13 results about "Plastic object" patented technology

The invention relates to the technical field of plastic material preparation, and discloses a modified bamboo fiber, a PBAT composite material and a plastic object. The modified bamboo fiber comprises bamboo fiber subjected to hot pressing treatment in water and a closed aziridine cross-linking agent loaded on the bamboo fiber, and the mass ratio of the bamboo fiber subjected to hot pressing treatment in water to the closed aziridine cross-linking agent is 100: (1-10). The PBAT composite material comprises the following components in parts by weight: PBAT and modified bamboo fibers, and the mass ratio of the PBAT to the modified bamboo fibers is 100: (20-40). The modified bamboo fiber is subjected to hot pressing treatment in water, so that the generation of volatile gas caused by high-temperature processing can be avoided when the modified bamboo fiber is applied to the plastic material, and the interface interaction with the plastic material can be improved; the closed aziridine cross-linking agent can release active groups at high temperature, and can react with active functional groups such as hydroxyl and carboxyl on the surfaces of the bamboo fibers and the surfaces of the plastic materials, so that the interface interaction between the bamboo fibers and the plastic matrix is improved, and the tensile strength of the composite material is improved.

According to some embodiments of the present disclosure, there is provided a device comprising processing circuitry configured to receive a polarized image of an object at least partially made of polarized material, detect a contour of the object from the polarized image, calculate a probability that the contour of the object is a stored contour, and output a control signal indicating a match based on the calculated probability being above a threshold. In some embodiments, the present disclosure enables sorting or segregating plastic objects for manufacturing, recycling, reuse, or repurposing.

The application discloses a kind of based on the waste plastic detection method of improvement M2Det, the described method includes: through camera real-time sampling and the way of web crawler, collection multiple waste plastic data;Original picture is randomly divided into training set, verification set and test set;Through data enhancement method expansion existing data set and obtain a large amount of data;Using improved M2Det algorithm establishes the identification model of waste plastic;Using deformable convolution instead of ordinary convolution, using ResNeXt-101 as main network instead of ResNet-101 to improve feature extraction capability, establish final detection model;Based on the detection model trained, through camera shooting picture obtains final detection result.The application effectively solves the problem that waste plastic sorting background is complex and the problem that different plastic shape is greatly different, improves the identification precision of detecting multiple common waste plastic objects, and is helpful to practical production application.

The application belongs to the technical field of sludge dewatering treatment, and discloses a sludge dewatering treatment device, which comprises a machine body, a feeding hopper is fixedly connected to one side of the top end of the machine body in a penetrating mode, a starting driving assembly drives a square groove wheel to rotate, two groups of symmetrical L-shaped tool holders installed on the square groove wheel can cut some plastic objects and solid sludge contained in the sludge when the square groove wheel is in contact with the slide plate rod, the U-shaped frame plate and the plurality of conical rod rods can be driven to rotate synchronously, and are used for beating and stirring the sludge, the convex disc is driven to rotate, the filter screen plate one is driven to rotate in a multi-directional lifting mode, secondary separation is performed, the water body after separation enters the water pipe, the water rotating plate in contact with the water body can purify the water by activated carbon, the screw rod in rotation drives the abutting plate to abut and press one end of the filter screen plate one, so that the filter screen plate one presents an inclined state in the machine body, the clamped plug on the machine body is manually opened, and the sludge can be discharged.

Methods and systems for using multiple hyperspectral cameras sensitive to different wavelengths to predict characteristics of objects for further processing, including recycling, are described. The multiple hyperspectral images can be used to predict higher resolution spectra by using a trained machine learning model. The higher resolution spectra may be more easily analyzed to sort plastics into a recyclability category. The hyperspectral images may also be used to identify and analyze dark or black plastics, which are challenging for SWIR, MWIR, and other wavelengths. The machine learning model may also predict the base polymers and contaminants of plastic objects for recycling. The hyperspectral images may be used to predict recyclability and other characteristics using a trained machine learning model.

This invention discloses a two-stage stepped crusher for waste plastics, including a frame, a crushing section and a shearing section mounted on the frame; a guide member is provided inside the frame, with the feed end of the guide member connecting to the discharge end of the crushing section and the discharge end of the guide member connecting to the feed end of the shearing section; a conveying mechanism is provided inside the guide member, and the conveying mechanism includes a conveying component located at the feed end of the shearing section, with a guide strip at one end of the conveying component for diverting materials; the guide strip fixed to one end of the conveying component divides the guide plate into multiple sets of groove structures, and the separated grooves facilitate the orientation of plastic objects to the conveying component; and a combing component movably connected inside the guide strip achieves reciprocating motion through a drive unit, causing the combing component to change the direction of long strips of plastic objects placed horizontally on the guide strip. This device achieves a combination of conveying, guiding and combing, which not only ensures the smooth feeding and conveying efficiency of various plastic materials, but also avoids the horizontal accumulation of long strips of plastic objects and prevents blockage.

An apparatus and method for cooling molded plastic objects, in particular caps for closing containers, are described, in which a perforated tubular body receives the objects to be cooled within it, a rotating helix body arranged in the tubular body transports the objects to an outlet of the tubular body from which the objects are transferred into a second perforated tubular body surrounding the tubular body, the objects are then transported along the second tubular body by a rotation of a second helix body, and in which the objects are cooled by ventilation passing through the holes in the tubular body and the second tubular body.

A method of training a machine learning model for performing plastic type classification is provided. The method includes: pre-training the machine learning model based on unlabeled spectral data of plastic samples using self-supervised learning with spectra masking to obtain a pre-trained machine learning model; and fine-tuning the pre-trained machine learning model based on labeled spectral data of plastic samples for performing plastic type classification. There is also provided a corresponding system for training a machine learning model for performing plastic type classification. A method of classifying a plastic type of a plastic object is also provided. The method includes: obtaining spectral data of the plastic object; and classifying the plastic type of the plastic object based on the spectral data of the plastic object using a machine learning model trained according to the above-mentioned method of training a machine learning model for performing plastic type classification. There is also provided a corresponding system for classifying a plastic type of a plastic object.

The utility model discloses a crushing device for recycling renewable resources, which comprises a crushing separator body and a feeding box arranged at the top end of the crushing separator body, and further comprises a material pressing mechanism, the material pressing mechanism comprises a side mounting plate, an L-shaped bracket, a U-shaped supporting plate, an electric push rod, a flange ring, a bottom connecting disc, a connecting disc, a vertical connecting pipe, a pressing plate, a T-shaped fixed strip and a rubber cushion plate, the material pressing mechanism is arranged outside a case of the crusher separator body, and the material pressing mechanism can drive the pressing plate to perform lifting operation above a feeding box of the crusher separator body through the electric push rod; the pressing plate can press renewable resources into the space between the crushing rollers of the crushing separator body for smooth crushing, and the design of the pressing mechanism facilitates smooth entering of some round plastic bottles or smooth plastic objects in the renewable resources into the space between the crushing rollers for smooth crushing, so that the crushing efficiency and the crushing quality of the renewable resources are improved.

A method for producing a tool including a sheet, the method including the steps of: providing a first cellulose sheet; attaching first and second plastic layers each to one side of the first cellulose sheet; upon the attaching, placing a first side of a plastic object on the first plastic layer; pressing a metal object on a portion of a second side of the plastic object; vibrating the metal object parallel to the first plastic layer together with the pressing thereon; and ceasing the vibrating, thereby ceasing the heating.

A contact lens may include a lens body, which includes an anterior surface, a posterior surface opposite the anterior surface, a bulk hydrogel material, and thin plastic objects partially embedded in the bulk hydrogel. Each thin plastic object is made of a crosslinked polymeric material different from the bulk hydrogel material and has a thickness of between about 0.5 micron and about 30 microns and a width or length of greater than about 2.0 mm. Each thin plastic object includes an exposed surface and a buried surface directly in contact with the bulk hydrogel material. The exposed surface merges with the anterior surface or the posterior surface and has a curvature substantially identical to the curvature of the anterior surface or the posterior surface.

The application discloses a plastic material identification method and device, equipment and a readable storage medium, and relates to the technical field of artificial intelligence. The method comprises the following steps: obtaining an original hyperspectral image of a plastic object to be identified, and performing black and white correction on the original hyperspectral image to obtain a reflectivity image; extracting a gray-scale image, a false color image and reflectivity data of a target region from the reflectivity image; then performing segmentation and selection processing on the original hyperspectral image based on the gray-scale image, the false color image and the reflectivity data of the target region to obtain target data; and finally inputting the target data into a hyperspectral classification model to obtain a material identification result of the plastic object to be identified. The method avoids the damage to the plastic, reduces the cost of plastic material identification, and increases the accuracy of plastic material identification.