Indian Institute of Technology Madras

Indian Institute of Technology

Indian Institute of Technology Madras (iit Madras)

Sujith Raman Pillai Indusekharan Nair

Vishnu Rajasekharan Unni

Vineeth Nair Vinod

Induja Pavithran

Manikandan Raghunathan

Premchand Chandramouly Premakumari

Vineeth Nair

Nitin Babu George

Meenatchidevi Murugesan

Achintya Mukhopadhyay

Gireeshkumaran Thampi

Sulochana Karuppusamy

Saravanan Gopalan

Akshay Seshadri

Ankan Banerjee

The invention discloses systems and methods for predicting and controlling lean blowout in combustion systems such as turbines, engines and combustors. The systemis configured to detect and predict time of occurrence of blowout using a computerand to take control action by a controllerthrough actuators, to prevent the blowout. The methodinvolves acquiring time series data () of combustion in the combustion system, including acoustic pressure amplitude, chemiluminescence intensity, or global heat release rate, fitting a log periodic power law equation to the time series data (), computing a time of impending blowout using the fit equation (), and controlling the combustion unit () to move away from impending blowout and prevent the blowout. The invention provides for predicting exact blowout times significantly earlier, and to control the combustion unit to prevent blowout, thus enabling reduction in emissions.

System and method to predict and control blowout in combustion systems

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.

Apparatus to estimate the root means square value or the amplitude of limit cycle oscillations in systems that encounter oscillatory instabilities and methods thereof

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.

System and method for optimizing passive control strategies of oscillatory instabilities in turbulent systems using finite-time Lyapunov exponents

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.

Devices and methods for early prediction of impending instabilities of a system

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.

System and method for detecting precursors to control blowout in combustion systems

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.

System and method for controlling oscillatory instabilities in a device

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.

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Chennai, India

Sujith Raman Pillai Indusekharan Nair