Simmonds Precision Products, Inc.

Simmonds Precision Prodcuts, Inc.

Mokhtar M Sadok

Radoslaw Romuald Zakrzewski

Robert Zeliff

Jeffrey James Shirer

Michael Anthony Lynch

Eric Robert Bechhoefer

William B Spillman, Jr

Scott Robert Durkee

Bruce R Kline

Scott Fusare

Disclosed is a rotor track and balance system for rotorcraft that includes a data processing unit, a tachometer sensor and at least one accelerometer. The tachometer sensor is located remotely from the data processing unit and is mounted proximate to the rotating blades of the rotorcraft. The tachometer sensor is adapted to measure the speed and position of the rotating blades and to wirelessly transmit speed and position data to the data processor. The at least one accelerometer is also located remotely from the data processing unit and is mounted proximate the rotating blades of the rotorcraft. Each accelerometer is adapted to measure vibration anomalies in the rotating blades and to wirelessly transmit vibration data to the data processor. The data processing unit synchronizes the wireless data transmitted from the tachometer sensor and the wireless accelerometer(s) and determines necessary adjustments to be made in order to reduce the vibration anomalies in the rotor blades.

Wireless rotor track and balance system for rotorcraft

Detecting video phenomena, such as fire in an aircraft cargo bay, includes receiving a plurality of video images from a plurality of sources, compensating the images to provide enhanced images, extracting features from the enhanced images, and combining the features from the plurality of sources to detect the video phenomena. Extracting features may include determining an energy indicator for each of a subset of the plurality of frames. Detecting video phenomena may also include comparing energy indicators for each of the subset of the plurality of frames to a reference frame. The reference frame corresponds to a video frame taken when no fire is present, video frame immediately preceding each of the subset of the plurality of frames, or a video frame immediately preceding a frame that is immediately preceding each of the subset of the plurality of frames. Image-based and non-image based techniques are described herein in connection with fire detection and/or verification and other applications.

Detection and recognition of fog presence within an aircraft compartment using video images

A wireless sensor system for an aircraft including a central access point and a plurality of slave nodes arranged in a star network in which the central access point wirelessly exchanges data with the slave nodes in a bidirectional manner. At least one of the antenna at the central access point and the antenna of each of the slave nodes is circularly polarized.

Circularly polarized antennas for a wireless sensor system

Method for distinguishing a smoke condition from a dust condition using video images

Described are techniques used in a wire diagnostics system to detect events, such as defects, that may occur within a wire or cable under test. An incident voltage signal is sent out on the wire and a measured voltage signal is obtained which includes the incident voltage and the reflected voltage. Compensation processing is performed on the measured waveform to remove unwanted reflective components. Additionally, the waveform is then subject to attenuation processing and event detection processing. Detected events, such as defects, are classified and output as results. Events are classified by parametric classification using a library of known events or faults. The library of known events or faults is previously generated using empirical analysis and modeling techniques. Additionally, joint time-frequency domain reflectometry (TFDR) techniques are described for event identification and classification for a wire under test.

Wire fault detection

Method for detection and recognition of fog presence within an aircraft compartment using video images

Detecting video phenomena, such as fire in an aircraft cargo bay, includes receiving a plurality of video images from a plurality of sources, compensating the images to provide enhanced images, extracting features from the enhanced images, and combining the features from the plurality of sources to detect the video phenomena. The plurality of sources may include cameras having a sensitivity of between 400 nm and 1000 nm and/or may include cameras having a sensitivity of between 7 and 14 micrometers. Extracting features may include determining an energy indicator for each of a subset of the plurality of frames. Detecting video phenomena may also include comparing energy indicators for each of the subset of the plurality of frames to a reference frame. The reference frame corresponds to a video frame taken when no fire is present, video frame immediately preceding each of the subset of the plurality of frames, or a video frame immediately preceding a frame that is immediately preceding each of the subset of the plurality of frames.

Viewing a compartment

Video detection/verification system

Detecting a fire, such as a fire in an aircraft cargo bay, includes receiving a plurality of frames of video information, determining an energy indicator for each of a subset of the plurality of frames, and detecting the presence of fire in response to the energy indicator for each of the subset of the plurality of frames corresponding to a predetermined pattern as a function of time. Detecting a fire may also include comparing energy indicators for each of the subset of the plurality of frames to a reference frame. The reference frame may correspond to a video frame taken when no fire is present or a video frame immediately preceding each of the subset of the plurality of frames. At least some of the subset of the plurality of frames may be provided by a camera having a sensitivity of between 400 nm and 1000 nm that may generates 640&#xd7;480 pixels per frame. At least some of the subset of the plurality of frames may be provided by a CCD camera or a CMOS camera. At least some of the subset of the plurality of frames may be provided by a camera having a sensitivity of between 7 and 14 micrometers, which may be an IR camera.

Detecting fire using cameras

Detecting fire and non-fire conditions includes receiving a plurality of frames of video information, determining an energy indicator for each of a subset of the plurality of frames, detecting a fire condition in response to the energy indicator for each of the subset of the plurality of frames forming a pattern as a function of time corresponding to a fire condition, and detecting a non-fire condition in response to the energy indicator for each of the subset of the plurality of frames forming a pattern as a function of time corresponding to a non-fire condition. Detecting fire and non-fire conditions may also include comparing energy indicators for each of the subset of the plurality of frames to a reference frame. The reference frame may correspond to a video frame taken when no fire is present, a video frame immediately preceding each of the subset of the plurality of frames, or a video frame immediately preceding a frame that is immediately preceding each of the subset of the plurality of frames.

Distinguishing between fire and non-fire conditions using cameras

This disclosure is directed to apparatus for measuring height of a surface of liquid in a container utilizing a light source and camera pair disposed above the liquid surface in a predetermined spatial relationship to each other and the container. The light source illuminates the liquid surface with a light pattern and the camera captures the area image of the light pattern in a form of discrete picture elements (pixels) that are processed in an image processor to determine the height of liquid in the container. In another embodiment, the pixels of the area image are further processed to determine attitude of the liquid surface so that the processor may determine the quantity of liquid in the container based on the determined height and attitude of the liquid surface and container geometry data stored in a memory thereof. In yet another embodiment, a plurality of light source/camera pairs are disposed above the liquid surface, each pair operates by capturing an area image of the light pattern on a portion of the liquid surface illuminated by its light source. The pixels of the area image of each pair are processed in the image processor to determine the heights of the corresponding liquid surface portions. In still another embodiment, a plurality of cameras are disposed above the liquid surface to observe at least one light pattern at different viewing angles. Each camera captures an area image of the at least one light pattern and the pixels of such area images are processed in the image processor to determine at least one height for the liquid surface in the container. In this embodiment, the image processor may include an algorithm for combining together the pixels of the various area images of the plurality of cameras to determine the at least one liquid surface height.

Apparatus for measuring height of a liquid in a container using area image pattern recognition techniques

A method of and apparatus for discriminating among ultrasonic echoes reflected from various objects in a tank containing liquid is disclosed. Ultrasonic signals are generated from an ultrasonic transducer into liquid contained in a tank. Ultrasonic echoes are received by the transducer from various objects in the tank including a surface of the liquid in response to the generated ultrasonic signal and are converted into electrical echo signals representative thereof. Data samples of the electrical echo signals are generated and processed by a signal processor using wavelet function processing to generate wavelet coefficients thereof in a wavelet domain. The wavelet coefficients of the echo data samples are used to discriminate the ultrasonic echoes reflected from the various objects in or part of the tank. In one embodiment, echoes reflected from the liquid surface are discriminated from echoes reflected from other objects based on the wavelet coefficients of the echo data samples of each. In another embodiment, energy of each of the ultrasonic echoes determined from the wavelet coefficients thereof is used to discriminate the ultrasonic echoes from the various reflective surfaces.

Growing community of inventors

Vergennes, VT, United States of America

Mokhtar M Sadok