Novel Sensing Networks for Intelligent Monitoring (Newton) Z Q Lang, H Chen, T Dodd Department of Automatic Control & Systems Engineering University of.

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Presentation transcript:

Novel Sensing Networks for Intelligent Monitoring (Newton) Z Q Lang, H Chen, T Dodd Department of Automatic Control & Systems Engineering University of Sheffield 9 July 2013

Outline Time domain modelling and frequency domain analysis – Core signal processing technique of the autonomous monitoring system to be developed by Newton Project Application to processing data from the new PEC sensing module developed at Newcastle An idea to apply the approach to the signal analysis in the novel RFID based PEC sensing technology being developed at Newcastle Conclusions

Autonomous monitoring system to be developed by the Newton Project Time Domain Modelling and Frequency Domain Analysis

Why modelling systems, and why analysing system models in the frequency domain? Result A represents system behaviours while Result B represents the system properties. Infrastructural Systems Excitations Response Signals Modelling Process Model frequency domain feature based monitoring Signal feature based monitoring Result B Result A The frequency domain analysis of system properties can reveal unique features of monitored systems.

Experimental tests using the new PEC sensing module developed at Newcastle Excitation Response sample New PEC sensing module Defects

Illustration of the time domain modelling and frequency domain analysis process Modelling Excitation Responses Extraction of models’ frequency domain features Structural Models Models’ Frequency Domain Feature Index

Data Analysis Results Case 1: 0mm defect Case 2: 2mm defect Case 3: 4mm defect Case 4: 6mm defect Case 5: 8mm defect Case 6: 10mm defect Case 7: 12mm defect Case 8: 14mm defect Case 9: 16mm defect

An illustration of RFID Sensing and the idea of application of time domain modelling and frequency domain analysis approach Input 1 Output (125kHz Pulse) Input 2 (1.95kHz) A system (composed of RFID reader, tag and associated sample area) Input 1 Input 2Output

Output of RFID system FFT of Output 125KHz2*125KHz3*125KHz 1.95KHz 2*1.95KHz 3*1.95KHz 4*1.95KHz 125KHz 125KHz-3*1.95KHz 125KHz-1.95KHz Evidence of possible system nonlinearities

Conclusions The time domain modelling and frequency domain analysis approach has been successfully applied to analyse data from the new PEC sensing module developed at Newcastle. The RFID sensing system may need to be considered as a two inputs and one output nonlinear system so nonlinear system time domain modelling and frequency domain analysis should be used to resolve the associated autonomous monitoring problems. Plan for next step: - Investigating accuracy issues with defect detection using PEC sensing and time domain modelling and frequency domain analysis. - Studying the application of time domain modelling and frequency domain analysis to RFID sensing based autonomous monitoring. - Studying mobile robot based implementation technology.