Abstract:
An optical network includes a multidimensional coder and modulator for handling multiple-in-multiple-out MIMO spatial lightpath properties and content of any specific supercarrier, a spatial mode multiplexer responsive to orthogonal frequency division multiplexing OFDM transmissions and the multidimensional coder, a spatial-spectral routing node coupled over a fiber link to the spatial mode multiplexer for performing switching granularity by a spatial mode reconnection, a multidimensional decoder and demodulator; and a spatial mode demultiplexer coupled over a fiber link to the spatial-spectral routing node and responsive to the multidimensional decoder and demodulator.
Abstract:
Systems and methods for a risk mitigation system for electrical power grids. To mitigate risks such as natural destructive forces, collected risk data and EPG data can be fused to obtain fused data. The vulnerability metric and fragility metric of the EPG based on risk profiles generated from the fused data can be predicted with a physics-informed neural network (PINN) trained with the fused data. EPG threat metrics can be developed by integrating the vulnerability metric, fragility metric, and the risk profiles into an integrated score that determines the probability of failure of the EPG caused by natural destructive forces. The present embodiments can perform a corrective action with an automated helper to mitigate the risks to the EPG caused by the natural destructive forces determined from the EPG threat metrics.
Abstract:
A method for time synchronization using distributed fiber optic sensing (DFOS) that employs several trusted time beacons that are attached to the DFOS sensing fiber which in turn is connected to the DFOS interrogator. The beacons transmit their signal via two different mediums, (1) wirelessly to sensor nodes in the coverage area, and (2) through vibrations on fiber to the DFOS/DAS system located at a trusted area such as the central office. Wireless broadcast to nearby sensors includes a timestamp and beacon ID. All the sensors in the field use one of the beacons in their vicinity (the one with the strongest signal) as their time reference and send the data back with the corresponding beacon index.
Abstract:
Aspects of the present disclosure describe distributed fiber optic sensor systems, methods, and structures that advantageously enable/provide for the proper placement/assignment of sensors in the DFOS network to provide for high reliability, fault tolerant operation that survives multiple fiber failures.
Abstract:
Aspects of the present disclosure describe dynamic road traffic noise mapping using DFOS over a telecommunications network that enables mapping of road traffic-induced noise at any observer location. DFOS is used to obtain instant traffic data including vehicle speed, volume, and vehicle types, based on vibration and acoustic signal along the length of a sensing fiber along with location information. A sound pressure level at a point of interest is determined, and traffic data associated with such point is incorporated into a reference noise emission database and a wave propagation theory for total sound pressure level prediction and mapping. Real-time wind speed using DFOS—such as distributed acoustic sensing (DAS)—is obtained to provide sound pressure adjustment due to the wind speed.
Abstract:
Aspects of the present disclosure describe distributed fiber optic sensing systems, methods, and structures that advantageously are employed to determine the location and depth of underground fiber-optic facilities that may be carrying telecommunications traffic.
Abstract:
Aspects of the present disclosure describe distributed fiber optic sensing (DFOS)—distributed acoustic sensing (DAS) based systems, methods, and structures that advantageously enable and/or facilitate the determination of natural frequency(ies) of civil infrastructures.
Abstract:
Methods and systems for training a neural network include generate an image of a mask. A copy of an image is generated from an original set of training data. The copy is altered to add the image of a mask to a face detected within the copy. An augmented set of training data is generated that includes the original set of training data and the altered copy. A neural network model is trained to recognize masked faces using the augmented set of training data.
Abstract:
Aspects of the present disclosure describe systems, methods and structures employing two-stage detection/analysis for distributed vibration sensing (DVS) along an optical fiber in which a first stage provides pre-processed signal data and the second stage—based on the first stage result—only processes locations that have or might have vibrational activity resulting in increased sensitivity and reduced false alarms.
Abstract:
Aspects of the present disclosure describe optical fiber sensing systems, methods and structures disclosing a distributed fiber sensor network constructed on an existing, live network, data carrying, optical fiber telecommunications infrastructure to detect temperatures, acoustic effects, and vehicle traffic—among others. Of particular significance, sensing systems, methods, and structures according to aspects of the present disclosure may advantageously identify specific network locations relative to manholes/handholes and environmental conditions within those manholes/handholes namely, normal, flooded, frozen/iced, etc.