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1 The Distributed Measurement Systems: a New Challenge for the Metrologists by Alessandro Ferrero and Roberto Ottoboni Politecnico di Milano – Dipartimento.

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Presentation on theme: "1 The Distributed Measurement Systems: a New Challenge for the Metrologists by Alessandro Ferrero and Roberto Ottoboni Politecnico di Milano – Dipartimento."— Presentation transcript:

1 1 The Distributed Measurement Systems: a New Challenge for the Metrologists by Alessandro Ferrero and Roberto Ottoboni Politecnico di Milano – Dipartimento di Elettrotecnica Milano - Italy

2 Politecnico di Milano INGRID 2008 – Lacco Ameno – Ischia – ITALY – April 9-11, 2008 2 Overview Introduction Introduction Evolution of the Measurement Instruments Evolution of the Measurement Instruments DSP-based architectures DSP-based architectures Virtual Instruments (VI) Virtual Instruments (VI) Distributed Measurement Systems (DMS) Distributed Measurement Systems (DMS) Metrology issues Metrology issues

3 Politecnico di Milano INGRID 2008 – Lacco Ameno – Ischia – ITALY – April 9-11, 2008 3 Signal processing & Measurement Signal processing is the basis of the measurement activity Signal processing is the basis of the measurement activity Any evolution in signal processing techniques has a direct impact on measurement systems Any evolution in signal processing techniques has a direct impact on measurement systems

4 Politecnico di Milano INGRID 2008 – Lacco Ameno – Ischia – ITALY – April 9-11, 2008 4 Digital Signal Processing Analog signals can be converted into a sequence of digital samples Analog signals can be converted into a sequence of digital samples The sampling theorem provides the conditions for preserving the information associated with the original analog signal The sampling theorem provides the conditions for preserving the information associated with the original analog signal The modern instruments are based on DSP techniques The modern instruments are based on DSP techniques They have benefited of the recent, impressive evolution of the DSP techniques and devices They have benefited of the recent, impressive evolution of the DSP techniques and devices

5 Politecnico di Milano INGRID 2008 – Lacco Ameno – Ischia – ITALY – April 9-11, 2008 5 The first revolution: DSP-based instruments T&C ADC Mem Comp Field Input signals Meas. Analog processing Digital processing From: A measurement, an instrument To: A measurement, an algorithm

6 Politecnico di Milano INGRID 2008 – Lacco Ameno – Ischia – ITALY – April 9-11, 2008 6 The second revolution: Virtual Instruments T&C ADC Mem Comp Field Input signals Meas. Interf. An interface is added to: An interface is added to: Provide an instrument-like, user-friendly Front Panel Provide an instrument-like, user-friendly Front Panel Provide a graphic programming interface Provide a graphic programming interface

7 Politecnico di Milano INGRID 2008 – Lacco Ameno – Ischia – ITALY – April 9-11, 2008 7 The third revolution: Distributed Measurement Instruments T&C ADC Mem Comp Interf. Net Int. Field World Input signals An interface to an interconnection network is added An interface to an interconnection network is added

8 Politecnico di Milano INGRID 2008 – Lacco Ameno – Ischia – ITALY – April 9-11, 2008 8 The new paradigm The desired measurement result is provided by a network of cooperating instruments that share their resources The desired measurement result is provided by a network of cooperating instruments that share their resources Internet/Intranet Field ADC Measurement unit 1 Measurement unit j Measurement unit N Supervising unit

9 Politecnico di Milano INGRID 2008 – Lacco Ameno – Ischia – ITALY – April 9-11, 2008 9 Better performance … …more problems! The different units share resources and data The different units share resources and data collected under different conditions collected under different conditions acquired by different hardware systems acquired by different hardware systems The evaluation of the measurement uncertainty becomes a problem. The evaluation of the measurement uncertainty becomes a problem.

10 Politecnico di Milano INGRID 2008 – Lacco Ameno – Ischia – ITALY – April 9-11, 2008 10 The most mischievous problem The lack of time synchronization between the sampling devices of the different units. The lack of time synchronization between the sampling devices of the different units. When measured data are shared across a public-domain network (Internet), the transmission time becomes largely unpredictable. When measured data are shared across a public-domain network (Internet), the transmission time becomes largely unpredictable. The risk is that the different units start working on different timelines. The risk is that the different units start working on different timelines.

11 Politecnico di Milano INGRID 2008 – Lacco Ameno – Ischia – ITALY – April 9-11, 2008 11 The lack of synchronization The same event is seen at different time instants by the different units The same event is seen at different time instants by the different units Different delays are introduced Different delays are introduced Their estimation may be cumbersome Their estimation may be cumbersome The consequent uncertainty estimation useless The consequent uncertainty estimation useless Unit 1 Event at time t 1 Unit 2 Event at time t 2 t t

12 Politecnico di Milano INGRID 2008 – Lacco Ameno – Ischia – ITALY – April 9-11, 2008 12 The solution Clock synchronization Clock synchronization A unique timeline is defined for all units A unique timeline is defined for all units A timestamp can be associated to each transmitted data A timestamp can be associated to each transmitted data Measurement uncertainty is not related to the transmission delay, but to the residual synchronization error. Measurement uncertainty is not related to the transmission delay, but to the residual synchronization error.

13 Politecnico di Milano INGRID 2008 – Lacco Ameno – Ischia – ITALY – April 9-11, 2008 13 Clock synchronization How accurate? How accurate? As always, it depends on the target uncertainty. As always, it depends on the target uncertainty. The case of the identification of the origin of transient disturbances in the electric system. The case of the identification of the origin of transient disturbances in the electric system.

14 Politecnico di Milano INGRID 2008 – Lacco Ameno – Ischia – ITALY – April 9-11, 2008 14 Measuring unit 1 Measuring unit 2 t0t0 t1t1 t2t2 t If t 2 - t 1 > 0, If t 2 - t 1 > 0, then the disturbance’s origin is upstream the measuring unit 1 The synchronization uncertainty must be significantly lower than t 2 - t 1 The synchronization uncertainty must be significantly lower than t 2 - t 1

15 Politecnico di Milano INGRID 2008 – Lacco Ameno – Ischia – ITALY – April 9-11, 2008 15 Clock synchronization How accurate? How accurate? As always, it depends on the target uncertainty. As always, it depends on the target uncertainty. The case of the identification of the origin of transient disturbances in the electric system. The case of the identification of the origin of transient disturbances in the electric system. A GPS synchronization is required A GPS synchronization is required  50 ns with respect to UTC  50 ns with respect to UTC The case of the identification of harmonic disturbances The case of the identification of harmonic disturbances

16 Politecnico di Milano INGRID 2008 – Lacco Ameno – Ischia – ITALY – April 9-11, 2008 16 Each measurement unit measures suitable power quality indices averaged over a given interval Each measurement unit measures suitable power quality indices averaged over a given interval The synchronization uncertainty must be significantly lower than the duration of the averaging interval The synchronization uncertainty must be significantly lower than the duration of the averaging interval Load1 Load 2 Load j Load N Feeder Measuring units

17 Politecnico di Milano INGRID 2008 – Lacco Ameno – Ischia – ITALY – April 9-11, 2008 17 Clock synchronization How accurate? How accurate? As always, it depends on the target uncertainty. As always, it depends on the target uncertainty. The case of the identification of the origin of transient disturbances in the electric system. The case of the identification of the origin of transient disturbances in the electric system. A GPS synchronization is required A GPS synchronization is required  50 ns with respect to UTC  50 ns with respect to UTC The case of the identification of harmonic disturbances The case of the identification of harmonic disturbances A NTP synchronization is sufficient (  10 ms) A NTP synchronization is sufficient (  10 ms)

18 Politecnico di Milano INGRID 2008 – Lacco Ameno – Ischia – ITALY – April 9-11, 2008 18 Conclusions DMS benefit of the evolution of the interconnection of the computing systems. DMS benefit of the evolution of the interconnection of the computing systems. They are the natural evolution of the remote measurement systems They are the natural evolution of the remote measurement systems They are a promising tool for the solution of very complex measurement tasks They are a promising tool for the solution of very complex measurement tasks The present new problems in metrology The present new problems in metrology If disregarded they may lead to largely incorrect results If disregarded they may lead to largely incorrect results


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