Environment ( FOEN ), freight wagon leasing company Wascosa and Savvy Telematic Systems conducted a research project to analyse ‘ flat spot detection ’ and developed a solution for rail freight transport . Flat spots on freight wagon wheel sets are problematic . Not only do they lead to increased noise emissions , they also cause the wheel sets to wear out more quickly . In many cases , the flat spots are detected only after many kilometres on the rails , resulting in increased defects and costs . Wascosa and Savvy came up with a development that makes it possible to identify flat spots via acoustic irregularities and eliminate the flat spots efficiently . Savvy ’ s newly developed flat spot algorithm evaluates the vibrations in the time and frequency range on the telematic system . The measured data is processed directly on the telematic system to calculate different indicators and is compared to historical data . If there is a flat spot on the wagon , this will influence the indicators and trigger an alarm signal . In 2000 , some 265,000 people were exposed to damaging or annoying railway noise . To protect them , a comprehensive noise protection plan in accordance with the Swiss Federal Railroad Noise Control Act ( 14 March 2000 ) was implemented by 2015 . Measures include work on Swiss rolling stock , noise barriers , and sound-proof windows . This makes it possible to protect between 160,000 and 170,000 people from noise while meeting the deadlines in most cases and undercutting the original budget by a considerable margin . The objective of the research project was to develop a reliable early detection system using telematic devices without the need to install an external sensor system and transmitting information to the IT system environment via API interfaces . When the project was launched , Wascosa AG had already equipped several hundred intermodal wagons with telematic systems developed by Savvy . This fleet of intelligent freight wagons constituted a solid foundation for the one-year project ’ s proof of concept . With average working cycles exceeding 100,000km - even

200,000km are not rare - intermodal wagons are some of the most intensely used freight wagons in the business . Correspondingly , flat spots will affect noise emissions . However , noise perception , especially as it pertains to trains , not only depends on the volume but also on the characteristics of a sound emission . While the sound of a passing freight train can be heard from quite a distance , it is not necessarily annoying ; a flat spot on the other hand generates a distinct , unnatural periodic thumping sound . During operations there are a lot of factors that have an effect on the wheel ( imbalance , uneven running surfaces and infrastructure , etc .) and the wagon ( natural vibrations , load influences , etc .). This leads to a wide range of different overlapping frequencies which are perceived as a ‘ whooshing ’ sound . Not every recurring vibration is a flat spot and , vice versa , not every disturbance on the running surface corresponds to a flat spot . It is therefore important to find significant correlations between the measured data of the affected wagons and the dimensions of the flat spots on the wagon wheels . For the whole duration of the research and development project , the Savvy CargoTrac-Ex telematic devices recorded innumerable parameters , such as accelerations in three axes ( x , y , and z ), the velocity or position of the Wascosa wagons . At Savvy , big data analyses were conducted with the large amount of data collected from the Wascosa wagons to recognize flat spot patterns and develop reliable algorithms for flat spot detection . The aim of the flat spot algorithm developed is to analyse , evaluate and transform the vibration parameters in the time and frequency range so that it generates significant and reliable indicators of the wagon ’ s dynamic vibration behaviour . The measured data is processed directly on the telematic system . The resulting indicators are recorded locally on the telematic system and compared with historical parameters . If there is a flat spot on the wagon , then an alarm is set off . The final algorithm was successfully integrated into the telematic firmware and rolled out on the Wascosa wagon fleet during the project . Initial applications for other SAVVY customers have confirmed the algorithm ’ s effectiveness : new flat spots were

also reliably detected in that context . Christoph Becker , project manager at Wascosa said : “ The results have exceeded expectations by far . Thanks to the new data , we can effectively recognise critical situations , remedy them efficiently , and have an additional tool to manage vehicle maintenance and continue to optimise our predictive maintenance process .” From the onset , the research project was aimed at developing a solution for operators that was economical and suited for everyday use . Each development stage was reviewed in this respect and the results were optimised accordingly . Thanks to the Savvy team ’ s experience and the large amount of data from Wascosa ’ s highperformance intermodal fleet , a procedure was created that hardly affects the telematic system ’ s power consumption , thereby protecting existing investments . In addition to noise reduction and added safety , positive economic effects are also expected thanks to the early remedy of defects . The key to this reliability lies in the Savvy team ’ s 20 years of experience in developing high-precision , robust telematic devices and intelligent software algorithms . The algorithms make the telematic device intelligent in such a way that notifications are only sent if needed . Transmission in 10 minute intervals , eg , is not required . In addition , the device ’ s battery-saving software intelligence ensures an autonomous lifecycle of up to 15 years . Savvy CEO Aida Kaeser added : “ We are extremely pleased to have successfully brought this project with Wascosa to its roll-out phase . Our collaboration has demonstrated that Wascosa is an innovative partner . We would be happy to conduct other R & D projects with Wascosa , projects that will continue to make rail freight shipments more innovative and efficient .”

www . savvy-telematics . com

Thanks to the Savvy team ’ s experience and the large amount of data from Wascosa ’ s fleet , a procedure was created that hardly affects the telematic system ’ s power consumption , thereby protecting existing investments

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