A statistical analysis of monitored data for methane prediction

This research describes an investigation into the application of a statistical method for the prediction of methane concentration in longwall coal districts. An important and necessary part of the research was the acquiring of representative mine environmental and coal production data and a number o...

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Main Author: Dixon, Darron William
Format: Thesis (University of Nottingham only)
Language:English
Published: 1992
Subjects:
Online Access:https://eprints.nottingham.ac.uk/12977/
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author Dixon, Darron William
author_facet Dixon, Darron William
author_sort Dixon, Darron William
building Nottingham Research Data Repository
collection Online Access
description This research describes an investigation into the application of a statistical method for the prediction of methane concentration in longwall coal districts. An important and necessary part of the research was the acquiring of representative mine environmental and coal production data and a number of shortcomings were identified in this area. The monitored data was used to build univariate time series models of general air body methane concentration, air velocity, barometric pressure, coal production and methane drainage variables of varying timescales according to the Box-Jenkins method of time series analysis. The univariate models were used to identify causal relationships between methane concentration and its explanatory variables. Coal production was found to be the dominant variable in the determination of the quantity of methane emitted and where appropriate, multivariate time series models were built in which expressions for methane concentration in terms of coal production were obtained. Forecasts of methane concentration values were generated from both univariate and multivariate models and a comparison was made of their forecasting capabilities. Finally, suggestions were made as to the potential use of time series models for application to mining process control.
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format Thesis (University of Nottingham only)
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language English
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publishDate 1992
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spelling nottingham-129772025-02-28T11:22:26Z https://eprints.nottingham.ac.uk/12977/ A statistical analysis of monitored data for methane prediction Dixon, Darron William This research describes an investigation into the application of a statistical method for the prediction of methane concentration in longwall coal districts. An important and necessary part of the research was the acquiring of representative mine environmental and coal production data and a number of shortcomings were identified in this area. The monitored data was used to build univariate time series models of general air body methane concentration, air velocity, barometric pressure, coal production and methane drainage variables of varying timescales according to the Box-Jenkins method of time series analysis. The univariate models were used to identify causal relationships between methane concentration and its explanatory variables. Coal production was found to be the dominant variable in the determination of the quantity of methane emitted and where appropriate, multivariate time series models were built in which expressions for methane concentration in terms of coal production were obtained. Forecasts of methane concentration values were generated from both univariate and multivariate models and a comparison was made of their forecasting capabilities. Finally, suggestions were made as to the potential use of time series models for application to mining process control. 1992 Thesis (University of Nottingham only) NonPeerReviewed application/pdf en arr https://eprints.nottingham.ac.uk/12977/1/334922.pdf Dixon, Darron William (1992) A statistical analysis of monitored data for methane prediction. PhD thesis, University of Nottingham. Mine workings Methane gas Mathematical models Fluid mechanics Firedamp
spellingShingle Mine workings
Methane gas
Mathematical models
Fluid mechanics
Firedamp
Dixon, Darron William
A statistical analysis of monitored data for methane prediction
title A statistical analysis of monitored data for methane prediction
title_full A statistical analysis of monitored data for methane prediction
title_fullStr A statistical analysis of monitored data for methane prediction
title_full_unstemmed A statistical analysis of monitored data for methane prediction
title_short A statistical analysis of monitored data for methane prediction
title_sort statistical analysis of monitored data for methane prediction
topic Mine workings
Methane gas
Mathematical models
Fluid mechanics
Firedamp
url https://eprints.nottingham.ac.uk/12977/