Patents
Literature
Patsnap Eureka AI that helps you search prior art, draft patents, and assess FTO risks, powered by patent and scientific literature data.

3results about How to "Fast fitting" patented technology

Method for acquiring thickness and refractive index of film, test system, storage medium and application

ActiveCN121954923Aavoid discontinuitiesAvoid thermal driftPhase-affecting property measurementsUsing optical meansFrequency mixerRefractive index
The invention discloses a method for obtaining the thickness and refractive index of a film, a test system, a storage medium and application. The method for obtaining the thickness and the refractive index of the thin film comprises the following steps: obtaining an intermediate frequency signal carrying transmission phase information by using two groups of nonlinear transmission line terahertz frequency comb generators and a broadband mixer, and obtaining an actually measured phase curve based on the intermediate frequency signal; constructing an equivalent multi-optical-path interference model of the thin film, performing coherent superposition on multiple reflection components of a measured wave signal in the thin film in a complex field to obtain a complex phase of a total transmission field, and obtaining a phase-frequency change spectrum based on the complex phase as a model phase curve; and an error function of the model phase curve and the actually measured phase curve is constructed, and a parameter combination enabling the error function to take the minimum value is solved by scanning the parameter combination of the refractive index n and the thickness d of the thin film. According to the method, thermal drift or time drift of the phase is avoided, and then calculation errors caused by phase jump are avoided.
Owner:SUZHOU INST OF NANO TECH & NANO BIONICS CHINESE ACEDEMY OF SCI

A method for preparing a long-lasting stain-resistant fabric

This invention discloses a method for preparing a long-lasting stain-resistant fabric, relating to the field of fabric technology. The long-lasting stain-resistant fabric prepared by this invention comprises, from the inside out, Lycra fabric, foamed rubber, and a stain-resistant film. The stain-resistant film is prepared by reacting hyperbranched polyglycidyl ether with modified cyclodextrin. The modified cyclodextrin is obtained by grafting a hydroxylamine polymer onto mercapto-carboxymethyl-cyclodextrin, which enhances stability and introduces a large number of hydroxyl groups, enhancing hydrophilicity and giving the fabric stain resistance. It also increases the density of the stain-resistant film, thereby enhancing the fabric's tear resistance. The foamed rubber is prepared by vulcanizing and foaming a blend of chloroprene rubber, polyurethane rubber, and fluorinated polyether nitrile. The addition of polyurethane rubber accelerates the vulcanization speed and improves the tear resistance of the foamed rubber. It also tightly bonds the Lycra fabric, foamed rubber, and stain-resistant film, enhancing the fabric's peel strength and extending its service life.
Owner:史秀龙

Methods for Improving YOLOv8 Networks and Their Application in Strip Surface Defect Detection

ActiveCN118365599Bachieve learningaccurate captureImage enhancementImage analysisDeformation modelingData set
This invention relates to the field of defect detection technology, specifically to a method for improving the YOLOv8 network and its application in strip steel surface defect detection. Based on YOLOv8, this invention first proposes an improved coordinate attention mechanism, the three-channel coordinate attention mechanism TCCA. Addressing the overly simplistic offset mask generation method in DCNv2, which leads to insufficient deformation modeling capabilities, this invention proposes deeply embedding TCCA into DCNv2. Furthermore, this invention introduces a global attention mechanism to improve the model's ability to extract global features. The invention also introduces a BiFPN structure and dynamic serpentine convolution to enhance the model's multi-scale feature fusion capabilities. MDPioU replaces the original loss function of YOLOv8, solving the problem of loss of effectiveness due to identical aspect ratios in predicted bounding boxes, while increasing convergence speed and localization ability. Extensive comparative and ablation experiments on the NEU-DET dataset demonstrate that the improved algorithm of this invention achieves higher defect detection accuracy and faster speed.
Owner:CHINA UNIV OF MINING & TECH