Patent classifications
G01N21/359
SENSOR DEVICES COMPRISING A METAL-ORGANIC FRAMEWORK MATERIAL AND METHODS OF MAKING AND USING THE SAME
Disclosed herein are embodiments of sensor devices comprising a sensing component able to determine the presence of, detect, and/or quantify detectable species in a variety of environments and applications. The sensing components disclosed herein can comprise MOF materials, plasmonic nanomaterials, redox-active molecules, a metal, or any combinations thereof. In some exemplary embodiments, optical properties of the plasmonic nanomaterials and/or the redox-active molecules combined with MOF materials can be monitored directly to detect analyte species through their impact on external conditions surrounding the material or as a result of charge transfer to and from the plasmonic nanomaterial and/or the redox-active molecule as a result of interactions with the MOF material.
SENSOR DEVICES COMPRISING A METAL-ORGANIC FRAMEWORK MATERIAL AND METHODS OF MAKING AND USING THE SAME
Disclosed herein are embodiments of sensor devices comprising a sensing component able to determine the presence of, detect, and/or quantify detectable species in a variety of environments and applications. The sensing components disclosed herein can comprise MOF materials, plasmonic nanomaterials, redox-active molecules, a metal, or any combinations thereof. In some exemplary embodiments, optical properties of the plasmonic nanomaterials and/or the redox-active molecules combined with MOF materials can be monitored directly to detect analyte species through their impact on external conditions surrounding the material or as a result of charge transfer to and from the plasmonic nanomaterial and/or the redox-active molecule as a result of interactions with the MOF material.
BLOOD MEASUREMENT DEVICE
Provided is a blood measurement device capable of accurately estimating the amount of a component contained in blood by passing light beams for calculating the amount of the component contained in blood along the same optical axis. A blood measurement device 10 of the present invention includes a light emitting part 11 having a first light emitting part 111 and a second light emitting part 112, a light receiving part 19, an actuator 16, and a computation and control part 17 that estimates a glucose level and controls operation of the actuator 16. When applicating a first light beam from the first light emitting part 111 to a measurement site, the computation and control part 17 causes the actuator 16 to move a light emission point of the first light emitting part 111 onto an optical axis 22 defined to penetrate through the measurement site, and when applicating a second light beam from the second light emitting part 112 to the measurement site, the computation and control part 17 causes the actuator 16 to move a light emission point of the second light emitting part 112 onto the optical axis 22.
Real Time Mine Monitoring System and Method
The present invention relates to a method for detecting changes in the ore grade of a rock face in near real time. The method includes the step of providing a scanning system having at least a hyperspectral imager, a position system, a LiDAR or range determination unit and computational resources. Further, the method involves determining a precise location of the scanning system utilising the position system. The rock face is scanned with the range determination unit to determine rock face position information. The method involves scanning the rock face with the hyperspectral imager to produce a corresponding rock face hyperspectral image. Further the method involves utilising the computational resources to fuse together the rock face position information and the corresponding rock face hyperspectral image to produce a rock face position and content information map of the rock face.
Machine learning-based circuit board inspection
Circuit board inspection by receiving a near infrared (NIR) image of at least a portion of a circuit board, analyzing the NIR image using a machine learning model, and detecting anomalous circuit board portions according to the analysis.
Machine learning-based circuit board inspection
Circuit board inspection by receiving a near infrared (NIR) image of at least a portion of a circuit board, analyzing the NIR image using a machine learning model, and detecting anomalous circuit board portions according to the analysis.
System and method for determining vapor pressure of produced hydrocarbon streams via spectroscopy
An NIR analyzer with the optical probes across a pipe, or in a bypass configuration, after a stabilizer in an oil or condensate production plant. Prior to use, liquid samples from the plant are analyzed in a chemical lab to obtain reference vapor pressure or compositional values. A chemometric model using known techniques is then built with the captured absorption spectra and the reference lab results. Preprocessing methodologies can be used to help mitigate interferences of the fluid, instrument drift, and contaminate build up on the lenses in contact with the fluid. The chemometric model is implemented through the NIR analyzer as the calibration curve to predict the vapor pressure or other values of the flowing fluid in real time.
System and method for determining vapor pressure of produced hydrocarbon streams via spectroscopy
An NIR analyzer with the optical probes across a pipe, or in a bypass configuration, after a stabilizer in an oil or condensate production plant. Prior to use, liquid samples from the plant are analyzed in a chemical lab to obtain reference vapor pressure or compositional values. A chemometric model using known techniques is then built with the captured absorption spectra and the reference lab results. Preprocessing methodologies can be used to help mitigate interferences of the fluid, instrument drift, and contaminate build up on the lenses in contact with the fluid. The chemometric model is implemented through the NIR analyzer as the calibration curve to predict the vapor pressure or other values of the flowing fluid in real time.
METHOD AND APPARATUS FOR DETERMINING A REFLECTANCE OF A TARGET OBJECT
A method and apparatus for determining a reflectance, of at least a portion of a target object, in at least one selected wavelength range of electromagnetic (EM) radiation are disclosed. The method comprises, for each selected wavelength range, providing a digital image including at least one target object and a plurality of reference objects, each reference object having respective non-identical predetermined reflectance characteristics, with a digital camera arrangement that provides output image data that comprises digital numbers that are responsive to radiation, in only a selected wavelength range, incident at a sensing plane of the digital camera arrangement. A relationship between a first set of the digital numbers is determined and a first set of the respective predetermined reflectance characteristics of the reference objects. Responsive to the relationship, a further set of digital numbers is transformed to allocate a value of reflectance for each of the digital numbers in the further set. For at least a portion of the target object, a corresponding first group of allocated values of reflectance is determined and responsive to the first group of allocated values, determining a reflectance of the portion of the target object.
METHOD AND APPARATUS FOR DETERMINING A REFLECTANCE OF A TARGET OBJECT
A method and apparatus for determining a reflectance, of at least a portion of a target object, in at least one selected wavelength range of electromagnetic (EM) radiation are disclosed. The method comprises, for each selected wavelength range, providing a digital image including at least one target object and a plurality of reference objects, each reference object having respective non-identical predetermined reflectance characteristics, with a digital camera arrangement that provides output image data that comprises digital numbers that are responsive to radiation, in only a selected wavelength range, incident at a sensing plane of the digital camera arrangement. A relationship between a first set of the digital numbers is determined and a first set of the respective predetermined reflectance characteristics of the reference objects. Responsive to the relationship, a further set of digital numbers is transformed to allocate a value of reflectance for each of the digital numbers in the further set. For at least a portion of the target object, a corresponding first group of allocated values of reflectance is determined and responsive to the first group of allocated values, determining a reflectance of the portion of the target object.