|Table of Contents|

Design method of grinding profile of over worn rail(PDF)

《交通运输工程学报》[ISSN:1671-1637/CN:61-1369/U]

Issue:
2022年02期
Page:
111-122
Research Field:
道路与铁道工程
Publishing date:

Info

Title:
Design method of grinding profile of over worn rail
Author(s):
LIN Feng-tao1;  DENG Zhuo-xin1; 2;  PANG Hua-fei1; 3;  WANG Song-tao1;  YANG Jian4;  DING Jun-jun5;  CHEN Dao-yun1
(1. Key Laboratory of Ministry of Education for Conveyance and Equipment, East China Jiaotong University, Nanchang 330013, Jiangxi, China; 2. Guangzhou Railway Polytechnic, Guangzhou 510430, Guangdong, China; 3. Guangdong Intercity Railway Operation Co., Ltd., Guangzhou 510310, Guangdong, China; 4. Anhui Huirui Rail Intelligent Equipment Co., Ltd., Hefei 230001, Anhui, China; 5. School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, Sichuan, China)
Keywords:
railway vehicle dynamics;  rail profile design;  arc parameter;  simulated annealing;  representative profile;  wheel-rail contact geometry
PACS:
U211.5
DOI:
10.19818/j.cnki.1671-1637.2022.02.008
Abstract:
A rail profile design method with the arc tangency point as the key parameter was proposed for the grinding of over worn rail. Specifically, taking the wheel-rail contact region as the optimization area and the rail wear and the removed amount of grinding material as the optimization objective function, taking the profile boundary, concavity and convexity, derailment coefficient and wheel-rail lateral force as the constraint conditions, the multi-objective function of designed grinding profile of worn rail was established. The multiple simulated annealing optimization algorithm was integrated for solutions. To obtain the rail profile representing the curve of a heavy haul line, which was adopted as the optimized input data, the representative profiles of four kinds of rails were obtained by using the least square distance algorithm, arithmetic average algorithm, weighted average algorithm and scatter reconstruction algorithm. The correlations between the rail representative profiles of the four algorithms and the measured profile contact point probability distribution curve were calculated by using the Pearson correlation coefficient, Kendall rank correlation coefficient and Spearman rank correlation coefficient, and the representative profile with the highest correlation was taken as the actual profile of the curve section of the equivalent heavy haul line. The economical grinding profile of over worn rail in a heavy haul line and the optimized profile using the arc profile design method were analyzed. Analysis results show that compared with the on-site grinding profile of rail, the optimized rail profile has a reduced grinding and cutting amount for its sectional profile by 69.56 mm2, a decrease of 64.98%, a slightly increased derailment coefficient, the same lateral wheel-rail force, small lateral wheelset displacement change, and similar curve passing performance. Although the wear area under 800 000 passes increases by 2.19 mm2, and the wear rate of rail slightly rises, the overall service life of rail is still prolonged. 3 tabs, 17 figs, 30 refs.

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Last Update: 2022-06-10