Abstract: A method for early damage recognition of a machine, and program and control unit for executing the method are disclosed. The method is disclosed for early damage recognition, wherein a frequency-transformed signal, filtered of dominant excitations, is supplied to a comparative early damage recognition, and wherein, after the filtering, damage of the machine is recognized by comparing the signal to a comparison value.

Abstract: A method for detecting an abnormal die includes providing a wafer, determining the surrounding dies in accordance with a position of a target die on the wafer, calculating a difference between a value of an electrical characteristic of each of the surrounding dies and a value of an electrical characteristic of the target die to obtain the electrical characteristic deviations, ranking the absolute values of the electrical characteristic deviations to generate a ranking result, and determining the characteristic-related dies from the surrounding dies in accordance with the ranking result, determining a target-related area in accordance with the position of the target die, determining the target-related die from the characteristic-related dies in accordance with the target-related area and determining whether the target die is qualified in accordance with the target-related die.

Abstract: In a general implementation, data regarding a rock sample from a drilling site is received. A thermal-mechanical interaction model is generated based on the rock sample date. The thermal-mechanical interaction model is used to determine a penetration rate and mechanical damage around perforation channels through the modeling of heat that is emitted on an exposed surface of the rock sample by a laser beam emitted from a laser beam source. The determined penetration rate and mechanical damage is used to evaluate an effectiveness of the laser beam source to be used in a perforation at the drilling site.

Abstract: The invention relates to a computer-implemented method for generating an image of a subsurface of an area of interest from seismic data. The method comprises providing seismic wavefields, providing a zero-offset seismic wavefield dataset, determining a seismic velocity parameter model w(x) comprising an initial model w0(x), a low frequency perturbation term ?mb(x) and a high frequency perturbation term ?mr(x), determining an optimal seismic velocity parameter model wopt(x) by computing a plurality of iterations, each iteration comprising calculating and optimizing a cost function, said cost function being dependent on the zero-offset seismic wavefield and on the low frequency perturbation term ?mb(x) as a parameter in the optimization of the cost function, the high frequency perturbation term ?mr(x) being related to the velocity parameter model w(x) to keep the provided zero-offset seismic wavefield data invariant with respect to the low frequency perturbation term ?mb(x).

Abstract: In one embodiment, a system for correcting parallax error is provided. An image is received from a camera and a plurality of points is received from a LiDAR sensor. The points are placed on the image based on coordinates associated with each point. The image is divided into a plurality of cells by placing a grid over the image. For each cell, a minimum distance between the points in the cell and the camera is determined. For each cell, a margin is calculated based on the determined minimum distance. For each cell, points that have a distance from the camera that is greater than the minimum distance plus the margin are removed or deleted. The image and/or the remaining points are then used to provide one or more vehicle functions.

Abstract: Disclosed is a calibration method for a rotating accelerometer gravity gradiometer, wherein linear motion error coefficients, angular motion error coefficients, self-gradient model parameters and scale factors of the rotating accelerometer gravity gradiometer are calibrated once by changing linear motion, angular motion, and self-gradient excitations of the rotating accelerometer gravity gradiometer. The calibrated linear and angular motion error coefficients are used for compensating for motion errors of the gravity gradiometer online, and the calibrated self-gradient model parameters are used for self-gradient compensation. The calibration method provided by the present invention is easy to operate and not limited by any calibration site, thereby being suitable for programmed self-calibration and realizing an important engineering value.

Abstract: A measuring method for a portable electrical energy system includes acquiring a total capacity and an initial electric quantity percentage of each battery pack, detecting a discharging current and a discharging time of each battery pack, calculating a discharging capacity of each battery pack, calculating a remaining electric quantity of each battery pack; calculating a real-time electric quantity percentage of each battery pack; acquiring an open circuit voltage of each battery pack and a real-time internal resistance of a cell unit of each battery pack; calculating a remaining electric quantity of each battery pack; and calculating a remaining electric quantity of the portable electrical energy system. This method can reduce the calculation error of the remaining electric quantity and improve the battery utilization.

Abstract: A method of an electronic device that includes a power source is disclosed. The method determines a health of the power source, a temperature of the power source, and a state of charge of the power source. The method then sets a performance state cap for the electronic device based on at least the health of the power source.

Abstract: A method for determining a wear value of a battery of a mobile electronic device comprises using historical battery status data to estimate an actual capacity Qact of the battery and using a design capacity Qdes of the battery and the estimated actual capacity Qact of the battery to determine the wear value of the battery. A computer program is configured so that, when executed by a processor, the processor implements the method for determining a wear value of a battery of a mobile electronic device.

Abstract: Systems, methods and apparatus for network sensitive data collection are disclosed. A system according to one embodiment can include a plurality of input sensors operatively coupled to a component of an industrial environment and a data collector having a controller. The controller may include: a transmission environment circuit to determine a transmission condition corresponding to transmission of a subset of output data, a network management circuit to update a sensor data transmission protocol, a data collection band circuit to determine at least one collection parameter, a machine learning data analysis circuit to receive output data and learn at least one output data pattern, and a response circuit to adjust an operating parameter of the component based on one of a mismatch or a match of the at least one output data pattern and the state of the component.

Abstract: The present invention discloses a method for measuring an actual temperature of a flame by using all information of a radiation spectrum and a measurement system thereof. The method includes: conducting more theoretical data processing by using energy level structure correction, wherein all information of the radiation spectrum can be used; and by way of a keyboard input manner or a data transmission input manner, acquiring an energy level structure correction parameter, and finally acquiring a more accurate actual temperature value of a measured flame. The method effectively overcomes a defect that the true temperature of the flame can be obtained by only conducting radiance correction through data processing with great calculations when adpted multi-spectral temperature measurement method.

Abstract: A system includes multiple sensors having different, and overlapping, fields of regard and a controller communicatively coupled to sensors. Methods for calibrating the multiple sensors include obtaining data from the sensors, determining optimized transformation parameters for at least one of the sensors, and transforming the data from one sensor projection plane to the other sensor projection plane. The method is an iterative process that uses the metric of mutual information between the data sets, and transformed data sets of the sensors, to determine an optimized set of transformation parameters. The sensors may be a plurality of lidar sensors, a camera and a lidar sensor, or other sets of sensors.

Abstract: A method, device, and system of estimation fatigue life of a technical system are disclosed. The method includes computing a lifing probability distribution for at least one component of the technical system based on material property scatter data and at least one damage scenario associated with the at least one component. Further, the method includes determining a time-damage accumulation for the at least one component by combining plurality of damage scenario and damage accumulation rules for the at least one component. Furthermore, the method includes determining a spatial-damage accumulation and a cumulative time-damage accumulation for each of a plurality of regions in the at least one component. The method also includes determining an integral damage including integral of the spatial-damage accumulation and the cumulative time-damage accumulation for the at least one component based on simulation of the at least one damage scenario and conditional probabilities for the at least one damage scenario.

Abstract: Embodiments of the present disclosure are directed to methods and systems for assessing integrity of chromatography columns, systems, and processes. The methods and systems can comprise one or more of extracting a block and signal combination for analysis, performing a transition analysis, performing one or more statistical process controls, and/or implementing in-process controls based on the statistical process controls.

Abstract: A system for processing acoustic data to identify an event includes a receiver unit including a processor and a memory. The receiver unit is configured to receive a signal from a sensor disposed along a sensor path or across a sensor area. A processing application is stored in the memory. The processing application, when executed on the processor, configures the processor to: receive the signal from the sensor, where the signal includes an indication of an acoustic signal received at one or more lengths along the sensor path or across a portion of the sensor area and the signal is indicative of the acoustic signal across a frequency spectrum; determine a plurality of frequency domain features of the signal across the frequency spectrum; and generate an output comprising the plurality of frequency domain features.

Abstract: An environment sensing method includes the following steps, carried out by a data processor a) defining an occupancy grid comprising a plurality of cells; b) acquiring at least one measurement result from a distance sensor, representative of the distance of one or more nearest targets; and c) computing an occupation probability of the cells of the occupancy grid by applying to the measurement an inverse sensor model stored in a memory device in the form of a data structure representing a plurality of model grids associated to respective distance measurement results, at least some cells of a model grid corresponding to a plurality of contiguous cells of the occupancy grid belonging to a same of a plurality of angular sectors into which the field of view of the distance sensor is divided, and associating a same occupation probability to each one of the plurality of cells.

Abstract: A method is described for seismic imaging including generating extended image gathers by extended reverse time migration of a seismic dataset using an earth model; processing the extended image gathers to generate processed image gathers; performing extended modeling based on the processed image gathers to generate a modeled seismic dataset; enhancing the processed image gathers to generate an enhanced image; performing extended modeling based on the enhanced image gathers to generate a modeled enhanced dataset; differencing the modeled enhanced dataset and the modeled seismic dataset to determine a data residual; inverting the data residual to generate a model residual; updating the earth model based on the model residual to create an updated earth model; performing seismic imaging of the seismic dataset using the updated earth model to create an improved seismic image. The method may be executed by a computer system.

Abstract: A method including: obtaining first LiDAR dataset and second LiDAR dataset of environment from LiDAR database, first LiDAR dataset and second LiDAR dataset being captured at first time period and second time period, respectively, second time period being later than first time period; dividing first and second LiDAR datasets into first and second LiDAR subsets; matching given first LiDAR subset with given second LiDAR subset; detecting first objects and second objects in given first and second LiDAR subsets; determining average offset between locations of first objects and locations of second objects; creating given link between given first object and at least one second object, said second object lying within predefined threshold distance from given first object in direction of average offset; and evaluating validity of given link, based upon whether or not given link satisfies growth criterion, given first object is associated with at most one valid link.

Abstract: Provided are a failure prediction support device, a failure prediction support method, and a failure prediction support program, by which a user can easily know an abnormality in time series data relating to an apparatus. The failure prediction support device includes: a difference detection part, acquiring actual machine time series data being time series data relating to control of an apparatus and simulation time series data being time series data relating to control of the simulated apparatus, and detecting a difference between the actual machine time series data and the simulation time series data; a determination part, determining whether or not the difference satisfies a condition predetermined in relation to an abnormality in the actual machine time series data; and a notification processing part, notifying that the difference has been detected when it is determined that the difference satisfies the condition.

Abstract: According to one aspect, data identifying a component is received, wherein the component is part of a system associated with a wellhead. A location at which the component is positioned relative to one or more other components is identified. The useful remaining operational life of the component is predicted based on at least an operational parameter specific to the location, and the operational history of the component or one or more components equivalent thereto. According to another aspect, a model representing at least a portion of a proposed system associated with a wellhead is generated, the model comprising a plurality of objects, each of which has a proposed location and represents an existing component. The useful remaining operational life for each object is predicted based on an operational parameter at the corresponding proposed location, and data associated with the respective operational history of the existing component.