790 results about "Waste sorting" patented technology

The invention relates to the technical field of environment intelligent management, and discloses a multi-community-oriented AI intelligent household garbage control processing system which comprises a multi-mode sensing module, a data processing and edge calculation module, a garbage quantity prediction and scheduling optimization module, an intelligent decision and multi-source data fusion module and a self-adaptive adjustment and feedback mechanism module. The multi-community-oriented AI intelligent household garbage control processing method comprises the following steps that S1, a multi-modal sensing module collects garbage data; s2, an edge calculation module performs preprocessing, classification and encrypted transmission; s3, optimizing transportation and scheduling; s4, generating an optimal processing decision; and S5, adaptively adjusting the strategy. Through the technical scheme of combining multi-modal perception and edge calculation, accurate garbage data acquisition and efficient processing in a multi-community environment are realized, the technical effects of reducing data transmission burden and improving garbage classification data quality are achieved, and garbage classification is more accurate and reliable.

The invention relates to a composite material garbage sorting method based on a hyper-spectrum technology and an AI classification model. The method comprises the following steps that S1, multi-modal data collection is conducted; s2, the collected multi-modal data are preprocessed and fused, and combined features of the multi-modal data are obtained; s3, constructing a classification model based on the multi-modal neural network model, and performing classification according to the joint features; s4, based on a classification result, using a SegFormer deep segmentation network to identify junk components at a pixel level, and realizing accurate segmentation of a plurality of material composition objects; s5, target tracking of the garbage trajectory is kept through a target tracking algorithm; and S6, on the basis of the target tracking result in the S5, the position of the garbage on the conveying belt is predicted in real time, and the sorting action is precisely executed according to the classification and segmentation result. According to the invention, the complex composite material garbage can be efficiently and accurately treated.

The invention provides a super-network personalized federal learning method for garbage classification. According to the method, the precision of the model is improved. The method comprises the following steps: firstly, initializing a shared layer parameter, a personalized layer parameter of each client and a super network initialization parameter, issuing the shared layer parameter to each client, then training a personalized layer on local data by each client, updating the personalized layer parameter, sending the shared layer parameter to a server by each client, and sending the shared layer parameter to the server by each client. And the server performs weighted aggregation through the weight generated by the super network, updates a shared layer parameter, optimizes the super network and updates a weight generation strategy for next aggregation. According to the method, the aggregation weight of the client sharing layer is dynamically generated by introducing the super network, and the limitation of a simple average aggregation mode is overcome.

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.

The invention discloses an intelligent garbage sorting system and method based on mechanical arm visual grabbing, the system comprises an upper computer, a depth camera and a mechanical arm, and a visual perception module, a target recognition module, a grabbing prediction module and a planning control module are integrated in the upper computer; the visual perception module is used for controlling the depth camera to obtain junk RGB-D information in a scene; the target recognition module receives the RGB information, performs garbage recognition by adopting a multi-target detection recognition algorithm, recognizes garbage types and position information in a scene, and obtains a local depth image according to the garbage position information and depth information; the grabbing prediction module is used for carrying out grabbing pose prediction by adopting a grabbing pose prediction algorithm according to the local depth image to obtain an optimal grabbing pose; the planning control module completes coordinate transformation according to the optimal grabbing posture and controls the mechanical arm to execute grabbing and sorting tasks according to the grabbing posture after coordinate transformation and the garbage category; the accuracy and efficiency of garbage classification are improved.

The invention provides an intelligent garbage classification box management and control method, which comprises the steps of performing logic verification on a cleaning data set and garbage box layout reference information, and if data contradiction is detected, triggering a rule base correction mechanism to generate an integrated data set; performing redundant field deletion operation on the integrated data set, and fusing meteorological time sequence data and dustbin distribution data to generate a structured feature set; performing time sequence analysis on the structured feature set, and if it is detected that a meteorological feature value exceeds a preset threshold value, marking the structured feature set as a high-influence time period, and generating a marked feature set; inputting the labeled feature set into a random forest model, and predicting the saturation distribution of the garbage cans in each region in combination with historical clearance records; and calling a scheduling optimization model according to the saturation distribution, and if a high-saturation region is detected, dynamically generating a clearance path parameter, and outputting a final scheduling scheme.

The invention relates to the technical field of garbage treatment, in particular to a smart city-oriented garbage classification and recognition system, which comprises an image acquisition and restoration module, a multi-modal feature fusion module, a dynamic classification decision module and a classification result output module, wherein the image acquisition and restoration module is used for acquiring and restoring an image of a garbage throwing point and outputting a restored three-dimensional image; the multi-modal feature fusion module is used for fusing the extracted features into multi-modal fusion features through a space-time alignment algorithm; the dynamic classification decision module is used for classifying the parallel double-branch convolutional neural network integrated with the attention mechanism; and the classification result output module is used for triggering a control signal of the garbage recycling equipment. According to the intelligent urban garbage classification system, through collaborative design of multi-modal feature fusion and a parallel classification structure, accurate recognition of garbage materials and purposes in a complex environment is achieved, the recycling equipment can be automatically linked, and the overall intelligent level of the intelligent urban garbage classification system is improved.

The invention relates to the technical field of household garbage treatment, in particular to a rural household garbage classification and resourceful treatment circulation system, which comprises straw, harmful garbage, recyclable garbage, kitchen garbage, large household garbage and sludge; the rural household garbage treatment system comprises a household garbage classification system, a household garbage pyrolysis treatment system, a household garbage recycling treatment system, a harmful garbage recycling treatment system, a kitchen garbage recycling treatment system, a large household garbage classification recycling treatment system and a sludge recycling treatment system. By means of a centralized treatment mode of the rural domestic garbage, the problem that landfill of the rural domestic garbage is difficult is solved, corresponding economic value is brought to the rural area, the idea of waste utilization, circular economy, energy conservation and emission reduction is achieved, the rural environment is better, and the economic benefit of the rural area is improved. And a solid foundation is laid for creating a high-quality living environment in rural areas.

The invention belongs to the technical field of garbage classification, and particularly relates to an intelligent household garbage classification device. When garbage is thrown, the garbage firstly passes through a first sensing assembly, the first sensing assembly senses the quantity of the thrown garbage and transmits information to a control mechanism, and the control mechanism controls a garbage sorting and conveying mechanism according to the quantity of the garbage; garbage falls on the garbage throwing mechanism in sequence, the garbage on the garbage throwing mechanism is shot through the image recognition mechanism, data are transmitted to the control mechanism, the control mechanism judges the garbage type, then the garbage throwing mechanism is controlled to throw the garbage into the garbage receiving mechanism of the corresponding type, and garbage classification work is completed. According to the garbage sorting and conveying device, garbage can be classified, meanwhile, through the arrangement of the garbage sorting and conveying mechanism, the device can treat various kinds of garbage at a time, and the device is more suitable for practical application.

The invention relates to a fusion detection method for heterogeneous sensors of an intelligent gangue selection robot in a limited space, and belongs to the field of fusion of technical heterogeneous sensors. VOC time sequence signals of a bionic electronic nose array, laser radar cloud data and pose information of an inertial measurement unit are synchronously collected, and the VOC time sequence signals are denoised through a generative adversarial network model; voxel filtering and outlier elimination are carried out on the laser radar cloud data; the VOC concentration gradient is predicted based on CFD simulation, a three-dimensional environment map is constructed in combination with laser radar cloud data and inertial measurement unit poses, and a smell concentration thermodynamic diagram is marked; and extracting robust odor fingerprints from the denoised VOC time sequence signals, aligning feature distribution of different mining areas, and updating the classification model. According to the scheme, the gangue selection robot is guided to preferentially explore a hidden area with low VOC concentration and high CO2 accumulation through the odor concentration gradient, and the detection capacity of non-dominant gangue piles is remarkably improved.

The utility model discloses a solid-liquid separation device for garbage classification, which relates to the technical field of garbage classification and comprises a water storage tank, a separation tank is rotatably arranged in the water storage tank, a filter screen is fixedly connected to the bottom of the separation tank, connecting rods are fixedly connected to two sides of the separation tank, electric push rods are hinged to outer walls of two sides of the water storage tank, and the electric push rods are fixedly connected to the bottom of the separation tank. The output ends of the two electric push rods are hinged to the outer walls of the two connecting rods correspondingly, sliding rods are fixedly connected to the upper ends of plate bodies on the two sides of the separation box correspondingly, and the mounting shafts, the connecting rods, the electric push rods, the sliding rods, sliding blocks, pulleys, connecting frames, positioning columns, protection plates, adjusting screw rods, mounting plates and brush structures are arranged; the effect of automatically cleaning the filter screen is achieved, the problems that a filter screen in an existing solid-liquid separation device for garbage classification needs to be manually detached to be cleaned, cleaning is troublesome and not convenient enough are solved, and the solid-liquid separation device for garbage classification has practicability.

The invention relates to the technical field of garbage classified transportation, and provides an intelligent garbage classified transportation control method and system, and the method comprises the steps: obtaining a coordinate region semantic tag; based on a YOLOV5 neural network model, carrying out classification identification on the junk image, and obtaining a confidence coefficient vector of a classification result; collecting the weight of garbage in the garbage can at a preset frequency, and constructing weight time sequence data; material information of garbage in the garbage can is obtained, and garbage material characteristics are obtained; obtaining multi-dimensional feature fusion information; and performing block chain chaining on the multi-dimensional feature fusion information to obtain a block chain traceability code. According to the method, the comprehensive index for tracing can be obtained, so that quick retrieval during tracing is facilitated, and the overall tracing capability of garbage classified transportation can be enhanced; the problem that in the prior art, due to the fact that garbage can positioning information, garbage materials and other multi-dimensional information are not fused, the garbage classification transportation tracking and tracing overall capacity needs to be further enhanced is solved.

The invention provides a building solid waste self-adaptive sorting method and system based on multi-modal vector retrieval. The method comprises the steps that original data of building solid waste are collected; extracting multiple data features from the original data; fusing the plurality of data features to obtain a fused feature vector; performing similarity matching on the fused feature vector database in a vector retrieval mode, and confirming solid waste material classification and a corresponding sorting decision instruction; and based on the sorting decision instruction, building solid waste sorting is executed. The problems that a traditional sorting technology is low in precision and poor in adaptability are solved. The system can be widely applied to the fields of construction waste recovery, resourceful treatment and the like, and has remarkable economic and environmental benefits.

The invention provides an intelligent garbage classification robot system and method based on multi-modal sensing, and the system comprises a multi-modal sensing subsystem which is used for detecting the garbage form in real time, judging the material rigidity in real time, and carrying out the component recognition; the sorting execution module is used for sorting the garbage in real time according to the recognition result of the multi-mode sensing subsystem; and the rebate control module is used for calculating a rebate amount and carrying out fee payment. According to the technical scheme, the sorting efficiency and sorting quality of garbage classification are improved.

The invention discloses an urban garbage classified collection and scheduling method based on the Internet of Things, and relates to the technical field of urban garbage classified collection, and the method comprises the steps: deploying an intelligent garbage can with the filling rate and environmental parameter perception capability in each region of a city, and uploading the collected state data to an edge gateway of the region through a low-power wide area network; the edge gateway performs localized priority evaluation based on the received real-time state data of each intelligent garbage can in combination with the capacity information, the last clearance time and the attribute of the area where the intelligent garbage can is located, and generates a dynamic priority score of each garbage can; when the dynamic priority score of any dustbin exceeds a preset response threshold value, the edge gateway triggers an event reporting mechanism and sends a clearance alarm containing position and priority information to a regional dispatching center; and on the basis of receiving the clearance alarm, the regional dispatching center combines weather forecast, festival calendar and regional people flow density data to carry out trend prediction on the garbage cans which are not alarmed yet and have high filling risks.

The invention provides a garbage collection classification management method and system driven by a mobile internet. The garbage collection classification management method comprises the steps that an internet terminal dynamically adjusts garbage classification rules according to received environment data; the internet terminal determines a garbage classification result according to the received garbage data and environmental data in combination with the dynamically adjusted garbage classification rule, and sends the garbage classification result to the user mobile device for display; each type of garbage throwing is monitored and recorded; the internet terminal controls the clearing and transporting vehicle to clear and transport garbage according to the priority of the garbage in the intelligent garbage can, and carries out self-adaptive planning of a clearing and transporting path of the clearing and transporting vehicle according to the comprehensive condition of the priority of the garbage in the clearing and transporting vehicle; and the internet terminal controls the cleaning and transporting vehicle to transport the garbage to the garbage station according to the planned path. The system comprises modules corresponding to the steps of the method.

The invention relates to a garbage sorting identification method and device based on multi-feature fusion, and the method comprises the steps: carrying out the multi-dimensional feature extraction of an obtained garbage image, and obtaining a color feature, a texture feature and a shape feature; performing normalization processing on the color features, the texture features and the shape features; obtaining a color weight coefficient, a texture weight coefficient and a shape weight coefficient by adopting an attention mechanism based on the normalized color features, texture features and shape features; fusing the color features, the texture features and the shape features by adopting a feature pyramid to obtain fused features; carrying out dimension reduction enhancement processing on the fusion features; and garbage sorting identification is carried out based on the fusion features after dimension reduction enhancement processing. According to the method, the problem of feature judgment in a complex environment can be solved, the capacity of distinguishing garbage with similar appearances is remarkably improved, and the requirement of modern garbage sorting for high-precision recognition can be met.

The invention discloses a medical garbage classifying and crushing device, and relates to the technical field of garbage classifying and crushing, the medical garbage classifying and crushing device comprises a crushing and classifying auxiliary mechanism arranged in a protective cover, the crushing and classifying auxiliary mechanism is arranged, a movable puncture needle and a needle plate pair are arranged in a crushing roller, and the crushing roller is driven to move through a connecting rod; crushed glass bottle bodies, rubber plugs and aluminum caps are punctured through movable puncture of the puncture needle, the puncture needle cannot puncture the glass due to the characteristics of the glass, so that only the crushed rubber plugs and aluminum caps can be punctured, the rubber plugs and the aluminum caps are punctured on the puncture needle, follow-up classification is facilitated, and when penicillin bottles are not separated in advance, the penicillin bottles can be conveniently separated in advance. And integrated crushing is completed, classification in advance is not needed, so that the whole penicillin bottles are classified while being crushed, and the overall crushing and classification efficiency and effect are greatly improved.

The invention relates to the field of garbage classification, and discloses an intelligent identifying and sorting system for multi-target medical garbage classification, which is used for solving the problems of target shielding and missing classification during medical garbage classification, and comprises the following steps: acquiring stacked garbage weight information and stacked garbage images; the vibration frequency is adjusted according to the weight information of the stacked garbage and the stacked garbage images, the actual vibration frequency is obtained, the garbage on the conveying belt is dispersed according to the actual vibration frequency, the garbage recognition area is divided into isometric sub-recognition areas, the recognition garbage image of each sub-recognition area is obtained, and the recognition garbage image of each sub-recognition area is obtained; the method comprises the following steps of: identifying garbage images of the medical garbage, recording each identified garbage image as marked garbage, grabbing the marked garbage through a grabbing arm, classifying the grabbed garbage, recording a garbage classification process, and carrying out visual statistics on garbage classification treatment conditions according to the garbage classification process, so that the medical garbage classification efficiency is effectively improved, and the probability of missing classification of harmful garbage is reduced.

The invention relates to the technical field of urban garbage management, and discloses a garbage recycling resource benefit dynamic evaluation method for urban large housekeepers. The method comprises the following steps: receiving real-time sensor data of a plurality of garbage collection points, determining garbage type distribution and processing priorities by using a preset garbage classification model, and dynamically generating a resource allocation strategy which comprises recycling vehicle path planning and processing equipment scheduling instructions. And predicting a garbage increment trend through a preset spatial-temporal distribution model, adjusting resource allocation strategy parameters, updating a processing priority through an iterative optimization algorithm, and outputting a resource scheduling scheme. According to the method, the condition of a recycling point can be accurately mastered in real time, accurate garbage classification and efficient resource allocation are achieved, garbage increment can be predicted, emergencies can be dealt with, garbage recycling resource benefits are effectively improved, urban garbage management work is optimized, and urban sustainable development is promoted.

The invention relates to the technical field of artificial intelligence and computer vision, in particular to a junk image recognition method and system based on multi-modal fusion, and the method comprises the steps: S01, obtaining the multi-modal data of at least two modals of to-be-recognized junk; and S02, processing the multi-modal data by adopting a dynamic confidence-attention fusion mechanism to solve the problem of information conflict or inconsistent confidence among different modal data. According to the technical scheme provided by the invention, the accuracy, robustness and adaptive capacity of an automatic garbage identification and sorting system can be remarkably improved, and the method has important theoretical value and wide application prospect for promoting effective landing of a garbage classification policy and development of an intelligent environmental protection industry.

The invention discloses an intelligent classification dustbin based on image recognition sorting, and belongs to the field of intelligent garbage classification equipment, the intelligent classification dustbin is characterized in that a garbage receiving box is arranged at the upper part in a main box body, a plurality of garbage storage boxes are arranged at the lower part in the main box body, and an outlet of the garbage receiving box is connected with each garbage storage box through a sorting mechanism; a garbage receiving opening is formed in the side surface of the garbage receiving box of the main box body; the visual identification and classification device is arranged in the main box body and can collect and receive garbage images of garbage from the garbage receiving port, perform feature extraction and classification and identification on the garbage images by using a convolutional neural network, determine garbage categories and send sorting control signals to the sorting mechanism according to the garbage categories; and the sorting mechanism can sort the received garbage into the corresponding garbage storage boxes according to the corresponding sorting control signals sent by the visual identification and classification device. According to the garbage can, the garbage classification accuracy and the operation efficiency can be improved, and garbage classification is promoted to develop towards the intelligent, green and sustainable direction.

The utility model provides an efficient solid waste utilization sorting device, which relates to the technical field of solid waste sorting equipment, and comprises support legs and a sorting box, the inner side of the sorting box is provided with a hopper, the inner wall of the sorting box is rotatably connected with two crushing rollers, the sorting box is internally provided with a conveyor belt, the outside of a magnetic roller is provided with a scraper blade, and the scraper blade is provided with a baffle plate. According to the efficient solid waste utilization sorting device, through cooperation of the crushing roller, the magnetic roller and the brush, building waste is damaged through the crushing roller, internal steel bars are exposed or disengaged from the building waste, the adsorption effect is formed on the steel bars through magnetic force of the magnetic roller, and the steel bars are separated from the building waste; the reinforcing steel bars are sucked away from the interior of the building waste, rapid sorting is achieved, the reinforcing steel bars on the magnetic roller are blocked through the scraper, the reinforcing steel bars blocked by the scraper are swept into the collecting box through rotation of the brush, the reinforcing steel bars are collected in a unified mode, and the utilization rate of the solid waste is increased.

The invention provides a cleaning and sweeping vehicle operation optimization method and system based on intelligent recognition, a medium and a product, and relates to the technical field of intelligent control. The method comprises the following steps: acquiring pavement image information by using a plurality of garbage monitors; then, using a garbage classification model subjected to deep learning training to determine garbage category information according to the road surface image; then, geometric dimension data and garbage distribution density information are obtained in combination with the road surface image information, and garbage volume information is calculated; determining weight coefficient information according to a garbage category weight model; obtaining pavement garbage equivalent information by integrating the volume, the weight coefficient and the distribution density information; and working parameters of the rolling brush assembly motor and the high-pressure water pump are adjusted according to a set strategy to optimize the operation of the cleaning and sweeping vehicle. By implementing the method, the working parameters of the rolling brush assembly motor and the high-pressure water pump can be intelligently and efficiently adjusted, so that the cleaning and sweeping vehicle operation is more targeted, and the cleaning efficiency is improved.

The invention discloses an automobile laser cutting waste classified collection and storage device, and relates to the field of laser cutting, the automobile laser cutting waste classified collection and storage device comprises a bearing frame, a bottom frame and long steel pipes, the interior of the bottom frame is fixedly connected with two sets of inclined plate frames in mirror symmetry, and the two sets of long steel pipes are fixedly connected to the middle position of the lower side of the bottom frame; a classified collection mechanism is arranged below the bottom frame and located between the two sets of long steel pipes. Waste materials are gathered through the angle plates and the protruding edges of the inclined plate frame, and it is ensured that the waste materials accurately fall into the classified collection mechanism; the first net rack blocks small metal materials, the second net rack retains chippings, and the bottom box collects cooling liquid, so that the three types of materials are thoroughly separated; the gear motor drives the crank rod and the push rod to drive the second net rack to swing, accumulation is prevented, the screening efficiency is improved, the separation effect is guaranteed, no mixed collection exists in the whole process, small metal materials can be recycled, chippings can be treated in a centralized mode, cooling liquid can be filtered and reused, resource waste is thoroughly avoided, and the energy-saving and consumption-reducing requirements of a workshop are met.

The invention discloses an intelligent classification and identification method and system for urban solid waste, and relates to the technical field of waste classification and identification. Comprising the following steps: acquiring collected historical junk pictures, and performing unified processing; performing multi-dimensional evaluation on the historical junk pictures after the unified processing, performing quantitative scoring, and screening out the pictures meeting the requirements; performing data enhancement processing on the screened pictures to obtain a historical data set; constructing a junk recognition model based on the historical data set, and training, verifying and testing the constructed junk recognition model to obtain a final junk recognition model; the technical key points are as follows: aiming at a core application scene of garbage mixing and stacking, a corresponding garbage recognition model for realizing high-precision recognition through multi-scale feature fusion and an attention mechanism is constructed, the problem that garbage recognition in a scene with a large amount of garbage and stacking cannot be realized in the prior art is effectively solved, the garbage recognition speed is high, and the recognition efficiency is high. And the requirement for real-time sorting is met, the using effect is good, and the good using prospect is achieved.

The invention relates to the technical field of resource optimization, in particular to a background garbage classification resource optimization decision-making system based on big data, and the system comprises a garbage classification recognition module; a collection demand prediction module; a dynamic collection scheduling module; and a resource optimization decision module. In the scheme, through AI visual identification and multi-modal data fusion, the fused data comprises weight, spectrum and smell sensor data. And in combination with a deep learning model, accurate recognition of garbage categories and materials is realized, and particularly, directional recognition and sorting of high-value recoverable objects are enhanced. The system solves the problem of misjudgment of similar material garbage through a dynamic threshold value judgment and secondary verification mechanism. And meanwhile, a recycling closed loop is constructed for high-value garbage, the resource recycling efficiency is remarkably improved, and environmental pollution is reduced.

The invention discloses a three-stage differential garbage classification treatment system, and relates to the technical field of energy conservation and environmental protection. A throwing opening is formed in the top of a shell, a classification mechanism is arranged in the shell, and the classification mechanism comprises a three-stage differential separation module, a throwing module and a visual recognition module; the three-stage differential separation module comprises a first conveying belt, a second conveying belt and a third conveying belt which are sequentially arranged from top to bottom, a dispersing roller is arranged below the throwing opening and is in transmission connection with the first conveying belt through a belt, a throwing module is arranged at one end of the third conveying belt, and a visual recognition module is arranged above the throwing module; more than two garbage cans are arranged at the bottom in the shell, and a compression mechanism is arranged in one garbage can. According to the three-stage differential garbage classification treatment system, the three-stage differential separation module is utilized, multiple kinds of garbage can be thrown at a time and accurately recognized and sorted, compared with manual throwing, the error rate is greatly reduced, and the recognition accuracy rate reaches up to 97.3%.

The invention relates to the technical field of garbage classification, in particular to an intelligent kitchen garbage classification system based on the Internet of Things, which comprises a node access module, an image preprocessing module, an edge structure judgment module, an oil-water proportion sensing module and a garbage type classification module. According to the method, effective binding of node states is realized through combination of node geographic identifiers and timestamps, the spatial traceability precision of garbage throwing behaviors is improved, the physical identification accuracy of garbage components in the image is enhanced through linkage of image gray difference extraction and spectral reflectivity calculation, direction features are constructed through gradient amplitudes of edge regions, and the spatial traceability precision of the garbage throwing behaviors is improved. The target stability of edge features in the image is enhanced by combining a texture consistency screening mechanism of a continuous region, and spectrum inversion processing of oil and water distribution in the image is completed through grease feature peak matching and moisture index threshold extraction; and the imaging recognition capability of typical components of the kitchen waste is improved, and the reliability of kitchen waste image recognition and the automation level of the classification process are enhanced.

The utility model relates to the technical field of slag waste sorting, and discloses a slag waste sorting device which comprises a sorting box, a first vibration assembly is arranged between the two sides of the inner wall of the sorting box, and a first screening plate and a second screening plate are sequentially arranged on the first vibration assembly from top to bottom. And two mounting frames are fixedly connected between the two sides of the inner wall of the sorting box. According to the slag waste screening device, the first vibration assembly, the first screening plate, the second screening plate, the beating rod, the pushing plate, the first pushing assembly, the motor, the second vibration assembly, the third screening plate, the fourth screening plate, the second pushing assembly, the guide frame and other structures are used in cooperation, slag waste can be screened for multiple times, and therefore the situation that slag waste screening is not thorough enough is reduced; and the screening effect of the slag waste is improved, the situation that the slag waste needs to be screened subsequently is avoided, the labor amount of personnel is effectively reduced, and the subsequent processing efficiency of the slag waste is further improved.