High-Dynamic and High-resolution Automatic Photon Counting OTDR

for Optical Fiber Network Monitoring

Felipe Calliari

, Luis E. Y. Herrera

, Jean Pierre von der Weid

and Gustavo C. Amaral

1,2

Center for Telecommunication Studies, Pontiﬁcal Catholic University of Rio de Janeiro, Rio de Janeiro 22451-900, Brazil

Institute for Quantum Information Science, and Department of Physics and Astronomy,

University of Calgary, Calgary, Canada

Keywords:

Photon-Counting OTDR, Signal Processing, FPGA.

Abstract:

In this work, the development of a hybrid structure for the monitoring of optical ﬁbers, using two types of

Photon Counting Optical Time Domain Reﬂectometers (ν-OTDR), is presented. While one ν-OTDR presents

a 32 dB dynamic range with spatial resolution of 6 m and minute-range measurements, the other has a 14 dB

dynamic range and a resolution of 3 cm with hour-range measurements. By employing a trend ﬁlter capable

of detecting ﬁber faults in the ν-OTDR ﬁber proﬁle and interchanging between either OTDR techniques in an

automatic fashion, we were able to harness the qualities of both in the minimum amount of measurement time.

Our experimental results performed with multiple optical ﬁber links attest the structure’s capability of auto-

matically detecting faults in an optical ﬁber link with ultra-high-resolution and minute-range measurements.

Furthermore, tunability of the hybrid structure enabling the monitoring of wavelength-division multiplexed

optical networks has been demonstrated.

1 INTRODUCTION

Optical ﬁbers have many advantages over other

transmission methods (cables, satellites, etc.), which

amounts to its immunity to electrical or magnetic in-

terference, its weight in relation to metallic cables,

and its low manufacturing cost. Although optical

ﬁbers are rather reliable, they can sometimes be dam-

aged. The causes are the most varied: in the ocean,

for example, ships can break optical ﬁbers, and even

sharks and other marine animals can chew the ﬁber

protective coating. On land, optical ﬁbers are used

following physical infrastructures such as highways,

railroads and electric power transmission lines and

can be broken due to works, storms or accidents. In

general, mechanical stress is highly prejudicial and

should be avoided.

Fiber monitoring is essential to enable long-

distance optical telecommunications links since the

high data rates can be jeopardized due to the afore-

mentioned mechanical hazards that they might be ex-

posed to. In addition, the supervision of the phys-

ical layer of the network is fundamental because

a break can cause the suspension of essential ser-

vices, such as bank, telephone or internet services

links. One way of discovering where a failure oc-

curred in communications systems using ﬁber optics

is to use a Rayleigh scatter-based monitoring system.

There are some types of techniques that make use of

this phenomenon, but what stands out most certainly

is the Optical Time Domain Reﬂectometer (OTDR)

(Barnoski et al., 1977). Through the use of an OTDR

it is possible to extract information about the ﬁber’s

integrity by accessing only one end of the ﬁber, i.e., a

central transmission station can monitor all the ﬁbers

connected to it without the need to install an apparatus

for monitoring at each of the multiple nodes of the op-

tical network. A good quality OTDR offers both good

spatial resolution (less than 20 meters) and long range

(greater than 200 kilometers) (Zhao et al., 2015).

The OTDR operates as follows: pulses of light,

which are emitted periodically, are coupled to the

test ﬁber through a circulator; the light pulses enter

through port 1 of the circulator and exit through port

2 which is connected to the optical ﬁber under test;

as these pulses propagate within the ﬁber a portion

of the light is back-reﬂected due to Rayleigh scatter-

ing and Fresnel reﬂection; the backscattered light en-

ters through port 2 of the circulator and is directed

to port 3, which is connected to a photodetector; the

electrical signal generated by the detector is sent to a

microprocessor which calculates the round trip time,

Calliari, F., Herrera, L., Weid, J. and Amaral, G.

High-Dynamic and High-resolution Automatic Photon Counting OTDR for Optical Fiber Network Monitoring.

DOI: 10.5220/0006643900820090

In Proceedings of the 6th International Conference on Photonics, Optics and Laser Technology (PHOTOPTICS 2018), pages 82-90

ISBN: 978-989-758-286-8

associates the backscattered power to a position in the

ﬁber and produces an OTDR trace otherwise known

as the ﬁber proﬁle.

One of the most important parameters of an

OTDR is the dynamic range, which is expressed in

dB, and refers to the maximum length of an optical

link that can be measured; it can also be understood

as the maximum attenuation that can be measured in

a optical ﬁber link. Another important parameter is

the spatial resolution of the OTDR, which reﬂects the

sensitivity to resolve two adjacent events. The spatial

resolution depends mainly on the light pulse width en-

tering the ﬁber. The greatest compromise relationship

in OTDRs is between the dynamic range and spatial

resolution since, in order to achieve higher resolution,

narrow pulses are required, but, on ther other hand,

the narrower the pulse, the less energy it will carry

which results in a lower dynamic range (Agrawal,

1997).

1.1 Photon Counting OTDR

With the advent of the Geiger-mode Single Pho-

ton Detector (SPD) in the telecommunication wave-

length, the Photon-Counting OTDR (ν-OTDR) was

proposed. Such devices offer higher sensitivity due

to extremely low power detection in the single-photon

regime (Eraerds et al., 2010). Operating in the gated

mode, such SPDs can attain high photon detection ef-

ﬁciencies and extremely low dark count rates (Eraerds

et al., 2010). The gated operation requires, however,

an intelligent management system to reduce monitor-

ing periods and enhance the acquisition of statistically

relevant data (Amaral et al., 2015).

The ν-OTDR can offer some advantages when

compared to a conventional state-of-the-art OTDR,

some of which include: higher spatial resolution, bet-

ter dynamic range, better 2-point resolution, lower

timing jitter and superior behavior concerning after-

pulsing (Eraerds et al., 2010; Amaral, 2014). Of

course, there are disadvantages too, some of which

are: dead zones after large loss events (charge per-

sistence effect); and trace speed, depending on the

application (Herrera, 2015). Recently, a tunable ν-

OTDR with 6 meters spatial resolution and 32 dB

dynamic range has been proposed in a WDM-PON

context (Amaral et al., 2014), herewith dubbed the

High-Dynamic ν-OTDR, or HD-ν-OTDR. In (Her-

rera et al., 2015), the ν-OTDR is employed in a setup

for ultra-high resolution measurements up to 3 cen-

timeters with a 14 dB dynamic range, the Ultra-High

Resolution ν-OTDR, or UHR-ν-OTDR.

2 MEASUREMENT

ARRANGEMENT

In this work, the compromise relationship between

dynamic range and spatial resolution has been tack-

led and a proposal for reducing the gap between the

aforementioned prominent ν-OTDR techniques has

been reached. The herewith described monitoring

structure aims to unite the high dynamic range of the

HD-ν-OTDR to the high resolution provided by the

UHR-ν-OTDR with the objective of accurately and

quickly ﬁnding faults in an optical ﬁber link. More

importantly, the monitoring structure is fully auto-

matic since an algorithm tailored for the application

of ﬁnding faults in a ﬁber proﬁle has been included.

The chart shown in Fig. 1 shows the steps taken by

the system to inspect a ﬁber optical link.

Figure 1: Flowchart of the Hybrid and Automatic ν-OTDR.

First, the system uses the HD-ν-OTDR to obtain

a ﬁber proﬁle whose resolution is ∼ 6 m. Despite the

limited resolution, the acquisition rate is quite high

in a 20 km link, for example, the system allows the

determination of the last point of the proﬁle with a

signal-to-noise ratio of 10 dB in just under two min-

utes (Amaral, 2014). Then the trend ﬁlter estimates

the positions that may present faults and sends them

as events list to the HR-ν-OTDR. The signal process-

ing step is also quite accelerated, with extremely ac-

curate results in just under a minute (Amaral et al.,

2015). The HR-ν-OTDR, in turn, analyzes only the

regions around the points of interest. Although the

acquisition is time-consuming, the extremely signiﬁ-

cant reduction of the total ﬁber length to be inspected

enables the results to be acquired with palatable times,

in the order of minutes.

It is interesting, at this point, to explain the archi-

tectures of the different ν-OTDRs separately. How-

ever, in Fig. 2, the complete architecture of the pro-

posal is presented. It should be noted that all com-

ponents that originally belong to the HD-ν-OTDR ar-

chitecture are above the SPD’s line and, conversely,

the components below the SPD’s line are part of the

HR-ν-OTDR architecture. In this architecture, all the

devices that can be employed in both architectures are

shared so that it is not only simpliﬁed but, also, occu-

High-Dynamic and High-resolution Automatic Photon Counting OTDR for Optical Fiber Network Monitoring

pies less physical space.

In Fig. 2, the ﬁrst Semiconductor Optical Am-

pliﬁer (SOA), right after the Tunable Laser Source

(TLS), boosts the optical signal inside a narrow win-

dow of 60 ns with a 2 A peak current driver creating

high power narrow light pulses. The second SOA is

driven by a 600 mA current pulse with 60 ns width.

Even though the driving pulse is not enough to reach

full power operation of the second SOA alone, the

ﬁrst boost guarantees optimal power usage while the

second acted as a gainless optical switch, shaping the

width of the optical pulse down to 60 ns. The tandem

conﬁguration of the SOAs guarantees a high extinc-

tion rate, contributing to the overall dynamic range of

the detections. An FPGA is responsible for trigger-

ing a digital delay generator (DDG) which, in turn,

triggers both of the SOA’s drivers. The FPGA is

also responsible for creating the gate pulses for the

SPD; each detection is stored with its respective tim-

ing stamp and the data is transmitted through an USB

cable from the FPGA to a computer. Wavelength tun-

ability, in this setup, is guaranteed by the TLS.

In order to maximize the number of detections and

reduce the acquisition time, a train of gates, spaced

apart by the dead time of the SPD, is created (Weg-

muller et al., 2004; Amaral, 2014). With every new

light pulse that is sent into the optical ﬁber, a delay

is added to the train of gates to ensure that the entire

ﬁber is analyzed. The FPGA board is responsible for

managing the train of gates and the delays between

pulses as well as enabling the light pulses through the

SOA’s driver. This process is graphically detailed in

Fig. 3 (Amaral et al., 2015). Each detection is as-

sociated with a 16 bit word – the time stamp – com-

posed by r and s, the Gate and Pulse number, respec-

tively. The parameters a, b and c represent the gate

window, the dead time and the maximum delay be-

tween pulses.

Back to Fig. 2, we ﬁnd, below the SPD line,

the architecture of the UHR-ν-OTDR. The 115 fs

wide pulses from an Ultra Wideband Laser Source

(UWS) passes through a narrow bandpass ﬁlter and

are then ampliﬁed by an Erbium Doped Fibre Am-

pliﬁer (EDFA). The bandpass ﬁlter ensures that the

EDFA will amplify only the selected wavelength and

thus not wasting optical power. The tunability is guar-

anteed by the Tunable Filter which exhibits an ultra-

sharp roll-off ideal for Dense WDM (DWDM) moni-

toring. The pulses are, then, directed to an SOA which

works as fast optical switch, reducing the pulse repe-

tition rate and satisfy the condition of one light pulse

traversing the ﬁber at a time. The enabling pulses of

the SOA are generated by a DDG, which is triggered

by the synchronizing signal from the UWS. These en-

abling pulses are reshaped by the SOA driver which

is capable of driving the SOA with 4 ns-wide 600 mA

pulses.

Since the light pulse passing through the SOA is

115 fs wide which is much narrower than 4 ns, the

transmitted light pulse degrades due to the presence

of ampliﬁed spontaneous emission (ASE) generated

by the SOA. However, the corresponding ASE power

is approximately 10 dB below the pulse peak and has

little effect on the achievable spatial resolution of the

technique (Herrera et al., 2016). The DDG also trig-

gers the SPD with varying delays such as to cover

the whole ﬁber length. Detections are processed by

a Time-to-Digital Converter and sent to a computer.

A Variable Optical Attenuator (VOA) at the SPAD’s

input guarantees that the power does not exceed the

saturation limit so the detector is kept at linear regime

(Eraerds et al., 2010). Wavelength tunability, in this

setup, is achieved by the use of a narrow bandpass

ﬁlter at the source’s output (BPF).

It is evident from the schematic of Fig. 2 that the

management system is essential for the architecture

operation. It is responsible for interfacing with both

ν-OTDRs and to processes the respective ﬁber pro-

ﬁles with the fault ﬁnding algorithm. It is also re-

sponsible for switching between the operation modes,

which is accomplished by actuating upon the Optical

and Radio-Frequency switches – OS and RFS in Fig.

2. The OS is responsible for injecting either the HD-

ν-OTDR or the UHR-ν-OTDR pulse into the ﬁber

while the RFS is responsible for directing the correct

gate pulse to the SPD as they differ from one mode to

the other (Amaral et al., 2015; Herrera et al., 2016).

3 RESULTS - LONG-DISTANCE

FIBER LINK

A 36 km long ﬁber link composed of three almost

identical ﬁbers with 12 km each was used to gener-

ate the OTDR trace and the ﬁltered signature shown

in Fig. 4. The trend ﬁlter of choice for this work is the

Adaptive `

Filter, presented in (von der Weid et al.,

2016), which has been shown to outperform several

other signal processing techniques that focus on the

identiﬁcation of trends in data series. Depending on

the size of the data series, the processing time can take

from a few minutes to a few hours, which would be

the case for a 36000 points data series. With the 6 me-

ters bin, which corresponds to the spatial resolution of

the HR-ν-OTDR, the approximately 36km ﬁber pro-

ﬁle is represented by a ∼ 6000 points data series, so

the Adaptive `

Filter takes about two minutes to pro-

cess the proﬁle.

PHOTOPTICS 2018 - 6th International Conference on Photonics, Optics and Laser Technology

Figure 2: Architecture of the Hybrid and Automatic ν-OTDR for fast and accurate fault ﬁnding in optical ﬁber links.

Figure 3: Graphical representation of the higher data ac-

quisition method using the time-shifted train of gates in a

single optical pulse (Amaral et al., 2015).

The output from the Adaptive `

Filter is a list

of events containing the location of candidates for

ﬁber faults. The results were as follows: 0, 1011 ± 6,

12303 ± 6, 24603 ± 6 and 36830 ± 6 meters. It is ev-

ident that the beginning of the ﬁber is the ﬁrst value

of the list, which is neglected. It is noteworthy that

the ﬁlter always selects the ﬁrst positions, so it can be

consistently neglected and is not an ad hoc procedure.

The second value corresponds to a spurious detection

and the rest corresponds to connectors and the ﬁber

end.

Figure 4: HD-ν-OTDR trace and the ﬁltered signature of

the ∼ 36km ﬁber link.

According to the chart presented in Fig. 1, this

list of events will be scrutinized with extreme reso-

lution by the UHR-ν-OTDR; its role is both to deter-

mine whether the points correspond to actual faults

and, in case it is indeed a fault, determine its position

with higher resolution. The UHR-ν-OTDR is fed with

the fault candidates positions and, also, with a spatial

window (arbitrarily set as ±100 meters) within which

to search. The results of the UHR-ν-OTDR are shown

in Figs. 5, 6, and 7.

Figs. 5 to 7 present the UHR-ν-OTDR monitoring

results for the three actual faults in the link. It also

High-Dynamic and High-resolution Automatic Photon Counting OTDR for Optical Fiber Network Monitoring

Figure 5: High-resolution measurement around 12303 ± 6

meters.

Figure 6: High-resolution measurement around 24603 ± 6

meters.

Figure 7: High-resolution measurement around 36830 ± 6

meters.

presents the detailed detection of the Adaptive `

Fil-

ter, closing the last step of the chart presented in Fig.

1. The result of the 1011 ± 6 meters spurious detec-

tion is not presented, for simplicity. However, as ex-

pected, the Adaptive `

Filter did not detect any trend

break, which is interpreted as the absence of fault.

Overall, the whole procedure of determining, with

precisions of up to 3cm, the fault positions of a 36km

ﬁber has taken approximately 18 minutes where: 150

seconds correspond to the acquisition of the ﬁrst pro-

ﬁle with the HD-ν-OTDR; 150 seconds correspond

to the processing step of the Adaptive `

Filter that

identiﬁes potential fault candidates; 600 seconds cor-

respond to the UHR-ν-OTDR measurements where

each 200 meter stretch take one fourth of the whole

time; and the ﬁnal 300 seconds correspond to the time

the Adaptive `

Filter takes to process all of the high-

resolution measurements, one fourth of the time per

stretch.

4 RESULTS - MEDIUM-RANGE

DWDM LINK

In order to evaluate the possibility of inspecting a

wavelength-multiplexed link, link 2 was assembled

containing a ∼2 km feeder ﬁber and two wavelength-

dedicated ﬁbers of ∼3.6 km and ∼12 km connected

by a passive wavelength division multiplexer (WDM)

at channels 37 and 40 of the DWDM grid. The results

of the HD-ν-OTDR are presented in Figs. 8 and 9.

Figure 8: HD-ν-OTDR trace and the ﬁltered signature of the

∼ 2 + 3.6km ﬁber link at channel 37 of the DWDM grid.

Figure 9: HD-ν-OTDR trace and the ﬁltered signature of

the ∼ 2 + 12km ﬁber link at channel 40 of the DWDM grid.

Since both HD-ν-OTDR measurements (for chan-

nels 37 and 40) discovered a fault candidate at the

same position (around 1948 ± 6 meters), we show,

in Fig. 10, the high-resolution measurement result

which is common for both measurements. Once

again, we do not present the high-resolution measure-

ment results for the spurious detections since, as ex-

pected, these have been discarded as fault positions

after scrutiny of the UHR-ν-OTDR.

Apart from the WDM that connects the feeder

ﬁber to the user ﬁber, no other faults were present at

the measured links apart from the ﬁber ends. These

PHOTOPTICS 2018 - 6th International Conference on Photonics, Optics and Laser Technology

Figure 10: High-resolution measurement around 1945 ± 6

meters.

are presented in Fig. 11 and 12. The overall timing

taken by the monitoring structure to return the high-

resolution results for both links was approximately 25

minutes. It is clear that, even though the structure

is robust against spurious detections in the ﬁrst step,

the impact is negative in the total timing. That is, of

course, because each extra candidate scrutinized by

the UHR-ν-OTDR translates into at least 3 extra min-

utes distributed between the data acquisition and the

signal processing steps.

Figure 11: High-resolution measurement around 5525 ± 6

meters.

Figure 12: High-resolution measurement around 14250 ± 6

meters.

5 TUNABILITY, COHERENCE,

CHROMATIC DISPERSION

AND SPATIAL RESOLUTION

A tunable OTDR measurement compatible with

WDM networks (as speciﬁed in ITUT G.694.1) must

not only be capable of selecting the center wavelength

of emission but also the spectral width of the opti-

cal signal. The current Dense WDM (DWDM) chan-

nels are either 0.8 nm wide comporting 40 channels

or 0.4 nm wide comporting 80 channels, but devices

that can operate with 0.2 nm wide channels (the so-

called Ultra-Dense WDM) have already been pro-

posed (Shahpari et al., 2015). The increasing num-

ber of channels will enable higher user capacity and

more ﬂexibility of the interconnections at the expense

of reduced bandwidth per channel.

Compatibility between the probing pulse spectral

shape and the network to be monitored becomes clear

by the result of Fig. 13. In it, a broadband source was

used to probe a WDM network composed by a feeder

ﬁber, a WDM splitter and four user ﬁbers. Since the

source does not provide wavelength selectivity, the

backscattered power from all the channels are over-

lapped and cannot be distinguished in the resulting

proﬁle except by the end-ﬁber reﬂection peak.

Figure 13: OTDR trace of a WDM network using the HD-ν-

OTDR and a broadband light source. The overlapped proﬁle

does not allow for the distinction between each user ﬁber.

In Fig. 14, on the other hand, the proﬁles were ac-

quired employing a spectrally-tailored optical source

in order to meet the WDM channel’s characteristics

so that each individual user ﬁber could be probed in-

dividually. Evidently, more time needs to be spent

in these measurements since each user ﬁber has to be

monitored individually.

Recall that the pulse generated by the UWS for

high-resolution inspection has an extremely broad

spectrum and must be spectrally-tailored in order to

ﬁt the requirements of the WDM network it is applied

to – see Section 2. At this point, two distinct effects

High-Dynamic and High-resolution Automatic Photon Counting OTDR for Optical Fiber Network Monitoring

Figure 14: Individual OTDR traces using the HD-ν-OTDR

for each of the user ﬁbers. By spectrally-tailoring the opti-

cal signal, each user ﬁber can be individually addressed due

to wavelength selectivity characteristics of WDM devices.

are in contrast: the coherent Rayleigh noise (CRN),

which grows inversely proportional to the spectral

width (De Souza, 2006); and the chromatic disper-

sion, which grows proportionally to the spectral width

(Herrera et al., 2015). The CRN are the ﬂuctuations in

backscatter intensity due to the interference caused by

the superposition of several light waves arriving at the

detector with random phases (Shimizu et al., 1992).

Although the CRN arises due to the random dis-

tribution of the incoming wave phases, it cannot be

averaged out with long-time measurements such as

the counting noise (von der Weid et al., 2016). In

order to illustrate the effect of the CRN on OTDR

measurements, Fig. 15 presents two OTDR proﬁles

of the same ﬁber – but using probe pulses with dif-

ferent line-widths: 600 kHz, the intrinsic linewidth

of a tunable coherent laser; and 100GHz, a probe

pulse spectrally-tairoled to match the 0.8 nm channel

of DWDM-PONs (Caballero et al., 2013).

Figure 15: OTDR traces using the HD-ν-OTDR with two

different spectral widths. The red trace, which has a much

higher noise, was taken using a coherent laser with 600 kHz

linewidth. The black trace was taken by employing a wave-

length sweeping technique that mimics a broader linewidth

(Caballero et al., 2013); for this, the same TLS was swept

from 1554.13 to 1554.93 nm.

It becomes clear, thus, that, in order to avoid the

presence of CRN in the OTDR proﬁle, the probe pulse

should be as spectrally broad as possible; in the spe-

ciﬁc case of WDM-PONs, the broader linewidth is

the one that matches the whole channel bandwidth.

Broadening the linewidth of the laser, however, will

increase the time stretching of the optical pulse as it

traverses the ﬁber due to chromatic dispersion (El-

refaie et al., 1988). Also, since the original emit-

ted pulses are transform-limited, the spectral tailor-

ing will have a direct impact on the time broaden-

ing. This condition constitutes a compromise rela-

tionship: if the optical pulse is spectrally-tailored

to a narrow bandwidth, it will be enlarged in time

and render poor spatial resolution in both short- and

long-distance measurements; however, if the pulse is

spectrally-tailored to the broader possible bandwidth

value, the optical pulse will exhibit a good spatial

resolution for short-distance measurements and, due

to chromatic dispersion, a poor spatial resolution for

long-distance measurements. This compromise rela-

tionship is translated in Fig. 16, where the achievable

spatial resolution versus the bandwidth of the pulse

is plotted for different ﬁber lengths. It is worth not-

ing that, for each distance measurement, there is an

optimal bandwidth value that corresponds to the best

achievable spatial resolution. Also, detector’s jitter

may, sometimes, limit the spatial resolution instead of

either the chromatic dispersion or the spectral width.

Figure 16: The compromise relationship between the spatial

resolution and the spectral width for different ﬁber lengths.

As expected, for longer ﬁbers, broader bandwidths have a

harsher impact on diminishing the achievable spatial reso-

lution. In a 10 meter ﬁber, chromatic dispersion has negli-

gible effect and the spatial resolution will be limited by the

detector’s jitter, as demonstrated by the blue dots.

The model used to ﬁt the experimental data was

the following:

= ∆λ · a +

∆λ

, (1)

where a corresponds to 2 · ﬁber length · D and b cor-

responds to pulse width of the UWS-1000H at full

bandwidth, ie, b ≈ 20fs · 800 nm. Also, we have used

PHOTOPTICS 2018 - 6th International Conference on Photonics, Optics and Laser Technology

an approximation for the dispersion factor D and as-

sumed that it remained constant within ∆λ. From the

results, it is clear that slope for ∆λ ≥ 1 nm is well

ﬁtted, but the experimental results below this value

show some inconsistencies with the ﬁt. We conjec-

ture that this behaviour may arise from the fact that

the pulse peak power for reduced ∆λ is very low and

the measurement results may be distorted. The back-

reﬂected power also diminishes as the ﬁber length

grows, which is observed in a higher contrast between

experimental and ﬁtted data for the longer ﬁbers of

24.6 km and 32.8 km. The pulse width enlargement

for low values of ∆λ is due to the transform-limited

pulse, i.e., it is as short as its spectral bandwidth per-

mits.

6 CONCLUSIONS

An automatic, highly accurate, and fast optical ﬁber

link monitoring structure that aims to ally the best fea-

tures of two distinct and prominent monitoring struc-

tures, namely the High-Dynamic and Ultra-High-

Resolution Photon Counting OTDRs (Amaral et al.,

2015; Herrera et al., 2015), has been successfully

assembled. The fundamental constituent of the pro-

posed architecture is a fault ﬁnding algorithm capa-

ble of accurately identifying fault candidates in a ﬁber

proﬁle. The employed algorithm enables the automa-

tion of the whole process so that an operator is no

longer necessary to inspect each ﬁber proﬁle, i.e., the

results are output automatically. A video contain-

ing an experimental run of the method can be found

in (Optoelectronics Laboratory – F. Calliari, L. E. Y.

Herrera, J. P. von der Weid, and G. C. Amaral, ).

The presented technology has been experimen-

tally veriﬁed in long-range, mid-range, and wave-

length multiplexed optical ﬁber links. The process

involves four distinct steps: initially, a fast high-

dynamic measurement is performed with the HD-ν-

OTDR; next, the ﬁber proﬁle is processed by the

Adaptive `

Filter and the fault candidates are iden-

tiﬁed; having the candidates list from the previous

step, a high-resolution measurement is performed in

the vicinity of the fault candidate position using the

UHR-ν-OTDR; ﬁnally, the results of the previous step

are also processed by the Adaptive `

Filter and the

actual fault positions are identiﬁed with extremely

high accuracy. Our results show that faults in links

as long as 36 km could be inspected with spatial res-

olutions of up to 3 cm in less than 15 minutes. This

work paves the way for low-cost, highly reliable, au-

tomatic, and fast monitoring of optical ﬁber links.

ACKNOWLEDGMENT

The authors would like to thank brazilian agencies

CNPq, Capes and FAPERJ for ﬁnancial support.

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PHOTOPTICS 2018 - 6th International Conference on Photonics, Optics and Laser Technology