A Review on Rail Defect Detection Systems Based on Wireless Sensors

Zhao, Yuliang; Liu, Zhiqiang; Yi, Dong; Yu, Xiao-Dong; Sha, Xiaopeng; Li, Lianjiang; Sun, Hui; Zhan, Zhikun; Li, Wen J.

doi:10.3390/s22176409

Cited by 24 publications

(14 citation statements)

References 116 publications

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“…In circumstances where the surface of rail wear rail heads is severely damaged or substantially worn, ultrasonic waves are ineffective [53]. Ultrasonic waves cannot detect smaller defects [53,54]. For electromagnetic detection, the velocity effect can change the signal's amplitude, and the signal is more susceptible to interference from the environment.…”

Section: Ementioning

confidence: 99%

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IoT Based Railway Track Faults Detection and Localization Using Acoustic Analysis

et al. 2022

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Rail is one of the most energy efficient and economical modes of transportation amongst many. Regular inspection of railway track health is essential for ensuring robust and secure train operations. Investigations and delayed discovery pose a serious risk to the safe functioning of rail transportation. The traditional method of manually examining the rail track using a railway cart is both inefficient and susceptible to mistakes and bias. It is imperative to automate inspection in order to avert catastrophes and save countless lives particularly in zones where train accidents are numerous. The purpose of this research is to develop an Internet of Things (IoT)-based autonomous railway track fault detection system to enhance the existing railway cart system in order to address the aforementioned issues. In addition to data collection on Pakistani railway lines, this work contributes significantly to railway track fault identification and classification based on acoustic analysis, as well as fault localization. Due to their frequency of occurrences, six types of track's faults were first targeted: wheel burnt, loose nuts and bolts, crash sleeper, creep, low joint, and point and crossing. Support vector machines, logistic regression, random forest, extra tree classifier, decision tree classifier, multilayer perceptron and ensemble with hard and soft voting were among the machine learning methods used. The results indicate that acoustic data can successfully assist in discriminating the track defects and localizing the defects in real time. The results show that MLP achieved the best results, with an accuracy of 98.4 percent.

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Section: Ementioning

confidence: 99%

“…Consequently, a well-designed algorithm is required to counteract these impacts. Unlike ultrasonic inspection, electromagnetic inspection can identify faults close to the surface [54].…”

Section: Ementioning

confidence: 99%

IoT Based Railway Track Faults Detection and Localization Using Acoustic Analysis

et al. 2022

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“…Therefore, it is crucial to provide a stable and reliable power supply for the railway monitoring system. 2,3 Wireless power transfer (WPT) enables contactless transmission of electrical power. It has the potential to power the monitoring system wirelessly.…”

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confidence: 99%

“…Even if one onboard receiver is not working, other receivers can continue to obtain electrical energy, so the system has better stability. (2) The system proposed in this article dramatically reduces the volume of the system's transmitter by introducing a repeater on the ground.…”

mentioning

confidence: 99%

A multi‐loads capacitive power transfer system for railway intelligent monitoring systems based on single relay plate

Zhang

Luo

Cheng

et al. 2023

Circuit Theory & Apps

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SummaryThis paper proposes a multi‐loads capacitive power transfer (CPT) system based on a single relay plate for railway monitoring systems. The proposed system can supply power wirelessly to the monitoring system on the trackside and train carriages simultaneously to eliminate traditional power cables connection and prevent frequent battery replacement. Unlike the traditional multiple loads CPT systems, the proposed system uses only one relay plate, which is more stable and uncomplicated considering the coupler installation space and moving dynamically in the railway system. The proposed system adopts a CL‐LCLC‐CL compensation network to achieve a load‐independent output. The limitation of the charging load quantity is given in detail considering the coupler voltage stress distribution. An experimental prototype with three loads is also built to verify the effectiveness of the proposed system. Experimental results show that the proposed system achieves wireless power transfer to multiple loads simultaneously with two loads on the receiver and one on the repeater side. The load‐independent property is also achieved when two loads are removed. The maximum experimental efficiency is about 87.13%.

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“…is particularly important! The existing surface defect detection methods include traditional classical artificial vision, virtual structured light, point cloud scanning, ultrasonic detection and other methods [4][5][6][7]. After a long period of development, artificial vision is an indispensable and widely used method, but its shortcomings are still obvious, such as low efficiency, relying on experience, easy to miss detection, difficult to quantify visualization, large individual differences, difficult to unify standards, and difficult to trace the source.…”

mentioning

confidence: 99%

Research on Digital Testing Technology for Full Surface Defects of Cross scale Heteromorphic Metal Devices

Liu

Ma²,

Bai³

et al. 2023

J. Phys.: Conf. Ser.

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There are many types of cross scale special-shaped metal components in various fields, and the surface quality (defects) of some key components will affect the device performance and even cause the long-term stability and reliability of the system to decline. The existing manual inspection methods are difficult to accurately quantify and establish a digital traceability database, so it is urgent to study the automatic digital inspection technology of full surface defects. However, most of the devices are curved surfaces with different shapes, large size spans, various types of surface defects and diffuse reflection imaging, and the background of machine vision images is complex, which greatly increases the difficulty of defect detection. Based on the principle of machine vision imaging, this paper designs a long depth of field and low distortion imaging system for curved surfaces. Combined with a flexible scanning motion mechanism with multiple degrees of freedom, this paper studies the technology of complex background defect extraction to realize the full surface defect detection of cross scale special-shaped metal devices.

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A Review on Rail Defect Detection Systems Based on Wireless Sensors

Cited by 24 publications

References 116 publications

IoT Based Railway Track Faults Detection and Localization Using Acoustic Analysis

IoT Based Railway Track Faults Detection and Localization Using Acoustic Analysis

A multi‐loads capacitive power transfer system for railway intelligent monitoring systems based on single relay plate

Research on Digital Testing Technology for Full Surface Defects of Cross scale Heteromorphic Metal Devices

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