CHNSpec Technology （Zhejiang）Co.,Ltd Company News

In today's society, the issue of food safety has attracted much attention. Consumers' demands for the quality, safety and authenticity of food are increasing day by day. The traditional methods of food safety testing usually have drawbacks such as long testing time, laborious operation, destructive nature of the tests, and limited testing scope. However, the emergence of hyperspectral technology has injected new vitality and great development potential into the field of food safety testing. Hyperspectral technology is a cutting-edge approach that integrates spectroscopy with imaging technology. It can simultaneously obtain a large amount of spectral information and spatial image information of the object being detected. Through the analysis of these data, one can deeply understand various characteristics of the food. At the level of food quality inspection, hyperspectral technology can quickly and non-destructively evaluate indicators such as the freshness, maturity status and texture of food. For example, for fruits and vegetables, hyperspectral technology can determine the internal sugar content, acidity and whether there is mechanical damage by detecting the spectral characteristics of their surfaces. For meat products, it can detect the moisture content, fat distribution and protein content, thereby accurately assessing the quality of the meat. In terms of component analysis, hyperspectral technology demonstrates outstanding capabilities. It can accurately measure the contents of various nutrients in food, such as vitamins, minerals, amino acids, etc. Moreover, it can also detect the contents of chemical substances like additives and preservatives in food, ensuring that they comply with relevant standards and regulations. For the identification of the authenticity of food, hyperspectral technology also plays a crucial role. Foods from different origins, varieties, and processing methods often have unique spectral characteristics. By constructing a large-scale spectral database and using advanced pattern recognition algorithms, hyperspectral technology can accurately distinguish between genuine and fake food, such as identifying genuine and fake honey, genuine and fake olive oil, etc. In the field of detecting whether food has been contaminated, hyperspectral technology has significant advantages. It can detect various types of contamination in food, such as heavy metal pollution, pesticide residues, and microbial contamination. For instance, by analyzing the spectral characteristics of the food surface, the presence and distribution of pesticide residues can be quickly detected. Regarding microbial contamination, hyperspectral technology can detect the spectral changes caused by microbial metabolites, thereby achieving early warning and detection.   However, although hyperspectral technology has demonstrated great potential in food safety testing, it still faces some challenges at present. The high cost of hyperspectral equipment restricts its widespread application in some small testing institutions and enterprises. Additionally, the processing and analysis of hyperspectral data require professional knowledge and complex algorithms, and have high technical requirements for operators. At the same time, the standards and methods of hyperspectral testing still need to be further optimized and unified to ensure the accuracy and reliability of the test results. In order to fully unleash the potential of hyperspectral technology in food safety testing, efforts are needed in the following areas in the future. On one hand, more investment should be made in the research and development of hyperspectral technology to reduce equipment costs, improve the stability and portability of the equipment. On the other hand, cross-disciplinary cooperation should be strengthened to cultivate professionals who are proficient in spectral technology and familiar with the field of food safety, and develop more efficient and accurate data processing and analysis methods. At the same time, a complete set of hyperspectral testing standards and quality control systems should be established to promote the wide application of hyperspectral technology in the field of food safety testing. In conclusion, hyperspectral technology, as a highly innovative and forward-looking detection method, has a vast application space in food safety testing. With the continuous advancement and improvement of the technology, we firmly believe that it will play an increasingly important role in ensuring food safety and safeguarding the health of consumers.  

The CMYK values measured by the spectrophotometer are different from those in Photoshop. Here are the main differences between them:   Measurement method: A spectrophotometer is a physical device that determines color information by measuring the absorption and reflection of light. It can directly measure the color of an object's surface and convert it into CMYK values. In Photoshop, CMYK is calculated based on the color model and algorithm.   Color space: Spectrophotometers typically use actual physical color spaces, such as the CIE Lab color space or other standard color spaces. The CMYK values provided by them are relative to these color spaces. While in Photoshop, CMYK is based on its internal color management system and color profile, and usually uses device-dependent color spaces.   Calibration and profile: A spectrophotometer needs to be calibrated and configured to ensure accurate color measurement. It usually requires reference to a standard color chart or calibration target. In Photoshop, CMYK can be converted and displayed based on the color profile selected by the user.   Color accuracy: A spectrophotometer theoretically can offer higher color accuracy because it directly measures the physical properties of colors. The CMYK conversion in Photoshop is usually limited by the color management system and profile, and there may be some color discrepancies.   In summary, the CMYK values measured by the spectrophotometer are based on the actual colors obtained through physical measurement, while the CMYK values in Photoshop are calculated values based on software algorithms and color profiles. Their accuracy and application methods may differ. In the ink printing, packaging, and paper industry, the most commonly used density meters are those from two brands: China's Color Spectrum and the United States' X-Rite (also known as Color iX). The main ones include:   1. X-Rite:eXact Spectrophotometer 2. ColorScan: DS-700C Spectrophotometer

In the current industrial landscape, plastic products are ubiquitous. From ordinary daily necessities to high-end industrial components, plastic has become an indispensable material in modern manufacturing due to its rich and diverse properties as well as its wide applicability. In the plastic industry, haze meters are playing a pivotal role and have become a key tool for ensuring product quality.   Transparency as one of the important indicators for measuring the optical performance of transparent or semi-transparent plastic materials, when light passes through the plastic materials, due to the structural characteristics within the materials, possible impurities or surface conditions and other factors, it will cause light scattering and absorption, thereby making the passed light become hazy and unclear. The haze meter precisely measures the degree of light scattering to provide quantitative evaluation basis for the optical performance of products for the plastic industry. For plastic product manufacturing enterprises, the application of the haze meter has significant and multiple meanings. Firstly, it is indispensable for ensuring the appearance quality of products. In those application fields with high requirements for appearance, such as optical lenses, display panel panels, etc., low haze plastic materials can give a clear and transparent visual experience, thereby enhancing the level and competitiveness of products. Through strict quality inspection with the haze meter, it can promptly detect and eliminate products with haze not meeting the standards, preventing defective products from flowing into the market. Secondly, the haze meter also plays a key role in the process of product research and development and quality control. When developing new plastic materials or improving production processes, the haze meter can provide accurate optical performance data, helping engineers understand the characteristics and change trends of the materials, and then optimize the formulation and process parameters to enhance the quality stability of products. In the production process, regularly using the haze meter to conduct sampling tests on products can monitor production quality in real time, adjust production processes in a timely manner, and ensure that products always meet quality standards.   Furthermore, the haze meter also provides strong support for the standardization construction and quality certification in the plastic industry. Numerous industry standards and quality certification systems have clear regulations on the haze of plastic materials, and the measurement results of the haze meter can serve as an important reference for judging whether the products meet the standards. By using the haze meter for testing, enterprises' products can be more easily recognized by the market and their credibility and competitiveness can be enhanced. With the continuous progress of technology, the performance of the haze meter is also constantly upgrading. Modern haze meters have high precision, high stability, and simple operation features, and can meet the actual needs of different-sized plastic enterprises. At the same time, some advanced haze meters also have data storage, analysis, and transmission functions, which can be seamlessly connected with the enterprise's quality management system to improve the efficiency and informatization level of quality management. In conclusion, the haze meter occupies an irreplaceable position in the plastic industry. It is not only a loyal guardian of product quality but also an important driving force for the continuous development and progress of the plastic industry. In the future, as the requirements for product quality in the plastic industry continue to rise, the application of haze meters will be more extensive and in-depth, and will continue to contribute significantly to the vigorous development of the plastic industry.

During the process of furniture making and renovation, paint color matching is a crucial technique. It not only affects the aesthetic appeal of the furniture but also directly influences the overall style and atmosphere of the furniture. With the advancement of technology, color matching software has been increasingly widely applied in color management, providing more precise and efficient solutions for furniture paint color matching.   I. Traditional Methods of Paint Color Mixing and Their Limitations The traditional methods of paint color mixing mainly rely on the experience and visual judgment of color mixers. They adjust the color of the paint by adding different proportions of pigments or color pastes. Although this method can meet the color mixing requirements to some extent, it has obvious limitations: 1. Subjectivity: The color mixing results are often influenced by the personal experience and subjective feelings of the color mixer, making it difficult to ensure the accuracy and consistency of the colors. 2. Low efficiency: The traditional color mixing method requires repeated color trials and adjustments, consuming a lot of time and materials. 3. Difficult to achieve precise color matching: For complex or special color requirements, the traditional method is difficult to achieve the desired color mixing effect.   II. Precise Color Management of Color Matching Software Color matching software utilizes digital technology to achieve precise management and control of colors, providing a more efficient and accurate solution for furniture painting color matching. Its main advantages are as follows: 1. Color Database Support: The color matching software has a rich color database built-in, covering various common and special colors. Users can directly select or refer to them to quickly determine the target color. 2. Precise Color Matching Algorithm: The software uses advanced color matching algorithms to automatically calculate the required pigment or color paste proportions based on the color parameters or samples input by the user, achieving precise color matching. 3. Visual Preview: The software supports real-time preview function. Users can view the color matching results at any time during the color matching process to ensure the accuracy of the color. 4. Efficiency Enhancement: Using color matching software for color matching can significantly shorten the color matching time, reduce material waste, and improve production efficiency.   With the development of technology, color matching software has been increasingly widely applied in the field of furniture paint color matching. Its precise color management and control functions provide more efficient and accurate solutions for furniture manufacturing and renovation. Taking Color Spectrum Technology as an example, its intelligent color matching solution effectively assists customers in solving the problem of paint color matching. This solution covers the entire process from color selection, color matching to sample making, greatly simplifying the work of color matching technicians. Through simple instrument operation and data processing, technicians can successfully complete the color matching of samples. This solution is not only easy to operate and easy to master, but also realizes the electronicization of sample data and formula data, ensuring the accuracy of the formula and the efficiency of color matching. Moreover, it can provide multiple color matching schemes for selection, and flexibly adjust according to cost and actual needs. What's more remarkable is that this solution supports color matching using waste materials and old materials, effectively saving costs. In the paint industry, the application of intelligent color matching is helping enterprises achieve transformation and upgrading, enhance competitiveness, and better cope with increasingly fierce domestic and international market competition. The information in this article is provided by Color Spectrum. For more details, please visit the official website of Color Spectrum Color Difference Meter Manufacturer.

Mosaic joint treatment is a decorative product that addresses the issues of unsightly gaps between tiles and the dirtiness and blackness of the gaps. Currently, the most popular type of mosaic joint treatment on the market is the epoxy colored sand type. The epoxy colored sand does not require vacuum packaging and can be directly mixed with colors at the customer's construction site. It can match the corresponding mosaic joint treatment according to the customer's needs and the style of decoration. Due to its physical property of being able to naturally disperse air, the epoxy colored sand mosaic joint treatment can make the area filled with the mosaic joint and the tiles look as smooth as possible, thereby enhancing the aesthetic appeal of the decoration.   Current Status of Grout Color Matching: In the process of grouting work, the most crucial part is how to match the desired grout color. However, in actual grouting work, several problems often arise: ① Grout color matching skills cannot be mastered overnight; ② Even if one has learned how to do color matching, the entire process is very time-consuming. On average, it takes one hour to match a color similar to the tiles, which significantly prolongs the working time of grouting operations; ③ In the early stage of grout color matching, the formula needs to be constantly adjusted using grout, which wastes a large amount of raw materials and increases the cost of grouting work.   Transforming the current situation of joint sealant color matching: In response to the current situation of joint sealant color matching, CaiPu Technology has launched a specialized tool for the joint sealant color matching industry - CaiLu. ① By using the CaiLu joint sealant color matching instrument, the color matching time has been shortened from 1 hour to 30 seconds, saving time for color matching work. ② Based directly on the color formula calculated by the CaiLu mini-program, joint sealant operations can be carried out without wasting raw materials. ③ On-site, colors can be immediately adjusted according to customer needs, allowing customers to immediately see the joint sealant effect, enhancing customers' trust in your operation and improving your competitive advantage in this industry. ④ The CaiLu joint sealant color matching instrument can help you significantly reduce the working time for joint sealant and can handle more customers in one day.

In the realm of wood processing, the application of colors is like a fantastic magic feast, which can instantly infuse the otherwise unremarkable wood with a brand new vitality. Currently, the emergence of color matching software has brought about a highly disruptive transformation in the application of wood dyes.   The selection of traditional wood dyes often relied on experience and limited color card references, which not only restricted the creative space of designers and artisans but also made it difficult to achieve the expected color effects precisely. However, with the introduction of color matching software, this situation has been greatly reversed. The color matching software has built an extremely large color database for wood dyes. Whether it is warm earth tones, fresh natural color schemes, or dazzling fashionable color series, they can all be easily found in the software. Designers can conduct endless color exploration based on different wood types, textures, and design requirements in the software. By adjusting parameters such as color saturation, lightness, and contrast, they can find the most suitable dye formula combinations for the wood.   For instance, when creating furniture with a retro style, color matching software can assist designers in quickly screening out dark-colored dye schemes that carry a strong historical flavor. For wooden products with a modern minimalist style, the software can offer simple and clear color combinations. Meanwhile, the software can simulate the color presentation states of wood under different lighting conditions to ensure that the final dyeing effect is at its best in various environments. Moreover, the color matching software also has a powerful color matching analysis function. It can provide scientific and reasonable color matching suggestions for wood dyes based on color psychology and aesthetic principles. Just like choosing complementary colors can create a strong visual impact, similar colors can shape a harmonious and unified atmosphere. Thus, wood dyeing is no longer a blind attempt but a meticulous planning based on professional knowledge and creative inspiration.   In the actual application process, the color matching software not only enhances the efficiency of selecting wood dyes but also significantly reduces the cost expenditure. By conducting virtual dyeing operations in the software, it can effectively avoid material waste caused by unsatisfactory actual dyeing results. Meanwhile, the software can also be closely integrated with the production process of wood processing enterprises to achieve automatic color matching and dyeing control, thereby improving production efficiency and product quality. In conclusion, the application of color matching software in the field of wood dyes has brought unprecedented innovative opportunities to the wood processing industry. It makes the colors of wood more brilliant and colorful, opening a new door to an endless stream of creativity for designers and artisans. In the future, with the continuous progress of technology, it is believed that the color matching software will play a more crucial role in the field of wood dyes, creating more exquisite and magnificent wood products for us.  

I. Causes of Color Difference Raw material differences There may be slight color variations among different batches of paint. Even if they are from the same brand and model, the color may still differ due to factors such as production time and storage conditions. Moreover, the material of the furniture itself can also affect the color. For instance, the texture and density of wood vary, and the absorption of paint by wood also differs, resulting in color differences after touch-up painting.   Environmental factors Lighting conditions are one of the important factors affecting color perception. Furniture colors may appear differently under varying light intensities and angles. Additionally, environmental factors such as temperature and humidity can also influence the drying speed and color stability of paint, leading to color differences.   Construction techniques The construction techniques during touch-up painting also have a significant impact on color differences. If the thickness and uniformity of the spray are inconsistent, or if the base coat and top coat are not properly matched, color differences may occur. Moreover, the technical proficiency and experience of the painters can also affect the touch-up painting results.   II. Methods to Solve Color Difference Problems Selecting appropriate paint Before touch-up painting, we should choose high-quality and stable paint. At the same time, we should select the paint type and color that match the original furniture's color based on its original color and material. We can compare different brands and models of paint using a color difference meter to choose the one with the closest color.   Controlling the construction environment To reduce the influence of environmental factors on color perception, we should carry out touch-up painting under suitable temperature, humidity, and lighting conditions. We can use humidifiers, air conditioners, etc. to adjust the humidity and temperature of the environment, and avoid direct sunlight and strong light exposure.   Strict construction techniques During touch-up painting, we should operate strictly in accordance with the construction techniques requirements. We should control the thickness, uniformity, and drying time of the spray to ensure that the paint can fully dry and cure. At the same time, we should pay attention to the pressure and angle of the spray gun to avoid problems such as sagging and bubbling.   Using a color difference meter for adjustment During touch-up painting, we can regularly use a color difference meter to measure the color and make adjustments based on the measurement results. A color difference meter is a specialized instrument used to measure color differences. It can measure the X, Y, and Z tristimulus values of the color and then calculate the color difference between the two colors. If the color difference is large, we can appropriately increase or decrease the proportion of pigments or adjust the amount of thinner to achieve a satisfactory effect.   III. Notes Before performing the re-painting of furniture, it is advisable to conduct a trial on an inconspicuous part first to ensure that the color and effect of the paint meet the requirements. During the construction process, safety should be paid attention to. Protective equipment should be worn to avoid damage to the body caused by the paint.   After re-painting the furniture, appropriate maintenance should be carried out to prevent the influence of environmental factors such as direct sunlight and humidity on the paint, thereby prolonging the service life of the furniture. In conclusion, the color difference problem in furniture touch-up painting can be solved by choosing appropriate paints, controlling the construction environment, strictly adhering to construction techniques, and adjusting through color difference meters. As long as we pay attention to every step carefully, we can restore the furniture to its original condition and add more beauty to our lives.

At the end of 2013, Cai Cen Technology successfully held a highly anticipated technical demonstration meeting for 7 - 12um hyperspectral cameras. In this meeting, renowned experts and scholars from Zhejiang University, the Chinese Academy of Sciences, Tsinghua University, Beijing Institute of Technology, Tongji University, Hangzhou Dianzi University and China University of Metrology gathered together to jointly offer suggestions and strategies for the development of hyperspectral camera technology. At the beginning of the meeting, Yuan Kun, the General Manager of Cai Pu Technology, took the lead in presenting a comprehensive and in-depth report on the 7 - 12um hyperspectral imaging system solution to all the attending experts. He clearly expounded the significant strategic importance of this project for Cai Pu Technology and the entire industry. Subsequently, the project team detailedly demonstrated the current progress and mid-term achievements of the project from multiple key dimensions such as optical scheme, structural scheme, embedded system scheme, image processing algorithm scheme, and testing scheme to the experts. During the argumentation phase, the experts engaged in a rigorous and meticulous discussion on the 7 - 12um hyperspectral imaging system solution proposed by Cai Pu Technology. With their profound academic attainments and rich industry experience, the experts expressed their own viewpoints, conducted in-depth analyses from multiple aspects such as technical feasibility, innovation, and application prospects, and put forward many constructive opinions and suggestions. To ensure the smooth progress of the project and the continuous optimization of the technology, a project technical expert committee was established at the meeting site. The committee members conducted more in-depth discussions on core contents such as the index design, scheme maturity, and test scheme of the 7 - 12um hyperspectral imaging system project. The experts unanimously believed that this project not only presents extremely high technical challenges but also has broad market application prospects, and is expected to achieve breakthrough applications in multiple fields. Among them, the potential value in the military field has attracted widespread attention. The 7-12um hyperspectral camera technology holds irreplaceable advantages in military reconnaissance. It can simultaneously detect targets within continuous working bands, directly reflecting the spectral characteristics of the measured objects, thereby accurately differentiating the surface components and states of the targets, obtaining precise corresponding relationships between space detection information and actual ground targets, and providing key intelligence for detailed battlefield reconnaissance. In complex battlefield environments, this technology can assist military personnel in quickly identifying hidden military facilities, weapons and equipment, as well as potential threat targets. Meanwhile, this technology can also effectively identify camouflaged targets. Based on the different spectral characteristics between the background and the camouflaged target, hyperspectral cameras can sensitively detect military equipment that has been camouflaged. By inverting the spectral characteristic curves, the composition of the target can be deduced, making it impossible for camouflaged targets hidden in various environments to remain undetected. In areas with dense vegetation, by utilizing spectral characteristics such as the red edge effect of the vegetation, green camouflaged targets hidden within can be easily identified, significantly enhancing the accuracy of military reconnaissance. Furthermore, the airborne equipment equipped with a 7-12um hyperspectral camera can perform remote sensing operations by distinguishing most colors within a wide spectral range and with extremely high resolution. It can be used to identify, measure and track various materials and objects, including detecting weak-signal military activities and hidden obstacles, as well as identifying dangerous goods, providing comprehensive support for military operations. At the meeting, Cai Pu Technology solemnly stated that the 7 - 12um hyperspectral camera is the company's top project for 2025, carrying great expectations. The company will spare no effort, integrate various resources, increase R&D investment, strictly control product quality, and ensure that it does not disappoint the earnest expectations of all experts. In 2025, it will successfully launch this product, adding another "national weapon" to China's hyperspectral imaging field and injecting new vitality into the development of Cai Pu. Cai Pu Technology has been deeply engaged in the field of optical instruments. It has achieved fruitful results in the research and development of high-spectrum cameras and unmanned aerial vehicle high-spectrum measurement systems, and possesses a number of patented technologies. It has published several academic papers in renowned domestic and foreign journals. The successful holding of this technical demonstration meeting is another important milestone for Cai Pu Technology on the road of scientific and technological innovation. In the future, with the launch of 7 - 12um high-spectrum cameras, it is expected to play an important role in environmental monitoring, agricultural remote sensing, industrial inspection, and biomedicine, promoting the technological upgrading and development of related industries, and also contributing to the further enhancement of China's national defense strength in the military field.

In the textile industry, goose down and duck down have become high-quality raw materials for making high-end thermal insulation products due to their excellent thermal insulation properties. However, there is a significant difference in market prices between goose down and duck down. Some unscrupulous merchants, in pursuit of high profits, often mix duck down into goose down to pass off inferior products as high-quality ones. This not only harms the interests of consumers but also disrupts the market order. Therefore, it is particularly important to accurately and efficiently conduct quantitative detection of goose and duck mixed down. In recent years, the development of hyperspectral camera technology has provided an innovative solution to this detection problem.   I. Sample Preparation: Collect a large quantity of pure goose down and duck down samples, ensuring their sources are reliable and representative. Use a high-precision electronic scale to accurately weigh the goose down and duck down in different proportions, and prepare a series of samples with known mixed ratios of goose and duck down, such as setting samples with different duck down mixing ratios of 5%, 10%, 15%,... 95%, each with multiple replicate samples to improve the accuracy and reliability of the experiment. Evenly spread the prepared mixed down samples on a specially designed sample platform, ensuring uniform distribution without overlapping or gaps, to ensure that the hyperspectral camera can obtain comprehensive and accurate spectral information.   II. Hyperspectral Image Acquisition: In this paper, a hyperspectral camera with a spectral range of 400-1000nm was applied. The product FS13 from Hangzhou Cai Pu Technology Co., Ltd. can be used for related research. The spectral range is from 400 to 1000nm, with a wavelength resolution better than 2.5nm and up to 1200 spectral channels. The acquisition speed for the full spectral range can reach 128FPS, and after band selection, the maximum speed is 3300Hz (supporting multi-region band selection). Multiple shots were taken for each mixed fluff sample, and images were obtained from different angles to reduce detection errors caused by local feature differences of the samples. After each shot, the collected hyperspectral image data was promptly transmitted to the computer for storage to avoid data loss.   III. Data Preprocessing: Utilize professional data processing software to conduct preprocessing on the hyperspectral image data collected. Firstly, perform radiometric correction to eliminate the radiometric errors caused by the performance differences of the camera itself and environmental factors, ensuring that the spectral data of different images are comparable. Then, carry out geometric correction to correct the image deformation caused by factors such as the camera's shooting angle and the sample's placement position, ensuring that the position of each pixel point in the image is accurate. Finally, apply noise reduction processing to the image, using filtering algorithms to remove the noise interference in the image, improving the quality and clarity of the image, so as to extract spectral features more accurately in the subsequent steps. IV. Spectral Feature Extraction: For the preprocessed hyperspectral images, specific algorithms and software tools are utilized to extract spectral features for the goose down and duck down regions respectively. Through the analysis and comparison of a large amount of image data, the specific wavelength range that can significantly distinguish goose down from duck down is determined in the visible light to near-infrared spectral region. At these key wavelengths, the reflectance values of goose down and duck down are carefully measured and recorded to form their respective unique spectral feature datasets. For example, after multiple experiments and analyses, it was found that there are obvious differences in the reflectance curves of goose down and duck down within the wavelength range of 700nm - 800nm, and these differences can serve as important bases for identifying the two types. V. Model Establishment and Validation: Based on the spectral characteristic data of goose down and duck down extracted, using machine learning or statistical methods, establish a spectral model for quantitative analysis of goose and duck mixed down. Common modeling methods include support vector machines, partial least squares, etc. During the modeling process, a portion of sample data with known mixed ratios is used as the training set to train the model, enabling it to learn the intrinsic relationship between the spectral characteristics of goose down and duck down and the mixed ratio. Another portion of samples not involved in the training is used as the validation set to validate the established model. The high-spectrum image data of the validation set samples is input into the model, and the predicted mixed ratio of goose down and duck down is calculated through the model and compared with the actually known mixed ratio for contrast analysis. By calculating the error between the predicted value and the true value, such as root mean square error, mean absolute error, etc., the accuracy and reliability of the model are evaluated. Based on the validation results, the model is adjusted and optimized, such as adjusting model parameters, adding or reducing feature variables, etc., to improve the performance of the model.   VI. Result Analysis and Evaluation: Summarize and statistically analyze the detection results of all mixed down samples. Calculate the average values, standard deviations, and other statistical indicators of the detection results under different mixing ratios, and evaluate the stability and repeatability of the detection method. Compare and analyze the detection results of the hyperspectral camera with those of traditional detection methods (such as chemical analysis methods), further verifying the accuracy of the hyperspectral camera detection method. Through the analysis of a large amount of experimental data, obtain the key performance indicators such as the error range and detection accuracy of the hyperspectral camera in the quantitative detection of goose and duck mixed down. The experimental results show that this method can quickly and accurately detect the precise proportion of goose down and duck down in the mixed down within a short time, and the detection error can be effectively controlled within a very small range, fully demonstrating its high reliability and practicability. The application of hyperspectral camera technology has greatly improved the accuracy and efficiency of quantitative detection of goose and duck mixed down. For production enterprises, it can ensure product quality and maintain brand reputation; for regulatory authorities, it provides powerful technical support for cracking down on counterfeit and substandard products in the market, helping to purify the market environment and safeguard the legitimate rights and interests of consumers. With the continuous development and improvement of technology, it is believed that the application of hyperspectral cameras in quantitative detection of goose and duck mixed down and other related fields will be more extensive and in-depth, injecting new vitality into the healthy development of the industry.

With the extensive application of plastic products in numerous fields such as automobiles, electronics, and medical care, plastic welding technology, as a key means for connecting plastic products, its welding quality directly affects product performance and service life. Traditional methods for evaluating plastic welding quality, such as visual inspection and destructive tests, have limitations including strong subjectivity, inability to comprehensively reflect internal quality, and potential damage to the products. The emergence of laser transmittance meters has provided a brand-new, efficient, and accurate solution for evaluating plastic welding quality.   I. Working Principle of Laser Transmittance Meter The laser transmittance meter operates based on the principle of light transmission. When a laser beam of a specific wavelength is irradiated onto a plastic sample, some of the light is absorbed, some is scattered, and the remaining light passes through the plastic. The instrument precisely measures the incident light intensity and the transmitted light intensity through a high-precision light detector. For the assessment of plastic welding quality, the laser transmittance meter can sensitively detect the difference in transmittance between the welded and non-welded areas. Welding defects, such as bubbles, inclusions, and incomplete penetration, can alter the microstructure within the plastic and subsequently affect the laser transmittance. For instance, the presence of bubbles will increase light scattering, resulting in a decrease in transmittance; inclusions and foreign substances will change the light propagation path, leading to abnormal transmittance. By analyzing the changes in transmittance, the welding quality can be accurately evaluated.   II. Characteristics and Advantages of the Color Spectrum Laser Transmittance Meter TH-20   The Color Spectrum Laser Transmittance Meter TH - 200 demonstrates outstanding performance in the assessment of plastic welding quality. It features a high-precision optical detection system that enables precise measurement of laser transmittance, with a measurement accuracy of ±0.1%. This high-precision characteristic enables it to sensitively capture minute changes during plastic welding, providing a solid foundation for accurate assessment of welding quality. TH - 200 has a wide spectral measurement range, covering various commonly used laser wavelengths, and is adaptable to the needs of different plastic materials and welding processes. Whether it is used for common polypropylene (PP) plastic welding in automotive manufacturing or polycarbonate (PC) plastic welding in the electronics industry, TH - 200 can accurately measure its laser transmittance.   This instrument is easy to operate and is equipped with an intuitive user interface and automated measurement software. Operators only need to place the plastic sample at the designated position, start the measurement program, and the instrument can quickly complete the measurement and generate detailed data reports. This greatly improves the detection efficiency and is suitable for large-scale detection on production lines. In addition, TH - 200 has good stability and reliability, can operate stably in industrial production environments for a long time, reduces the frequency of equipment maintenance and calibration, and lowers the usage cost.   III. Innovative Application Methods of Laser Transmittance Meter in Plastic Welding Quality Assessment   1.Material screening and evaluation before welding   Before plastic welding, the laser transmittance of different batches of plastic raw materials is tested by using the Color Spectrum Laser Transmittance Tester TH-200. By analyzing the test data, the batches of materials whose laser transmittance meets the requirements of the welding process can be selected, ensuring the consistency and stability of the raw materials. Meanwhile, for cases where different types of plastics need to be welded, TH-200 can assist engineers in choosing plastic material combinations with matching laser transmittance, optimizing the welding process and improving the welding quality. For example, in the welding of automotive interior parts, through the testing by TH-200, selecting appropriate plastic material combinations can effectively reduce welding defects and improve the aesthetics and durability of the interior parts.   2. Real-time Monitoring of Welding Process   Integrate TH - 200 into the plastic welding equipment and monitor the real-time changes of the laser transmittance in the welding area during the welding process. When the welding process parameters fluctuate, such as unstable laser power or changes in welding speed, it will cause abnormal melting and solidification states of the plastic in the welding area, thereby leading to changes in the laser transmittance. TH - 200 can promptly capture these changes and feed back the data to the welding control system. The control system automatically adjusts the welding process parameters based on the feedback data to achieve closed-loop control of the welding process and ensure the stability of the welding quality. For example, on the welding production line of electronic device casings, by monitoring the laser transmittance in real time and adjusting the welding parameters promptly, it can effectively reduce the scrap rate and improve production efficiency.   3. Comprehensive quality inspection after welding   After the welding is completed, the laser transmittance of the welded joint is detected using TH - 200. By comparing the data with the standard data before welding and the real-time data during the welding process, it is possible to determine whether there are defects in the welded joint, such as incomplete penetration, false welding, and pores. For the quality problems detected, the causes can be further analyzed and corresponding improvement measures can be taken. In addition, TH - 200 can also indirectly evaluate the strength of the welded joint. Research shows that there is a certain correlation between the laser transmittance of the welded joint and the welding strength. By establishing a mathematical model of laser transmittance and welding strength, and using the laser transmittance data measured by TH - 200, the strength of the welded joint can be predicted, providing a more comprehensive basis for product quality assessment.   The innovative application of the color spectrum laser transmittance instrument TH - 200 in the quality assessment of plastic welding brings a new quality control method to the plastic welding industry. Through material screening before welding, real-time monitoring during the welding process, and quality detection and assessment after welding, TH - 200 can effectively improve the quality of plastic welding, reduce production costs, and enhance production efficiency. With the continuous improvement of product quality requirements in the manufacturing industry, the application prospects of laser transmittance instruments in the plastic welding field will be even broader. It will continue to promote the development of plastic welding technology and provide strong support for product innovation and quality improvement in various industries.

In the modern field of plastic processing, plastic welding, as a crucial connection technology, is widely applied in numerous industries such as automobile manufacturing, electronic equipment, and medical devices. During the plastic welding process, the measurement of light transmittance is gradually becoming an important aspect that cannot be ignored. What are the scientific basis and practical significance behind this?   The principle of plastic welding is to utilize energy sources such as heat, pressure or ultrasonic waves to make the connection parts of plastic components reach a molten state, thereby achieving molecular fusion. Among various welding methods, laser welding is favored due to its high precision, low heat-affected zone and good sealing performance. When welding plastics with laser, a laser beam needs to pass through the upper layer of plastic, which is absorbed by the lower layer and converted into heat energy, thus achieving the welding. At this time, the light transmittance becomes a key factor affecting the welding quality.   Schematic diagram of plastic welding process   Transmittance directly affects the transmission efficiency of laser energy in plastic materials. If the transmittance of the upper layer plastic is too low, the laser energy cannot effectively penetrate and reach the lower layer plastic, making it difficult to generate sufficient heat to achieve good welding. Conversely, if the transmittance is too high, it may cause the lower layer plastic to absorb insufficient energy, which also affects the welding strength. An appropriate transmittance can ensure the precise distribution of laser energy in plastic materials and achieve high-quality welding results. For example, in the welding of automotive interior parts, the requirements for welding strength and appearance quality are extremely high. Only by precisely controlling the transmittance can the welding parts be firmly and beautifully bonded, avoiding defects such as false welding and detachment. So, how can the transmittance of plastic be accurately measured? This is where the new product of Color Spectrum, the laser transmittance meter, comes into play. This instrument is specifically designed for the transmittance measurement requirements in the field of plastic welding and has many outstanding features. It uses advanced laser light sources and highly sensitive detectors to quickly and accurately measure the transmittance of various plastic materials under specific wavelength lasers. Its measurement accuracy is extremely high, capable of precisely measuring to several decimal places, greatly improving the reliability of the measurement results.   Actual measurement software interface   The Color Spectrum Laser Transmittance Meter is easy to operate and can be mastered by non-professionals. The instrument is equipped with an intuitive operation interface and a clear display screen, making the measurement data immediately understandable. Moreover, it has powerful data storage and analysis functions, capable of conducting statistical analysis on multiple measurement data, providing strong data support for the optimization of plastic welding processes. In practical applications, operators only need to place the sample to be measured on the measurement platform of the instrument and press the measurement button. Instantly, accurate transmittance data can be obtained. This convenience greatly enhances production efficiency and reduces time waste caused by cumbersome measurements.   In the plastic welding process, by using the Chroma Spectra Laser Transmittance Meter to precisely measure the transmittance, enterprises can screen and optimize plastic materials based on the measurement results. For plastics with transmittance not meeting the welding requirements, improvements can be made by adjusting the formula, adding additives, or changing the processing technology. Meanwhile, during the welding process, monitoring the changes in transmittance in real time can promptly identify potential welding problems, such as material batch differences, equipment failures, etc., and take timely measures for adjustment to ensure the stability and consistency of welding quality.   In conclusion, measuring transmittance in plastic welding is of crucial significance. It is not only a key factor in ensuring welding quality but also an important means to promote the continuous optimization and innovation of plastic welding processes. The Chroma Spectra Laser Transmittance Meter, with its advanced technology, outstanding performance, and convenient operation, provides a reliable solution for transmittance measurement in the plastic welding industry, helping enterprises improve product quality and production efficiency in the fierce market competition, and creating greater value.

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.