Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: An illustrative embodiment disclosed herein is an apparatus including a processor and a memory. In some embodiments, the memory includes programmed instructions that, when executed by the processor, cause the apparatus to store a first object and a second object in a first region based on the first object and the second object having a first policy. In some embodiments, the memory includes programmed instructions that, when executed by the processor, cause the apparatus to store a third object in a second region based on the third object having a second policy. In some embodiments, a virtual disk includes the first region and the second region.

Abstract: One embodiment provides a system for facilitating anomaly detection. During operation, the system determines, by a computing device, a set of training instances, wherein a training instance represents a single class of data within a predefined range. The system computes a similarity score for each testing instance in a set of testing instances, wherein the similarity score is based on a similarity function which takes as input a respective testing instance and the set of training instances. The system determines a boundary threshold based on an ordering of the similarity score for each testing instance. The system classifies a first testing instance as an anomaly responsive to determining that the first testing instance falls outside the boundary threshold, thereby enhancing data mining and outlier detection in the single class of data using unlabeled training instances.

Abstract: A plurality of strain values are received from a plurality of sensors permanently attached to an asset configured to carry a load. A strain profile of the asset is monitored based on the plurality of strain values. Additional information about the asset is received. A load rating factor is monitored based on the additional information and the strain profile. An equivalent accumulated damage factor is monitored based on the load rating factor. A remaining life prediction for the asset is calculated based on the strain profile and the equivalent accumulated damage factor.

Abstract: 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.

Abstract: A system is provided for determining a manufacturing network topology and fault propagation information. During operation, the system stores data associated with a processing system which includes machines and associated processes, wherein the data includes timestamp information, machine status information, and product-batch information. The system determines, based on the data, a network topology which corresponds to the processing system, wherein the network topology indicates flows of outputs between the machines as part of the processes. The system determines utilization information of a plurality of the machines of the processing system. The system displays one or more of the flows of outputs based on the utilization information, thereby facilitating diagnosis of the processing system.

Abstract: A system is provided for determining causes of faults in a manufacturing system. The system stores data associated with a processing system which includes machines and associated processes, wherein the data includes timestamp information, machine status information, and product-batch information. The system determines, based on the data, a topology of the processing system, wherein the topology indicates flows of outputs between the machines as part of the processes. The system determines information of machine faults in association with the topology. The system generates, based on the machine-fault information, one or more fault parameters which indicates frequency and severity of a respective fault. The system constructs, based on the topology and the machine-fault information, a system model which includes the one or more fault parameters, thereby facilitating diagnosis of the processing system.

Abstract: An illustrative embodiment disclosed herein is an apparatus including a processor having programmed instructions to map a plurality of objects to a region and map the region to a plurality of vdisks. The plurality of objects are stored in the plurality of vdisks. The processor has programmed instructions to, responsive to mapping the plurality of objects to the region, identify a policy associated with the region. The policy specifies a policy action in response to satisfying a predetermined condition. The processor has programmed instructions to, responsive to satisfying the predetermined condition, access the plurality of vdisks and perform the policy action on the plurality of objects.

Abstract: A sensor system includes an optical fiber. A set of wavelength shift sensors are inscribed on the optical fiber. The set includes at least one first wavelength shift sensor configured to reflect a first wavelength band of input light as a first optical output signal. The first wavelength shift sensor has a first value of an optical characteristic that modifies intensity of the first optical output signal. At least one second wavelength shift sensor is configured to reflect a second wavelength band of input light as a second optical output signal. The second wavelength shift sensor has a second value of the optical characteristic that modifies intensity of the second optical output signal, wherein the second value is different from the first value.

Abstract: 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.

Abstract: One embodiment provides a system for facilitating anomaly detection. During operation, the system determines, by a computing device, a set of testing data which includes a plurality of data points, wherein the set includes a data series for a first variable and one or more second variables, and wherein the one or more second variables are dependent on the first variable. The system divides the set of testing data into a number of groups based on a type of the data series. The system determines an inter-quartile range for a respective group. The system classifies a first testing data point in the respective group as an anomaly based on the inter-quartile range for the respective group, thereby enhancing data mining and outlier detection for the data series for multiple variables.

Abstract: 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.

Abstract: One embodiment can provide a system for estimating a useful life of a load-bearing structure at least partly made of a conductive material. During operation, the system establishes a physics-based damage model for the load-bearing structure, performs a dynamic measurement to obtain at least one conductive property of the load-bearing structure as a function of fatigue cycles, estimates parameters of the physics-based damage model based on the measured conductive property, and estimates the useful life of the load-bearing structure based on the estimated parameters of the physics-based damage model.

Abstract: One embodiment can provide a system for detecting faults in a machine. During operation, the system can obtain a dynamic signal associated with the machine, apply one or more signal-processing techniques to the dynamic signal to obtain frequency, amplitude, and/or time-frequency information associated with the dynamic signal, extract motion-insensitive features from the obtained frequency, amplitude, and/or time-frequency information associated with the dynamic signal, and determine whether a fault occurs in the machine based on the extracted features.

Abstract: 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.

Abstract: A partial discharge (PD) detection system includes a PD sensor configured to sense a PD event of an electrical system and to generate a sensor signal in response to the PD event. An envelope generator is coupled to receive the sensor signal from the PD sensor. The envelope generator extracts an envelope signal from the sensor signal. A digitizer is configured to convert the envelope signal to a digital representation of the PD event.

Abstract: One embodiment provides a system for facilitating anomaly detection and characterization. During operation, the system determines, by a computing device, a first set of testing data which includes a plurality of data points, wherein the first set includes a data series for a first variable and one or more second variables. The system identifies anomalies by dividing the first set into a number of groups and performing an inter-quartile range analysis on data in each respective group. The system obtains, from the first set, a second set of testing data which includes a data series from a recent time period occurring before a current time, and which further includes a first data point from the identified anomalies. The system classifies the first data point as a first type of anomaly based on whether a magnitude of a derivative of the second set is greater than a first predetermined threshold.