Patent classifications
G01J5/0846
APPARATUS FOR COUNTING OBJECTS
Apparatus for counting objects is disclosed. Apparatus includes a power source (108), a radio transceiver (110), two or more passive infrared (PIR) sensors (120A, 120B, 120C), one or more memories (104) including computer program code (106), a processor (102) to execute the computer program code (106), and a mechanical field of view limiting structure (126A, 128A, 130A, 126B, 128B, 130B, 126C, 128C, 130C) configured to limit the field of view of each infrared-sensitive element. The apparatus is caused to: detecting (202), by the first PIR sensor, a first motion; detecting (204), by the second PIR sensor, a second motion; if the second motion is detected within a predetermined time period after the first motion, increasing an inward count, or if the first motion is detected within a predetermined time period after the second motion, increasing an outward count; and transmitting the inward/outward count.
SYSTEMS AND METHODS FOR MEASURING TEMPERATURE
Systems and methods disclosed herein use a multi-color pyrometer configured to determine a first temperature in a high temperature range and a single-color pyrometer configured to determine second temperature in a low temperature range. The system uses information gained from determination of the first temperature in the high temperature range to facilitate later determining the second temperature in the low temperature range. The first temperature in the high temperature range and the second temperature in the low temperature range are used to monitor and control different engine operations that occur at different times.
SYSTEM AND METHODS FOR DETECTING, CONFIRMING, CLASSIFYING, AND MONITORING A FIRE
One variation of a method for detecting a fire includes: during a first time period: detecting an increase in ambient light intensity and detecting an increase in ambient humidity; responsive to the increase in ambient light intensity and the increase in ambient humidity, detecting a fire event; during a second time period: correlating a decrease in ambient light intensity with an increase in visual obscuration; detecting an increase in ambient air temperature; in response to a magnitude of the increase in visual obscuration remaining below a high obscuration threshold and a magnitude of the increase in ambient temperature remaining below a high temperature threshold, classifying the fire as an incipient fire; and, in response to the magnitude of the increase in visual obscuration exceeding the high obscuration threshold and the magnitude of the increase in ambient temperature exceeding the high temperature threshold, classifying the fire as a developed fire.
Method for Operating a Thermal Imaging Camera, and Thermal Imaging Camera
A method for operating a thermal imaging camera includes measuring two-dimensional temperature information including a thermal image of a setting using an infrared detector array of the thermal imaging camera, the infrared detector array including a plurality of pixels sensitive to infrared radiation. At least one of ambient humidity information and ambient air temperature information is provided. An evaluation device is used to calculate two-dimensional information about a mold formation risk. The method includes generating a mold risk map of the setting using a mold growth model and using the calculated two-dimensional temperature information, and the provided at least one of ambient humidity information and ambient air temperature information.
SYSTEM AND METHODS FOR DETECTING, CONFIRMING, CLASSIFYING, AND MONITORING A FIRE
One variation of a method for detecting a fire includes: during a first time period: detecting an increase in ambient light intensity and detecting an increase in ambient humidity; responsive to the increase in ambient light intensity and the increase in ambient humidity, detecting a fire event; during a second time period: correlating a decrease in ambient light intensity with an increase in visual obscuration; detecting an increase in ambient air temperature; in response to a magnitude of the increase in visual obscuration remaining below a high obscuration threshold and a magnitude of the increase in ambient temperature remaining below a high temperature threshold, classifying the fire as an incipient fire; and, in response to the magnitude of the increase in visual obscuration exceeding the high obscuration threshold and the magnitude of the increase in ambient temperature exceeding the high temperature threshold, classifying the fire as a developed fire.
DYNAMIC RADIOMETRIC THERMAL IMAGING COMPENSATION
Systems and methods for dynamic radiometric thermal imaging compensation. The method includes analyzing a visible light image to determine an emissivity value for each of a plurality of visible light pixels making up the visible light image. The method includes associating each of the plurality of thermal pixels making up a thermal image corresponding to the visible light image with at least one of the plurality of visible light pixels making up the visible light image. The method includes generating a second thermal image by, for each of the plurality of thermal pixels making up the thermal image, determining a temperature value based on the thermal pixel value of the thermal pixel and the emissivity value of the at least one of the plurality of visible light pixels associated with the thermal pixel.
Temperature calibration with band gap absorption method
A method and apparatus for calibration non-contact temperature sensors within a process chamber are described herein. The calibration of the non-contact temperature sensors includes the utilization of a band edge detector to determine the band edge absorption wavelength of a substrate. The band edge detector is configured to measure the intensity of a range of wavelengths and determines the actual temperature of a substrate based off the band edge absorption wavelength and the material of the substrate. The calibration method is automated and does not require human intervention or disassembly of a process chamber for each calibration.
Infrared temperature sensor
An infrared temperature sensor comprises a first communication port and a second communication port. A plurality of infrared temperature sensors can be cascaded to each other and connected to an external host controller through the second communication port. The external host controller can set up and administer the unique addresses of the plurality of the infrared temperature sensors through the second communication port, whereby to selectively perform multicasting communication or unicasting communication with the plurality of infrared temperature sensors through the first communication port. The infrared temperature sensor further comprises a second thermopile sensing element used to sense the thermal radiation of a package structure, whereby to compensate for the measurement error induced by temperature variation of the package structure. Thus, the measurement accuracy is increased.
Stove guard using a broad field of view
A stove guard having a data processing unit and a heat sensor arrangement for receiving heat radiation from objects located in a given field of view and for delivering the detector signals indicative of the received heat radiation to the data processing unit. The heat sensor arrangement is arranged to generate detector signals differently corresponding to the heat radiation received from a central area of the field of view than to the heat radiation received from a circumferential area of the field of view.
Emulating a spectral measurement device
Certain examples relate to emulating a spectral measurement device in a color measurement apparatus. In these examples, a primary spectral measurement device measures a first spectral characteristic of a rendered color output. A predictive model, parametrized by parameter values, is applied to the measurement from the primary spectral measurement device to determine a predicted measurement of a second spectral characteristic of the rendered color output which would be measured by an ancillary spectral measurement device. Parameter values are generated by training the predictive model with data from the primary spectral measurement device and the ancillary spectral measurement device.