Innovative Monitoring and Predictive Maintenance Solutions on Lightweight Wagon

Grant Agreement no.: 730863 - S2R-OC-IP5-03-2015

Project Start Date: 01/11/2016

Project End Date: 30/04/2019

DELIVERABLE D2.1

Overall Measurement Concept for Cargo Condition Monitoring System

Work Package: WP 2 Dissemination Level: PU Status: Final Leader beneficiary: PER Due date of deliverable: 31/10/2017 Actual submission date: 31/10/2017 Prepared by: David Vincent, Perpetuum Ltd. (PER) Contributors: Dachuan Shi, Technische Universität Berlin (TUB)

Philipp Krause, Technische Universität Berlin (TUB) Liang Cheng, Newcastle University (UNEW) Cristian Ulianov Newcastle University (UNEW) Raluca Marin-Perianu, Inertia Technology B.V. (INE) Mihai Marin-Perianu Inertia Technology B.V. (INE)

Verified by: Dachuan Shi (UNEW)

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Document history Version Date Author(s) Description D1 14/07/2017 Dachuan Shi (TUB) Document initiated D2 31/07/2017 David Vincent (PER) Content added D3 04/09/2017 David Vincent (PER) Draft structure

D4 12/09/2017 Liang Cheng (UNEW) Update of structure, content added D5 20/09/2017 Raluca Marin-Perianu (INE) Content added

D5 04/10/2017 Dachuan Shi (TUB) Update of structure, content added D6 24/10/2017 Dachuan Shi (TUB)

David Vincent (PER) Content, conclusions and executive summary added, integration

D7 27/10/2017 All Revision - pre-final version D8 31/10/2017 Siân Evans Formatting and proofread

FINAL 31/10/2017 Siân Evans Submission of final version

The INNOWAG project consortium

No Partner organisation Short Name Country 1 NEWCASTLE UNIVERSITY UNEW UK

2 INERTIA TECHNOLOGY B.V INE Netherlands

3 HAVELLANDISCHE EISENBAHN AKTIENGESELLSCHAFT HVLE Germany

4 LUCCHINI RS SPA LRS Italy 5 NEW OPERA AISBL NEWO Belgium 6 PERPETUUM LIMITED PER UK

7 POLITECNICO DI MILANO POLIM Italy 8 TECHNISCHE UNIVERSITAET BERLIN TUB Germany

9 UNION DES INDUSTRIES FERROVIAIRES EUROPEENNES UNIFE Belgium

10 UZINA DE VAGOANE AIUD SA UVA Romania 11 VYZKUMNY USTAV ZELEZNICNI VUZ Czech Republic

Disclaimer This report was prepared as an account of work funded by Shift2Rail Joint Undertaking. The contents of this document are provided “AS IS”, and no guarantee or warranty is provided that the information is fit for particular purposes.

The information, analyses and views set out in this report are those of the author(s) and do not necessarily reflect the official opinion of the European Union. Neither the Community institutions and bodies, nor any person acting on their behalf may be held responsible for the use which may be made of the information contained therein. The user, thereof, uses the information at its sole risk and liability.

Copyright notice © 2016 – 2019 INNOWAG Consortium

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Table of Contents

Executive Summary ..................................................................................................................... 4List of abbreviations .................................................................................................................. 5List of figures ............................................................................................................................ 5List of tables .............................................................................................................................. 5

1. INTRODUCTION ................................................................................................................... 61.1 Objectives ..................................................................................................................... 61.2 Background ................................................................................................................... 6

2. CONCEPT OF CARGO CONDITION MONITORING SYSTEM ........................................... 82.1 Summary of state of the art CCMS ............................................................................... 8

2.1.1 Case study: container wagon ................................................................................... 82.1.2 Case study: Tank wagon .......................................................................................... 9

2.2 Features of the new CCMS ........................................................................................ 103. GENERAL SYSTEM ARCHITECTURE AND SPECIFIC FEATURES ................................ 11

3.1 Definition of the potential system architectures .......................................................... 113.1.1 In-vehicle system .................................................................................................... 113.1.2 Intra-train network ................................................................................................... 16

3.2 Specific features and technologies for Case One: container wagon .......................... 183.3 Specific features and technologies for Case Two: tank wagon .................................. 193.4 Comparison of architectures and discussions on optional technologies .................... 21

4. CONCLUSIONS .................................................................................................................. 24References ................................................................................................................................. 25

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Executive Summary

This deliverable presents the results of task 2.1 within Work Package WP2. As the first step of the development of cargo condition monitoring system, task 2.1 aims at the outline design for general condition monitoring and formulating the measurement concept for the specific use cases. Therefore, the following activities have been carried out:

• Design and setup of a modular monitoring platform as basis for general condition monitoring (TRL 3)

• Formulation of overall measurement concept in the case of a. container wagon with sensitive goods b. tank wagon carrying hazardous goods

• Definition of required features and technologies including available sensor equipment, position of attachment for condition monitoring, etc.

Section 1 introduces the overall Work Stream WS1, i.e. Cargo Condition Monitoring, and the specific objectives of Work Package WP2 within WS1. The outcomes of WP1 related to WS1 are presented, providing the benchmark for the development.

Section 2 reviews the existing solutions dedicated for containers and tank wagons, especially focusing on the mounting solutions. Taking as a benchmark this information and the state of the art of the general monitoring devices, the features of the new system to be developed have been proposed.

Section 3 describes several potential system architectures, considering both the in-vehicle network and the intra-train network. A distributed system design is preferred, considering easier scalability and better compatibility with wagon condition monitoring systems. Moreover, the dedicated measurement arrangements are elaborated for the defined cases, concerning the applicable sensors, the required features and appropriate mounting.

Finally, the conclusions highlight the advantages of the proposed concept and the important issues of designing wireless distributed energy harvester powered monitoring systems in the context of rail freight wagons.

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List of abbreviations

BLE Bluetooth Low Energy CCMS Cargo Condition Monitoring System LDHV Low-Density High-Value LPWAN Low Power Wide Area Network MEMS Microelectromechanical system RF Radio Frequency T2G Train-to-Ground TRL Technical Readiness Level UHF Ultra-High Frequency WP Work Package WPAN Wireless Personal Area Network WS Work Stream WSN Wireless Sensor Network

List of figures

Figure 1 Different door mounting solutions (top left: DB Cargo Smartbox (DB Cargo, 2010)); top right: Starcom Tetis R source: https://www.starcomsystems.com/products/tetis; bottom: Starcom Tetis source: http://www.satphonestore.com/application-browsing/tracking/fleet-tracking-satellite/starcom-tetis-tracking-system.html ) ............................................................................... 8Figure 2 Demonstrations of different tank wagon monitoring systems (top left: IMT’s smart tank sensors on a Hoyer tank container source: https://www.hoyer-group.com/en/press/news/details/smart-tanks-for-smart-transports/ ; top right: XLOAD level sensors source: http://railcore.com/app/uploads/2016/02/TRIG_brochure.pdf ; bottom: Guardmagic Railroad fuerl tank monitoring system source: https://www.guardmagic.com/01-engl/11e-solution/16e-train-tank-online/train-tank-002.jpg ) ......................................................... 9Figure 3 Architecture 1 ............................................................................................................... 12Figure 4 Architecture 2 ............................................................................................................... 14Figure 5 Architecture 3 with onboard RFID solution ................................................................... 15Figure 6 Architecture 4 with wayside RFID solution ................................................................... 16Figure 7 Intra-train communication ............................................................................................. 17Figure 8 Train-to-Ground communication .................................................................................. 17Figure 9 Configurations of the sensor arrangement for container monitoring ............................ 19Figure 10 Configurations of the sensor arrangement in the terms of tank monitoring ............... 21

List of tables

Table 1 General specifications and limitations of the energy harvesting methods potentially to be applied ........................................................................................................................................ 11Table 2 Sensors and required features in Case One ................................................................. 18Table 3 Sensors and required features in Case Two ................................................................. 20Table 4 Architectures of intra-train system for general condition monitoring ............................. 22Table 5 Potential technologies for each functional module ........................................................ 23

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1. INTRODUCTION

It is commonly accepted that the rail freight transport is more appropriate for bulk cargo and heavy goods like coal and ores. However, the type of transported goods has started to change over the past years. WP1 has identified two types of goods, i.e. Low-density high-value goods (LDHV) and dangerous goods, of which tracing and monitoring play a significant role to increase the attractiveness of rail freight transport by improving the visibility, reliability and safety of railway freight service.

1.1 Objectives

The work stream 1 (WS1) of the INNOWAG project is to develop a system based on an autonomous self-powered wireless sensor network (WSN) for cargo tracing and monitoring the condition of key parameters for critical types of cargo. The proposed system will overcome the issues related to sensor wiring and power supply on freight trains by using a wireless communication network powered by energy harvesting solutions.

The development of WS1’s concept starts from the work package 1 (WP1), providing benchmarks and outlining the requirements for the design of the innovative cargo condition monitoring system (CCMS), which have been addressed by the deliverable D1.1 and D1.2 accordingly.

WP2 deals with the elaboration and validation of a technology concept defining suitable configurations for a CCMS in the scope of rail freight transport of special goods. The specific objectives of WP2 are presented as follows:

• Formulation of the overall system concept in the case of LDHV-goods transported by container wagons and dangerous goods transported by tank wagons, especially considering the arrangement of data acquisition devices, i.e. sensor systems and tracing devices;

• Design of a power supply system providing an autonomous operation of cargo condition monitoring through utilisation of energy harvesting technologies, such as vibration harvesters, solar panels, radio frequency (RF) harvesters, etc.;

• Design of a WSN that ensures secure, regular and reliable data communication within the network, i.e. intra-train communication, as well as a communication system between the WSN and a central application server, i.e. Train-to-Ground (T2G) communication;

• Establishing an IT infrastructure for data processing, storage and representation; • Validation of the developed technologies for cargo condition monitoring system (CCMS)

in a relevant environment (at TRL 5).

WP2 is broken down into four tasks. This report presents the results of Task 2.1 Monitoring Sensor Systems, defining several potential modular system architectures and especially focusing on the measurement concepts that can record the most significant condition parameters of special goods, and should be compatible with the energy harvesting technologies and the wireless communication technologies.

1.2 Background

The previous deliverable D1.1 investigated the individual technologies and solutions in different areas, namely:

• sensing and sensor technologies in terms of the potential measurands within the project scope;

• energy harvesting technologies applied in the railway sector; • identification and tracking solutions used in the railway sector; • wireless communication technologies used in the railway as well as other industrial sectors • big data approaches in the railway sector

The integrated condition monitoring solutions have been reviewed in D1.1 as well, including existing CCMS specific for containers and tank wagons (/containers). This provides information

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on benchmark products and the state of the art of sensor as well as telematics applications on freight wagons, which is summaries as below:

• Almost all monitoring systems are based on concentrated data collection devices, i.e. telematics boxes, integrating GPS for tracking, GSM for data transmission, sensors for measuring, etc.

• Telematics boxes allow wired or wireless connection (mostly based on IEEE 802.15.4) to external sensors for measuring condition parameters of wagons / goods.

• A product can provide several additional optional functions and/or different optional solutions for one module.

• Tracking & tracing of wagons is the most important application in practice. • Existing devices are mostly powered by batteries, whereas a few deploy axle generators

or solar panels. • GSM is the standard solution for data transmission, GNSS for tracking. • RFID technology is only used for wagon identification, rarely for data communication • Web application is the standard solution for the user interface. Cloud platform is a common

choice.

The deliverable D1.2 defined INNOWAG performance indicators for assessing the performance or potential performance of the outputs, and proposed the requirements of the further development. Two use cases have been proposed:

• Case One: LDHV goods transported by flat wagons using containers • Case Two: Flammable gas transported by tank wagons

Clearly, the selection of sensor technologies relies on the specific use cases. Therefore, the prioritisation in terms of measurands were specified for both cases, namely:

i. Case One: • MUST: geolocation, temperature inside containers • SHOULD: humidity inside containers • COULD: shocks that containers are exposed to, vibration that containers are exposed

to, intrusion into containers, weight ii. Case Two:

• MUST: geolocation, temperature inside tanks • SHOULD: gas leak

Based on the inputs from D1.1 and D1.2, this report started from a brief review on the features of the existing CCMS dedicated for containers and tank wagons to set the benchmark.

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2. CONCEPT OF CARGO CONDITION MONITORING SYSTEM

2.1 Summary of state of the art CCMS

The current monitoring systems applied for rail freight transport are referred to as the telematics devices, most of which are attached on the outside surface of loading units for the purposes of tracking. In the example from VTG connect, see INNOWAG D1.1 (2017), permanent monitoring of the wagon is achieved by adding a tracking device and a solar panel to it. It can also receive data via Bluetooth LE from other instruments, allowing a more distributed power, cost and information load.

To monitor specific condition parameters, it requires the connection with additional sensors and dedicated designs of mechanical interface in terms of mounting, since an added complication in cargo monitoring is that not all sensors have a ready interface on the outside of the cargo container. Hazardous goods transported in tanks use sensors with an interface on the outside, and have the added advantage of a high value asset that may justify some permanent sensor cabling. This may enable some lower complexity radio transmission schemes. The following case studies aim at summarising the parameters monitored and the mounting solutions used by the existing CCMS designed for containers and tanks, based on the outcomes of the deliverable D1.1.

2.1.1 Case study: container wagon

Since conventional containers are designed without any mechanical interface on sidewalls for the installation of sensors, the door mounting is the only existing solution in terms of mounting. The following pictures in Figure 1 present three different door mounting solutions.

Figure 1 Different door mounting solutions (top left: DB Cargo Smartbox (DB Cargo, 2010)); top right:

Starcom Tetis R source: https://www.starcomsystems.com/products/tetis; bottom: Starcom Tetis source: http://www.satphonestore.com/application-browsing/tracking/fleet-tracking-satellite/starcom-tetis-tracking-

system.html )

These devices are designed in two parts: one part inside the container, integrating sensors for measurements, and the other part outside the container for tracking and data communication. Besides geolocation, the measurands could usually be intrusion, temperature, humidity, shock, light, tilt, etc.

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2.1.2 Case study: Tank wagon

In the case of tank wagons, the mounting of sensors can be based on the existing fittings, such as joints for manometers and thermometers, dip-tube, domes, etc., which vary in design and position. The following pictures in Figure 2 demonstrate several ways of the sensor arrangement on tank wagons:

• Reading thermometers and manometers using universal sensors • Level measuring using RF sensors placed on the outside bottom of the tank or on the

dome or using invasive sensors mounted on the dome • Monitoring of temperature and pressure through the dip tube or on the dome

The typical parameters measured are temperature, pressure, valve status, dome opening and filling level.

Figure 2 Demonstrations of different tank wagon monitoring systems (top left: IMT’s smart tank sensors on a Hoyer tank container source: https://www.hoyer-group.com/en/press/news/details/smart-tanks-for-

smart-transports/ ; top right: XLOAD level sensors source: http://railcore.com/app/uploads/2016/02/TRIG_brochure.pdf ; bottom: Guardmagic Railroad fuel tank

monitoring system source: https://www.guardmagic.com/01-engl/11e-solution/16e-train-tank-online/train-tank-002.jpg )

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2.2 Features of the new CCMS

Based on the existing and emerging solutions for condition monitoring and tracking, the new CCMS will be a modular system, with costs, data transport and sensor requirements delegated to the most appropriate stakeholder.

Breaking this down into system functionality, the following functional stages (features) can be identified:

i. Cargo parameter sensing (cargo owner) and sensor data servicing and transmission (conveyor)

The new CCMS will be able to transmit data from any sensors selected by the cargo owner, using CCMS enabled infrastructure, which would be supplied as an added service by the freight forwarder (conveyor).

ii. Vehicle-side hub with distributed nodes (wagon owner)

Relative costs are therefore minimised at each stage by avoiding the tracking and T2G / intra-train communication module in the container mounted unit, exploiting equipment (with minimal sensing) fitted to the wagon. For sensing cargo parameters, only sensor nodes should be placed on the container.

Since wagon condition monitoring systems are nowadays more demanded by conveyors and wagon owners, the new CCMS considers either the compatibility with them by using a common communication interface or an integrated scalable solution by adding bogie nodes, where the sensors for monitoring of wagons / bogies are mostly placed. This results in a distributed system design.

iii. Data transmission to driver (intra-train communication) in the case of safety-related monitoring (conveyor)

When the driver can be aware of the abnormal conditions of goods / wagons, appropriate measures can be taken to prevent accidents.

iv. Data location and transmission to terminal (T2G) (conveyor / wagon owner)

Data with a time and location stamp are sent to terminal (e.g. cloud and server PC) to for the further processing and assessment to maximally extract knowledge from the data.

v. Permanent power supply or long battery life (conveyor)

Advance data processing, such as failure prediction, requires sufficient data rate in terms of sensing and transmission, which costs more power. In this sense, the energy harvesting solutions are applied to extend the period of battery change or even provide permanent power supply.

vi. Utilisation of infrastructure in view of future technologies

Finally, yet importantly, low-TRL technologies and solutions will also be investigated to demonstrate the feasible utilisation of the infrastructure in the near future, such as data communication via trackside RFID reader or LPWAN (low-power wide-area networks) based base stations that are currently deployed in urban areas.

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3. GENERAL SYSTEM ARCHITECTURE AND SPECIFIC FEATURES

Designing a system that involves communications with sensors on an unpowered freight wagon needs to achieve a balance between available power, communication rate, communication type and the demands for data. These elements must be matched correctly if the system is to function. At the stage of the outline design, it is important to have an overview where the power could come from, which communication would to be established, what data needs to be measured, and where the measurements can take place. The following subsections present the general system architectures, and then specify the sensor technologies and the features for both use cases respectively.

Of the possible designs below, further work in other tasks will elaborate on the feasibility of the various schemes, especially focusing on power supply and wireless communication.

3.1 Definition of the potential system architectures

The system configurations may vary depending on specific application scenarios. In this sense, a modular design makes the envisaged CCMS highly flexible. For one functional module, several solutions have been identified in the previous deliverables. Due to their difference in TRL, the possible alternative approaches to cargo condition monitoring are with varying levels of new technology requirements and available data rates. Both trackside (RFID portals) and real time (mobile communications) approaches are considered for data retrieval from the train, and both have advantages, depending on level of coverage, amount of data required, and equipment cost (RF powered transceivers have a limited data capacity but are very low cost. The additional infrastructure required in the form of gateways could be substantial if not already deployed for other applications). Some approaches are more modular than others, or require the addition of more equipment. Not all desired parameters are available in all approaches, due to the use of a modular approach or not.

3.1.1 In-vehicle system

The following architectures present the subsystems / components and the link between them within one wagon. Although these general architectures below are illustrated by example of container wagons, they are applicable for other types of freight vehicles as well. For a specific loading unit, the dedicated sensor arrangement should be designed according to the construction of the loading unit and the type of the transported goods.

Recent developments in solar powered instrumentation on freight wagons (see VTG connect, above) open the prospect of using the wagon tracking device as a gateway to location and data communication services.

Harvesting power through whatever appropriate means locally to sensors, with distributed functionality, should allow shared facilities across the wagon to increase power for local functions, as well as reducing cost and complexity of individual modules. Sensor functions should be distributed in such a way that they are applied at low cost and only as required, on the assumption that enabled freight wagons and infrastructure will support the sensors if and when they are fitted.

It should be noted that energy harvesting methods need to be supported by appropriate energy storage and management systems. Table 1 illustrates the limitations and opportunities available for the principle energy harvesting methods being considered here:

Table 1 General specifications and limitations of the energy harvesting methods potentially to be applied

Energy harvester

type Power

availability Constraints Energy storage requirements

Available mounting locations

Solar 100 mW/cm2 during daylight hours

Seasonal and diurnal, affected by cleanliness, location.

>10kJ (for example D cell rechargeable). Full functions for 24 hours

Above suspension, open air

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(exposure to sunlight).

Vibration >30mW when train in motion

Must be mounted on axlebox/below primary suspension. Sensor mass limited by mounting constraints

>3J. Reduced functionality when wagon is stationary.

Below primary suspension, fixing points must be available.

RF Microwatts, when reader switched on

Only enough power to return a simple sensor value when polled.

Single reading and transmission (microjoules, mF capacitor).

Metal structure will have interference to the communication between reader and tag

Wind

1 mW/cm2

when train in motion, using a micro turbine with 30 l/min

may be vulnerable to damage

Additional energy storage for extended stationary periods

open air

Architecture 1

The following architecture proposal in Figure 3 carries the lowest technical risk and represents the distributed system concept, with innovation including harvester power sources appropriate to the power requirements integrated with each component. The system may be configured or extended as required, with the minimum basic level of infrastructure in place.

Figure 3 Architecture 1

Building on available technology, with a focus on delivering sensor readings in/around the cargo container the following components are proposed:

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1) Communications hub, powered by solar harvesting, containing tracking module, communication module, local low power networking module and integral temperature and shock sensors as options. The communication module could be referred to as the T2G communication or the intra-train communication, which is addressed in Section 3.1.2. The optional technologies for each module are discussed in Section 3.4.

Permanently attached to a digitally enabled tracked wagon, this is the communication hub used to locate the cargo and provide basic remote communications and local networking support to any other additional sensor of interest (this could include both wagon condition and cargo condition sensing).

If not already fitted to the wagon, the communications hub may be temporarily fixed to the container in conjunction with the cargo sensor hub.

2) Cargo sensor hub/node; with local radio communications via low power network to the communications hub on the outside. Its configurations are determined by the application in Section 3.2 and Section 3.3. By example of container monitoring, it could be either a sensor hub with low power radio/RF connection enabled to sensors on the inside of the container or only a sensor node integrating multiple sensors. The former requires a lot of power, having to be powered by solar / wind harvesting. The latter can be a simply battery powered sensor node. RF harvesting can be also applicable depending on the demands of data.

3) Bogie mounted wagon/wheel condition monitoring unit, powered by vibration harvesting. The bogie node delivers vehicle condition monitoring (if required, but outside the scope of the project).

Architecture 2

The following proposal in Figure 4 entirely relies on wheel mounted vibration energy harvesters and carries the great amount of technical risk, while moving the majority of the investment to the wheels of the wagon. But this approach does minimise the investment required in the wagon body or cargo container. Data rates may be significantly lower than wagon body mounted communications solutions including higher power harvesters, and it will be more difficult to measure shocks due to shunting.

It is sensible to use vibration energy harvester power to measure location, gather sensor readings and remotely transmit data. The very limited RF harvester power available can then be used only for sensor readings and short range radio transmissions, yielding a higher data rate. This two-level energy harvesting design maybe cannot provide sufficient power to fulfil the measurement requirements. A further investigation will be carried out to identify the power trade-off.

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Figure 4 Architecture 2

Architecture 3

This design deals with a RFID-based sensing platform that incorporates an on-board RFID reader, reading the data from the tag sensor nodes. This proposal includes a significant reliance on RF power transmission technology for sensor reading transmission around the wagon, but allows for remote transmission using harvester powered communications. At this stage, it is uncertain if the range and power transmission requirements can be achieved for the data rate required to transmit around the outside of the container.

As demonstrated in Figure 5, Architecture 3 consists of:

1) Tag cargo sensor node

Each tag sensor node includes one or several sensors, the types of which depend on the goods type. The sensors are connected to a controller embedded in the tag sensor node, recording the sensed data in a memory and controlling the RFID tag to send the data to RFID reader when the tag is polled by RFID reader. Tag sensor nodes can be powered by solar or wind harvesting. Considering less needs of power in this case, battery can be a backup solution.Error! Reference source not found. 2) Reader hub

RFID reader is placed on the bogie where the antenna of the RFID reader enables the RF (wireless) communication between the reader and the tag sensor nodes on the wagon. The data from each tag sensor node will be requested and obtained at a defined data rate. Due to the limited communication range of RFID technique, there is one RFID reader required for each wagon.

3) Communication hub

The data gathered by the RFID reader is sent to the communication node placed on the same bogie via the wired connection, which forwards the data to the terminal or the locomotive. The gateway node also contains the tracking module.

Both reader hub and communication hub are powered by vibration harvesting with one harvester on each wheel. Alternatively, the reader can be moved to the wagon in conjunction with communication module, same as the one in Arch 1 powered by a solar panel.

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4) Tag bogie node used for wagon monitoring, having the same scheme as tag cargo node (if required, but outside the scope of the project).

Figure 5 Architecture 3 with on-board RFID solution

Architecture 4

This architecture deals with the alternative design of the RFID-based sensing platform that incorporates a wayside RFID reader, reading the data from the tag sensor nodes on the trains passing by. This also has the great amount of technical risk

In Architecture 4, the tag sensor node is the same as Architecture 3. The difference is that the reader hub is fixed on the wayside. The on-board tracking module is not needed because the wagons can be tracked by the wayside devices along the track, where the location is known when installed.

The RFID reader will receive the data from each tag sensor node when the train passes by. There is only one RFID reader needed at each wayside point. Regarding the communication between the reader and the terminal, it can be either wired or wireless communication. If wireless communication is decided, cellular networks or communication satellites will be involved. Otherwise Ethernet cables could be used for the wired communication.

It must be noted that the lack of RFID infrastructure and the issues of data exchange between different stakeholders make Arch 4 hardly applicable. Nevertheless, demonstration of the technical feasibility of such low-TRL technologies is one of the project objectives as well. This wayside solution can significantly simplify the vehicle-side instrumentation.

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Figure 6 Architecture 4 with wayside RFID solution

3.1.2 Intra-train network

The envisaged CCMS concerns not only the system within one vehicle but also the network across the train. Depending on the freight traffic mode, the capability of intra-train communication may be required. By example of the trainload traffic, only one T2G communication module is required on the train, which is usually preferred to be placed on the locomotive. This means the networks on the individual wagons and the locomotive constitute one WSN, allowing the communication between wagons and wagons as well as between wagons and the locomotive. In the case of single wagonload traffic, each wagon should, by contrast, have an independent network. The connection between the wagon and the locomotive could be not necessary. In this sense, different ways of the intra-train communication are considered. Figure 7 shows the data links across the train:

a. Multi-hop wireless network from wagon to wagon (dark blue). This means that each wagon needs to relay the sensor data from numbers of wagons before it towards the locomotive. It can be applied to any of the system architectures showed in the previous step, i.e. with container nodes only (red), or with additional wheel nodes (green).

Advantages: Disadvantage:

+ Only short-range communication involved

- Inefficient due to accumulation of data along the way

- Slow data propagation - Not scalable - Energy consumption higher for nodes

closer to the locomotive - Higher chance of data loss

b. Direct wireless link from each wagon to locomotive (orange). Similarly, this can be applied to any of the system architectures showed in the previous step, i.e. with container nodes/bridges only (red) or with additional wheel nodes (green).

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Advantages: Disadvantage:

+ Faster + More scalable + More balanced energy consumption

among nodes + More robust to data loss

- Nodes farther from the locomotive have a worse link and may consume more power and loose more data

c. Hybrid wireless network, combining option a and option b.

d. No intra-train communication

Advantages: Disadvantage:

+ Simplicity + Scalability

- Drivers cannot be aware of the conditions of goods/wagons.

Figure 7 Intra-train communication

Figure 8Figure 7 shows the T2G communication, considering different in-vehicle architectures. and the presence of intra-train communication.

a. Direct link from container node to terminal. The wireless node on the container is equipped with a cargo sensor hub/node for sending directly the sensor data.

b. Connection to terminal via the node on the wagon/bogie. In this case, there is a short-range link between the container node and the wagon/bogie node, and a long-range link from the wagon/bogie node and the terminal.

c. Connection to terminal via the locomotive. This works in conjunction with the intra-train communication, where the sensor data is first sent to the locomotive, and from there it is forwarded over a long-range connection to the terminal

Figure 8 Train-to-Ground communication

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3.2 Specific features and technologies for Case One: container wagon

Above are the general system designs. In terms of the sensing solutions, the sensor arrangement must be considered by giving a concrete application case. For the purposes of the demonstration, two cases have been defined in the previous work. Case One is defined that LDHV goods are transported by flat wagons using containers. As mentioned in Section 1.2 the prioritisation of the measurands has been proposed in the previous deliverable:

• MUST: geolocation, temperature • SHOULD: humidity • COULD: shocks, intrusion, vibration levels, weight

That means geolocalisation and temperature measurements must be achieved within project duration, whereas humidity measurements should be implemented, may not be achieved. Measurements of shocks, vibration levels as well as weight and intrusion detections are desirable, not necessary, could be planned as an optional function, if time and resources permit implementation.

The sensor technologies for obtaining these measurands were reviewed in D1.1, being mature enough (at TRL 9). Especially, the low-power MEMS sensors are suitable for the implementation of the sensor nodes within a WSN. Table 2 shows the applicable sensor types and the required features.

Table 2 Sensors and required features in Case One

Measurand Sensor type Required features

Temperature Temperature sensor

• Measurement range: -40°C to + 60°C • Accuracy: ≤ 2°C • Sampling rate: 5% of the total recording interval and

a maximum period of 15 min for temperature sensitive goods

Humidity Humidity sensor • Measurement range. up to 100% • Accuracy: ≤ 3% • Sampling rate: same as temperature sensor

Shock Accelerometer • Measurement range. up to 50 g • Sampling rate: hourly min/max/average

Vibration Accelerometer Measurement range. up to 16 g

Weight Strain gauge • Measurement range: manual configuration • Accuracy: ≤ 1% for weight measurements • Sampling rate: on change / per loading/unloading

Intrusion

Reed switch • Should be compatible with the mounting solution • Event driven

Light sensor • Threshold needs to be identified by testing

RFID seal • Frequency should be compatible • Event driven

Amongst them, the weight sensor could be regarded as a small specific monitoring system rather than a sensor. Since a weight “sensor” typically consists of two strain gauges per bogie and a central control unit, it has its own GUI for executing measurements and displaying results. The commercial weight sensors do not allow the further development and thus are hardly fitted into the integrated CCMS envisaged by INNOWAG. On the other hand, the development of a weighing system based on strain gauges is out of the scope regarding the limited project resources.

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Therefore, it is suggested that INNOWAG CCMS could maintain the possibility of wireless communication with the existing weight sensors rather than include them. Architecture 1 has the most favourable distributed power and communications system to achieve this.

Three applicable solutions are proposed for intrusion detection. However, reed switch requires a specific mounting and trigger design, whereas RFID seal requires the deployment of a RFID reader. The application of light sensors has fewer constrains for detecting door opening. The threshold must be defined by testing.

Regarding the mounting, the case studies show the feasible ways to install telematics devices without damaging or reconstructing the standard container. The container-side unit of the developed CCMS will be based on the door mounting as well, considering the influences of the mounting location on harvesting energy and communicating data.

The container-side unit can be divided into two parts. One part contains the sensors / sensor nodes measuring the environmental parameters inside the container. The other part is installed outside the container for data transmission. To be specific, there are two configurations concerning the sensor arrangement, see Figure 9.

a. Small network of wireless sensor nodes (yellow) inside the container, with short range communication to the bridge node (red) on the door. The bridge node is half inside and half outside the container. The inside part communicates with the passive or active sensor nodes, and the outside part communicates with the exterior. Each part has a dedicated radio module. The two parts are connected via wires and thus the sensor data is forwarded from the container to the exterior. The sensor inside could be RF powered sensors that are very low cost “disposable” sensors, single parameter only, attached to the specific cargo by the shipper or owner of the cargo. These sensors are only active for a single journey (or until the packaging is reused), or could be attached to hazardous material shipments.

Advantages: Disadvantage:

+ Multi-point sensing is possible inside the container

+ Flexibility and scalability for sensing inside the container

- The bridge node is more complex and must power two radio modules, one for communicating with sensors, the other for achieving the connection to ground.

b. One wireless node with multiple sensors, the sensor protruding inside the container and the wireless part (at least the antenna) being mounted outside the container.

Advantages: Disadvantage:

+ Simplicity + Smaller power consumption than

option a

- Single-point measurements

Figure 9 Configurations of the sensor arrangement for container monitoring

3.3 Specific features and technologies for Case Two: tank wagon

Case Two is defined that Flammable gases are transported by tank wagons.

In this case, the prioritisation of the measurands is as follows:

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• MUST: geolocation, temperature • SHOULD: gas leak

The environmental parameters, i.e. temperature and pressure, significantly depend on the type of the transport gas. Generally, gases transported by tanks can be compressed gases, liquefied gases, strongly cooled liquefied gases, dissolved gases under pressure. The working pressure is commonly under 30 bar, while the temperature ranges from - 40°C to + 70°C. These ranges are covered by the common MEMS sensors.

The gas leak could be indirectly detected by monitoring of temperature and pressure, since the gas leak must result in the status changes of the inner temperature and pressure. The indicators for alarms may vary according to the normal temperature and pressure, and thus should be investigated for specific scenarios. In the case of liquefied gases, gas leak could principally also be detected by monitoring of the liquid level. However, the level measurement technologies are mostly power hungry especially for the measurement range of about 3 m (i.e. tank height), and are not applicable for low voltage supply. In practice, the level measurements are mostly executed only for loading / unloading of tanks rather than continuously monitoring. Nevertheless, a case study shows the feasibility of utilising the ultrasonic sensor mounted on the tank bottom for level monitoring. This should be investigated in the further development. The conventional detection methods of gas leak use gas / chemical sensors, infrared sensors or are based on acoustic measurements, which are usually used for detecting gas release in each area. Womble (2007) mentioned on-board sensors are also capable of detecting the airborne acoustic emission from the gas leak. In addition, the on-board method could include the vibration measurement of the tank walls. Again, this solution based on acoustic emission sensors is not a low-power solution, and thus is not suitable in this project although power cycling and duty ratio can be used, where sufficient energy storage is available, to significantly reduce the average power consumption. Table 3 summaries the most feasible sensor technologies and required features in Case Two.

Table 3 Sensors and required features in Case Two

Measurand Sensor type Required features

Temperature Temperature sensor

• Measurement range: -40°C to + 70°C (for most gases)

• Accuracy: ≤ 2°C • high sampling rate when power is sufficient

Gas leak

Pressure sensor + temperature sensor

• Measurement range: up to 30 bar (for most gases)

• high sampling rate when power is sufficient • specific indicators of gas leak

Level sensor (ultrasonic) • Measurement range covers the tank height

(about 3 m) • low power consumption

Regarding the mounting, the case studies show the feasible ways to install sensors on tank wagons through the existing fittings, such as joints for manometers and thermometers, dip-tube, domes, etc. The flange mount is the common solution. The sensors could be integrated in one housing plugging into the tank or distributed on the tank. The sensor arrangement mainly relies on the positions and designs of the fittings, and should also consider its influence on communicating data and harvesting energy. Figure 10 illustrates the mentioned two potential configurations with red pieces for the parts inside the tank and yellow ones for the parts outside the tank.

a. Small network of wireless sensor nodes distributed on the tank in the case that different sensor technologies should be deployed on different positions. For instance, the universal sensor reads the thermometer on the tank dome, while the ultrasonic sensor mounted at the

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tank bottom monitors the liquid level. The pressure sensor is plugged into the tank wall. These three types of sensors cannot be integrated in one node.

b. One wireless node with multiple sensors, which is simple for mounting, but may have communication issues with the bogie nodes, especially the tank node is placed on the dome.

Figure 10 Configurations of the sensor arrangement in the terms of tank monitoring

It should be noted that a single insertion point with multiple sensors requires fewer intrusions into the pressure vessel, and will therefore carry a low installation cost. Communication around the tank may be achieved through incorporating a local energy harvester into the sensor interface, or by cabling to the sensor. These would, by definition, be high value installations.

3.4 Comparison of architectures and discussions on optional technologies

Energy harvester powered or other low power instrumentation systems generally operate at a measurement and transmission rate matched to the application. The system is mostly turned off when actions are not required, to save power. In battery powered systems the limiting factor is how large the battery can be and how frequently it can be economically changed. All actions are therefore optimised to undertake the least possible amount of activity in the shortest possible time. Energy harvester powered systems are designed to use an average power that is less than the average power harvested, with energy storage in place to match source/demand levelling.

So far four system architectures for general condition monitoring have been proposed with considerations on the data links across the train and the links from the train to the ground. The combinations are given in Table 4.

Table 4 Architectures of intra-train system for general condition monitoring

In-vehicle Architecture

Intra-train communication

Train-to-Ground communication Comments

Arch 1

with option a, b, c option c + lowest technical risk + compatible and easy Integratable with existing wagon / cargo monitoring systems + easy scalable by adding sensor nodes for cargo / wagon monitoring - multiple harvesters involved due to the distributed design

without option d option b

Arch 2

with option a, b, c option c + capable of integrating bogie monitoring + minimise the instrumentation on wagon side and container side - high technical risk - remote transmission requires more power due to the facility position - overall lower data rate

without option d option b

Arch 3 with option a, b, c option c + fewer power demands on tag sensor nodes

- low TRL and high technical risk - high complexity and power consumption of bogie-side instrumentation without option d option b

Arch 4 without option d Option a

+ least instrumentation on wagon-side + overall low costs for on-board devices + integratable with wagon identification with RFID technology - low TRL and high technical risk - lack of infrastructure at present - issues of data ownership and data exchange

The various technologies and solutions for each functional module have been summarised in D1.1, and initially discussed and narrowed down in D1.2. In the sense of their applicability within the context of the potential system designs, they are assessed in Table 5.

Table 5 Potential technologies for each functional module

Module Technologies and solutions

Assessment

Sensing passive or semi-passive RFID-based sensor

Inapplicable, since the sensing component needs to be placed inside the container/tank, whereas the antenna needs to be placed outside.

conventional sensor

Detailed in Section 3.2 and Section 3.3

Tracking wayside RFID Applicable for Arch 4

GNSS Most common solution

terrestrial radiolocation

Technical feasible by using the mobile network. However, the accuracy significantly depends on the concentration of cell base stations. In the case of rail freight transport, the accuracy could not be guaranteed due to a limited number of base stations along the track.

Train-to-Ground communication

mobile network Most common solution

wayside RFID Applicable for Arch 4

Satellite Applicable, but much more expensive. Suitable for specific scenarios in a lack of ground infrastructure for terrestrial communication.

LPWAN Potential applicable in view of future trends. It also depends on infrastructure.

Intra-train communication

Bluetooth Low Energy

BLE is the most power efficient and has a very attractive ratio of energy per bit transmitted. However, the range of BLE is possibly too low.

WPAN such as IEEE 802.15.4

More suitable when mount the network manager at the top of the wagon, where a vertical line of sight is more achievable.

UHF (such as 868 MHz, 433 MHz)

More suitable for local network, as the signal has more chance of bending round the size of metalwork on a train

To be investigated and tested in next task

Terminal (IT infrastructure)

Cloud Both solutions are available, having to be adapted to INNOWAG use cases. software platform

on local servers (e.g. OSIsoft PI system)

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4. CONCLUSIONS

The problems around low cost, robust, wireless distributed energy harvester powered instrumentation systems applied to rail freight cargo condition monitoring have been discussed. Several approaches have been proposed, making use of available technologies for sensing, harvesting power and wireless transmitting power as well as data around the vehicle, with advantages and disadvantages that may eliminate some options after further investigation and development in subsequent tasks. The key trade-offs to be considered are; energy vs robustness, communications vs energy available, sensor type vs energy and data rate.

All the proposed architectures require different stakeholders to invest in the monitoring system, by mounting equipment to the ground infrastructure, the wagon, container and/or individual cargo box. A more distributed approach, where direct benefit is accrued directly to the equipment installer (for example, wagon tracking or sensors that are compatible with multi-modal transport) may assist in acceptance and deployment of the technology. An appropriate technical solution, once the communication and energy distribution/provision solutions have been fully assessed, should take this into account. Nevertheless, the main hub for tacking and remote communication is supposed to be mounted on the wagon, guaranteeing the benefits of the wagon holder, who should also be the owner of the monitoring equipment. Therefore, it is also important to maintain the compatibility or/and integrability of the CCMS with wagon condition monitoring system.

Moreover, the detailed measurement concept and sensor arrangements are proposed for the both cases. The sensor installation mainly depends on the construction of the freight wagon or cargo containers on an assumption that a reconstruction must be avoided. Especially in the case of tank wagons, the wagon design varies according to the goods type. An appropriate measurement system will be identified in a given specific scenario after basic testing of sensors and establishing the monitoring platform.

In the sense of a modular design, the optional solutions/technologies have been further narrowed down. Basically, different solutions are suitable to different scenarios. It is suggested that a most common option could be used for the general system design, remaining the compatibility with other options. The communication module and the power supply system will be focused in next tasks.

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References

INNOWAG D1.2 (2017), Deliverable D1.2: Specifications and Requirements for INNOWAG Technologies and Solutions, Shift2Rail project: Innovative Monitoring and Predictive Maintenance Solutions on Lightweight Wagon

INNOWAG D1.1 (2017), Deliverable D1.1: Benchmark and market drivers for an integrated intelligent and lightweight wagon solution, Shift2Rail project: Innovative Monitoring and Predictive Maintenance Solutions on Lightweight Wagon,

DB SCHENKER (2010), Presentation. DB SCHENKERsmartbox, 3rd European Conference on ICT for Transport Logistics 2010 in Bremen

Ovinto (2017), Monitoring of hazardous goods in unpowered transport units, online article, Source: http://www.ovinto.com/method.html, access: 10.07.2017

IMT (2017), Smart tank sensors, online article, Source: https://www.intermodaltelematics.com/, access: 10.07.2017

Mercury® xPRESS Platform Guide, Source: http://www.thingmagic.com/index.php/embedded-rfid-readers/44-mercury-xpress-platform/418-xpress-platform

DB Cargo (2010), Presentation. DB SCHENKERsmartbox, 3rd European Conference on ICT for Transport Logistics 2010 in Bremen

P. C. Womble et al. (2007), A Pressured Tank Car Inspection System for Railroad Transportation Security, 2007 IEEE Conference on Technologies for Homeland Security