Systems and methods for performing the dynamic anomaly localization of utility pole aerial/suspended/supported wires/cables by distributed fiber optic sensing. In sharp contrast to the prior art, our inventive systems and methods according to aspects of the present disclosure advantageously identify a “location region” on a utility pole supporting an affected wire/cable, thereby permitting the identification and reporting of service personnel that are uniquely responsible for responding to such anomalous condition(s).

A variable-frequency light source is configured to emit a light beam and modulate a frequency of the light beam. A fiber optic cable is attached to the variable frequency light source. The fiber optic cable is configured to receive the light beam at an inlet and pass the light beam to an exit. Multiple optical detectors are attached to the fiber optic cable. Each of the optical detectors is configured to detect a specified frequency of light that is backscattered through the fiber optic cable. An actuation mechanism is attached to the fiber optic cable. The actuation mechanism is configured to deform the fiber optic cable in response to a stimulus.

A detection system according to the present disclosure includes an optical fiber (10) configured to detect environment information, an acquisition unit (21) configured to acquire the environment information included in an optical signal received from the optical fiber (10), and a detection unit (22) configured to detect an event in the vicinity of the optical fiber (10) on the basis of a first environment pattern based on environment information acquired from an optical signal associated to a first period and a second environment pattern based on environment information acquired from an optical signal associated to a second period.

Disclosed is a signal processing method for a distributed acoustic sensing system (DAS), where a scattered signal that was scattered at a scattering location along an optical path is received and interfered with a local oscillator signal to generate a first carrier signal that is modulated by a phase difference between the local oscillator signal and the scattered signal. The first carrier signal is then digitally processed in order to generate a second carrier signal that is modulated by a spatial differential of the phase difference. The spatial differential of the phase difference is directly related to the strain (or acoustic environment) of the optical path at the scattering location, and so enables the strain at the scattering location to be estimated.

The high sensitivity provided by an enhanced DAS system comprising a DAS interrogator and a high reflectivity fiber allows for the deployment of such a high reflectivity fiber as part of a wireline intervention cable which can be temporarily lowered into a well, thus avoiding the need to permanently cement such a high reflectivity optical fiber cable into the well. Instead, such a wireline cable incorporating the high reflectivity optical fiber has been found to be sensitive enough to detect micro-seismic activity and low frequency strain with many more measurement points and channels than conventional wireline deployed geophones and tiltmeters. Additionally, the cable requires no clamping and can be easily and quickly removed from one well and placed in another well.

A method for underground cable localization by fast time series template matching and distributed fiber optic sensing (DFOS) includes: providing the DFOS system including a length of optical sensor fiber; a DFOS interrogator in optical communication with the optical sensor fiber, said DFOS interrogator configured to generate optical pulses, introduce the generated pulses into the length of optical sensor fiber, and receive backscattered signals from the length of the optical sensor fiber; and an intelligent analyzer configured to analyze DFOS data received by the DFOS interrogator and determine from the backscattered signals, vibrational activity occurring at locations along the length of the optical sensor fiber; deploying a programmable vibration generator to a field location proximate to the length of optical sensor fiber; transmitting to the programmable vibration generator a unique vibration pattern to be generated by the vibration generator; and operating the programmable vibration generator to generate the unique vibration pattern transmitted; and operating the DFOS system and collecting/analyzing the determined vibrational activity to further determine vibrational activity indicative of the unique vibration pattern generated by the vibration generator.

A manhole position identification method of the present invention includes: measuring, from an end of an optical fiber, a temporal variation in scattering light from the optical fiber when an impact blow is applied to a cover of a manhole located on a path of the optical fiber, so as to obtain temporal variations in a scattering light intensity distribution in a longitudinal direction of the optical fiber; determining an occurrence of vibration due to the impact blow based on the temporal variations at positions in the scattering light intensity distribution, so as to identify an impact blow position on the optical fiber; and associating the impact blow position on the optical fiber with a map position of the manhole whose cover has received the impact blow, so as to identify a position of the manhole expressed in terms of optical fiber length from the end.

Systems, methods, and structures for efficiently identifying individual fibers located in a deployed cable that advantageously reduces laborious field efforts while reducing service outage time. The systems and methods locate a targeted fiber in a cable (“Cable ID”) and then identify the targeted fiber (“Fiber ID”) by detecting DFOS signal attentions—without cutting the optical fiber. Two distinct determinations may be made namely, Cable ID and Fiber ID. DFOS operation detects vibration signals occurring along a sensor fiber. As implemented, Cable ID is an interactive-machine learning-based algorithm that automatically locates cable position along a sensor fiber route. Fiber ID detects a signal attenuation by bending a group of fibers with bifurcation to pinpoint a targeted individual fiber within a fiber cable.

A system for sensing microbends and micro-deformations in three-dimensional space is based upon a distributed length optical fiber formed to include a group of offset cores disposed in a spiral configuration along the length of the fiber, each core including a fiber Bragg grating that exhibits the same Bragg wavelength. A micro-scale local deformation of the multicore fiber produces a local shift in the Bragg wavelength, where the use of multiple cores allows for a complete micro-scale modeling of the local deformation. Sequential probing of each core allows for optical frequency domain reflectometry (OFDR) allows for reconstruction of a given three-dimensional shape, delineating location and size of various microbends and micro-deformations.

A method of providing a hybrid distributed fiber optic sensing system (DFOS) that extends an existing fiber optic telecommunications network thereby providing that existing fiber optic telecommunications network with DFOS capabilities. The method provides a length of fiber optic cable, wherein said fiber optic cable conveys communications traffic; provides a DFOS interrogator system in optical communication with the communications fiber optic cable; extends the length of communications fiber optic cable with first and second lengths of fiber optic sensory cable, and operates the DFOS interrogator system such that first sensory data is generated in the first length of fiber optic sensory cable and second sensory data is generated in the second length of fiber optic sensory cable and conveyed to the DFOS interrogator system via the communications fiber optic cable, wherein the first type of sensory data and the second type of sensory data is a type selected from the group consisting of acoustic data, temperature data, and vibration data and the first type of sensory data is not the same type as the second type of sensory data.