Monitoring Large-Scale Rail Transit Systems Based on an Analytic Hierarchy Process/Gradient-Based Cuckoo Search Algorith
- PDF / 2,087,267 Bytes
- 13 Pages / 595.276 x 790.866 pts Page_size
- 12 Downloads / 215 Views
http://www.urt.cn/
ORIGINAL RESEARCH PAPERS
Monitoring Large-Scale Rail Transit Systems Based on an Analytic Hierarchy Process/Gradient-Based Cuckoo Search Algorithm (GBCS) Scheme Nihad Hasan Talib1 • Khalid Bin Hasnan2 • Azli Bin Nawawi2 • Haslina Binti Abdullah1 • Adel Muhsin Elewe3
Received: 10 September 2019 / Revised: 22 December 2019 / Accepted: 31 January 2020 / Published online: 23 April 2020 Ó The Author(s) 2020
Abstract Condition monitoring is used as a tool for maintenance management and function as input to decision support. Thus the key parameters in preventing severe damage to railway assets can be determined by automatic real-time monitoring. The technique of radio-frequency identification (RFID) is increasingly applied for the automatic real-time monitoring and control of railway assets, which employs radio waves without the use of physical contact. In this work, a 243-km2 area of Kuala Lumpur was selected. Because of its large size, determining the locations in which to install the RFID readers for monitoring the bogie components in the Kuala Lumpur railway system is a very complex task. The task involved three challenges: first, finding an optimal evolutionary method for railway network planning in order to deploy the RFID system in a
& Nihad Hasan Talib [email protected] Khalid Bin Hasnan [email protected] Azli Bin Nawawi [email protected] Haslina Binti Abdullah [email protected] Adel Muhsin Elewe [email protected] 1
Faculty of Mechanical and Manufacturing Engineering, UTHM, Batu Pahat, Johor, Malaysia
2
Faculty of Engineering Technology, UTHM, Batu Pahat, Johor, Malaysia
3
Department of Construction and Project Management, Mustansiriya University, Baghdad, Iraq
Communicated by Xuesong Zhou.
123
large-area; second, identifying the large area that involved functional features; third, determining which station or stations should be given priority in applying the RFID system to achieve the most effective monitoring of the trains. The first challenge was solved by using a gradientbase cuckoo search algorithm for RFID system deployment. The second challenge was solved by determining all necessary information using geographic information system (GIS) resources. Because of the huge volume of data collected from GIS, it was found that the best method for eliminating data was to develop a new clustering model to separate the useful from the unuseful data and to identify the most suitable stations. Finally, the data set was reduced by developing a specific filter, and the information collected was tested by an analytic hierarchy process as a technique to determine the best stations for system monitoring and control. The results showed the success of the proposed method in solving the significant challenge of large-scale area conditions correlated with multi-objective RFID functions. The method provides high reliability in working with complex and dynamic data. Keywords Geographic information system (GIS) Analytic hierarchy process (AHP) Radio-frequency identification (RFID) Gr
Data Loading...
