WiBRATE - Wireless, self-powered vibration monitoring and control for complex industrial systems



: 01-11-2011


: 31-10-2015


PARTNERS Systems Group - University of Twente

Applied Mechanics – University of Twente

LMS International NV

Inertia Technology B.V.

Honeywell Technology Solutions Lab Pvt. Ltd

Centro Ricerche FIAT S.C.p.A.

Università della Svizzera italiana – AlaRI

Perpetuum Ltd.





ir. Andrea Sanchez

ir. Pouria Zand

ir. Das Kallol Arthur Berkhof Tiedo Tinga Richard Loendersloot Paul Havinga



WiBRATE explores new paradigms for developing innovative strategies for wirelessly monitoring and controlling vibration using a network of intelligent embedded devices that power themselves using harvested vibration energy [1,2]. The possibilities that that Wireless Sensor Networks (WSNs) offer to vibration monitoring and control are explored on challenging cases such as:


Helicopter Rotor Blade (LMS) [3]


Car Assembly Line (Fiat)


Gas Turbine (Honeywell)


Train Bearings (Perpetumm)

C:\Users\SanchezA\AppData\Local\Microsoft\Windows\Temporary Internet Files\Content.Word\helicopterblade.jpg

The introduction on WSNs for condition monitoring promises significant advancements compared to traditional technologies. These possibilities are highlighted by the different case studies. For instance, the autonomy to place sensors on traditionally inaccessible locations is exploited for rotating blades as in the helicopter main rotor. Another feature of WiBRATE refers to the distributed sensing capabilities and synchronization aspects, relevant aspects for capturing the dynamic characteristics of the structures as in getting the vibration snapshot.

The necessary synergies for high frequency sampling and communication speeds have been investigated at the case of gas turbines, for which real time feedback is necessary on compressor vibration control. The most advanced implementation of wireless vibration surveillance has been achieved for train bearings, which have been proven a reliable tool not only for maintenance reasons, but for railroad diagnostics. The adaptability of wireless sensor network to complex environments is tested for an actual car assembly line where all electromagnetic noise present challenges for the wireless communication [4].





P. Zand, S. Chatterjea, K. Das, P.J.M Havinga. Wireless Industrial Monitoring and Control Networks: The Journey So Far and the Road Ahead, Journal of Sensor and Actuator Networks, 2012


K. Das, P.J.M. Havinga. Evaluation of DECT-ULE for robust communication in dense wireless sensor networks. In: Proceedings of the International Conference on the Internet of Things (IOT 2012), pp. 193-190. IEEE Communications Society. Wuxi, China. 2012


A. Sanchez Ramirez., K. Das., R. Loendersloot., T. Tinga., P. Havinga., Wireless Sensor Network for Helicopter Rotor Blade Vibration Monitoring: Requirements Definition and Technological Aspects. Proceedings of 10TH International Conference on Damage Assessment of Structures (DAMAS 2013). Submitted.


K. Das, P.J.M. Havinga. Evaluation of DECT-ULE for Robust communication in Dense Wireless Sensor Networks. In proceedings of the 3rd International Conference on the Internet of Things (IoT2012). October 2012 .