Embodiments herein describe coupling traditional fan and shaper control along with aggregated knowledge of the temperature history of a hardware device to optimally manage the temperature of the hardware device to preserve its expected life while also providing the lower power, best performing solution possible. In one embodiment, a cooling application manages the expected life by trading off performance and power versus temperature to achieve a desired (or accepted) lifetime. In one embodiment, the cooling application calculates a historical temperature value for the hardware device which is then used to determine the expected life of the hardware device.

A gas turbine engine starting system including an electric start generator (ESG) free of temperature sensors and configured to provide torque to a gas turbine engine. A fuel metering module is configured to provide a quantity of fuel to the gas turbine engine, and an electronic control system (ECS). The ESG includes a plurality of subcomponents. The ECS is configured to predict a future temperature of the ESG, predict that at an ongoing start or an uninitiated start will be unsuccessful, and provide the prediction that at an ongoing start or an uninitiated start will be unsuccessful to an operator. The prediction of the future temperature of the ESG is based on a plurality of historical ESG thermal trending information and an input ambient temperature. The prediction that at an ongoing start or an uninitiated start will be unsuccessful is based on the future temperature of the ESG.

In the present invention, provided is a monitoring device (10) including an operating-state-change information acquisition unit (11) that acquires operating-state-change information indicating a time-series change in operating states of an electrical device, the device being capable of assuming multiple types of operating states, a standard transition pattern storage unit (12) that stores standard transition pattern information indicating a pattern of transition between operating states generated in a normal electrical device, and a monitoring unit (13) that determines whether or not the electrical device is normal using the operating-state-change information and the standard transition pattern information.

An aircraft refueling system (10) includes a master controller (12), a fleet controller (14) in communication with the master controller, a platform controller (18) in communication with the fleet controller, and a fuel control system (16) in communication with the platform controller. Embodiments of an aircraft refueling system may include a primary pressure controller (20), a secondary pressure controller (22), a programmable logic controller (24), and a data logger controller (26). The master controller may be configured to receive and analyze data from at least one of the fleet controller, the platform controller, and the fuel control system; and to modify operational parameters or upgrade the fuel control system based at least in part on the analysis of received data.

A plant monitoring apparatus according to an embodiment includes a determiner and a display processor. The determiner compares a first process value acquired in time series from a first point of a monitoring target in a plant and a limit value corresponding to the first process value to determine a time when the first process value exceeds the limit value. The display processor causes a display device to display, in time series, the first process value within a time range decided on the basis of the time obtained by the determiner and the limit value corresponding to the first process value.

A method includes identifying a statistical performance of a monitoring rule associated with an asset monitoring system. The monitoring rule includes logic configured to identify one or more faults with at least one asset, and the statistical performance includes an effectiveness of the monitoring rule in identifying the one or more faults. The method also includes identifying an economic performance of the monitoring rule, where the economic performance is based on costs associated with different outcomes of the monitoring rule. The method further includes updating or replacing the monitoring rule based on the economic performance.

A method of monitoring equipment data of a piece of equipment includes extracting data specifications from a first image, the first image including data specification information for the piece of equipment, and storing the data specifications. The method further includes extracting measurement data from at least one second image, the at least one second image including measurement information for the piece of equipment. The method further includes associating the measurement data with the piece of equipment and storing the measurement data. The method further includes generating a measurement data trend profile for the piece of equipment and comparing operational measurement data against the measurement data trend profile. The method further includes notifying one or more users when the operational measurement data associated with the piece of equipment deviates from the measurement data trend profile.

A computer implemented method to determine aircraft sensor failure and correct aircraft sensor measurement in an aircraft system is provide. The computer implemented method includes determining, using a physics-based high-fidelity model, a high-fidelity system response over operating conditions during which sensor drift of a sensor of interest can be detected, creating, using an aircraft system controller, a reduced order model (ROM) using the high-fidelity system response, wherein the ROM correlates with the sensor of interest when operating normally, calculating, using the ROM, at least one reduced order sensor value, determining an error value between the reduced order sensor value and a sensor measurement reading from the sensor of interest, and comparing the error value to an error threshold, wherein the sensor of interest has failed when the error value is greater than the error threshold.

A system for determining health of a component is provided. The system includes an operational parameter module associated with the component and in communication with a controller. The controller is configured to receive an operating parameter signal from the operational parameter module. The controller is configured to monitor a change of the operating parameter over a predetermined time period. The controller is configured to compare the monitored operating parameter with a first predetermined threshold. The controller is configured to determine a rate of change of the monitored operating parameter over the predetermined time period. The controller is also configured to compare the determined rate of change with a second predetermined threshold. The controller is further configured to determine the health of the component based, at least in part, on the comparisons with the first and second predetermined thresholds respectively and one or more additional parameters associated with the component.

A system for determining a health condition and an anomaly of a field equipment 104 is provided. The system includes sensors 106A-N which sense information associated with the equipment 104, a field device 110 which receives the sensor data from sensors 106A-N, a camera unit 108 that captures visual data of the equipment 104 and a server 112. The server 112 includes a database 114 that stores the sensor data and the visual data. The server 112 further includes a fault detection module 202 that processes the sensor data to determine a fault or the health condition of the equipment 104, an image processing module 204 that is trained to detect the irregularities/anomaly in the equipment 104 by processing the visual data, and a report generation module 206 that generates an automated health report 212 based on the detected anomaly and the health condition of the equipment 104.