Abstract
In order to ensure the working performance of the seeder, reduce the labor intensity of manual testing, and improve the efficiency and accuracy of the detection, a real-time detection system for detecting the performance of no-till seeders was designed based on the LabVIEW software platform of virtual instrument technology and the MCC USB-231 data acquisition card. The detection system can be used to detect the seeding quality index and residue cover index. The detection of the seeding quality index included the middle detection between the metering device and the opener, the end detection between the opener and the furrow. The result of the field test showed that the detection accuracies of seed quantity, multiple index, and miss index were 94.51%, 92.83%, and 91.81%, respectively. The fault position can be accurately determined, and the measurement accuracy of residue cover index was 94.54%. The working performance of the no-tillage seeder can be monitored by the detection system to avoid the occurrence of reseeding and miss-seeding and improve production efficiency. Keywords: LabVIEW, no-tillage seeder, seeding quality, real-time detection, residue cover index DOI: 10.25165/j.ijabe.20211405.6208 Citation: Zhu H B, Qian C, Guo Z H, Bai L Z. Design of the real-time detection system based on LabVIEW for no-till seeder working performance. Int J Agric & Biol Eng, 2021; 14(5): 100–106.
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Claims 5
Claim · model-written summary
The system detected seed quantity with 94.51% accuracy in the field test.
Not reportedTaxon
Verbatim
e0“The result of the field test showed that the detection accuracies of seed quantity, multiple index, and miss index were 94.51%, 92.83%, and 91.81%, respectively.”
Claim · model-written summary
The system detected the multiple index with 92.83% accuracy in the field test.
Not reportedTaxon
Verbatim
e0“The result of the field test showed that the detection accuracies of seed quantity, multiple index, and miss index were 94.51%, 92.83%, and 91.81%, respectively.”
Claim · model-written summary
The system detected the miss index with 91.81% accuracy in the field test.
Not reportedTaxon
Verbatim
e0“The result of the field test showed that the detection accuracies of seed quantity, multiple index, and miss index were 94.51%, 92.83%, and 91.81%, respectively.”
Claim · model-written summary
The system accurately determined fault position.
- Outcome
- fault positione0
Not reportedComparator
Verbatim
e0“The fault position can be accurately determined, and the measurement accuracy of residue cover index was 94.54%.”
Claim · model-written summary
The system measured residue cover index with 94.54% accuracy.
Verbatim
e0“The fault position can be accurately determined, and the measurement accuracy of residue cover index was 94.54%.”