[HTML][HTML] 3d convolutional selective autoencoder for instability detection in combustion systems

T Gangopadhyay, V Ramanan, A Akintayo, PK Boor… - Energy and AI, 2021 - Elsevier
While analytical solutions of critical (phase) transitions in dynamical systems are abundant
for simple nonlinear systems, such analysis remains intractable for real-life dynamical …

Data-driven detection and early prediction of thermoacoustic instability in a multi-nozzle combustor

C Bhattacharya, J O'Connor, A Ray - Combustion Science and …, 2022 - Taylor & Francis
Thermoacoustic instability (TAI) is a critical issue in modern lean-burn gas-turbine
combustors, which is induced by a strong coupling between the resonant combustor …

Dynamic characterization of a ducted inverse diffusion flame using recurrence analysis

U Sen, T Gangopadhyay, C Bhattacharya… - Combustion Science …, 2018 - Taylor & Francis
Normal diffusion flame or partially premixed flame is used in many applications, such as
aviation engines, tanks, ocean vessels, and industrial furnaces, because of its high flame …

Reduced-order modelling of thermoacoustic instabilities in a two-heater Rijke tube

C Bhattacharya, S Mondal, A Ray… - … Theory and Modelling, 2020 - Taylor & Francis
The topic of thermoacoustic instabilities in combustors is well-investigated, as it is important
in the field of combustion, primarily in gas-turbine engines. In recent years, much attention …

Interpretable deep learning for monitoring combustion instability

T Gangopadhyay, SY Tan, A LoCurto, JB Michael… - IFAC-PapersOnLine, 2020 - Elsevier
Transitions from stable to unstable states occurring in dynamical systems can be sudden
leading to catastrophic failure and huge revenue loss. For detecting these transitions during …

[图书][B] Frontiers in Data-Driven Learning Via Probabilistic Finite State Automata

C Bhattacharya - 2022 - search.proquest.com
Anomaly detection is an essential step in the task of automating complex processes,
allowing the control algorithm to identify any undesirable operation and take preventive or …

Real-Time Monitoring and Diagnostics of Anomalous Behavior in Dynamical Systems

S Mondal, C Bhattacharya, NF Ghalyan… - Dynamics and Control of …, 2020 - Springer
Real-time condition monitoring of complex dynamical systems is of critical importance for
predictive maintenance. This chapter focuses on data-driven techniques of fault diagnostics …

Reconstruction of cross-modal visual features from acoustic pressure time series in combustion systems

T Gangopadhyay - 2021 - search.proquest.com
In many cyber-physical systems, imaging can be an important but expensive ordifficult to
deploy'sensing modality. One such example is detecting combustion instability using flame …

Trustworthy deep learning for cyber-physical systems

T Gangopadhyay - 2022 - search.proquest.com
In cyber-physical systems, along with the accuracy of decision-making, interpretability
remains one of the important aspects to build user trust and generate domain insights …

Real-Time Monitoring and Diagnostics of Anomalous Behavior in Dynamical

S Mondal, C Bhattacharya, NF Ghalyan… - Dynamics and Control …, 2019 - books.google.com
Real-time condition monitoring of complex dynamical systems is of critical importance for
predictive maintenance. This chapter focuses on data-driven techniques of fault diagnostics …