Abb Schweiz Ag

Abb Research Ltd.

Other

Hitachi Energy Ltd

Hitachi Energy Switzerland Ag

Abb Power Grids Switzerland Ag

Karen J Smiley

Shakeel Mahamood Mahate

Chihhung Hou

Mithun P Acharya

Paul F Wood

Mirrasoul Mousavi

David Neil Cox

Karl Eric Harper

Steven Thomas Zyglowicz

Thomas Edwin Long

Steven W Hudnut

Randall R Schrieber

Pankeshkumar Gopalbhai Patel

Frank Mueller

Hang Xu

Apparatuses, methods, systems, and techniques for detecting and effecting countermeasures against cyber-attacks on networked electrical power system (NEPS) devices include a trusted cyber-attack detection (TCAD) component including pre-trained cyber-attack detection logic which receives a first input indicating a physical parameter of a NEPS device and a second input indicating a computational state of a computer system of the NEPS device, determines an attack metric in response to the plurality of inputs. The attack metric can indicate whether the NEPS device is in the process of being attacked or whether the NEPS device has been successfully attacked and has been compromised.

Cyber-attack detection for networked electrical power system devices

Technologies for solar power system performance model tuning are disclosed. In at least one illustrative embodiment, a method of tuning a system performance model for a power plant may comprise estimating an expected output of an inverter of the power plant using the system performance model, obtaining a measured output of the inverter, determining whether a difference between the expected and measured inverter outputs is within a predefined range, and tuning the system performance model using the difference in response to determining that the difference is within the predefined range. The power plant may further comprise at least one solar panel array, and the inverter may be electrically coupled to the at least one solar panel array.

Technologies for solar power system performance model tuning

A method of operating a computer device includes obtaining measurements of one or more conditions of a power grid component associated with the computer device. The computer device forecasts a future state of the one or more conditions of the power grid component associated with the computer device. The computer device communicates with other computer devices associated with other power grid components to negotiate a behavior of the power grid component associated with the computer device using the forecast.

Technologies for optimizing power grids through decentralized forecasting

Among other things, one or more techniques and/or systems are provided for updating a model for generating a health profile of an industrial asset based upon data pertaining to the industrial asset. The health profile comprises a maintenance plan(s), which respectively comprise one or more recommended maintenance actions to be performed with respect to the industrial asset during a prediction period. The model may be periodically and/or intermittently updated based upon a comparison between the recommended maintenance actions and actual events of the industrial asset during the prediction period. Moreover, in some embodiments, different models may be selected for generating future health profiles of the industrial asset based upon a comparison between the recommended maintenance actions and actual events of the industrial asset during the prediction period.

Industrial asset health model update

Unique systems, methods, techniques and apparatuses for ranking and applying industrial analysis search results are disclosed. One exemplary embodiment is a computer implemented method comprising receiving a request to rank potential combinations of the data set and the plurality of data analysis tools; tagging the plurality of data analysis tools with one or more metadata tags selected from a plurality of metadata tags; tagging the data set with one or more metadata tags selected from the plurality of metadata tags; scoring a plurality of potential combinations of the data analysis tool and the plurality of data sets according to correspondence between the metadata tags tagged to the data analysis tool and the metadata tags tagged to each of the plurality of data sets; and outputting a user perceptible ranking of the plurality of potential combinations indicating the scoring.

Search engine for industrial analysis development toolset

An industrial asset management system includes a data acquisition system configured to receive asset data associated with at least one industrial asset and to modify the data acquisition system to enable the continued receipt of asset data associated with the at least one industrial asset in response to a detection of an internal change at the data acquisition system by the data acquisition system and a data processing system communicatively coupled to the data acquisition system and configured to process the asset data received from the data acquisition system and to modify the data processing system for the continued processing of the asset data in response to a detection by the data processing system of an internal change at the data processing system or the data acquisition system.

Industrial asset management systems and methods thereof

Among other things, one or more techniques and/or systems are provided for developing a criticality profile of an industrial asset. The criticality profile describes the importance of the industrial asset to a system in terms of one or more criticality metrics and/or one or more confidence profiles. Such metrics may include an operational metric indicative of the operation impact of the industrial asset on a system if the industrial asset remains unchanged or enters a degraded or improved state, a restoration metric indicative of a complexity of restoring the industrial asset to an operational state from the unchanged or degraded state and/or complexity of improving the industrial asset to an improved state, and/or an interdependency metric indicative of a relationship between the industrial asset and one or more other industrial assets and/or between the industrial asset and one or more structures in an environment associated with the industrial asset.

Criticality profile for industrial asset

Among other things, one or more techniques and/or systems are provided for generating a health profile of an industrial asset based upon data pertaining to such an industrial asset. The health profile describes an expected condition of the industrial asset during a prediction period, a predicted cause of the expected condition, and/or a predicted impact of the expected condition. In some embodiments, the health profile is generated using a model that is configured to be periodically and/or intermittently updated. Further, in some embodiments, a diagnostic profile may be generated describing diagnostic actions that may be taken to improve predictions included within a health profile and/or to improve a confidence in one or more of those predictions.

Among other things, one or more techniques and/or systems are provided for identifying event images captured during an event associated with power equipment, such as a maintenance action. An entity, such as a maintenance technician, is equipped with an image recorder and an audio recorder. In some embodiments, the image recorder and/or audio recorder are wearable, such as mounted to eyewear and/or headwear worn by the entity. Audio that is recorded by the audio recorder is processed to identify events (e.g., key actions in a maintenance procedure). Based upon the identification of an event from the audio, event images (e.g., images captured temporally proximate to when the event was identified in the audio) associated with the event are identified and stored in a library. In some embodiments, one or more of such event images are later displayed to entities via a heads-up display, for example.

Recording and providing for display images of events associated with power equipment

Among other things, one or more techniques and/or systems are provided for developing a health profile of an industrial asset based upon data pertaining to such an industrial asset. At least some of the data is transformed into primary state indicators, respectively representative of the status or condition of an aspect of the industrial asset. Using the primary state indicators, one or more events that are likely to occur to the industrial asset are identified and a health profile is developed based upon such events. The health profile may describe maintenance actions that will reduce a likelihood of an event(s) occurring, may describe a business impact on an entity associated with the industrial asset if an event(s) occurs, and/or may describe a performance impact on the industrial asset if an event(s) occurs, for example.

Industrial asset health profile

Among other things, one or more techniques and/or systems are provided for developing a timeline chronicling events pertaining to an industrial asset. Data is received from a plurality of assets, processed (e.g., to reduce duplicative and/or redundant data), and organized chronologically for presentation in a timeline. The data is further grouped and/or prioritized to display some portions of the data more prominently relative to other portions of the data in the timeline (e.g., which may be hidden). Grouping rules and/or prioritization rules for grouping and/or prioritizing the data may be a function of user interaction with the timeline and/or a function of a machine learning algorithm which may be configured to identify patterns in how users interact with the timeline based upon, among other things, a role the user plays relative to the industrial asset and/or an operating state of the industrial asset.

Industrial asset event chronology

Among other things, one or more techniques and/or systems are provided for facilitating development, by a user, of a model describing a condition of an industrial asset. An output parameter of the model can be defined within a model development environment. The output parameter describes a condition of the industrial asset and can be defined using one or more variables. During deployment of the model within a deployment environment, respective variables of the model can be mapped to a data store where data associated with the variable is located. In this way, during development, a user can specify variables to be used within the model without specifying where to fetch and/or push data associated with the variable, for example. Further, the model can be executed within the deployment environment to assess the condition for a plurality of industrial assets.

Model development environment for assisting user in developing model describing condition of industrial asset

A preferred method for evaluating a transformer design using data representing test results from a plurality of transformers and stored in a data base includes comparing the data representing test results to predetermined criteria for the test results to determine whether the test results satisfy the predetermined criteria. The preferred method also includes counting the number of the test results that do not satisfy the predetermined criteria, and generating an indication that a predetermined quantity of the test results do not satisfy the predetermined criteria if at least the predetermined quantity of the test results do not satisfy the predetermined criteria.

Method for evaluating a transformer design

A method for transformer testing includes receiving a failing test result of a transformer, the test result being determined from a test taken during transformer manufacture, determining, via a knowledge-based system, a predicted root cause of the failure based on the test result and a knowledge base of transformer information, and determining, via the knowledge-based system, a suggested course of action for the failure based on the test result and the knowledge base of transformer information.

Growing community of inventors

Raleigh, NC, United States of America

Karen J Smiley