A method for linking tillage implement condition identification with soil compaction and remediation

By standardizing and nonlinearly correcting the data from tillage machinery operations, and utilizing force-curvature coupling energy and viscous rheology assessment, the problem of misjudgment in soil condition identification was solved, enabling precise tillage depth and hydraulic control, and improving operational safety and soil remediation effectiveness.

CN121657429BActive Publication Date: 2026-05-26JILIN ACAD OF AGRI SCI
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Patent Information

Authority / Receiving Office
CN Β· China
Patent Type
Patents(China)
Current Assignee / Owner
JILIN ACAD OF AGRI SCI
Filing Date
2026-02-09
Publication Date
2026-05-26

AI Technical Summary

Technical Problem

Existing technologies cannot effectively distinguish between true high resistance due to compaction and true high resistance due to wet adhesion in soil condition identification, leading to malfunctions in tillage depth control, increasing the risk of tractors slipping and getting stuck, and increasing fuel consumption.

Method used

By collecting operational data from tillage machinery and performing standardized preprocessing, the Euclidean distance is corrected using force-curvature coupling energy assessment and viscous rheological asymmetry assessment to obtain working condition category labels and perform differentiated control of tillage depth and hydraulic pressure.

Benefits of technology

It improves the accuracy of soil condition identification, reduces the risk of tractors slipping and getting stuck and fuel consumption, and enhances soil remediation efficiency and operational economy.

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Abstract

This invention relates to the field of agricultural regulation, and particularly to a method for linking tillage implement condition identification with soil compaction remediation. The method includes: collecting real-time multi-source sensor data during tillage implement operation; obtaining a force-curvature coupling energy factor by performing force-curvature coupling energy assessment and relative difference normalization modulation on a zero-mean resistance data sequence; obtaining a viscous rheological asymmetry factor by performing energy asymmetry ratio assessment and logarithmic difference amplification modulation on a zero-mean resistance data sequence during loading and unloading processes; obtaining operating condition category labels by jointly correcting the basic Euclidean distance and performing clustering; and obtaining a linkage control command for tillage depth and hydraulic pressure by mapping the operating condition category labels to differentiated control strategies for tillage depth and hydraulic pressure. This addresses the problem that existing Euclidean distance clustering cannot distinguish between true high resistance due to compaction and false high resistance due to wet adhesion, leading to malfunctions in tillage depth control.
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