Rail Deflection Tests Using Photogrammetric Methods
Longstanding clients Coleman Rail and parent company, Acciona, approached our team with a track deflection challenge that required very accurate measurement of the rail displacement as a locomotive was driven through a project site.
The project site encompassed more than 100km of regional track and more than 200 deflection sites were nominated by the client in concert with a parallel geotechnical investigation. Agonics worked closely with partner, Gancel, and the Geodetic Systems International (GSI) industrial photogrammetric technology to design a rail deflection process that would capture deflections at both sleeper and mid-crib locations.
Data processing by Agonics has allowed Coleman Rail and its track consultants to calculate the track modulus at each site; this information will be used to assess the extent of work required and associated costs to lift sections of the Victorian rural rail network to a higher track class.
Two pilots studies of the Agonics deflection solution were completed at Williamstown and Wyndham Vale stabling yard utilising a range of track vehicles and under day/night conditions before embarking on the mainline scope. Once mobilised, the team negotiated a wide range of site conditions while navigating the frequent changes to COVID19 working restrictions during Victoria’s current outbreak.
Metro Trains Melbourne (MTM) Embarks on Whole of Network MLS Project
In preparation for the commissioning of a new track inspection vehicle and to realise an update to the Melbourne rail network asset inventory, MTM has partnered with Agonics to perform a whole of network MLS survey. The survey commenced in September 2020 during Melbourne’s strict midyear lockdown with the project teams implementing comprehensive COVID safe protocols. Since then we have completed recording across 880 km of complex inner city and suburban rail network and have processed what are arguably the most accurate LiDAR and imagery datasets ever recorded on the network.
Similar to our other rail network clients, the LiDAR and imagery datasets are being made available to MTM through the easy-to-use AIMS3D Viewer supporting internal projects and day to day maintenance and operations. The datasets being delivered will also play a critical role in the commissioning of a new track recording vehicle that is currently undergoing testing in Melbourne.
The new vehicle will avail of digital track centrelines produced by the MLS project so that geometry and other infrastructure defects can be accurately and repeatedly referenced in MTM’s maintenance systems. To ensure compatibility between data and systems and, most importantly measurement reporting repeatability, the track centrelines delivered by Agonics have been translated by us into the ENSCO track database that feeds localisation content to the various systems and reports generated by the IEV120. Establishing this new, authoritative track centreline database inclusive of speed limits, crossovers and turnout topology to an absolute accuracy of 100mm has ensured the smooth commissioning of the new vehicle.
Agonics Insight – Getting Actionable Information from LiDAR Data
There is little doubt that LiDAR is playing an increasingly important role in day-to-day rail maintenance and planning. In Australia we see a strong desire amongst our rail clients to leverage LiDAR more in their business, but LiDAR datasets alone are only part of the story. We asked Agonics Technical Director, David Presley, what networks should look for in terms of integrating LiDAR into their routine maintenance practices.
“I would say that from decades working with rail clients the same basic principles apply to solving any engineering challenge. The first of these is to understand what your actual requirements are before commissioning any LiDAR survey or buying hardware to do it yourself. A common pitfall is to focus on the hardware at the expense of downstream thinking as LiDAR scanners are relatively easy to understand and compare. However, the ancillary technology such as inertial measurement devices and trajectory understanding, which are needed to inform the raw LiDAR data and allow correlation back to the track reference systems, are often not on people’s radar. We’ve seen so many examples of datasets being collected without first really understanding why or without mapping out a workflow that will take this data and solve a business problem with it.”
“The second principle I think is to not underestimate the change management needed in your organisation to leverage LiDAR successfully in day-to-day maintenance. We are beginning to see some real maturity in this space now in the industry, which is great to see.”
We’ve been very busy of late helping our rail customers manage engineering compliance for their infrastructure assets. Occasionally we get to witness some of the amazing work of our forebears. Here are a few photos of some beautiful engineering structures in Victoria. If you need assistance with meeting PASS Assets requirements please contact our expert team.
Australia’s Longest Digital Twin
We recently completed data collection for Australia’s longest digital twin – 9,000 km of the interstate freight network on behalf of ARTC. This has been a mammoth task requiring close collaboration among the project stakeholders. The datasets collected will go to meet the immediate and evolving requirements of ARTC projects and support the development of an ARTC GIS Model, Linear Referencing System as well as the deployment of Ellipse Mobility eWorks. To read more on the project please read this article Infrastructure Magazine: ARTC creates digital twin of entire network | Infrastructure Magazine
Artificial Intelligence (AI) and Machine Learning
We often get asked if we utilise AI and/or Machine Learning when we analyse LiDAR and imagery. The short answer is, yes, we do, but we advise our clients to always exercise their engineering judgement in deciding what level of automation is suitable in their particular circumstances. The rail environment is complex and so, if you are interested in learning more about how we analyse imagery and LiDAR then please get in touch with us at firstname.lastname@example.org