Abstract
A piston is an important part of an engine. Its shape is designed into middle-convex and varying ellipse (MCVE) to adapt to the complex working environment. The main requirements of MCVE piston machining are high frequency response, small range tool motion, and high precision. In this article, an MCVE data model is established for the piston profile design, and the turning principle and control procedure are discussed to develop a fast tool servo (FTS) system for piston turning. In the end, back propagation neural network (BPNN) and genetic algorithm (GA) are combined to optimize the process parameters in the MCVE piston machining, which includes general turning parameters and special MCVE turning parameters. Through the experiments and BPNN-GA optimization, the ellipticity error (E) and surface roughness (Ra) of all pistons met the design requirements. According to verification experiments, the optimization results of E and Ra are 3.04 and 1.204 μm, respectively, and their relative errors are 10.13 and 4.27%, respectively. It has been proved that the MCVE data model and the control design of FTS are feasible and can effectively produce MCVE piston; the BPNN-GA optimization method is obviously effective and can improve processing effect and machining efficiency.
Similar content being viewed by others
References
Wu H , Li G ,Shi D , Zhang C (2007) Realization of CNC system on middle-convex and varying oval piston machining. Advanced design and manufacture to gain a competitive edge, pp 1586–1594
Zheng D (2014) Research on Derived CNC Lathe System for Large-Sized Non-circular Middle-convex and Varving Oval Piston, Ph.D. Thesis, China Agricultural University
Xie ST, Guo YB, Yang QQ, Chen LS (2009) Research on the shaping approach for non-cylinder piston turning. International Conference on Measuring Technology & Mechatronics Automation 3:129–132
Jiang S, Jiang S (2001) Study on the high performance linear servo system for middle-convex and varying ellipse piston machining. Chin J Mech Eng 37(04):58–61
Wu D, Chen K, Wang X (2009) An investigation of practical application of variable spindle speed machining to noncircular turning process. Int J Adv Manuf Technol 44(44):1094–1105
Wang HF, Yang S (2013) Design and control of a fast tool servo used in noncircular piston turning process. Mech Syst Signal Process 36(1):87–94
Wu D, Chen K (2010) Chatter suppression in fast tool servo-assisted turning by spindle speed variation. Int J Mach Tool Manu 50(12):1038–1047
Zhou H, Henson B, Wang X (2005) Extracted control approach for cnc non-circular turning. Asian Journal of Control 7(1):50–55
Sosnicki O, Pages A, Pacheco C, Maillard T (2010) Servo piezo tool spt400mml for the fast and precise machining of free forms. Int J Adv Manuf Technol 47(9):903–910
Ma HQ, Tian J, Hu D (2013) Development of a fast tool servo in noncircular turning and its control. Mech Syst Signal Process 41(1):705–713
Felter CL, Volund A, Imran T, Klit P (2010) Development of a model capable of predicting the performance of piston ring-cylinder liner-like tribological interfaces. Proc Inst Mech Eng 1(9):1–7
Mikalsen R, Jones E, Roskilly AP (2010) Predictive piston motion control in a free-piston internal combustion engine. Appl Energy 87(5):1722–1728
Ma H, Hu D, Zhang K (2005) A fast tool feeding mechanism using piezoelectric actuators in noncircular turning. Int J Adv Manuf Technol 27(27):254–259
Wang B, Wu Y, Wu X, Liu X, Peng H (2014) Real-time measuring method to measure the micro-displacement of a rotating cutter in precise piston noncylinder pinhole boring. Int J Adv Manuf Technol 70(9):1931–1937
Li AH, Zhao J, Gong Z, Lin F (2016) Optimal selection of cutting tool materials based on multi-criteria decision-making methods in machining Al-Si piston alloy. Int J Adv Manuf Technol 86(1):1–8
Krimpenis AA, Fountas NA, Ntalianis I, Vaxevanidis NM (2014) CNC micromilling properties and optimization using genetic algorithms. Int J Adv Manuf Technol 70(70):157–171
Goyal T, Walia RS, Sidhu TS (2011) Surface roughness optimization of cold-sprayed coatings using Taguchi method. Int J Adv Manuf Technol 60(5–8):611–623
Burnwal S, Deb S (2013) Scheduling optimization of flexible manufacturing system using cuckoo search-based approach. Int J Adv Manuf Technol 64(64):951–959
Kilickap E, Huseyinoglu M, Yardimeden A (2011) Optimization of drilling parameters on surface roughness in drilling of AISI 1045 using response surface methodology and genetic algorithm. Int J Adv Manuf Technol 52(1–4):79–88
Uthayakumar M, Prabhakaran G, Aravindan S, Sivaprasad JV (2009) Precision machining of an aluminum alloy piston reinforced with a cast iron insert. Int J Precis Eng Manuf 10(10):7–13
Ye Y, Yin CB, Gong Y (2016) Position control of nonlinear hydraulic system using an improved PSO based PID controller, Mech. Syst. Signal Process, 83:241–259
Escamilla-Salazar I, Torres-Treviño L, González-Ortíz B, Zambrano PC (2012) Machining optimization using swarm intelligence in titanium (6Al 4V) alloy. Int J Adv Manuf Technol 67(1–4):535–544
Li JG, Zhao H, Yao YX, Liu CQ (2008) Off-line optimization on nc machining based on virtual machining. Int J Adv Manuf Technol 36(9):908–917
Assarzadeh S, Ghoreishi M (2008) Neural-network-based modeling and optimization of the electro-discharge machining process. Int J Adv Manuf Technol 39(5):488–500
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Zhang, Y., Huang, Y., Shao, W. et al. Research on MCVE piston machining and process parameter optimization. Int J Adv Manuf Technol 93, 3955–3966 (2017). https://doi.org/10.1007/s00170-017-0838-4
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00170-017-0838-4