Optimization measurement method for checkweigher

• Autorzy: Ugodziński R. , Kamiński M. , Nowicki M. , Szewczyk R.
• Języki publikacji: EN

Abstrakty

EN

Abstract: The paper presents a new measurement method for checkweighers, where the measurement result is obtained by solving a simple optimization problem. The method assumes that the mass of constant geometry and a small masses spread is measured. The measurement accuracy changes as a function of noise-eliminating low-pass filter frequency was investigated. The state of knowledge about the filtration of checkweigher signal is also summarized.

Słowa kluczowe

EN

checkweigher; optimization; weighing methods; filter

• Wydawca: Wydawnictwo PAK
• Czasopismo: Measurement Automation Monitoring
• Rocznik: 2015
• Tom: Vol. 61, No. 2
• Strony: 39--42
• Opis fizyczny: Bibliogr. 13 poz., rys., wykr., wzory

Twórcy

autor

Ugodziński R.

• Industrial Research Institute for Automation and Measurements, Al. Jerozolimskie 202, 02-486 Warsaw

autor

Kamiński M.

• Industrial Research Institute for Automation and Measurements, Al. Jerozolimskie 202, 02-486 Warsaw

autor

Nowicki M.

• Warsaw University of Technology, Faculty of Mechatronics, sw. A. Boboli 8, 02-525 Warsaw

autor

Szewczyk R.

• Industrial Research Institute for Automation and Measurements, Al. Jerozolimskie 202, 02-486 Warsaw

Bibliografia

• [1] Maier R., Schmidt G.: Integrated digital control and filtering for an electrodynamically compensated weighing cell. IEEE Transactions on Instrumentation and Measurement 38(5) (1989), p. 998–1003.
• [2] Kaszyński R., Piskorowski J.: Selected structures of filters with time-varying parameters. IEEE Transactions on Instrumentation and Measurement 56 (6) (2007), p. 2338–2345.
• [3] Pietrzak P., Meller M., Niedzwiecki M.: Dynamic mass measurement in checkweighers using a discrete time-variant low-pass filter. Mechanical Systems and Signal Processing 48 (2014), p 67-76.
• [4] Piskorowski J., Barcinski T.: Dynamic compensation of load cell response: a time-varying approach. Mechanical Systems and Signal Processing 22 (2008), p. 1694–1704.
• [5] Halimic M., Balachandran W.: Kalman filter for dynamic weighing system. Proc. IEEE ISIE, vol. 2, 10-14 1995, p. 786–791.
• [6] Alhoseyni S. M. T., Yasin A., White, N. M.: The application of artificial neural network to intelligent weighing systems. Science, Measurement and Technology IEEE Proceedings 146 (1999), p. 265–269.
• [7] Bahar H. B., Horrocks D. H. Dynamic weight estimation using an artificial neural network. Artificial Intelligence in Engineering 12 (1998), p. 135-139.
• [8] Hernandez W.: Improving the response of a load cell by using optimal filtering recursive least-squares (RLS) lattice algorithm to perform adaptive filtering. Sensors 6 (2006), p. 697–711.
• [9] Yamazaki T., Sakurai Y., Ohnishi H., Kobayashi M.: Continuous mass measurement in checkweighers and conveyor belt scales. Proceedings of the 41st SICE Annual Conference (2002), vol. 1, p. 470–474.
• [10] Tasaki R., Yamazaki T., Ohnishi H., Kobayashi M., Kurosu, S.: Continuous weighing on a multi-stage conveyor belt with fir filter, Measurement, vol. 40, no. 7-8 (2007), p. 791–796.
• [11] Fukuda K., Yoshida K., Kinugasa T., Kamon M., Kagawa Y., Ono T.: A new method of mass measurement for checkweighers. Metrology and Measurement Systems XVII (2) (2010), pp. 151–162.
• [12] http://www.radwag.pl/pl/nowe-wagi-automatyczne-dwm,4,401-103
• [13] Bazydło P., Urbański M., Kamiński M., Szewczyk R.: Influence of the Environment on Operation of Checkweigher in Industrial Conditions. Advances in Intelligent Systems and Computing vol. 267, 2014, pp. 567-577.