Abstract: Methods and Systems are provided for performing early onset diagnostics for clogged injectors using fuel trims collected from the Engine Management System and evaluated in different operating modes of the engine. Example implementations use fuel trims that can estimate the contrast in combustion ratio ? across different operating modes defined on the engine speed and calculated engine load plane. Features are extracted, then classified using machine learning to output a diagnosis according to different levels of fuel injector clogging.

Abstract: The present invention relates to a system and a method for automatic fault diagnosis, troubleshooting and resolution recommendations in a data center comprising one or more resources. The method comprises at least one collector unit [102] collecting a first data from one or more resources of the data center. A mapping unit [104] identifies a failure impact on the one or more resources based on the first data collected by the at least one collector unit. The central module unit [110] creates a detailed relationship map for the one or more virtual and physical resources based on the identified failure impact. A fault processor [106] automatically diagnoses the data center on occurrence of a fault based on the relationship map, and troubleshoots at least one of the one or more resources based on the diagnosis.

Abstract: Sub-resolution measurement of fuel in fuel tank. In an embodiment, data, which comprise discrete fuel levels in a fuel tank and fuel injection rates for an internal combustion engine, are received. The fuel injection rates are integrated over a traversed distance to produce a fuel consumption series, and the discrete fuel levels are clustered over the traversed distance to produce a fuel level series. The fuel consumption and fuel level series are synchronized into a model that is used to generate sub-resolution measurements of fuel levels between the discrete fuel levels.

Abstract: Sub-resolution measurement of fuel in fuel tank. In an embodiment, data, which comprise discrete fuel levels in a fuel tank and fuel injection rates for an internal combustion engine, are received. The fuel injection rates are integrated over a traversed distance to produce a fuel consumption series, and the discrete fuel levels are clustered over the traversed distance to produce a fuel level series. The fuel consumption and fuel level series are synchronized into a model that is used to generate sub-resolution measurements of fuel levels between the discrete fuel levels.

Abstract: The present invention relates to a system and a method for automatic fault diagnosis, troubleshooting and resolution recommendations in a data center comprising one or more resources. The method comprises at least one collector unit [102] collecting a first data from one or more resources of the data center. A mapping unit [104] identifies a failure impact on the one or more resources based on the first data collected by the at least one collector unit. The central module unit [110] creates a detailed relationship map for the one or more virtual and physical resources based on the identified failure impact. A fault processor [106] automatically diagnoses the data center on occurrence of a fault based on the relationship map, and troubleshoots at least one of the one or more resources based on the diagnosis.