8results about How to "Accurate quality" patented technology

The invention provides a method and a device for evaluating the grade of a butter crab based on spectral information, and relates to the technical field of engineering optics. The method comprises the following steps of: performing spectral measurement on the butter crab to be evaluated by using a spectrograph to obtain spectral data, extracting characteristic parameters from the data, and then calculating the similarity to obtain the grade of the butter crab; and selecting the quality grade corresponding to the maximum similarity value as the initial quality grade of the butter crabs to be evaluated, wherein the grades comprise top-grade products, special-grade products, first-grade products and unqualified products. And further combining the characteristic parameters, calculating the yellow-blue value and the light transmission ratio area of the to-be-evaluated butter crab, and meanwhile, considering the fatness and ovary index to form a comprehensive evaluation index. And finally, comparing the evaluation index with a preset quality interval, correcting the to-be-determined quality grade according to a comparison result, and finally determining the actual quality grade of the to-be-evaluated butter crab. According to the method, comprehensive evaluation of the quality of the butter crabs is realized through a spectral measurement technology and a characteristic parameter extraction method.

The invention discloses a gas phase fingerprint spectrum of a transverse meridian mat. The gas phase fingerprint spectrum comprises a peak 1-5, and the retention time of the peak 1-5 is 16.89 + / -0.1 min, 17.36 + / -0.1 min, 17.89 + / -0.1 min, 19.37 + / -0.1 min and 19.6 + / -0.1 min in sequence; the construction method of the gas-phase fingerprint of the membranaceous beautyberry root comprises the following steps: crushing membranaceous beautyberry root to obtain membranaceous beautyberry root powder, adding water into the membranaceous beautyberry root powder, adding ethyl acetate, slightly boiling for 4 hours, naturally cooling to room temperature, standing for layering, and collecting an ethyl acetate layer as a test solution; carrying out liquid chromatography detection on the test solution; the method comprises the following steps: collecting 10 or more membranaceous beautyleaf root medicinal materials, carrying out detection operation according to the method, comparing obtained detection results, and selecting common characteristic peaks to obtain the gas-phase fingerprint spectrum of membranaceous beautyleaf root. The gas-phase fingerprint spectrum constructed by the method can be used for rapidly and accurately determining and identifying the membranaceous beautyberry root traditional Chinese medicinal material.

The invention relates to the technical field of USB chip testing, and particularly discloses a USB chip testing device which comprises a base, a placing table and a testing table, the placing table is connected to the base, the testing table is connected to the base, a USB plug is placed on the placing table, the testing table is used for testing whether a USB plug chip can be normally used or not, a plurality of testing ports are formed in the testing table, and the testing ports are used for testing whether the USB plug chip can be normally used or not. A plurality of test ports are arranged on the test board, test chips are arranged in the test ports, the automatic test assembly is connected to the test board and connected with the test chips, the automatic test assembly is used for testing USB chips, and the test chips may be worn and damaged after being used for a long time. Therefore, the automatic test assembly can detect whether the test chip is damaged or not while testing the USB chip, so that the condition of detection errors is prevented, and the quality condition of the USB chip can be ensured to be accurately tested.

The invention relates to the field of petroleum geological exploration reservoir evaluation, and discloses a compact sandstone reservoir quality evaluation method and related equipment, and the method comprises the following steps: determining reservoir indexes according to compact sandstone reservoir characteristics; determining a weight through an entropy weight method based on the reservoir indexes; constructing a target vector function by using an ideal point method based on the reservoir indexes; substituting the weights into a target vector function to obtain positive and negative ideal solutions; and constructing a reservoir quality model according to the positive and negative ideal solutions, and evaluating the reservoir quality of the tight sandstone reservoir based on the reservoir quality model. According to the method, the problem that the tight sandstone reservoir is difficult to evaluate is effectively solved, and a tight sandstone reservoir quality evaluation technology is formed.

The present invention discloses a bottom-sealed heat shrink film packaging machine, including a bottom-sealed heat shrink film packaging machine, including a film feeding and collecting mechanism, a box clamping and transporting mechanism, a transverse sealing and hot cutting mechanism, a film cutting mechanism and a frame; the frame: receiving or setting other mechanisms of the bottom-sealed heat shrink film packaging machine; four rollers are provided for the packaging machine to move its position, and four supporting feet are provided for the packaging machine to fix its position when working; an air source processor is also provided on the frame. The bottom-sealed heat shrink film packaging machine of the present invention is used for various product packaging boxes. It is mainly for the outer packaging of various square product boxes to perform a four-corner cutting process to improve the appearance, and adopts non-standard automation technology to cut the corners of the product packaging box, with high packaging efficiency, ensuring the product packaging appearance quality, high yield, and making the packaging film cutting line of excellent quality, precision, and small error, which can be very good for seamless packaging of products.

The invention provides a spectral data processing method and device of a tea pile and electronic equipment, and is applied to the technical field of rapid detection of field tea bud quality, the method comprises the following steps: inputting a tea pile mixed spectrum into a bilinear spectrum model to obtain a front leaf spectrum, the bilinear spectrum model being used for correcting the tea pile mixed spectrum; derivation is carried out on the front leaf spectrum of the tea pile to obtain a derivative set of the front leaf spectrum, and derivation is used for eliminating tea bud stacking structure information of the tea pile; the derivative set is input into a Gaussian process regression model adopting a radial basis kernel function, the front leaf quality is obtained, the radial basis kernel function in the Gaussian process regression model is used for eliminating front leaf proportion information of the tea pile, and the Gaussian process regression model is used for predicting the front leaf quality; according to the method, the influence of the tea bud stacking structure in the tea pile mixed spectrum and the proportion difference of the front leaves on the accurate inversion of the tea bud quality can be eliminated.

The present disclosure discloses a display device comprising: an external device interface unit for receiving image data from an external device; a display unit for outputting the image data; and a control unit for recognizing a type of the external device by using reference information of the external device, correcting an image quality of the image data by using distance information corresponding to the type of the external device, and outputting the corrected image data.

This invention relates to the field of feed production, processing, and testing technology. Specifically, it relates to a feed production, processing, and testing method based on big data. The method includes the following steps: S1, collecting historical feed production data and screening it according to processing stages to obtain historical production data corresponding to each processing stage; S2, obtaining the feed quality corresponding to the historical production data, and simultaneously obtaining the standard process and standard quality corresponding to each processing stage. Through big data modeling, a deep correlation analysis between process and quality is achieved, significantly improving the accuracy of quality control. This not only quantifies the differences in feed quality and process deviations at each stage, but also innovatively introduces modeling of raw material quality grades and processing sequence nodes. By calculating the positive and negative values ​​of the impact of process deviations on quality, it accurately identifies the positive or negative destructive effects of fluctuations in different process parameters on quality.