Coal sample hyperspectral image acquisition and processing methods

In the research and production practice of coal industry, it is very important to obtain accurate information of various characteristics of coal for optimizing coal utilization and improving product quality. Hyperspectral image technology, as a powerful means of analysis, can provide abundant information of coal internal structure and composition, and its application is based on efficient and accurate coal sample hyperspectral image acquisition and processing methods.

Hyperspectral imaging technology is an advanced technology integrating optics, electronics, computer science and other disciplines. Its working principle is based on the differences in the absorption, reflection and scattering properties of different substances to different wavelengths of light. Through hyperspectral imaging equipment, we can obtain the reflectance information of coal in the continuous spectral range, which is like the "fingerprint" of coal, containing rich material composition and structure information. Compared with traditional imaging technology, hyperspectral imaging technology has higher spectral resolution and can be accurate to the wavelength difference at the nanometer level, which can capture the spectral characteristics of various components in coal in more detail.

In this paper, a 900-1700nm hyperspectral camera is used, and FS-15, a product of Color Spectrum Technology (Zhejiang) Co., LTD., can be used for related research. Short-wave near-infrared hyperspectral camera, the acquisition speed of the full spectrum up to 200FPS, is widely used in the composition identification, substance identification, machine vision, agricultural product quality, screen detection and other fields.

The application of hyperspectral imaging technology in coal calorific value detection is relatively simple and efficient. First, hyperspectral image data is obtained by scanning coal samples with hyperspectral imaging equipment.The application of hyperspectral imaging technology in coal calorific value detection is relatively simple and efficient. First, hyperspectral image data is obtained by scanning coal samples with hyperspectral imaging equipment.

Hyperspectral image acquisition interface

These data contain information about the reflectivity of coal at different wavelengths. Then, professional data processing software is used to preprocess the acquired image data, remove noise, correct spectrum, etc., in order to improve the quality of data.

(a) The original image                                 (b) Area of interest

Selection of regions of interest in coal hyperspectral images

Region of interest mean spectral curve

Seven point SG smooth filtering

Due to the characteristics of the instrument itself and the influence of environmental factors, the collected spectrum may have some problems such as wavelength drift and intensity deviation. The purpose of spectral correction is to correct these deviations so that they can accurately reflect the real spectral characteristics of coal samples. Common spectral calibration methods include wavelength calibration and radiation calibration. Wavelength calibration Calibrates the wavelength accuracy of the imaging spectrometer by using standard materials with known spectral characteristics, such as mercury lamps and neon lamps, to ensure that the wavelength value corresponding to each pixel is accurate. Radiometric calibration is to convert the gray value of the image into the actual reflectance value by measuring the standard whiteboard with known reflectance, thus eliminating the influence of factors such as instrument response and uneven illumination on the spectral intensity.

The results of multivariate scattering correction are shown in the figure.

Multivariate scattering correction results

Standard normal transformation

Standard normal transformation result

The acquisition and processing of hyperspectral images of coal samples is a complicated and critical process. By selecting suitable acquisition equipment, optimizing the acquisition process and using advanced image processing methods, abundant and accurate coal information can be extracted from hyperspectral images, which provides strong technical support for the research, production and quality control of coal industry. With the continuous development of technology, the application prospect of hyperspectral image technology in the coal field will be broader, and it is expected to bring new breakthroughs for the development of the coal industry.