Federal Railroad Administration strictly regulates the inspection frequency of all track classes to ensure timely identification of rail defects including irregular gage which is a devastating rail geometry defect. Conventional rail inspection methods are both costly and labor-intensive, whereas existing novel technologies can be expensive and mostly focus on a specific inspection area, e.g. vertical alignment. iPhone 12 Pro was introduced to the public recently with a low-cost, low-resolution light detection and ranging (LiDAR) sensor that is purposed for better photography and virtual reality. Thanks to its portability and computational capacity, iPhone 12 Pro can potentially be used as a portable solution for irregular gage inspection, whose capacity and feasibility are unknown. This study first investigated the capability of the iPhone 12 Pro in calculating unloaded rail gages by its embedded LiDAR sensor. The results showed that uncalibrated raw gage values measured by the iPhone 12 Pro LiDAR sensor were systematically lower than the ground-truth values. The proposed method in this study then introduced logistic regression to calibrate the measured values through balancing the prediction performance and the efficiency, followed by validations using a Gaussian process classifier. The results show that the proposed method correctly identified all 39 high-risk locations with 227 false alarmed locations. The proposed method with the iPhone 12 Pro LiDAR sensor could potentially narrow down the possible “high-risk” gage sections and may result in a significant reduction in the field inspection workload by 48%.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Rail gage-based risk detection Using iPhone 12 pro


    Contributors:
    Ren, Yihao (author) / Dai, Zhenyu (author) / Lu, Pan (author) / Ai, Chengbo (author) / Huang, Ying (author) / Tolliver, Denver (author)


    Publication date :

    2023-04-01


    Size :

    9 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




    Detection of Range-Based Rail Gage and Missing Rail Fasteners

    Lorente, Alejandro García / Llorca, David Fernández / Velasco, Miguel Gavilán et al. | Transportation Research Record | 2014


    RAIL VEHICLE BASED DEPLOYABLE GAGE RESTRAINT MEASUREMENT SYSTEM

    BLOOM JEFFREY ALAN / CLEMENZI JACINDA LEAH / KIM ANTHONY KWAN et al. | European Patent Office | 2018

    Free access

    RAIL VEHICLE BASED DEPLOYABLE GAGE RESTRAINT MEASUREMENT SYSTEM

    BLOOM JEFFREY ALAN / CLEMENZI JACINDA LEAH / KIM ANTHONY KWAN et al. | European Patent Office | 2019

    Free access

    Rail vehicle based deployable gage restraint measurement system

    BLOOM JEFFREY ALAN / CLEMENZI JACINDA LEAH / KIM ANTHONY KWAN et al. | European Patent Office | 2018

    Free access

    Rail motor cars for l-m gage

    Zens, P. | Engineering Index Backfile | 1935