Abstract: Apparatus and associated methods relate to a self-contained ocean data and acquisition module (SCODAM) configured to mount to a floating body and having a sensor array, geospatial locating engine, wave measurement engine, communication engine to transmit collected data to a remote device, an energy conversion module adapted to convert ambient energy inputs into electrical energy, and an energy storage module configured to receive the converted electrical energy and to supply operating power to the SCODAM. In an illustrative example, the SCODAM may be configured to generate a transfer function based on motion characterization data obtained in a training mode corresponding to motion of the floating body in response to perturbation in a predetermined sequence and to apply the transfer function data obtained by the wave measurement engine to determine wave motion. Various embodiments may advantageously facilitate use of an existing floating body as an ocean data acquisition system (ODAS).

Abstract: A method for inertial sensor error modeling and compensation comprises obtaining multiple bias drift datasets for an elapsed time period for one or more gyroscopes; generating a 3D bias drift data plot using the multiple bias drift datasets; generating a partial bias drift data image based on the 3D bias drift data plot; and inputting the partial bias drift data image into a machine learning algorithm to predict how bias drift evolves over time for the gyroscopes. The machine learning algorithm uses the partial bias drift data image, the elapsed time period, and temperature history to compute a predicted bias over temperature with respect to time, to thereby predict bias drift data for a future time period for the gyroscopes. The machine learning algorithm outputs a completed bias drift image that represents drift data from the elapsed time period and the predicted bias drift data for the future time period.

Abstract: Systems and methods for tracking a heading of an excavator are provided. An initial heading of the excavator platform is obtained and a current azimuthal orientation of the excavator platform is associated with the initial heading. Coordinates of a measurement center of the GNSS device are obtained. Coordinates of a center of rotation of the excavator platform are determined using the initial heading of the excavator platform, the coordinates of the measurement center, and a known spatial relationship between the measurement center of the GNSS device and the center of rotation of the excavator platform. Rotation of the excavator platform is tracked from the initial heading to a first heading using rotation measurements from a swing sensor.

Abstract: A prediction device includes: a communication device that acquires measurement subject data including measurement data of a shape of a foot of a measurement subject person in a loaded state; a storage that stores first sample data in the loaded state and second sample data in an unloaded state, the first sample data and the second sample data being calculated from measurement data of foot shapes of a plurality of samples, the samples being identical both in the loaded state and the unloaded state; and a processor that predicts the shape of the foot of the measurement subject person in the unloaded state. The processor calculates a difference between the measurement subject data and the first sample data, and predicts the shape of the foot of the measurement subject person in the unloaded state based on the difference and the second sample data.

Abstract: A method includes receiving raw machine data; determining topographic attributes and underlying environmental characteristics; encoding the respective topographic attributes and the underlying environmental characteristics in hexagrid data structures; and storing the hexagrid data structures in a memory. A computing system includes a processor; and a memory storing instructions that, when executed by the one or more processors, cause the computing system to: receive raw machine data; determine topographic attributes and underlying environmental characteristics; encode the respective topographic attributes and the underlying environmental characteristics in hexagrid data structures; and store the hexagrid data structures in the memory.

Abstract: Methods and instrumentation for pulse scattering estimation and imaging of scattering parameters in a material object by transmitting a pulse along a transmit beam and directing a receive beam that crosses at least one transmit beam at an angle <45 deg. The receive beam is at least in an azimuth direction at the transmit beam, and records scattered receive signal from the overlap region. A receive interval of the receive signal is gated for further processing to form measurement and/or image signals from cross-beam observation cells.

Abstract: A method for calibrating a position measurement system includes receiving measurement data from the position measurement system and determining that the measurement data includes periodic distortion data. The position measurement system includes a nonius track and a master track. The method also includes modifying the measurement data by decomposing the periodic distortion data into periodic components and removing the periodic components from the measurement data.

Abstract: The present invention discloses an intelligent soft measurement method for wind speed in front of a wind turbine. The method includes: first using laser radar data as a data sample, judging delay orders between input and output by using an AIC or BIC criterion, defining a dynamic difference regression vector according to the delay orders, dividing hyperplanes according to a clustering result by using a machine learning algorithm, and performing dynamic differential input/output nonlinear mapping modeling in a global scope and sub-scopes by using an artificial intelligence dynamic regression algorithm, respectively. Empirical mode decomposition and power spectral density analysis are performed on the wind speed in front of a laser radar measuring machine and the wind speed in front of a soft measurement machine, thereby further verifying the estimation performance of intelligent soft measurement for the wind speed in front of a wind turbine.

Abstract: Sensor device, control system and method of communication between a sensor device and a control system. Sensor devices, control systems and methods for communication between sensor devices and control systems are provided. In these, sensor data are transmitted via first interfaces and redundant sensor data and/or other data are transmitted via second interfaces.

Abstract: A system and method model a time series from missing data by imputing missing values, denoising measured but noisy values, and forecasting future values of a single time series. A time series of potentially noisy, partially-measured values of a physical process is represented as a non-overlapping matrix. For several classes of common model functions, it can be proved that the resulting matrix has a low rank or approximately low rank, allowing a matrix estimation technique, for example singular value thresholding, to be efficiently applied. Applying such a technique produces a mean matrix that estimates latent values, of the physical process at times or intervals corresponding to measurements, with less error than previously known methods. These latent values have been denoised (if noisy) and imputed (if missing). Linear regression of the estimated latent values permits forecasting with an error that decreases as more measurements are made.

Abstract: Aspects relate to system and methods for determining a user specific mission operational performance, using machine-learning processes.

Abstract: Embodiments match sensor data output by a sensor to a trained pattern. Embodiments form a plurality of windows of an identified pattern from the sensor data, each of the plurality of windows having a substantially equal window length to a length of the trained pattern. For each of the windows, embodiments generate a corresponding first Symbolic Aggregate approximation (“SAX”) word, determine a Hamming distance between the first SAX word and a second SAX word corresponding to the trained pattern, and determine a final distance score based on coefficients between the first SAX word and the second SAX word. For each of the windows, embodiments determine a number of positions in the first SAX word that do not contribute to the final distance score, update the Hamming distance after eliminating the number of positions and determine an average distance based on the final distance score and the updated Hamming distance.

Abstract: Embodiments of the Invention provide real-time portable, deployable data acquisition units and monitoring consoles that can be used in combination with radio communication technology to provide for monitoring of wildfires and local weather conditions to aid in fighting wildfires.

Abstract: The present disclosure relates to a computer-implemented method of, a data processing system for, and a computer program product for indicating machine failures as well as to a corresponding machine and a computer-implemented method of training a neural network for indicating machine failures. At least one input signal based on at least one physical quantity of at least one machine part is transformed into at least one feature. A neural network predicts a class and/or a severity of at least one machine failure based on the at least one feature.

Abstract: A system includes one or more processors located remote from a plurality of containers configured to store recyclable material. The one or more processors are configured to receive image data generated by an imaging device positioned to have a field of view of an interior of a first container of the containers. The image data depicts the recyclable material within the first container. The one or more processors receive one or more weight measurements of the first container with the recyclable material therein and determine one or more characteristics of the recyclable material within the first container based on at least one of the image data or the one or more weight measurements. The one or more processors schedule a pickup date for the first container based on the one or more characteristics of the recyclable material that are determined.

Abstract: Methods and systems for performing transient processes may include: providing a path and path thresholds for an operational condition as a function of progress of a transient process based on historical data of previously performed transient processes; performing the transient process in a chemical reactor using operational parameters; measuring the operational condition of the transient process as a function of the progress of the transient process; and adjusting one or more of the operational parameters during the progress of the transient process to maintain the operational condition within the path thresholds.

Abstract: Systems, methods, and other embodiments associated with autonomous discrimination of operation vibration signals are described herein. In one embodiment, a method includes partitioning a frequency spectrum of output into a plurality of discrete bins, wherein the output is collected from vibration sensors monitoring a reference device; generating a representative time series signal for each bin while the device is operated in a deterministic stress load; generating a PSD for each bin by converting each signal from the time domain to the frequency domain; determining a maximum power spectral density value and a peak frequency value for each bin; selecting a subset of the bins that have maximum PSD values exceeding a threshold; assigning the representative time series signals from the selected subset of bins as operation vibration signals indicative of operational load on the reference device; and configuring a machine learning model based on at least the operation vibration signals.

Abstract: A method for alerting a user on an electronic device is described. The method includes identifying a signal at an ultrasound transmission frequency received at a first electronic device from a second electronic device. Further, the method includes receiving timing information corresponding to an exchange of an ultrasound transmission between the first electronic device and the second electronic device. Furthermore, a first distance value between the first electronic device and the second electronic device is computed by performing a time of flight estimation using the timing information. Furthermore, the first distance value is refined by using an output of a machine learning model to determine a second distance value. Furthermore, the method includes generating an alert based on the comparison of the second distance value with a predefined threshold distance value. In some examples, the alert can be indicative of a violation of a physical distancing norm in an environment.

Abstract: Methods and systems for analyzing an industrial structure are provided. With a plurality of sensors (e.g. FBGs and/or piezoelectric transducers and/or electromagnetic acoustic transducers) deployed in, on or in proximity to the structure, sensors are interrogated and a function representative of the impulse response of the structure is determined by passive inverse filter. Subsequently, a map of the propagation of the elastic waves through the structure is determined via various modalities, and in particular by tomography (of bulk or guided waves, by analysis of time of flight or of the complete signal). Embodiments especially relate to the management of the number and position of the sensors, to the use of artificial noise sources, and to automatically controlling the sensors and/or noise sources to monitor the health of the structure, or even to view the dynamic behavior of the structure.

Abstract: Methods and systems for a monitoring system for data collection in an industrial environment including a data collector communicatively coupled to a plurality of input channels connected to data collection points related to machine components, wherein at least one of the plurality of input channels is connected to a data collection point on a rotating machine component; a data acquisition circuit structured to interpret a plurality of detection values from the collected data, each of the plurality of detection values corresponding to at least one of the plurality of input channels; and an expert system analysis circuit structured to analyze the collected data, wherein the expert system analysis circuit determines a failure state for the rotating machine component based on analysis of the plurality of detection values, wherein upon determining the failure state the expert system analysis circuit provides the failure state to a data storage.