Online measurement method for roundness of large aluminum alloy ring based on laser ranging principle

Abstract

Aluminum alloy rings are widely used in aerospace, energy, petrochemical, and equipment applications. The loss of roundness often occurs because of the weak rigidity and unstable plasticity of aluminum alloy rings. Therefore, an online measurement technique for the roundness of aluminum alloy rings is critical for ensuring the processing quality of aluminum alloy rings. In this paper, an online roundness measurement method based on the laser ranging principle and improved particle swarm optimization (IPSO) is proposed with the aid of the rotation of the ring during the rolling process. First, the distance from the outer surface of the ring to the laser rangefinder was measured using a triangular laser rangefinder with the help of the rotation of the ring in the rolling process. Second, the distance data were denoized using an improved Kalman filter algorithm to reduce the influence of random noise on the measurement results. Finally, the roundness and geometric center were evaluated using the IPSO algorithm combined with the minimum zone circle (MZC) method and compared with the results obtained using the standard particle swarm optimization (PSO) algorithm, genetic algorithm (GA), and least square (LS) algorithm. The experimental results show that the roundness measured by the IPSO algorithm is less than 0.06 mm, demonstrating better performance in the roundness evaluation. The measurement method for roundness proposed in this paper is suitable for the online evaluation of large aluminum alloy rings, avoiding the influence of ring size on roundness measurement.

Keywords

Ring rolling laser ranging improved particle swarm optimization algorithm improved Kalman filter roundness evaluation

Get full access to this article

View all access options for this article.

References

Han

Hua

Zhou

, et al. A new cylindrical ring rolling technology for manufacturing thin-walled cylindrical ring. Int J Mech Sci 2014; 81: 95–108.

Cui

Ding

Cheng

. An analytical investigation on the workpiece roundness generation and its perfection strategies in centreless grinding. Proc IMechE, Part B: J Engineering Manufacture 2015; 229(3): 409–420.

Cleaver

Allwood

. Curvature development in ring rolling. J Mater Process Technol 2019; 267: 316–337.

Jiang

Huang

Luo

, et al. An improved dynamic model of defective bearings considering the three-dimensional geometric relationship between the rolling element and defect area. Mech Syst Signal Process 2019; 129: 694–716.

Zhou

Hua

Qian

. 3D coupled thermo-mechanical FE analysis of roll size effects on the radial–axial ring rolling process. Comp Mater Sci 2011; 50: 911–924.

Fan

Wang

. 3D finite element modeling and analysis of radial forging processes. J Manuf Process 2014; 16: 2329-334.

Zhang

. A novel geometry error measurement methodology for coaxiality evaluation. Proc IMechE, Part B: J Engineering Manufacture 2021; 235(4): 627–639.

Horikawa

Maruyama

Shimada

. A low cost, high accuracy roundness measuring system. Precis Eng 2001; 25: 3200–3205.

Zha

Chen

. A “double accuracy theory” and experimental research on precision grinding. Appl Sci 2020; 10: 6.

10.

Liu

Sun

, et al. A coaxiality measurement model based on multi-systematic errors separation for turbine shaft. Measurement 2021; 186.

11.

Liu

Zhang

Sun

, et al. A method to minimize stage-by-stage initial unbalance in the aero engine assembly of multistage rotors. Aerosp Sci Technol 2019; 85: 270–276.

12.

Liu

Mei

Sun

, et al. A novel cylindrical profile measurement model and errors separation method applied to stepped shafts precision model engineering. Measurement 2022; 188.

13.

Deng

Wang

Zhang

, et al. Vision measurement error analysis for nonlinear light refraction at high temperature. Appl Opt 2018; 57(20): 5556–5565.

14.

Fan

, et al. A vision-based processing methodology for profile grinding of contour surfaces. Proc IMechE, Part B: J Engineering Manufacture 2020; 234(1–2): 27–39.

15.

Dworkin

Nye

. Image processing for machine vision measurement of hot formed parts. J Mater Process Technol 2006; 174: 1–6.

16.

Ayub

Mohamed

Esa

. In-line inspection of roundness using machine vision. Procedia Technol 2014; 15: 807–816.

17.

Jia

Wang

Liu

, et al. An improved acquiring method for machine vision measurement of hot formed parts. J Mater Process Technol 2010; 210: 267–271.

18.

Liu

Jia

Wang

, et al. An improved online dimensional measurement method of large hot cylindrical forging. Measurement 2012; 45(8): 1–11.

19.

Mekid

Vacharanukul

. In-process out-of-roundness measurement probe for turned workpieces. Measurement 2011; 44(4): 762–766.

20.

Yang

Takamura

Takahashi

, et al. Multi-probe scanning system comprising three laser interferometers and one autocollimator for measuring flat bar mirror profile with nanometer accuracy. Precis Eng 2011; 35(4): 686–692.

21.

QJ 3194: 2004. Measurement method of large size roundness error.

22.

GB/T 7235: 2004. Geometrical product specification (GPS) - Method for evaluating roundness error - Measurement of radius variation.

23.

Fan

Sun

, et al. Application of adaptive Kalman filter in vehicle laser doppler velocimetry. Opt Fiber Technol 2018; 41: 163–167.

24.

Gunawardane

PDSH

Pathirana

APTD

Pallewela

REA

, et al. Additive Gaussian noise model and Kalman filter to enhance controllability of gesture-controlled teleoperated soft actuators. Proc IMechE, Part B: J Engineering Manufacture 2020; 234 (14): 2219–2229.

25.

Arthur

Attarian

Hamilton

, et al. Nonlinear Kalman filtering for censored observations. Appl Math Comput 2018; 316: 155–166.

26.

Nobrega

Oliveira

ALI

. Kalman filter-based method for online sequential extreme learning machine for regression problems. Eng Appl Artif Intel 2015; 44: 101–110.

27.

Nurunnabi

Sadahiro

Laefer

. Robust statistical approaches for circle fitting in laser scanning three-dimensional point cloud data. Pattern Recogn 2018; 81: 417–431.

28.

Zhang

Wang

Liu

, et al. A concentricity measurement method for large forgings based on laser ranging principle. Measurement 2019; 147: 106838.

29.

Luo

Han

, et al. Applying particle swarm optimization algorithm to roundness error evaluation based on minimum zone circle. Measurement 2014; 52: 12–21.

30.

Sun

. Applying particle swarm optimization algorithm to roundness measurement. Expert Syst Appl 2009; 36(2): 3428–3438.

31.

Yang

Yuan

, et al. A modified particle swarm optimizer with dynamic adaptation. Appl Math Comput 2007; 189(2): 1205–1213.

32.

Liu

Zhou

, et al. An algorithm for evaluating cylindricity according to the minimum condition. Measurement 2020; 158.

33.

Chen

Zhang

. An adaptive parameters adjustment and planning method for robotic belt grinding using modified quality model. Proc IMechE, Part B: J Engineering Manufacture 2021; 235(4): 605–615.

34.

Baek

Kim

Lee

, et al. Multi-probe system design for measuring the roundness and rotation error motion of a spindle using an error separation technique. Proc IMechE, Part B: J Engineering Manufacture 2019; 233(5): 1547–1560.

35.

Baek

Hwang

Cho

. Measurement of five-degrees-of-freedom spindle error motion using multi probe error separation. Proc IMechE, Part B: J Engineering Manufacture 2021; 235(9): 1373–1383.

36.

JJF 1130:2005. Guidelines for uncertainty evaluation in calibration of geometric measurement equipment.

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB