Rockwell Collins, Inc.

Hamilton Sundstrand Space Systems International, Inc.

Daniel J Kaplan

Christopher A Hohensee

Jake A Rohrig

Jason R Owen

Angelo J Joseph

James B Mayfield

Jeffrey J Deloy

Tristan J Kendall

Yeshani D WijesekaraGamachchige

Andrea P Gonzalez

Nels Waineo

Christopher Kistler

Yeshani D Wijesekara Gamachchige

Chadwick K J Harvey

Ashley Himmelmann

Rachel L LaDue

Andrea Gonzalez

A toilet for a zero-gravity condition, having: a seat extending from a first end to a second end, and from a first side to a second side; a leg rest at the first end of the seat that is level with the seat; a backrest at the second end of the seat that extends away from the seat, toward an outer end of the toilet, a first sidewall at the first side of the seat and a second sidewall at the second side of the seat, the sidewalls extend away from the seat toward the outer end of the toilet; a basin extending away from the seat toward an inner end of the toilet; a first inflatable member extending about the leg rest, the sidewalls and the backrest, the first inflatable member is configured to inflate against a back, sides and under legs of a person seated against the seat.

Toilet and garment for waste removal in a zero-gravity condition

A predictive maintenance system is disclosed. The system includes a network of analog and digital sensors, each sensor configured for measuring telemetry data associated with temperature levels, voltage levels, current levels, and other analog or digital parameters. The system includes microprocessors for receiving the (digitized) analog and digital telemetry data, tabulating and timestamping the raw telemetry datasets. The microprocessors compress the raw data and reduce its dimensionality by generating principal component sets from the raw data based on scalar parameters corresponding to machine learning algorithms stored to memory, the principal component sets capturing a majority of variances within the raw data. The principal component sets are organized into data packets including identifiers for the relevant algorithms. The data packets are transmitted via real time networks for either onboard storage or ground-based analysis.

Predictive maintenance system using avionics ethernet networks

A system for time synchronization over redundant switch-based avionics networks is disclosed. The system includes a master or source clock for determining precise UTC timing information from received satellite signals and generating time marks based on the timing information. The source clock generates network-compatible timing messages and forwards the timing messages to network switches within the switch-based avionics networks. The network switches modify the timing information to account for switch-based delays and forward the modified timing messages to destination clocks in aircraft end systems. The end systems relay timing messages back to the source clock via the network switches, the timing information again modified by the network switches according to switch-based delays, and based on the precise timing information exchanged destination clocks in end systems throughout the switched network can precisely synchronize to the source clock.

Time synchronization over redundant and deterministic switch-based avionics networks

A predictive maintenance system for an aircraft-based power converter subsystem (PCS) continuously measures primary system parameters such as input and output currents and voltages, ambient and PCS component temperatures, and hold-up capacitance voltage. The predictive maintenance system updates the likely failure rate of the PCS based on the primary parameters and secondary parameters (e.g., power consumption, power efficiency, thermal resistance, hold-up storage capacitance) derived therefrom. Sensed primary parameters and derived secondary parameters, as well as the updated failure rate, are stored to memory in order to monitor their time derivatives and regression over the PCS lifespan. Should the updated failure rate ever reach or exceed an acceptable failure rate threshold, the predictive maintenance system alerts the aircraft control system, end user, or provider to service the PCS in advance of an unanticipated field failure.

Predictive maintenance system for aviation power supplies

A combined alternating current (AC) and direct current (DC) power converter is disclosed. In embodiments, the power converter includes an electromagnetic interference (EMI) filter, a bridge rectifier, and a boost converter. The EMI filter is configured to receive an electrical signal from a power source. The bridge rectifier is coupled to the EMI filter and includes at least four diodes arranged in a diode bridge configuration. The boost converter is coupled to the bridge rectifier and includes a switched DC path and a switched AC path. The switched DC path includes a DC transistor and the switched AC path includes an AC transistor. The switched AC path can also include one or more diodes and/or switching elements.

Combined AC and DC power converter with an electromagnetic interference filter and a bridge rectifier

Growing community of inventors

Melbourne Beach, FL, United States of America

Daniel J Kaplan