The present invention relates to a power transformer asset management device and a method thereof, the device according to the present invention including: a full cycle database managing full cycle data of a power transformer; a physical performance evaluation unit performing physical performance evaluation that calculates a health index by analyzing and weighting life information, a failure ratio, operation history, and status information of a preventive diagnosis system from the full cycle data; a risk evaluation unit performing risk evaluation by generating a risk matrix using the physical performance evaluation result; an economic evaluation unit performing economic evaluation by evaluating costs over a full cycle of the power transformer; and an asset management unit establishing an investment plan for replacing the power transformer according to a maintenance priority of the power transformer determined using the physical performance evaluation result, the risk evaluation result, and the economic evaluation result.

Methods and systems for assessing, detecting, and responding to malfunctions involving components of autonomous vehicle and/or smart homes are described herein. Autonomous operation features and related components can be assessed using direct or indirect data regarding operation. Such assessment may be performed to determine the condition of components for salvage following a collision or other loss-event. To this end, the information regarding a plurality of components may be received. A component of the plurality of components may be identified for assessment. Assessment may including causing test signals to be sent to the identified component. In response to the test signal, one or more responses may be received. The received response may be compared to an expected response to determine whether the identified component is salvageable.

The unexpected failure of a turbomachine can be costly and dangerous. Processes may collect data from a turbomachine, calculate durations of machine events from the collected data, and apply a model to those machine-event durations to predict future machine-event durations and/or detect trends in the machine-event durations. This predictive output may be utilized to inform downstream functions regarding the health of the turbomachine. For example, a downstream function may utilize the predictive output to detect degradation or a potential future failure in the turbomachine and trigger remedial functions, such as alerts and/or controls, to prevent or mitigate the degradation or failure of the turbomachine.

Methods and systems for communicating between autonomous vehicles are described herein. Such communication may be performed for signaling, collision avoidance, path coordination, and/or autonomous control. A computing device may receive data for the same road segment from autonomous vehicles, including (i) an indication of a location within the road segment, and (ii) an indication of a condition of the road segment. The computing device may generate, from the data for the same road segment, an overall indication of the condition of the road segment, which may include a recommendation to vehicles approaching the road segment. Additionally, the computing device may receive a request from a computing device within a vehicle approaching the road segment to display vehicle data. The overall indication for the road segment may then be displayed on a user interface of the computing device.

Methods and systems for assessing, detecting, and responding to malfunctions involving components of autonomous vehicles and/or smart homes are described herein. Autonomous operation features and related components can be assessed using direct or indirect data regarding operation. Such assessment may be performed to determine the robustness of autonomous systems, including the use of virtual assessment of software components within a simulated environment. To this end, a server may retrieve one or more routines associated with autonomous operation. The server may also generate a set of test data associated with test conditions. The server may also execute an emulator that virtually simulates autonomous environment. The test data may be presented to the routines executing in the emulator to generate output data. The server may then analyze the output data to determine a quality metric.

Methods and systems for assessing, detecting, and responding to malfunctions involving components of autonomous vehicles and/or smart homes are described herein. Autonomous operation features and related components can be assessed using direct or indirect data regarding operation. Such assessment may be performed to determine the robustness of autonomous systems, including the use of virtual assessment of software components within a simulated environment. To this end, a server may retrieve one or more routines associated with autonomous operation. The server may also generate a set of test data associated with test conditions. The server may also execute an emulator that virtually simulates autonomous environment. The test data may be presented to the routines executing in the emulator to generate output data. The server may then analyze the output data to determine a quality metric.

Methods and systems for autonomous and semi-autonomous vehicle control relating to malfunctions are disclosed. Malfunctioning sensors or software of autonomous vehicles may be identified from operating data of the vehicle, and a component maintenance requirement status associated with such malfunctioning component may be generated. Based upon such status, usage restrictions may be enacted to limit operation of the vehicle while the component is malfunctioning. This may include disabling or restricting use of certain autonomous or semi-autonomous features of the vehicle until the component is repaired or replaced. Repair may be accomplished by automatically scheduling repair of the vehicle or installing an updated or uncorrupted version of a software program, in various embodiments.

Methods and systems for autonomous and semi-autonomous vehicle routing are disclosed. Roadway suitability for autonomous operation is scored to facilitate use in route determination. Maps of roadways suitable for various levels of autonomous operation may be generated. Such map data may be used by autonomous vehicles or other computer devices in determining routes based upon criteria for vehicle trips. Such routes may be automatically updated based upon changes in road conditions, vehicle conditions, operator conditions, or environmental conditions. Emergency routing using such map data is described, such as automatic routing and travel when a passenger is experiencing a medical emergency.

A method includes receiving raw data and generating a manufacturing data packet (MDP) that includes at least a portion of the raw data. Generating the MDP includes associating metadata with the raw data and associating a timestamp with the raw data. The timestamp is synchronized to a common reference time. A data model associated with the MDP is obtained. The data model includes one or more predefined data types and one or more predefined data fields. A first data type from the one or more predefined data types is determined based at least in part on characteristics of the raw data. An algorithm is determined based at least in part on the first data type. The MDP is processed according to the algorithm to produce an output. The first data type is associated with the raw data. The output is associated with a data field of the first data type.

Methods and systems for autonomous and semi-autonomous vehicle control relating to malfunctions are disclosed. Malfunctioning sensors or software of autonomous vehicles may be identified from operating data of the vehicle, and a component maintenance requirement status associated with such malfunctioning component may be generated. Based upon such status, usage restrictions may be enacted to limit operation of the vehicle while the component is malfunctioning. This may include disabling or restricting use of certain autonomous or semi-autonomous features of the vehicle until the component is repaired or replaced. Repair may be accomplished by automatically scheduling repair of the vehicle or installing an updated or uncorrupted version of a software program, in various embodiments.