A method for identifying seedling aerial seeding density based on a pneumatic launcher

By acquiring signal amplitude and constructing waveform mapping path in the pneumatic launcher, obtaining flow characteristic vector, and adjusting decision vector, the problem of inaccurate counting of non-spherical seeds in pneumatic conveying aerial seeding devices under high throughput conditions is solved, and adaptive and accurate measurement of seeding density is achieved.

CN121786609BActive Publication Date: 2026-05-26陕西省林业科学院
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
陕西省林业科学院
Filing Date
2026-03-05
Publication Date
2026-05-26

AI Technical Summary

Technical Problem

Existing pneumatic conveyor aerial seeding devices have difficulty accurately counting non-spherical seeds, especially winged seeds, under high throughput conditions, resulting in false counts and missed counts.

Method used

By acquiring the signal amplitude of the pneumatic launcher in real time, determining the upstream and downstream observation sequences of the event, constructing a waveform mapping path, obtaining the flow characteristic vector, dividing the start-up and running segments, adjusting the decision vector, quantifying the particle count increment, and achieving adaptive and accurate measurement of seeding density.

Benefits of technology

In a high-throughput aerodynamic seeding environment, accurate identification of single seeds and clusters was achieved, overcoming counting distortion caused by seed wing tumbling noise and cluster overlap, and ensuring accurate measurement of seeding density.

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Abstract

This invention relates to the field of seed counting technology, specifically to a method for identifying seedling aerial seeding density based on a pneumatic launcher. The invention determines the flow characteristic vector based on the degree of trajectory deviation and morphological residual of the waveform mapping path between the upstream and downstream observation sequences of passing events; it divides the device's operating period into a start-up period and a running period; based on the flow characteristic vector of the preceding passing event for each passing event within the running period, it adjusts the classification criterion of the flow characteristic vector of passing events within the start-up period to determine single-seed and cluster feature decision vectors; based on the deviation of the flow characteristic vector of passing events within the running period from the single-seed and cluster feature decision vectors, it determines the seed count increment and calculates the total seeding amount. This invention comprehensively integrates the microscopic motion characteristics and waveform morphology characteristics of seeds to accurately classify single seeds and clusters, improving the accuracy of seed measurement.
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