A method of probabilistically estimating a velocity of a plunger of a beam pump may comprise continuously monitoring well acoustics using a plurality of passive acoustic sensors attached to external structures of the beam pump; digitizing outputs of the plurality of passive acoustic sensors and sending the digitized outputs to a computing device for storage and processing; and using the digitized outputs of the plurality of passive acoustic sensors, estimating a probability of the velocity of the plunger using a hidden Markov model (HMM) to represent a probability of a position and the probability of the velocity of the plunger, the HMM comprising a state space model and an observational model.

A method of probabilistically estimating a velocity of a plunger of a beam pump may comprise continuously monitoring well acoustics using a plurality of passive acoustic sensors attached to external structures of the beam pump; digitizing outputs of the plurality of passive acoustic sensors and sending the digitized outputs to a computing device for storage and processing; and using the digitized outputs of the plurality of passive acoustic sensors, estimating a probability of the velocity of the plunger using a hidden Markov model (HMM) to represent a probability of a position and the probability of the velocity of the plunger, the HMM comprising a state space model and an observational model.

The measurement system 100 includes: a measurement apparatus 20 that measures vibrations of an object 40; an imaging apparatus 30 that is located so as to capture an image of the measurement apparatus 20; and a correction processing apparatus 10. the correction processing apparatus 10 includes: a displacement calculation unit 11 that calculates a displacement of the measurement apparatus 20 based on time-series images of the measurement apparatus 20 output from the imaging apparatus 30; a movement amount calculation unit 12 that calculates an amount of movement of the measurement apparatus 20 relative to the imaging apparatus 30, based on the displacement; and a correction processing unit 13 that corrects vibrations of the object measured by the measurement apparatus 20, using the calculated amount of movement of the measurement apparatus 20.

A method for diagnosing a problematic noise source based on big data information include: measuring noise data of a powertrain of a vehicle by using a real-time noise measurement device, and converting the noise data into a signal that can be input to a portable device for diagnosing the problematic noise source through an interface device; analyzing a noise through a deep learning algorithm of an artificial intelligence on a converted signal, and diagnosing the problematic noise source as a cause of the noise; and displaying the cause of the noise by outputting a diagnostic result as the problematic noise source, and transmitting the diagnostic result to the portable device.

A method for diagnosing a problematic noise source based on big data information include: measuring noise data of a powertrain of a vehicle by using a real-time noise measurement device, and converting the noise data into a signal that can be input to a portable device for diagnosing the problematic noise source through an interface device; analyzing a noise through a deep learning algorithm of an artificial intelligence on a converted signal, and diagnosing the problematic noise source as a cause of the noise; and displaying the cause of the noise by outputting a diagnostic result as the problematic noise source, and transmitting the diagnostic result to the portable device.

A multisensory system provides both temporal and spatial coverage capacities for auto-detection of bird collision events. The system includes an apparatus having a first circuitry to capture and store a series of images or video of a blade of a wind turbine; and a memory to store the images from the first circuitry. The apparatus also has one or more sensors to continuously sense vibration of the blade or for acoustic recordings; and a second circuitry to analyze the sensor data stream and/or the series of images or video to identify a cause of the vibration and to trigger the camera(s). A communication interface transmits data from the second circuitry to another device, wherein the second circuitry applies artificial intelligence or machine learning to control sensitivity of the one or more sensors.

A system includes a vertical charge pump assembly. The vertical charge pump assembly includes a top portion adjacent to a first end of the vertical charge pump assembly and a bottom portion adjacent to a second end of the vertical charge pump assembly. A pump motor is disposed in the top portion and an impeller is disposed in the bottom portion within a bowl casing. A shaft is disposed within a central passageway and connects the pump motor with the impeller. The vertical charge pump assembly also includes an inlet at the second end below the bowl casing. The pump inlet and the bowl casing are configured to be immersed in a fluid, and the vertical charge pump assembly is configured to pump the fluid into the inlet and upwards through the central passageway by rotation of the impeller. A vibration sensor is disposed on an external surface of the bottom portion, on or proximate to the bowl casing and the pump inlet. The vibration sensor includes a substrate comprising a polymer and a resonant layer disposed on a surface of the substrate. The resonant layer comprises an electrically conductive nanomaterial and is configured to produce a resonant response in response to receiving a radio frequency signal.

The innovation disclosed and claimed herein, in at least one aspect thereof, comprises continuously charging a cell phone while the user utilizes the cellular phone for ordinary activities (e.g. posting to social media sites, texting, talking, etc.). The signals from routine cellular phone operations will send signals to a photocoupler or other dedicated sensor. The dedicated sensor will output current to drive a magnet mechanism which will in turn drive a fan that generates current to charge to a super/ultra-capacitor.

The innovation disclosed and claimed herein, in at least one aspect thereof, comprises continuously charging a cell phone while the user utilizes the cellular phone for ordinary activities (e.g. posting to social media sites, texting, talking, etc.). The signals from routine cellular phone operations will send signals to a photocoupler or other dedicated sensor. The dedicated sensor will output current to drive a magnet mechanism which will in turn drive a fan that generates current to charge to a super/ultra-capacitor.

A disclosed example includes providing vibration information to a model, the vibration information corresponding to a first vibration measured at a first mobile device when the first mobile device is in a state of non-use by a user, the model based on a plurality of vibration patterns that correspond to second vibrations measured by second mobile devices in different environments; identifying, using the model, one of the vibration patterns that corresponds to the vibration information; determining an environment of the first mobile device based on the one of the vibration patterns; and instructing the first mobile device to modify a functionality of the first mobile device based on the environment.