收藏切换
Evolution Indicators of Heavy-Duty Railway Rail Wave Wear Damage Based on t-SNE
收藏切换
PDF
Zhong-mei WANG1, Wei DENG1, Jian-hua LIU1, Peng-xuan NIE1, Hai-bo WU1, Wen-kun WANG2
Science Technology and Engineering | 2025, 25(10) : 4199 - 4205
Less
收藏切换
Science Technology and Engineering | 2025, 25(10): 4199-4205
Papers·Automation and Computational Technology
Evolution Indicators of Heavy-Duty Railway Rail Wave Wear Damage Based on t-SNE
Full
Zhong-mei WANG1, Wei DENG1, Jian-hua LIU1, Peng-xuan NIE1, Hai-bo WU1, Wen-kun WANG2
Affiliations
  • 1 College of Railway Transportation, Hunan University of Technology, Zhuzhou 412000, China
  • 2 Zhuzhou Times Electronic Technology Co., Ltd., Zhuzhou 412007, China
Published: 2025-04-08 doi: 10.12404/j.issn.1671-1815.2403576
Outline
收藏切换

Understanding the evolution law of rail service performance is of great significance for reducing the operation and maintenance costs of heavy-duty railway rails. Due to the complex and variable operating environment of rail tracks, which makes it difficult to construct scientifically effective damage evolution indicators to reflect objective development patterns, a method based on t-SNE(t-distributed stochastic neighbor embedding) was proposed for constructing the evolution law of corrugation damage. Firstly, the time-domain, frequency-domain, statistical, and entropy features were extracted from the original rail corrugation vibration signal. The random forest algorithm was then used to rank the features by importance, and the top-ranked features were selected to construct the feature vector. Dimensionality reduction was performed using t-SNE and other methods, and it is found that t-SNE demonstrates superior performance. The final temporal damage degradation index is obtained through Euclidean distance metric and median filtering for smoothing. The results indicate that this method provides good discrimination, anti-interference capability, and practical applicability for damage stages classification.

rail wave grinding  /  injury evolution law  /  degradation trend characteristics  /  t-SNE  /  damage stages
Zhong-mei WANG, Wei DENG, Jian-hua LIU, Peng-xuan NIE, Hai-bo WU, Wen-kun WANG. Evolution Indicators of Heavy-Duty Railway Rail Wave Wear Damage Based on t-SNE[J]. Science Technology and Engineering, 2025 , 25 (10) : 4199 -4205 . DOI: 10.12404/j.issn.1671-1815.2403576
Year 2025 volume 25 Issue 10
PDF
309
121
Cite this Article
BibTeX
Article Info
doi: 10.12404/j.issn.1671-1815.2403576
  • Receive Date:2024-05-15
  • Online Date:2025-07-09
  • Published:2025-04-08
Article Data
Affiliations
History
  • Received:2024-05-15
  • Revised:2025-01-10
Funding
Affiliations
    1 College of Railway Transportation, Hunan University of Technology, Zhuzhou 412000, China
    2 Zhuzhou Times Electronic Technology Co., Ltd., Zhuzhou 412007, China
References
Share
https://castjournals.cast.org.cn/joweb/kxjsygc/EN/10.12404/j.issn.1671-1815.2403576
Share to
QR

Scan QR to access full text

Cite this article
BibTeX
Citations
表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
关闭全屏
  • BibTeX
  • EndNote
  • RefWorks
  • TxT