Measure the Rails
The key requirement for systematic and target-oriented rail maintenance is a covering knowledge about the current state of the rail- or tramway network's geometry (see Fig.2). This is achieved by a smart measuring strategy that combines odometer results (distance measuring), track geometry, longitudinal profiles and cross sections with exact GPS locations.
All these parameters are acquired by mobile metering devices or complete measuring vehicles. Initiated and pre-processed by Analog Devices Blackfin processors, the measurement data is finally transferred into a high-level analysis software that allows post-analyzing and pinpointing the measurements and defects on a digital map (Fig. 3).
Fig. 3: Measurements are combined with GPS data to pinpoint them in Geographic Information Systems (GIS).
The rail gauge is measured using no contact inductive sensor principles with accuracies in the 0.01 mm range. Software based FIR low-pass filters suppress high-frequency noise while subsequent moving average filters ensure that no "pseudo-peaks" are occurring in a result that is expected to be continuous.
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Measuring the track-to-track distance requires a set of complex and computational demanding floating-point algorithms to finally deliver the relatively simple result of the absolute horizontal and vertical distance (Fig. 4).
Fig. 4: Measuring the track to track distance (X/Y) demands for high-performance digital signal processing algorithms at runtime.
A high-precision laser beam which is attached to the side of a vehicle, wobbles ±5° within a distance range of 1 to 5 m under the control of a Blackfin processor. The profile of the neighboring rail which is expected within this scanning sector, is low-pass and median filtered and transformed from the polar into the cartesian coordinate-system. After applying some processing like vector-rotation and resampling, the profile passes through a pattern matching algorithm.
The goal is to find the exact vector to a characteristic geometric feature within the realhead. Due to the many obstacles like rocks or grass that are found on railways, this vector finally passes through a plausibility checker and a tracking algorithm to provide reliable and valid results. All this is done in a 5-Hz loop under real-time conditions.
High-speed eddy current sensors record both rail surfaces with micrometer accuracy (Fig. 5).
Fig. 5: Longitudinal rail profiles are acquired by no-contact eddy current sensors, pulsed by magnetic encoders.
A linear encoder processes signals from a magnetic ring that serves as an odometer and as a trigger for the AD sensor converters. This signal then goes through a FIR (Finite-Impulse-Response) filter with a bandpass topology reducing the spectrum to the characteristic wavelengths. On top of the surface profile, also metallurgical irregularities such as partial hardenings and welding points are recorded.
Laser technology is todays state of the art non-contact measuring principle to get the exact cross section of a railhead. Depending on the required accuracy or capturing speed, either traversing laser beams or laser "curtains" (Fig. 6.) are used to do the job. Raw profiles are linearized, scaled and spike filtered in real-time.
Fig. 6: Rail cross profiles are captured by high-speed laser scanners.
Older Technology - Metering Devices
Until some years ago the maintenance staff used many different metering devices identifying cracks and variances on the rails. Each methodology specialized in recording one specific rail defect and almost all these mechanical methods lacked precise and reproducible results.
In recent years industrial solutions providers like Schmid Engineering have taken advantage of embedding advanced processor technology and state of the art methodology into design. Advancing these methods into the railway infrastructure business gradually empowered mobile and multifunctional rail measuring by smart metering devices.
Rail monitor devices (Fig. 7) uses state of the art measurement technology to simultaneously define the cross profile of the rail, the head height, track gauge, inclination, depth and ambient temperature, detected and logged at any specific location.
Fig. 7: Rugged environments and tight schedules demands for light, easy to use and productive metering devices.
All key characteristics are processed and visualized on-site and stored to removable memory. The Railsurf sled (Fig. 8) continuously monitors and records longitudinal track parameters as an operator or a vehicle pulls it along the rails.
Fig. 8: The RailSurf sled, driven by Blackfin processors and LabVIEW Embedded, records longitudinal wavy irregulatities. A GPS receiver and inclination sensor is built into the operator panel.
It carries several sensors, mapping problems as corrugations, holes, cracks, variations in rail gauge and inclination. The resulting information can go onto removable memory or wirelessly transmitted to any operator interface.
Blackfin Processor as the "Heart" in the system
The Blackfin Processor as the "heart" of all these test tools empowers the convergence of MCU and DSP technology through offering dynamic power management for any given battery operation. The MCU part conveniently interfaces with scalable I/O like laser scanners, analog and digital sensors, keyboards, TFTs, batteries/fuelgauge and removable media. The DSP part is dedicated to advanced digital algorithms like filtering, FFTs or determination of the geometric residuals or other demanding computational tasks.
Recent advancements in graphical system design by LabVIEW Embedded offers a direct programming model of any Blackfin processors with its high level block diagram and dataflow-oriented language. This high-level approach with ready-to-use mathematical analysis blocks and graphical multitasking moves functionality to the next level of digital embedded design.
A multifunctional vehicle that is driven by a set of five interlinked Blackfin processors is able to record rail parameters up to 10 km of a railway section with 5-mm point-to-point resolution.
Blackfin #1 allows user interaction over a keyboard and two TFT monitors. Blackfin #2 records track geometry and longitudinal profiles at high speed and embeds GPS information into the measurements which is received by Blackfin #3. Together with cross-sections that are captured by Blackfin #4, all the data is finally streamed to Blackfin #5, which stores the huge amount of data in RAM buffers to be eventually saved to binary files on removable media.