Abstract: Techniques for monitoring and/or operating a power system asset are provided. A series of sets of first model parameter values (71-73) of a power system asset model is determined from data obtained by measurements. The series of sets of first model parameter values (71-73) is used to determine a set of second model parameter values (79) of a parameter evolution model different from the power system asset model. The parameter evolution model describes an evolution of one, several or all first model parameter values (71-73) of the power system asset model. An output is generated in dependence on at least one of the sets of first model parameter values (71-73) of the power system asset model and the set of second model parameter values (79) of the parameter evolution model.

Abstract: Embodiments of a process for estimating a rotational speed of a rotating component and a process for estimating an acceptable rotor imbalance of a rotating component are provided herein. The process for estimating the rotational speed of a rotating component for a charging system comprises measuring a vibration signal of the rotating component by means of a sensor; and identifying harmonic train members from a plurality of peaked components of the vibration signal. Further, the process comprises determining a candidate fundamental frequency from the harmonic train members; and determining a derived vibration amplitude value from the vibration signal. This determination involves a filtering of the vibration signal, removing periodic contributions having a high amplitude. A scalar value is then derived from the filtered signal as a derived vibration amplitude value, representing the integrated total vibration amplitude of the filtered signal at the current speed.

Abstract: The invention relates to a method and apparatus for monitoring the condition of subsystems within a renewable generation plant or microgrid which are using Supervisory Control and Data Acquisition (SCADA) systems for allowing plant operators to monitor and interact with a plant via human machine interfaces.

Abstract: A method for identifying gear tooth numbers in a gearbox using data obtained from a vibration measuring device delivered to a data acquisition device and data delivered by a user to a computer device, comprising: processing data delivered by a user to the computer device, where the data comprises a gearbox ratio and a number of stages of a gearbox for calculating a potential gear tooth combination in each stage of a gearbox, calculating frequencies of characteristic features for each potential tooth combination using the data delivered at the processing data, measuring vibration signals of the gearbox, calculating a frequency spectrum from measured data delivered at the measuring, determining an amplitude of components, of the frequency spectrum delivered at the calculating a frequency spectrum at frequencies of characteristic features for each potential tooth combination delivered at the calculating frequencies of characteristic features.

Abstract: An asset protection, monitoring, or control device is operative to execute a decision-making logic to process inputs and generate a decision-making logic output that comprises one or more time series, process the decision-making logic output using a machine learning model, and cause an action to be performed responsive to a machine learning model output.

Abstract: A method can be used to perform a state of health (SoH) estimation for a rechargeable battery energy storage system during operation of the rechargeable battery energy storage system. The rechargeable battery energy storage system includes a plurality of parallel strings that are individually controllable. The method includes selecting at least one string from the plurality of parallel strings, placing the selected at least one string into a SoH calibration mode for performing a SoH calibration while concurrently maintaining at least one other string of the plurality of parallel strings in operative mode, and causing the selected at least one string to return to the operative mode after the SoH calibration has been completed for the selected at least one string.

Abstract: A method can be used to perform a state of health (SoH) estimation for a rechargeable battery energy storage system during operation of the rechargeable battery energy storage system. The rechargeable battery energy storage system includes a plurality of parallel strings that are individually controllable. The method includes selecting at least one string from the plurality of parallel strings, placing the selected at least one string into a SoH calibration mode for performing a SoH calibration while concurrently maintaining at least one other string of the plurality of parallel strings in operative mode, and causing the selected at least one string to return to the operative mode after the SoH calibration has been completed for the selected at least one string.

Abstract: The subject of the invention is a method and an apparatus for identifying the most likely tooth numbers lot all of the gems in a gearbox, on the basis of measured dynamic signals and the total ratio of the gearbox. A method uses a data obtained from a vibration measuring device delivered to a data acquisition device and a data delivered by a user to a computer device.

Abstract: A method for identifying the discrete instantaneous angular speed of electromechanical systems in which electrical rotating machinery is used and in which at least one electrical signal is measured during an operation of the electromechanical system. The method includes measuring analog stator current signals and analog stator voltage signals for at least one phase A, B, C, converting the measurements into a digital discrete form, transmitting the digital discrete signals to a computer device wherein data analysis is performed in a processor unit on the basis of a simplified mathematical model of the dynamics of the motor or generator. During the data analysis an average rotor time constant is calculated, an average supply frequency value is identified, an average angular speed is obtained, and an instantaneous phase difference between the discrete stator current signals and the discrete stator voltage signals is determined.

Abstract: A method for condition monitoring of distributed drive-trains using Bayesian data fusion approach for measured data includes measurement of physical signals obtained from sensors attached to the components being chosen from the drive-train which are delivered to the computer means for processing the measured data and performing data fusion processes, using a data from information database containing at least one information system. The method is characterized by comprising two stages for data fusion processes performed by using Bayesian Inference, the first one for local data fusion process and the second one for global data fusion process, and on the basis of the second stage the assessment process of the condition of the drive-train is performed by choosing the maximum value of the received data, which maximum value serves as an indicator for the most likely fault present in the drive-train.

Abstract: The invention relates to a method and apparatus for monitoring the condition of subsystems within a renewable generation plant or microgrid which are using Supervisory Control and Data Acquisition (SCADA) systems for allowing plant operators to monitor and interact with a plant via human machine interfaces.

Abstract: The subject of the invention is a method and a computer program for assessing the condition of rotating machinery connected to an electric motor, where the motor (MM) and the rotating machine (RM) comprise a drive train electrically powered from a three phase motor and said motor is connected with a computing device. The invention is characterized in that is comprises the step of classifying the condition of rotating machine (RM) connected to the electric motor (MM) of a drive train with unknown condition, by analyzing all the extracted representative features obtained from the electric signals acquired from the electric motor (MM) of said drive train, by using a trained neural network whose twining was conducted by analyzing the extracted features from N different drive trains of N conditions, where said trained neural network data is stored in unit (3.5) of the computing device (CD, CD?) and next generating an output vector (Z=[Z1, . . .

Abstract: The present invention is concerned with a method for diagnosing the state of electromechanical systems in which electrical rotating machinery is used on the basis of analysis of impedance estimated from at least two currents and two voltages, measured during an operation of the electromechanical system. The method may be especially useful in the condition monitoring of electric motors and generators. The invention combines the information from both the voltage and current signals measurable at the motor terminals. Specifically, the measurements of voltage and current from two or more phases of a polyphase electrical machine are combined to estimate the impedance of the machine, impedance being the resistance to the flow of current that a circuit exhibits when a voltage is applied to it.

Abstract: A method for identifying a fault condition in an electrical machine in which at least a stator or a rotor has parallel winding branches is disclosed. A measurement is carried out for obtaining a set of circulating current values between two parallel winding branches of which each winding branch includes a single coil. A frequency analysis is applied on the set of circulating current values to obtain at least one frequency component. A fault condition of the electrical machine is determined on the basis of the at least one frequency component.

Abstract: A method for identifying the discrete instantaneous angular speed of electromechanical systems in which electrical rotating machinery is used and in which at least one electrical signal is measured during an operation of the electromechanical system. The method includes measuring analog stator current signals and analog stator voltage signals for at least one phase A, B, C, converting the measurements into a digital discrete form, transmitting the digital discrete signals to a computer device wherein data analysis is performed in a processor unit on the basis of a simplified mathematical model of the dynamics of the motor or generator. During the data analysis an average rotor time constant is calculated, an average supply frequency value is identified, an average angular speed is obtained, and an instantaneous phase difference between the discrete stator current signals and the discrete stator voltage signals is determined.

Abstract: The present invention is concerned with a method of determining stationary signals for the diagnostics of an electromechanical systems in which electrical rotating machinery is used and in which at least one electrical or mechanical signal is measured during an operation of the electromechanical system. The method is used especially for condition monitoring of electric motors and generators. The method consists of measuring an analog waveform signal (S) of the electromechanical system and then manipulating that signal in various ways to obtain a frequencies spectrum, from which a vector of interest frequencies and corresponding vector of amplitudes are extracted to diagnose the electromechanical system.

Abstract: The subject of the invention is a method and a computer program for assessing the condition of rotating machinery connected to an electric motor, where the motor (MM) and the rotating machine (RM) comprise a drive train electrically powered from a three phase motor and motor is connected with a computing device. The invention is characterized in that is comprises the step of classifying the condition of rotating machine (RM) connected to the electric motor (MM) of a drive train with unknown condition, by analyzing all the extracted representative features obtained from the electric signals acquired from the electric motor (MM) of said drive train, by using a, trained neural network whose twining was conducted by analyzing the extracted features from N different drive trains of N conditions, where said trained neural network data is stored in unit (3.5) of the computing device (CD, CD?) and next generating an output vector (Z=[Z1, . . .

Abstract: A method, apparatus and computer program for monitoring the condition of electromechanical systems in which electrical rotating machinery is used. The method includes measuring current and/or voltage signals, measuring an angular position of a rotating shaft of interest of the electromechanical systems or estimating the value of discrete angular position of a rotating shaft, synchronizing the current and/or voltage signals to the scaled angular displacement of the rotating shaft, dividing the synchronous electrical signals into intervals corresponding to each completed rotation of the rotating shaft, averaging a number of intervals of synchronous electrical signals to obtain an average synchronous electrical signal, extracting characteristic data of the magnitude from the values of the average synchronous electrical signal, and comparing the extracted characteristic data with a threshold limit to alarm the user when the limit is exceeded.

Abstract: A method for condition monitoring of distributed drive-trains using Bayesian data fusion approach for measured data includes measurement of physical signals obtained from sensors attached to the components being chosen from the drive-train which are delivered to the computer means for processing the measured data and performing data fusion processes, using a data from information database containing at least one information system. The method is characterized by comprising two stages for data fusion processes performed by using Bayesian Inference, the first one for local data fusion process and the second one for global data fusion process, and on the basis of the second stage the assessment process of the condition of the drive-train is performed by choosing the maximum value of the received data, which maximum value serves as an indicator for the most likely fault present in the drive-train.

Abstract: The present invention is concerned with a method for diagnosing the state of electromechanical systems in which electrical rotating machinery is used on the basis of analysis of impedance estimated from at least two currents and two voltages, measured during an operation of the electromechanical system. The method may be especially useful in the condition monitoring of electric motors and generators. The invention combines the information from both the voltage and current signals measurable at the motor terminals. Specifically, the measurements of voltage and current from two or more phases of a polyphase electrical machine are combined to estimate the impedance of the machine, impedance being the resistance to the flow of current that a circuit exhibits when a voltage is applied to it.