Palo Alto Research Center Inc.

Xerox Corporation

Consolidated Edison Company of New York, Inc.

General Electric Company

Massachusetts Institute of Technology

Metis Design Corporation

Other

Panasonic Corporation

Panasonic Holdings Corporation

Palo Alto Research Company Incorporated

Ajay Raghavan

Peter Kiesel

Bhaskar Saha

Todd Karin

Lars Wilko Sommer

Saroj Kumar Sahu

Qiushu Chen

Hong Yu

Alexander Lochbaum

Tobias Staudt

Anurag Ganguli

Kyle Arakaki

Deokwoo Jung

Saman Mostafavi

Jin Yan

Ryan A Rossi

Robert Roy Price

Juan Liu

Chang-Jun Bae

Jane Shin

Bradley Kittrell

Serena Lee

Julian Schwartz

Jungho Park

Hong Heather Yu

Tetsuyoshi Ogura

Brian Lee Wardle

Alex N Hegyi

Seth S Kessler

Hoe Jin Hah

Mark Teepe

Akira Minegishi

Geun-Chang Chung

Yosuke Tajika

Malcolm Graham Smith, Jr

Mohamed Alamgir

Fangzhou Cheng

Robert T Stinson, Iv

Bokkyu Choi

Gyu-Ok Hwang

Eric J Shrader

Daniel Davies

Yukinori Sasaki

Andreas Schuh

Spenser Anderson

Colin Campbell

Jingxiao Liu

Tu Hoang

Ozan Celik

Turki Haj Mohamad

Malcolm G Smith Jr

Robert T Stinson Iv

Kyle Arkaki

A method comprises receiving streaming data in the form of peak readings developed from spectrum data produced by multiplexed optical sensors of one or more optical fibers. The streaming data comprises wavelength and intensity data associated with the sensors. The method comprises determining, for a particular fiber, whether a number of the peak readings is the same as, or differs from, an expected number, N, where N corresponds to a total number of sensors of the particular fiber. The method also comprises correcting anomalous streaming data in response to determining that the number of the peak readings differs from the expected number, N. The method further comprises storing nominal wavelength and intensity streaming data and the corrected wavelength and intensity streaming data in a structured data table indexed by fiber ID and sensor ID.

System and method for processing signals acquired from multiplexed optical sensors

A sensor network comprises at least one lateral optical fiber and at least one longitudinal optical fiber. The lateral fiber comprises optical sensors coupled to a pavement in a transverse orientation relative to a direction of vehicle travel along the pavement. The longitudinal fiber comprises optical sensors coupled to the pavement in a longitudinal orientation relative to the direction of vehicle travel. The optical sensors are configured to produce wavelength shift signals comprising one or more lateral strain signals associated with the lateral fiber and one or more tangential strain signals associated with the longitudinal fiber. A processor is operatively coupled to the sensor network and configured to determine a weight of vehicles moving along the pavement based on the lateral and tangential strain signals. A transmitter is operatively coupled to the processor and configured to transmit the weight of vehicles to a predetermined location.

Traffic monitoring using optical sensors

A monitoring system for a power grid includes one or more power transformer monitors. Each power transformer monitor includes a plurality of optical sensors disposed on one or more optical fibers that sense parameters of the power transformer. Each optical sensor is configured to sense a power transformer parameter that is different from a power transformer parameter sensed by at least one other sensor of the plurality of optical sensors. An optical coupler spatially disperses optical signals from the optical sensors according to wavelength. A detector unit converts optical signals of the optical sensors to electrical signals representative of the sensed power transformer parameters.

Optical monitoring for power grid systems

A system includes a sensor network comprising at least two optical fibers coupled to a pavement. Each optical fiber includes one or more optical sensors installed a predetermined distance from one or more adjacent optical fibers. The one or more optical sensors are configured to produce a wavelength shift signal. A processor is configured to determine one or both of one or more attributes of one or more objects travelling on the pavement and a traffic condition of the pavement based on the wavelength shift signal. A transmitter is configured to transmit the one or more attributes to a predetermined location.

A partial discharge (PD) transducer that includes a PD sensor configured to sense a PD event of an electrical system. At least one light emitting device (LED) is arranged in series with the PD sensor. The LED is configured to receive the electrical sensor signal from the PD sensor and to generate a light signal in response to the electrical sensor signal.

Partial discharge transducer

One or more spacers for installing an optical cable are disposed in a trench that extends along an axis. The optical cable includes one or more optical sensors. Each spacer includes a base configured to rest in a bottom of the trench. A first arm extends from the base. The first arm is adjacent to a first wall of the trench. An opposing second arm extends from the base. The second arm is adjacent to an opposing second wall of the trench. The optical cable is configured to extend along the axis.

Installation of optical sensors for use in traffic monitoring

A sensor system includes a sensor network comprising at least one optical fiber having one or more optical sensors. At least one of the optical sensors is arranged to sense vibration of an electrical device and to produce a time variation in light output in response to the vibration. A detector generates an electrical time domain signal in response to the time variation in light output. An analyzer acquires a snapshot frequency component signal which comprises one or more time varying signals of frequency components of the time domain signal over a data acquisition time period. The analyzer detects a condition of the electrical device based on the snapshot frequency component signal.

Fiber optic sensing system for grid-based assets

A set of load responses of an asset for a sample of traffic loading events caused by objects of unknown weight is measured. At least one statistical parameter is determined from the set of load responses. A corresponding statistical parameter of known object weights loading the asset is determined. An object weight is assigned to a load response of the set of load responses based on correlation of the extracted statistical parameter to the corresponding statistical parameter.

Methods and system for determining a control load using statistical analysis

A monitoring system includes an array of optical sensors disposed within a transformer tank. Each optical sensor is configured to have an optical output that changes in response to a temperature within the transformer tank. An analyzer is coupled to the array of optical sensors. The analyzer is configured to determine a sensed temperature distribution based on the sensed temperature. The sensed temperature distribution is compared to an expected distribution. Exterior contamination of the transformer tank is detected based on the comparison.

Optical monitoring to detect contamination of power grid components

A corrosion monitoring system includes one or more objects coupled to respective portions of a transformer tank. The one or more objects are configured to corrode before the respective portions of the transformer tank. At least one optical sensor is coupled to each of the objects. The at least one optical sensor has an optical output that changes in response to strain of the object. An analyzer is coupled to the at least one optical sensor. The analyzer is configured to perform one or more of detecting and predicting corrosion of the transformer tank based on the output of the at least one optical sensor.

Optical monitoring to detect corrosion of power grid components

An approach to detecting partial discharge events involves retrofitting an electrical system to include a capacitive sensor configured to capacitively sense partial discharge events of a component of the electrical system. The capacitive sensor has a first electrical conductor that forms a first terminal of the capacitive sensor, a second electrical conductor that forms a second terminal of the capacitive sensor, and a dielectric that separates the first electrical conductor and the second electrical conductor. The capacitive sensor generates an electrical sensor signal at an output of the capacitive sensor in response to the partial discharge event. The electrical sensor signal is converted to an optical signal and the optical signal is processed to detect an occurrence of the partial discharge event.

Partial discharge sensor

A system and method are provided for determining a causal inference in a manufacturing process. During operation, the system can receive data associated with a processing system which includes a set of interconnected machines and an associated set of processes. The system can generate, based on the data, a graph indicating flows of outputs between the machines as part of the processes. The system can determine, based on a set of variables, one or more candidate clusters in the graph. The system can perform, based on one or more variables of interest, root cause analysis on the one or more candidate clusters by: applying an additive noise model to prune the one or more candidate clusters from the graph; and determining, based on the pruned graph, a candidate pathway likely to cause an issue in at least one process, thereby facilitating improved efficiency in the processing system.

System and method for casual inference in manufacturing process

One embodiment can provide a system for detecting anomaly for high-dimensional sensor data associated with one or more machines. During operation, the system can obtain sensor data from a set of sensor associated with one or machines, apply data exploration techniques on the sensor data to automatically process sensor data to identify a subset of feature sensors from the available set of feature sensors, apply an unsupervised machine-learning technique to the identified subset of feature sensors and the target sensor to learn a set of pair-wise univariate models, and determine whether and how an anomaly occurs in the operation of the one or more machines based on the set of pair-wise univariate models.

Method and system for unsupervised anomaly detection and accountability with majority voting for high-dimensional sensor data

A system includes a first optical sensor sensitive to both a parameter of interest, Parameter1, and at least one confounding parameter, Parameter2 and a second optical sensor sensitive only to the confounding parameter. Measurement circuitry measures Min response to light scattered by the first optical sensor, where M=value of Parameter1+K*value of Parameter2. The measurement circuitry also measures Min response to light scattered by the second optical sensor, where M=value of Parameter2. Compensation circuitry determines a compensation factor, K, for the confounding parameter based on measurements of Mand Mtaken over multiple load/unload cycles or over one or more thermal cycles. The compensation factor is used to determine the parameter of interest.

Method and system to separate optically measured coupled parameters

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Mountain View, CA, United States of America

Ajay Raghavan