United Technologies Corporation

Otis Elevator Company

Raytheon Technologies Corporation

Jun Liu

Chouhwan Moon

Allan J Volponi

Sheridon Everette Haye

Juan A Lence Barreiro

Harry Z Huang

Paul J Vasques

Juan A Lence-Barriero

A sensor for sensing debris in a lubrication flow through a lubrication channel in a gas turbine engine, the sensor including: a housing; external electronics communicating sensed data to a signal processor; internal electronics within the housing, the internal electronics being electronically connected to the external electronics, the internal electronics including a plurality of sensor coils adjacently disposed in a lubrication flow-wise direction; and internal damping material separating the plurality of sensor coils from the housing.

Vibration induced noise suppression device

An example data assessment method for a diagnostic system includes receiving a set of initialization data, analyzing the set of initialization data to identify a data outlier in the set of initialization data, and determining whether the set of initialization data is bimodal. The method further includes establishing a set of cleaned data based on the analysis and establishing a baseline operating condition for the device using the set of cleaned data.

Anomalous data detection method

A system and method for accurately calculating the oil quantity and oil consumption rate of an aircraft engine detects the level of oil in an oil tank, calculates the oil quantity in the oil tank by compensating for the acceleration of the aircraft, as well as changes in the pitch, yaw and roll of the aircraft. The oil consumption rate of the aircraft is also calculated by calculating the oil quantity at different times, and dividing the difference in oil quantity by the difference in times. The percentage change in oil consumption of the aircraft engine is also calculated. The oil quantity and oil consumption rate can be reported during and after the aircraft's flight.

Oil consumption monitoring for aircraft engine

Variable thresholds ( ) are generated in response to an average defect rate ( ) generated under certain conditions ( ), excesses of which can set an internal flag ( ). If an information request ( ) or service personnel visit to the elevator site ( ) occur, the internal flag, or the upward adjustment of the average defect rate ( ) can generate a maintenance flag ( ) which ultimately results in a maintenance recommendation message related to the particular parameter having a notable defect.

Condition-based, auto-thresholded elevator maintenance

Signal processing and diagnostic routines ( ) of elevator controllers ( ) count the total number of runs to landings (O-F) of elevators ( ) along with the number of runs to landings at which a value of a parameter of an elevator door condition or event is notable, (e.g., too high or too low). If any particular parameter is notable at more than one landing, and the ratio of (a) number of runs to landing at which said particular parameter is notable to (b) the total number of runs to landings exceeds a predetermined threshold, the problem is registered as a car door problem; otherwise, the problem is registered as a landing door problem at each landing where the value of the particular parameter is notable.

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Hartford, CT, United States of America

Jun Liu