Research on Grey Prediction of Electromagnetic Relay Contact Resistance

Abstract:

When the relay contacts are switched on the load circuit, contact pairs on-state directly reflects the relays reliability, and it also indirectly reflects machine performance of the relay. Therefore, the static contact resistance is one of the key features of the relays state estimation and failure warning. However, the contact resistance of the relay contact is uncertainty characteristics, small-scale sequence trend model is difficult to obtain an ideal prediction performance, and therefore grey model which based on small-scale sequence for prediction of electrical contact reliability of the relay is drawn on. Using the static contact resistance measurement value of the relay contact resistance as training samples to set up GM (1, 1) model and obtaining development grey number a and endogenous control grey number b by least square method, so as to get differential equation of original datas predicted value and then forecast the original data. In order to improve the prediction accuracy and weaken the influence of randomness, sliding smoothing formula to the original data is used to get improved prediction model. By comparing the difference between the accuracy of improved model and not improved model, it concludes that the improved model has possibility and accuracy higher.

• Periodical: Applied Mechanics and Materials (Volume 392)
• Pages: 667-671
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.392.667
• Online since: September 2013
• Authors: Xiao Jing Yang, Fang Yao, Zhi Gang Li, Xue Bo Feng
• Keywords: Electromagnetic Contact Resistance, Error Check, Grey Model, Improved Technology

References

[1] Deng Julong. Grey theory [M]. Wu han: Huazhong University of Science and Technology Press, (2002).

[2] Liu SifengDang YaoguoFang Zhigeng etal. Gray system theory and its application [M]. Beijing: Science Press, (2010).

[3] Yang XiaohongLiang ShuhuaWang Xianhuiet al. Effect of WC and CeO2 on microstructure and properties of W-Cu electrical contact material[J]. Int . Journal of Refractory Metals & Hard Materials201028：305 -311.

DOI: 10.1016/j.ijrmhm.2009.11.009

[4] HSU Li changWANG Chao hung. Forecasting integrated circuit output using multivariate grey model and grey relational analysis [J]. Expert Systems with Applications, 200936：1403 -1409.

DOI: 10.1016/j.eswa.2007.11.015

[5] TIEN Tzuli. The deterministic grey dynamic model with convolution integral DGDMC(1, n)[J]. Applied Mathematical Modelling200933：3498-3510.

DOI: 10.1016/j.apm.2008.11.012

[6] TRIVEDI H VSINGH J K. Application of grey system theory in the development of a runoff prediction model[J]. Biosystems Engineering200592(4)：521-526.

DOI: 10.1016/j.biosystemseng.2005.09.005

[7] HSU Li changWANG Chao hung. Forecasting integrated circuit output using multivariate grey model and grey relational analysis [J]. Expert Systems with Applications, 200936：1403 -1409.

DOI: 10.1016/j.eswa.2007.11.015

[8] Zhang LinXia Xintao. Application and Prospect of grey system theory in rolling bearing[J]. Modern Manufacturing Engineering2008（8）：128-131.

[9] Xia XintaoZhang Lin. Grey theory analysis of rolling bearing vibration and machining quality[J]. Bearig2009（1）：24-26.