Abstract: A method includes receiving a signal associated with one or more sensors. The method also includes examining one or more parameters of a signal conditioning circuit to determine whether clipping of the signal has occurred. The method further includes, upon a determination that clipping of the signal has occurred, decreasing a gain of the signal conditioning circuit. In addition, the method includes, upon a determination that clipping of the signal has not occurred, determining whether a cut-off frequency of the signal conditioning circuit is within a range of a frequency response of an object measured by the one or more sensors. The method can further include changing the cut-off frequency of the signal conditioning circuit and increasing a resistance or a capacitance of the signal conditioning circuit.

Abstract: A system for calibrating a thermal camera with a calibration target. The calibration target may have a pattern which can be seen on an infrared image captured by the camera. The pattern may be of various kinds. For example, the pattern may be a checkerboard with some, such as every other square, having one emissitivity and the remaining squares having a different emissitivity, or having infrared light sources placed at corners of the squares. A difference between the emmissitivities may be sufficient so that the checkerboard pattern appears in an infrared image captured by the camera for calibration. The calibration may aid in determining intrinsic and extrinsic parameters of the camera. The parameters may provide a basis for transforming camera pixel coordinates to a world coordinate system which allows measurement of real world entities by the thermal camera. Measurements may incorporate distances between objects, heights of objects, and so forth.

Abstract: A method includes receiving a signal associated with one or more sensors. The method also includes examining one or more parameters of a signal conditioning circuit to determine whether clipping of the signal has occurred. The method further includes, upon a determination that clipping of the signal has occurred, decreasing a gain of the signal conditioning circuit. In addition, the method includes, upon a determination that clipping of the signal has not occurred, determining whether a cut-off frequency of the signal conditioning circuit is within a range of a frequency response of an object measured by the one or more sensors. The method can further include changing the cut-off frequency of the signal conditioning circuit and increasing a resistance or a capacitance of the signal conditioning circuit.

Abstract: A method includes transmitting first wireless signals towards a conveyor belt having multiple layers of material. The first wireless signals penetrate one or more layers in the conveyor belt. The method also includes receiving second wireless signals that have interacted with the conveyor belt. The method further includes identifying a condition of the conveyor belt using the second wireless signals and outputting an indicator identifying the condition of the conveyor belt. Identifying the condition of the conveyor belt could include identifying a thickness of at least one of the layers in the conveyor belt. This could be done by identifying pulses in the second wireless signals and using time of flight calculations.

Abstract: A method includes receiving an image of a storage tank at a processing system, where the storage tank is capable of storing one or more materials. The method also includes processing the image to identify a level, profile, or amount of sludge or sediment present in the storage tank. Processing the image could include segmenting the image into multiple segments and using the segments to identify a non-linearity in the image. The image could be segmented into segments having different grey levels using grey level values associated with previously-identified sediment or sludge. The identified level or amount of sludge or sediment could be used to automatically schedule maintenance for the storage tank.

Abstract: A method includes transmitting first wireless signals towards a conveyor belt having multiple layers of material. The first wireless signals penetrate one or more layers in the conveyor belt. The method also includes receiving second wireless signals that have interacted with the conveyor belt. The method further includes identifying a condition of the conveyor belt using the second wireless signals and outputting an indicator identifying the condition of the conveyor belt. Identifying the condition of the conveyor belt could include identifying a thickness of at least one of the layers in the conveyor belt. This could be done by identifying pulses in the second wireless signals and using time of flight calculations.

Abstract: A system for calibrating a thermal camera with a calibration target. The calibration target may have a pattern which can be seen on an infrared image captured by the camera. The pattern may be of various kinds. For example, the pattern may be a checkerboard with some, such as every other square, having one emissitivity and the remaining squares having a different emissitivity, or having infrared light sources placed at corners of the squares. A difference between the emmissitivities may be sufficient so that the checkerboard pattern appears in an infrared image captured by the camera for calibration. The calibration may aid in determining intrinsic and extrinsic parameters of the camera. The parameters may provide a basis for transforming camera pixel coordinates to a world coordinate system which allows measurement of real world entities by the thermal camera. Measurements may incorporate distances between objects, heights of objects, and so forth.

Abstract: A method includes receiving an image of a storage tank at a processing system, where the storage tank is capable of storing one or more materials. The method also includes processing the image to identify a level, profile, or amount of sludge or sediment present in the storage tank. Processing the image could include segmenting the image into multiple segments and using the segments to identify a non-linearity in the image. The image could be segmented into segments having different grey levels using grey level values associated with previously-identified sediment or sludge. The identified level or amount of sludge or sediment could be used to automatically schedule maintenance for the storage tank.