92 results about "Industrial area" patented technology

The invention discloses an LNG (liquefied natural gas) station site selection method and device based on multi-scene dynamic coupling, a computer and a storage medium, belongs to the technical field of LNG infrastructure planning and intelligent transportation, and solves the technical problem that LNG station site selection is difficult to accurately predict under multi-scene dynamic change. The method comprises the following steps: collecting multi-scene site selection data of the LNG filling station; data processing is carried out, and a space-time fusion big data medium table is constructed; constructing a long short-term memory network LSTM and reinforcement learning RL coupling model, and obtaining a real-time demand prediction result; a multi-constraint site selection optimization model is constructed, and an LNG gas station candidate site set is obtained; performing optimization through scene classification and feature modeling and defining a multi-scene layout criterion to obtain an LNG gas station candidate set adaptive to multiple scenes; according to the method, the site selection planning of the LNG filling station is realized by fusing the requirements and constraints of multiple scenes such as high speed, suburban, city and industrial districts, and the method is suitable for the field of administrative planning of the government and site selection planning of gas supply enterprises on the LNG filling station.

The invention discloses an underwater acoustic-magnetic multi-modal fusion processing method, which comprises the following steps: carrying out preprocessing and time-space alignment on collected sonar and magnetic data, and extracting a morphological feature vector and a magnetic feature vector of a pipeline; based on a pipeline route trend, calculating an optimal matching path of a sonar contour and a magnetic force abnormal zone through dynamic time warping, establishing acoustic-magnetic mapping, and fusing features to generate a joint vector; finally, the type and state of the pipeline are judged according to the combined characteristics, and the problem that in a near-shore port and an industrial area water area, due to the interference of construction waste and the influence of a pipeline coating layer, a single sonar is difficult to accurately detect the pollution discharge pipeline and the cable is solved. According to the method, the complementarity of acoustic and magnetic characteristics is utilized, the accuracy of pipeline detection in a complex scene is improved, and reliable data support is provided for operation and maintenance of near-shore water area pipelines.

The invention discloses an industrial park comprehensive energy system low-carbon planning method considering a production process, and the method comprises the following steps: 1, obtaining the production line condition of an industrial park, and constructing a production line model; 2, determining to-be-planned equipment and parameters, and constructing a lower-layer planning operation model considering short-term uncertainty; 3, determining medium and long term uncertainty parameters, and constructing a medium and long term uncertainty set; step 4, determining a multi-objective optimization model; 5, searching a Pareto leading edge by using multi-target reinforcement learning based on a decomposition technology; and 6, selecting a proper Pareto frontier solution, and substituting the Pareto frontier solution into the lower-layer planning operation model to obtain a corresponding planning result. The invention aims to realize low-carbon transformation of an integrated energy system (IRIES) in an industrial area so as to cope with carbon reduction, emission reduction and challenges in a carbon dense area.

The invention belongs to the technical field of industrial area green land planning, and discloses a GIS-based industrial green land carbon evaluation decision system and method, which perform integrated scheme decision by acquiring multi-source dynamic data, performing space unit division, predicting dynamic carbon emission, identifying hot spot areas and time, and comprehensively considering factors such as vegetation characteristics and budget constraints. According to the method, dynamic changes of industrial development in an industrial area, staged green land construction budget and time sequence characteristics of vegetation growth can be comprehensively considered, and a green land planning scheme for realizing carbon sink benefit and cost input optimization matching in a planning period is generated.

The invention provides a high-performance concrete anticorrosive paint and a preparation method of a coating, and relates to the technical field of building materials and corrosion prevention. The coating is composed of a component A and a component B, the component A comprises epoxy resin, a composite solvent, an organic solvent, a dispersant, fumed silica and a leveling agent, and the component B comprises an epoxy hardener, a conductive polymer dispersion liquid and an organic solvent. The composite solvent is formed by compounding one or more of orthotitanate, phosphate and orthosilicate with an ester, ketone, alcohol, aromatic hydrocarbon, aliphatic hydrocarbon or ether organic solvent. The preparation method of the anticorrosive coating comprises the following steps: preparing the component A and the component B, mixing to form a coating, applying the coating to the surface of concrete, and curing. The coating is compact in structure and strong in adhesive force, can obviously improve the durability and corrosion resistance of concrete in extreme environments such as high salinity and high acid, and is particularly suitable for infrastructure protection in coastal and heavy corrosion industrial areas.

The invention relates to the field of industrial energy consumption data monitoring, in particular to a hydroelectric energy consumption data monitoring method and system based on edge computing, and the method comprises the steps: preprocessing the historical data of water meters and electricity meters in an industrial region, carrying out the clustering analysis to form a water meter cluster and an electricity meter cluster, and deploying an isolated forest model on an edge node corresponding to each cluster. And training a model by using a clustering result, and updating a model weight according to new data so as to adapt to data change. And inputting real-time data into the updated model, and calculating an abnormal score to evaluate whether the energy consumption data is abnormal or not, thereby realizing accurate hydroelectric energy consumption monitoring. According to the method, the adaptability and accuracy of hydroelectric energy consumption anomaly detection are remarkably improved by training and deploying the isolated forest models on the edge nodes for different equipment clusters and dynamically updating the model weight in combination with the similarity of the new data set.

The invention belongs to the technical field of intelligent sensing monitoring and micro-nano energy, and discloses an intelligent acid rain sensing monitoring method and system based on a total-current nano generator. The method comprises the following steps: preparing a total-current nano-generator as a sensing core element, and generating a characteristic electric signal corresponding to a pH value through the action with acid rain; constructing an intelligent algorithm processing module based on a ResNet 18-1D convolutional neural network (CNN), and performing multi-dimensional feature extraction and pH value intelligent classification on the collected electric signals; and displaying the electric signal waveform characteristics and the pH recognition result in real time through a visual interaction interface. According to the invention, the full-current nano generator is combined with the deep learning technology, the technical bottlenecks that a traditional acid rain detection method depends on a large professional instrument, needs external power supply support and is complex in operation process are broken through, and in-situ, rapid and intelligent monitoring of the acid rain pH value is realized. And an efficient and reliable solution is provided for real-time monitoring of acid rain in industrial areas and outdoor environments.

The invention relates to the technical field of heat supply system remote monitoring, and discloses an intelligent heat meter remote data acquisition method based on edge calculation. The method comprises the following four steps: constructing a user-device double-causal network model, realizing an anomaly detection and attribution mechanism based on causal reasoning, developing an interpretable anomaly report generation system and realizing a predictive maintenance suggestion system. By constructing the double-causal network reflecting the causal relationship between the user behavior and the system physical state, accurate attribution of abnormal data is realized, user behavior changes and equipment faults can be accurately distinguished, the diagnosis accuracy is improved, the false alarm rate is reduced, and the user experience is improved. The system is particularly suitable for remote monitoring and maintenance management of heat supply systems of large residential districts, commercial buildings and industrial districts and remote or difficult-to-reach heat supply stations.

The invention relates to the technical field of environment monitoring, and discloses an environment-friendly environment monitoring system, which collects static and dynamic data through a fixed monitoring station and a mobile device, realizes frequency adaptive calibration by adopting a linear interpolation or spline interpolation algorithm, and constructs a fusion data matrix of time-space alignment; matching an optimal environment evaluation model based on an optimization algorithm (such as an eagle algorithm), and dynamically selecting a prediction algorithm in combination with pollution characteristics; a differential response strategy is triggered through a multi-stage early warning mechanism (yellow / orange / red), a pollution source positioning map and an emergency scheme are synchronously generated, and'monitoring-analysis-disposal 'closed-loop management is realized. The method can be applied to the scenes of urban atmosphere, river water quality, industrial area multi-parameter pollution and the like, the monitoring precision (the omission ratio is reduced by more than or equal to 25%), the response speed (the early warning push is less than or equal to 8 seconds) and the resource utilization efficiency (the energy consumption is reduced by 20-35%) are effectively improved, and a high-reliability solution is provided for intelligent environmental protection.

The invention provides a carbon neutralization zoning simulation method, system and device based on a smart city, and relates to the technical field of carbon neutralization simulation, and the method mainly comprises the steps: carrying out the planning zoning of a map of a tested city; calculating the carbon emission of each partition and carrying out visualization processing to obtain geographic space data; calculating the carbon sink amount of each partition; collecting output value basic data of each industry of the detected partition and marking the output value basic data in geographic space data; carbon emission basic data, carbon sink basic data and output value basic data which are regularly acquired by a smart city system are stored in a smart city database based on a time sequence; predicting the future carbon emission, carbon sink and output value of the measured subarea; constructing a time sequence dynamic optimization model, and solving an industrial area layout scheme through a parallelization genetic algorithm; and generating suggestion information. According to the scheme, a quantifiable and adjustable carbon management tool is provided for overall planning of urban territorial space, and the scheme is particularly suitable for low-carbon planning and treatment of high-density coastal cities.

The present invention relates to the production of a sound-insulating textile surface comprising two fabric layers laminated to each other with the coated surfaces remaining on the inner surface, while the fabric surfaces remain on the outer surface. Providing benefits such as preventing noise pollution, improving sound acoustics and increasing privacy in many sectors from construction sites to production facilities, from homes to offices, from automobiles to industrial areas. The versatility of this fabric offers significant advantages, both aesthetically and functionally.

The present invention relates to the production of a sound-insulating textile surface comprising two fabric layers laminated to each other with the coated surfaces remaining on the inner surface, while the fabric surfaces remain on the outer surface. Providing benefits such as preventing noise pollution, improving sound acoustics and increasing privacy in many sectors from construction sites to production facilities, from homes to offices, from automobiles to industrial areas. The versatility of this fabric offers significant advantages, both aesthetically and functionally.

The application belongs to the technical field of industrial green land planning, and discloses a GIS-based industrial green land carbon assessment decision system and method. Through acquisition of multi-source dynamic data, spatial unit division, prediction of dynamic carbon emission, identification of hot spot areas and time, and integrated scheme decision considering factors such as vegetation characteristics and budget constraints, the system can comprehensively consider the dynamic changes of industrial development, the budget of green land construction in different stages, and the time sequence characteristics of vegetation growth, and generate a green land planning scheme that optimally matches carbon sink benefits and cost input within a planning period.

This invention discloses a YOLO-based method for detecting surface defects on printed circuit boards, belonging to the fields of computer vision and intelligent manufacturing technology. The method includes the following steps: deploying an industrial area scan camera at the inspection station of an automated production line; when a PCB enters the inspection station, the camera is triggered by a sensor to acquire and store images; the acquired image data is processed using data cleaning, data augmentation, and target annotation methods; the processed PCB defect dataset undergoes detailed statistical analysis to optimize the model training strategy; based on the data analysis results, optimization is performed using the YOLOv5 target detection framework to establish a surface defect detection model suitable for PCB production scenarios. This invention can effectively improve the automation level and detection accuracy of defect detection, is suitable for modern large-scale batch production of PCBs, and has good engineering application prospects and industrial promotion value.

This invention discloses a production method for preparing artificial land using various types of stones, a complete technology for preparing artificial soil through on-site crushing and application to the comprehensive transformation of national land. This invention employs on-site mobile processing, avoiding transportation costs. A single unit can produce soil for 1500 mu (approximately 100 hectares) annually, with a standard farmland cost of only 2658 yuan per mu, and the cost of remediating polluted farmland not exceeding 10,000 yuan per mu. The produced soil has a thickness of 33.3 cm, does not compact, and has extremely high water retention; even after 10 days at high temperatures, the moisture content of the lower layer still reaches 70%. Heavy metal content in the soil and agricultural products is far below national standards, mercury was not detected, and it is safe to grow all grains and vegetables. This invention can be applied on a large scale to the remediation of polluted farmland and the enhancement of carbon sequestration in industrial areas. It can rapidly increase soil carbon sequestration, lower temperatures, and transform ineffective rocky land into high-yield farmland, completely solving global problems such as the extremely slow formation, rapid loss, non-renewability, arable land shortage, and global warming of natural soils. One-time transformation benefits millennia, possessing extremely high economic, ecological, and social value.

The invention discloses an industrial area soil detection system based on space-time big data, and relates to the technical field of soil quality detection. The accuracy of the soil time data and the soil space data is effectively improved; the method comprises the following steps: acquiring soil time data and soil space image data of an industrial area through a soil data acquisition module, and performing space-time correlation to generate an industrial area soil data space-time model; performing time correlation on the soil time data and the soil space image data according to the industrial area soil data space-time model to generate an industrial area soil data detection model; detecting the soil quality of the industrial area according to the industrial area soil data detection model to obtain time soil quality; a spatial data updating module is used for updating the soil spatial image data to obtain optimal soil spatial image data; and visualizing the optimal soil space image data to obtain soil visualized data.

The utility model discloses a skid-mounted pressurizing hydrogenation device capable of improving hydrogenation rate, which comprises a hydrogen storage module, a pressurizing module and a hydrogenation module which are all fixed on a skid-mounted base of a steel frame structure. The hydrogen storage module adopts a high-pressure storage tank and a low-pressure buffer tank which are connected in series, the high-pressure storage tank is connected with a quick connector through a tube bundle vehicle interface, a hydraulic control regulating valve in the low-pressure buffer tank is driven by a first hydraulic cylinder, and a tank body is provided with a pressure gauge for monitoring pressure; the pressurization module comprises a hydraulic drive booster pump and a gas-liquid separator, the hydraulic drive booster pump is driven by a second hydraulic cylinder, the gas-liquid separator separates liquid through a perforated plate, and a liquid outlet is connected with a recovery pipeline; the hydrogenation module is connected with high-pressure and low-pressure filling channels through a hydraulic control switching valve, and hydrogenation connectors are arranged at the tail ends of the channels. The device realizes rapid pressure increase through hydraulic drive pressurization, the switching valve supports rapid switching of high pressure and low pressure, the positioning groove fixing module ensures efficient deployment, and the device is suitable for scenes such as concentrated hydrogen supply in green parks or temporary hydrogenation in industrial areas.

The invention relates to the field of production city planning and design, and discloses an AI large model-based production city planning and design application text-graphics technology platform, which comprises a basic data processing module, which is used for carrying out collection, cleaning preprocessing and storage management on production city planning data; the AI large model building module is used for training and optimizing an AI model and managing a model knowledge base; the production city planning design application module is used for generating, evaluating and optimizing a production city planning scheme and providing multi-scheme comparison and selection; and a text-to-map technology support module. Through a production-city fusion development evaluation module, industry chain planning and city function layout are deeply fused, a space cooperation relationship between an industrial area and a life circle is accurately analyzed, job-housing balance and public service resource allocation are dynamically optimized, a cooperation effect between industrial vitality and city livability is significantly improved, and a good social benefit is achieved. And transformation and upgrading of city production planning from physical space superposition to function organic fusion are promoted, and systematic support is provided for high-quality development of cities.

The application discloses an industrial area atmospheric environment monitoring management system and method, relates to the technical field of industrial internet of things environment monitoring, and comprises the following steps: triggering polarization imaging to scan a target area based on the space-time information of an abnormal event signal, acquiring polarization characteristic data of a pollution plume, and generating a spatial distribution characteristic parameter; inputting a sound pressure abnormality index and the spatial distribution characteristic parameter into an industrial equipment leakage causal model, calculating a pollution source confidence, and acquiring an industrial equipment traceability result and a leakage level when the pollution source confidence reaches a process safety dynamic threshold; acquiring hierarchical control instructions according to the industrial equipment traceability result and the leakage level, calculating a measured attenuation rate of an industrial pollutant, and verifying a dynamic response effect; and the application breaks through the technical limitation of traditional pollution source positioning depending on static empirical formulas by cross-modal fusion modeling of acoustic abnormal information and pollutant spatial distribution characteristics.

The invention discloses a pollution particulate matter multi-stage filtering device for air treatment, and relates to the technical field of air treatment. Comprising a bottom frame and an upper frame, a top bin is formed at the upper frame, an opening is formed in one side of the top bin, a coarse filtering mechanism is arranged between the inner walls of the two sides of the top bin, a first fan is arranged on one side of the upper frame and exhausts air filtered by the coarse filtering mechanism again, a bottom bin is arranged below the upper frame, and a second fan and a bottom filtering device are arranged at the bottom bin. Through the multi-stage collaborative design of the coarse filtering mechanism and the bottom filtering device, pollution particles with different particle sizes can be efficiently intercepted, the contact area is increased through the hollow cylindrical rotary filter screen, and the purification efficiency of mixed pollutants such as PM2.5 and PM10 is remarkably improved through fine filtering of the bottom filter cylinder and the end filter screen; the problem that the single-stage filtering capacity of a small single machine is insufficient is solved, and the pollution treatment requirements of industrial areas, construction sites and other local scenes are met.

The present invention provides an automatic calibration method and system for industrial area array cameras in the field of industrial area array camera calibration technology. The method includes: step S10, controlling the industrial area array camera to move to an area above a calibration feature; step S20, photographing the calibration feature to obtain a calibration photo, performing distortion correction on the calibration photo, using the calibration feature as a calibration mark point, and recording the machine coordinates of the photographing position at that time; step S30, dividing the pixel field of view into blocks to construct a point set of equally divided mark points; step S40, selecting the equally divided mark points and taking a difference between the calibration mark points, outputting a control parameter for the movement of the industrial area array camera based on the difference, completing an adaptive control process of a single-point spiral approximation, and recording the pixel coordinates and machine coordinates of the point; and step S50, executing an N-point calibration algorithm based on the pixel coordinates and machine coordinates to complete the calibration. The advantages of the present invention are: greatly improving the efficiency and safety of industrial area array camera calibration and greatly reducing the labor cost of industrial area array camera calibration.

The present application relates to the field of industrial energy consumption data monitoring, and more particularly to a water and electricity energy consumption data monitoring method and system based on edge computing, which comprises: preprocessing the historical data of water meters and electricity meters in the industrial area, performing cluster analysis to form water meter clusters and electricity meter clusters, and deploying an isolation forest model on each corresponding edge node of the clusters. The model is trained using the clustering results, and the model weights are updated according to new data to adapt to data changes. Real-time data is input into the updated model, and an anomaly score is calculated to evaluate whether the energy consumption data is abnormal, thereby achieving accurate water and electricity energy consumption monitoring. By training and deploying an isolation forest model on the edge node for different device clusters, and dynamically updating the model weights combined with the similarity of the new data set, the adaptability and accuracy of water and electricity energy consumption anomaly detection are significantly improved.

The present application relates to the technical field of cathodic protection, in particular to a complex buried pipe network cathodic protection optimization method under current interference, comprising the following steps: collecting the data of soil resistivity, pipeline material and environmental humidity from differentiated industrial areas by adopting field sampling method, obtaining environmental parameter characteristics by analyzing the variability and correlation of the data.In the present application, the model can be accurately adjusted to various complex interference conditions by simulating the scene test of the environment, optimizing the distribution of current and potential, not only improving the stability of the cathodic protection system in the variable interference environment, but also realizing the fine adjustment of current and potential parameters through the simulation and multiple simulation tests of electromagnetic field data, significantly improving the corrosion prevention effect of buried pipe network and the overall efficiency of the system, ensuring the long-term safety and stability of buried pipe network in complex current interference environment through real-time monitoring and adjustment, significantly prolonging the service life of the facility.

The invention relates to a cross-modal industrial data efficient cleaning and semantic unification method and device, computer equipment, a storage medium and a computer program product. The method comprises the steps of collecting multi-modal original data of a target industrial area through multiple communication protocols, and performing format analysis on the multi-modal original data to obtain initial data; according to the data type of the initial data, cleaning the initial data, and respectively converting various types of cleaned data into structured feature vectors to obtain target feature vectors; on the basis of a cross-modal attention mechanism, performing feature fusion on each target feature vector to obtain a cross-modal fusion feature; mapping the cross-modal fusion feature to a unified semantic space to obtain target data; and outputting the target data by using a standardized data interface. By adopting the method, the complexity and the isomerism of the multi-modal data in an industrial scene can be effectively handled, and the efficiency and the precision of data cleaning are remarkably improved.

The invention discloses a tracing identification method for industrial wastewater in a municipal pipe network based on a three-dimensional fluorescence spectrum angle algorithm. The tracing identification method is characterized by comprising the following steps: collecting industrial area municipal pipe network confluence well water outside a factory, industrial wastewater raw water in the factory, treated industrial wastewater and a water sample of an enterprise inspection well; mixing the municipal pipe network confluence well water with the industrial wastewater raw water, the treated industrial wastewater and enterprise inspection well water in the factory according to a series of different proportions to obtain three-dimensional fluorescence spectrum data of water samples with different mixing proportions; reading the three-dimensional fluorescence spectrum data obtained after correction in the step 1 in a python environment, flattening the three-dimensional fluorescence spectrum data into a one-dimensional vector, and performing normalization processing on the one-dimensional vector to obtain one-dimensional vectors of each group of mixed water samples; the spectral difference and similarity between samples are compared and analyzed through a spectral angle algorithm, the characteristics of the industrial wastewater are quantitatively evaluated, qualitative recognition of the industrial wastewater in the municipal pipe network is achieved, and the method has the advantages of being efficient, accurate and convenient.

The present invention relates to the production of a sound-insulating textile surface comprising two fabric layers laminated to each other with the coated surfaces remaining on the inner surface, while the fabric surfaces remain on the outer surface. Providing benefits such as preventing noise pollution, improving sound acoustics and increasing privacy in many sectors from construction sites to production facilities, from homes to offices, from automobiles to industrial areas. The versatility of this fabric offers significant advantages, both aesthetically and functionally.

The invention discloses a PCB industrial internet networking method based on 5G and a wireless sensor network and a related device. The method comprises the following steps: acquiring production requirements of a PCB industrial area and integrating the production requirements into 5G configuration data so as to carry out resource configuration on a 5G private network; configuring and initializing a wireless sensing layer according to production requirements; the method comprises the following steps: collecting and preprocessing data of a PCB industrial area through a plurality of sensor nodes; based on the LORA wireless technology, gathering the collected data to a gathering node, and filtering the gathered data by the gathering node to obtain filtered gathered data; the filtered and converged data and other data are transmitted to a cloud server through a 5G private network; and data fusion is carried out through the cloud server and an intelligent decision instruction is generated. According to the invention, through cooperative operation of the 5G private network and the wireless sensing layer, fusion and intelligent decision-making of production data are realized, and integrity and reliability of network coverage are improved, so that efficient and stable operation of PCB production is guaranteed.

The utility model discloses automatic yardage roll conveying equipment, which belongs to the technical field of yardage roll conveying and is characterized by comprising an intelligent transfer platform, the top of the intelligent transfer platform is movably connected with a yardage roll frame adjusting transfer mechanism, and the top of the intelligent transfer platform is movably connected with a yardage roll transfer anti-scattering mechanism. A roller support in traditional winding and unwinding equipment is independent and is changed into a movable support capable of being transferred through an intelligent transfer platform, guide rails of the intelligent transfer platform are arranged in a plurality of operation areas in an industrial area, the movable support can conduct positioning transfer on the positions of all the operation areas, and therefore the purpose that the intelligent transfer platform can be used for transfer is achieved. When rolling is needed, the movable support without the yardage roll on the storage roller can be transferred to a discharging area of the rolling device to be positioned and clamped, the movable support and the rolling device are integrated, after the yardage roll is stored, the storage roller bearing the yardage roll can be supported through the movable supporting plate, and the yardage roll is prevented from being scattered.

The application discloses a point gluing assembly method of a high-temperature silicon pressure sensor, belongs to super-precision operation in the micro field, is applied to high-precision assembly of a pressure chip and a fixed tube seat in the high-temperature silicon pressure sensor, and particularly relates to camera calibration of a double-microscopic visual system, feature recognition of a point gluing hole of the pressure chip and a metal pin of the fixed tube seat and a high-precision alignment assembly strategy. Different from manual or semi-automatic alignment assembly adopted in the industry, the application calibrates the mapping relationship between an industrial area array camera and a world coordinate system and the mapping relationship between double-camera coordinate systems, carries out coordinate conversion on feature information collected by the microscopic vision, and realizes alignment and assembly of the pressure chip and the fixed tube seat of the high-temperature silicon pressure sensor by using the obtained coordinate information. The method avoids the fact that manual assembly error is large, nanosilver paste used in point gluing assembly overflows, and glue stress after solidification influences pressure measurement precision.

This application discloses an industrial area inspection method, apparatus, electronic device, and storage medium, relating to the field of intelligent detection. The method includes: determining abnormal area identification results based on a pre-trained target detection model using visible light images, thermal imaging images, and acoustic imaging images of the inspection area; extracting corresponding abnormal defect parameters according to the type of abnormal defect, and generating natural language report text and annotation guidance information through a large model; performing consistency verification on the annotation guidance information until the verification passes; annotating the visible light image based on the verified annotation guidance information to obtain a visualized annotated image; determining the fault risk level and target risk suggestion corresponding to the abnormal area based on the abnormal defect parameters, and displaying the natural language report text, visualized annotated image, fault risk level, and target risk suggestion as the inspection result to the user. The above technical solution improves inspection efficiency and intelligence.