A method and system for optimizing RF energy delivery to a tissue ROI with a thermoacoustic system includes directing with a RF applicator, RF energy pulses into the tissue ROI having an object of interest and a reference separated by a boundary; detecting with a thermoacoustic transducer, a multi-polar thermoacoustic signal generated at the boundary in response to the RF energy pulses and processing the multi-polar acoustic signal to determine a peak-to-peak amplitude; detecting with the thermoacoustic transducer, an artifact multi-polar thermoacoustic signal generated at a location other than the boundary and processing it to determine a peak-to-peak amplitude; utilizing an electromagnetic model coupled with a model of patient anatomy to place dielectric or conducting materials near the thermoacoustic transducer or the RF applicator to optimize a signal-to-noise ratio of the multi-polar thermoacoustic signal generated at the boundary or minimize the artifact multi-polar thermoacoustic signal generated at a location other than the boundary; and directing with the RF applicator, RF energy pulses into the ROI for a thermoacoustic measurement and determine a parameter of the object of interest.

System and method for identification and verification of authorization of a subject to use a substance delivery device.

A temperature state of one or more fluids in one or more enclosures is determined. Acoustic data is collected using a microphone. Frequency domain features are determined based on the acoustic data, where the frequency domain features are obtained across a frequency range of the acoustic data. The frequency domain features are correlated to the output of a machine learning acoustic analysis model and the one or more fluids are classified based on temperature based on the correlated one or more frequency domain features. In addition, the machine learning acoustic analysis model is trained by recording acoustic training data using a microphone and collecting temperature data for a fluid across a range of temperatures for the fluid. Frequency domain features are determined across a frequency range of the acoustic training data and the frequency domain features are correlated to the temperature data for a fluid.

A monitoring system for a multi-cell rechargeable energy storage system (RESS) that includes a plurality of battery cells is described. The monitoring system includes a sensor that is arranged to monitor one or multiple heat transfer plates thermally coupled to the plurality of battery cells, a controller is in communication with the sensor. The controller including an instruction set that is executable to monitor, via the sensor, a parameter of the heat transfer plate and detect a thermal runaway event when the parameter of the heat transfer plate exceeds a threshold. The thermal runaway event is communicated to a battery controller.

A monitoring system for a multi-cell rechargeable energy storage system (RESS) that includes a plurality of battery cells is described. The monitoring system includes a sensor that is arranged to monitor one or multiple heat transfer plates thermally coupled to the plurality of battery cells, a controller is in communication with the sensor. The controller including an instruction set that is executable to monitor, via the sensor, a parameter of the heat transfer plate and detect a thermal runaway event when the parameter of the heat transfer plate exceeds a threshold. The thermal runaway event is communicated to a battery controller.

An apparatus and method for real-time sensing of properties in industrial manufacturing equipment are described. The sensing system includes first plural sensors mounted within a processing environment of a semiconductor device manufacturing system, wherein each sensor is assigned to a different region to monitor a physical or chemical property of the assigned region of the manufacturing system, and a reader system having componentry configured to simultaneously and wirelessly interrogate the plural sensors. The reader system uses a single high frequency interrogation sequence that includes (1) transmitting a first request pulse signal to the first plural sensors, the first request pulse signal being associated with a first frequency band, and (2) receiving uniquely identifiable response signals from the first plural sensors that provide real-time monitoring of variations in the physical or chemical property at each assigned region of the system.

An apparatus and method for real-time sensing of properties in industrial manufacturing equipment are described. The sensing system includes first plural sensors mounted within a processing environment of a semiconductor device manufacturing system, wherein each sensor is assigned to a different region to monitor a physical or chemical property of the assigned region of the manufacturing system, and a reader system having componentry configured to simultaneously and wirelessly interrogate the plural sensors. The reader system uses a single high frequency interrogation sequence that includes (1) transmitting a first request pulse signal to the first plural sensors, the first request pulse signal being associated with a first frequency band, and (2) receiving uniquely identifiable response signals from the first plural sensors that provide real-time monitoring of variations in the physical or chemical property at each assigned region of the system.

A temperature state of one or more fluids in one or more enclosures is determined. Acoustic data is collected using a microphone. Frequency domain features are determined based on the acoustic data, where the frequency domain features are obtained across a frequency range of the acoustic data. The frequency domain features are correlated to the output of a machine learning acoustic analysis model and the one or more fluids are classified based on temperature based on the correlated one or more frequency domain features. In addition, the machine learning acoustic analysis model is trained by recording acoustic training data using a microphone and collecting temperature data for a fluid across a range of temperatures for the fluid. Frequency domain features are determined across a frequency range of the acoustic training data and the frequency domain features are correlated to the temperature data for a fluid.

This disclosure relates to a system and method for measuring average temperature of mixed fluid in an enclosed chamber. Measurement is based on two independent principle as measuring variation in acoustic wave velocity and variation in resistivity that works on a single setup. First principle is based on measuring acoustic wave velocity in a known medium, which is isolated from the surrounding. The system comprises a primary pipe and a secondary pipe, wherein the ends of the pipes reside inside the enclosed chamber. The primary pipe is made out of good conductor of heat and filled with air. Ends of the primary pipe is fitted with a transducers have one transmitter at one end and one receiver at another end. Average temperature of the mixed fluid is measured based on the variations in sound velocity of acoustic wave passed through the primary pipe and resistivity variations of the primary pipe.

This disclosure relates to a system and method for measuring average temperature of mixed fluid in an enclosed chamber. Measurement is based on two independent principle as measuring variation in acoustic wave velocity and variation in resistivity that works on a single setup. First principle is based on measuring acoustic wave velocity in a known medium, which is isolated from the surrounding. The system comprises a primary pipe and a secondary pipe, wherein the ends of the pipes reside inside the enclosed chamber. The primary pipe is made out of good conductor of heat and filled with air. Ends of the primary pipe is fitted with a transducers have one transmitter at one end and one receiver at another end. Average temperature of the mixed fluid is measured based on the variations in sound velocity of acoustic wave passed through the primary pipe and resistivity variations of the primary pipe.