A multi-sensor-based grain processing quality monitoring method

By employing a hierarchical and progressive anomaly determination mechanism based on multi-sensor collaborative monitoring and dynamic threshold adjustment, the problem of low traceability accuracy and misjudgment in existing grain processing monitoring systems has been solved. This enables accurate identification and attribution of rice processing quality anomalies, improving the reliability and response speed of monitoring.

CN122193522APending Publication Date: 2026-06-12BEIJING LENONG JIAHE AGRICULTURAL TECHNOLOGY CO LTD
View PDF 1 Cites 0 Cited by

Patent Information

Authority / Receiving Office
CN Β· China
Patent Type
Applications(China)
Current Assignee / Owner
BEIJING LENONG JIAHE AGRICULTURAL TECHNOLOGY CO LTD
Filing Date
2026-03-30
Publication Date
2026-06-12

AI Technical Summary

Technical Problem

Existing grain processing monitoring systems rely on offline sampling, which makes it easy to miss sudden quality fluctuations and prevents timely intervention. Furthermore, the independent nature of various test data leads to low accuracy in tracing the causes of anomalies, frequent misjudgments, and the inability to dynamically adjust the preset indicator database, resulting in decreased monitoring reliability.

Method used

By employing multi-sensor collaborative monitoring and integrating parameters such as rice whiteness value, vibration velocity, object distance drift, and grain count deviation rate, a hierarchical progressive anomaly judgment mechanism with dynamic threshold adjustment is constructed. This mechanism is then cross-validated using historical data and embryo retention rate to dynamically adjust the whiteness value range.

Benefits of technology

It enables accurate identification and attribution of abnormal rice processing quality, eliminates the influence of dimensional and environmental fluctuations, avoids false alarms, adaptively optimizes monitoring logic, and improves the accuracy and response speed of tracing the cause of abnormalities.

✦ Generated by Eureka AI based on patent content.

Smart Images

  • Figure CN122193522A_ABST
    Figure CN122193522A_ABST
Patent Text Reader

Abstract

The present application relates to the technical field of grain processing, and particularly relates to a grain processing quality monitoring method based on multiple sensors, which comprises the following steps: whiteness monitoring; abnormality index calculation; abnormality type positioning; and sensitivity feedback. Through multiple sensor cooperative monitoring and statistical analysis, the present application realizes accurate identification and attribution of rice processing quality abnormalities. By further introducing parameters such as equipment vibration, object distance drift and particle count deviation rate, and combining historical data benchmarks for standardized processing, the abnormality determination is more robust, and the true process quality fluctuation caused by equipment vibration and rice grain stacking can be effectively distinguished from the measurement distortion, thereby avoiding false alarms caused by sensor interference. Through statistical observation of the occurrence frequency of various abnormalities within an observation period, the tolerance of the whiteness threshold value is dynamically adjusted, and the problem of low accuracy of abnormality cause tracing and slow response speed caused by the relative independence of various detection data is effectively solved.
Need to check novelty before this filing date? Find Prior Art