779results about How to "Effective positioning" patented technology

The invention discloses a method for analyzing a matching degree between a demand and an output result based on text semantics. The method comprises the following steps: step 1, labeling a data set; step 2, technical document preprocessing; 3, training and predicting a single-parameter model; 4, integrating prediction results of the multi-parameter model; the method has the beneficial effects thatthe method is simple; deep learning and the NLP technology are applied to the field of project association degree calculation of enterprise project management for the first time. Calculating an association matching degree between the two projects according to project requirements and result description; the associated project positioning difficulty is effectively reduced; meanwhile, the demand side can be helped to quickly and efficiently locate high-quality projects adapting to the demand of the demand side; time and resource investment for achievement screening and matching are greatly reduced, the association matching degree between projects is calculated by means of text data of existing project achievement technical documents and project declaration guidelines, and then large enterprises are assisted in screening high-quality projects with the high matching degree in the project bidding and tendering link.

The invention discloses a conflict detection processing method and system based on a BIM model, a medium and a product, and relates to the technical field of constructional engineering, and the method comprises the steps: obtaining a construction project design scheme; based on a preset model framework, determining a BIM model according to the construction project design scheme; predicting potential conflict points in the BIM model based on a preset conflict mode library; matching the potential conflict points with the building structure, the electromechanical pipeline and the equipment layout by using a space mapping algorithm, and determining possible conflict areas; on the basis of a natural language processing technology, operable solution suggestions are generated according to the possible conflict areas; after the operable solution suggestions are sent to the user, the solution suggestions determined by the user are received; and adjusting the BIM model based on the solution suggestion. By implementing the method, the accuracy and intelligence of conflict detection can be improved.

The invention discloses a surface water river-entering sewage draining exit pollution abnormity tracing method and device based on intelligent Internet of Things. The method comprises the following steps: constructing a database according to surface water pollution basic data; all pollution sources in the database are divided into different levels of pipeline logic relations according to the upstream and downstream communication relation of the land parcel area, the pipe network and the water system, and a pollution source-land parcel-pipe network-monitoring station intelligent Internet of Things grid is constructed; carrying out preprocessing and feature analysis on all data in the intelligent Internet of Things grid to construct a model database; a traceability model and a pollution contribution model are built based on the model database, the traceability model is used for calculating the pollution contribution rate of each pollution source, and a target discharge port or a target pollution discharge node is determined according to the pollution contribution rate; the pollution contribution model is used for generating and displaying a pollution contribution value of the target discharge port or the target pollution discharge point in response to an input instruction. The problem that a pollution source cannot be quickly and accurately determined in surface water environment management is solved.

The invention provides a zero sample image anomaly detection and positioning method based on a pre-training vision-language model, relates to the technical field of image anomaly detection and positioning, and aims to train a learnable adapter and a learnable text prompt by using a universal vision anomaly detection data set. A normal state text prompt and an abnormal state text prompt are constructed, and a normal state text representation and an abnormal state text representation are respectively obtained. In the aspect of image features, characterization of different levels of an image in a picture encoder is obtained, and image features of neighbor information of different scales are aggregated through window sizes of different scales and are adjusted by an adapter. And finally, calculating the similarity between the text-image features, and obtaining a probability score that the image is classified as abnormal by using a normalization mode. According to the invention, the general abnormal data set is utilized to train the learnable text prompt and the learnable adapter, so that the problem of how to carry out image anomaly detection when the training sample cannot be acquired is solved, the pre-training model can adapt to the target detection data set, and zero sample detection and positioning are effectively carried out.

The invention discloses an intelligent unmanned rescue boat, a rescue control method and rescue control equipment. The rescue boat comprises a boat body, a power system, a multi-sensor system, a communication system, a processor and a memory. The multi-sensor system comprises a visual sensor, a thermal imaging sensor, a sonar sensor, a positioning sensor and a meteorological sensor. The communication system is used for exchanging data with external equipment; the processor is connected with the multi-sensor system and the communication system; the memory is connected with the processor and stores a computer program; and the processor executes the program in the memory, controls the multi-sensor system to scan a surrounding water area, identifies and positions at least one drowning person, determines an obstacle avoidance demand, generates an optimal rescue path, and controls the power system to move the ship body according to the optimal path to implement rescue. According to the invention, rescue tasks can be efficiently and accurately executed under complex sea conditions, and the success rate and efficiency of sea rescue are improved.

The invention relates to the technical field of software application testing, in particular to an automatic intelligent testing system and method for software application. The method comprises the following steps: acquiring test environment parameters of software to be tested, calculating a dynamic waiting time reference value, and generating waiting mechanism configuration data; performing element positioning information collection and element positioning strategy generation on a user interface of the software application based on the waiting mechanism configuration data to obtain element positioning configuration data; performing conditional waiting strategy processing according to the element positioning configuration data and the waiting mechanism configuration data to generate conditional waiting mapping data; and performing visual AI auxiliary positioning processing according to the conditional waiting mapping data to generate visual positioning feature data. Through real-time monitoring of test environment parameters, the system automatically calculates and configures appropriate waiting time, so that the test process can flexibly adapt to various operation environments.

The invention relates to the technical field of data processing and robot positioning, in particular to a weighted fusion agricultural robot positioning method and system based on deviation filtering, and the method comprises the steps: obtaining the state data of a real-time dynamic differential positioning system and an inertial measurement unit, obtaining the state priori estimation at the current moment, inputting a kinetic model, and obtaining an observation value; then introducing a deviation mean value based on a difference value between an observation value and an actual measurement value, correcting the state priori estimation based on the deviation mean value to obtain state posteriori estimation, and introducing a smoothing factor to adaptively adjust a weight factor based on a difference value of the state posteriori estimation of the real-time dynamic differential positioning system and the inertial measurement unit to obtain the state priori estimation. And the weight factor at the current moment is obtained, and adaptive weighted fusion processing is carried out, so that high-precision positioning of the agricultural robot can be realized, and the robustness and the anti-interference capability of the system are improved.

The invention relates to the technical field of leakage traceability, in particular to a water transfer project leakage traceability identification method and system, and the method comprises the following steps: setting monitoring points in a water transfer project, collecting the temperature, pressure and flow velocity data of the key monitoring points, carrying out the time sequence analysis of parameters, analyzing the water flow dynamic state and environment change in real time, and generating state monitoring data. According to the method, the environment change near the leakage is analyzed by using the state monitoring data, the abnormal change is identified through simulation comparison analysis, the leakage point is predicted and positioned more accurately, the energy state before and after the leakage is evaluated through entropy increase calculation, and the leakage position and time are further predicted accurately; by simulating energy flow under differentiated environment conditions, the accuracy of seepage path identification is improved, and more efficient seepage source positioning is realized, so that the whole seepage traceability identification process is more systematic and scientific, and the safety supervision and maintenance efficiency of water conservancy facilities is greatly enhanced.

The invention discloses a PCB surface defect detection method and system, an electronic device and a medium, and relates to the technical field of defect detection, the connection condition caused by excessive tin soldering of a tin bridge or adjacent welding spots can be automatically identified by judging the connection state between the welding spots, an overall detection instruction is triggered, early detection is facilitated, connectivity defects are avoided, and the detection efficiency is improved. And the welding spot connection reliability is improved. The image is divided into a plurality of image blocks, the texture difference data of each image block is obtained, the texture abnormal state of the surface of the PCB can be finely analyzed by calculating the texture deviation coefficient, the subtle texture change in different areas can be identified by the block analysis method, and surface defects such as scratches and bubbles on the surface of the PCB can be accurately detected. And in combination with the texture deviation coefficient and the geometric features of the welding spots, unified normalization fitting is performed on the defect features to generate the defect recognition index, so that the defect features of different types can be captured, and the robustness and accuracy of the model can be improved.

The invention discloses a power distribution network fault positioning method and equipment based on a graph convolutional neural network, belongs to the technical field of power distribution network fault positioning, and is used for solving the technical problems that a traditional fault positioning method depends on feature information of a single node, neglects the overall structure of a power distribution network and is difficult to deal with a complex and changeable power distribution network. The method comprises the steps of performing data preprocessing on a collected data set to obtain a target data set; constructing an optimization matrix based on the target data set and the topological structure diagram of the to-be-tested power distribution network; performing node feature extraction on the topological structure diagram to obtain a node feature vector; training a graph convolutional neural network through the optimization matrix and the node feature vectors, and performing sample balance adjustment to obtain a power distribution network fault positioning model; and inputting the to-be-detected data into the power distribution network fault positioning model for identification to obtain state parameters of each node, and positioning a fault node according to the node state parameters. According to the invention, the accuracy and robustness of power distribution network fault positioning are improved.

The invention discloses a method and a device for detecting and positioning surface defects of a PCB (Printed Circuit Board). The method comprises the following steps: acquiring a reference image and a sample image of the PCB; processing the light and shade distribution of the sample image to obtain a sample image with uniform illumination; correcting a pixel difference between the sample image and the reference image to enable the reference image and the sample image to achieve pixel-level alignment; carrying out defect detection index calculation on the reference image and the sample image according to regions, and detecting and positioning defects. According to the method, the detection accuracy and efficiency are improved, the hardware cost and the calculation overhead are reduced, and deployment and implementation in the actual production and manufacturing process are easy; meanwhile, due to the high automation attribute, the detection reliability and the flexible adjustment capability, the method has wide application prospects and practical value.

The invention discloses a detection method for plastic packaging bag production, and relates to the technical field of plastic packaging bag production, and the detection method specifically comprises the following steps: 1, placing a plastic packaging bag on a detection table, enabling an upper clamping plate and a transverse plate to move downwards, enabling the upper clamping plate to firstly contact with the packaging bag, and carrying out preliminary positioning; 2, after the pressing plate makes contact, an adjusting plate makes contact with the packaging bag and pushes the packaging bag to move towards the two sides, and stretching, unfolding and flattening are achieved through assistance of balls; 3, the upper clamping plate continues to move downwards, the extension plate makes contact with the fixed plate and is limited, the position of the pressing plate is determined, then a first air cylinder is started to drive a movable plate to move towards one side, and a control assembly on the movable plate drives the to-be-tested plastic packaging bag to be subjected to a stretching test. According to the detection method for plastic packaging bag production, the plastic packaging bag is stretched, unfolded and flattened through the adjusting plate, it can be ensured that the packaging bag is in a flat state in the detection process, and therefore the real physical performance of the packaging bag can be reflected more accurately.

The invention provides a Texaco gasification device corrosion problem analysis method, which comprises the following steps: selecting key monitoring points to monitor the corrosion condition of a target device, installing intelligent sensors at the points, collecting operation data in real time and transmitting the operation data to a central processing unit; analyzing the data, identifying an area possibly having a corrosion risk and an abnormal change trend, and determining a suspected corrosion area; carrying out deep detection on the areas to obtain detection data; detection data, equipment operation data and maintenance records are encrypted and stored, so that the authenticity, non-tampering and traceability of the data are ensured, and a reliable basis is provided for subsequent analysis and decision making; and in combination with an intelligent manufacturing technology, operation parameters and maintenance plans of the device are optimized according to a corrosion analysis result, and accurate analysis and effective prevention and control of corrosion problems are realized. By means of the scheme, accurate analysis and effective prevention and control of the corrosion problem of the Texaco gasification device are achieved, and the overall equipment management level and safety are improved.

The invention relates to a plant steel truss floor support plate, and belongs to the field of building steel structures, the plant steel truss floor support plate comprises a first bottom plate and a second bottom plate, the first bottom plate is arranged on the second bottom plate, the size of the second bottom plate is larger than that of the first bottom plate, and a plurality of first vertical rib positioning grooves are formed in the second bottom plate; the first vertical rib positioning grooves are formed close to the side face of the first bottom plate, second vertical rib positioning grooves are formed in the two sides of the first bottom plate, the second vertical rib positioning grooves penetrate through the bottom and the top of the first bottom plate, the second vertical rib positioning grooves correspond to the first vertical rib positioning grooves in a one-to-one mode and are communicated with the first vertical rib positioning grooves, and the first vertical rib positioning grooves in the two sides of the second bottom plate correspond to each other in a one-to-one mode. The floor support plate has the advantages that the vertical steel bars can be accurately and rapidly positioned, the vertical steel bars are not prone to deviation in the welding process, meanwhile, splicing of the adjacent bottom plates is facilitated, the machining difficulty of the floor support plate is lowered, and the situation of slurry leakage in the concrete pouring process is reduced.

The invention belongs to the technical field of roadway surrounding rock monitoring, and particularly relates to a fiber bragg grating roof separation monitoring device and method.The device comprises an anchor fluke, a shell, a rope, a sleeve, a protection box and a fiber bragg grating and further comprises a movement detection mechanism; the mobile detection mechanism comprises a winding drum, a lead screw, a base, a first magnet, a concave block, a sliding block, a fixing plate, an elastic frame, rotating teeth and a compression spring. The fiber bragg grating roof separation monitoring device solves the problem that in the monitoring process of an existing fiber bragg grating monitoring device, due to fatigue stress, loosening and falling of bonding points and damage of sensitive elements, the monitoring precision is reduced, redundant configuration of signals during monitoring is achieved, and the precision and reliability of the fiber bragg grating roof separation monitoring device are greatly improved.

The invention discloses a coal rock fracture image recognition method and system based on deep learning and post-processing, a coal rock fracture image recognition model is adopted to recognize and classify spliced coal rock fracture images, the model comprises an improved YOLOv5 target detection network, an image segmentation network and a classifier which are connected in sequence, after the image segmentation network outputs the binary image, parallax depth calculation is carried out on cracks and non-cracks in the crack images at different angles, and the cracks are determined based on the parallax depth; after the fracture is determined, carrying out image feature numeralization on the binarized image, and extracting fracture image feature parameters; the fractal dimension of the fracture is calculated, whether the fracture can be represented or not is preliminarily judged based on the fractal dimension, if yes, the fracture image feature parameters are input into a classifier, the type of the coal rock fracture is output, and if not, the specific type of the fracture is output. And the parallax depth, the fractal dimension and the image features are integrated for recognition and classification, so that the problems of misrecognition and missed recognition are effectively reduced.

The invention provides an infrared weak and small target detection method and system, electronic equipment and a storage medium, and belongs to the technical field of target detection, and the method comprises the steps: improving a YOLOv8 model for the features of an infrared weak and small target image; and performing target detection on the infrared weak and small target image by using the improved YOLOv8 model. According to the invention, a stronger infrared weak and small target detection capability is provided for the YOLOv8 model, and the problem of target detection precision bottleneck of a traditional model in a complex scene is effectively solved.

The invention provides a marketing information identification method and device based on vehicle positioning, equipment and a medium, and relates to the technical field of financial science and technology. According to the method, the parking characteristics and the parking information of the vehicle can be accurately obtained by obtaining the vehicle positioning data. By analyzing the vehicle parking characteristics, the vehicle parking information is identified, so that high-frequency parking points in the use process of the vehicle can be identified, and potential collecting and distributing places can be identified. A clustering algorithm is used to analyze the vehicle parking information, and the target distribution place with concentrated vehicle rental demands can be effectively identified. By identifying the target marketing object in the preset radiation range of the target distribution place, the potential customer group can be more accurately positioned, so that the identification accuracy and the identification efficiency of the marketing information are improved, the customer obtaining cost is reduced, more accurate market positioning and customer service are provided, the pertinence and the effectiveness of the marketing activity are enhanced, and the marketing efficiency is improved. And the marketing efficiency and the conversion rate are improved.

The invention discloses an aircraft noise source positioning method comprising the following steps: sound field signals are collected, and the sound field signals comprise sound pressure signals and three-dimensional particle vibration velocity signals; preprocessing the sound pressure signal and the three-dimensional particle vibration velocity signal to obtain frequency spectrum data; inputting the frequency spectrum data into a trained noise recognition model, and judging a noise event; when the noise event is judged to be aircraft noise, noise source positioning is carried out according to corresponding spectrum data; according to the invention, noise event identification can be carried out firstly, so that the influence of the sound source arrival direction and other noise sources is eliminated, and errors are avoided; and the sound pressure and the three-dimensional particle vibration velocity are collected for preprocessing, effective sound intensity signals are obtained for positioning, and the positioning precision is improved.

The invention discloses a multi-sensor fusion vehicle rapid positioning method and device, a storage medium and electronic equipment, and belongs to the technical field of vehicle positioning. The positioning method comprises the following steps: firstly, acquiring standard data of a vehicle in a driving process on a preset planned path through multiple sensors, and constructing an offline three-dimensional map containing a key frame image database; secondly, collecting fact pose data in a vehicle driving process as initial pose estimation, collecting online current frame environment image data in real time through a camera, extracting a global feature vector in the online current frame environment image, matching K pictures similar to the image from a key frame image database, and carrying out initial pose estimation on the K pictures; and extracting local feature points and descriptors in the K pictures, screening out the most approximate picture from the K pictures as a target picture, and calculating to obtain real-time pose estimation of the vehicle. According to the method provided by the invention, more efficient, more accurate and more reliable vehicle positioning is realized through the cooperation of online processing and offline processing.

The utility model provides a coil panel and cooking equipment, and relates to the technical field of cooking equipment. The coil disc includes: a first heat insulating member; the coil is arranged on the first side of the first heat insulation part and can generate heat radiation and an electromagnetic field after being electrified; the magnetic part is arranged on the second side, away from the coil, of the heat insulation part; and at least part of the second heat insulation component is located between the first heat insulation component and the magnetic part, and the first heat insulation component and the second heat insulation component are made of different materials.

The invention discloses a method for improving the stability of an absolute pressure type pressure sensor and the absolute pressure type pressure sensor, and the method comprises the steps: placing an absolute pressure chip in a square groove of a sintering pedestal, and carrying out the positioning of the absolute pressure chip; dispensing glue on the periphery of the sintering base, and bonding the ceramic insulating cover in the inner cavity of the sintering base; a circuit on the absolute pressure chip is connected with a pin on the sintering base through a gold wire, and the pressing ring, the corrugated diaphragm and the sintering base are welded and fixed; a cavity between the corrugated diaphragm and the sintering base is filled with silicone oil, and the cavity is sealed through steel balls. According to the method, in the process of improving the stability of the absolute pressure type pressure sensor, the square groove is formed in the sintering base, and the absolute pressure chip is placed in the square groove of the sintering base, so that on one hand, the absolute pressure chip can be effectively positioned; the internal stress generated by thermal mismatch caused by material performance mismatch between the adhesive and the sintering base and between the adhesive and the chip is eliminated, and the stability of the absolute pressure chip sensor is improved.

The invention provides an under-forest economic area multi-unmanned aerial vehicle cooperative positioning method, and belongs to the technical field of positioning navigation application. The method comprises the following steps: acquiring an all-sky photo of an under-forest point location, and calculating the crown opening degree of the point location; the hovering positioning time of the unmanned aerial vehicle is set according to the crown opening degree, and under-forest hovering positioning of the base station unmanned aerial vehicle is carried out by using satellite signals; positioning the under-forest sensing unmanned aerial vehicle cluster based on the position information of the base station unmanned aerial vehicle; on the basis of multi-unmanned-aerial-vehicle cooperation of the base station unmanned aerial vehicle and the sensing unmanned aerial vehicle cluster, under-forest positioning signals are explored, and multi-unmanned-aerial-vehicle cooperative under-forest positioning is achieved According to the method, efficient and accurate positioning of the under-forest economic area can be achieved through cooperation of satellite signals and the multiple unmanned aerial vehicles, the position information service of vertical integration of the canopy is promoted, mechanical and automatic support is provided for under-forest planting and breeding, and intensive and efficient development of under-forest economy is assisted.

The invention relates to the technical field of visual identification and detection of polishing robots, in particular to a multi-type polishing area detection algorithm for casting autonomous polishing. Comprising the following steps of S1, process type classification, S2, defect type classification, S3, bulge type defect detection, S4, crator defect detection, S5, rough surface defect detection and S6, point-by-point grinding process detection. According to a grinding target area detection algorithm provided by the invention, a position sensing basis is provided for grinding track planning by classifying grinding areas; different detection algorithm libraries are formed and deployed in a system of the grinding robot, the adaptability to detection of the to-be-ground area can be enhanced, and the working capacity of the grinding robot is improved.

The invention relates to a three-phase cable positioning method and device, a storage medium and electronic equipment, and aims to efficiently position a three-phase cable by using a small number of magnetic field sensors and reduce the calculation complexity and cost. The method comprises the following steps: respectively acquiring instantaneous magnetic field components of a to-be-detected three-phase cable in a preset power frequency period based on a first magnetic field sensor, a second magnetic field sensor and a third magnetic field sensor; adjusting the direction of each magnetic field sensor in the first magnetic field sensor, the second magnetic field sensor and the third magnetic field sensor to enable the amplitude of the instantaneous magnetic field component in the z-axis direction corresponding to each magnetic field sensor to be 0; the overall positions of the first magnetic field sensor, the second magnetic field sensor and the third magnetic field sensor are adjusted, so that instantaneous resultant magnetic field amplitudes corresponding to the first magnetic field sensor and the third magnetic field sensor are equal; and determining the laying depth of the to-be-measured three-phase cable according to the instantaneous magnetic field components corresponding to the first magnetic field sensor and the second magnetic field sensor respectively.

The invention discloses a GIS internal multi-source partial discharge signal positioning method comprising the following steps: carrying out noise reduction processing on ultrahigh frequency signals collected by a plurality of sensors to obtain pure signals corresponding to the sensors; based on the pure signals corresponding to the sensors, the time difference of the partial discharge signals of the jth partial discharge source received by any two sensors is solved by using an initial energy increase cross-correlation method, and the multi-source time difference is obtained; according to the multi-source time difference, generating MN-1 spaces and calculating the fitness of each space, taking the positioning position in the space with the best fitness as the coordinate of the partial discharge source, i = 1, 2, 3,..., N, j = 1, 2, 3,..., M, N being the total number of sensors, and M being the total number of the partial discharge source; according to the invention, the positioning of the multi-source partial discharge signal can be realized.

The invention provides a spinal endoscopic image deblurring method and system, and the method comprises the steps: carrying out the multi-scale convolution operation of a spinal endoscopic image, obtaining the difference of image contrast among different scales, segmenting the spinal endoscopic image into a plurality of local structure images, and obtaining a plurality of local structure images; determining the brightness uniformity of each local structure image through the distribution gradient of the pixels in each local structure image and the difference quantity of the contrast; determining the dependency relationship of the textures between the adjacent local structure images through the texture difference between the adjacent local structure images on the spine tissue structure; performing contrast enhancement on the brightness of the local structure image according to the dependency relationship and the brightness uniformity to obtain a local enhanced image; and fusing and reconstructing the fuzzy region through all the local enhanced images to obtain a deblurred spinal endoscope image. By adopting the scheme provided by the invention, local adaptive equalization enhancement of the image brightness of the spinal endoscope can be realized, so that detail blurring caused by non-uniform illumination is reduced.

The invention relates to a linear actuator with power-off self-locking and constant supporting force. The linear actuator comprises a driving assembly, a gas spring unit, a braking assembly and a planetary roller lead screw pair. The driving assembly converts electric energy into rotating kinetic energy to drive the actuator to operate. The air spring unit provides constant supporting force through a built-in high-pressure air cavity, and the pressure is adjusted through an inflation valve so as to dynamically adjust the supporting force. The braking assembly realizes power-off self-locking through a movable permanent magnet and a liquid sealing structure; the planetary roller lead screw pair converts rotation kinetic energy of the driving assembly into linear motion. The technical problems that an existing linear actuator is high in energy consumption, unstable in supporting force and lack of a self-locking function are solved.

The utility model relates to the technical field of mammary gland puncture, and discloses a positioning device for mammary gland puncture, which comprises a fixing structure arranged above a device shell, a connecting column is inserted into the top end of the inner wall of the device shell in a sliding manner, a spring is fixedly connected to the bottom end of the surface of the device shell, and the other end of the spring is fixedly connected with a cover plate. The bottom end of the cover plate is slidably sleeved with a containing bin through threads, the bottom end of the device shell communicates with a guide needle, the bottom end of a connecting column is fixedly connected with a moving block, the bottom end of the inner wall of the device shell is fixedly connected with a round rod, and the bottom end of a fixing structure is fixedly connected with a puncture needle. Through the cooperative arrangement of the connecting column, the guide needle, the moving block and the reset spring, a doctor can be helped to more accurately determine the target position in the mammary gland, the puncture needle can accurately enter an area needing to be examined or sampled, personal errors are reduced, and the puncture accuracy is improved.

An ancient painting damage detection method comprises the steps of collecting ancient painting damage images, constructing an ancient painting damage detection data set, dividing the data set, constructing an ancient painting damage detection network, extracting features of the ancient painting damage images, training the ancient painting damage detection network and testing the ancient painting damage detection network. Due to the fact that the dynamic self-adaptive convolution and global information fusion module is adopted, the damaged area in the damaged ancient painting image is detected, the technical problems that in the prior art, ancient painting damage detection is inaccurate and not attached are solved, position information of the damaged area of the ancient painting can be effectively recognized and positioned, the prediction frame can be adjusted in a self-adaptive mode, and the prediction accuracy is improved. Damage positions of different types of ancient paintings are identified, and the detection precision and the perception identification capability of the network are improved. The method has the advantages of high detection speed, high precision and the like, and can be used for computer detection of ancient painting damage.