Abstract: Buckwheat hulling detection is a key process for improving both hulling efficiency and product quality, and it plays an essential role throughout the entire buckwheat processing chain. At present, the detection of hulling performance mainly relies on manual sampling combined with visual inspection by operators. This traditional approach is not only time-consuming and labor-intensive but also highly subjective and inefficient, which severely limits the standardization, automation, and large-scale development of the buckwheat processing industry. Therefore, it is of great practical significance to develop an efficient and reliable online detection method for buckwheat hulling. To address the problems associated with difficult sampling and low detection efficiency, this study selected a 6QB-150 rubbing-type buckwheat hulling machine as the research object and designed an online detection device for buckwheat hulling. The device is mainly composed of two functional modules: a sampling mechanism and an image acquisition system. The sampling mechanism is capable of performing timed and quantitative sampling of the hulled materials during operation, ensuring representative and stable sample collection. The image acquisition system captures high-resolution images of the sampled materials, thereby providing reliable visual data for subsequent analysis of hulling performance. In order to optimize the structural parameters of the sampling mechanism, especially the discharge height, EDEM-based discrete element method (EDEM) simulations were conducted to analyze the motion behavior and spatial distribution of buckwheat particles during the sampling process. The simulation results demonstrated that the discharge height has a significant influence on particle dispersion characteristics. When the discharge height was within the range of 550–600 mm, the buckwheat particles exhibited a relatively uniform distribution, which is favorable for improving the consistency and accuracy of image acquisition. On this basis, systematic experimental studies were carried out to further evaluate the performance and rationality of the designed online detection device. A series of discharge height control experiments were conducted, in which the discharge height was used as the key influencing factor. The experimental range was set from 350 mm to 600 mm with an interval of 50 mm. For each height level, the distribution states of buckwheat samples were captured using an industrial camera. The spatial distribution uniformity of the buckwheat grains during the sampling process was quantitatively evaluated using the mean-to-variance ratio as an index. The experimental results indicated that discharge height has a pronounced effect on both the spatial distribution of particles and the quality of the captured images. As the discharge height increased, the dispersion of buckwheat grains gradually improved, leading to more uniform spatial distribution. When the discharge height was controlled within the range of 550–600 mm, the mean-to-variance ratio of the captured buckwheat images ranged from 3 to 5, indicating relatively low variability and high uniformity. Under these conditions, particle overlap and clustering were effectively reduced, which significantly enhanced the clarity and reliability of image features used for subsequent detection and analysis. Overall, this study systematically investigated the design and performance of an online detection device for buckwheat hulling. The proposed system effectively overcomes the limitations of traditional manual sampling methods, significantly improves detection efficiency and objectivity, and provides stable and high-quality image data for intelligent analysis. The results not only reveal the relationship between discharge height and image acquisition quality but also provide a theoretical basis and technical support for the optimization of sampling parameters in online detection systems. Furthermore, the research outcomes contribute to the development of intelligent and automated equipment in agricultural processing, offering important support for improving processing efficiency, ensuring product quality, increasing farmers’ income, and promoting the modernization of agriculture.