The Distributed Measurement
Systems: a New Challenge
for the Metrologists
by
Alessandro Ferrero and Roberto Ottoboni
Politecnico di Milano – Dipartimento di Elettrotecnica
Milano - Italy
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Overview
Introduction
 Evolution of the Measurement Instruments

DSP-based architectures
 Virtual Instruments (VI)
 Distributed Measurement Systems (DMS)


Metrology issues
INGRID 2008 – Lacco Ameno – Ischia – ITALY – April 9-11, 2008
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Signal processing & Measurement
Signal processing is the basis of the
measurement activity
 Any
evolution in signal processing
techniques has a direct impact on
measurement systems

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Digital Signal Processing

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 modern instruments are based on
DSP techniques
 They have benefited of the recent,
impressive evolution of the DSP
techniques and devices

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The first revolution:
DSP-based instruments
Field
Digital processing
Meas.
Input signals
T&C
ADC
Mem
Comp
From: A measurement, an instrument
To: A measurement, an algorithm
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The second revolution:
Virtual Instruments
Field
Meas.
Interf.
Input signals
T&C

ADC
Mem
Comp
An interface is added to:
Provide an instrument-like, user-friendly Front
Panel
 Provide a graphic programming interface

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The third revolution:
Distributed Measurement Instruments
Field
Interf.
Input signals
T&C

ADC
An interface to an
interconnection
network is added
Mem
Comp
Net Int.
World
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The new paradigm

The desired measurement result is
provided by a network of cooperating
instruments that share their resources
Field
ADC
Measurement unit 1
Supervising unit
ADC
Field
Internet/Intranet
Field
ADC
Measurement unit j
Measurement
unit N
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– Lacco Ameno – Ischia – ITALY – April 9-11, 2008
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Better performance …
…more problems!

The different units share resources and
data
collected under different conditions
 acquired by different hardware systems


The evaluation of the measurement
uncertainty becomes a problem.
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The most mischievous problem
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.
 The risk is that the different units start
working on different timelines.

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The lack of synchronization
Event at time t1 Event at time t2
Unit 1
Unit 2
t
t
The same event is seen at different time
instants by the different units
 Different delays are introduced
 Their estimation may be cumbersome


The consequent uncertainty estimation useless
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The solution

Clock synchronization
A unique timeline is defined for all units
 A timestamp can be associated to each
transmitted data


Measurement uncertainty is not related to
the transmission delay, but to the residual
synchronization error.
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Clock synchronization
How accurate?
 As always, it depends on the target
uncertainty.
 The case of the identification of the origin
of transient disturbances in the electric
system.

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t2
Measuring
unit 2
Measuring
unit 1
t1
t0
t
If t2 - t1 > 0,
then the disturbance’s origin is upstream
the measuring unit 1
 The synchronization uncertainty must be
significantly lower than t2 - t1

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Clock synchronization
How accurate?
 As always, it depends on the target
uncertainty.
 The case of the identification of the origin
of transient disturbances in the electric
system.


A GPS synchronization is required
 50

ns with respect to UTC
The case of the identification of harmonic
disturbances
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Measuring units
Load1
Feeder
Load 2
Load j
Load N
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

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Clock synchronization
How accurate?
 As always, it depends on the target
uncertainty.
 The case of the identification of the origin
of transient disturbances in the electric
system.


A GPS synchronization is required
 50

ns with respect to UTC
The case of the identification of harmonic
disturbances

A NTP synchronization is sufficient (10 ms)
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Conclusions
DMS benefit of the evolution of the
interconnection of the computing systems.
 They are the natural evolution of the
remote measurement systems
 They are a promising tool for the solution
of very complex measurement tasks
 The present new problems in metrology
 If disregarded they may lead to largely
incorrect results

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