Abstract: Oscillatory instabilities are ubiquitous of systems, and these usually arise out of low amplitude aperiodic oscillations. These oscillatory instabilities generally affect the performance and the lifespan of systems in an adverse manner. An apparatus and a method are disclosed here to estimate the rms value or the amplitude of limit cycle oscillations for control of the oscillatory instability.

Abstract: A system and method for optimizing passive control strategies of oscillatory instabilities in turbulent systems using finite-time Lyapunov exponents are disclosed. The method includes receiving data from one or more measuring devices connected to the turbulent flow system incorporating a control strategy in the flow field. One or more flow characteristics are determined from the data obtained from the measuring devices. The method involves computing critical dynamics from backward time finite-time Lyapunov exponent (FTLE) field based on the one or more flow characteristics. Next, one or more regions of critical dynamics associated with impending oscillatory instabilities in the turbulent flow system are identified. The identified region of critical dynamics is disrupted the control the onset of oscillatory instabilities in the turbulent flow system.

Abstract: Oscillatory instabilities are ubiquitous of systems, and these usually arise out of low amplitude aperiodic oscillations. These oscillatory instabilities generally affect the performance and the lifespan of systems in an adverse manner An apparatus and a method are disclosed here to estimate the rms value or the amplitude of limit cycle oscillations for control of the oscillatory instability.

Abstract: A system and method for optimizing passive control strategies of oscillatory instabilities in turbulent systems using finite-time Lyapunov exponents are disclosed. The method includes receiving data from one or more measuring devices connected to the turbulent flow system incorporating a control strategy in the flow field. One or more flow characteristics are determined from the data obtained from the measuring devices. The method involves computing critical dynamics from backward time finite-time Lyapunov exponent (FTLE) field based on the one or more flow characteristics. Next, one or more regions of critical dynamics associated with impending oscillatory instabilities in the turbulent flow system are identified. The identified region of critical dynamics is disrupted the control the onset of oscillatory instabilities in the turbulent flow system.

Abstract: The invention includes a method for predicting the operational state of equipment with turbulent flow characterized by time series data relating to its operation. The invention further includes a system and method for predicting the onset of an impending oscillatory instability. Further, the invention includes a system and method for identifying an impending absorbing transition such as flame blowout in combustion systems. A variable representing the dynamics of operation is measured with the help of a sensor, to obtain time series data. A complex network is then derived from the measured time series data. Network properties are then calculated using the complex network to identify the state of stability relating to operation of the equipment. The stability information may include one of thermoacoustic instability, aero-elastic instability such as flutter, flow-induced vibration, magneto-hydrodynamic, aerodynamic, aeromechanical, aero-acoustic instability or onset of flame blowout of a combustor.

Abstract: A method and system for determining one or more precursors to control blowout in a combustor is provided. The method includes obtaining a time series signal corresponding to a dynamic state variable of the combustor. The method includes detecting one or more precursor based on an analysis of the time series signal using one or more parameters to control blowout in the combustor. One or more parameters include a Hurst exponent estimation, a Burst count estimation, and a recurrence quantification based estimation.

Abstract: A method for detecting onset of oscillatory instability in a device is described. The method includes obtaining a symbolic time series of a time series signal corresponding to a dynamic state variable of the device. The method further includes detecting the onset of oscillatory instability in the device based on the symbolic time series.

Abstract: A system for early detection of onset of oscillatory instabilities in practical devices is described. The system consists of a measuring device, an instability detection unit and a control unit. The measuring device is configured to generate signals corresponding to the dynamics happening inside the practical device. The instability detection unit is configured to diagnose the stability of the practical device from the signals that are generated by the measuring device. Further, the control unit is configured to control various operating parameters in the practical device based on the information obtained from the instability detection unit.

Abstract: The invention includes a method for predicting the operational state of equipment with turbulent flow characterized by time series data relating to its operation. The invention further includes a system and method for predicting the onset of an impending oscillatory instability. Further, the invention includes a system and method for identifying an impending absorbing transition such as flame blowout in combustion systems. A variable representing the dynamics of operation is measured with the help of a sensor, to obtain time series data. A complex network is then derived from the measured time series data. Network properties are then calculated using the complex network to identify the state of stability relating to operation of the equipment. The stability information may include one of thermoacoustic instability, aero-elastic instability such as flutter, flow-induced vibration, magneto-hydrodynamic, aerodynamic, aeromechanical, aero-acoustic instability or onset of flame blowout of a combustor.

Abstract: A method for detecting onset of oscillatory instability in a device is described. The method includes obtaining a symbolic time series of a time series signal corresponding to a dynamic state variable of the device. The method further includes detecting the onset of oscillatory instability in the device based on the symbolic time series.

Abstract: A method and system for determining one or more precursors to control blowout in a combustor is provided. The method includes obtaining a time series signal corresponding to a dynamic state variable of the combustor. The method includes detecting one or more precursor based on an analysis of the time series signal using one or more parameters to control blowout in the combustor. One or more parameters include a Hurst exponent estimation, a Burst count estimation, and a recurrence quantification based estimation.

Abstract: A system for early detection of onset of oscillatory instabilities in practical devices is described. The system consists of a measuring device, an instability detection unit and a control unit. The measuring device is configured to generate signals corresponding to the dynamics happening inside the practical device. The instability detection unit is configured to diagnose the stability of the practical device from the signals that are generated by the measuring device. Further, the control unit is configured to control various operating parameters in the practical device based on the information obtained from the instability detection unit.