An information processing device includes: a memory; and a processor coupled to the memory and configured to: learn a classification rule that classifies an abnormal degree of a production facility from a text feature amount based on the text feature amount obtained from a number of texts included in a plurality of pieces of log data obtained in a predetermined process of the production facility and production history information of the production facility; extract a text feature amount of log data to be monitored obtained in the predetermined process of the production facility; and determine an abnormal degree of the production facility when the log data to be monitored is obtained based on the text feature amount and the classification rule.

Methods and systems for autonomous vehicle recharging or refueling are disclosed. Autonomous vehicles may be automatically refueled by routing the vehicles to available fueling stations when not in operation, according to methods described herein. A fuel level within a tank of an autonomous vehicle may be monitored until it reaches a refueling threshold, at which point an on-board computer may generate a predicted use profile for the vehicle. Based upon the predicted use profile, a time and location for the vehicle to refuel the vehicle may be determined. In some embodiments, the vehicle may be controlled to automatically travel to a fueling station, refill a fuel tank, and return to its starting location in order to refuel when not in use.

Methods and apparatus are provided for an integrated vehicle health management system that uses a model based reasoner to develop real-time diagnostic and maintenance information about a vehicle. A model having nodes is used to represent sensors, components, functions and other elements of the system. Parameterized input sensors provide flexible definitions of each node. Once developed, the model is loaded into an operational flight program to provide real-time failure analysis of the vehicle.

A vehicle maintenance scheduling and fault monitoring apparatus includes a vehicle system maintenance rules generation module and a vehicle system fault detection module. The rules generation module determines a correlation between pairs of precedent historical vehicle fault data, of historical time-stamped vehicle fault data, and a subsequent different historical vehicle fault data, and generates vehicle system maintenance rules based on the correlation determined for the pairs of the precedent historical vehicle fault data and the subsequent different historical vehicle fault data. The fault detection module monitors faults of the vehicle system, determines an imminent occurrence of a subsequent vehicle fault, based on application of the vehicle system maintenance rules to the plurality of time-stamped precedent vehicle fault data, and generates a maintenance report corresponding to the imminent occurrence of the subsequent vehicle fault so that proactive maintenance is performed on the vehicle system.

A data generating apparatus according to the one aspect of the present invention may include a converter configured to acquire conversion information in which a conversion rule is defined for converting first data acquired by performing a maintenance operation into second data processable by a facility maintenance management system and to convert the first data in accordance with the conversion rule defined in the acquired conversion information to generate the second data.

Methods and apparatus are provided for an integrated vehicle health management system that uses a model based reasoner to develop real-time diagnostic and maintenance information about a vehicle. A model having nodes is used to represent sensors, components, functions and other elements of the system. Parameterized input sensors provide flexible definitions of each node. Once developed, the model is loaded into an operational flight program to provide real-time failure analysis of the vehicle.

Device (1) for the provision of electric power, wherein the device (1) comprises: at least one integrated temperature sensor (3-1, 3-2) which detects an operating temperature progression of at least one component (2-1, 2-2) of the device (1) and a monitoring unit (5) which, on the basis of the at least one detected operating temperature progression and the adjusted power, monitors the operating state of a device cooling arrangement of the device (1).

Disclosed herein are techniques to make the synthesized monitoring conditions of partially-observable hybrid systems robust to partial observability of sensor uncertainty and partial controllability due to actuator disturbance. The approach herein shows that the monitoring conditions result in provable safety guarantees with fallback controllers that react to monitor violation at runtime.

Various aspects of prognosis of an installed high voltage equipment (HVE) by a monitoring system are described. One or more models are dynamically selected from a plurality of models tuned from data obtained from a plurality of HVEs communicatively connected with the monitoring system. A failure mode of the installed HVE is predicted, based on input parameters associated with the installed HVE, using the one or more models. At least one prognostic response is determined for the installed HVE, based on the predicted failure mode, using the one or more models. The at least one prognostic response is provided for the installed HVE.

A method including: determining whether a cooling system is operating in a cooling mode, such that the cooling system is not operating in a reheat mode, a humidification mode or a dehumidification mode; determining whether the cooling system is operating in a compressor mode, such that the cooling system is not operating in a pump refrigerant economization mode; determining whether the cooling system is at steady-state; and if the cooling system is operating in the cooling mode and the compressor mode and is at steady-state, evaluating one or more rules to determine if a degradation symptom exists for the cooling system. The method further includes: subsequent to the evaluation, generating a degradation evaluation value to indicate whether the one or more rules are satisfied; and based on the degradation evaluation value, generating an alarm signal or performing a countermeasure.