Wireless monitoring boosts train maintenance efficiency
12 June 2017
SKF developed a wireless condition monitoring system to enable condition based maintenance practices (CBM) that will help rail operators spend their maintenance budgets more effectively.
SKF Insight gives key information on the state of critical wheel-set components. It relies on retrofitting a small advanced, wireless sensor to the wheelset axlebox assembly – which takes just a few minutes for a complete wheel-set– to detect bearing damage and wheel flats quickly and accurately. By raising wheel-set maintenance efficiency practices, it helps to keep rolling stock in good working order.
“Trains need to be out on the track, rather than spending time in maintenance depots being serviced,” says Mark Rhodes, Development Consultant at SKF.
Despite being in a noisy environment, the wireless sensor picks up inconsistencies in the vibration of a bearing as it begins to fail. Sophisticated vibration signal processing and algorithms separate the signal from the noise, ensuring that the sensor produces and sends accurate data for further remote diagnostic analysis if needed.
Earlier versions of this technology sent the information from the sensors to a processor installed on the rail vehicle, via cables. However, SKF Insight uses wireless data transmission – sending data directly from the sensor to the cloud and further on to the remote diagnostics centre, using mobile networks.
“There’s now no need to fit a cumbersome on-board gateway router – and all the cables have been removed,” adds Nils Ekholm, Technical Leader at SKF.
A key part of the system is its ability to provide clear recommendations from complex data. Once the data from a sensor has been processed and a damage has been detected, SKF produce a report. If a maintenance operation is recommended the operator receives a notification and the component/bearing exchange can be planned and performed at a suitable time.
Besides vibration, the wireless sensor system also analyses information on temperature – as well as speed GPS positional data. All generated data is stored securely in the SKF cloud.
The system has already gone through successful field trials in different countries. In 2015, it was fitted to a railway vehicle owned by the Swedish national railway operator, SJ, where it accurately detected three damaged bearings. It is currently being verified and validated on more trains in the field. The full SKF Insight Rail system is due to be launched in 2017.
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