3227results about How to "Wide applicability" patented technology

The invention provides a textile woven structure anomaly detection method, which comprises the following steps: acquiring real-time tension monitoring data of warps and wefts in a jacquard textile weaving process, and establishing a tension distribution model in a normal weaving state according to the real-time tension monitoring data; if the classification result is in an abnormal state, spraying a pre-prepared chemical reagent on the surface of the abnormal position of the jacquard textile, and collecting spectral data of the surface of the textile after spraying; performing feature extraction and classification on the spectral data, and obtaining a comprehensive anomaly detection result by comparing a classification result with a tension position anomaly detection result; according to the comprehensive anomaly detection result, an abnormal area is accurately positioned and marked, and a sample in the abnormal area is cut and conveyed to a sample analysis device; and carrying out microstructure analysis on the cut sample, extracting fiber arrangement characteristics, judging the abnormal degree of fiber arrangement, and obtaining a microstructure abnormality evaluation result.

The invention belongs to the technical field of copper-clad plates, and relates to a low-dielectric high-heat-resistance copper-clad plate and a preparation method thereof. By introducing the POSS resin, the dielectric constant of the copper-clad plate is effectively reduced, which is crucial for reducing signal delay and improving signal transmission efficiency. The introduction of the POSS resin not only improves the dielectric properties of the material, but also improves the glass transition temperature (Tg) of the material, which means that the physical and chemical properties of the material can be kept unchanged at a higher temperature, and the material is suitable for wider environmental conditions. By using the resin and the inorganic filler in a specific ratio, the copper-clad plate shows excellent copper foil peel strength, and ensures that the bonding force between the copper foil and the base material is not easily weakened under long-term use or severe conditions. Meanwhile, the material also has excellent CAF (conductive anode wire) resistance, can effectively prevent internal short circuit caused by moisture, and prolongs the service life of an electronic product.

The invention discloses a pallet protection corner automatic putting machine. The pallet protection corner automatic putting machine comprises a top protection corner putting combination machine and aside face protection corner putting combination machine; the top protection corner putting combination machine comprises a bottom circulation base and a pair of top protection corner single machines,the side face protection corner putting combination machine comprises a bottom fixed base and four side face protection corner single machines, the top face protection corner single machines are provided with electrical control parts, top protection corner containing grooves, limiting mechanisms, and top protection corner mounting claws, the top protection corner mounting claws grab protection corners in the top protection corner containing grooves, and put the protection corners on four edges of the top of a packaging box, each side face protection corner single machine comprises a second electrical control part, a side protection corner containing groove, and a side protection corner mounting claw, and the side protection corner mounting claws grab the protection corners in the side protection corner mounting grooves and put the protection corners on the four sides of the side face of the packaging box. The pallet protection corner automatic putting machine is reasonable in layout,smooth in operation, high in adaptation, automatic in full process, free of artificial duty and capable of greatly improving protection corner putting and threading packaging capacity.

The invention discloses a novel electric power system source network load storage coordinated optimization planning method, and relates to the technical field of electric power system optimization, and the method comprises the steps: S1, building a load prediction model based on various user side load dynamic adjustment data, and improving the prediction precision, S2, determining parameters and constraint conditions of each link of source network load storage of an electric power system, s3, carrying out source network load storage collaborative optimization scheduling by utilizing an optimization algorithm; S4, evaluating and verifying an optimization result; according to the novel power system source-network-load-storage coordinated optimization planning method, the precision of load prediction is greatly improved, so that the problem that supply and demand matching is difficult is effectively solved, rapid fluctuation or sudden change of user loads can be rapidly responded, the adaptability and flexibility of a scheduling strategy are remarkably improved, and the scheduling efficiency is improved. The problems of supply and demand matching and scheduling flexibility caused by low load prediction precision under the condition of dynamic adjustment of various user side loads in the prior art are solved.

The invention relates to the technical field of intelligent detection of building materials, in particular to a real-time detection method for grain composition characteristics of muck. The method comprises the following steps: S1, acquiring original point cloud data; s2, particle point cloud clustering; s3, determining the particle size of the sieved particles; s4, particle morphological feature extraction; s5, correcting the mass of the particles; and S6, grading feature output. The method has the characteristics of high precision, high efficiency, low cost, wide applicability and the like in particle grading characteristic detection, is particularly suitable for grading characteristic detection of residual mud particles, can also meet the real-time detection requirements of related particulate matters in other fields, such as mineral particle screening, building gravel detection, agricultural granular fertilizer grading and the like, and has a wide application prospect. Rapid and accurate detection of grain composition characteristics in different industries can be realized, and the requirements of various industrial production and engineering application are met.

The invention relates to a rainfall kinetic energy space-time prediction method based on dual-polarization weather radar observation parameters, and the method comprises the steps: firstly processing minute-resolution raindrop spectrometer data, calculating raindrop diameter distribution, and calibrating the data of a rain gauge; secondly, dual-polarization radar parameters (ZH, ZDR and KDP) are calculated based on a physical formula, rainfall kinetic energy KE is calculated in combination with micro-physical characteristics, and rainfall types are marked; and then, after atmospheric field variables are extracted and physical normalization is carried out, a bidirectional time series kinetic energy prediction network (BTKE-Net) is constructed, and rainfall kinetic energy is accurately predicted through BiLSTM and a deep regression network. And finally, after attenuation and offset correction, inputting the data into the trained BTKE-Net model, and carrying out real-time space-time prediction. The innovation of the invention lies in that the application potential of the dual-polarization weather radar in the water environment field is excavated, large-range high-precision rainfall kinetic energy space-time prediction is realized, and more accurate scientific basis and decision support are provided for water and soil conservation and meteorological disaster prevention and control.

The invention provides a ground surface settlement monitoring method and system fusing Beidou and InSAR data. The method comprises the following steps: receiving positioning data from a Beidou satellite system and earth surface deformation data acquired by a synthetic aperture radar interference measurement system; based on the positioning data and the earth surface deformation data, correcting the earth surface deformation data according to the environmental factors through a space-time fusion model to obtain corrected earth surface deformation data; by means of the corrected surface deformation data, a multi-stage analysis technology is adopted, the development trend of surface subsidence is determined, a surface subsidence distribution diagram is generated, and the surface subsidence distribution diagram is used for displaying spatial distribution characteristics of surface subsidence; and according to the ground surface settlement distribution diagram, the future ground surface settlement condition is monitored by using the space-time fusion model, and a ground surface settlement monitoring report can provide a scientific basis for early warning and prevention of geological disasters. The ground surface settlement monitoring efficiency and monitoring effect are improved.

The invention belongs to the technical field of data processing, and particularly relates to a method and system for document content recognition and intelligent paragraph and chapter disassembly. The method comprises the following steps: S1, splitting a PDF document into pages, and converting the pages into pictures; s2, performing DOM (Document Object Model) structure analysis on the split PDF page to obtain a text character set; s3, performing layout analysis on the PDF page picture to obtain a layout region set; s4, aggregating the obtained text character set and the layout area set into character blocks; s5, performing reading sequence recovery operation on the character blocks; s6, defining a title matching mode set; s7, traversing the row sequence of the block sequence, and obtaining a hierarchical relationship between directories through a comparison algorithm; s8, outputting a structured content block result; and S9, carrying out visual display on the PDF page picture and the content block coordinates, drawing a new coordinate area by a user, and carrying out secondary disassembly according to the provided coordinate area information.

The invention discloses a floating type photovoltaic platform device capable of actively adjusting the angle of a photovoltaic module, which comprises floating bodies, a photovoltaic mechanism, a central control system, connecting floating bodies and gravity anchors, and is characterized in that the photovoltaic mechanism is mounted on the floating bodies, the floating bodies are connected with the gravity anchors, the gravity anchors are placed in a water area, the plurality of floating bodies are connected through the connecting floating bodies, and the central control system is connected with the central control system. The central control system is installed on the connecting floating body, the central control system is respectively connected with the floating body and the photovoltaic mechanism, the floating body comprises an adjusting air cushion and a supporting floating body, the adjusting air cushion is arranged on the supporting floating body, the photovoltaic mechanism is arranged on the adjusting air cushion, and the supporting floating body is respectively connected with the connecting floating body and the gravity anchor. The sun position and the illumination intensity are monitored in real time through the central control system, the angle of the photovoltaic mechanism is actively adjusted through the adjusting air cushion, it is ensured that the photovoltaic assembly can receive sunlight at the optimal angle all the time, and therefore the photoelectric conversion efficiency is remarkably improved.

The invention relates to a multi-modal target identification and tracking prediction method based on a laser radar and a binocular camera, and belongs to the field of robot / unmanned system perception identification. Comprising the following steps: preprocessing a target two-dimensional image acquired by a binocular camera and target point cloud data acquired by a laser radar to obtain a preprocessed two-dimensional image and point cloud data; s2, performing two-dimensional target detection and tracking detection based on the preprocessed two-dimensional image to obtain a two-dimensional target detection and tracking result; s3, performing three-dimensional target detection based on the preprocessed point cloud data and the two-dimensional target detection and tracking result to obtain a three-dimensional detection result; and S4, based on the pixel coordinates in the two-dimensional target detection and tracking result and the pixel coordinates of the vertexes of the target point cloud boundary in the three-dimensional detection result, target fusion tracking prediction is carried out, and the target ID, the position, the category and the target point cloud boundary are obtained. And accurate identification and tracking of the target are realized.

The invention discloses a code printing quality control method and system of a laser vision code printing machine, relates to the technical field of code printing quality control, and aims to solve the problem that the laser vision code printing machine cannot perform code printing optimization according to a code printing process. According to the method, abnormal identification is carried out on the unqualified quality indexes in the code printing monitoring data, specific problems such as laser parameter abnormity, equipment faults and hardware problems can be accurately identified, the accuracy enables subsequent improvement measures to solve the problems in a more targeted manner, and the accuracy of code printing quality detection is improved by formulating clear code printing quality detection standards and targets. According to the method, the standardization and consistency of quality detection work are ensured, the division standard of quality evaluation is clarified, the quality evaluation result is more objective and accurate, the coding efficiency is improved by designing a reasonable path type, a starting point, an ending point and a path sequence, the accuracy and no intersection or overlapping of a coding path are ensured through the path simulation step, and the coding efficiency is improved. And repeated coding and waste are avoided.

The invention discloses an indoor environment performance optimization design method and system for a tall and large space building based on CFD and a multi-objective optimization algorithm, and the method comprises the steps: building a parameterized analysis model through combining with a BIM model, carrying out the digital simulation analysis of an indoor light environment and energy consumption through employing Honeybee Radio and Honeybee Entry plug-ins in Rhino and Grasshopper environments, determining optimization parameters and objectives, and carrying out the optimization of the indoor environment and energy consumption. And a BIM model and an IDF file corresponding to the optimal schemes are exported, the uniformity of the indoor airflow organization is evaluated based on FFD software, and parameters of the optimal schemes are determined. Compared with a traditional indoor environment optimization method, the high and large space building indoor environment performance optimization and evaluation method is efficient, accurate and economical, and has higher accuracy, higher adaptability and wider applicability. Natural lighting, building energy consumption and indoor three-dimensional thermal comfort can be considered at the same time, and optimization of the indoor environment performance of the tall and large space building is achieved.

The invention discloses an LLM-based graduation design thesis intelligent evaluation system. The system comprises a data input module, a preprocessing module, an LLM evaluation module and an evaluation result output module. Text data of graduation papers are input into the data input module, the data input module is connected with the preprocessing module, the text data, processed by the preprocessing module, of the graduation papers are input into the LLM evaluation module, and the evaluation result output module is connected with the LLM evaluation module. According to the system, a large language model is utilized to perform multi-dimensional evaluation on graduation theses submitted by students, including but not limited to content quality, logic structure, language expression, innovation, academic specification and the like. According to the LLM-based undergraduate thesis evaluation system, the LLM can adapt to thesis evaluation requirements in different subject fields through a fine adjustment mode.

The invention relates to a method for improving the same-circle mechanical property uniformity of a low-carbon cold heading steel wire rod, which comprises the following steps of: firstly, carrying out sectional heating on a steel billet at the temperature of a preheating section of 715-785 DEG C, the heating temperature of a first section of 810-850 DEG C, the heating temperature of a second section of 920-960 DEG C and the temperature of a soaking section of 1000-1040 DEG C; then the prepared steel billet is rolled into a wire rod, the initial rolling temperature ranges from 910 DEG C to 950 DEG C, the finish rolling inlet temperature ranges from 865 DEG C to 885 DEG C, the finish rolling outlet temperature is smaller than or equal to 1020 DEG C, and the finish rolling temperature ranges from 890 DEG C to 910 DEG C; the prepared wire is subjected to water cooling to 840-860 DEG C for spinning, and then the wire is rolled into a wire rod at 780-850 DEG C; and finally, the prepared wire rod is placed on a stelmor slow cooling line for heat preservation and slow cooling, the stelmor slow cooling speed is 0.2-1 DEG C / s, the temperature of entering a heat preservation vestibule is 740-770 DEG C, the heat preservation time of the heat preservation vestibule is 75-150 min, and the temperature of leaving the heat preservation vestibule is smaller than or equal to 400 DEG C. By means of the method, the same-circle mechanical property tensile strength fluctuation of the steel wire rod is smaller than or equal to 10 Mpa, the percentage reduction of area fluctuation is smaller than or equal to 2%, the percentage elongation after fracture fluctuation is smaller than or equal to 2%, the yield strength fluctuation is smaller than or equal to 8 Mpa, metallographic structures are evenly distributed, and no abnormal structure exists.

The invention provides an ultrafast laser welding method and device for large-spacing heterogeneous materials. The ultrafast laser welding method specifically comprises the steps that a lower workpiece and an upper workpiece are stacked and clamped through a clamp; a laser beam is collimated, then enters a scanning galvanometer and is focused through a field lens after being emitted, first scanning laser energy is absorbed by a lower-layer material to generate plasma, the plasma continuously expands and overflows, meanwhile, the lower-layer material is melted to fill a gap, and the quasi-optical contact condition is achieved; free expansion of plasmas in second scanning is effectively inhibited, laser energy is limited near a welding seam, the melting volume of the area is remarkably increased, and the welding strength is remarkably improved; and the third scanning and the second scanning are consistent in mechanism, the material melting amount is increased, and finally welding head strengthening is achieved. Through the scanning galvanometer and the field lens, a focusing light spot moves along a specified route in the contact surface of the upper and lower workpieces, so that the workpieces are melted and combined. After three times of scanning, the large-spacing heterogeneous material can finally obtain a high-strength and high-quality welding joint.

The invention discloses an urban underground space structure health detection method and detection system, and the method comprises the steps: S1, collecting the multi-modal data of an underground space structure through the deployment of diversified sensors; s2, preprocessing the collected data, wherein the preprocessing comprises filtering denoising and feature extraction; s3, performing pattern recognition and health state evaluation on the processed data by using a deep learning model; s4, dynamically adjusting a threshold value of health assessment according to the environmental parameters, and predicting a future health trend; and S5, the evaluation result is displayed through a visual platform, a corresponding health examination report is generated, the health condition of the underground space structure can be monitored in real time by integrating multiple sensors and utilizing a data processing technology, potential problems can be found in time, an early warning threshold value can be dynamically adjusted according to real-time monitoring data through a dynamic threshold value adjusting mechanism, and the early warning efficiency is improved. The problems of false alarm and missing alarm caused by a fixed threshold value are avoided, and the accuracy and reliability of early warning are improved. The method is suitable for various underground space structures.

The invention relates to the field of industrial vision, in particular to an operator behavior analysis method and system based on trajectory analysis. The method comprises the following steps: acquiring an action video of an operator, performing action feature extraction on a picture of the action video, performing fitting processing on an action feature point set, and setting a paragraph step length, the action track curve is divided into paragraphs according to the paragraph step length, the space distance between action track points in the action track paragraphs and standard track points in the standard operation track is calculated, the dynamic parameter difference is analyzed according to the action track paragraphs and the standard track paragraphs matched with the action track paragraphs, and a behavior monitoring result is obtained according to the dynamic parameter difference. The system comprises a video acquisition device, a video identification model, a curve fitting module, a paragraph matching module and an anomaly detection module. The method is lower in cost, cannot be interfered by an industrial field environment, and is wider in applicability. And the track is dynamically divided into track paragraphs, so that the applicability of the method is improved.

The invention discloses a vertex measurement device and method based on a spectral confocal technology, and the method comprises the steps: transmitting a plurality of light beams through a plurality of light-emitting apertures which are arranged in a preset geometrical shape, carrying out the dispersion of the plurality of light beams into dispersion light beams with different wavelengths through a dispersion lens, irradiating the dispersion light beams to the surface of a measured workpiece, receiving reflected light, and carrying out the measurement of the measured workpiece. The reflected light is transmitted to the spectrum analysis device through a corresponding optical fiber channel; the spectrum analysis device analyzes the light intensity and wavelength of each group of reflected light and extracts spectrum data; calculating the height or space coordinate of the vertex of the surface of the workpiece according to the change condition of the spectral data of each group of reflected light rays; the processing circuit outputs the calculated vertex height or space coordinate information; according to the method, the vertex information of the workpiece can be effectively derived through ingenious spectral analysis and geometric fitting technologies, and the method has wide applicability and is particularly suitable for vertex measurement scenes of high-precision spherical surfaces, aspheric surfaces and conical surfaces.

The invention relates to the technical field of target detection, in particular to an aquatic organism multi-target detection method and system based on YOLO. The method comprises the following steps: carrying out aquatic organism image acquisition on a target water area to obtain an aquatic organism image; performing resolution enhancement on the aquatic organism image to obtain an enhanced aquatic organism image; performing multi-branch hierarchical feature extraction on the enhanced aquatic organism image to obtain a residual enhanced biological feature image set; performing cross-scale feature fusion on the residual enhanced biological feature image set to obtain a fused aquatic organism feature image; performing historical detection data acquisition on the target water area to obtain an aquatic organism historical detection data set; and performing anchor frame generation on the fused aquatic organism feature map based on an aquatic organism historical detection data set to obtain an initial anchor frame set. The defects in aquatic organism monitoring and recognition in the prior art are effectively overcome, and the accuracy, efficiency and practicability of detection are improved.

The invention discloses a KAN-based photovoltaic power prediction method and system, and the method comprises the following steps: collecting historical data, preprocessing the historical data to form a data set, and dividing the data set into a training set and a test set; constructing a photovoltaic output day-ahead prediction model, and training the photovoltaic output day-ahead prediction model; testing and evaluating the trained photovoltaic output day-ahead prediction model; using the photovoltaic output day-ahead prediction model to predict photovoltaic power; the photovoltaic output day-ahead prediction model comprises a spatial feature extraction module, a time sequence feature extraction module and a spatial-temporal feature fusion and prediction power output module; the spatial feature extraction module extracts variable features at the same time point, learns the relation of the input variable features, and outputs spatial features; the time sequence feature extraction module extracts features between feature variables at different time points, learns a variable feature interaction relationship at different time points, and outputs time sequence features; and finally, the output module fuses the time sequence features and the spatial features and outputs a photovoltaic output prediction result.

The invention relates to the technical field of ship roll-on and roll-off equipment, and discloses a large automobile roll-on and roll-off transport ship movable ramp and a mounting method.The large automobile roll-on and roll-off transport ship movable ramp comprises a first hinge mount, a first ramp joint is rotatably arranged on the first hinge mount, and a second ramp joint is arranged at the end, away from the first hinge mount, of the first ramp joint; the end, away from the first ramp joint, of the second ramp joint is connected with a third ramp joint, a second hinge seat is arranged on the surface of the upper end of the hull structure and located on the inner side of the first hinge seat, a hinge shaft is arranged on the second hinge seat, and the second hinge seat is rotationally connected with the end of the third ramp joint through the hinge shaft. According to the movable ramp of the large automobile roll-on-roll-off transport ship, by arranging the supporting assembly and pulling out the positioning plug pin, when the third ramp section is lifted, the sliding block can slide along the rail base, then the positioning pin is clamped into the positioning hole, it is guaranteed that the position of the sliding block is fixed, then the supporting rod can effectively support the third ramp section, and the requirement for safe passing of automobiles is met.

The invention provides a method for reducing light source phase noise in a double-field quantum key distribution system, which combines an optical phase-locked loop (OPLL) and a proportional integral (PI) control technology, and comprises the following steps of: firstly, performing beat frequency on laser signals of light source ends Alice and Bob, and realizing frequency locking and phase synchronization of a laser through the OPLL; on the basis, the system introduces frequency deviation through an acousto-optic modulator (AOM) to ensure the stability of a beat frequency signal. Further, the system couples the optical signals after frequency beating through an optical beam splitter, and detects the power of the coupled optical signals. The detected power value is transmitted to the FPGA control module to serve as an input parameter of PI control, a proportionality coefficient and an integral coefficient are adjusted in real time, a feedback control signal is generated and used for dynamically adjusting a front phase modulator of a receiving end Bob, and therefore the phase noise of a light source end is effectively reduced.

The invention discloses a CoFeCuMn LDH nanosheet, a confinement catalytic membrane and a preparation method of the CoFeCuMn LDH nanosheet. The preparation method of the CoFeCuMn LDH nanosheet comprises the steps that A1, cobalt salt, ferric salt, copper salt and manganese salt are dissolved in pure water according to a preset proportion to prepare a first solution, sodium hydroxide is dissolved in pure water to prepare a second solution, and sodium carbonate is dissolved in pure water to prepare a third solution; a2, adding the first solution and the second solution into the third solution, and stirring to obtain a mixed solution; a3, carrying out hydrothermal reaction on the mixed solution; a4, centrifugally washing the product obtained in the step A3 to obtain a precipitate; and A5, the sediment is dried, and the CoFeCuMn LDH nanosheet is obtained. According to the CoFeCuMn LDH nanosheet, the confinement catalytic membrane and the preparation methods of the CoFeCuMn LDH nanosheet and the confinement catalytic membrane, the degradation efficiency and the degradation rate of new pollutants are remarkably improved.

The invention provides a digital person business card interaction method, electronic equipment and a storage medium, and belongs to the technical field of data processing, and the method comprises the steps: responding to a business card viewing instruction, and outputting a target digital person business card associated with the business card viewing instruction; receiving an inquiry instruction based on the target digital person business card, and judging whether the inquiry instruction has a corresponding standard problem or not; if yes, inputting an information set associated with the standard question and the target digital person business card into a pre-trained information desensitization large model; if not, calling a preset search engine to search the inquiry instruction, determining a search data set based on a search result, and inputting the inquiry instruction, the target digital person business card and the search data set into a pre-trained information desensitization large model; and obtaining a desensitization answer output by the information desensitization large model, and outputting the desensitization answer. According to the method, the interaction efficiency of the recruitment process can be remarkably improved, the hysteresis of information transmission is reduced, and the personal information security is protected.

The utility model provides an intercepting and purifying device suitable for river-entering farmland ditches, which comprises an intercepting structure and a purifying structure, the intercepting structure comprises a sludge deposition and grit chamber and a steel grating, a denitrification device containing denitrifying phosphorus-accumulating bacteria and adsorptive mineral materials is placed in the sludge deposition and grit chamber, and the steel grating is arranged in the sludge deposition and grit chamber. A sand setting inlet and a sand setting outlet are formed in the two opposite sides of the steel grating respectively, the steel grating is arranged at the sand setting outlet, and the sand setting inlet is used for being communicated with an ecological ditch; the purification structure comprises an ecological purification pond and a gabion packing bed, the ecological purification pond is provided with a purification inlet and a purification outlet, gabions are arranged at the purification inlet and the purification outlet, the ecological purification pond is tightly attached to the sludge deposition and grit chamber, the purification inlet is opposite to and communicated with the grit inlet, and the gabion packing bed is arranged in the sludge deposition and grit chamber. And the gabion packing bed is arranged in the ecological purification pond.

The invention relates to the field of intelligent forecasting of ship swaying motion, and provides a ship swaying motion forecasting method based on a physical information neural network, which comprises the following steps: simulating heaving motion of a ship in real waves by adopting fluid mechanics, and collecting swaying motion data when the ship moves in the waves; constructing a physical information neural network model, initializing the physical information neural network model and completing data preprocessing; constructing a wave excitation force function by using the obtained motion data, fusing the wave excitation force function into a physical information neural network model, and training the physical information neural network model; and inputting the real-time motion data into the trained physical information neural network model, and predicting the heaving displacement and the pitching angle of the ship.

The invention provides a method for training an end-to-end automatic driving strategy, and the method comprises the following steps: S1, data collection and preprocessing, S2, defining a loss function and an optimizer, and constructing a model, S3, data division, S4, model training, S5, evaluation on a verification set, S6, model adjustment and optimization, and S7, test set evaluation. S8, weight pruning and evaluation: calculating and evaluating the importance of each weight by adopting a gradient norm calculation mode, evaluating the model after weight pruning by using the test set in the step S7 according to an importance evaluation result, starting from a relatively small proportion, gradually increasing and removing unimportant weights, and if the performance of the model does not reach the standard at the moment, evaluating the model after weight pruning by using the test set in the step S7. According to the method, through weight pruning, the applicability of a model system is wider, and the training efficiency of the system is higher.

The invention discloses a light source intensity adjusting method and system for surface defect detection, and the method comprises the steps: setting a first light source intensity and a second light source intensity, and obtaining a to-be-detected region image under the corresponding light source intensity, the first light source intensity being smaller than the second light source intensity; the corresponding illumination instability degree is calculated according to the to-be-detected area image under the first light source intensity and the second light source intensity, the optimal light source intensity is determined by continuously reducing the range between the first light source intensity and the second light source intensity to search the light intensity mean value of the first light source intensity and the second light source intensity or by means of step-by-step light intensity adjustment, and the light intensity of the to-be-detected area is determined according to the optimal light source intensity. And carrying out surface defect detection and measurement work on the to-be-detected area. According to the invention, the optimal illumination light source intensity suitable for the current detection environment can be rapidly adjusted.

The invention discloses an automobile auxiliary driving monocular distance measurement method and device based on a lightweight occupation prediction network, and the method comprises the steps: firstly constructing a 3D occupation prediction data set, and then constructing a monocular occupation prediction teacher model based on multi-frame time sequence fusion and time sequence stereo depth estimation, and a lightweight monocular occupation prediction student model based on single-frame input. And training the occupation prediction teacher model to obtain the occupation prediction teacher model with good performance, and evaluating the performance of the teacher model. And performing distillation training of the student model by using the teacher network intermediate layer features and output to obtain a performance-improved lightweight occupation prediction student model, and evaluating the performance of the student model. And finally, performing forward reasoning on the student model, and performing connected domain analysis on an interested instance (such as a vehicle and a pedestrian) from a reasoning result to complete monocular distance measurement. The method provided by the invention overcomes the problem of inaccurate distance measurement caused by unstable detection frame in the traditional monocular distance measurement method, and improves the performance while lightening the model by using the distillation technology.

The invention discloses an indoor visible light fusion positioning method based on deep learning. The method comprises the following steps: step 1, acquiring AoA information and UWB distance information data of visible light at different positions, preprocessing the data, and converting the data into a two-dimensional matrix format to facilitate network input; 2, constructing a network model for extracting features of the preprocessed data, performing feature fusion, processing the fused features, and outputting positioning continuous coordinate values of the obtained data; step 3, training the network model, using samples including and not including AoA data, and ensuring that the network model can perform effective learning under the condition that only UWB data exists; according to the invention, the penetrability of the UWB signal is utilized to make up for the defect that visible light is easy to block, and high precision and stability can be maintained in different environments.