A method for detecting low-frequency oscillations, in particular subsynchronous resonances, in an electrical supply grid is provided. The grid has a line voltage with a rated line frequency. The method comprises recording first and second series of measurements each for performing a frequency analysis (FFT). The method includes performing a lower frequency analysis for the first series for a lower frequency range and forming a lower amplitude spectrum. The method includes performing an upper frequency analysis for the second series for an upper frequency range and forming an upper amplitude spectrum. The method includes testing whether a low-frequency oscillation component can be identified in the lower amplitude spectrum, and testing whether a low-frequency oscillation component can be identified in the upper amplitude spectrum, where the presence of a low-frequency oscillation is assumed when a low-frequency oscillation component is identified in at least one of the lower and upper amplitude spectra.

A method for detecting low-frequency oscillations, in particular subsynchronous resonances, in an electrical supply grid is provided. The grid has a line voltage with a rated line frequency. The method comprises recording first and second series of measurements each for performing a frequency analysis (FFT). The method includes performing a lower frequency analysis for the first series for a lower frequency range and forming a lower amplitude spectrum. The method includes performing an upper frequency analysis for the second series for an upper frequency range and forming an upper amplitude spectrum. The method includes testing whether a low-frequency oscillation component can be identified in the lower amplitude spectrum, and testing whether a low-frequency oscillation component can be identified in the upper amplitude spectrum, where the presence of a low-frequency oscillation is assumed when a low-frequency oscillation component is identified in at least one of the lower and upper amplitude spectra.

A method evaluates a frequency spectrum representative of at least one time-dependent signal, the at least one time dependent signal being derived from an output from a measuring device under predetermined measuring device operating conditions. The time-dependent signal, includes a portion being representative of a wanted signal, and a portion being representative of noise. The method includes the steps of determining, based on the frequency spectrum of the signal, a value representative of the noise floor, identifying, based on the frequency spectrum of the signal derived under the predetermined operating condition, a peak component, and if the peak component satisfies a relative peak criterion determined on the basis of the determined value representative of the noise floor, determining the wanted signal by applying a predetermined algorithm. The invention further relates to a method for determining flow of a measuring device, and a sensor.

A method evaluates a frequency spectrum representative of at least one time-dependent signal, the at least one time dependent signal being derived from an output from a measuring device under predetermined measuring device operating conditions. The time-dependent signal, includes a portion being representative of a wanted signal, and a portion being representative of noise. The method includes the steps of determining, based on the frequency spectrum of the signal, a value representative of the noise floor, identifying, based on the frequency spectrum of the signal derived under the predetermined operating condition, a peak component, and if the peak component satisfies a relative peak criterion determined on the basis of the determined value representative of the noise floor, determining the wanted signal by applying a predetermined algorithm. The invention further relates to a method for determining flow of a measuring device, and a sensor.

A method evaluates a frequency spectrum representative of at least one time-dependent signal, the at least one time dependent signal being derived from an output from a measuring device under predetermined measuring device operating conditions. The time-dependent signal, includes a portion being representative of a wanted signal, and a portion being representative of noise. The method includes the steps of determining, based on the frequency spectrum of the signal, a value representative of the noise floor, identifying, based on the frequency spectrum of the signal derived under the predetermined operating condition, a peak component, and if the peak component satisfies a relative peak criterion determined on the basis of the determined value representative of the noise floor, determining the wanted signal by applying a predetermined algorithm. The invention further relates to a method for determining flow of a measuring device, and a sensor.

A method for detecting low-frequency oscillations, in particular subsynchronous resonances, in a grid is provided. The method includes recording a series of measurements, having measurement points, of a grid variable over a measurement time period, for performing a frequency analysis and multiplying the series a time-dependent sinusoidal test function for the same measurement time period. The test function is characterized by a test frequency and a test angle as phase angle. The series for each measurement point is multiplied by the test function in order to obtain a test product for each measurement point. The method includes adding the test products taking into consideration the mathematical sign thereof to give a product sum, and evaluating, depending on the product sum, whether the series of measurements has a low-frequency oscillation having a frequency in the region of the test frequency and a phase angle in the region of the test angle.

A method for detecting low-frequency oscillations, in particular subsynchronous resonances, in a grid is provided. The method includes recording a series of measurements, having measurement points, of a grid variable over a measurement time period, for performing a frequency analysis and multiplying the series a time-dependent sinusoidal test function for the same measurement time period. The test function is characterized by a test frequency and a test angle as phase angle. The series for each measurement point is multiplied by the test function in order to obtain a test product for each measurement point. The method includes adding the test products taking into consideration the mathematical sign thereof to give a product sum, and evaluating, depending on the product sum, whether the series of measurements has a low-frequency oscillation having a frequency in the region of the test frequency and a phase angle in the region of the test angle.

A harmonic detection system (1) comprises a measurement component (71), a harmonic abnormality determination unit (561), and a smartphone (9). The measurement component (71) is installed at a specific position on a distribution line constituting a distribution network (100), and measures data related to the current of the distribution line. The harmonic abnormality determination unit (561) uses some or all of the data related to current as detection data to detect abnormality related to harmonics. The smartphone (9) is owned by a user (G), and notifies the user that an abnormality has occurred in the distribution line when a harmonic is detected.

A detection method is provided to detect the normal harmonics of the first harmonic of Earth's atmospheric electromagnetic resonance frequency of 15.3 Hz and abnormal frequencies of corresponding to neurological diseases. The method will assist and guide neurological specialists in providing a good treatment to the patients in order to reduce the abnormal frequencies in such a way as to control the disease and maintain a balanced well-being of the patient.

A detection method is provided to detect the normal harmonics of the first harmonic of Earth's atmospheric electromagnetic resonance frequency of 15.3 Hz and abnormal frequencies of corresponding to neurological diseases. The method will assist and guide neurological specialists in providing a good treatment to the patients in order to reduce the abnormal frequencies in such a way as to control the disease and maintain a balanced well-being of the patient.