In order to control the quality of spline shaft in rolling process, an efficient measurement method for rolling performance evaluation is essential. Here, a newly developed on-machine non-contact measurement prototype based on laser displacement sensor and rotary encoder is proposed. The prototype is intended for the automated evaluation of the spline shaft rolling performance by measuring the dimensional change of tooth root, which is correlated with the surface residual stress and micro-hardness. Laser displacement sensor and rotary encoder are used to record the polar radius and polar angle of each point on measuring section. Data are displayed in a polar coordinate system and fitted in a gear. Through multipoint curvature method, the roots of spline shaft are recognized automatically. Then, the dimensional change can be calculated by fitting the radius of the tooth root circle before and after rolling. Systematic error covering offset error is also analyzed and calibrated. At last, measurement test results show that the system has advantages of simple structure, high measurement precision (radius error < 0.6 μm), high measurement efficiency (measuring time < 2 s) and automatic control ability, providing a new opportunity for the efficient evaluation of various spline shafts in high-precision mechanical processing.
Hong-Wei Li
,
Zhi-Qiang Liang
,
Jia-Jie Pei
,
Li Jiao
,
Li-Jing Xie
,
Xi-Bin Wang
. New Measurement Method for Spline New Measurement Method for Spline Laser Displacement Sensor[J]. Chinese Journal of Mechanical Engineering, 2018
, 31(4)
: 69
-69
.
DOI: 10.1186/s10033-018-0265-y
In order to control the quality of spline shaft in rolling process, an efficient measurement method for rolling performance evaluation is essential. Here, a newly developed on-machine non-contact measurement prototype based on laser displacement sensor and rotary encoder is proposed. The prototype is intended for the automated evaluation of the spline shaft rolling performance by measuring the dimensional change of tooth root, which is correlated with the surface residual stress and micro-hardness. Laser displacement sensor and rotary encoder are used to record the polar radius and polar angle of each point on measuring section. Data are displayed in a polar coordinate system and fitted in a gear. Through multipoint curvature method, the roots of spline shaft are recognized automatically. Then, the dimensional change can be calculated by fitting the radius of the tooth root circle before and after rolling. Systematic error covering offset error is also analyzed and calibrated. At last, measurement test results show that the system has advantages of simple structure, high measurement precision (radius error < 0.6 μm), high measurement efficiency (measuring time < 2 s) and automatic control ability, providing a new opportunity for the efficient evaluation of various spline shafts in high-precision mechanical processing.
[1] A V Guimaraesa, P C Brasileirob, G C Giovanni, et al. Failure analysis of a half-shaft of a formula SAE racing car. Case Studies in Engineering Failure Analysis, 2016, 7: 17-23.
[2] I Barsoum, F Khan, Z Barsoum. Analysis of the torsional strength of hardened splined shafts. Materials and Design, 2014, 54: 130-136.
[3] L J Shen, A Lohrengel, G Schäfer. Plain-fretting fatigue competition and prediction in spline shaft-hub connection. International Journal of Fatigue, 2013, 52: 68-81.
[4] Y J Li, W F Zhang, C H Tao. Fracture analysis of a castellated shaft. Engineering Failure Analysis, 2007, 14: 573-578.
[5] N S Rossini, M Dassisti, K Y Benyounis, et al. Methods of measuring residual stresses in components. Materials and Design, 2012, 35: 572-588.
[6] K Guptaa, R F Laubschera, P J Davimb, et al. Recent developments in sustainable manufacturing of gears: a review. Journal of Cleaner Production, 2016, 112(4): 3320-3330.
[7] Y C Zhang, J X Han, X B Fu, et al. Measurement and control technology of the size for large hot forgings. Measurement, 2014, 49: 52-59.
[8] J Rejc, U Cinkelj, M Munih. Dimensional measurements of a gray-iron object using a robot and a laser displacement sensor. Robotics and Computer-Integrated Manufacturing, 2009, 25: 155-167.
[9] Y Gao, Q Feng, J Y Cui. A simple method for dynamically measuring the diameters of train wheels using a one-dimensional laser displacement transducer. Optics and Lasers in Engineering, 2014, 53: 158-163.
[10] J H Sun, J Zhang, Z Liu. A vision measurement model of laser displacement sensor and its calibration method. Optics and Lasers in Engineering, 2013, 51: 1344-1352.
[11] C Hong, S Ibarkai. Non-contact R-test with laser displacement sensors for error calibration of five-axis machine tools. Precision Engineering, 2013, 37: 159-171.
[12] Y Kondo, K Hasegawa, H Kawamata, et al. On-machine non-contact dimension-measurement system with laser displacement sensor for vane-tip machining of RFQs. Nuclear Instruments and Methods in Physics Research A, 2012, 667: 5-10.
[13] F M Zhang, X H Qu, J F Ouyang. An automated inner dimensional measurement system based on a laser displacement sensor for long-stepped pipes. Sensors, 2012, 12: 5824-5834.
[14] Y C Tan, Z M Ripin. Technique of measuring piston secondary motion using laser displacement sensors. Experimental Mechanics, 2012, 52: 1447-1459.
[15] E S Gadelmawla. Computer vision algorithms for measurement and inspection of spur gears. Measurement, 2011, 44: 1669-1678.
[16] M A Younes, A M Khalil, M N Damir. Automatic measurement of spur-gear dimensions using laser light. Part 1: measurement of tooth thickness and pitch. Optical Engineering, 2005, 44: 1-13.
[17] P F Su, L J Wang, M Komori. Design of laser interferometric system for measurement of gear tooth flank. Optic, 2011, 122: 1301-1304.
[18] W Gao, M Furukawa, S Kiyono. Cutting error measurement of flexspline gears of harmonic speed reducers using laser probes. Precision Engineering, 2004, 28: 358-363.
[19] E J Hearn. Mechanics of materials volume 1: an introduction to the mechanics of elastic and plastic deformation of solids and structural materials. 3rd ed. Musselburgh: Butterworth-Heinemann; 1997.
[20] J H Han, T Poston. Chord-to-point distance accumulation and planar curvature: a new approach to discrete curvature. Pattern Recognition Letters, 2001, 22: 1133-1144.
