connected with the communication protocol stack through software interfaces; the network management module is preferentially connected with a wireless network in a close range through a locally deployed base station, the network management module issues a data instruction to the first terminal, the second terminal and the third terminal through the wireless network, and the user management module authorizes the terminal access module to passively access terminal equipment information through an identity authentication mechanism. A special data source is limited through the data management module, data layering isolation circulation is achieved, the problem that data are prone to pollution and interference is solved, and product quality can be more accurately controlled.

The invention relates to the technical field of refrigeration, and provides a door body assembly of embedded refrigeration equipment and the embedded refrigeration equipment. The door body assembly of the embedded refrigeration equipment comprises a box door which is rotatably connected to a refrigeration box body of the refrigeration equipment, and the refrigeration box body is used for being embedded into a containing space formed by a mounting body; the door plate is connected to the box door through a sliding mechanism so as to move relative to the width direction of the box door; the box door has a critical door opening angle which is smaller than the maximum door opening angle of the box door; in the process that the box door rotates to the critical door opening angle from the closed position, the sliding mechanism drives the door plate to move relative to the box door, the moving distance is delta s, and the moving distance delta s is not smaller than the critical safety distance corresponding to the critical door opening angle; the critical safety distance is the minimum sliding distance required for the door plate not to interfere with the outside in the process of rotating the box door from the closing position to the maximum opening angle; and when the box door rotates from the critical door opening angle to the maximum door opening angle, the door plate is static relative to the box door.

The invention discloses a waveform design method and system for tracking a sea surface maneuvering target by an unmanned ship-mounted radar, relates to the technical field of radar communication, and aims to solve the technical problem of inaccurate maneuvering target tracking in a sea surface clutter environment. The method is technically characterized by comprising the following steps: predicting a target state by using a marginalized particle filter algorithm, and obtaining a predicted measurement value; generating a hypothesis tree according to the observation data; performing target state estimation on each assumed branch by using a marginalized particle filter algorithm; a multi-hypothesis tracking algorithm is used to calculate an association probability and update a hypothesis weight, hypothesis pruning and fusion are carried out, and final target state estimation is obtained; a plurality of waveform selection criteria are used as a model, and an interactive multi-criterion selection method is utilized to determine an optimal criterion with the highest effective probability and an optimal transmitted waveform parameter. According to the method, false alarms caused by sea clutters can be effectively handled, the performance of the unmanned ship-mounted radar for processing complex tracking scenes can be improved, and a more accurate and robust target tracking result can be obtained.

The invention discloses a muscle force estimation method based on surface electromyogram signals and adjustable input characteristics. The method comprises the steps that the surface electromyogram signals and force signals in a muscle contraction state are synchronously collected; the EMD-DWT method is adopted to preprocess the surface electromyogram signals; segmenting the surface electromyogram signals and the force signals by adopting a sliding window, extracting features of the surface electromyogram signals, extracting an average value of the force signals, and making sample labels; a Pearson's correlation coefficient method is adopted to calculate correlation coefficients of the extracted features and the force signals; sequentially adding features with high correlation coefficients to form an input vector of the model, constructing a muscle force estimation regression model for training and testing, and adjusting the number of input features according to errors of a training set and a testing set. According to the method, effective features can be accurately and rapidly extracted, the number of the features can be determined, and it is guaranteed that high muscle force estimation precision is achieved under the condition that the input dimension is low.

The invention discloses a tunnel fire smoke diffusion detection method based on deep learning and image segmentation, and belongs to the technical field of fire smoke diffusion detection. The method comprises the following steps: S1, data acquisition and processing: acquiring a monitoring video in a tunnel environment by using an image acquisition module, obtaining diversified smoke image data when a fire occurs in a tunnel, and storing the obtained smoke image data in a data storage module; s2, smoke image segmentation and enhancement: utilizing an image processing module to segment and enhance the smoke image data acquired in the S1; s3, smoke recognition: after image segmentation and enhancement are completed, smoke target detection is performed on the processed image by using a YOLO v5 deep learning model based on a smoke detection module; s4, result analysis and visualization: utilizing a result analysis and visualization module to display the smoke recognition result obtained in the S3 in real time; and S5, data storage: storing a result displayed in the S4 in real time in a data storage module. Compared with the prior art, fire smoke diffusion can be accurately monitored in real time, timely control and early warning are achieved, and the influence of smoke diffusion on the tunnel environment and the external environment is reduced.