Disclosed is a monitoring apparatus for monitoring a state of wear of a component of a reciprocating piston internal combustion engine wherein an oil collection device is provided for the collection of lubrication oil from the cylinder so that a predetermined measured quantity of lubrication oil is suppliable from the cylinder to a measurement device.

A device for determining fluid degradation includes a memory and processing circuitry configured to cause the device to generate first calibration data of an e-machine at a first time, generate second calibration data of the e-machine at a second time subsequent to the first time, and determine that the fluid is degraded in response to a difference between the first calibration data and the second calibration data being greater than or equal to a degradation threshold.

Methods and systems are provided for filtering an oil dilution amount based on a current value of the oil dilution amount. In one example, filtering the oil dilution amount may include decreasing a sensitivity of filtering at lower oil dilution below a threshold; otherwise, increasing the sensitivity of filtering. The sensitivity of the filtering may be decreased by implementing a larger time constant, while the sensitivity of the filtering may be increased by implementing a smaller time constant.

Apparatuses are disclosed including an apparatus for machine fluid monitoring or sampling comprising a transparent sight glass attachable to a machine such that machine fluid is transferable to the sight glass. The sight glass may have one or more ports, an open first end, a closed second end, and a cavity for the machine fluid. A grommet may be positioned in a first port of the sight glass and may have a sealable access pathway through the grommet to the cavity within the sight glass through which a probe may be extended. A magnetic plug may be positioned in the second port of the sight glass extending into the cavity within the sight glass such that the magnetic plug is positionable for contact with the machine fluid. A sample port assembly may be connected to the sight glass whereby samples of the machine fluid are accessible.

Methods and systems for failure prediction using analysis of oil or other lubricant. Raw data about feature(s) of each of a plurality of particles filtered from a fluid sample are used to categorize each particle into one of a plurality of categories, each category being defined by one or more of: chemical composition, size and morphology. Particle physical characteristics in each category are quantified to obtain a set of categorized data. The categorized data are compared with historical data. Results of the comparing are evaluated to generate a prediction of any failure or mechanism of failure.

Methods and systems for operating an aircraft engine. A health parameter for the aircraft engine is monitored by a health evaluation device, the health parameter received from a first instrument. the health parameter is compared, by the health evaluation device, to a predetermined threshold. When the health parameter reaches the predetermined threshold, the health evaluation device wirelessly transmits a fault signal to a controller associated with the aircraft engine to elicit a health response from the controller, the fault signal containing at least two mutually-exclusive fault codes associated with an operating condition of the aircraft engine monitored by a second instrument.

Methods and systems for failure prediction using analysis of oil or other lubricant. Raw data about feature(s) of each of a plurality of particles filtered from a fluid sample are used to categorize each particle into one of a plurality of categories, each category being defined by one or more of: chemical composition, size and morphology. Particle physical characteristics in each category are quantified to obtain a set of categorized data. The categorized data are compared with historical data. Results of the comparing are evaluated to generate a prediction of any failure or mechanism of failure.

Methods and systems for failure prediction using analysis of oil or other lubricant. Raw data about feature(s) of each of a plurality of particles filtered from a fluid sample are used to categorize each particle into one of a plurality of categories, each category being defined by one or more of: chemical composition, size and morphology. Particle physical characteristics in each category are quantified to obtain a set of categorized data. The categorized data are compared with historical data. Results of the comparing are evaluated to generate a prediction of any failure or mechanism of failure.

Systems and methods disclosed provide an automotive fluids management and maintenance system (AFMMS) that manages and maintains fluids within vehicles by accurately and in a controlled manner directing the propulsion of these fluids into vehicle's internal components and also accurately and in a controlled manner draining fluids out of vehicle's internal components. The systems and methods enable a technician to dispense any desired fluid and pump the same into a vehicle internal component with speed, efficiency, accuracy, and in a very clean and unwasteful manner. The AFMMS is powered by a standard shop air supply. Once charged with air pressure, the AFMMS becomes mobile and is without any attachments, e.g., to a wall air supply, thus making it safe and convenient to be used around any shop environment, as well as outside in parking lots.

A system including one or more generators predicts engine oil life. Generator data is received or generated by a controller. The generator data describes the operation of the generator including a load placed on the generator. Engine data may also be received or generated by the controller describing an engine coupled to the generator. The controller calculates an estimated oil life based at least on the generator data and/or the engine data.