Banner Engineering Corporation

Wade David Oberpriller

Ashley Wise

Paul D Bratton

Jeff Bromen

Thomas J Beckey

Michael A Dean

Neal Andrew Schumacher

Haozhe Dong

Kathryn Grant Phillips Longley

Chunmei Kang

Apparatus and associated methods relate to a field-adjustable distance sensor configured to translate a transfer function of the sensor by a substantially constant value in a position domain by calibration at one or more known distances. In an illustrative example, the transfer function may correlate multiple distances to corresponding position vectors describing a position of a light signal on a receiver. The receiver may, for example, generate a detection signal corresponding to a position on the receiver of a light signal reflected off a target. A control circuit may, for example, generate a position vector in response to the detection signal. A calibration constant (C) may be generated, for example, as a function of a known distance of the target and position vector. C may be applied, for example, to translate the transfer function in the position domain. Various embodiments may advantageously reduce non-linear error in a distance sensor.

Pixel domain field calibration of triangulation sensors

Apparatus and associated methods relate to detecting jams when an intensity of a reflected signal exceeds a predetermined intensity threshold and an intensity window metric based on historic intensity value(s) fails to exceed an intensity window threshold for more than a predetermined time threshold. In an illustrative example, a jam detection unit (JDU) may emit a signal and detect a reflection of the signal. The JDU may, for example, compare intensity of the reflected signal to the intensity threshold. The JDU, for example, may compare the intensity threshold with at least one historic intensity value to determine the intensity window metric. If the intensity value exceeds the intensity threshold and the intensity window metric has not exceeded the intensity window threshold for longer than the time threshold, then the JDU may, for example, generate a jam signal. Various embodiments may advantageously detect jams based on intensity of a reflected signal.

Non-contact motion detection sensor utilizing distance and intensity statistics

Apparatus and associated methods relate to a method of non-contact motion detection. A one-dimensional optical sensor detects motion of a target or objects on a conveyor belt through a continuous measurement of targets or objects and a real-time comparison of the pixel images captured by the one-dimensional optical sensor. In an illustrative embodiment, a one-dimensional sensor may be configured to determine motion of objects based on changes to the captured intensities of pixel images over time. The sensor may continually capture photoelectric pixel images and compare a current pixel image with a previous pixel image to determine a frame differential image value. The frame differential image value is evaluated against a predetermined threshold over a predetermined time period. Based on the evaluation, a signal is output indicating whether the objects on the conveyor belt are moving or jammed.

Image-based jam detection

Apparatus and associated methods relate to enabling a radar system to use different sensing mechanisms to estimate a distance from a target based on different detection zones (e.g., far-field and near-field). In an illustrative example, a curve fitting method may be applied for near-field sensing, and a Fourier transform may be used for far-field sensing. A predetermined set of rules may be applied to select when to use the near-field sensing mechanism and when to use the far-field mechanism. The frequency of a target signal within a beat signal that has less than two sinusoidal cycles may be estimated with improved accuracy. Accordingly, the distance of a target that is within a predetermined distance range (e.g., two meters range for 24 GHz ISM band limitation) may be reliably estimated.

Near range radar

An example method for stabilizing a sensor component includes: positioning the sensor component relative to a support with retaining members in contact with the sensor component, a first of the retaining members being a resilient biasing member and a second one of the retaining members being an adjustable retaining member; adjusting the adjustable retaining member to reposition the sensor component and deform the resilient retaining member; immobilizing the sensor component with an additional, rigid retaining member in contact with the sensor component; and filling a space between the sensor component and the support with a glue. An example holder of a sensor component includes support members; retaining members adapted to cooperatively adjustably retain the sensor component support members; and an additional, rigid retaining member adapted to cooperate with other retaining members to fixedly retain the sensor component.

Sensor component stabilization

Multiple signal characteristics representing an entire field of view of an FMCW (FM-CW) sensor are evaluated to determine whether the field of view has changed. Signal characteristics representing the field can be compared to representative signal characteristics obtained from previous scans. At least one signal characteristic representing at least a portion of the scene can be evaluated by comparing the signal characteristic to a dynamic threshold. The dynamic threshold can be redefined after each scan from the statistics of the signal characteristic. The dead zone of a sensor can be reduced by filtering out noise that would otherwise overshadow a signal representing the near-field region of a scene. The noise can be filtered by subtracting a polynomial curve from a time-domain signal representing the scene after fitting the polynomial curve to a representative signal generated based on previous scene scans.

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Chaska, MN, United States of America

Wade David Oberpriller