Reconfigurable miniature sensor nodes for condition monitoring

The wireless sensor networks are being deployed at escalating rate for various application fields. The ever growing number of application areas requires a diverse set of algorithms with disparate processing needs. The wireless sensor networks also need to adapt to the prevailing energy conditions and processing requirements. The preceding reasons rule out the use of a single fixed design. Instead a general purpose design that can rapidly adapt to different conditions and requirements is desired. In lieu of the traditional inflexible wireless sensor node consisting of a micro-controller, radio transceiver, sensor array and energy storage, we propose a rapidly reconfigurable miniature sensor node, implemented with a transport triggered architecture processor on a low-power Flash FPGA. Also power consumption and silicon area usage comparison between 16-bit fixed and floating point and 32-bit floating point implementations is presented in this paper. The implemented processors and algorithms are intended for rolling bearing condition monitoring, but can be fully extended for other applications as well.

[1]  David E. Culler,et al.  The mote revolution: low power wireless sensor network devices , 2004 .

[2]  Joseph A. Paradiso,et al.  Energy scavenging for mobile and wireless electronics , 2005, IEEE Pervasive Computing.

[3]  Mo-Yuen Chow,et al.  Neural-network-based motor rolling bearing fault diagnosis , 2000, IEEE Trans. Ind. Electron..

[4]  Jarmo Takala,et al.  Codesign toolset for application-specific instruction-set processors , 2007, Electronic Imaging.

[5]  David E. Culler,et al.  Perpetual environmentally powered sensor networks , 2005, IPSN 2005. Fourth International Symposium on Information Processing in Sensor Networks, 2005..

[6]  Pai H. Chou,et al.  Everlast: Long-life, Supercapacitor-operated Wireless Sensor Node , 2006, ISLPED'06 Proceedings of the 2006 International Symposium on Low Power Electronics and Design.

[7]  Janne Janhunen Programmable MIMO detectors , 2011 .

[8]  Ming Liang,et al.  Parameter-free bearing fault detection based on maximum likelihood estimation and differentiation , 2009 .

[9]  Guang Meng,et al.  Bearing Fault Detection Using Higher-Order Statistics Based ARMA Model , 2007 .

[10]  Purushottam Kulkarni,et al.  Energy Harvesting Sensor Nodes: Survey and Implications , 2011, IEEE Communications Surveys & Tutorials.

[11]  Philip Levis,et al.  Surviving sensor network software faults , 2009, SOSP '09.

[12]  Mani B. Srivastava,et al.  Power management in energy harvesting sensor networks , 2007, TECS.