Zobrazeno 1 - 9
of 9
pro vyhledávání: '"TV, Vishnu"'
Automated equipment health monitoring from streaming multisensor time-series data can be used to enable condition-based maintenance, avoid sudden catastrophic failures, and ensure high operational availability. We note that most complex machinery has
Externí odkaz:
http://arxiv.org/abs/2006.16556
Deep neural networks (DNNs) have achieved state-of-the-art results on time series classification (TSC) tasks. In this work, we focus on leveraging DNNs in the often-encountered practical scenario where access to labeled training data is difficult, an
Externí odkaz:
http://arxiv.org/abs/1909.07155
Recently, neural networks trained as optimizers under the "learning to learn" or meta-learning framework have been shown to be effective for a broad range of optimization tasks including derivative-free black-box function optimization. Recurrent neur
Externí odkaz:
http://arxiv.org/abs/1907.06901
Prognostics or Remaining Useful Life (RUL) Estimation from multi-sensor time series data is useful to enable condition-based maintenance and ensure high operational availability of equipment. We propose a novel deep learning based approach for Progno
Externí odkaz:
http://arxiv.org/abs/1903.09795
Autor:
Gugulothu, Narendhar, TV, Vishnu, Malhotra, Pankaj, Vig, Lovekesh, Agarwal, Puneet, Shroff, Gautam
We consider the problem of estimating the remaining useful life (RUL) of a system or a machine from sensor data. Many approaches for RUL estimation based on sensor data make assumptions about how machines degrade. Additionally, sensor data from machi
Externí odkaz:
http://arxiv.org/abs/1709.01073
Inspired by the tremendous success of deep Convolutional Neural Networks as generic feature extractors for images, we propose TimeNet: a deep recurrent neural network (RNN) trained on diverse time series in an unsupervised manner using sequence to se
Externí odkaz:
http://arxiv.org/abs/1706.08838
Autor:
Malhotra, Pankaj, TV, Vishnu, Ramakrishnan, Anusha, Anand, Gaurangi, Vig, Lovekesh, Agarwal, Puneet, Shroff, Gautam
Many approaches for estimation of Remaining Useful Life (RUL) of a machine, using its operational sensor data, make assumptions about how a system degrades or a fault evolves, e.g., exponential degradation. However, in many domains degradation may no
Externí odkaz:
http://arxiv.org/abs/1608.06154
Autor:
Saurav, Sakti, Malhotra, Pankaj, TV, Vishnu, Gugulothu, Narendhar, Vig, Lovekesh, Agarwal, Puneet, Shroff, Gautam
Publikováno v:
ACM International Conference Proceeding Series; 1/11/2018, p78-87, 10p
Autor:
Vishnu Kumar TV; School of Electronics Engineering, Vellore Institute of Technology Chennai, Tamil Nadu, India., John A; School of Electronics Engineering, Vellore Institute of Technology Chennai, Tamil Nadu, India., Vighnesh M; School of Electronics Engineering, Vellore Institute of Technology Chennai, Tamil Nadu, India., Jagannath M; School of Electronics Engineering, Vellore Institute of Technology Chennai, Tamil Nadu, India.
Publikováno v:
Materials today. Proceedings [Mater Today Proc] 2022; Vol. 62, pp. 4605-4611. Date of Electronic Publication: 2022 Mar 11.