Ash Monitor Research Articles

Online Ash Content Monitor by Automatic Composition Identification and Dynamic Parameter Adjustment Method in Multicoal Preparation

The online measurement of coal ash has overcome the shortcomings of chemical tests. However, there could be large fluctuations and errors in the results of online ash monitors because of the transient change in coal quality resulting from different geological conditions in the mining process. In this study, to resolve the problems of the dual-energy γ-ray online ash monitor in the Linhuan Coal Preparation Plant, we investigated the internal factors, such as the composition of multimineral and multicoal, and external factors, such as the moisture and impurities, which affect the measurement results of the coal ash monitor. Furthermore, we developed a mathematical model to determine the effect of relevant factors on the coefficient of the online ash monitor, which revealed the relationship between coal composition and the parameters of the ash monitor, ensuring the stable and accurate measurement of ash in clean coal. The method of determining parameters used in the case of coal blending has been applied in the Linhuan Coal Preparation Plant. By comparing with tested ash content, the average absolute error and relative error for daily ash content measured in April are 0.21 and 2.18%, respectively. Meanwhile, it shows certain accuracy and reproducibility while opposed to the daily average absolute error of 0.22 and relative error of 2.39% in May.

The Online Correction of Gamma-ray Ash Monitor in Coal Preparation Plant

ABSTRACT In coal preparation plant, the control strategy of the separation process is made mainly based on the timely feedback of the clean coal ash. But the results of commonly used gamma-ray coal ash monitor only could reflect the trends of coal quality and fail to satisfy the dynamic amendment of operation parameter. The actual ash remains to be obtained by a complex process, consisting of the manual sampling, sample preparation, and laboratory analysis. To solve the above problem, this paper first analyzed the working principle of ash monitor and its influence factors. Then, mass of data relevant to the obtain of online ash were collected, and the correlation analysis showed that the on-line ash deviation was highly related to the coal flux on the conveying belt. Aiming to improve the accuracy of the online measurement of coal ash, different mathematical curve models and machine learning Least Squares Support Vector Machine (LS-SVM) models are used for the on-line ash correction. The results of prediction simulation indicate that the LS-SVM algorithm (root-mean-square error [RMSE] = 0.3335) is better than the conventional regression model (RMSE = 0.1747) in predicting the ash content. Therefore, the coal flux data could be used for the correction of online ash with LS-SVM algorithm.

アジア大での環境負荷軽減と石炭需給の安定化 ジグ制御システムの開発とインドネシアのオンビリン炭鉱への適用

In this study, a control system incorporating the know-how of the skilled operators using fuzzy logic is applied by using on-line ash monitors conventionally employed for product coal quality control as a jig control system sensor to a coal preparation plant of the Ombilin Mine in Indonesia. The computer simulation experiments demonstrate that the response can be improved by means of modification of the fuzzy rules. Based on the results of the simulation experiments, it is clear that the present proportional/integral-operation fuzzy control system is effective in mitigating the large dead times of 60 seconds due to the sampling interval of the ash monitor, and also in mitigating the parameter variations due to the properties of raw coal. The experimental results show that the coal washery jig control system developed with the use of the PI fuzzy control system is capable of controlling the clean coal ash content to within a ± 3% range of the target ash content of the clean coal.

Dynamics of On-Line Ash Monitors in Monitoring and Control Systems

On-line ash monitors have been in use for many years in coal industry. Their operation is usually based on the scattering or the absorption of incident gamma radiation, and the derived ash value is the result of a time-averaged measurement. The natural radiation method is also used in on-line ash content measurements. A review of the ash monitors applied in Polish coal preparation plants is presented in this paper. Most of monitor installations are designed to monitor trends of ash content in coals, rather than to react to rapid changes of ash content. These data averaged over the period of tens of seconds (or several minutes) are often used by an operator to adjust the operation of a plant manually. In the case of closed loop control systems with on-line ash monitors, the dynamic properties of these instruments are important. The concept of an ash monitor with a time constant (or a time of measurement) adapting to variations of an input signal (ash content) have been analyzed. The fuzzy logic has been applied to establish the structure of the adaptive filter. Such a system allows us to speed-up the reaction of the instrument to rapid variations of ash content and at the same time to achieve better statistical accuracy over a longer period of time. This is particularly important in closed loop control systems or in splitting of a coal stream to different products. Simulation analysis of the coal blending control system applied in the "Sosnica" plant is presented in this article. Application of an on-line ash monitor with an adaptive time constant is discussed and some results of practical experiments are presented.

A simulation study of coal blending control using a fuzzy logic ash monitor

On-line nuclear meters have been in use in the coal industry for many years. They have been utilised for coal quality monitoring, in the control systems for coal blending, or for separating coals in the heavy media separation process. Their operation is based on the scattering or the absorption of incident gamma radiation, and the derived density or ash value is the result of a time-averaged measurement. The simulation analysis shows that the best results are given by the monitors in which the time of measurement is variable and adapts to changes of the input signal. An example of a coal blending control system which stabilises coal quality of the blend with the use of the fuzzy logic ash monitor has been analysed.

Fuzzy logic control of coal blending

On-line nuclear meters have been in use in the coal industry for many years. They have been utilised for coal quality monitoring, in the control systems for coal blending, or for separating coals in the heavy media separation process. Their operation is based on the scattering or the absorption of incident gamma radiation, and the derived density or ash value is the result of a time-averaged measurement. In this paper, dynamic models of ash monitors have been presented and discussed. The analysis of monitors with constant measurement time shows that it is possible to determine optimal time for which the dynamic error is the smallest. The analysis also shows that the best results are given by the monitors in which the measurement time is variable and adap to changes of the input signal. The fuzzy logic has been applied to control ash monitor operation. An example of a coal blending control system which stabilises coal quality of the blend with the use of the fuzzy ash monitor has been analysed.

97/02524 Model FJ-2821 γ-ray ash monitor and its application

97/02524 Model FJ-2821 γ-ray ash monitor and its application

Microwave Gauge for the On-Line Determination of Moisture

A non-contacting microwave transmission gauge has been developed for on-conveyor determination of moisture in coal. A laboratory evaluation has been completed on a range of fine (< 5 mm) and coarse (< 50 mm) coal samples from New South Wales, coal washeries. An industrial prototype of the microwave moisture gauge was installed at Howick coal washery, New South Wales, in April 1989, for on-belt determination of moisture in the total washery product. The moisture content of the coal has been determined from a measurement of microwave phase shift by the microwave gauge and coal mass per unit area by Coalscan 3500 ash monitor. The product comprised a mixture of bypass and washed coal, with a nominal topsize of 50 mm, that was typically segregated such that the bypass coal formed the lowermost layer of the conveyor. The conveyor loading was typically in the range 200-600 tonnes/h and the product moisture in the range 6-12 wt%. An on-line calibration was obtained from a correlation of the gauge predicted moistu...

Coal Sorting

The concept of the bulk sorting of coal using a fast acting ash monitor plus a diverter to identify and separate the high ash segments from a stream of coal is introduced. Examples of coal sorting at two Australian mines are reviewed. Methods of assessing the sortability of a particular stream of coal by real time data acquisition and computer simulation of the operation of a sorter are presented. Ash-yield curves generated from such data are presented, showing the effect of changing the sort time.

Automatic In-line Ash Monitor for Coal Slurries

Monitoring of the ash content in a coal preparation plant is essential for properly adjusting the cleaning system to cope with variations occurring in the feed. The principles, installation and testing of an automatic in-line ash monitor are described. Operation of the monitor is based on the specific gravity-ash content relationship for a particular coal seam, or blend of different seams, stored in computer memory. Hence from a measured coal specific gravity the ash content can indirectly be determined.Results from pilot plant testing of the in-line ash monitor on minus 10 mm coal (21-32% ash) have shown good agreement with the standard (ASTM) laboratory analysis method. Accuracy of the in-line ash monitor has been found to be within ± 0.6% of the laboratory analysis.The in-line ash monitor can easily be integrated in an overall process control particularly in monitoring the ash content of the raw coal. The ash monitor components can also be used to measure other parameters essential for process control such as solids throughput, water flowrate and per cent solids simultaneously.