振噪融合的地铁钢轨波磨快速测量方法

从建力; 王源; 徐舟; 李伟; 陈嵘; 王平

doi:10.3969/j.issn.0258-2724.20220260

振噪融合的地铁钢轨波磨快速测量方法

doi: 10.3969/j.issn.0258-2724.20220260

从建力^{1, 2,},
王源³,
徐舟^{1, 2},
李伟⁴,
陈嵘^{1, 2, ,},
王平^{1, 2}

1.
西南交通大学高速铁路线路工程教育部重点实验室，四川成都 610031
2.
西南交通大学土木工程学院，四川成都 610031
3.
南方科技大学系统设计与智能制造学院，广州深圳 518055
4.
深圳地铁运营集团有限公司，广州深圳 518400

基金项目: 国家自然科学基金（52278464， 52008198， 51778542）；国家重点研发计划（2021YFB3703601）；四川省杰出青年科技人才项目（2020JDJQ0033）

详细信息

作者简介:
从建力（1992—），男，博士研究生，研究方向为轨道状态智能检测与运维， E-mail：jlcong2019@my.swjtu.edu.cn

通讯作者:
陈嵘(1981—), 男, 教授, 博士, 研究方向为轨道动力学及轨道平顺性调控, E-mail：chenrong@home.swjtu.edu.cn

中图分类号: U216.4
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- 文章访问数: 342
- HTML全文浏览量: 67
- PDF下载量: 53
- 被引次数: 0
出版历程
- 收稿日期: 2022-04-11
- 修回日期: 2022-10-13
- 网络出版日期: 2023-04-12
- 刊出日期: 2022-12-01

Rail Corrugation Measurement Method Based on Vibration-Noise Fusion in Metro System

CONG Jianli^{1, 2
,},
WANG Yuan³,
XU Zhou^{1, 2},
LI Wei⁴,
CHEN Rong^{1, 2
, ,},
WANG Ping^{1, 2}

1.
MOE Key Laboratory of High-Speed Railway Engineering, Southwest Jiaotong University, Chengdu 610031, China
2.
School of Civil Engineering, Southwest Jiaotong University, Chengdu 610031, China
3.
School of System Design and Intelligent Manufacturing, Southern University of Science and Technology, Shenzhen 518055, China
4.
Shenzhen Metro Operation Group Co. Ltd., Shenzhen 518400, China

摘要

摘要:
为实现数据驱动的钢轨波磨状态修，提出一种时-空密集型的钢轨波磨测量方法. 首先，采用智能终端检测列车编组车体振动和车厢噪声，对列车编组不同车体三向加速度进行波形匹配，得到延时估计值，修正列车运行速度和里程估计误差；其次，基于声纹谱能量法分析车厢声纹数据，并定义“波噪比”指标，量化钢轨波磨噪声能量及其高阶谐波能量占噪声总能量的比值，作为钢轨波磨自动识别的依据；最后，建立列车响应到钢轨波磨状态的反向映射关系，获取波噪比超限时的钢轨波磨波长和里程信息，以地铁某区间实测为例，采用钢轨波磨仪测量1.6 km范围的轨面短波不平顺，将测量结果 [0,50] mm波长范围的波深峰峰值与车厢声纹波噪比进行对比. 结果表明：当波噪比阈值取为0.2时，基于声纹数据识别的钢轨波磨与线路分布一致，验证了该方法可为钢轨波磨状态评估提供数据支撑.
- 波噪比 /
- 振噪融合 /
- 钢轨波磨 /
- 状态修 /
- 声纹特征
Abstract:
To realize the condition-based maintenance of rail corrugation in a data-driven way, a time-space intensive measurement method of rail corrugation is proposed. First, the intelligent terminal is used to detect vibration and noise at a car body of the train formation, the acceleration waveforms in three directions of different car bodies were matched to obtain the estimated time delay, and the error of the train speed and mileage estimation was corrected. Second, the car voiceprint data is analyzed with the voiceprint spectrum energy method, and the corrugation-noise ratio index is defined to quantify the ratio of rail corrugation noise energy and its high-order harmonic energy to the total noise energy, as the basis for automatic identification of rail corrugation. Finally, the inverse mapping relationship between the train response and rail corrugation sate is established to obtain the rail corrugation wavelength and mileage information when the corrugation-noise ratio exceeds the limit. The field test in metro line is taken as an example, where a rail corrugation measurement trolley was used to measure the shortwave irregularity of the rail surface on 1.6 km rail, and the measured peak-to-peak value in the wavelength range of [0,50] mm was compared to the corrugation-noise ratio of voiceprint data. The results show that, when the threshold of the corrugation-noise ratio is set as 0.2, the rail corrugation identified by the voiceprint data is consistent with the line distribution, which verifies that this method can enhance data evidence in evaluating rail corrugation state.
- corrugation-noise ratio /
- vibration-noise fusion /
- rail corrugation /
- condition-based maintenance /
- voiceprint feature

HTML全文

图 1 多智能终端监测列车振动-声纹

Figure 1. Multi-intelligent terminal monitoring train vibration-voiceprint

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图 2 车厢振动与噪声融合算法

Figure 2. Vibration-noise fusion algorithm for car

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图 3 无GPS环境下列车运行速度估计原理

Figure 3. Principle of train speed estimation without GPS

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图 4 移动窗下噪声数据频域表示

Figure 4. Spectrum of noise data in moving window

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图 5 某区间车载智能终端振动测量数据

Figure 5. Vibration data of on-board intelligent terminal in one section

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图 6 某区间车厢声纹信息分析

Figure 6. Voiceprint information analysis for car in one section

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图 7 某区段钢轨短波不平顺现场测量

Figure 7. Field test of shortwave irregularity for rail in certain section

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图 8 基于波噪比的钢轨波磨识别效果

Figure 8. Identification results of rail corrugation based on corrugation-noise ratio

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图 9 全线波噪比统计概率分布

Figure 9. Statistical probability distribution of corrugation-noise ratio for metro line

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图 10 全线钢轨波磨状态分布地图

Figure 10. Distribution map of rail corrugation state along metro line

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