SAFERAIL – improving inspection to keep rolling stock on track
Posted: 6 December 2011 | | No comments yet
Today’s European rail networks are getting busier with trains travelling at higher speeds, and carrying more passengers and heavier axle loads, than ever before. This combination of factors is putting considerable pressure on the existing infrastructure, leading to increased demands in inspection and maintenance of rail assets.
To maximise safety efficiency in rail travel the rail industry has applied a pro-active maintenance policy for wheelsets. This policy combines on-line monitoring and manual inspections during production and maintenance. Minimising wheel set failures not only improves safety but also helps reduce maintenance costs, and is a consideration for both train and light-rail vehicle operators.
A European collaborative research project called SAFERAIL, jointly led by TWI and the University of Birmingham, has spent the last three years developing new inspection technology. This technology is intended to extend on the current state-of-the-art for both trackside monitoring and manual inspection of rolling stock wheelsets in a bid to minimise wheelset failures and improve safety and reduce maintenance costs.
SAFERAIL was partially funded by a grant from the European Commission under the Seventh Framework Programme. Eleven European organisations comprising SMEs, research institutes and end users have worked together to develop and test the technology. The research and development stage of the SAFERAIL project is now complete. The partners have produced proof of concepts and are now in the process of commercialising the solutions, with some partners having technology that can already be offered.
SAFERAIL seeks to minimise wheelset failures through research and development of new techniques for both trackside monitoring systems and manual inspection systems.
Currently, there are several methods already in use for wheelset monitoring of moving rolling stock, including standard, strain-based, and accelerometer-based wheel impact, mechanical profile monitors, hot box, sliding wheel, acoustic bearing defect, wheel profile and cracked wheel detectors, and Automated Optical Inspection (AOI) systems.
The existing wayside detection monitors can check rolling stock for poorly performing axle bearings, inefficiencies in the braking system, skidded or spalled wheels, and transient lateral motion (otherwise known as ‘hunting’). However, the output of existing on-line detectors is not fully reliable, and can lead to misinterpretation of the acquired data.
The main purpose of existing on-line systems is to detect severe wheelset defects just before they result in a catastrophic failure. The most classic example of this is the hot box detector, which can detect heat emitted by the bearing and report its imminent failure by triggering an alarm in time for the train to stop. However, wheelset bearings can heat up and seize extremely rapidly and cause derailment before the train passes over the hot box detector. Another example is wheel impact monitors. These measure the impact loads from wheels of passing rolling stock on rails, and can detect defective train wheels that are out-ofround due to flat spots. However, they cannot provide any information regarding tight surface breaking cracking or internal defects that may be present in the wheel. As a direct consequence, any severe surface-breaking or deep internal defect will be missed by such systems, and will remain undetected until the defective wheelset is taken out of service for inspection and maintenance. Nonetheless, failing to detect severe defects in time, between maintenance intervals, may subsequently lead to severe structural degradation of the wheel resulting in derailment.
SAFERAIL aims to improve existing wayside monitoring capability by developing online systems based on vibration analysis, acoustic emission and thermography techniques. The prototypes are to be modular, and capable of being combined to give a greater assurance on defect detection. Trackside monitoring system solutions based on infrared thermography, vibration and acoustic sensing techniques are already in the market, but these techniques can be largely improved upon with better data acquisition systems, innovative data analysis algorithms and information extraction methods.
Even with trackside monitoring, manual inspection of wheelsets is still a necessity. Manual inspection normally takes place during production and maintenance. Typically, the industry uses classical Non-Destructive Evaluation (NDE) tools such as standard ultra – sonic testing (UT), Magnetic Particle Inspection (MPI) and Eddy Current probes. Inspection of wheelsets with such NDE tools is prone to human error (sometimes severe defects can be missed). The fact that these techniques have been in use by the rail industry for the past 50 years means that they are not only regarded as traditional solutions to the inspection problem, but also as undoubted standards. However, these techniques are timeconsuming and, in the case of Magnetic Particle Inspection (MPI), messy and require the full disassembly of wheelsets.
Development of improved manual nondestructive evaluation techniques for inspection of wheelsets during production and maintenance is another of SAFERAIL’s prime objectives.
A key area of development in the project is the trackside inspection of passing rolling stock – be that freight or passenger trains or trams. Put simply, acoustic emission sensors and highfrequency vibrations detectors are attached to the rail and an associated data signal signature is acquired each time a rail wagon passes.
Two prototype trackside monitoring systems, using High-Frequency Vibration Analysis (HFVA), were installed by APT and are up and running at De Lijn sites in Belgium. One system is at De Lijn’s HQ in Antwerp and the other is at a site in Lombardsijde. The inspection points were located close to the workshop which houses the trams when service is completed for the day. In this way all trams are monitored every day. Data results including a digital camera image of the vehicle are sent over the Ethernet to a server at APT. The data is sent after the measurement has been processed by the HFVA module. The results can be examined anywhere in the world via a password-protected internet browser. In addition, alerts can be automatically sent by email and text messaging on mobile phones.
The system has successfully detected wheel flats and out-of-roundness. In addition, it has also detected suspension faults and rail brake misalignments. De Lijn actually operates trams rather than trains, but the inspection techniques used apply to trains too, and this has been tested with VTG’s freight wagons at its Long Marston site in the UK.
Another trackside monitoring system developed by partners Feldman, Envirocoustics, and the University of Birmingham is installed at EMEF’s site in Lisbon, Portugal. This system is based on acoustic emission sensing. For vehicle wheelset condition follow up, and damage pattern recognition, each train and vehicle is identified with RFID technology. A beacon exchanges data with passing trains, and searches in a database of fitted bogies and wheelset type. Alerts from the network sensors grid can be programmed to warn of a major problem that can occur in the bogies/wheelsets. EMEF also record all the results from their regular workshop inspections of each wagon. This data is stored in a database and the knowledge of bogie and wheelset maintenance helps to give a clearer picture of the different types of defects that can be expected to occur in-service.
On 3 May 2011, the SAFERAIL consortium invited selected guests from the rail industry to see at first hand the recent developments of the consortium. This was followed by a site visit to Belém train station on REFER’s Cascais Line, Lisbon, Portugal. A live demonstration was given of the acoustic emission based trackside inspection system. Included guests were António Mendonça, the Portuguese former Minister for Public Works, Transport and Communications and Transport Secretary Correia da Fonseca. The installed system collects acoustic emission data for each passing train. The first phase is to correlate this data with rolling stock maintenance manual inspections already taking place at EMEF. The second phase is to train the pattern recognition algorithms and then programme alerts for any anticipated faults/defects occurring in the rolling stock bogies and wheelsets. The algorithms will also take into account the maintenance data recorded for a particular bogie.
The SAFERAIL Portugal demonstration was carried out thanks to the technical work conducted by consortium partners Feldman and EMEF Innovation and Birmingham University. Contributions were also made by Portuguese rail infrastructure manager REFER and REFER Telecom who supported the infrastructure access and data link. BRISA provided the radio frequency technology which the trackside system used to identify the passing rolling stock.
Independently, ISQ has been investigating thermography technology and have been developing a trackside inspection prototype based on infrared thermography sensors. The system detects hot spots of passing rolling stock (wheels and axle boxes) using an array of thermopile sensors. REFER made available a section of public track where it was already using a commercially available hot box detector from another provider so that ISQ could perform comparative studies. At passing train speeds of 53km/h, the temperature data acquisition was comparable to the commercially available hot box detector but implemented with lower cost sensors and in hardware one tenth of the price. The results showed to be promising and the system useful for a preliminary assessment of temperature condition of wheels and axles.
SAFERAIL has developed new inspection techniques based on Alternative Current Field Measurement (ACFM) and Phased Array Ultrasonic Testing (PAUT). Despite the fact that ultrasonic phased arrays are faster and much more reliable, than traditionally used NDE equipment, they can still miss surface-breaking defects, which means traditionally that wheelsets also need to be inspected using either eddy current probes or, more commonly, MPI.
Ultrasonic phased arrays have the capability of emitting ultrasonic shear waves under different angles by steering the ultrasound beam. TWI and ISQ have jointly been investigating this feature and, through modelling and trials at VTG, SNCF and EMEF, have developed new inspection procedures for the inspection of axles and wheels. Crucially, ISQ and TWI were able to perform inspections of axles using PAUT from the axle end face. This avoids having to disassemble the axle from the wheel set and saves a lot of down time.
Ultrasonic inspection does have a dead zone and, crucially, a crack present in the first few millimetres of surface cannot normally be detected. Using ACFM to inspect as well ensures a greater defect detection capability.
ACFM is an electromagnetic inspection technique, used to detect and size surface breaking cracks in metals. It is typically used to replace MPI, as ACFM can work through paint and dirt, and measures the depth of the defect. It works by inducing a current in the surface of the piece to be inspected. Any defects in the component will change the direction of these sub-surface currents; these changes are detected by small sensors, and are used to compute the length and depth of the defect.
ACFM offers the possibility of allowing quicker inspection than that delivered by MPI, and PAUT will allow more extensive information to be gathered faster than with conventional ultrasonic inspection.
As the inventors of ACFM, TSC is leading the development and commercialisation of the ACFM inspection system. The University of Birmingham have also been investigating ACFM through modelling and experiments in the project in order to better understand the ACFM signals, especially those relating to multiple rolling contact fatigue wheel surface defects. TSC is working to improve the speed of data collection and analysis, plus the development of algorithms to improve the accuracy of depth sizing typical defects. TSC have developed new novel ACFM probes for both axle and wheel profile inspection. TSC used a variety of numerical models and verification methods to ensure the probes’ electromagnetic field suited the complex geometries of the wheelsets. In addition the wheel probe includes sensors mounted on sprung loaded pistons to accommodate different wheel profiles. One of the advantages of ACFM is that it ignores surface scratches, and only detects defects which have some depth.
Overview videos of the technologies used in SAFERAIL have been developed and will be available soon for public access at the project website.
New trackside monitoring and manual inspection prototype systems have been manufactured and trialled in a real environment.
Although the trackside inspection systems have been proven to detect wheelset defects, they are unable to accurately size them. Therefore, no matter how good the defect detection of the systems, regular manual inspection during maintenance periods is still necessary. However, with the improved trackside inspection capability and confidence it is possible that the frequency of manual inspection scheduled at the workshop can be reduced. With further trials and validation it is hoped that data collected from the manual inspection can be correlated with the trackside information.
The processing algorithms developed determine if there is a suspected fault for a given wheelset. This will give early indication of any problems; in other words, to allow a precursor check for any new-forming defects such as a lack of ovality, skid flats, spalls and cracks.
All of the wayside detection systems have the possibility to connect to a railway’s computer network (Knowledge and Information System) to provide the information they require on wheelset performance.
The trackside inspection systems can be placed at pre-chosen strategic points on the rail network and will monitor faults in the wheels and axles of passing trains. It can look at a range of defects including flats in the wheels, defective wheelset bearings, significant cracks and wheel profile abnormalities. Using a special identification system, each wheelset is given a unique code. If a fault is identified on a wheelset, the system will automatically alert the signalling engineers who will then decide what action to take for that particular train, i.e. advise maintenance, reduce speed or stop it completely.
The successful implementation of the SAFERAIL deliverables offers the rail industry several technical advantages, which will increase the reliability of rolling stock operations and help towards the optimisation of operation cost efficiency.
The consortium hopes that the technology can be taken down the path of full commercialisation. Some partners in SAFERAIL are more advanced than others in this respect and have enhanced their prototypes to a high degree of technology readiness. The partners also believe they can realise commercial solutions that will be far cheaper than those currently in the market.
About the Authors
Dr. Ian Nicholson is Project Coordinator for the SAFERAIL project. He joined TWI Ltd in 2005 and his current role is Technical Consultant. He has over 17 years experience in microelectronics, sensor, software development and systems integration. His current research topics deal with the automation of non-destructive testing methods for application in different industries. He is also Project Coordinator for a number of industrial collaborative projects funded directly by industry and the European Commission.
Dr. Mayorkinos Papaelias is a Research fellow at the Rail Research and Education Centre at the University of Birmingham. His research interests are development of novel NDT techniques, relationship of microstructure and mechanical properties of metals, and metallurgy of rails. He is currently involved as Project Coordinator in several industrial collaborative research projects related to the wind power and railway sectors which are financially supported by the European Commission. He is Scientific Coordinator for the SAFERAIL project.