EP0559942B1 - Steuerung für ein Elektrofilter - Google Patents
Steuerung für ein Elektrofilter Download PDFInfo
- Publication number
- EP0559942B1 EP0559942B1 EP19920104314 EP92104314A EP0559942B1 EP 0559942 B1 EP0559942 B1 EP 0559942B1 EP 19920104314 EP19920104314 EP 19920104314 EP 92104314 A EP92104314 A EP 92104314A EP 0559942 B1 EP0559942 B1 EP 0559942B1
- Authority
- EP
- European Patent Office
- Prior art keywords
- breakdown
- filter
- control
- time
- control according
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Expired - Lifetime
Links
- 230000015556 catabolic process Effects 0.000 claims description 86
- 239000008186 active pharmaceutical agent Substances 0.000 claims description 30
- 238000005457 optimization Methods 0.000 claims description 26
- 238000011156 evaluation Methods 0.000 claims description 8
- 238000000034 method Methods 0.000 claims description 3
- 230000008569 process Effects 0.000 claims description 3
- 230000009467 reduction Effects 0.000 claims description 2
- 238000009434 installation Methods 0.000 claims 1
- 230000001537 neural effect Effects 0.000 claims 1
- 238000004148 unit process Methods 0.000 claims 1
- 238000012544 monitoring process Methods 0.000 description 20
- 238000002242 deionisation method Methods 0.000 description 17
- 230000006870 function Effects 0.000 description 10
- 238000012937 correction Methods 0.000 description 8
- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 description 4
- 238000013528 artificial neural network Methods 0.000 description 4
- 229910052799 carbon Inorganic materials 0.000 description 4
- 230000000694 effects Effects 0.000 description 3
- 239000012717 electrostatic precipitator Substances 0.000 description 2
- 230000009471 action Effects 0.000 description 1
- 238000013459 approach Methods 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 238000004590 computer program Methods 0.000 description 1
- 230000002950 deficient Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000005315 distribution function Methods 0.000 description 1
- 230000005611 electricity Effects 0.000 description 1
- 206010027175 memory impairment Diseases 0.000 description 1
- 238000012806 monitoring device Methods 0.000 description 1
- 239000004065 semiconductor Substances 0.000 description 1
- 239000007921 spray Substances 0.000 description 1
- 238000005507 spraying Methods 0.000 description 1
Images
Classifications
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B03—SEPARATION OF SOLID MATERIALS USING LIQUIDS OR USING PNEUMATIC TABLES OR JIGS; MAGNETIC OR ELECTROSTATIC SEPARATION OF SOLID MATERIALS FROM SOLID MATERIALS OR FLUIDS; SEPARATION BY HIGH-VOLTAGE ELECTRIC FIELDS
- B03C—MAGNETIC OR ELECTROSTATIC SEPARATION OF SOLID MATERIALS FROM SOLID MATERIALS OR FLUIDS; SEPARATION BY HIGH-VOLTAGE ELECTRIC FIELDS
- B03C3/00—Separating dispersed particles from gases or vapour, e.g. air, by electrostatic effect
- B03C3/34—Constructional details or accessories or operation thereof
- B03C3/66—Applications of electricity supply techniques
- B03C3/68—Control systems therefor
Definitions
- the present invention relates to a control for an electrostatic filter, in which filter breakdowns are continuously evaluated on the basis of evaluation rules and on the basis of the evaluation results new, optimized control parameters, i.e. at least one breakdown waiting time and one deionization time for which the electrostatic filter is determined and given to the electrostatic filter.
- a generic control is also known from EP 0 103 950 A2. With this control, the frequency of filter breakdowns is determined and control parameters are changed if the breakdown rate exceeds certain frequencies. The control of this font is already carrying out a certain self-optimization.
- the object of the present invention is to provide a further control for an electrostatic filter which optimizes and monitors itself.
- the allocation to the breakdown types is preferably weighted, the sum of the weightings always giving the value 1. Furthermore, an incoming breakdown is advantageously assigned to at most two types of breakdown at the same time.
- the incoming breakdown and a predeterminable number of immediately preceding breakdowns are preferably evaluated. In principle, however, it is also possible to work with a continuously acting forgetfulness factor.
- Self-optimization is particularly optimal if the filter current is also optimized, and only after the deionization time has been optimized.
- the filter current at which this filter voltage maximum is reached is then predefined as a filter current setpoint for the electrostatic filter.
- control has an optimization unit designed as a neural network, the control shows self-learning behavior. This makes it possible to optimize not only the control parameters, but also the evaluation rules themselves.
- the controller has a display device located in a control room, e.g. a monitor that is assigned can be displayed by means of the display device, process states, process data and / or the control parameters. This makes it possible to monitor the electrostatic filter and, if necessary, to take corrective action. It is also possible to manually enter new parameters into the control system and to observe their effects. As a result, the control can be optimized even further than the self-optimizing control itself can.
- the controller is at least partially implemented in an independent subsystem of a networked automation system of a technical system, i.e. the self-optimizing controller is used as an independent subsystem of the automation system, the self-optimizing controller and the rest of the networked automation system have as little effect possible.
- a networked automation system is described, for example, in the older DE application P 41 25 374.4.
- FIG 1 there is the power supply device of an electrostatic filter, e.g. a power plant, from a power unit 1, by means of which the electrostatic filter (not shown for the sake of clarity) is supplied with electricity.
- the power section 1 can be, for example, an intermediate circuit converter, as is generally known, e.g. from DE-OS 35 22 569 or DE-GM 90 03 125.
- the power section 1 is controlled via a control device 2, which controls the power section 1 on the basis of the specifications of the further control levels 3 to 5.
- the technical limits of power unit 1 are of course taken into account when driving power unit 1.
- the control device 2 receives its setpoints from the monitoring unit 3.
- the setpoints are, for example, the current setpoint I * for the filter current I F and an enable signal.
- the control device 2 reports to the monitoring unit 3 if it cannot control the power section 1 in accordance with requirements, for example because a wire break has occurred or because one of the semiconductor power elements of the power section 1 is defective.
- the filter voltage U F is continuously evaluated in the monitoring unit 3, and certain filter states, for example filter breakdown, short circuit or other errors, are inferred therefrom. Furthermore, the monitoring unit 3 records a filter characteristic from time to time, for example every minute, the meaning and purpose of which will be explained later in connection with FIG. 6.
- the monitoring unit 3 receives data both from the optimization unit 4 and from the user interface 5.
- the user interface 5 provides the monitoring unit 3 with, for example, the operating mode (pulse operation, DC voltage operation, mixed operation, etc.) and the time interval in which a filter characteristic curve is recorded again and again shall be.
- the further parameters are initially specified by the user interface 5 to the optimization unit 4, which is typically a fuzzy control unit.
- the optimization unit 4 specifies to the monitoring unit 3 the further control parameters which the monitoring unit 3 requires to control the control device.
- the control parameters will be explained in more detail later in FIG. 2.
- the optimization unit 4 automatically evaluates these messages on the basis of empirical values, determines new, optimized control parameters on the basis of the evaluation results and specifies these parameters to the monitoring unit 3.
- the control parameters are now explained in more detail below in connection with FIG. 2.
- FIG. 2 shows the current I F flowing in the electrostatic filter and the time t to the right.
- a filter breakdown occurs at time T 1 . If the filter breakdown has not gone out by itself by the time T 2 , the monitoring unit 3 blocks the control of the power section 1 via the release line 6. The power section 1 consequently no longer feeds energy into the electrostatic filter. The current I F in the electrostatic precipitator suddenly drops to zero due to a lack of further energy supply.
- the monitoring unit 3 releases the control device 2 again via the release line 6 and also gives the control device 2 the value I O as the new current setpoint.
- the filter current I F is then continuously increased to the value I *, which is reached at time T 4 , unless a new breakdown takes place beforehand.
- Typical control parameters for the power supply device of the electrostatic filter are now the breakdown waiting time t DS , the deionization time t E and the desired filter current I *.
- the breakdown waiting time t DS is given by the difference between the times T 2 and T 1 .
- the deionization time t E is given by the difference between the times T 3 and T 2 .
- Further possible control parameters are the rise time, ie the difference between the times T 4 and T 3 as well the current reduction after a breakdown, i.e. the difference between I O and I DS .
- the data of, for example, the last 100 copies are kept constantly available.
- the optimization unit 4 first optimizes the breakdown waiting time t DS .
- the optimization of the breakdown waiting time t DS is based on the fact of experience that self-extinguishing filter breakthroughs generally have a certain minimum duration on the one hand, but on the other hand no longer extinguish themselves above a certain maximum duration.
- the relative frequency of self-extinguishing filter breakdowns as a function of the extinguishing time t L is consequently calculated from the data stored in the optimization unit 4. Then we try to find a suitable distribution curve, For example, to fit a parabola or a Gaussian curve into the H values, as is shown schematically in FIG. In FIG 3, a parabola was fitted into the H values.
- the determination of the optimized breakdown waiting time t DS can also be carried out more easily. In this case it simply becomes the mean t L ⁇ the extinguishing times t L are determined and multiplied by a suitable factor F.
- weighting functions G F , G R and G Z shown in FIG. 4 instead of the weighting functions G F , G R and G Z shown in FIG. 4, other weighting functions can of course also be used be used. It should only be ensured that the sum of the selected weighting functions is always 1 and that the weighting functions G F and G Z do not overlap, or in other words that t 3 is always greater than or at most equal to t 2 .
- the number of copies to be saved can be specified as required. The number can be 50, for example, but can also be 500.
- the optimization unit 4 calculates the quotient of the number N R of representative punches and the number N F of secondary breakdowns.
- N F ⁇ G F
- the deionization time t E is optimal when the ratio of representative carbon to secondary carbon has a value that can be selected by the user, for example 10. If the ratio is greater than 10, the deionization time t E is too long and must therefore be reduced. Conversely, the deionization time t E must be increased if too many follow-throughs occur.
- the deionization time t E is optimized in the following way.
- a correction factor k E for the deionization time is calculated from the quotient of representative breakthroughs to follow-through breakthroughs based on a predetermined function curve.
- k E must be zero if the ratio of representative breakdowns to random breakdowns is reached.
- the correction factor k E must be greater than zero if the ratio is undershot and less than zero if the ratio is exceeded.
- a correction factor k I for the filter current setpoint I * then results from the ratio of N R to N Z.
- the slopes of the correction functions k E or k I can of course also run differently than shown in FIG. 5. In particular, they can be steeper or flatter if this is required for reasons of stability, and in particular the correction functions k E and k I can also be different from one another.
- the new, optimized control parameters t DS , t E and I * determined in this way are specified by the optimization unit 4 of the monitoring unit 3.
- the monitoring unit 3 therefore controls the electrostatic precipitator with these optimized control parameters t DS , t E and I * until the operating behavior of the electrostatic filter changes and a new correction of the control parameters t DS , t E and I * is necessary.
- the optimization unit 4 triggers the recording of a filter characteristic by the monitoring unit 3.
- the monitoring unit 3 receives then a filter characteristic of the filter voltage U F ie, as a function of the filter current I F is determined.
- the monitoring unit 3 is used as the setpoint I * for the filter current I F the maximum current I max , minus a safety discount of, for example, 5%, is predetermined and the filter current I F is optimized as described above.
- the monitoring unit 3 is given the setpoint I * for the filter current I F as the current at which the voltage maximum U max is reached.
- the optimization of the filter current described above is omitted.
- the optimization of the filter current would be pointless in this case, since above the voltage maximum U max a back spray would occur, which would greatly reduce the efficiency of the electrostatic filter.
- control device 2 the monitoring device 3, the optimization unit 4 and the user interface 5 can of course also be implemented in the form of a computer program, a hardware configuration is not necessary.
- present invention can of course also be used with pulsed electrostatic filters. In this case, the pulse height and duration as well as the pulse repetition frequency are available for optimization in addition to the breakdown waiting time t DS and deionization time t E.
- the optimization unit can of course not only understand the human, fuzzy logic, so it is not just a fuzzy control unit, but can also be designed as a neural network with self-learning behavior. This makes it possible not only to optimize the control parameters, but also the evaluation rules themselves.
- This self-learning behavior is generally known as "supervised learning by back propagation" of a neural network.
- the neural network can be formed in a manner known per se.
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- Engineering & Computer Science (AREA)
- Automation & Control Theory (AREA)
- Electrostatic Separation (AREA)
Priority Applications (3)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
EP19920104314 EP0559942B1 (de) | 1992-03-12 | 1992-03-12 | Steuerung für ein Elektrofilter |
DK92104314T DK0559942T3 (da) | 1992-03-12 | 1992-03-12 | |
DE59206952T DE59206952D1 (de) | 1992-03-12 | 1992-03-12 | Steuerung für ein Elektrofilter |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
EP19920104314 EP0559942B1 (de) | 1992-03-12 | 1992-03-12 | Steuerung für ein Elektrofilter |
Publications (2)
Publication Number | Publication Date |
---|---|
EP0559942A1 EP0559942A1 (de) | 1993-09-15 |
EP0559942B1 true EP0559942B1 (de) | 1996-08-21 |
Family
ID=8209428
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
EP19920104314 Expired - Lifetime EP0559942B1 (de) | 1992-03-12 | 1992-03-12 | Steuerung für ein Elektrofilter |
Country Status (3)
Country | Link |
---|---|
EP (1) | EP0559942B1 (da) |
DE (1) | DE59206952D1 (da) |
DK (1) | DK0559942T3 (da) |
Families Citing this family (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN105170333B (zh) * | 2015-09-06 | 2018-01-30 | 江苏科技大学 | 静电除尘用电源的模糊预测控制系统及方法 |
Family Cites Families (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US4311491A (en) * | 1980-08-18 | 1982-01-19 | Research Cottrell, Inc. | Electrostatic precipitator control for high resistivity particulate |
DE3364432D1 (en) * | 1982-07-28 | 1986-08-14 | Smidth & Co As F L | Method of protecting a thyristor switch of a pulse generator for an electrostatic precipitator |
DE3522569A1 (de) * | 1985-06-24 | 1987-01-02 | Metallgesellschaft Ag | Stromversorgung fuer ein elektrofilter |
US4811197A (en) * | 1987-09-02 | 1989-03-07 | Environmental Elements Corp. | Electrostatic dust collector system |
DE9003125U1 (de) * | 1990-03-16 | 1990-05-23 | Siemens AG, 1000 Berlin und 8000 München | Stromzwischenkreisumrichter zur Stromversorgung eines Elektrofilters |
-
1992
- 1992-03-12 DE DE59206952T patent/DE59206952D1/de not_active Expired - Fee Related
- 1992-03-12 EP EP19920104314 patent/EP0559942B1/de not_active Expired - Lifetime
- 1992-03-12 DK DK92104314T patent/DK0559942T3/da active
Also Published As
Publication number | Publication date |
---|---|
EP0559942A1 (de) | 1993-09-15 |
DK0559942T3 (da) | 1997-02-10 |
DE59206952D1 (de) | 1996-09-26 |
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