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Extrapolation of Tractor Traction Resistance Load Spectrum and Compilation of Loading Spectrum Based on Optimal Threshold Selection Using a Genetic Algorithm

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Listed:
  • Meng Yang

    (College of Engineering, Nanjing Agricultural University, Nanjing 210031, China)

  • Xiaoxu Sun

    (College of Engineering, Nanjing Agricultural University, Nanjing 210031, China)

  • Xiaoting Deng

    (College of Engineering, Nanjing Agricultural University, Nanjing 210031, China)

  • Zhixiong Lu

    (College of Engineering, Nanjing Agricultural University, Nanjing 210031, China)

  • Tao Wang

    (College of Emergency Management, Nanjing Tech University, Nanjing 210009, China)

Abstract

To obtain the load spectrum of the traction resistance of the three-point suspension device under tractor-plowing conditions, a load spectrum extrapolation method based on a genetic algorithm optimal threshold selection is proposed. This article first uses a pin force sensor to measure the plowing resistance of the tractor’s three-point suspension device under plowing conditions and preprocesses the collected load signal. Next, a genetic algorithm is introduced to select the threshold based on the Peak Over Threshold (POT) extremum extrapolation model. The Generalized Pareto Distribution (GPD) fits the extreme load distribution that exceeds the threshold range, generating new extreme points that follow the GPD distribution to replace the extreme points in the original data, achieving the extrapolation of the load spectrum. Finally, the loading spectrum that can be achieved on the test bench is obtained based on the miner fatigue theory and accelerated life theory. The results show that the upper threshold of the time-domain load data obtained by the genetic algorithm is 10.975 kN, and the grey correlation degree is 0.7249. The optimal lower threshold is 8.5455 kN, the grey correlation degree is 0.7722, and the fitting effect of the GPD distribution is good. The plowing operation was divided into five stages: plowing tool insertion, acceleration operation, constant speed operation, deceleration operation, and plowing tool extraction. A traction resistance loading spectrum that can be achieved on the test bench was developed. The load spectrum extrapolation method based on the genetic algorithm optimal threshold selection can improve the accuracy of threshold selection and achieve the extrapolation and reconstruction of the load spectrum. After processing the extrapolated load spectrum, it can be transformed into a load spectrum that can be recognized by the test bench.

Suggested Citation

  • Meng Yang & Xiaoxu Sun & Xiaoting Deng & Zhixiong Lu & Tao Wang, 2023. "Extrapolation of Tractor Traction Resistance Load Spectrum and Compilation of Loading Spectrum Based on Optimal Threshold Selection Using a Genetic Algorithm," Agriculture, MDPI, vol. 13(6), pages 1-20, May.
    • Handle: RePEc:gam:jagris:v:13:y:2023:i:6:p:1133-:d:1157885
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    References listed on IDEAS

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    Cited by:

    1. Liming Sun & Mengnan Liu & Zhipeng Wang & Chuqiao Wang & Fuqiang Luo, 2023. "Research on Load Spectrum Reconstruction Method of Exhaust System Mounting Bracket of a Hybrid Tractor Based on MOPSO-Wavelet Decomposition Technique," Agriculture, MDPI, vol. 13(10), pages 1-18, September.
    2. Zhengkai Wu & Jiazhong Wang & Yazhou Xing & Shanshan Li & Jinggang Yi & Chunming Zhao, 2023. "Energy Management of Sowing Unit for Extended-Range Electric Tractor Based on Improved CD-CS Fuzzy Rules," Agriculture, MDPI, vol. 13(7), pages 1-18, June.

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