Abstract: An abnormal temperature detection device includes a temperature acquirer configured to acquire temperature data, a preprocessor configured to perform preprocessing for calculating difference data indicating a difference sequence in the temperature data, generating substituted data in which either of a piece of difference data which is a positive number or a piece of difference data which is a negative number is substituted with zero, and calculating a similarity between the substituted data and reference data obtained from training data in which normality or abnormality has been identified, a learner configured to perform machine learning on the similarity calculated by the preprocessor and output an identification function, and a determiner configured to determine whether temperature data for detection acquired by the temperature acquirer and subjected to the preprocessing by the preprocessor is normal or abnormal by using the identification function.

Abstract: A relearning necessity determination method is provided for determining a necessity of relearning of a learned diagnostic model in a machine tool including a machining abnormality diagnosing unit. The machining abnormality diagnosing unit determines normal or abnormality of machining using the diagnostic model generated through machine learning. The method includes storing a cumulative cutting time or a cumulative cutting distance of a tool mounted to the machine tool as a tool usage, storing the tool usage when the machining abnormality diagnosing unit diagnoses the machining as machining abnormality, and determining the necessity of the relearning of the diagnostic model based on a frequency distribution of the tool usage stored in the storing of the tool usage.

Abstract: A state-of-charge (SOC) online estimation method of an intelligent battery includes steps of performing online estimation on the SOC based on a real-time estimation model, wherein the real-time estimation model is based on an equivalent circuit model, and then obtaining online estimates of the SOC through the SOC-OCV (open circuit voltage) relationship, the current-voltage relationship under different working conditions, and the current terminal voltage and temperature of the intelligent battery. The intelligent battery that is able to apply the SOC online estimation method includes a battery cell and a cell management unit, wherein the cell management unit includes a sensor module, a switching device, a controller module, a communication module and a printed circuit board (PCB), the sensor module includes a voltage sensor and a temperature sensor; the voltage sensor, the temperature sensor, the switching device, the controller module and the communication module are integrated on the PCB.

Abstract: The present disclosure relates to a method for analysis of an average deuterium substitution rate of a deuterium-substituted sample using information of a 1H-NMR spectrum of the deuterium-substituted sample.

Abstract: The present disclosure relates to a sensor system having at least one measuring point having at least one first sensor and one measuring transducer. The first sensor is configured to output first sensor signals that are a function of a first measurand of a measuring medium present at the measuring point. The measuring transducer is connected to the first sensor in order to receive the first sensor signals and comprises an evaluation application which is configured to determine one additional piece of information that is different from the first measurand using an evaluation algorithm on the basis of at least the first sensor signals. The sensor system furthermore comprises a higher-level data processing structure, such as a server or a cloud. Both the higher-level data processing structure and the measuring transducer are configured to execute a training application configured to train the evaluation algorithm.

Abstract: An embodiment of the present invention provides a counting information updating method for a portable electronic device having a plurality of spheres connected with each other. The method includes: generating an angular velocity signal by a first sensor of the portable electronic device and generating an acceleration signal by a second sensor of the portable electronic device in response to a sphere moving operation; and estimating counting information corresponding to the sphere moving operation by using the angular velocity signal with an assistance of the acceleration signal.

Abstract: A method for predicting heaving motion parameters of a semi-submersible offshore platform based on heaving acceleration includes: in heaving motion of a semi-submersible offshore platform, representing heaving acceleration of the semi-submersible offshore platform based on a linear potential flow theory; considering a noise influence of a heaving motion measurement marine environment, a low-frequency influence caused by a slow change of the environment and an influence caused by a baseline drift error of an acceleration sensor, introducing a noise term, a low-frequency change term and a baseline drift error term, and uniformly representing the noise term, the low-frequency change term and the baseline drift error term by a unified Prony sequence; and removing a drift term from uniformly represented heaving acceleration, establishing a relationship between the heaving acceleration and heaving motion parameters in terms of the remaining Prony sequence with the drift term being removed, and estimating the heavin

Abstract: A method for determining a temperature estimating model for estimating a temperature in a battery module includes: estimating temperatures using a preliminary verification profile with models based on respective parameter sets; calculating first errors corresponding to differences between measured and estimated temperatures; comparing whether respective first errors for the respective parameter sets are less than a first threshold value; for parameter sets having a first error that is less than the first threshold value, calculating a maximum error; extracting a second parameter set by calculating a product of the maximum error and a first value plus a product of the first error and a second value; estimating temperatures according to reverification profile; calculating a second error corresponding to a difference between measured temperatures of the reverification profile and estimated temperatures; and finalizing the model when the second error is less than a third threshold value.

Abstract: Methods for diagnosing failure mechanisms and for predicting lifetime of metal batteries include monitoring rest voltage and Coulombic Efficiency over relatively few cycles to provide profiles that indicate, by the trends thereof, a particular failure mechanism (e.g., electrolyte depletion, loss of metal inventory, increased cell impedance). The methods also include cycling over relatively few cycles an anode-free cell, having the same cathode and electrolyte as the metal battery, but with a current collector instead of the anode. Discharge capacity is monitored and profiled, and a discharge capacity curve is fitted to the discharge capacity profile to discern a capacity retention per cycle. The lifetime of the metal battery is determined using the capacity retention per cycle discerned from the anode-free cell. Related systems include a metal-based battery and an anode-free cell or a battery cell reconfigurable between a metal-based and an anode-free cell.

Abstract: A system and method for redundant electric power for an electric aircraft is provided. The system includes a plurality of battery packs which includes at least a first pack monitor unit and at least a second pack monitor unit configured to detect a first battery pack datum and a second battery pack datum, and transmit the pair of battery pack datum to a controller. Each battery pack. The system further includes a contactor coupled to the electric aircraft, a plurality of loads communicatively coupled to each battery pack of the plurality of battery packs, and a controller, wherein the controller is designed and configured to receive the first battery pack and the second battery pack datum, compare the first battery pack datum to the second battery pack datum as a function of a differential threshold, and generate an alert datum as a function of the comparison.

Abstract: Included are embodiments for remotely determining a battery characteristic. Some embodiments include searching for a first wireless signal that identifies the energy storage device and, in response to receiving the first wireless signal, determining a current charge level of the energy storage device. Some embodiments include receiving a second wireless signal from the energy storage device, determining from the second wireless signal, whether the current charge level of the energy storage device reaches a predetermined threshold, and in response to determining that the current charge level of the energy storage device reaches the predetermined threshold, facilitating replacement of the battery.

Abstract: A battery cell monitor circuit includes a first serial transceiver, a second serial transceiver, and a command decoder. The command decoder is configured to cause the first serial transceiver or the second serial transceiver to transmit a response to a battery monitoring command based on a response direction field included in the battery monitoring command.

Abstract: A disruptor adjustment system comprising: a disruptor assembly configured to disrupt a volume of smelt flowing from a smelt spout into a dissolving tank, wherein the disruptor assembly comprises an actuator operatively engaged to a disruptor, a sensor configured to record process data from the recovery boiler; and a control system configured to receive a sensor output signal from the sensor, wherein the sensor output signal indicates the process data at a measured time, wherein the control system is further configured to compare the sensor output signal to a programmed operation range, and to send a disruptor input signal to the disruptor assembly to adjust a disruptor operating condition if the process data of the sensor output signal is outside of the programmed operation range. In certain exemplary embodiments, the sensor is an image capture device. In certain exemplary embodiments, the disruptor assembly can be adjusted remotely.

Abstract: A multi-stage inversion method for deblending seismic data includes: a) acquiring blended seismic data from a plurality of seismic sources; b) constructing an optimization model that includes the acquired blended seismic data and unblended seismic data; c) performing sparse inversion, via a computer processor, on the optimization model; d) estimating high-amplitude coherent energy from result of the performing sparse inversion in c); e) re-blending the estimated high-amplitude coherent energy; and f) computing blended data with an attenuated direct arrival energy.

Abstract: An optical pulse measuring method measuring an optical pulse generated from a pulse light source is provided. The method includes: splitting the optical pulse and then focusing them at a measuring point, so as to generate gas plasma by the autocorrelation of the split optical pulses; receiving the sound signal from the gas plasma and generate a plasma sound signal; and using the plasma sound signal to calculate the characteristics of the optical pulse. A measuring device is also provided.

Abstract: A topography apparatus may be coupled to an e-vaping device, within an interior defined by a housing of the e-vaping device, such that the topography apparatus may be coupled to an e-vaping device that may generate vapor independently of the topography apparatus. The topography apparatus may generate and communicate vapor topography data associated with vapor generation by the e-vaping device without altering an external appearance or vapor-generation performance of the e-vaping device. The topography apparatus may be detachably coupled to the interior of the e-vaping device. The topography apparatus includes an interface assembly configured to couple with a power supply, control circuitry, and/or sensor of the e-vaping device. Such coupling may include coupling with internal power or communication conduits of the e-vaping device, such that the topography apparatus taps into power and/or communication lines of the e-vaping device without requiring modification of the circuitry of the e-vaping device.

Abstract: A plurality of known compounds with known CCS values is analyzed using a DMS device. The DMS device determines how the intensities of their transmitted ions vary with different separation voltages (SVs) and compensation voltages (CVs). A machine learning algorithm builds a data model from the known m/z value, known CCS value, and measured pairs of CV and SV values that provide optimal transmission through the DMS device for each of the known compounds. An unknown compound with an unknown CCS value is then analyzed. The DMS device determines how the intensity of its ions varies with the same different SVs and CVs. Finally, the machine learning algorithm predicts the CCS value of the unknown compound from the data model, the known m/z of the unknown compound, and the measured pairs of CV and SV values that provide optimal transmission through the DMS device for the unknown compound.

Abstract: The present disclosure relates to a sensor system having at least one measuring point having at least one first sensor and one measuring transducer. The first sensor is configured to output first sensor signals that are a function of a first measurand of a measuring medium present at the measuring point. The measuring transducer is connected to the first sensor in order to receive the first sensor signals and comprises an evaluation application which is configured to determine one additional piece of information that is different from the first measurand using an evaluation algorithm on the basis of at least the first sensor signals. The sensor system furthermore comprises a higher-level data processing structure, such as a server or a cloud. Both the higher-level data processing structure and the measuring transducer are configured to execute a training application configured to train the evaluation algorithm.

Abstract: An optical scanning apparatus includes first and second light sources, a rotatable polygonal mirror, a motor, first and second mirrors, first and second lenses, and a casing. Within a mounting range, a top wall of an accommodating portion is provided with at least one projection projecting toward an opening of the accommodating portion. The projection extends from a first side wall to a second side wall of the accommodating portion. The top wall includes a recess formed opposite from the projection, and is free from a portion projecting toward the opening over a range from the first side wall to the second side wall, other than the projection in the mounting range. A free end portion of the projection is in a position remoter from the opening than a reflecting surface of the rotatable polygonal mirror is with respect to a rotational axis direction of the motor.

Abstract: A computing system obtains test data for a particle source. The test data was generated by the particle source when the particle source was caused to emit particles. The test data comprises a first set of measurements of a first type and a second set of measurements of a second type. The computing system applies a data agnostic predictive model to the test data. The data agnostic predictive model is generated without a parametric analysis of variables of the first type and variables of the second type. The data agnostic predictive model outputs, based upon the test data, a value that is indicative of whether or not the test data is abnormal. Based upon the value, the computing system outputs an indication that the particle source was operating sub-optimally when emitting the particles.