Root cause analysis of process fault conditions on an industrial concentrator circuit by use of causality maps and extreme learning machines
Access Status
Authors
Date
2015Type
Metadata
Show full item recordCitation
Source Title
ISSN
School
Collection
Abstract
Model-based fault diagnosis tends to be too expensive or time-consuming to apply in the mineral processing industries, owing to the complexity and variability of operations. In contrast, data-based methods are inexpensive, but do not exploit the availability of first principle knowledge of plant operations. In this investigation, the use of process causality maps in conjunction with data-based fault diagnosis is considered as a hybrid methodology that can leverage the advantages of both approaches. Extreme learning machine algorithms are used to implement the data-based component of the approach. These algorithms can be deployed rapidly on large-scale systems and have the ability to deal with highly nonlinear systems. Two different variants are considered, viz. one used in combination with principal component analysis, as well as one with a bagging algorithm for fault diagnosis and applied to an industrial concentrator circuit in South Africa. The use of process causality maps led to significantly more effective fault diagnosis, while the use of extreme learning machines in combination with principal component analysis likewise allowed markedly better fault detection and diagnosis. In contrast, fault diagnosis with the bagging approach did not perform particularly well, owing to the high degree of correlation between the variables, which made it difficult to isolate individual causal variables.
Related items
Showing items related by title, author, creator and subject.
-
Khalid, Muhammad Imran (2010)In the 21st Century, water is already a limited and valuable resource, in particular the limited availability of fresh water sources. The projected increase in global population from 6 billion people in 2010 to 9 billion ...
-
Kamiel, B.; Howard, Ian (2014)Centrifugal pumps are one of the rotating machines that are widely used in various industries such as oil and gas, petrochemical, water treatment, power generation, agriculture, and fertilizers. During its operation, it ...
-
Seligmann, Benjamin; Németh, E.; Hangos, K.; Cameron, I. (2012)A novel hazard identification methodology applied to process systems is presented in this paper. This blended hazard identification (BLHAZID) methodology blends two different types of HAZID methods: the function-driven ...