The disclosure relates to a method for determining and/or monitoring the state of a transformer oil, comprising the steps of a) performing an acoustic spectroscopy of the transformer oil, multiple ultrasonic emission signals of different frequencies and/or amplitudes being emitted into the transformer oil and corresponding reflected and/or transmitted ultrasonic reception signals of different frequencies and/or amplitudes being received after having passed through the transformer oil; and b) comparing the ultrasonic emission signals with the corresponding ultrasonic reception signals, an n-dimensional function characteristic of the transformer oil being ascertained; and c) matching the ascertained characteristic n-dimensional function from step b) with a reference function of corresponding dimension known for transformer oils, a reference transformer oil being determined; and d) registering a first value of at least one characteristic physical property of the transformer oil; and e) comparing the first value with a corresponding value of the reference transformer oil; and f) ascertaining the state of the transformer oil based on the comparison performed in step e). Furthermore, the disclosure relates to a device (100, 200) for determining and/or monitoring the state of a transformer oil.

The disclosure relates to a method for determining and/or monitoring the state of a transformer oil, comprising the steps of a) performing an acoustic spectroscopy of the transformer oil, multiple ultrasonic emission signals of different frequencies and/or amplitudes being emitted into the transformer oil and corresponding reflected and/or transmitted ultrasonic reception signals of different frequencies and/or amplitudes being received after having passed through the transformer oil; and b) comparing the ultrasonic emission signals with the corresponding ultrasonic reception signals, an n-dimensional function characteristic of the transformer oil being ascertained; and c) matching the ascertained characteristic n-dimensional function from step b) with a reference function of corresponding dimension known for transformer oils, a reference transformer oil being determined; and d) registering a first value of at least one characteristic physical property of the transformer oil; and e) comparing the first value with a corresponding value of the reference transformer oil; and f) ascertaining the state of the transformer oil based on the comparison performed in step e). Furthermore, the disclosure relates to a device (100, 200) for determining and/or monitoring the state of a transformer oil.

A method for identifying a mechanical impedance of an electromagnetic load may include generating a waveform signal for driving an electromagnetic load and, during driving of the electromagnetic load by the waveform signal or a signal derived therefrom, receiving a current signal representative of a current associated with the electromagnetic load and a back electromotive force signal representative of a back electromotive force associated with the electromagnetic load. The method may also include implementing an adaptive filter to identify parameters of the mechanical impedance of the electromagnetic load, wherein an input of a coefficient control for adapting coefficients of the adaptive filter is a first signal derived from the back electromotive force signal and a target of the coefficient control for adapting coefficients of the adaptive filter is a second signal derived from the current signal.

A method for identifying a mechanical impedance of an electromagnetic load may include generating a waveform signal for driving an electromagnetic load and, during driving of the electromagnetic load by the waveform signal or a signal derived therefrom, receiving a current signal representative of a current associated with the electromagnetic load and a back electromotive force signal representative of a back electromotive force associated with the electromagnetic load. The method may also include implementing an adaptive filter to identify parameters of the mechanical impedance of the electromagnetic load, wherein an input of a coefficient control for adapting coefficients of the adaptive filter is a first signal derived from the back electromotive force signal and a target of the coefficient control for adapting coefficients of the adaptive filter is a second signal derived from the current signal.

A predicting device, including a processor configured to: acquire displacement data that expresses a time series of displacements at respective points in time that are input to a vibration proofing member, and velocity data that expresses a time series of velocities at respective points in time that are input to the vibration proofing member; generate first load data of the vibration proofing member by inputting the acquired displacement data and velocity data into a model that is for inferring, from the displacement data and the velocity data, load data; generate second load data of the vibration proofing member by inputting the acquired displacement data and velocity data into a regression trained model that is for inferring, from the displacement data and the velocity data, load data; and infer load data relating to the vibration proofing member by adding together the generated first load data and the generated second load data.

A predicting device, including a processor configured to: acquire displacement data that expresses a time series of displacements at respective points in time that are input to a vibration proofing member, and velocity data that expresses a time series of velocities at respective points in time that are input to the vibration proofing member; generate first load data of the vibration proofing member by inputting the acquired displacement data and velocity data into a model that is for inferring, from the displacement data and the velocity data, load data; generate second load data of the vibration proofing member by inputting the acquired displacement data and velocity data into a regression trained model that is for inferring, from the displacement data and the velocity data, load data; and infer load data relating to the vibration proofing member by adding together the generated first load data and the generated second load data.

A predicting device, including a processor configured to: acquire displacement data that expresses a time series of displacements at respective points in time that are input to a vibration proofing member, and velocity data that expresses a time series of velocities at respective points in time that are input to the vibration proofing member; generate first load data of the vibration proofing member by inputting the acquired displacement data and velocity data into a model that is for inferring, from the displacement data and the velocity data, load data; generate second load data of the vibration proofing member by inputting the acquired displacement data and velocity data into a regression trained model that is for inferring, from the displacement data and the velocity data, load data; and infer load data relating to the vibration proofing member by adding together the generated first load data and the generated second load data.

A predicting device, including a processor configured to: acquire displacement data that expresses a time series of displacements at respective points in time that are input to a vibration proofing member, and velocity data that expresses a time series of velocities at respective points in time that are input to the vibration proofing member; generate first load data of the vibration proofing member by inputting the acquired displacement data and velocity data into a model that is for inferring, from the displacement data and the velocity data, load data; generate second load data of the vibration proofing member by inputting the acquired displacement data and velocity data into a regression trained model that is for inferring, from the displacement data and the velocity data, load data; and infer load data relating to the vibration proofing member by adding together the generated first load data and the generated second load data.

An acoustic measuring device suitable for performing measurements on a surface in contact with a flow. This acoustic measuring device comprises an acoustic surface delimiting a cavity, which has an axis of revolution, which comprises a recess centered with respect to the axis of revolution, configured to house an acoustic sensor and which, in a longitudinal plane passing through the axis of revolution, follows a logarithmic profile which extends from a first edge separating the recess and the acoustic surface.

Methods, systems, and devices for determining an acoustic parameter of a downhole fluid using an acoustic assembly. Methods include transmitting a plurality of pulses; measuring values for at least one wave property measured for reflections of the plurality of pulses received at at least one acoustic receiver, including: a first value for a first reflection traveling a first known distance from a first acoustically reflective surface having a first known acoustic impedance, a second value for a second reflection traveling a second known distance substantially the same as the first known distance from a second acoustically reflective surface having a second known acoustic impedance, and a third value for a third reflection traveling a third known distance from a third acoustically reflective surface having a third known acoustic impedance substantially the same as the second acoustic impedance; and estimating the acoustic parameter using the values.