This decommissioned ERA site remains active temporarily to support our final migration steps to https://ualberta.scholaris.ca, ERA's new home. All new collections and items, including Spring 2025 theses, are at that site. For assistance, please contact erahelp@ualberta.ca.
Search
Skip to Search Results- 1Alighardashi, Hashem
- 1Amjad, Faraz
- 1Chiplunkar, Ranjith Ravi Kumar
- 1Fang, Mengqi
- 1Khosbayar, Anudari
- 1Mohankumar, Yashas
- 1Bayesian networks
- 1Bayesian networks based soft sensors
- 1Cauchy distribution
- 1Chance constraint
- 1Closed skew-normal distribution
- 1Computer Vision
-
Hierarchical Monitoring and Probabilistic Graphical Model Based Fault Detection and Diagnosis
DownloadFall 2020
As the rapid development of modern industry, data based fault detection and diagnosis for industrial processes have become increasingly critical to ensure process safety and product quality. To effectively make use of underlying features of process data, multiple data based fault detection and...
-
Spring 2022
Chiplunkar, Ranjith Ravi Kumar
Data-driven modeling has been finding increasing prominence in process systems engineering in both academia and industries. Latent variable modeling forms an important component of data-driven modeling. Through latent variable modeling, not only can we deal with issues such as collinearity,...
-
Limits of Control Performance for Networked Control Systems with Random Communication Delays
DownloadSpring 2021
Networked control systems (NCSs) and distributed networked control systems (DNCSs) increasingly appear in the modern process industry due to continuous expansion of system scales, physical setups and functionalities. Control loops in a NCS are closed through information exchange between the...
-
Machine Learning for Robust Tracking of Interface Level Inside a Primary Separation Vessel in the Presence of Occlusions and Noise
DownloadSpring 2021
A Primary Separation Vessel (PSV), used in the oil sands industry, is an important process equipment, where Bitumen is separated from the oil sand using a density based separation process. The interface level between a bitumen rich layer (froth) and a layer that has moderate amounts of bitumen in...
-
Fall 2017
Process measurements collected from daily industrial plant operations are essential for process control and optimization. However, due to various reasons, the process data are always corrupted by errors, so that process model constraints representing the mass balance and energy balance are not...
-
RESERVOIR HISTORY MATCHING USING CONSTRAINED ENSEMBLE KALMAN FILTER AND PARTICLE FILTER METHODS
DownloadSpring 2015
The high heterogeneity of petroleum reservoirs, represented by their spatially varying rock properties (porosity and permeability), greatly dictates the quantity of recoverable oil. In this work, the estimation of these rock properties, which is crucial for the future performance prediction of a...
-
Spring 2021
For efficient process control and monitoring, accurate real-time information of quality variables is essential. To predict these quality (or slow-rate) variables at a fast-rate, in the industry, inferential/soft sensors are often used. However, most of the conventional methods for soft sensors do...
-
Simultaneous Gross Error Detection and Data Reconciliation Using Gaussian Mixture Distribution
DownloadFall 2017
The intensive competitive nature of the world market, the growing significance of quality products, and the increasing importance and the number of safety and environmental issues and regulations, respectively, have increased the need for fast and low-cost changes in chemical processes to enhance...
-
Spring 2020
Steam allocation is an important decision to be made for bitumen thermo-recovery using the Steam Assisted Gravity Drainage (SAGD) technique. This is due to the significant amount of steam requirement and often limited steam generation capacity. Steam-to-oil ratio (SOR) is an important parameter...