PRE2018 3 Group3

Preface

Group Members

Name	Study	ID Number
Max Hanssen	Industrial Design	1257269
Jorick van Hekke	Electrical Engineering	1225185
Suryanto Horlez	Computer Science	1286714
Joeri Schults	Mechanical Engineering	1266330
Jules Vaes	Mechanical Engineering	1263196

Problem statement

The railways in the Netherlands are very vulnerable for all kinds of things. Think for example of fallen leaves, snow, weeds, dead animals, etc. These factors lead to unwanted delays. This autonomous robot is designed to tackle this problem and prevent delays from happening.

Subject

Autonomous railway cleaning robot

Objectives

• The system must be able to navigate through the Dutch railway system autonomously
• The system must be able to recognize the different obstacles on the railway
• The system must be able to clean the railway from obstacles autonomously.
  • For special occasions the system must alert the involved companies
• The system must provide a short-term solution for certain problems
• The system must avoid colliding with obstacles
• The system must be deployable at any time
• The system must not hinder the human operated train traffic

Users

The NS and ProRail. Indirect users are the train-users.

State of the Art

The past project of PRE2016 3 Group 3 was conducted in a similar design case. Hence, the wiki of this project was analysed along with the 63 references of their wiki page (numbered 1 - 63). However, some of these references could not be found anymore, as this project was conducted in 2016. Under each analyzed reference a short sentence describes a summary and relevance to our project.

• Link to the wiki of project group PRE2016 3 Group 3: http://cstwiki.wtb.tue.nl/index.php?title=PRE2016_3_Groep3#Group_3:_Railway_Maintenance_Robots

1. Smith, O. (2016). No more commuter misery? Trains fight leaves with lasers. Retrieved from http://www.thememo.com/2016/09/12/train-leaves-leaf-zapping-trains-rail-safety-and-standards-board-are-arming-up-with-microwaves-and-lasers/

   description

2. ETS SPOOR B.V. (n.d.). Railmonitor. Retrieved from http://www.etsspoor.nl/producten/meetapparatuur/railmonitor/

   description

3. Statistics about railway disturbances in the Netherlands. Retrieved from https://www.rijdendetreinen.nl/statistieken/

   description

4. Different kind of disturbances around railway tracks. Retrieved from https://www.prorail.nl/reizigers/storingen-op-het-spoor/

   description

5. Article about leaves on the railway tracks. Retrieved from http://www.metronieuws.nl/nieuws/binnenland/2016/11/die-rot-blaadjes-op-het-spoor-waarom-doen-ze-niets/

   description

6. Smith, O. (2016). No more commuter misery? Trains fight leaves with lasers. Retrieved from http://www.thememo.com/2016/09/12/train-leaves-leaf-zapping-trains-rail-safety-and-standards-board-are-arming-up-with-microwaves-and-lasers/

   description

7. Sorokanich, B. (2016). This Hand-Held Laser Makes Rust Literally Evaporate. Retrieved from http://www.roadandtrack.com/car-culture/classic-cars/videos/a30597/best-rust-remover-laser/

   description

8. P-Laser (2017). Laser cleaning applications. Retrieved from http://www.p-laser.com/applications_detail.aspx?AGUID=1f846979-8fea-4745-bcea-663800c027e5&LGUID=8565a502-c109-43ef-b1a1-dfba5f3edbf6/

   description

9. Schreiner, M. et all (2008) Handbook on the Use of Lasers in Conservation and Conservation Science. Retrieved from http://www.science4heritage.org/COSTG7/booklet/

   description

10. Vega, R. et all (1990). Laser ice removal system. Retrieved from https://www.google.com/patents/US4900891/

    description

11. Paper geometry railways. Retrieved from http://crema.di.unimi.it/~fscotti/ita/pdf/Scotti02.pdf/

    description

12. Paper wear railways. Retrieved from https://docs.google.com/viewer?url=patentimages.storage.googleapis.com/pdfs/US6218961.pdf/

    description

13. Railway monitor. Retrieved from http://www.etsspoor.nl/producten/meetapparatuur/railmonitor/

    Page not found; report: The RailMonitor is a mobile measuring system which can measure the cross direction profile of the railway tracks

14. Drones with infrared cameras 1. Retrieved from https://www.prorail.nl/nieuws/proef-met-drones-controleren-wisselverwarming-met-infraroodcamera-s/

    Measuring the temperature of railway switches to see if they are frozen (locked) or not. This is done by using drones equipped with an infrared camera.

15. Drones with infrared cameras 2. Retrieved from https://tweakers.net/nieuws/86694/prorail-zet-drones-in-om-verwarming-van-wissels-te-controleren.html/

    Page not found; report: The infrared images provide ProRail with information about the switches.

16. Railway switches inspection robot Felix. Retrieved from http://research.loccioni.com/en/robotics/felix/

    The first mobile robot for automatic railroad switch inspection Felix.

17. Europees Spoorweg bureau. System Requirements Specification (SUBSET-026). Paragraph 3.6.5. Retrieved from http://www.era.europa.eu/Document-Register/Pages/Set-3-System-Requirements-Specification.aspx

    The European Rail Traffic Management System (ERTMS) is a single interoperable train control and command system in the European Union.

18. European Rail Traffic Management System (ERTMS). Retrieved from http://www.railway-technology.com/projects/european-rail-traffic-management-system-ertms/

    The ERTMS is a major industrial project being implemented to enhance cross-border interoperability through Europe by creating a single standard for railway signalling. ERTMS is a continuous communication-based signalling system.

19. Falch (2017). cont jet 125 2500-26-0-e. Retrieved from http://www.falch.com/products/g588.html

    Working Page → http://www.falch.com/products/g569.html → Information about the base jet 125 2500-26-0-e high pressure water jet.

20. Baveck Machines (2017). Rail infrastructure - Rust removing brush. Retrieved from http://www.baveck.nl/en/rail-infrastructure/24-rust-removing-brush/

    Information about a rust removing brush for the railways.

21. Tackling a leafy issue, Railway Technology, retrieved from http://www.railway-technology.com/features/feature1457/

    The leafy issue on the railways can be tackled with a laser which causes to lift the leafy munch off the rails.

22. Herfst, ProRail, retrieved from https://www.prorail.nl/reizigers/weersinvloeden/herfst

    The different measures ProRail takes during the autumn.

23. Test met watersproeiers tegen gladheid door blaadjes op spoor geslaagd, Spoor Pro, 26 march 2015, retrieved from http://www.spoorpro.nl/spoorbouw/2015/03/26/test-met-watersproeiers-tegen-gladheid-op-spoor-geslaagd/

    An experiment with a water jet installation showed that this is a solution considering the slippery railways caused by leafs.

24. Nu al herfst?, ProRail, 14 august 2014, retrieved from https://www.prorail.nl/reizigers/nieuws/nu-al-herfst

    During the autumn of 2014 ProRail started an experiment which involved a water jet installation and a laser to solve the leafy problem.

25. Bladeren op het spoor weglaseren, Nemo Kennislink, 20 august 2014, retrieved from https://www.nemokennislink.nl/publicaties/bladeren-op-het-spoor-weglaseren

    Currently, the NS has developed a laser technique in collaboration with the Technical University of Delft. The lasers, mounted underneath the train, heat up the tracks. This causes leaves and other dirt not to attach to the tracks. This article specifies the method and accuracy of this technique.

26. With Laser Railhead Cleaner your train will never be late because of leaves in its way, Wonderful Engineering, retrieve from http://wonderfulengineering.com/with-laser-railhead-cleaner-your-train-will-never-be-late-because-of-leaves-in-its-way/

    Gives another explanation of the laser technique that is researched by the NS in collaboration with the Technical University of Delft, with other interesting details of the laser method and it’s specifications.

27. Zapping the leaves from the rails, Delta, 8 September 2014, retrieved from http://delta.tudelft.nl/artikel/zapping-the-leaves-from-the-rails/28710

    Page not found. Is another reference to an explanation of the laser technique, explained by the Technical University of Delft.

28. Jaarverslag 2015, ProRail. Retrieved from http://www.jaarverslagprorail.nl/FbContent.ashx/pub_1000/Downloads/ProRail-jaarverslag-2015.pdf/

    Page not found. Yearly report of statistics of NS in 2015.

29. Sprinter manufactured by Bombardier Technologies. Retrieved from http://www.bombardier.com/content/bombardiercom/en/transportation/projects/project.sprinter-netherlands.html?f-region=all&show-by-page=50&page=1&f-country=nl&f-segment=all&f-type=all&f-name=all

    Page not found. Refers to the sprinter light train of ProRail produced Bombardier Transportation, a Canadian company, in cooperation with Siemens.

30. Sprinter manufactured by Bombardier Technologies. Retrieved from https://nl.wikipedia.org/wiki/Sprinter_Lighttrain#cite_note-2

    The Wiki page of the Sprinter Light train that is currently still active in the Netherlands. This is the single type of train that the past project group had put their focus on.

31. Type 10 Scharfenberger Coupler. Retrieved from http://voith.com/en/products-services/power-transmission/scharfenberg-couplers/scharfenberg-couplers-railcars-14310.html

    Reference to couplers for railcars. It is assumed that the type 10 general coupler is used for the Sprinter Light train.

32. United States Patent, Obstacle Detection System, December 2000. Retrieved from https://docs.google.com/viewer?url=patentimages.storage.googleapis.com/pdfs/US6163755.pdf

    Reference to a patent of a US obstacle detection system. From this patent it can be concluded that the system oan give real time feedback back to the driver of the train.

33. Underground train map of Milan. Retrieved from http://italy4.me/wp-content/uploads/2015/01/karta-milan-metro.pdf

    Reference to the map of metro railway track in Milan. No relevance to our project.

34. Bridge by Meppel (Netherlands) without catenary, retrieved from https://en.wikipedia.org/wiki/Overhead_line

    Reference to a picture of a train riding on an overhead line used on the wiki of their project. No further relevance to our project.

35. Tesla Powerwall, retrieved from https://www.tesla.com/nl_NL/powerwall

    Tesla powerwall is a fully automated system which does not require any maintenance, it works best when combined with solar panels, so it can store excess energy so it can be used later.

36. Examples of frontal areas of cars, retrieved from http://ecomodder.com/wiki/index.php/Vehicle_Coefficient_of_Drag_List

    List of coefficients of drag for different types of cars. Could be useful when designing the shape of the robot.

37. Examples of drag coefficients, retrieved from http://www.brighthubengineering.com/hydraulics-civil-engineering/58434-drag-force-for-fluid-flow-past-an-immersed-object/#imgn_2

    Drag force equation. Could be useful when designing the shape of the robot.

38. Examples of rolling resistance coefficients, retrieved from https://en.wikipedia.org/wiki/Rolling_resistance

    List of different coefficients of rolling friction. Could be useful to look into when designing the wheels.

39. More examples of different rolling resistance coefficients, retrieved from http://auto.howstuffworks.com/tire4.html

    Information about rolling friction, focussing on car tires. Only interesting when thinking of tires (not for train wheels).

40. Information about the caternary, retrieved from http://energievoorziening.funnymedia.nl/bovenleiding%20nieuw/bovenleiding.htm

    Information on the caternary (bovenleiding) used in the dutch railway system. Is useful to read through.

41. Meer spanning op het spoor?, ProRail, 8 january 2014, retrieved from https://www.prorail.nl/nieuws/meer-spanning-op-het-spoor

    Article from 2014 stating that ProRail is considering to raise the voltage on the train tracks. This would result in more punctuality. Is useful to read through.

42. Jaarverslag NS 2016, retrieved from http://www.nsjaarverslag.nl/jaarverslag-2016/energie3/a1128_Energie

    Yearly report of the NS. Lists some good numbers for NS. Not directly interesting for our project.

43. Mobiliteitsbeeld 2016, Rijksoverheid, retrieved from http://www.nsjaarverslag.nl/jaarverslag-2016/energie3/a1128_Energie

    Mobiliteitsbeeld of the NS in which the NS talks about their usage of green energy for the trains. Could be useful to read through.

44. P-Laser (2017). Laser cleaning applications. Retrieved from http://www.p-laser.com/applications_detail.aspx?AGUID=1f846979-8fea-4745-bcea-663800c027e5&LGUID=8565a502-c109-43ef-b1a1-dfba5f3edbf6

    A company that makes laser cleaning machines that can remove rust or paint from a solid surface. Looks very effective in removing rust, so maybe the other group was right in using this technology?

45. Adapt Laser Systems (2017). Lasersystem CL 1000, Most Powerful hand held laser on the market. Retrieved from http://adapt-laser.com/ourproducts.php?id=21

    Same as 44, but other company.

46. Gray, R. (2015) End of the line for autumn train delays? Dutch begin trials to zap leaf litter from the tracks with LASERS. Retrieved from http://www.dailymail.co.uk/sciencetech/article-2860418/End-line-autumn-train-delays-Dutch-begin-trials-zap-leaf-litter-tracks-LASERS.html

    Very important article about the testing of lasers on dutch trains to get rid of leaves and rust, which would be more effective than brushing the rails.

47. Used ICCD camera, retrieved from http://www.stanfordcomputeroptics.com/products/iccd-framing-camera.html#features

    Very fast camera that the group wanted to use for their design.

48. Calculations storage data, retrieved from http://eckstein.rutgers.edu/mis/handouts/storage-calcs.pdf

    Calculations for memory storage. Don’t know why this should be important.

49. Height differences in the Netherlands, retrieved from http://www.geo-informatie.nl/geodesk/hgt-300dpi.pdf

    A map of the Netherlands is shown with its enormous height differences. Ranging from 5 meters below sea level in the Middle-West to around 300 meters above sea level in the south of Limburg.

50. ProRail in cijfers. Retrieved from https://www.prorail.nl/over-prorail/wat-doet-prorail/prorail-in-cijfers

    The Netherlands has the busiest railways in all of Europe, in 2015 3.3 million train journeys have been made, which results in a total covered distance of 152 million kilometers (this is approximately the distance between earth and the sun). ProRail owns 7021 kilometers of tracks and there are 404 train stations, of which some are only used in special occasions.

51. Onderzoek naar plotselinge slijtage op spoor. Retrieved from http://nieuws.nl/algemeen/20130226/onderzoek-naar-plotselinge-slijtage-op-spoor/

    Page could not be found; Nu.nl also reports an article about this: Every piece of the railway tracks get checked at least every month, however sometimes it is unclear how the tracks get affected by wear.

52. Berke, C. (2016). Laser Rust Removal: Too Good To Be true? Retrieved from http://shortshift.co/laser-rust-removal/

    Laser rust removal device can clean up rust on metals, but applying it in an autonomous robot would cost a lot of money, since such devices are very expensive high-end industrial tools.

53. Adapt Laser Systems (2017). Lasersystem CL 1000 Most Powerful hand held laser on the market. Retrieved from http://adapt-laser.com/ourproducts.php?id=21

    Page not found; Adaps Laser Systems’ website providing powerful (hand-held) lasers.

54. 400W 808nm CW High Power Laser Diode Stack for Heat Treatment, Very Powerful ! Retrieved from http://www.ebay.com/itm/400W-808nm-CW-High-Power-Laser-Diode-Stack-for-Heat-Treatment-Very-Powerful-/270918323182/

    400W Laser Diode Stack with Collimated Beam Spot, used for heat treatment on mostly metals, basically burns everything put in front of it.

55. Gampat, C. (2015). The Lifespan of a Difital Camera Is Way Too Short. Retrieved from http://www.thephoblographer.com/2015/09/11/the-lifespan-of-a-digital-camera-is-way-too-short/

    The lifespan of a digital camera have decreased from their analog counterparts, this is because of all the less-durable electronic parts, and the frequent technological advancements.

56. Highspeed camera PCE-TC 225. Retrieved from https://www.pce-instruments.com/dutch/index.htm?id=google-nl&_artnr=3650570&_p=5438.95&_pmode=0&_pbexkey=74&_date=20170310000501&_pbhash=b6e2287ec9f5de8edebe8d8b4d2a1a4eed2f956ee5b8aa4175be524fd9261b0d&gclid=CjwKEAjwzKPGBRCS55Oe46q9hCkSJAAMvVuM4Fza-mwEB0kj6YoZD2SDZ1Y4IfdoLMq0Rj4KzlL5IBoCPhTw_wcB

    Professional high speed camera, recording up to 964 fps (allows for around 40x slow down time) with a resolution of 640 x 120

57. Tesla Powerwall, retrieved from https://www.tesla.com/nl_NL/powerwall

    Tesla powerwall is a fully automated system which does not require any maintenance, it works best when combined with solar panels, so it can store excess energy so it can be used later.

58. SpoorPro: Steeds vaker tekort treinonderdelen. Retrieved from http://www.treinreiziger.nl/spoorpro-steeds-vaker-tekort-treinonderdelen/

    Because of the increase in electronics and mechatronics in trains, the different parts are less available. The lifespan of the different parts of the train vary also, the train itself will be good for 50 years, but the software is unmaintainable after only a few years.

59. W-SQ 20 Mobile. Retrieved from http://www.whisperpower.com/nl/4/5/37/producten/generatoren-1500-1800-rpm/w-sq-20-mobile.html

    W-SQ 20 Mobile Generator delivering a power of 20kW and outputting 230 @ 50 Hz (standard electricity grid in the EU).

60. What is a CPUs Lifespan? Retrieved from http://www.tomshardware.co.uk/answers/id-2567579/cpus-lifespan.html

    The usage of a CPU results in wear, the lifespan of silicon transistors in the CPU are around 20-30 years. Most CPU can last longer than a decade. It really is hard to specify the lifespan, since every unit is used differently and the chips are just different on microscopic level.

61. Shewan, D. (2017). Robots will destroy our jobs – and we’re not ready for it. Retrieved from https://www.theguardian.com/technology/2017/jan/11/robots-jobs-employees-artificial-intelligence

    Robots will take over a lot of jobs in the future, everyone is aware of that, but a lot of people think their specific job will not be affected. Engineers are needed, especially with all the advancements made nowadays.

62. Loonwijzer. Retrieved from https://www.loonwijzer.nl/home/salaris/salarischeck?job-id=5112020000000#/

    An engineer earns around 54,203 euros each year

63. van de Velde, P. (2014). Hoogste salarissen na studie techniek. Retrieved from http://www.telegraaf.nl/dft/geld/werk-inkomen/22218328/__Hoogste_salaris_na_techniek__.html

    Page is not available anymore on Telegraaf.nl.

Next to the references found during the past project by PRE2016 Group 3, the following 25 new other references are analysed. These also include a short sentence under each reference to give a small description of the article or patent.

• New article Sunny

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• New article Sunny

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• New article Sunny

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• New article Sunny

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• New article Sunny

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• Daurelio, G., Chita, G., & Cinquepalmi, M. (1999). Laser surface cleaning, de-rusting, de-painting and de-oxidizing. Applied Physics A, 69(1), S543-S546.

https://link.springer.com/content/pdf/10.1007%2Fs003390051467.pdf

This research is about how different types of lasers affect the paint, rust and oxide on materials.

• Pesticides and the environment. Retrieved from:

https://www.milieucentraal.nl/in-en-om-het-huis/ongediertebestrijding/bestrijdingsmiddelen-en-het-milieu/

This site is about how pesticides should be chosen and how they affect the environment.

• Bijna 5.000 treinen vertraagd door dieren op het spoor (2018). Retrieved from:

https://www.ad.nl/binnenland/bijna-5-000-treinen-vertraagd-door-dieren-op-het-spoor~ab1c706d/

4861 trains in 2017 had delays due to incidents with animals on the railways.

• Statics about the cause of failure: animals on the railway. Retrieved from:

https://www.rijdendetreinen.nl/statistieken/oorzaken/dier-op-het-spoor

This site gives information about train failures due to animals on the railways.

• Gomez, A., Diez, G., Salazar, A., & Diaz, A. (2016, December). Animal identification in low quality camera-trap images using very deep convolutional neural networks and confidence thresholds. In International Symposium on Visual Computing(pp. 747-756). Springer, Cham. https://link.springer.com/chapter/10.1007/978-3-319-50835-1_67

This paper is about how a system can recognize animals and classify them by using a camera and a very deep convolutional neural networks.

• New article Max

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• New article Max

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• New article Max

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• New article Max

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• New article Max

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• New article Jules

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• New article Jules

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• New article Jules

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• New article Jules

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• New article Jules

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• New article Joeri

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• New article Joeri

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• New article Joeri

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• New article Joeri

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• New article Joeri

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Approach

We will conduct a study and analysis and will come up with a design. If time allows it, we will make a shitty prototype as well.

Planning

Planning	Monday	Thursday	Remarks
Week 1	Introduction + groups	The plan	Plan finished before Monday
Week 2	Feedback session + research problem approach	Research + contact NS	Complete questions for NS
Week 3	Feedback session + research solution	Research solutions	Complete possible solutions for the system
Week 4	Feedback session + research components	Components list	Complete possible components for the system
Week 5	Feedback session + integrating	integrating	Integrate the components in one coherent system
Week 6	Feedback session + budget calculation	Extra time to complete the above	Gather feedback
Week 7	Feedback session + finalize	Finalize + presentation preparation	Finish remaining tasks
Week 8	Feedback session + finalize + presentation preparation	Finalize + presentation preparation	Make sure everything is according to the assignment

Milestones

• First group meeting with everyone
• Solutions ready
• Integrating solution
• Final report
• Final design
• Presentation
• A program that differentiates glass, plants, snow from the other trash

Deliverables

• Wiki (report)
• Final presentation
• (shitty prototype)

Who will do what

• Sunny (Computer Science): the software of the design
• Jorick (Electrical Engineering): the electronic components of the design.
• Max (Industrial Design): the look and feel of the design.
• Jules (Mechanical Engineering): the 3D model of the design and the general functioning of the design.
• Joeri (Mechanical Engineering): the 3D model of the design and the general functioning of the design.
• Everyone:comment/help on other peoples work

Brainstorm (extra)

Move to logbook