Anisotropic elastic properties and subsequently in situ stress properties for a rock formation surrounding a wellbore are computed from rock physics and geomechanical models. Mineralogy data measured from DRIFTS on cuttings from the wellbore and rock physics and geomechanical models that have been log-calibrated in another wellbore are used in the computation. The method includes: (1) Defining and calibrating rock physics and geomechanical models using data from the first wellbore; (2) using DRIFTS analysis to measure mineralogy data on rock cuttings obtained through drilling operation in the second wellbore; and (3) using previously calibrated models to estimate in situ stress properties, including a stress index and the minimum principal stress magnitude.

A method of detecting a vibration node between a non-collocated sensor-actuator pair of a rotatable component includes applying an excitation signal to an actuator of the sensor actuator pair. The method also includes obtaining frequency response data from the sensor-actuator pair. The method further includes analyzing the frequency response data to ascertain a resonant frequency of the rotatable component. The method includes identifying a resonance/anti-resonance peak pair in the frequency response data for the non-collocated sensor-actuator pair. Furthermore, the method includes determining whether the vibration node is located between a sensor and the actuator of the non-collocated sensor-actuator pair based on the resonance/anti-resonance peak pair.

The present invention relates to a system and method for monitoring in real time the nutriment intake (feed and/or water) of farm animals, including but not limited to poultry, turkeys, pigs and cows, based on the measurement and identification of the nutriment uptake sounds and/or the working of the nutriment supply system, while the presence and eating position of the animals is monitored by using real-time image analysis.

Methods and devices for high speed detection of terahertz radiation are provided. A photoacoustic transducer receives a pulse of terahertz (THz) radiation. The transducer may comprise a solid, liquid, or semi-solid material. For example, the transducer may be a composite material having a polymer and radiation absorbing particles. The photoacoustic transducer produces an acoustic wave (e.g., an ultrasound wave) in response to receiving the pulse of THz radiation. An acoustic sensor receives the acoustic wave produced by the photoacoustic transducer and thus provides detection of the THz wave.

A first series of images of a first fluid is received. A first set of fluid characteristics of the first fluid is determined from the first series of images. A second series of images of a second fluid is received. A second set of fluid characteristics of the second fluid is determined from the second series of images. A match is determined to be found between the first set of fluid characteristics and the second set of fluid characteristics. The second fluid is identified based upon determining that the first set of fluid characteristics matches the second set of fluid characteristics.

A system for monitoring the movement of objects, structures, models of structures, cables and the like provides for the acquisition of images with an optical sensing device such as a video camera fixedly mounted at a selected distance from the item studied, in which the images are arranged into frames divided into pixels which are characterized by an intensity reflected or emitted over a selected time interval, and a data processing system to calculate a physical displacement as function of time of the item being studied or a portion of the item being studied based on an output from the video camera, and in some embodiments the system visually distinguishes one or more locations in the frame to indicate a difference in the phase of motion for multiple objects appearing in the frame.

Methods, systems, and devices for determining an acoustic parameter of a downhole fluid using an acoustic assembly. Methods include transmitting a plurality of pulses; measuring values for at least one wave property measured for reflections of the plurality of pulses received at at least one acoustic receiver, including: a first value for a first reflection traveling a first known distance from a first acoustically reflective surface having a first known acoustic impedance, a second value for a second reflection traveling a second known distance substantially the same as the first known distance from a second acoustically reflective surface having a second known acoustic impedance, and a third value for a third reflection traveling a third known distance from a third acoustically reflective surface having a third known acoustic impedance substantially the same as the second acoustic impedance; and estimating the acoustic parameter using the values.

An acoustic device for localized and contactless measurement of viscoelasticity of a product to be analyzed. The device includes a generator of high-frequency ultrasonic pulses; an ultrasonic receiver for receiving the high-frequency ultrasonic pulses; the generator and the receiver being disposed relative to each other such that the high-frequency ultrasonic pulses propagate within the sample to be analyzed. The generator and the receiver are mounted on a tubular connecting sleeve intended to connect together two portions of a pipe in which the product to be analysed is intended to move from one portion to another. The tubular sleeve includes a first mounting zone for the generator and a second mounting zone for the receiver. The tubular sleeve is non-anechoic in the first and second mounting zones and, according to a circumferential distribution, anechoic between the first and second mounting zones.

Systems and methods for material composition detection includes a vessel containing a quantity of a fluid composition therein which has at least a first and second fluids. At least one acoustic transducer is positioned on an exterior sidewall of the vessel. A computerized device has a processor and is in communication with the acoustic transducer. A metric of a property of the first fluid is determined based on a first signal of the acoustic transducer. A metric of a property of the second fluid is determined based on a second signal of the acoustic transducer. A metric of a property of the fluid composition at a point in time is determined based on the metrics of the first and second fluids, and at least a determinable volume of at least a portion of the vessel. A material identity of the fluid composition is determined at the point in time.

A prediction method of part surface roughness and tool wear based on multi-task learning belong to the file of machining technology. Firstly, the vibration signals in the machining process are collected; next, the part surface roughness and tool wear are measured, and the measured results are corresponding to the vibration signals respectively; secondly, the samples are expanded, the features are extracted and normalized; then, a multi-task prediction model based on deep belief networks (DBN) is constructed, and the part surface roughness and tool wear are taken as the output of the model, and the features are extracted as the input to establish the multi-task DBN prediction model; finally, the vibration signals are input into the multi-task prediction model to predict the surface roughness and tool wear.