808 Ó WILEY-VCH Verlag GmbH, D-69469 Weinheim, 1998 0930-7516/98/0101-00808 $ 17.50+.50/0 Chem. Eng. Technol. 21 (1998) 10

References

[1] Schuler, H.; Schmidt, Chr.-U., Chem. Ing. Techn. 63 (1991) pp. 3 189.[2] Brammer, K.; Siffling, G., Kalman-Bucy-Filter, Deterministische Beo-

bachtung und stochastische Filterung, R. Oldenbourg Verlag, München-Wien 1975.

[3] Litz, W., J. Thermal Anal. 27 (1983) p. 215.

This paper will also be published in German in Chem. Ing. Tech. 70 (1998) No. 10.

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Forecast of Hot Spots and Glowing Zonesin Activated Carbon Filters

By Peter Neumann, Georg Lauber, Zoltµn Hrabovszki,Thomas Pfeil, and Klaus G. Schmidt*

1 Problem

Based on their great bandwidth of separable flue gassubstances, activated carbon filters have a wide operationrange. Especially for the separation of toxic compounds, e.g.dioxines and furanes, they attain very high efficiency.Subsequently, the usability of activated carbon filters fordioxine control in thermal recycling processes is examined.

In activated carbon filters designed as fixed bed or movedbed, cold oxidation takes place and, consequently, a contin-uous conversion of carbon into CO and CO2. These reactionsas well as the adsorption and chemisorption processes areexothermic. In regular operating conditions of a plant, thereaction heat of oxidation is provided by the flue gas.

But in areas with slow flow it is possible that self-heating canarise through insufficient heat disposal (hot spot). Thetemperature increase produced hereby, accompanied byintensified CO/CO2 production, accelerates further oxida-tion, which can lead to a zone of glowing carbon.

Apart from the increased risk of further expansion of self-heating with corresponding widening of the glowing zone, itcan be expected that the harmful substances already adsorbedwill be exposed.

Regularly, the required minimum gas flow is ensured byconstructive means and appropriate plant operation methods.

Mathematic models are available for the layout of thosefilters, which are based on theoretic calculations. Differentoperational states, common dynamic or other operationalphenomena, e. g. caking of adhesive dust, are not considered.Such zones of glowing carbon have to be considered aspotentially dangerous. Therefore, the early detection of suchareas is exceptionally important.

The process described is based on the strong temperaturedependence of the CO production. With DCO monitoring ±

shaping the CO difference in the same measuring instrumentby measuring before and behind the activated carbon filter ± alocal temperature increase is detectable concurrently with thecorrespondingly increased CO production.

Examinations have shown that very small glowing zones inthe scale of 5 � 10±5 of the total carbon filter volume aredetectable. Due to security reasons, the DCO control is oftenbuilt as a redundant system.

The detection of glowing zones with thermocouples is a veryinsensitive method compared to DCO control because of thelocal limitation of temperature measurement in general.

In common DCO monitoring, the signal is influenced by anumber of disturbances. These are essentially± CO peaks from upstream processes, e.g. combustion and

drying,± gas volume fluctuations and± temperature fluctuations.

CO peaks from combustion lead to an unintended change inthe measuring signal. At first, the concentration at themeasuring point of the gas inlet increases, whereas theconcentration remains low at the outlet. This results in anegative DCO value. As the peak reaches the outlet, themeasured CO concentration at this point is higher than at thegas inlet, which results in a high DCO peak. Such a high peakcan lead to a misinterpretation, resp. a supposed hot spotdetection.

Based on the fact that industrial DCO measuring instru-ments only emit a positive signal, using a smoothing methodlike calculating mean values or simliar, would lead to anexclusively positive signal and, therefore, to a misinterpreta-tion.

Fluctuations of the gas flow are not considered inconcentration measurements in general. The CO generationto be controlled is the product of gas flow and concentration.Reduced gas flow results in a higher DCO signal. This alsoleads to a misinterpretation of the measured concentrationsince the absolute CO production does not change at constanttemperature.

Temperature fluctuations change the CO production atincreasing temperature to higher values. This is important ifthere is no process equipment in front of the activated carbonfilter which is capable of regulating the gas temperature to anearly constant value, as for example a scrubber.

2 Performance of Forecast

The primary target of forecast is the early information of theplant operator about irregularities of the DCO production.

All DCO measurements and further operational data arestored and processed in a computer network, including arelational database for data analyzing and storing.

The analysis contains, among others, the± data compression (at high data volume),± plausibility checking and measured values adjustment (e.g.

software filtering to avoid combustion-caused CO peaks),

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±

[*] Dr.-Ing. P. Neumann, Dipl.-Ing. G. Lauber, Dipl.-Ing. Z. Hrabovzski,T. Pfeil, Prof. Dr.-Ing. K. G. Schmidt, Institut für Umwelttechnologie undUmweltanalytik e.V. (IUTA), Bliersheimer Straûe 60, D-47229 Duisburg,Germany.

0930-7516/98/1010-0808 $ 17.50+.50/0

± standardization of the measured values (e.g. dependency ofthe gas flow),

± analyzing of the concentration progress and generation ofdifferent mean values, as well as differentiation for thedetermination of the gradient (forecast).The single steps for an installed forecast system are

described below:1. Acquisition and storing of the DCO values every 4 seconds,

with corresponding status information (running, defect,maintenance) of the measuring instruments, as well asfurther operational data, such as gas flow, temperature, COconcentration, into a relational database.

2. Compressing of measuredDCO values to one-minute meanvalues. This is suitable without information loss because ofthe sluggish reaction of measuring instruments.A typical signal progress is shown in Fig. 1.

Figure 1. DCO signal progress of 1 minute mean values without softwarefiltering.

3. Disturbance signal suppression and standardization (rel-ative to temperature and gas flow) under consideration ofstatus information. In this way, validated values are thebasis for forecast.

Figure 2. DCO signal progress of 1 minute mean values with software filtering.

4. Quasi-continuous generation and storing of absolute meanvalues of the validated values for the periods of 10 minutes,1 hour, 6 hours, 12 hours, and 24 hours.

5. Quasi-continuous generation and storing of gradients of thevalidated values for the periods of 10 minutes, 1 hour, 6hours, 12 hours, and 24 hours. In case several successive one-minute values should be discarded in step 3, the gradientswill be calculated from the last validated one-minute data.(For example, if there are several high CO peaks from thecombustion over a period longer than 10 minutes, so thatthere are no valid data sampled for this period, the 10-minute gradient remains constant).

6. Execution of the DCO forecast through assessment of thegradients and absolute mean values by comparison withthreshold values, which define the limits for notification oralarm. These threshold values were determined by inten-sive evaluation of operation data on the facility. Calibrationand maintenance cycles, operation start and stop behavior,average measure signal levels over several weeks, drift ofthe zero setting and sensitivity changes of the measuringinstruments were considered.

7. Feedback of notifications of the forecast and, if necessary,triggering of warnings or alarms. The threshold values willbe fixed by the requirements of the plant and operatinginstructions. Such operating instructions can contain forexample inspection of measuring instruments and periph-ery, increased carbon discharge or inertisation of the filterwith nitrogen.Fig. 3 shows a principle progress of specific thresholds

(gradients) for discrete intervals of time. It may be surprisingat first that the threshold values for the 6-hour gradientpossess a minimum. The reasons for this are: The thresholdsfor 10 minutes and 1 hour have to be higher, because theinfluence of short-time fluctuations in the measured values ismuch stronger. This influence decreases with increasingperiods through larger attenuation of the values. With muchlonger periods, such as for 12 and 24 hours, the equipmentcaused zero-drift and sensivity change requires higher thresh-olds.

Figure 3. Threshold progress for DCO forecast.

3 Results

Using the DCO forecast presented, it is possible for the firsttime to make long-term statements. This is reached byelimination of system-immanent misinterpretations of the

Chem. Eng. Technol. 21 (1998) 10, Ó WILEY-VCH Verlag GmbH, D-69469 Weinheim, 1998 0930-7516/98/1010-0809 $ 17.50+.50/0 809

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810 Ó WILEY-VCH Verlag GmbH, D-69469 Weinheim, 1998 0930-7516/98/0101-00810 $ 17.50+.50/0 Chem. Eng. Technol. 21 (1998) 10

DCO signals. This forecast ensures an early, false-alarm-freedetection of glowing zones in activated carbon filters.

Operators and other responsible persons can take measuresin sufficiently good time to fight the hot spot or glowing zone.

The available period for an installed system covers 24 hoursat minimum to stop the plant without mechanical damage

through overheating and thus affect the environment. Thismeans that activated carbon filters can be operated even bycalling on demand.

Received: November 14, 1997 [K 2331]

This paper was also published in German in Chem. Ing. Tech. 70 (1998) No. 7.

Communications

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