Linearized Bregman Iterations for Automatic Optical Fiber Fault Analysis

• Published in: IEEE transactions on instrumentation and measurement Vol. 68; no. 10; pp. 3699 - 3711
• Main Authors: Lunglmayr, Michael, Amaral, Gustavo C.
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.10.2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Automation; Comparative studies; Computer simulation; Data analysis; Fault detection; Fault location; Linearization; Optical communication; optical fiber measurements; Optical fibers; Optical network units; Optical pulses; Optical sensors; Optical signal processing; optical time-domain reflectometry (OTDR); Optical variables measurement; Parameter estimation; Photons; Reflectometry; Sensitivity analysis; Signal processing; Signal processing algorithms; Subsystems
• ISSN: 0018-9456; 1557-9662
• DOI: 10.1109/TIM.2018.2882258

Supervision of the physical layer of optical networks is an extremely relevant subject. To detect fiber faults, single-ended solutions, such as the optical time-domain reflectometry (OTDR), allow for precise measurements of fault profiles. Combining the OTDR with a signal processing approach for high-dimensional sparse parameter estimation allows for automated and reliable results in reduced time. In this paper, a measurement system composed of a photon-counting OTDR data acquisition unit and a processing unit based on a linearized Bregman iterations' algorithm for automatic fault finding is proposed. An in-depth comparative study of the proposed algorithm's fault-finding prowess in the presence of noise is presented. Characteristics, such as sensitivity, specificity, processing time, and complexity, are analyzed in simulated environments. Real-life measurements that are conducted using the photon-counting OTDR subsystem for data acquisition and the linearized Bregman-based processing unit for automated data analysis demonstrated accurate results. It is concluded that the proposed measurement system is particularly well-suited to the task of fault finding. The natural characteristic of the algorithm fosters embedding the solution in digital hardware, allowing for reduced costs and processing time.