Zobrazeno 1 - 10
of 49
pro vyhledávání: '"Muddu Madakyaru"'
Autor:
Sriprasad Acharya, Jitendra Carpenter, Muddu Madakyaru, Poulumi Dey, Anoop Kishore Vatti, Tamal Banerjee
Publikováno v:
ACS Omega, Vol 9, Iss 30, Pp 33174-33182 (2024)
Externí odkaz:
https://doaj.org/article/442a3c884d81430abd7b84d754967bb7
Publikováno v:
Frontiers in Sensors, Vol 5 (2024)
Drunk driving poses a significant threat to road safety, necessitating effective detection methods to enhance preventive measures and ensure the well-being of road users. Recognizing the critical importance of identifying drunk driving incidents for
Externí odkaz:
https://doaj.org/article/da29e5a83f60482286c42c31d3020dc8
Autor:
Muddu Madakyaru
Publikováno v:
ACS Omega, Vol 9, Iss 4, Pp 5051-5067 (2024)
Externí odkaz:
https://doaj.org/article/127eb7b4d718499580149a6ddfeff72d
Publikováno v:
ChemEngineering, Vol 8, Iss 3, p 45 (2024)
Effective fault detection in chemical processes is of utmost importance to ensure operational safety, minimize environmental impact, and optimize production efficiency. To enhance the monitoring of chemical processes under noisy conditions, an innova
Externí odkaz:
https://doaj.org/article/53298fe5bbf549f3b7999953c2c1062a
Publikováno v:
ChemEngineering, Vol 8, Iss 1, p 1 (2023)
Fault detection is crucial in maintaining reliability, safety, and consistent product quality in chemical engineering processes. Accurate fault detection allows for identifying anomalies, signaling deviations from the system’s nominal behavior, ens
Externí odkaz:
https://doaj.org/article/d26020b707d846c8badc15b7726a6bce
Publikováno v:
IEEE Access, Vol 10, Pp 1051-1067 (2022)
Fault detection is necessary for safe operation in modern process plants. The kernel principal component analysis (KPCA) technique has been widely utilized for monitoring non-linear processes because it enhances dimension reduction and fault detectio
Externí odkaz:
https://doaj.org/article/e7a8872653dc43b3a0c554f972a389e2
Publikováno v:
Energies, Vol 16, Iss 15, p 5793 (2023)
Efficient detection of sensor faults in wind turbines is essential to ensure the reliable operation and performance of these renewable energy systems. This paper presents a novel semi-supervised data-based monitoring technique for fault detection in
Externí odkaz:
https://doaj.org/article/e04d2b5d25724d9e82aca508385f17fa
Autor:
K. Ramakrishna Kini, Muddu Madakyaru
Publikováno v:
IEEE Access, Vol 8, Pp 205863-205877 (2020)
Vowing to the increasing complexity in industrial processes, the need for safety is of highest priority and this has led to development of efficient fault detection (FD) methods. Also, with rapid development of data acquisition systems, process histo
Externí odkaz:
https://doaj.org/article/b423215b10f647ba915cf094bb43d2cd
Publikováno v:
Modelling and Simulation in Engineering, Vol 2013 (2013)
Proper control of distillation columns requires estimating some key variables that are challenging to measure online (such as compositions), which are usually estimated using inferential models. Commonly used inferential models include latent variabl
Externí odkaz:
https://doaj.org/article/374e56be59b94e83a144f6cbded10591
Autor:
Muddu Madakyaru, K. Ramakrishna Kini
Publikováno v:
International Journal of Information Technology. 14:3001-3010
The partial least squares (PLS) is a commonly applied multi-variate method in anomaly detection problems. The PLS strategy has been amalgamated with $$T^{2}$$ T 2 and squared prediction error (SPE) based statistical indicators to detect anomalies in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8c45f12093710a640e8500d8bf6a402a
https://doi.org/10.1007/s41870-022-01046-0
https://doi.org/10.1007/s41870-022-01046-0