10536results about "Sorting" patented technology

The invention relates to the technical field of solid waste treatment, in particular to an intelligent waste sorting method based on multi-sensor fusion. Carrying out multi-level fusion decision making: carrying out sewage reflection suppression on the visible light image; carrying out matching identification and rejecting a liquid pollution area based on a near infrared spectrum; fusing the visible light texture, the spectral feature and the electromagnetic signal to generate a space grid feature vector; identifying the material category through a cascade classifier, and dynamically adjusting the weight of each sensor in the decision according to the environmental parameters; self-adaptive sorting execution: triggering a corresponding sorting execution mechanism according to an identification result; based on the transmission belt speed, the execution mechanism response delay and the material physical attribute, the action advance compensation amount is calculated; the action time of an execution mechanism is adaptively prolonged for the stacked materials according to the stacking hierarchy; and online feedback optimization. Through dynamic compensation and time sequence adjustment, the time sequence consistency of multi-sensor data is ensured, and the influence of band speed fluctuation is overcome.

A system including: a robotic frame including at least an actuated arm, a machine-vision system including at least a camera, the machine-vision system communicatively connected to a computing device, the computing device including at least a processor and a memory communicatively connected to the at least a processor, the memory storing instructions configuring the at least a processor to: receive image data from the at least a camera, the image data including at least two captured viewpoints of a produce item, extract at least an object-level visual feature from the image data using a machine vision model, assign a defect classification label to the produce item as a function of the at least an object-level visual feature, and control the at least an actuated arm to perform a handling operation on the produce item as a function of the defect classification label.

The invention discloses an ECU assembling and detecting production line for an automobile and a process of the ECU assembling and detecting production line. The ECU assembling and detecting production line comprises a circuit board feeding mechanism, an implanting mechanism in butt joint with the circuit board feeding mechanism, a detecting mechanism in butt joint with the implanting mechanism and a classifying and packaging mechanism in butt joint with the detecting mechanism. By means of the mode, circuit board feeding, injection molding embedding, injection molding material taking, detecting and classified packaging are integrated, the automation degree is high, secondary positioning and accurate positioning of the circuit board can be achieved, the horizontal position and angle of the circuit board can be automatically adjusted, and the injection mold can be aligned in a self-adaptive mode; each performance of a product can be synchronously detected, and code printing and identification can be carried out without repeatedly carrying and positioning the product and classifying and collecting defective products and non-defective products in different mold cavities, so that subsequent searching for reasons of the defective products is facilitated, and later maintenance of equipment is facilitated.

System for packing and sorting comprises: a server comprising a memory, a processor, and a sortation engine, an automated packaging device, and a packaging sorting system. The automated packaging device is configured to: receive one or more sorted articles through an opening of a repository of the automated packaging device, and seal the repository to form a package. The package sorting system configured to: direct a package computer controlled vehicle to move to a receiving position about the automated packaging device for receiving the package from the automated packaging device, and direct the package computer controlled vehicle to transport and deposit the received package into a package receptacle.

The invention discloses microminiature needle body high-speed visual screening equipment and a screening method thereof, and belongs to the technical field of industrial automatic detection and sorting. The equipment comprises an equipment frame, a feeding module, a visual identification module, a grabbing module, a control module and a material receiving module. The feeding module is used for conveying to-be-screened needle bodies. The visual identification module performs image acquisition and model identification on the needle body; the grabbing module is provided with a plurality of grabbing clamping jaws, can move in the horizontal direction and the vertical direction under the driving of the control module, and grabs a plurality of needle bodies of the same model at the same time at a time. The material receiving module comprises a plurality of material receiving boxes and a transposition driving mechanism for driving the material receiving boxes to move so as to align the target material receiving box to the grabbing module. The equipment disclosed by the invention can be widely applied to high-efficiency sorting of micro-miniature needle bodies with the diameters ranging from 0.3 mm to 3mm and the lengths ranging from 3mm to 77mm, has high precision, high speed and high reliability, and is suitable for large-scale production and multi-variety and small-batch production requirements.

A sorting mechanism (1), which relates to the technical field of circuit board production, and comprises a first pick-and-place assembly (11), a second pick-and-place assembly (12), a first driving assembly (13), and a connecting base (14). The first pick-and-place assembly (11) and the second pick-and-place assembly (12) are slidably provided on the connecting base (14) by means of the first driving assembly (13), and the first driving assembly (13) can drive the first pick-and-place assembly (11) and the second pick-and-place assembly (12) to move independently. The first pick-and-place assembly (11) is used for gripping a board to be sorted, and the second pick-and-place assembly (12) is used for gripping a first spacer paper. The first driving assembly (13) is used for driving the first pick-and-place assembly (11) to grip a board to be sorted from a feeding station and convey said board to a first target position, and for driving the second pick-and-place assembly (12) to grip a first spacer paper from the feeding station and convey the first spacer paper to a second target position. The sorting mechanism (1) enables sorting of boards to be sorted and first spacer papers that are stacked together, thereby improving the applicability and universality. Also provided are a conveying and inspection apparatus and an automatic sorting device.

The invention belongs to the technical field of biological sample sorting, and discloses a visual identification control system for automatic sorting of biological samples, through cooperation of a multi-modal sensing acquisition unit and a knowledge graph multi-dimensional identification unit, condensed water of a frozen sample tube can be penetrated to accurately identify label and molecular characteristics, and'condensed water shielding 'and'label damage' are distinguished; meanwhile, a sample preprocessing state is associated, and samples which do not meet requirements are automatically intercepted. Compared with the prior art, manual secondary verification is not needed, sorting dislocation caused by optical interference of smear glass slides is thoroughly solved, the sorting precision and efficiency of mixed samples are remarkably improved, and diversified sample treatment requirements in clinical detection are met; the full-link twin operation and maintenance unit integrates key data in a sorting process through a block chain technology, and is interconnected and intercommunicated with a hospital LIS system and a sample storage system; and when the subsequent storage environment of the sample is abnormal, the quality state of the sorting stage can be reversely associated, and the compliance auditing vulnerability is eliminated.

The invention relates to the technical field of screen thickness detection, in particular to a thickness detection device for mobile phone screen production, which comprises a movable bracket, a controller, a conveyor, a detection frame, a sliding rail, a sliding block and a conveying assembly, the controller is fixedly mounted on the right side of the front part of the movable bracket, and the conveyor is fixedly mounted on the top of the movable bracket; a conveying assembly is arranged on the conveyor, a detection frame is fixedly connected to the outer side of the left portion of the movable support, sliding rails are fixedly connected to the top and the bottom of the detection frame, and sliding blocks are slidably connected to the sliding rails. By means of the laser thickness gauges which are opposite up and down, in cooperation with reverse front-back movement driven by the reciprocating assembly, a rhombic latticed scanning track is formed by overlapping the conveying belts to drive the screen to be conveyed at a constant speed, the whole area of the screen can be covered, missing detection is avoided, the screen is limited by the pressing wheels, and deviation in the conveying process is prevented. The laser calculates the distance difference value through the time difference / phase difference to obtain the thickness, detection data is direct, errors are small, and the detection accuracy is guaranteed.

The invention discloses an auto spare part deformation detection device based on visual analysis, relates to the field of auto spare part detection, and solves the problem that an existing detection device reduces the accuracy of a lens, the auto spare part deformation detection device comprises a workbench and a positioning column fixedly mounted at the top of the workbench, and a top plate is fixedly mounted at the top of the positioning column; a display host is fixedly mounted at the top of the top plate; a detection probe is fixedly mounted at the bottom of the display host; the feeding mechanism is used for cleaning the surface of the detection probe and conveying accessories to be detected, and the feeding mechanism is mounted at the top of the workbench; a plurality of accessories are conveyed to the outer side of the detection probe in sequence through the feeding mechanism, the detection probe can conveniently conduct visual detection on the accessories, the detection condition is transmitted to the display host to be observed by workers, the surface of the detection probe is brushed in the accessory conveying process, and therefore the effect of conveniently cleaning the detection probe is achieved; and the visual detection accuracy of the accessory is improved.

The invention discloses a module belt conveying assembly and NC sorting equipment, and belongs to the field of logistics conveying. Comprising a conveying assembly, the conveying assembly comprises two sets of supporting frames, a plurality of sets of supporting beams are fixed to the supporting frames, and a PLC control system is fixed to the positions, close to the feeding end, of the supporting frames; the driving assembly comprises a driving shaft with a bearing arranged between the two groups of supporting frames; the transmission assemblies comprise a plurality of transmission parts which are fixedly connected to the driving shaft in a sleeving mode and arranged at intervals, jacking parts are arranged on the transmission parts, and power parts are arranged on the supporting beams; and the NC sorting modules are used for sorting the goods. According to the module belt conveying assembly and the NC sorting equipment, through cooperation of the transmission part jacking part, the supporting beam power part and the jacking assembly, overall horizontal jacking of a module belt is achieved, extra loads and eccentric wear of a conveying shaft are eliminated, shaft deformation is prevented, and bearing wear is relieved; stable material sorting is guaranteed, the clamping stagnation and slipping risks are reduced, and the stability and durability of equipment are improved.

The invention discloses an intelligent sorting method and device for a positive electrode material of a retired lithium ion battery based on a spectrum method, and the device is connected in series with a pretreatment module, a cleaning module, an identification module and a sorting module through a conveying belt in a supporting module to form an automatic sorting assembly line. Pre-treating the retired battery to obtain a clean positive plate; an X-ray fluorescence spectrophotometer in the recognition module collects the spectrum of the positive plate and transmits the spectrum to an industrial personal computer, and the spectrum is preprocessed and then input into a classifier library; the classifier library comprises a main classifier and an increment classifier based on element and spectral shape dual channels, if the output confidence reaches a preset threshold value, the material category is judged, otherwise, the spectrum is temporarily stored as an unknown spectrum; after unknown spectrums are accumulated to a set number, new categories are identified through a clustering algorithm, and a lightweight dichotomy increment classifier is trained and added into a classifier library; and the sorting module drives the hydraulic pushing hand to sort the positive plates according to the identification result. Through cooperative evolution of the main classifier and the increment classifier, the sorting precision is effectively improved.

The invention provides a filter stick defective product sorting method for reinforcement learning self-adaptive grabbing, and relates to the technical field of filter stick sorting. The defects of the filter stick are recognized through a multi-view visual module, image coordinates are compensated in real time in combination with the speed of a conveying belt, and the image coordinates are accurately mapped to a three-dimensional working space of a mechanical arm; then, defect poses, production line states and mechanical arm parameters are input to a reinforcement learning module, so that the optimal grabbing action and clamping pressure are output, and efficient sorting of the driving mechanical arm and the soft clamping jaw is achieved; and meanwhile, the feedback evaluation unit acquires a grabbing result through a sensor, generates a reward signal optimization strategy network, and realizes continuous online learning. The technical problems that in a high-speed flexible production line, a traditional sorting system is insufficient in grabbing precision and high in false grabbing rate due to the fact that visual recognition and a mechanical grabbing strategy are disjointed are solved. According to the invention, the collaborative precision of defect identification and grabbing and the sorting efficiency in the filter stick production line are obviously improved.

The invention relates to the technical field of fruit and peach screening, in particular to a fruit and peach multi-stage screening and quality detection method which comprises the following steps: S1, fruit and peach variety judgment: collecting multi-angle images, extracting color, texture and contour features, and outputting variety labels and parameter sets in a classified manner; s2, growth feature mapping: extracting structure key points, matching the structure key points with a variety template, and generating a growth deviation vector; s3, area perception analysis: dividing fruit surface areas based on growth deviation, and independently identifying defects and maturity; s4, grade discrimination: fusing identification results, combining varieties and deviations, and dynamically evaluating a comprehensive quality label; and S5, screening instruction generation: converting the quality label into a control instruction, and driving the sorting device to complete output. According to the invention, integrated automatic processing of intelligent identification of fruit and peach varieties, accurate detection of regional defects and grade screening control is realized, and the accuracy and flexibility of fruit and peach screening are significantly improved.

The invention relates to the technical field of semiconductor device manufacturing, solves the technical problem that in the prior art, automatic grain digging treatment cannot be carried out on detected LED support defective products, and provides a grain digging control method, device and equipment for LED support defective products. Acquiring a real-time image of the to-be-detected LED bracket under a preset target illumination condition; performing visual detection processing on the real-time image, and judging whether the to-be-detected LED bracket is a defective bracket product or not according to a visual detection processing result; when the to-be-detected LED bracket is judged to be a defective bracket product, defect position detection is carried out on the defective bracket product to obtain defect position information; according to the defect position information, defective stent particles in the defective stent products are removed, and particle digging control over the defective stent products is achieved. According to the automatic grain digging device, automatic grain digging treatment can be accurately carried out on the LED support defective products.

The invention provides a seed screening method and system based on a laser radar technology, and relates to the technical field of agricultural automation, and the method comprises the steps: extracting geometric features and defect features from optimized point cloud data; extracting mildew and insect pest spectral features from the optimized spectral data; a multi-dimensional feature set is obtained; calculating seed plumpness, roundness and surface roughness based on the optimized point cloud data; calculating a sag index and a crack feature based on point cloud edge detection; fusing the geometric features, the defect features and the pest spectral features to generate a comprehensive score; a machine learning model is utilized to execute final grading, and a first probability predictor based on laser radar features and a second probability predictor based on pest spectral features are trained respectively; and inputting the probability outputs of the two predictors into a second-layer grading model of the meta-learning architecture, and outputting a final quality grade. According to the method, efficient and accurate seed screening is realized through automatic process and algorithm design.

The invention discloses an automatic guider assembly line and an automatic guider assembly method, and relates to the field of manufacturing of automobile shock absorbers, and the automatic guider assembly line is characterized by comprising a first material machine and a second material machine which are separated from each other, and a butt joint conveying belt for connecting the first material machine and the second material machine. The first material machine is provided with an assembly rotating disc used for sequentially stacking parts such as an oil scraper ring and a valve block to form a small assembly, and a small assembly detection station and a small assembly NG discharging station are arranged before the small assembly is installed into a guider bare part. And the second material machine is used for performing bushing press fitting and final detection on the semi-finished products conveyed from the first material machine. Precise assembly and high-force press-fitting procedures are separated, so that the problem of process interference is effectively solved, and the assembly stability and the product quality are improved; meanwhile, the middle quality doors are arranged on the sub-assembly levels, so that unqualified products can be removed in advance, the cost superposition type waste is fundamentally avoided, and the production efficiency and the economic benefits are remarkably improved.

The invention discloses an intelligent fructus aurantii sorting machine based on a five-connecting-rod mechanical arm and a sorting method. The sorting machine comprises a collecting mechanism, a conveying mechanism, a supporting mechanism, a sorting mechanism, a camera support, a feeding device, a lower computer, an upper computer and a vacuum adsorption control system. The sorting mechanism comprises a vacuum adsorption sorting device, a five-connecting-rod mechanical arm and a sorting mechanism supporting base, double motors are adopted to cooperatively drive and control space positioning of an end effector of the mechanical arm, and high-precision target grabbing is achieved through angle difference compensation. The upper computer converts the target center position recognized by the visual recognition device into space coordinates of the tail end of the mechanical arm through a coordinate conversion algorithm, and the five-connecting-rod mechanical arm is driven to complete precise sorting operation. Stable adsorption of the fructus aurantii is completed by means of vacuum negative pressure, the fructus aurantii naturally falls off by directly cutting off a negative pressure air source, and intelligent grading and sorting operation of the quality of the fructus aurantii is achieved. The device is suitable for automatic sorting of the traditional Chinese medicinal material fructus aurantii and is high in sorting efficiency, accurate in positioning and high in adaptability.

The invention discloses an echelon utilization method for waste power batteries of new energy vehicles, which comprises the following steps: firstly, collecting and preliminarily classifying and screening retired batteries according to health states, and quickly eliminating potential safety hazards by using infrared thermal imaging and voltage consistency detection; comprehensive performance detection including complementary energy detection, discharge capacity test at different temperatures, direct current internal resistance measurement and charge and discharge temperature rise test is carried out; key parameters are extracted from the detection data, comprehensive performance analysis is carried out in combination with application scene requirements, and a comprehensive evaluation score is generated; selecting similar batteries to form a pre-combination unit according to the score sequence; a grouping result is optimized through a clustering algorithm in the three-dimensional performance coordinate system, and it is ensured that the deviation of core parameters of the same group of batteries is smaller than a set threshold value; the stability and the operation efficiency of the echelon utilization system are improved, the adaptive capacity of the echelon utilization system in different application scenes is enhanced, and a guarantee is provided for stable operation of the echelon utilization battery system.

The invention discloses corrugated paper conveying equipment based on visual screening. The corrugated paper conveying equipment comprises an equipment frame, and a lifting seat is arranged at one end of the equipment frame in a lifting mode; the first conveyor is arranged in the equipment frame, one end of the first conveyor is rotationally installed in the lifting base, and the other end of the first conveyor is arranged at the end of the equipment frame in a lifting mode; a plurality of industrial cameras are arranged on the top of the first conveyor, unqualified products are found in time, when it is detected that a paperboard has defects and dimensional deviation, a material taking suction cup downwards adsorbs the paperboard and then rapidly lifts the paperboard upwards, the whole screening action is rapid and timely, and the unqualified products are effectively prevented from being mixed into qualified products; after the material taking suction cup lifts the materials, the second conveyor moves to the position below the material taking suction cup to receive and take the materials, the cleaning brush cleans the material taking suction cup during resetting, dust, chippings and other loose sundries can be effectively removed, and the adsorption effect and the service life of the vacuum suction cup are guaranteed.

The invention belongs to the technical field of intelligent manufacturing, and particularly relates to a paperboard sorting and self-adaptive indentation intelligent control system based on machine vision, which comprises an indentation operation component, a sorting visual identification component, a finished product transportation line and a defective product transportation line, and further comprises a self-adaptive indentation control system, an integrated thin film pressure sensor is mounted in the indentation cutter in the indentation machine; an image acquisition and processing unit, a time-illumination association unit, an adaptive shooting adjustment unit, an optimal frame selection strategy unit, a motion control and cooperation unit, a regular verification unit and a pressure adjustment unit are arranged in the adaptive indentation control system. Visual inspection is introduced, reflection interference can be eliminated, the problem of false detection caused by reflection of the film-coated paperboard in traditional single-light-source shooting is solved, the image recognition capacity is excellent, the screening efficiency is high, technological parameter backtracking and optimization are supported, and the yield only has small deviation due to seasonal fluctuation.

The invention relates to the technical field of coal mine mechanical arms, in particular to an intelligent coal mine resource sorting mechanical arm which comprises a moving seat and a supporting arm, a rotating motor is installed at the top end of the moving seat, the supporting arm is installed at the output end of the rotating motor, and a sorting mechanism is arranged at one end of the supporting arm. And the sorting mechanism comprises a sealing barrel installed at one end of the supporting arm, an air cylinder is installed at the top end of the interior of the sealing barrel, a mounting plate A is fixed to the bottom end of the sealing barrel, and four sets of joints A are hinged to the periphery of the mounting plate A. An elastic piece drives a magnetic block A to generate intermittent slight up-down movement; the magnetic block A forms soft striking on the surface of the coal gangue, high-frequency slight vibration generated by striking can effectively shake off coal slime and fine dust attached to the surface of the coal gangue, the problem of coal resource waste caused by direct mixing treatment of the coal slime and the coal gangue in traditional operation is avoided, and the resource utilization rate of coal mine separation operation is increased.

The invention discloses a scrap aluminum classification and rapid identification method, and relates to the field of scrap aluminum classification and rapid identification, the method comprises the following steps: S1, grading pretreatment: to-be-sorted scrap aluminum is conveyed into a three-layer vibrating screen machine through a conveying belt for grading screening, and different sizes of scrap aluminum are sorted out; and S2, impurity separation is conducted, specifically, the classified scrap aluminum is conveyed into a drum-type magnetic separator, magnetic impurities are removed, then the scrap aluminum subjected to magnetic separation is conveyed to an airflow separator, light non-metal impurities are separated, then the scrap aluminum is conveyed to an objective table through a conveying belt, full-process automatic treatment is conducted, manual dependence is reduced, the production efficiency is improved, and the production cost is reduced. A single production line can reduce the workload of sorting workers; and compared with manual sorting, due to the fact that classification is accurate, the rejection rate of the regenerated aluminum alloy can be effectively reduced, and economic benefits are remarkably improved.

The invention provides a system device for intelligently sorting coal gangue. The system device comprises a feeding unit, a machine vision recognition unit, a main control unit and a sorting execution unit which are connected in sequence, the feeding unit comprises a vibrating feeder and a refining and shaping mechanism; the machine vision identification unit comprises a high-speed industrial camera and a near infrared spectrum camera; a coal gangue recognition model based on deep learning is arranged in the main control unit; the sorting execution unit comprises a plurality of high-pressure electromagnetic air valve nozzles which are evenly distributed in the transverse direction of the conveying belt. The vibration feeding mechanism and the material uniformizing and shaping mechanism are combined, so that single-layer uniform distribution of materials is ensured, and overlapping and shielding of the materials are effectively avoided; machine vision and near infrared spectrum multi-modal information fusion is adopted, and a deep learning algorithm is combined, so that the accuracy and adaptability of coal gangue recognition are remarkably improved; and through the time delay compensation and accurate positioning technology, it is ensured that the sorting execution mechanism accurately hits the target, and the sorting efficiency is improved.

The invention discloses an automobile audio inductor assembling machine which comprises a first machining conveying line used for conveying a dispensing jig, and a first material planting mechanical arm, a dispensing machine and a CCD visual camera are sequentially arranged above the first machining conveying line from the starting end to the terminal end; the second machining conveying line is located on one side of the first machining conveying line, and a second material planting mechanical arm used for planting a second assembly is arranged above the second machining conveying line; the jig transferring manipulator is used for transferring the dispensing jig from the terminal end of the first processing conveying line to the starting end of the second processing conveying line; and the press-fit rail is in butt joint with the tail end of the second machining conveying line, a baking jig is received on the press-fit rail, a press-fit channel is formed in the middle of the baking jig, and a separation assembly is arranged at the initial end of the press-fit rail and used for opening or closing the press-fit channel. According to the invention, the assembling efficiency, the dispensing efficiency and the baking jig filling efficiency of the two components of the automobile audio inductor are improved.

The invention relates to the technical field of freshwater fish culture, in particular to a freshwater fish intelligent detection and grading system based on machine vision, which comprises an image acquisition unit, an image processing unit, an image analysis unit, a grading decision unit and a control and output unit, after the image processing unit extracts a target area, the image analysis unit completes three-dimensional contour reconstruction morphological parameter calculation activity stress evaluation and body surface defect detection; the grading decision-making unit achieves specification and quality two-dimensional grading according to the multi-dimensional features, and the control and output unit drives the execution mechanism to complete sorting and generate a report. Multi-dimensional automatic detection and precise grading of the size, vitality and health condition of the freshwater fish are achieved, full-process automation of freshwater fish grading is achieved, the grading precision and efficiency are improved, the labor cost is reduced, and the method is suitable for large-scale freshwater fish breeding and processing scenes.

The invention provides a bottle sorting and data monitoring method and system and bottle recycling equipment. The method comprises the following steps: collecting a visible light image and near infrared spectrum data of a bottle target, and preprocessing the collected visible light image and near infrared spectrum data; extracting a fusion spectrum feature vector of the pre-processed visible light image and the near infrared spectrum data, and generating a feature matrix for material classification; inputting the feature matrix into a lightweight convolutional neural network model deployed in an edge calculation unit, and obtaining a recognition result of the material and form of the bottle; a sorting control instruction is generated based on the recognition result, and motion space state representation is constructed in combination with current state information of the mechanical arm; and inputting the spatial state representation into a path optimization model based on deep reinforcement learning, and outputting and executing an optimal sorting path and a coordination action sequence. According to the method, the precision and robustness of bottle identification can be improved, the recycling efficiency of renewable resources can be improved, and the recycling cost can be reduced.

According to the library book sorting device and the control method thereof, when books are taken out, the tops of the books are pulled out to be inclined through a book pulling device, then the books are clamped from the two sides through a book clamping device to be completely taken out, and when the books are pulled out, a control system controls the cut-off position of a cut-off distribution device on a magnetorheological fluid storage sleeve according to the thickness of the books; the flow of the magnetorheological fluid entering the book raking sleeve is adjusted, then the size of the book raking sleeve and the contact area of the book raking sleeve and the book are adjusted, meanwhile, the electrifying strength of the electromagnet is controlled, then the hardness of the magnetorheological fluid in the book raking sleeve is adjusted till the book raking sleeve can be completely attached to the book, and the book raking sleeve can be suitable for raking the thick and heavy book and can also be used for raking the book. And no extrusion stress is generated on the books, so that the books are prevented from being extruded, deformed or scratched and abraded, and nondestructive book taking and sorting are realized.

The invention relates to the technical field of echelon utilization of decommissioned lithium ion batteries, in particular to a decommissioned power lithium battery sorting method and system based on DBSCAN and WOA-FCM. The method comprises the steps that static characteristics of decommissioned power lithium batteries are determined; based on the static characteristics, first-stage sorting is carried out on the retired power lithium batteries through a density-based noise application space clustering algorithm, so that abnormal batteries are eliminated, and the clustering number of normal batteries is determined; and for the remaining normal batteries after the abnormal batteries are removed, dynamic characteristics are extracted based on a battery discharge voltage curve, second-stage sorting is carried out through a whale optimization-based fuzzy C-means clustering algorithm, and a battery sorting result is obtained. Therefore, through two-stage collaborative optimization, the sorting accuracy and efficiency are improved, and the high consistency of the recombined battery packs is ensured.

The application discloses a kind of full automatic waste fabric identification sorting control system, it is related to resource reusing technical field, including identification analysis module, the type, color, component and fibre fineness data of waste fabric on the surface of automatic conveying module are acquired and analyzed by identification analysis module, obtain the component composition and its weight distribution of each area of waste fabric, generate data form and send to data module, and sorting action module is controlled by sorting strategy control module to carry out sorting screening;Using machine vision technology and fabric visual identification model determines the type of waste fabric and divides its area, so that different parts of fabric can be detected and identified, improve the component identification precision of fabric;By extracting the color value of different areas and correcting the color value of spectral data in the identification analysis module, the influence of the color on the surface of the fabric on light, especially visible light, is eliminated, making the spectral data closer to the truth, and the analysis result is more accurate.

The invention discloses a tomato raw material loading, unloading and sorting method and system fused with AI visual recognition, and relates to the technical field of AI vision. A tomato raw material loading, unloading and sorting method fused with AI visual identification comprises the following steps that multiple frames of images are collected, qualified images are reserved through quality detection, the qualified frames are subjected to pixel-level segmentation, tomato segmentation masks are generated through multi-frame fusion, and blind areas are complemented; based on the complemented segmentation mask, high residual target points are judged, space attributes are extracted, the optimal moving path and action queue of the crane pipe are obtained, and a dynamic complementing and scanning queue is inserted to be issued and executed; and in the execution process, residual changes are monitored, the flushing effect is judged, dynamic recognition, complementary scanning and queue updating are conducted, parameters are adjusted, and sorting is conducted till discharging is completed. Accurate recognition, efficient path planning and dynamic supplementary scanning in the tomato loading, unloading and sorting process are achieved, and then the problems that in the prior art, due to insufficient recognition precision, path planning is unreasonable, and residual areas are missed in scanning are effectively solved.