Anti-interference method and device for intelligent multi-span greenhouse substrate weighing system

By integrating visual morphological features with weight time-series data, the system identifies and compensates for non-physiological interference, solving the data distortion problem caused by the tipping of vines in climbing crops and achieving high reliability and accuracy of the intelligent multi-span greenhouse substrate weighing system.

CN122329463APending Publication Date: 2026-07-03INTELLIGENT EQUIPMENT RESEARCH CENTER BEIJING ACADEMY OF AGRICULTURE AND FORESTRY SCIENCES
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-03-25
Publication Date
2026-07-03

AI Technical Summary

Technical Problem

Existing intelligent multi-span greenhouse substrate weighing systems suffer from data distortion due to non-physiological interference caused by the falling of vines in climbing crops. Traditional filtering algorithms and fixed threshold methods are unable to effectively distinguish between physiological and non-physiological interference, leading to inaccurate irrigation decisions.

Method used

By acquiring visual morphological features and weight time-series data of vine crops, fusing multimodal data representation, identifying and compensating for non-physiological interference, generating corrected weight time-series data, and using a visual transformer and a spatiotemporal dual-stream Transformer network for data fusion, and combining the water absorption characteristics of vine crops and a neural constant differential equation model for interference compensation.

Benefits of technology

It overcomes the blind spots of a single sensor, improves the reliability of weighing data, avoids false alarms of physiological signals, and ensures the accuracy of irrigation decisions.

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Abstract

This application provides an anti-interference method and device for an intelligent multi-span greenhouse substrate weighing system, relating to the field of agricultural data processing technology. The method includes: acquiring visual morphological features of vine-like crops and time-series weight data of the substrate; the visual morphological features include the inclination angle of the vine-like crops' stems and the contact state between the stems and the substrate; fusing the visual morphological features and the weight time-series data to obtain a multimodal data representation; identifying non-physiological interferences in the weight time-series data based on the multimodal data representation; and compensating for the identified non-physiological interferences to generate corrected weight time-series data. This application overcomes the perception blind spot of a single sensor, endowing the weighing system with intuitive perception capabilities of interference sources, avoiding the false rejection of useful physiological signals by traditional filtering algorithms, and significantly improving the reliability of weighing data.
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