In recent years, the range of sensing technologies has expanded rapidly, whereas sensor devices have become cheaper. This has led to a rapid expansion in condition monitoring of systems, structures, vehicles, and machinery using sensors. Key factors are the recent advances in networking technologies such as wireless communication and mobile ad hoc networking coupled with the technology to integrate devices. Wireless sensor networks (WSNs) can be used for monitoring the railway infrastructure such as bridges, rail tracks, track beds, and track equipment along with vehicle health monitoring such as chassis, bogies, wheels, and wagons. Condition monitoring reduces human inspection requirements through automated monitoring, reduces maintenance through detecting faults before they escalate, and improves safety and reliability. This is vital for the development, upgrading, and expansion of railway networks. This paper surveys these wireless sensors network technology for monitoring in the railway industry for analyzing systems, structures, vehicles, and machinery. This paper focuses on practical engineering solutions, principally, which sensor devices are used and what they are used for; and the identification of sensor configurations and network topologies. It identifies their respective motivations and distinguishes their advantages and disadvantages in a comparative review.

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Wireless Sensor Networks for Condition Monitoring in the Railway Industry: A Survey

Nowadays, the railway industry is in a position where it is able to exploit the opportunities created by the IIoT (Industrial Internet of Things) and enabling communication technologies under the paradigm of Internet of Trains. This review details the evolution of communication technologies since the deployment of GSM-R, describing the main alternatives and how railway requirements, specifications and recommendations have evolved over time. The advantages of the latest generation of broadband communication systems (e.g., LTE, 5G, IEEE 802.11ad) and the emergence of Wireless Sensor Networks (WSNs) for the railway environment are also explained together with the strategic roadmap to ensure a smooth migration from GSM-R. Furthermore, this survey focuses on providing a holistic approach, identifying scenarios and architectures where railways could leverage better commercial IIoT capabilities. After reviewing the main industrial developments, short and medium-term IIoT-enabled services for smart railways are evaluated. Then, it is analyzed the latest research on predictive maintenance, smart infrastructure, advanced monitoring of assets, video surveillance systems, railway operations, Passenger and Freight Information Systems (PIS/FIS), train control systems, safety assurance, signaling systems, cyber security and energy efficiency. Overall, it can be stated that the aim of this article is to provide a detailed examination of the state-of-the-art of different technologies and services that will revolutionize the railway industry and will allow for confronting today challenges.

https://www.mdpi.com/1424-8220/17/6/1457/pdf

Towards the Internet of Smart Trains: A Review on Industrial IoT-Connected Railways

Foreword Chapter 1 Introduction to SHM (Daniel L Balageas) Chapter 2 Vibration-based techniques for SHM (Claus-Peter Fritzen) Chapter 3 Fiber-optics sensors (Alfredo Guemes and Jose M Menendez) Chapter 4 SHM with piezoelectric sensors (Philippe Guy and Thomas Monnier) Chapter 5 SHM using electrical resistance (Michelle Salvia and Jean-Christophe Abry) Chapter 6 Low frequency electromagnetic techniques (Michel B Lemistre) Chapter 7 Capacitive methods for SHM in civil engineering (Xavier Derobert and Jean Iaquinta) Short Bibliographies of the Contributors Index

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Structural health monitoring

In this work, a new methodology is presented for reconstruction of the impact force history using artificial neural networks (ANNs) and spectral components of sensor data recorded by piezoceramic sensors. A large set of data, required for training the ANNs, was generated by using an efficient nonlinear finite element (FE) model of a sensorised composite stiffened panel. Impact experiments were performed on a composite plate equipped with surface-mounted piezoceramic sensors to validate the numerical modelling approach. Using the FE model of the panel, data were generated for impacts that are likely to occur during the life-time of an aircraft, consisting of large mass (e.g. dropping tool) and small mass (e.g. debris) impacts at various locations, i.e. in the bay, on the foot of a stringer and over/under a stringer. Even though the panel undergoes large deformation during impact (nonlinear response), the established networks predict the impact force history and its peak with reasonable accuracy.

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Identification of impact force for smart composite stiffened panels

Cement-based piezoelectric composites are employed as the sensing elements of a new smart traffic monitoring system. The piezoelectricity of the cement-based piezoelectric sensors enables powerful and accurate real-time detection of the pressure induced by the traffic flow. To describe the mechanical-electrical conversion mechanism between traffic flow and the electrical output of the embedded piezoelectric sensors, a mathematical model is established based on Duhamel's integral, the constitutive law and the charge-leakage characteristics of the piezoelectric composite. Laboratory tests show that the voltage magnitude of the sensor is linearly proportional to the applied pressure, which ensures the reliability of the cement-based piezoelectric sensors for traffic monitoring. A series of on-site road tests by a 10 tonne truck and a 6.8 tonne van show that vehicle weight-in-motion can be predicted based on the mechanical-electrical model by taking into account the vehicle speed and the charge-leakage property of the piezoelectric sensor. In the speed range from 20 km h−1 to 70 km h−1, the error of the repeated weigh-in-motion measurements of the 6.8 tonne van is less than 1 tonne. The results indicate that the embedded cement-based piezoelectric sensors and associated measurement setup have good capability of smart traffic monitoring, such as traffic flow detection, vehicle speed detection and weigh-in-motion measurement.

https://iopscience.iop.org/article/10.1088/0964-1726/24/2/025023/pdf

A new smart traffic monitoring method using embedded cement-based piezoelectric sensors

SUMMARY

This paper presents an in situ implementation of the weigh-in-motion (WIM) concept for the railway transport. The presented WIM system constitutes a part of a larger structural health monitoring system dedicated to railway bridges. The identification of train load acting on a bridge is necessary for performing subsequent identification of damage in the analyzed structure. Some existing WIM methods in the railway applications have been reviewed. The authors' implementation based on piezoelectric sensors has been described in detail. Hardware development of the WIM system, including wireless data transfer to a remote analysis centre, has been outlined. Results from measurement sessions carried out in situ have been presented and successfully verified by a numerical model of rail–sleeper–ground interaction. Copyright © 2010 John Wiley & Sons, Ltd.

Piezo-based weigh-in-motion system for the railway transport

This paper presents results of in situ investigation of a railway truss bridge in the context of structural health monitoring (SHM). Three experimental methods are examined. Dynamic responses of the bridge recorded by strain gauges are confronted with alternative ways of acquisition using piezoelectric patch sensors and ultrasonic probeheads. All types of sensors produce similar output. Also the corresponding responses of the numerical model of the bridge match experimental data.

http://iopscience.iop.org/article/10.1088/0964-1726/20/3/035016/pdf

Structural health monitoring of a railway truss bridge using vibration-based and ultrasonic methods

The so-called Adaptive Impact Absorption (AIA) is a research area of safety engineering devoted to problems of shock absorption in various unpredictable scenarios of collisions. It makes use of smart technologies (systems equipped with sensors, controllable dissipaters and specialised tools for signal processing). Examples of engineering applications for AIA systems are protective road barriers, automotive bumpers or adaptive landing gears. One of the most challenging problems for AIA systems is on-line identification of impact loads, which is crucial for introducing the optimum real-time strategy of adaptive impact absorption. This paper presents the concept of an impactometer and develops the methodology able to perform real-time impact load identification. Considered dynamic excitation is generated by a mass M1 impacting with initial velocity V0. An analytical formulation of the problem, supported with numerical simulations and experimental verifications is presented. Two identification algorithms based on measured response of the impacted structure are proposed and discussed. Finally, a concept of the AIA device utilizing the idea of impactometer is briefly presented.

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On-line impact load identification

Real-Time Dynamic Load Identification

The paper presents some results of research on the Weight-in-motion (WIM) system. The device is used for identification of loads on the road surface generated by traveling vehicles. The proposed approach utilizes the piezoelectric measurement techniques to monitor strain development in a deformable body and eventually these measurements are used for tire-pavement load identification. An advantage of the proposed concept is that no additional limitation for a vehicle velocity and direction is required in order to make the measurement feasible. The device allow to identify many parameters which can be stored for statistical and planning purposes. When an overload or an exceed in speed limit is detected the data can be sent for penalization purposes. The research includes a computer simulation of the bending plate detector using the Finite Element Method (FEM). Its objective is to validate the concept as well as to test some factors which are important with respect to the proposed load identification methodology. An experimental research involved field tests on the WIM system using a bending plate detector and inductive loops to detect a vehicle.

Krzysztof Sekuła

Papers

Piezo-based weigh-in-motion system for the railway transport

Structural health monitoring of a railway truss bridge using vibration-based and ultrasonic methods

On-line impact load identification

Real-Time Dynamic Load Identification

Weigh-in-Motion System Testing