arXiv subjects
Publications and source records attributed to Florian Azendorf.
Signal fading creates points along the fiber where phase cannot be extracted, so they are conventionally discarded. Instead, we propose a Kalman-based solution for {\phi}-OTDR full-fiber monitoring. Experiments demonstrate phase and temperature estimation with approximately 15 times better spatial density than if removing these points.
We present a theoretical, algorithmic, and experimental study of temperature sensing using $\phi$-OTDR with coherent detection. A physics-based model is developed to relate the measured Rayleigh backscattered signal to temperature variations along the fiber, showing that the phase evolution encodes the cumulative temperature change between the interrogator and the sensing location, while the amplitude exhibits only local sensitivity. Based on this insight, we propose robust algorithms for temperature-event detection and temperature-profile reconstruction. Experimental results demonstrate reliable recovery of temperature-induced perturbations in standard single-mode fibers using coherently detected $\phi$-OTDR.
Monitoring a 118 km subsea cable using Distributed acoustic, state-of-polarization, and Brillouin sensing captured storm-induced strain up to $\approx 0.003 \mu\epsilon$ (dynamic) and $\approx 180 \mu\epsilon$ (static), demonstrating consistent yet distinct modal responses to environmental loading.
We present $\phi$-OTDR for detecting and localising full spark-gap breakdowns by analysing backscattered light phase and frequency-domain signatures during high-voltage discharges synchronised with oscilloscope-recorded events. Measuring sub-kHz confirms clear discharge signatures and acoustic reconstruction over long links with $\approx$ 10 m spatial resolution.
Pairing coherent correlation OTDR with low-complexity analysis methods, we investigate the detection of fast temperature changes and vibrations in optical fibers. A localization accuracy of ~2 m and extraction of vibration amplitudes and frequencies is demonstrated.
A deployed fiber with in-house and underground sections is interrogated with a coherent correlation OTDR. The origin and propagation speed of a hammer-generated pressure wave in the underground section is detected and acoustic signals are monitored.
Distributed fiber sensing based on correlation-aided phase-sensitive optical time domain reflectometry is presented. The focus is on correlation as an enabler for high spatial resolution. Results from different applications are presented.
A coherent optical subassembly (COSA) is evaluated for coherent-correlation optical time domain reflectometry (CC-OTDR) based fibre sensing. Even though the COSA was originally designed for digital communication applications, acoustic signals with frequencies up to 360 Hz can be detected after 50 km of transmission.
Fiber optic sensing is becoming an important means to physically secure today's network infrastructure. However, a network-wide deployment of the monitors will require cost reduction of the interrogator system, which can only be achieved by highly integrated system components. In this contribution, we report on the use of an in-house designed single-chip coherent transceiver for acoustic fiber sensing. The transceiver on the basis of silicon photonics contains a high-speed dual-polarization IQ-modulator as well as a coherent receiver with balanced photodiodes and trans-impedance amplifiers, as defined by the OIF integrated coherent transmit-receive optical sub assembly (IC-TROSA) implementation agreement. The laser, used for transmission and as local oscillator, is provided external to the photonic integrated circuit and can be chosen according to the line-width requirements of the sensing system. The acoustic sensing demonstration is using a correlation-based optical time domain reflectometry with coherent detection. This method is able to detect, besides the amplitude information, the phase of the back-scattered signal, which has a significantly higher sensitivity to environmental effects on the fiber, like temperature and strain. As a proof of concept, sensing of an acoustic signal after a fiber span of 20 km is demonstrated by evaluating the obtained phase information, providing information on external dynamic events up to a frequency of 1.75 kHz.
We report on methods to monitor the transmission path in optical networks using a correlation-based OTDR technique with direct and coherent detection. A high probing symbol rate can provide picosecond-accuracy of the fiber propagation delay, while a sensitive phase detection with a high repetition rate allows the monitoring of dynamic effects in the vicinity of the fiber. We discuss various approaches to evaluate the measured traces and show the results of a few monitoring applications.
Superimposed temperature variations and dynamic strain applied through a 400 Hz acoustic signal on a 195 m single-mode fiber section are successfully measured using a coherent correlation optical time domain reflectometry as an interrogator.
In this paper, we report on the development progress of correlation-based optical time domain reflectometry (OTDR). Substituting the direct detection receiver with a coherent receiver enables to extract the phase and polarization information of the reflected signal. Furthermore, due to the mixing of a weak probe signal with a strong local oscillator the sensitivity of the receiver improved. This improvement was demonstrated by analyzing the reflection from an angled physical contact (APC) connector. To further quantify the improvements, we compare the direct detection correlation OTDR (C-OTDR) with the coherent detection correlation OTDR (CC-OTDR) with respect to the spatial and amplitude resolution.
The use of optical fiber as sensor as well as transmission medium for sensing data is discussed, enabling the use of optically active sensors without power supply at distances of tens of kilometers. Depending on the interrogation system, a spatial resolution of less than a millimeter can be achieved. The basic sensing principle is optical time-domain reflectometry (OTDR) with direct detection or coherent detection of the Rayleigh back-scattered or Fresnel reflected signal. Spatial resolution is improved by a cross-correlation between the transmitted sequence and the received signals.
We propose a deep learning approach based on an autoencoder for identifying and localizing fiber faults in passive optical networks. The experimental results show that the proposed method detects faults with 97% accuracy, pinpoints them with an RMSE of 0.18 m and outperforms conventional techniques.
Secure and reliable data communication in optical networks is critical for high-speed Internet. However, optical fibers, serving as the data transmission medium providing connectivity to billons of users worldwide, are prone to a variety of anomalies resulting from hard failures (e.g., fiber cuts) and malicious physical attacks (e.g., optical eavesdropping (fiber tapping)) etc. Such anomalies may cause network disruption and thereby inducing huge financial and data losses, or compromise the confidentiality of optical networks by gaining unauthorized access to the carried data, or gradually degrade the network operations. Therefore, it is highly required to implement efficient anomaly detection, diagnosis, and localization schemes for enhancing the availability and reliability of optical networks. In this paper, we propose a data driven approach to accurately and quickly detect, diagnose, and localize fiber anomalies including fiber cuts, and optical eavesdropping attacks. The proposed method combines an autoencoder-based anomaly detection and an attention-based bidirectional gated recurrent unit algorithm, whereby the former is used for fault detection and the latter is adopted for fault diagnosis and localization once an anomaly is detected by the autoencoder. We verify the efficiency of our proposed approach by experiments under various anomaly scenarios using real operational data. The experimental results demonstrate that: (i) the autoencoder detects any fiber fault or anomaly with an F1 score of 96.86%; and (ii) the attention-based bidirectional gated recurrent unit algorithm identifies the the detected anomalies with an average accuracy of 98.2%, and localizes the faults with an average root mean square error of 0.19 m.
The temperature dependence of the latency of an optical signal transmitted over an optical fiber was investigated by means of a correlation OTDR. While the bare fiber showed a linear latency increase over temperature, the jumper cable inside a jacket with tight buffer as inner jacket showed an increased elongation effect, especially in the range of lower tempera-tures. This could be attributed to the tight buffer. For future latency sensitive applications in the area of 5G networks these effects have to be taken into account.
A correlation optical time-domain reflectometry (COTDR) method is presented, which measures the propagation delay with an accuracy of a few picoseconds. This accuracy is achieved using a test signal data rate of 10 Gbit/s and employing cross-correlation and pulse fitting techniques. In this paper we introduce and evaluate the basic signal processing steps, investigate the measurement accuracy, and discuss applications for monitoring link delay and chromatic dispersion of long fiber spans as well as temperature sensing applications.
Using a Correlation-OTDR, we characterized the temperature-induced group delay variations of two nested antiresonant nodeless hollow core fibers. The temperature sensitivity of both is substantially less than for SSMF with some dependency on coating type.