Jian Fang NEC Labs America

Jian Fang

Researcher

Optical Networking & Sensing

Posts

Field Trials of Vibration Detection, Localization and Classification over Deployed Telecom Fiber Cables

We review sensing fusion results of integrating fiber sensing with video for machine-learning-based localization and classification of impulsive acoustic event detection. Classification accuracy >97% was achieved on aerial coils, and >99% using fiber-based signal enhancers.

Template Matching Method with Distributed Acoustic Sensing Data and Simulation Data

We propose a new method to detect acoustic signals by matching distributed acoustic sensing data with simulation. In the simulation of the dynamic strain on an optical fiber, the optical fiber layouts and the gauge length are properly incorporated. We apply the proposed method to the acoustic-source localization and demonstrate the method localizes the source accurately even under the layouts which include the straight optical fiber for the sensing points with the large gauge-length settings.

Field Tests of Impulsive Acoustic Event Detection, Localization, and Classification Over Telecom Fiber Networks

We report distributed-fiber-optic-sensing results on impulsive acoustic events localization/classification over telecom networks. A deep-learning-based model was trained to classify starter-gun and fireworks signatures with high accuracy of > 99% using fiber-based-signal-enhancer and >97% using aerial coils.

Evolution of Fiber Infrastructure – From Data Transmission to Network Sensing

We review multiple use cases over deployed networks including co-existing sensing/data transmission, cable cut prevention and perimeter intrusion detection to realize telecom infrastructure can be sensing backbones instead of the sole function of data transmission.

Remote Drone Detection and Localization with Optical Fiber Microphones and Distributed Acoustic Sensing

We demonstrate the first fiber-optic drone detection method with ultra-highly sensitive optical microphones and distributed acoustic sensor. Accurate drone localization has been achieved through acoustic field mapping and data fusion.

Perimeter Intrusion Detection with Rayleigh Enhanced Fiber Using Telecom Cables as Sensing Backhaul

We report field test results of facility perimeter intrusion detection with distributed-fiber-sensing technology and backscattering-enhanced-fiber by using deployed telecom fiber cables as sensing backhaul. Various intrusive activities, such as walking/jumping at >100ft distance, are detected.

Distributed Fiber Sensor Network Using Telecom Cables as Sensing Media: Technology Advancements and Applications

Distributed fiber optic sensing (DFOS) is a rapidly evolving field that allows the existing optical fiber infrastructure for telecommunications to be reused for wide-area sensing. Using the backscattering mechanisms of glass—which includes Rayleigh, Brillouin, and Raman backscatter—it is possible to realize distributed vibration and temperature sensors with good sensitivity at every fiber position, and spatial resolution is determined by the bandwidth of the interrogation signal. In this paper, we will review the main technologies in currently deployed DFOS. We review the digital signal processing operations that are performed to extract the sensing parameters of interest. We report recent distributed vibration sensing, distributed acoustic sensing, and distributed temperature sensing field trial results over an existing network with reconfigurable add/drop multiplexers carrying live telecom traffic, showing that the network is capable of simultaneous traffic and temperature monitoring. We report Brillouin optical time-domain reflectometry experimental results for monitoring static strain on aerial fiber cables suspended on utility poles. Finally, we demonstrate an example of network modification to make passive optical networks compatible with DFOS by adding reflective semiconductor optical amplifiers at optical network units.

Bipolar Cyclic Linear Coding for Brillouin Optical Time Domain Analysis

We demonstrate, for the first time, that cyclic linear pulse coding can be bipolar for BOTDA sensors, breaking the unipolar limitation of linear coding techniques and elevating the coding gain for a given code length.

Multi-parameter distributed fiber sensing with higherorder optical and acoustic modes

We propose a novel multi-parameter sensing technique based on a Brillouin optical time domain reflectometry in the elliptical-core few-mode fiber, using higher-order optical and acoustic modes. Multiple Brillouin peaks are observed for the backscattering of both the LP01 mode and LP11 mode. We characterize the temperature and strain coefficients for various optical–acoustic mode pairs. By selecting the proper combination of modes pairs, the performance of multi-parameter sensing can be optimized. Distributed sensing of temperature and strain is demonstrated over a 0.5-km elliptical-core few-mode fiber, with the discriminative uncertainty of 0.28°C and 5.81 ?? for temperature and strain, respectively.

Distributed Temperature and Strain Sensing Using Brillouin Optical Time Domain Reflectometry Over a Few Mode Elliptical Core Optical Fiber

We propose a single-ended Brillouin-based sensor in elliptical-core few-mode optical fiber for multi-parameter measurement using spontaneous Brillouin scattering. Distributed sensing of temperature and strain is demonstrated over 0.5 km elliptical-core few-mode fiber.