Year | 2015 |
Credits | Dr Jaime Valls MiroPrincipal Research Darren LeeOmegalib Programming Ben SimonsData Visualisation Production, Houdini |
3D Stereo | Yes |
Tags | FEIT data viz lidar point-cloud water pipes |
This project is a collaborative effort between UTS, Monash and the University of Newcastle.
Some of Sydney’s water pipes are over 100 years old, they’re cast iron and they’re corroding – because that’s usually what happens when you put iron under ground!
The data-set contains 36 million individual points. It was collected using a laser scanner developed specifically for this project, by the Centre for Autonomous Systems (CAS). The laser scanner is attached to an autonomous robot which can travel inside the pipe, when the pipe is emptied of water. This produces the inner surface scan.
There is also an electro-magnetic sensor attached. It can estimate the thickness of the pipe wall, while the pipe is still in the ground. This estimate provides the outer surface.
Both the laser data and the electro-magnetic data are actually fed into complex surface analysis software which runs on GPU's tasked to estimate the surfaces you see in this visualisation. It is this software which also colours the surface. So, the data being visualised is also partly indicating an estimation performance in an on-going software development project. This particular pipe is in the labs here at UTS and is being used to calibrate the scanners.
The Data Arena is able to handle such large data sets with ease – users are able to view and interactively navigate the point cloud in real time.
Civil Engineers use this visualisation to examine the thickness of the pipe network at different areas. The segment shown in the image above is a portion of pipe that developed a serious leak, due to gradual corrosion and the pressure of the water inside.
This project deals with the water pipes that carry drinking water for Sydney’s residents. The researchers sought to analyse the data that is currently being used to monitor and inspect these pipes using various techniques in order to be able to more reliably identify damaged segments of water pipe before they break and start to leak.
The water pipes examined in this project were actually taken out of the ground and then inspected with very high definition 3D lasers that generate point cloud data sets containing millions of individual samples. Dealing with such a large data set can be very challenging, so the idea behind this visualisation was to manipulate and represent the data in a manner that allowed technicians to easily find the crevices and holes that they were looking for.
The colours provide a visual indication of the thickness of the water pipe in each location. Red indicates that the wall of the pipe is thinning due to rust and corrosion, the yellow highlights regions which are still relatively thick. Thin sections of piping are more likely to develop cracks or holes – eventually the water pipe will not be able to withstand the pressure of the water inside and it will fracture and break.
Although this project addresses water pipes in Sydney Australia, much of the world uses similar concrete-coated iron pipes to deliver water.