In example implementations described herein, there are systems and methods for computation of force and moment in the time domain for a physical system including one or more sensors, which can involve obtaining material properties and first modal properties of the physical system; generating a material property matrix from the material properties and second modal properties from the obtained modal properties; measuring, via the sensors, a set of motion responses of the physical system; obtaining first quantities based on the second modal properties and the material property matrix; calculating a first intermediate matrix from the second modal properties and the set of motion responses; recursively computing, for each time step during measurement of the response, a second intermediate matrix based on (1) the first quantities, (2) the second modal properties, (3) the first intermediate matrix, and (4) a previously computed second intermediate matrix from at least one previous time step; and calculating the force and the moment for each time step during the measurement of the set of motion responses based on the second intermediate matrix and the second modal properties.

An object of the present invention is to provide a method of a practical level for performing sensor fusion of multiple vibration sensors such as a seismometer, and in an example, to extend a dynamic range of a high-sensitivity geophone by sensor fusion of the high-sensitivity geophone and a low-sensitivity acceleration geophone. A state related to the high-sensitivity geophone is estimated by capturing, in a Kalman filter, an acceleration record from the low-sensitivity acceleration geophone and a velocity record, or a displacement record, and an acceleration record of the high-sensitivity geophone, and estimating and calculating them as the linear Kalman filter problem with a control input. The high-sensitivity geophone is an actual device, but the state can be estimated using a sensor value of the low-sensitivity acceleration geophone even when the record is saturated. This extends the dynamic range of the high-sensitivity geophone.

An object of the present invention is to provide a method of a practical level for performing sensor fusion of multiple vibration sensors such as a seismometer, and in an example, to extend a dynamic range of a high-sensitivity geophone by sensor fusion of the high-sensitivity geophone and a low-sensitivity acceleration geophone. A state related to the high-sensitivity geophone is estimated by capturing, in a Kalman filter, an acceleration record from the low-sensitivity acceleration geophone and a velocity record, or a displacement record, and an acceleration record of the high-sensitivity geophone, and estimating and calculating them as the linear Kalman filter problem with a control input. The high-sensitivity geophone is an actual device, but the state can be estimated using a sensor value of the low-sensitivity acceleration geophone even when the record is saturated. This extends the dynamic range of the high-sensitivity geophone.

A mat system and method for collecting dynamic comfort data relative to a seat occupied by an occupant, the mat system including a sensor matrix layer configured to be disposed (i) extending along at least a portion of a top surface of a seat bottom and including a first shear force sensor mounted adjacent to the top surface of the seat bottom and configured to measure a first shear force generally parallel to the top surface of the seat bottom, or (ii) extending along a portion of a forward surface of a seat back including a second shear force sensor mounted adjacent to the forward surface of the seat back and configured to measure a second shear force generally parallel to the forward surface of the seat back, or (iii) both. The mat system may also include a temperature sensor, a normal force/pressure sensor or a vibration sensor.

A method analyzing a machine having a rotating shaft includes generating an electric measurement signal dependent on mechanical vibrations from the shaft rotation; sampling the measurement signal to generate a digital measurement data signal; performing a decimation of the digital measurement data signal to achieve a digital signal having a reduced sampling frequency, where the decimation includes controlling the reduced sampling frequency such that the number of sample values per revolution of the shaft is kept at a substantially constant value, and receiving the digital signal at an enhancer input performing a correlation in the enhancer so as to produce an output signal sequence where repetitive signals amplitude components are amplified in relation to stochastic signal components, and performing a condition analysis for analyzing the condition of the machine dependent on the digital signal having a reduced sampling frequency.

A method analyzing a machine having a rotating shaft includes generating an electric measurement signal dependent on mechanical vibrations from the shaft rotation; sampling the measurement signal to generate a digital measurement data signal; performing a decimation of the digital measurement data signal to achieve a digital signal having a reduced sampling frequency, where the decimation includes controlling the reduced sampling frequency such that the number of sample values per revolution of the shaft is kept at a substantially constant value, and receiving the digital signal at an enhancer input performing a correlation in the enhancer so as to produce an output signal sequence where repetitive signals amplitude components are amplified in relation to stochastic signal components, and performing a condition analysis for analyzing the condition of the machine dependent on the digital signal having a reduced sampling frequency.

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.

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.

A detection device and a detection system that detect a whistle sound to estimate the distance to the sound source are provided. The detection device (1) includes a detector (20) that detects a sound wave; storage (30) that contains characteristic information indicating frequencies of a fundamental and harmonics of a whistle sound and levels of the harmonics relative to the fundamental; a frequency analysis unit (41) that determines a frequency spectrum of a sound wave detected by the detector; a determination unit (45) that determines whether the frequency spectrum has peaks of the fundamental and the harmonics and how many times the peaks of the harmonics from the fundamental exceed a preset minimum level; and a distance estimation unit (46) that estimates a distance to a sound source of a whistle sound detected by the detector, based on a relationship between propagation distances and attenuations of a sound wave as well as information on the levels included in the characteristic information and the result of determination by the determination unit.

An ultrasonic bonding apparatus includes an ultrasonic bonding machine having an ultrasonic tool for applying an ultrasonic wave to a bonding target member mounted on a fixed object fixed to a jig, while pressing a bonding member against the bonding target member; and a bonding inspection apparatus for inspecting a bonding quality of the bonding target member and the bonding member. The bonding inspection apparatus includes: a bonded-state measuring device for detecting a vibration in the jig or a housing of the ultrasonic bonding machine equipped with the jig, to thereby output a detection signal; and a bonded-state determination device for determining, in a bonding process for the bonding target member and the bonding member, a bonded state between the bonding target member and the bonding member on the basis of the detection signal outputted by the bonded-state measuring device.