Design and experiment of seeding performance monitoring system for suction corn planter

Kun Liu, Shujuan Yi

Abstract


To realize the highly precise and real-time monitoring of seeding performance in suction-type corn planter, and intelligent detection technology was presented. In this monitoring system, firstly, the sensor was designed based on the photoelectric technology. Meanwhile, in order to reduce the influence of dust in the field on the photoelectric sensor, the installation position of the sensor was changed to the space under the seed plate instead of the traditional position, that is, the middle of the seed tube. Secondly, the scattering angle of the highlighting light-emitting diodes was considered to calculate the spacing of transmitters to realize non-blind area detection. Last but not least, the peak-detection algorithm was utilized to increase the detection accuracy. Therefore, after a lot of the indoor and field experiments, the analysis shows that the detection accuracy of seeding quantity can reach 98.45%, alarm delay time under abnormal circumstances is not more than 2 s. Obviously, this system can meet the requirements of seeding completely and improve its reliability greatly.
Keywords: seeding performance, monitoring system, peak-detection algorithm, photoelectric detection
DOI: 10.25165/j.ijabe.20191204.4185

Citation: Liu K, Yi S J. Design and experiment of seeding performance monitoring system for suction corn planter. Int J Agric & Biol Eng, 2019; 12(4): 97–103.

Keywords


seeding performance, monitoring system, peak-detection algorithm, photoelectric detection

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References


Wang C H, Li W G. Based on MCU control pneumatic type no-till planter monitoring system. Transactions of the CSAM, 2013; 44(51): 56–59. (in Chinese)

Ahmad A, Al-Mallahi, Kataoka Takashi. Monitoring the flow of seeds in grain drill using fiber sensor. 4th IFAC Conference on Modeling and Control in Agriculture, 2013; pp.311–314.

Qi J T, Jia H L, Li Y. Design and test of fault monitoring system for corn precision planter. Int J Agric & Biol Eng, 2015; 8(6): 13–20.

Xia L M, Wang X Y, Geng D Y, Zhang Q F. Sliding Monitoring System for Ground Wheel Based on ATMEGA16 for No-Tillage Planter—CT246. 2010 CCTA, 2011; 531–537.

Abdolahzare Z, Mehdizadeh S A. Nonlinear mathematical modeling of seed spacing uniformity of a pneumatic planter using genetic programming and image processing. Neural Computing and Applications, 2018; 29(2): 363–375.

Liu Y H. The research of electromagnetic vibrating cotton intensive cotton planting equipment. Qingdao: Shandong University of Science and Technology, 2005. (in Chinese)

Young S L, Pierce F J. Precision planting and crop thinning. Automation: The Future of Weed Control in Cropping Systems. Springer, 2013; pp.99–124.

Li D, Geng D Y, Ma B T, Li Q H, Wang Z W. Research on the performance monitoring system of maize precision planter. Agricultural Machinery Research, 2013; 35(11): 71–74. (in Chinese)

Zhao M Q, Hu Y W, Liu Y Q. Measurement and analysis on vibration characteristics of pneumatic seed metering device of no-till seeder. Transactions of the CSAE, 2012; 28(26): 78–83. (in Chinese)

Song P, Zhang J X. The real-time monitoring system for the performance of precision planter. Journal of Agricultural Machinery, 2011; 2: 71–74. (in Chinese)

Liu J Y, Liu F, Zhang P J. Design of monitoring system for air suction seeder metering device. Agricultural Machinery Research, 2015; 9: 143–146. (in Chinese)

Xia L M, Wang X Y, Geng D Y, Zhang Q F. Performance monitoring system for precision planter based on MSP430-CT171. 2010 CCTA, 2011; pp.158–165.

Li L X, Hao Z M, Yang W, Xia X Y, Wang J H. Design of seeding performance detection system for precision seeder. Agricultural Engineering, 2012; 8: 16–19. (in Chinese)

Su W, Wang F L. Study on pneumatic system of vacuum seed planter. Journal of Northeast Agricultural University, 2012; 43(5): 61–64. (in Chinese)

Zhou L M, Zhang X C, Yuan Y W. Design of capacitance seed rate sensor of wheat planter. Transactions of the CSAE, 2010; 26(10): 99–103. (in Chinese)

Liu W Z, Zhao M Q. The performance theory analysis and experiment. Transactions of the CSAE, 2010; 26(9): 133–138. (in Chinese)

Scholkmann F, Boss J, Wolf M. An efficient algorithm for automatic peak detection in noisy periodic and quasi-periodic signals. Algorithms, 2012; 5: 588–603.

Chen Y, Yang X, Liu H L. Processing FBG sensing signals with exponent modified Gaussian curve fitting peak detection method. Spectroscopy and Spectral Analysis, 2016; 36(5): 1526–1531.

Slodzinski R, Hildebrand L, Vautz W. Peak detection algorithm based on second derivative for two dimensional ion mobility spectrometry signals. Peak Detection Algorithm based on Second Derivative Properties. Springer, 2015; pp.342–354.

Bödeker B, Vautz W, Baumbach J I. Peak finding and referencing in MCC/IMS-data. International Journal for Ion Mobility Spectrometry, 2008; 11(4): 83–87.

Adam A, Ibrahim Z, Mokhtar N, Shapiai M I, Cumming P, Mubin M. Improving EEG signal peak detection using feature weight learning of a neural network with random weights for eye event-related applications. Sādhanā, 2017; 42(5): 641–653.

Rai H M, Trivedi A, Chatterjee K, Shukla S. R-peak detection using daubechies wavelet and ECG signal classification using radial basis function neural network. Journal of the Institution of Engineers, 2014; 95(1): 63–71.

Hao W N, Chen J Y. Peak position detection-based acquisition algorithm of multiple access interference resistance. China Satellite Navigation Conference (CSNC), 2016; 2: 29-46. (in Chinese)

Lomaliza J-P, Park H. Improved peak detection technique for robust PPG-based heartrate monitoring system on smartphones. Multimedia Tools and Applications, 2018; 77(13): 17131–17155.

Zhou L M, Wang S M, Zhang X C, Yuan Y W, Zhang J M. Seed monitoring system for corn planter based on capacitance signal]. Transactions of the CSAE, 2012; 28(13): 16–21. (in Chinese)




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