Journal of Sensor Science and Technology (센서학회지)

The Korean Sensors Society (한국센서학회)
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Acceleration Sensor Based Measurement and Noise Reduction of Dynamic Weights

가속도 센서에 기반한 동하중의 측정 및 잡음 감소

  • Na, Seung-You (Dept. of Electronics and Computer Engineering, Chonnam National University) ;
  • Shin, Dae-Jung (Dept. of Electronics and Computer Engineering, Chonnam National University)
  • 나승유 (전남대학교 컴퓨터공학과) ;
  • 신대정 (전남대학교 컴퓨터공학과)
  • Published : 2004.01.30
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Abstract

Due to various types of errors added to dynamic weight measurement data, proper methods to reduce measurement errors are required to produce reliable weights. To cope with parasitic types of errors in real systems, information provided by the various sensors is utilized and combined in such a way to reduce the measurement errors of load cells. In addition to four channels of load cells from a trailer, an accelerometer is used to obtain the information to compensate the error induced from vertical movement of the vehicle due to the variation of ground level. A model trailer system is run to verify the effectiveness of the proposed method to reduce noise of dynamic weight measurements. Experiments show that the processed error magnitudes of less than 20 g can be obtained for 10 Kg experimental loads.

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References

  1. S. Blackmore and C. Marshall, 'Yield mapping; errors and algorithms,' 3rd International Conference on Precision Agriculture, 1996
  2. P.N. Wheeler, R.J. Godwin, C.D. Watt, and B.S. Blackmore, 'Trailer based yield mapping,' 1st European Conference on Precision Agriculture, 1997
  3. M.J. Krumpelman and K.A. Sudduth, 'Design and analysis of a grain weighing system,' 2000 ASAE Annual International Meeting, 2000
  4. W.Q. Shu, 'Dynamic weighing under non-zero initial conditions,' IEEE Transactions on Instrumentation and Measurement, vol. 42, no. 4, pp. 806-811, 1993 https://doi.org/10.1109/19.234489
  5. M. Danaci and D.H. Horrocks, 'A nonlinear regression technique for improved dynamic weighing,' Proceedings of the European conference on Circuit Theory and Design, Istanbul, Turkey, pp. 507-510, August 1995
  6. H.B. Bahar and D.H. Horrocks, 'Dynamic weight estimation using and artificial neural network,' Artificial Intelligence in Engineerins, pp. 135-139, 1998
  7. P. Lingman and B. Schmidtbauer, 'Road slope and vehicle mass estimation using Kalman filtering,' Proc. of the IAVSD Symposium 2001, Copenhagen.