6results about How to "Accurate quality evaluation" patented technology

The present invention discloses a method and system for evaluating coal quality based on hyperspectral imaging technology, and relates to the technical field of coal quality evaluation. The method comprises: obtaining visible-near infrared, short-wave infrared, and thermal infrared hyperspectral images of a region containing a coal target; performing image processing and fusion on a plurality of hyperspectral images to obtain an original hyperspectral image; using a target detection algorithm to identify the coal region in the image; extracting spatial-spectral fusion features based on the hyperspectral images of the coal region, and predicting the ash, moisture, volatile content, and calorific value of the coal according to the relationship between the spatial-spectral fusion features and a plurality of basic indicators of coal quality; performing calculation and correction according to the predicted ash, moisture, volatile content, and calorific value to obtain a corrected calorific value; comprehensively evaluating the moisture, ash, volatile content, and corrected calorific value of the coal to evaluate the coal quality and classify the coal. The present invention can achieve more accurate coal quality detection and evaluation.

The present invention relates to the field of image processing technology, and in particular to a packaging film quality detection method and system based on machine vision, comprising: obtaining a top image and a side image of a film sample, performing circle fitting on all edge points of the top image to obtain the degree of dirt influence on the film sample, performing threshold segmentation on the side image to obtain a number of suspected areas, calculating the defect evaluation of each suspected area and screening out a number of defective areas, marking the defective areas caused by dirt in all defective areas, calculating the degree of weakening of each defective area caused by dirt, and then correcting the defect evaluation of each defective area caused by dirt, and finally obtaining the quality evaluation of the film sample. The present invention collects and analyzes the top image and the side image of the packaging film sample, and makes an accurate defect evaluation on the defects generated in the production process, thereby improving the accuracy of packaging film quality detection.

The invention provides a light field image quality evaluation method based on a visual language model. According to the method, multi-dimensional comprehensive evaluation of a light field image is realized through the following steps of: (a) evaluating the definition, brightness, angle consistency and the like of the light field image through antonym prompt pairing by utilizing a text prompt function of a visual language model; (b) removing fixed position embedding of a visual language model image encoder so as to improve the adaptability of the model to light field images with different space and angle resolutions; (c) finely adjusting the antonym prompt pair by using a context optimization technology to adapt to the multi-view characteristic of the light field image, and keeping the network weight of the visual language model unchanged; and (d) comprehensively evaluating the light field image based on multi-dimensional evaluation indexes such as brightness, color and angle consistency, and generating an overall quality score. The method can be used for efficient coding, transmission, rendering and other light field image processing scenes, and a new solution is provided for light field image quality evaluation.

The present invention relates to the technical field of pressure sensors, and in particular to an intelligent compensation system for pressure sensor detection, including a pressure sensor fixing slot for placing a pressure sensor to be detected, an auxiliary sensor fixing slot for placing a standard pressure sensor for auxiliary monitoring, a temperature regulating unit, a pressurizing column, a pressure data verification unit for verifying the standard pressure sensor or the pressurizing column, and a data analysis module, wherein the data analysis module is used to perform compensation calculations on the pressure data and classify the pressure sensor to be detected. By setting a standard pressure sensor, the present invention can simultaneously determine whether the working status of other components meets the standards when judging the sensor to be detected, so that the working environment when the sensor to be detected is a standard preset environment, and the temperature and pressure conditions of the pressure sensor are reasonably controlled, so that the quality evaluation of the pressure sensor is more accurate.

The invention relates to the field of traditional Chinese medicine analysis, in particular to a method for simultaneously determining the content of six carbohydrate components in rhizoma polygonati. The invention discloses a method for simultaneously determining the contents of six carbohydrate components in rhizoma polygonati, which comprises the following steps of: establishing a relative correction factor and a relative intercept between the five carbohydrate components of fructose, glucose, kestose, nystose and nystose in the rhizoma polygonati and an internal reference substance by taking cane sugar which is low in cost and easy to obtain as the internal reference substance; according to the method, the contents of sucrose and other five carbohydrate components in the rhizoma polygonati are calculated by only adopting sucrose as a reference substance and utilizing a relative correction factor, a relative intercept and a relative retention value, so that multi-index quality evaluation on the rhizoma polygonati (crude products and processed products) is simple, convenient, rapid, comprehensive and accurate, and the quality controllability and the stable curative effect of the product are ensured; meanwhile, the detection cost and time are saved.

The application relates to the technical field of image quality evaluation, in particular to an infrared image quality evaluation method based on multi-scale features, which comprises the following steps: acquiring a large number of infrared images labeled with quality score labels to construct a training sample set; constructing an infrared image quality evaluation model based on multi-scale features; wherein the infrared image quality evaluation model is composed of a main branch network, an auxiliary branch network and an output layer; inputting sample images in the training sample set into the infrared image quality evaluation model, iteratively training the infrared image quality evaluation model by using a mean square error loss function until convergence is achieved, and obtaining a trained infrared image quality evaluation model; inputting an infrared image to be evaluated into the trained infrared image quality evaluation model to obtain a quality score output by the infrared image quality evaluation model for the infrared image to be evaluated. The method effectively improves the accuracy of infrared image quality evaluation and has stronger generalization ability and stability.