The Experimental Determination of Coal Mill Models

Bollinger,; Snowden,

doi:10.1109/mper.1983.5519007

Cited by 4 publications

(7 citation statements)

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“…Breakage matrix is considered to simulate the grinding process. Some relatively simplified models of mills are developed in [129,[136][137][138][139][140][141][142][143][144][145][146][147], where the coal in the pulverizer is divided into two groups, unpulverized and pulverized. These detailed and simplified models can be used for mill FDD purpose.…”

Section: Mill Fault Detection Using Quantitative Model-based Methodsmentioning

confidence: 99%

“…Though results look interesting and show quick fault detection, these methods focus on one or two faults only. Detailed and complete models developed in [129][130][131][132][133][134][135][136][137][138][139][140][141][142][143][144][145][146][147] should be tried with the aim of multiple fault identification.…”

Section: Comparison Of Various Fault Diagnostic Approachesmentioning

confidence: 99%

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Review of control and fault diagnosis methods applied to coal mills

Agrawal

Panigrahi

Subbarao

2015

Journal of Process Control

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Section: Mill Fault Detection Using Quantitative Model-based Methodsmentioning

confidence: 99%

Section: Comparison Of Various Fault Diagnostic Approachesmentioning

confidence: 99%

Review of control and fault diagnosis methods applied to coal mills

Agrawal

Panigrahi

Subbarao

2015

Journal of Process Control

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“…Equation (4) represents that the mass change rate of the coal in mill is proportional to the difference between the coal flow into the mill and the fraction of coal that is converted into pulverized fuel K 1 5M c (t). Equation (5) represents that the change of mass of pulverized fuel in mill is proportional to the difference between the fraction of coal converted into pulverized and the pulverized coal flow outlet from the mill. Equation (6) represents that the total amount of mill current consumed to run the mill motor is equal to the sum of mill current required to grind over surface area, mill current to pulverized coal, and mill current to run empty mill.…”

Section: Coal Mill Modeling For the Normal Grinding Processmentioning

confidence: 99%

“…The milling process at power plants is different from the grinding process in mineral industry as it involves not only grinding but also heat transferring. An approximated linear transfer function model was obtained by Bollinger and Snowden in 1983 [5]. Mill modeling achieved by a system identification method was reported in 1984 [6].…”

Section: Introductionmentioning

confidence: 99%

Development of a Multisegment Coal Mill Model Using an Evolutionary Computation Technique

Wei

Wang

2007

IEEE Trans. On Energy Conversion

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This paper presents a multisegment coal mill model that covers the whole milling process from mill startup to shutdown. This multisegment mathematical model is derived through analysis of energy transferring, heat exchange, and mass flow balances. The work presented in the paper focuses on modeling E-type vertical spindle coal mills that are widely used in coal-fired power plants. An evolutionary computation technique is adopted to identify the unknown model parameters using the on-site measurement data. The identified parameters are then validated with different sets of online measured data. Validation results indicate that the model is accurate enough to represent the whole process of coal mill dynamics and can be used for prediction of the mill dynamic performance. Therefore, the model can be used for online monitoring, fault detection, and control to improve the efficiency of combustion.

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“…Compared with the vertical mills, tube-ball mills are more complex in structure and have a much higher grinding capacity. The modeling procedure adopted in the paper is different from the work reported in [2], [3], [7], [8], and [9]. The mathematical model is transparent with the respect to engineering process as all the parameters of the model have their specified physics meaning.…”

Section: Introductionmentioning

confidence: 99%

Mathematic modeling and condition monitoring of power station tube-ball mill systems

Wei¹,

Wang²,

Guo³

2009

2009 American Control Conference

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The paper presents a newly developed nonlinear Tube-Ball mill model for model based on-line condition monitoring. This mathematical model is derived through analyzing energy transferring, heat exchange and mass flow balances. Evolutionary techniques are adopted to identify the unknown system parameters using the on-site measurement data. The identified system parameters are then validated using multiple on-line measurement data. Validation has been conducted by comparing the measured and simulated values. The results indicate that the model can represent the coal mill dynamics and can be used to predict the mill dynamic performance. Then the model is implemented on-line and it can run on-line along with the real milling process. It is then adopted for on-line condition and safety monitoring, fault detection, and control to improve the efficiency of combustion.

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The Experimental Determination of Coal Mill Models

Cited by 4 publications

References 0 publications

Review of control and fault diagnosis methods applied to coal mills

Review of control and fault diagnosis methods applied to coal mills

Development of a Multisegment Coal Mill Model Using an Evolutionary Computation Technique

Mathematic modeling and condition monitoring of power station tube-ball mill systems

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