7 results about "Plastic object" patented technology

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.

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.

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.