Coal moisture estimation in power plant mills

Abstract

Abstract-Knowledge of moisture content in raw coal feed to a power plant coal mill is of importance for efficient operation of the mill. The moisture is commonly measured approximately once a day using offline chemical analysis methods; however, it would be advantageous for the dynamic operation of the plant if an on-line estimate were available. In this paper we such propose an on-line estimator (an extended Kalman filter) that uses only existing measurements. The scheme is tested on actual coal mill data collected during a one-month operating period, and it is found that the daily measured moisture content agrees with the estimates.

Review of control and fault diagnosis methods applied to coal mills

“…The researches done to identify problems in the milling system using model based fault diagnosis are provided in [3,[119][120][121][122][123][124][125][126][127][128]. P. F. Odgaard and B. Mataji [119][120][121][122] presented an observer-based method for detecting faults and estimating moisture content in the coal in coal mills using simplified energy balance model of the coal mill.…”

“…A kalman estimator is designed and sign of the energy imbalance is used to isolate the faults. P. Andersen et al [123] also attempted to estimate moisture in coal entering and leaving the mill using kalman filter applied to the energy balance model. Some approaches for preventing control constraint violations for mills are developed by P.F.…”

“…The quantitative model based techniques for the mill FDD are presented in [3,[119][120][121][122][123][124][125][126][127][128]. These methods are sensitive to the mathematical model used to describe the process behaviour.…”

Application of Model-Based Deep Learning Algorithm in Fault Diagnosis of Coal Mills

“…Odgaard and Mataji [2] used a simplified energy balance equation to monitor and diagnose abnormal energy flow in the coal mill. Andersen et al [3] designed a Kalman filter to estimate the moisture in the coal that enters and exists a coal mill to determine whether the energy in the coal mill is in normal condition. Based on the multisegment model of coal mills established by Wei et al [4], Guo et al [5] realized the monitoring of the state of coal mills by identifying the abnormal variation in the model parameters.…”