Title:

Based on fiber sensor network rail transit IoT monitoring system

Group publication title:

Optica Applicata

Creator:

Liu, Zhao ; Wang, Yifang ; Hou, Yingjuan ; Yu, Chunrong

Contributor:

Urbańczyk, Wacław. Redakcja

Subject and Keywords:

optyka ; fiber sensing internet of things (FS-IoT) ; fiber Bragg grating (FBG) ; health monitoring ; state assessment ; electric multiple units (EMU)

Description:

Optica Applicata, Vol. 55, 2025, nr 1, s. 5-17 ; Optica Applicata is an international journal, published in a non-periodical form in the years 1971-1973 and quarterly since 1973. From the beginning of the year 2008, Optica Applicata is an Open Access journal available online via the Internet, with free access to the full text of articles serving the best interests of the scientific community. The journal is abstracted and indexed in: Chemical Abstracts, Compendex, Current Contents, Inspec, Referativnyj Zhurnal, SCI Expanded, Scopus, Ulrich’s Periodicals Directory ; click here to follow the link

Abstrakt:

In the process of train operation, the status information directly reflects the degree of safety of the operation. Online health monitoring and completion of train status assessment are important signs of train intelligent control. To obtain the stress field distribution of the support position (bearing area) of the train, proposed a EMU health monitoring and intelligent state assessment system based on fiber sensing internet of things (FS-IoT). The system adopts the method of combining multiple sensitized FBG sensors into a sensing network to obtain the stress field distribution at the measured location. When the train is faulty or the external environment affects the train’s operation, the stress field and vibration field on the train’s motion components will change significantly. Obtain real-time physical field information of sensitive locations through the FBG sensor array, which can realize online monitoring of train status. A distributed combinatorial optimization algorithm based on FS-IoT was designed, and the weight distribution of FBG test data at different locations on the inversion results was analyzed based on data mining. In the sensitization FBG testing experiment, under the same stress conditions, the sensitivity increased from 12.440 to 49.935 pm/kN, and had good linearity. In dynamic testing, when the test carriage passes through the rail connection, there will be significant fluctuations in the center wavelength of the FBG, with a maximum wavelength offset of 2530.2 pm. The peak-to-peak values of the two test data are basically the same, indicating that stress changes can be inverted by the peak position. Finally, a train state inversion model based on FBG sensing network and a system framework for intelligent state evaluation are presented, providing new design ideas for train state monitoring.

Publisher:

Oficyna Wydawnicza Politechniki Wrocławskiej

Place of publication:

Wrocław

Date:

2025

Resource Type:

artykuł

Resource Identifier:

doi:10.37190/oa/196289

Source:

<sygn. PWr A3481II> ; click here to follow the link ; click here to follow the link

Language:

eng

Relation:

Optica Applicata ; Optica Applicata, Vol. 55, 2025 ; Optica Applicata, Vol. 55, 2025, nr 1 ; Politechnika Wrocławska. Wydział Podstawowych Problemów Techniki

Rights:

Wszystkie prawa zastrzeżone (Copyright)

Access Rights:

Dla wszystkich w zakresie dozwolonego użytku

Location:

Politechnika Wrocławska