Risk assessment methodologies in maintenance decision making: A review of dependability modelling approaches
P Chemweno, L Pintelon, PN Muchiri… - Reliability Engineering & …, 2018 - Elsevier
The risk assessment process performs an important role in maintenance decision making,
through structuring the process of identifying, prioritizing, and thereafter formulating effective …
through structuring the process of identifying, prioritizing, and thereafter formulating effective …
Block-wise parallel semisupervised linear dynamical system for massive and inconsecutive time-series data with application to soft sensing
Linear dynamical system (LDS) has established itself as a powerful tool for soft sensing
dynamic industrial processes, which, however, still faces some practically pivotal issues …
dynamic industrial processes, which, however, still faces some practically pivotal issues …
Distributed semisupervised HMM for dynamic inferential sensor development
Hidden Markov model (HMM) has proven effective for inferential sensing of dynamical and
non-Gaussian industrial processes. However, large-scale process data introduce …
non-Gaussian industrial processes. However, large-scale process data introduce …
Virtual sensing for dynamic industrial process based on localized linear dynamical system models with time-delay optimization
Virtual sensors play an important role in real-time sensing of key quality-related variables in
industrial processes. Linear dynamical system (LDS) paradigm has established itself as a …
industrial processes. Linear dynamical system (LDS) paradigm has established itself as a …
Path following fault-tolerant control of distributed drive autonomous unmanned vehicle via adaptive terminal sliding mode
Y Li, Q Chen, T Zhang, J Wang - Journal of the Franklin Institute, 2024 - Elsevier
The distributed drive autonomous unmanned vehicle (DDAUV) with unknown fault input of
steering system will seriously deviate from the desired path and affect driving safety. This …
steering system will seriously deviate from the desired path and affect driving safety. This …
A novel semi-supervised robust learning framework for dynamic generative latent variable models and its application to industrial virtual metrology
Among a variety of virtual metrology models, dynamic generative latent variable models
(DGLVMs) have proven to be an effective tool, owing to outstanding advantages in dealing …
(DGLVMs) have proven to be an effective tool, owing to outstanding advantages in dealing …
Semi-Supervised Robust Hidden Markov Regression for Large-Scale Time-Series Industrial Data Analytics and Its Applications to Soft Sensing
Hidden Markov models (HMMs) for time-series data analysis are attracting wide interests in
industries due to their ability to model the extensively existing dynamics and non …
industries due to their ability to model the extensively existing dynamics and non …
Learning reactive and predictive differentiable controllers for switching linear dynamical models
S Saxena, A LaGrassa… - 2021 IEEE International …, 2021 - ieeexplore.ieee.org
Humans leverage the dynamics of the environment and their own bodies to accomplish
challenging tasks such as grasping an object while walking past it or pushing off a wall to …
challenging tasks such as grasping an object while walking past it or pushing off a wall to …
Semi-supervised optimal recursive filtering and smoothing in non-Gaussian Markov switching models
Filtering and smoothing in switching state-space models are important in numerous
applications. The classic family of conditionally Gaussian linear state space models …
applications. The classic family of conditionally Gaussian linear state space models …
Advantages and challenges of information fusion technique for big data analysis: proposed framework
Introduction: Recently, with the surge in the availability of relevant data in various industries,
the use of Information Fusion technique for data analysis is increasing. This method has …
the use of Information Fusion technique for data analysis is increasing. This method has …