Deep learning-based raw coffee impurity and defect intelligent detection system

Abstract

The invention discloses an intelligent detection system for impurities and defects of raw coffee based on deep learning. The intelligent detection system comprises a visual detection module, a smell detection module, an optical detection module, a data management module, a data output system and a display device, the visual inspection is used for observing the surface of the raw coffee; the smell detection is used for detecting the taste of the raw coffee; and optical detection, which is used for analyzing and measuring the material composition and structure of the raw coffee and detecting whether foreign matters are contained in the coffee beans. According to the intelligent raw coffee impurity and defect detection system based on deep learning, the image processing module is arranged, images can be detected in all directions, the images are segmented through an image separation algorithm, the processing efficiency can be improved, meanwhile, the data management module can store and classify data, an independent database can be established, and the detection accuracy is improved. The coffee beans can be detected more accurately through internal data, and the detection effect of the device can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of green coffee detection, and specifically to an intelligent detection system for impurities and defects in green coffee based on deep learning. Background Technique

[0002] Green coffee refers to unroasted coffee beans. Green coffee beans are usually green, have a certain hardness and moisture content. Green coffee is the initial raw material in the coffee industry chain. After subsequent processing such as roasting, it can become drinkable coffee. In order to ensure the quality of green coffee, remove impurities and defects, and improve the quality of the final coffee product, it is necessary to detect the impurities and defects in green coffee through an intelligent detection system. An intelligent detection system is a system that uses advanced technologies and algorithms to automatically detect, analyze, and judge specific objects. The intelligent detection system can complete the detection process automatically without manual intervention. At the same time, the intelligent detection system uses advanced detection technologies to ensure the accuracy of the detection results. In the detection of impurities and defects in green coffee, the intelligent detection system can efficiently and accurately identify impurities and defects, improving production quality and efficiency. However, when the existing intelligent detection systems are in use, they cannot perform in-depth detection, the detection efficiency is low, and at the same time, they cannot adjust the detected data and standards according to the detection, making them inconvenient to use. Summary of the Invention

[0003] The purpose of the present invention is to provide an intelligent detection system for impurities and defects in green coffee based on deep learning, so as to solve the problems put forward in the above background technique that in-depth detection cannot be performed, the detection efficiency is low, and at the same time, the detected data and standards cannot be adjusted according to the detection, making it inconvenient to use.

[0004] To achieve the above purpose, the present invention provides the following technical solution: An intelligent detection system for impurities and defects in green coffee based on deep learning, including visual detection, odor detection, optical detection, a data management module, a data output system, and a display device;

[0005] Visual detection, which is used to observe the surface of green coffee;

[0006] Odor detection, which is used to detect the smell of green coffee;

[0007] Optical detection, which is used to analyze and measure the material composition and structure of green coffee, and detect whether there are foreign objects in the coffee beans;

[0008] The data output system, which is used to integrate and analyze the results of visual detection, odor detection, and optical detection, and compare the detection results with standard data through this;

[0009] The display device, which is used to display the data generated by the comparison;

[0010] A data management module, which is used to store and integrate the generated data, providing a basis for visual inspection, odor detection, and optical detection.

[0011] Preferably, the visual inspection includes: an image acquisition device and an image processing module. The green coffee is photographed by the image acquisition device to extract the appearance data of the green coffee. The image acquisition device transmits the picture to the image processing module, and at the same time, the image processing module can analyze the coffee beans inside the picture.

[0012] Preferably, the odor detection includes: a gas collection device and an odor detector. The taste of the green coffee is collected by the gas collection device, and at this time, the odor detector detects and analyzes the taste components.

[0013] Preferably, the optical detection includes: a comparative analysis module and a spectral analysis device. The spectral analysis device can irradiate the green coffee to detect whether the substances inside the green coffee are the same. At the same time, the spectral analysis device transmits the information to the comparative analysis module, and the comparative analysis module analyzes whether there are impurities inside the green coffee.

[0014] Preferably, the data output system can transmit the detected data to the inside of the data management module. At this time, the data management module can provide a basis for visual inspection, odor detection, and optical detection.

[0015] Preferably, the data output system can transmit the generated data to the display device, and the data is displayed through the display device.

[0016] Preferably, the image processing module includes: an image segmentation algorithm, a data recognition algorithm, and a feature extraction algorithm. The image segmentation algorithm performs segmentation and observation on the image. The data recognition algorithm can monitor the shape, color, and texture of the extracted green coffee, and the feature extraction algorithm classifies and identifies the extracted features.

[0017] Compared with the prior art, the beneficial effects of the present invention are: The intelligent detection system for impurities and defects of green coffee based on deep learning:

[0018] 1. An image processing module is set up, which can perform comprehensive detection on the picture. The picture is segmented and processed by the image segmentation algorithm, which can improve the processing efficiency. At the same time, the data management module can store and classify the data, establish an independent database, which is convenient for more accurate detection of coffee beans through internal data, and can improve the detection effect of the device;

[0019] 2. Visual detection, odor detection, and optical detection are set up. By using different devices to detect green coffee, the detection accuracy can also be improved. Green coffee can be detected by its appearance, and odor detection can be carried out to detect it by the smell of green coffee to determine whether the green coffee has deteriorated. Statistical optical detection can be used to check whether there are impurities inside the green coffee, and it can be detected comprehensively. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 Schematic diagram of the detection component structure of the present invention;

[0021] Figure 2 Schematic diagram of the detection process structure of the present invention;

[0022] Figure 3 Schematic diagram of the internal structure of the image processing module of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0023] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0024] Please refer to Figures 1 - 3 , the present invention provides a technical solution: an intelligent detection system for impurities and defects in green coffee based on deep learning, including visual detection, odor detection, optical detection, a data management module, a data output system, and a display device;

[0025] Visual detection, which is used to observe the surface of green coffee;

[0026] Odor detection, which is used to detect the smell of green coffee;

[0027] Optical detection, which is used to analyze and measure the material composition and structure of green coffee and detect whether there are foreign substances in coffee beans;

[0028] The data output system, which is used to integrate and analyze the results of visual detection, odor detection, and optical detection, and compare the detection results with standard data through this;

[0029] The display device, which is used to display the data generated by the comparison;

[0030] The data management module, which is used to store and integrate the generated data and provide a basis for visual detection, odor detection, and optical detection.

[0031] Raw coffee can be placed in a container. At this time, visual inspection can take pictures of the raw coffee and detect the appearance of the raw coffee. At the same time, odor detection can collect and detect the odor of the raw coffee, detect the taste of the raw coffee, and detect whether the outer layer of the raw coffee has deteriorated. At the same time, optical detection irradiates the raw coffee through a spectral analysis device, and detects the close relationship of the raw coffee through the spectral analysis device, and detects whether there are impurities inside the raw coffee. By using these three devices to detect the raw coffee at the same time, the efficiency of raw coffee detection can be improved. After visual inspection, odor detection, and optical detection are completed, the generated data can be transmitted to the inside of the data output system. Through the data output system, multiple data can be processed and integrated, and the result of raw coffee detection can be obtained. The data output system can transmit the detection result to the inside of the display device, and the detected data can be displayed through the display device for the convenience of the user to view. At the same time, the data output system transmits the data to the inside of the data management module. Through the data management module, the detected information is stored and analyzed, and the historical data is analyzed and processed at the same time. At the same time, the data management module transmits the data to the inside of visual inspection, odor detection, and optical detection, so that the data management module can adjust the inspection conditions of the three, and adjust the detection standards of visual inspection, odor detection, and optical detection according to the particularity of the raw coffee.

[0032] The visual inspection includes: an image acquisition device and an image processing module. The raw coffee is photographed by the image acquisition device, and the appearance data of the raw coffee is extracted to generate a picture by the image acquisition device. The image acquisition device transmits the picture to the image processing module, and at the same time, the image processing module can analyze the coffee beans inside the picture;

[0033] The image acquisition device can photograph the appearance of the raw coffee and collect the data of the raw coffee. At this time, the photographed picture is transmitted to the inside of the image processing module. The picture is processed by the image processing module, and the raw coffee inside the picture is detected to detect whether the appearance of the raw coffee is damaged. After the image processing module completes the detection, the data can be transmitted to the inside of the data output system, and this data is analyzed by the data output system.

[0034] The odor detection includes: a gas collection device and an odor detector. The taste of the raw coffee is collected by the gas collection device, and at this time, the odor detector detects and analyzes the taste components;

[0035] The gas collection device can detect the taste of green coffee, while the odor detector can detect the odor collected by the gas collection device to check whether the odor has deteriorated, verify whether the taste of the green coffee is similar to that of conventional green coffee, and detect whether the taste of the green coffee is normal. After the odor detector finishes the detection, it can transmit the data to the inside of the data output system, and the data output system analyzes this data.

[0036] The optical detection includes: a comparison analysis module and a spectral analysis device. The spectral analysis device can irradiate the green coffee to detect whether the substances inside the green coffee are the same. At the same time, the spectral analysis device transmits the information to the comparison analysis module, and the comparison analysis module analyzes whether there are impurities inside the green coffee.

[0037] The spectral analysis device can irradiate the green coffee to detect whether there are impurities inside the green coffee. At the same time, the spectral analysis device transmits the sensed information to the inside of the comparison analysis module, and the comparison analysis module conducts a confirmation analysis on the green coffee. At this time, the comparison analysis module transmits this data to the inside of the data output system, and the data output system analyzes this data.

[0038] The data output system can transmit the detected data to the inside of the data management module. At this time, the data management module can provide a basis for visual detection, odor detection, and optical detection.

[0039] The data output system transmits the data to the inside of the data management module. The data management module archives the generated data and at the same time analyzes and processes the data to change the standard.

[0040] The data output system can transmit the generated data to the display device, and the display device displays the data.

[0041] The display device can display the detected data, which is convenient for users to distinguish the green coffee in the picture.

[0042] The image processing module includes: an image segmentation algorithm, a data recognition algorithm, and a feature extraction algorithm. The image segmentation algorithm conducts a segmented observation of the image. The data recognition algorithm can monitor the shape, color, and texture of the extracted green coffee. The feature extraction algorithm classifies and identifies the extracted features.

[0043] The image segmentation algorithm can segment the image to facilitate the detection of raw coffee in different areas, reduce repeated inspections, improve inspection efficiency, and facilitate the location of impurities. The feature extraction algorithm can extract the texture and features on the surface of the raw coffee to determine whether there are impurities on its surface. At the same time, the data recognition algorithm can classify and identify the data generated by the feature extraction algorithm to determine whether the raw coffee contains defects.

[0044] Working principle: When using the deep learning-based intelligent detection system for impurities and defects in green coffee, a data management module, a data output system and a display device are set up, which can enable more accurate detection of coffee beans, while improving the detection effect of the device and increasing its overall practicality.

[0045] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. Intelligent detection system for impurities and defects in green coffee based on deep learning, characterized by: It includes visual detection, odor detection, optical detection, data management module, data output system and display device; Visual inspection, which is used to observe the surface of green coffee; Odor detection, which is used to detect the taste of green coffee; Optical testing, which is used to analyze and measure the material composition and structure of green coffee and detect whether there are foreign objects in the coffee beans; Data output system, which is used to integrate and analyze the visual detection, odor detection, and optical detection results, and compare the detection results with standard data; A display device, which is used to display the data generated by the comparison; The data management module is used to store and integrate the generated data to provide a basis for visual inspection, odor inspection and optical inspection.

2. The deep learning-based intelligent detection system for green coffee impurities and defects according to claim 1, characterized in that: The visual inspection includes: an image acquisition device and an image processing module. The image acquisition device is used to photograph the green coffee and extract the appearance data of the green coffee. The image acquisition device transmits the picture to the image processing module, and the image processing module can analyze the coffee beans in the picture.

3. The deep learning-based intelligent detection system for green coffee impurities and defects according to claim 1, characterized in that: The odor detection includes: a gas collection device and an odor detector. The gas collection device is used to collect the smell of the green coffee, and the odor detector is used to detect and analyze the flavor components.

4. The deep learning-based intelligent detection system for green coffee impurities and defects according to claim 1, characterized in that: The optical detection includes: a comparison analysis module and a spectrum analysis device. The spectrum analysis device can irradiate the green coffee to detect whether the substances inside the green coffee are the same. At the same time, the spectrum analysis device transmits information to the comparison analysis module, and the comparison analysis module is used to analyze whether there are impurities inside the green coffee.

5. The deep learning-based intelligent detection system for green coffee impurities and defects according to claim 1, characterized in that: The data output system can transmit the detected data to the inside of the data management module, and the data management module can improve the detection basis for visual detection, odor detection and optical detection.

6. The deep learning-based intelligent detection system for green coffee impurities and defects according to claim 1, characterized in that: The data output system can transmit the generated data to a display device, and display the data through the display device.

7. The deep learning-based intelligent detection system for green coffee impurities and defects according to claim 2, characterized in that: The image processing module includes: an image segmentation algorithm, a data recognition algorithm and a feature extraction algorithm. The image segmentation algorithm is used to segment and observe the image. The data recognition algorithm can monitor the shape, color and texture of the extracted green coffee. The feature extraction algorithm is used to classify and identify the extracted features.

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