CN109276990B - Circulating pump consumption reduction intelligent management system - Google Patents
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- 230000009467 reduction Effects 0.000 title claims description 13
- 230000000694 effects Effects 0.000 claims abstract description 30
- 238000001514 detection method Methods 0.000 claims abstract description 18
- 238000005265 energy consumption Methods 0.000 claims abstract description 12
- 239000002002 slurry Substances 0.000 claims description 38
- UGFAIRIUMAVXCW-UHFFFAOYSA-N Carbon monoxide Chemical compound [O+]#[C-] UGFAIRIUMAVXCW-UHFFFAOYSA-N 0.000 claims description 14
- 239000003546 flue gas Substances 0.000 claims description 14
- 238000010801 machine learning Methods 0.000 claims description 9
- 235000019738 Limestone Nutrition 0.000 claims description 5
- 238000010521 absorption reaction Methods 0.000 claims description 5
- 239000010440 gypsum Substances 0.000 claims description 5
- 229910052602 gypsum Inorganic materials 0.000 claims description 5
- 239000006028 limestone Substances 0.000 claims description 5
- 239000000284 extract Substances 0.000 claims description 4
- 238000000034 method Methods 0.000 claims description 4
- 239000000463 material Substances 0.000 claims description 3
- 238000004364 calculation method Methods 0.000 abstract description 5
- 230000009977 dual effect Effects 0.000 abstract description 5
- 238000005206 flow analysis Methods 0.000 abstract 1
- RAHZWNYVWXNFOC-UHFFFAOYSA-N Sulphur dioxide Chemical compound O=S=O RAHZWNYVWXNFOC-UHFFFAOYSA-N 0.000 description 114
- 230000009471 action Effects 0.000 description 3
- 238000011156 evaluation Methods 0.000 description 3
- 238000011161 development Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000004134 energy conservation Methods 0.000 description 2
- 239000003344 environmental pollutant Substances 0.000 description 2
- 230000006870 function Effects 0.000 description 2
- 238000012544 monitoring process Methods 0.000 description 2
- 231100000719 pollutant Toxicity 0.000 description 2
- 230000000007 visual effect Effects 0.000 description 2
- 239000002699 waste material Substances 0.000 description 2
- 239000003245 coal Substances 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 238000012706 support-vector machine Methods 0.000 description 1
- 239000013598 vector Substances 0.000 description 1
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
- B01D—SEPARATION
- B01D53/00—Separation of gases or vapours; Recovering vapours of volatile solvents from gases; Chemical or biological purification of waste gases, e.g. engine exhaust gases, smoke, fumes, flue gases, aerosols
- B01D53/34—Chemical or biological purification of waste gases
- B01D53/74—General processes for purification of waste gases; Apparatus or devices specially adapted therefor
- B01D53/80—Semi-solid phase processes, i.e. by using slurries
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
- B01D—SEPARATION
- B01D53/00—Separation of gases or vapours; Recovering vapours of volatile solvents from gases; Chemical or biological purification of waste gases, e.g. engine exhaust gases, smoke, fumes, flue gases, aerosols
- B01D53/34—Chemical or biological purification of waste gases
- B01D53/46—Removing components of defined structure
- B01D53/48—Sulfur compounds
- B01D53/50—Sulfur oxides
- B01D53/501—Sulfur oxides by treating the gases with a solution or a suspension of an alkali or earth-alkali or ammonium compound
- B01D53/502—Sulfur oxides by treating the gases with a solution or a suspension of an alkali or earth-alkali or ammonium compound characterised by a specific solution or suspension
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
- B01D—SEPARATION
- B01D53/00—Separation of gases or vapours; Recovering vapours of volatile solvents from gases; Chemical or biological purification of waste gases, e.g. engine exhaust gases, smoke, fumes, flue gases, aerosols
- B01D53/34—Chemical or biological purification of waste gases
- B01D53/46—Removing components of defined structure
- B01D53/48—Sulfur compounds
- B01D53/50—Sulfur oxides
- B01D53/501—Sulfur oxides by treating the gases with a solution or a suspension of an alkali or earth-alkali or ammonium compound
- B01D53/504—Sulfur oxides by treating the gases with a solution or a suspension of an alkali or earth-alkali or ammonium compound characterised by a specific device
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F04—POSITIVE - DISPLACEMENT MACHINES FOR LIQUIDS; PUMPS FOR LIQUIDS OR ELASTIC FLUIDS
- F04B—POSITIVE-DISPLACEMENT MACHINES FOR LIQUIDS; PUMPS
- F04B49/00—Control, e.g. of pump delivery, or pump pressure of, or safety measures for, machines, pumps, or pumping installations, not otherwise provided for, or of interest apart from, groups F04B1/00 - F04B47/00
- F04B49/06—Control using electricity
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
- B01D—SEPARATION
- B01D2258/00—Sources of waste gases
- B01D2258/02—Other waste gases
- B01D2258/0283—Flue gases
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Abstract
The invention provides a circulating pump consumption-reducing intelligent management system which is used for guiding operators of a power plant and comprises a working condition detection module, an operation tracking module, an operation effect tracking module, a computing platform and a display device, wherein the working condition detection module, the operation tracking module and the operation effect tracking module are responsible for data flow trajectory tracking, the computing platform is responsible for data flow analysis and calculation, and the display device is responsible for calculation result display. The system provided by the application can calculate and display the historical SO2 emission mean value and the estimated SO2 emission mean value in real time for operators, SO that the operators can conveniently know the working condition trend and the estimated SO2 emission trend in the past period of time in real time, more quickly master whether the working condition trend and the estimated SO2 emission trend exceed the standards or not, can check the operation of the operators, find out illegal operation and warn; the self-learning circulation pump can automatically learn, provide suitable operation suggestions for the same working condition and the cross working condition, and reasonably start and stop the circulation pump through the operation suggestions so as to achieve the dual purposes of ensuring the safety requirement of the circulation pump and reducing the energy consumption.
Description
Technical Field
The invention relates to the field of energy conservation and consumption reduction, in particular to an intelligent management system for consumption reduction of a circulating pump.
Background
In recent years, with the rapid development of electric utilities, strict control of the emission of pollutants generated by burning coal has become an important part of the development of electric utilities. The control of the sulfur dioxide emission in the tail flue gas of the boiler of the thermal power plant is an important ring for treating atmospheric pollutants, the state has a clear hourly emission average value standard of the sulfur dioxide concentration, and the over-standard emission penalty is serious.
A Distributed Control System (DCS) on the environment-friendly side of a power plant only provides a current instantaneous sulfur dioxide concentration value, whether the average value of the past 1 hour exceeds the standard or not cannot be determined, whether the average value of the future 1 hour exceeds the standard or not cannot be predicted, and field workers often start circulating pumps with more than necessary number to cause electric energy waste for ensuring that the average value does not exceed the standard. In the prior art, a set of complete management system is not provided, field staff can be effectively guided to reasonably operate the circulating pump, and the problem of electric energy waste always exists and is not solved. Therefore, an intelligent management system is urgently needed in the market to guide field workers and reasonably start and stop the circulating pump so as to achieve the dual purposes of ensuring the safety requirement of the circulating pump and reducing the energy consumption.
Disclosure of Invention
The invention provides a consumption-reducing intelligent management system for a circulating pump, which comprises a working condition detection module, an operation tracking module, an operation effect tracking module, a computing platform and display equipment.
The working condition detection module comprises various detection devices and is used for detecting the working condition state of the equipment, wherein the working condition state comprises boiler load, raw flue gas flow, raw flue gas SO2 concentration, net flue gas SO2 concentration, absorption tower gypsum slurry density, absorption tower gypsum slurry pH value, Aft tower slurry pH value, limestone slurry tank slurry density, slurry supply flow and the like;
the operation tracking module comprises various sensing devices arranged on the equipment and is used for acquiring the operation track of the equipment, wherein the operation track comprises the start and stop of each circulating pump, the start and stop of a slurry supply pump, the opening of a slurry supply valve and the like;
the operation effect tracking module is used for acquiring operation effect parameters corresponding to the operation track of the equipment, wherein the operation effect parameters comprise instantaneous values and hour average values of SO2 emission, energy consumption and material consumption;
for the above data flow monitoring and trajectory tracking, algorithms that can be used include euclidean distance of multidimensional vectors, euler functions, support vector machine algorithms.
The computing platform is used for computing the historical SO2 emission mean value in natural hours of every 1 minute in the past set time in real time according to the detection result of the working condition detection module, and judging whether the historical SO2 emission mean value exceeds the standard or not; calculating an estimated emission mean value of SO2 in natural hours of every 1 minute in a set time in the future according to the current working condition, and calculating whether an energy-saving space or exceeding possibility exists or not according to national emission standards, historical emission mean values of SO2 and estimated emission mean values of SO 2; the method comprises the steps that a computing platform associates equipment operation tracks, corresponding operation effect parameters and current equipment working condition states, the computing platform learns the equipment operation tracks and operation effects under various equipment working condition states through a machine learning method, a rule base is established, whether staff operation is in compliance or not is evaluated through the rule base, illegal operation is warned, or proper equipment operation tracks are given according to the rule base. In the present invention, the existing algorithms that can be used for the operation result analysis include a quick sorting algorithm and an ordered queue data comparison algorithm.
And the display device is used for displaying the national emission standard, the historical emission mean value of SO2 and the predicted emission mean value of SO 2.
Optionally, the display device displays the historical emission mean value of the SO2, the actually measured emission value of the SO2 and the working condition state of the device together in a visual mode, and the historical emission mean value of the SO2 is displayed in a curve mode, SO that an operator can know the working condition trend and the SO2 emission trend of a past period of time in real time conveniently, and whether the exceeding is already achieved or not is possible to be achieved or not is mastered more quickly.
Optionally, the user may set the emission target value through the computing platform under the national emission standard, and the computing platform provides a suitable device operation trajectory, which is as close as possible to the emission target value while meeting the national emission standard, so as to achieve the energy saving and consumption reduction target. On the display device, the emission target value is a straight line over a period of time set in the past, the emission target itself is identified, and the user can observe the difference between the measured emission value of the SO2 and the emission target value. If the measured emission values of SO2 are adjusted to be on the line of the emission target values during a period set in the future, the natural hour emission mean is the emission target value, i.e. it is a dynamic target emission curve.
Optionally, the system comprises an online knowledge network; the computing platform extracts the one-to-one correspondence equipment working condition state, equipment operation track and operation effect of the compliance and uploads the operation result to the online knowledge network. The device condition state here includes a base condition including a boiler load, a raw flue gas flow rate, and a raw flue gas SO2 concentration.
Optionally, the online knowledge network establishes different knowledge groups according to different equipment working conditions or basic working conditions, and calculates and evaluates the optimal equipment operation track in each group according to the operation effect. Under a normal working state, when the system monitors that the operation track of the equipment or the basic working condition changes, the system triggers the online knowledge network to perform machine learning, performs knowledge classification, induces the knowledge into different knowledge groups, and performs a series of actions such as evaluation and the like.
Optionally, the online knowledge network provides a fast retrieval capability, a data tracing capability, and a data tracing capability.
Optionally, the online knowledge network provides an optimal device operation trajectory of the current device operating condition state as an operation suggestion according to the current device operating condition state. The operation proposal specifically refers to a scheme for adjusting limestone slurry supply flow required by starting and stopping a specific circulating pump, matching the starting and stopping of the circulating pump, corresponding energy consumption after starting and stopping, a future instantaneous SO2 discharge value and the like. Because the operation suggestion supports data tracing, the working condition time and the specific working condition index, emission value index and the like according to the operation suggestion can be inquired, and the use suggestion has safe and credible basis.
Optionally, in a general case, after learning a knowledge point, the online knowledge network can only support an operation suggestion under the same working condition, but the online knowledge network of the present invention provides an operation suggestion across working conditions, for example, the current working condition has no better historical operation knowledge, but requires a higher working condition to have better operation knowledge, and the operation under the current working condition can be guided by using the operation suggestion, so as to make an operation suggestion.
Optionally, starting or stopping one pump has a great influence on the emission concentration of the SO2, and when the pump is not suitable for being recommended to be started or stopped, the pH value of the slurry is adjusted by means of the recommended slurry supply flow rate, SO that the emission concentration of the SO2 is adjusted. The online knowledge network learns the relation among the variation of the slurry supply flow, the variation of the slurry pH value and the variation of the SO2 discharge concentration through a machine, and provides an adjustment suggestion of the slurry supply flow through calculation, SO that the SO2 discharge concentration is controlled.
As can be seen from the above description of the present invention, compared with the prior art, the intelligent management system for consumption reduction of a circulation pump provided by the present invention has the following advantages:
1. the historical SO2 emission average value is calculated in real time and displayed to an operator, SO that the operator can conveniently know the working condition trend and the SO2 emission trend in the past period in real time, and can more quickly know whether the standard is exceeded or not and whether the standard is possibly exceeded or not.
2. Like the operator shows the SO2 predicted emission mean, the operator is facilitated to calculate whether there is an energy-saving space or an out-of-compliance possibility according to the national emission standard, the SO2 historical emission mean and the SO2 predicted emission mean.
3. And establishing a rule base through a machine learning method, automatically analyzing and evaluating whether the operation of the staff is in compliance, and warning illegal operation.
4. An online knowledge network with autonomous learning ability is established, rapid retrieval ability and data tracking ability are provided, and data tracing is supported.
5. The online knowledge network can provide suitable operation suggestions for the same working condition and the cross working condition, and the circulating pump is reasonably started and stopped through the operation suggestions so as to achieve the dual purposes of ensuring the safety requirement of the circulating pump and reducing the energy consumption.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the invention and not to limit the invention.
Wherein:
FIG. 1 is a schematic diagram of a first embodiment of an intelligent consumption-reducing management system for a circulation pump according to the present invention;
FIG. 2 is a schematic diagram of the second embodiment of the intelligent consumption-reducing management system for the circulation pump according to the present invention;
FIG. 3 is a flowchart illustrating a second embodiment of the intelligent consumption-reducing management system for a circulation pump according to the present invention;
Detailed Description
In order to make the technical problems, technical solutions and advantageous effects to be solved by the present invention clearer and clearer, the present invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The first embodiment is as follows: referring to fig. 1, the intelligent management system for reducing consumption of the circulating pump is used for guiding operators of a power plant to reasonably start and stop the circulating pump so as to achieve the dual purposes of ensuring the safety requirement of the circulating pump and reducing energy consumption.
The working condition detection module comprises various detection devices and is used for detecting the working condition state of the equipment, including real-time basic working condition monitoring. The working condition states comprise boiler load, raw flue gas flow, raw flue gas SO2 concentration, net flue gas SO2 concentration, absorption tower gypsum slurry density, absorption tower gypsum slurry pH value, Aft tower slurry pH value, limestone slurry box slurry density, slurry supply flow and the like. The base conditions include boiler load, raw flue gas flow, and raw flue gas SO2 concentration.
The operation tracking module comprises various sensing devices arranged on the equipment and is used for discovering operation and acquiring the operation track of the equipment, wherein the operation track comprises the start and stop of each circulating pump, the start and stop of a slurry supply pump, the opening of a slurry supply valve and the like;
the operation effect tracking module is used for acquiring operation effect parameters corresponding to the operation track of the equipment, wherein the operation effect parameters comprise instantaneous values and hour average values of SO2 emission, energy consumption and material consumption;
the computing platform is based on a working condition detection module and an operation tracking module, and the operation effect tracking module has the following functions:
according to the detection result of the working condition detection module, calculating the historical SO2 emission mean value in the natural hour of every 1 minute in the past 2 hours in real time, and judging whether the historical SO2 emission mean value exceeds the standard or not;
and calculating the estimated emission mean value of SO2 in natural hours of every 1 minute in the next 1 hour according to the current working condition, and calculating whether an energy-saving space is available or exceeds the standard according to the national emission standard, the historical emission mean value of SO2 and the estimated emission mean value of SO 2.
The method comprises the steps that a computing platform associates equipment operation tracks, corresponding operation effect parameters and current equipment working condition states, the computing platform learns the equipment operation tracks and operation effects under various equipment working condition states through a machine learning method, a rule base is established, whether staff operation is in compliance or not is evaluated through the rule base, illegal operation is warned, or proper equipment operation tracks are given according to the rule base.
The display equipment displays the national emission standard, the historical SO2 emission mean value, the actually measured SO2 emission value, the estimated SO2 emission mean value and the equipment working condition state together in a visual mode, the historical SO2 emission mean value is displayed in a curve mode, an operator can conveniently know the working condition trend and the SO2 emission trend in a past period of time in real time, and whether the standard exceeding is achieved or not is possible to be achieved or not can be mastered more quickly. Meanwhile, a user can set a discharge target value through the computing platform under the national discharge standard, and the computing platform gives a proper equipment operation track, so that the discharge target value is approached as much as possible while the national discharge standard is met, and the aims of energy conservation and consumption reduction are achieved. On the display device, the emission target value is a straight line over a period of time set in the past, the emission target itself is identified, and the user can observe the difference between the measured emission value of the SO2 and the emission target value. If the measured emission values of SO2 are adjusted to be on the line of the emission target values during a period set in the future, the natural hour emission mean is the emission target value, i.e. it is a dynamic target emission curve.
Example two: referring to fig. 2, the difference from the first embodiment is that the system of the present embodiment further includes an online knowledge network. The online knowledge network provides rapid retrieval capability, data tracking capability and data traceability capability.
And the rule base extracts the equipment working condition state, the equipment operation track and the operation effect which are in one-to-one correspondence with the compliance, and uploads the equipment working condition state, the equipment operation track and the operation effect to the online knowledge network.
The online knowledge network establishes different knowledge groups according to different equipment working condition states or basic working conditions, and calculates and evaluates the optimal equipment operation track in each group according to the operation effect. Under a normal working state, when the system monitors that the operation track of the equipment or the basic working condition changes, the system triggers the online knowledge network to perform machine learning, performs knowledge classification, induces the knowledge into different knowledge groups, and performs a series of actions such as evaluation and the like.
When the online knowledge network works, the online knowledge network provides the optimal equipment operation track of the current equipment working condition state as an operation suggestion according to the current equipment working condition state. The operation proposal specifically refers to a scheme for adjusting limestone slurry supply flow required by starting and stopping a specific circulating pump, matching the starting and stopping of the circulating pump, corresponding energy consumption after starting and stopping, a future instantaneous SO2 discharge value and the like. Because the operation suggestion supports data tracing, the working condition time and the specific working condition index, emission value index and the like according to the operation suggestion can be inquired, and the use suggestion has safe and credible basis.
The online knowledge network can also provide operation suggestions across working conditions, for example, the current working conditions do not have better historical operation knowledge, but the higher working conditions are required to have better operation knowledge, so that the operation of the current working conditions can be guided by using the operation suggestions.
Because the starting or stopping of one pump has great influence on the SO2 discharge concentration, when the pump is not suitable to be recommended to be started or stopped, the pH value of the slurry is adjusted by the method of recommending the slurry supply flow, and the adjustment on the SO2 discharge concentration is further realized. The online knowledge network can also control the SO2 emission concentration by learning the relationship among the variation of the slurry supply flow, the variation of the slurry pH value and the variation of the SO2 emission concentration through a machine and giving an adjustment suggestion of the slurry supply flow through calculation.
When the system works, referring to fig. 3, firstly, a data stream trajectory is tracked by a working condition detection module, an operation tracking module and an operation effect tracking module, and then the data stream is transmitted to a computing platform for analysis, wherein the computing platform mainly performs the following work:
1. the calculation platform calculates the historical emission mean value of SO2 and the predicted emission mean value of SO2, and displays the past 2-hour working condition, the trend graph of important measuring point values, the historical emission mean trend graph of SO2 and the predicted emission mean trend graph of SO2 in the future 1 hour through display equipment.
2. And discovering the operation through an operation tracking module, performing compliance check on the operation by using a rule base, and if the operation is found to be improper, performing violation warning.
3. The real-time basic working condition is monitored through the working condition detection module, historical operation is found out by utilizing the quick retrieval capability of the online knowledge network, the optimal operation recommendation of the current working condition is made, and when the historical operation matched with the current working condition cannot be found out, if the higher working condition is required to have better operation knowledge, the operation recommendation of the cross-basic working condition can be given by taking the reference.
4. And the online knowledge network performs machine learning and extracts new knowledge through a rule base. Firstly, an operation tracking module discovers operation, a computing platform acquires the equipment working condition state, the equipment operation track and the operation effect of the operation, the operation effect evaluation is carried out, a rule base is formed, the rule base can carry out compliance check on the subsequent operation, after the rule base is formed, the operation of compliance is extracted to an online learning network, and meanwhile, knowledge rule analysis and knowledge rule action range analysis are carried out through machine learning, so that the online knowledge network not only can acquire historical operation and carry out operation recommendation on the same working condition, but also can cross basic working conditions and carry out operation recommendation on the basic working conditions which do not appear.
In summary, compared with the prior art, the invention has the following advantages:
1. the historical SO2 emission average value is calculated in real time and displayed to an operator, SO that the operator can conveniently know the working condition trend and the SO2 emission trend in the past period in real time, and can more quickly know whether the standard is exceeded or not and whether the standard is possibly exceeded or not.
2. Like the operator shows the SO2 predicted emission mean, the operator is facilitated to calculate whether there is an energy-saving space or an out-of-compliance possibility according to the national emission standard, the SO2 historical emission mean and the SO2 predicted emission mean.
3. And establishing a rule base through a machine learning method, automatically analyzing and evaluating whether the operation of the staff is in compliance, and warning illegal operation.
4. An online knowledge network with autonomous learning ability is established, rapid retrieval ability and data tracking ability are provided, and data tracing is supported.
5. The online knowledge network can provide suitable operation suggestions for the same working condition and the cross working condition, and the circulating pump is reasonably started and stopped through the operation suggestions so as to achieve the dual purposes of ensuring the safety requirement of the circulating pump and reducing the energy consumption.
The invention has been described above with reference to the accompanying drawings, it is obvious that the invention is not limited to the specific implementation in the above-described manner, and it is within the scope of the invention to apply the inventive concept and solution to other applications without substantial modification.
Claims (7)
1. A consumption-reducing intelligent management system for a circulating pump is characterized by comprising a working condition detection module, an operation tracking module, an operation effect tracking module, a computing platform, display equipment and an online knowledge network;
the working condition detection module is used for detecting the working condition state of the equipment, and the working condition state comprises boiler load, raw flue gas flow and raw flue gas SO2Concentration, clean flue gas SO2Concentration, density of gypsum slurry of the absorption tower, pH value of slurry of the Aft tower, density of slurry of a limestone slurry tank and slurry supply flow;
the operation tracking module is used for acquiring an operation track of the equipment, wherein the operation track comprises the start and stop of each circulating pump, the start and stop of a slurry supply pump and the opening of a slurry supply valve;
an operation effect tracking module for collecting operation effect parameters corresponding to the operation track of the equipment, including SO2Instantaneous values and hour-average values of emission, energy consumption and material consumption;
the computing platform is used for computing the SO within the natural hour of every 1 minute in the past set time in real time according to the detection result of the working condition detection module2Average value of historical emission, judging SO2Whether the historical emission mean value exceeds the standard or not; according to the current working condition, calculating SO in natural hours of every 1 minute in the set time in the future2Estimated mean value of emissions, according to national emission standards, SO2Historical emission mean and SO2Calculating whether an energy-saving space or exceeding standard is possible or not according to the estimated emission mean value; the method comprises the steps that a computing platform associates equipment operation tracks, corresponding operation effect parameters and current equipment working condition states, the computing platform learns the equipment operation tracks and operation effects under various equipment working condition states through a machine learning method, a rule base is established, whether staff operation is in compliance or not is evaluated through the rule base, illegal operation is warned, or proper equipment operation tracks are given according to the rule base;
display device for displaying national emission standards, SO2Historical emission mean and SO2Predicting an emission mean value;
the computing platform extracts the one-to-one correspondence equipment working condition state, equipment operation track and operation effect of the compliance and uploads the operation result to the online knowledge network;
the online knowledge network autonomously learns the variation of the slurry supply flow, the variation of the slurry pH value and the SO2Controlling SO by calculating the relationship between the variation of the discharge concentration and giving a proposal for adjusting the slurry supply flow2The concentration of the emission.
2. The intelligent management system for consumption reduction of circulating pump of claim 1, wherein the display device displays SO2Average of historical emissions, SO2The measured emission value and the working condition state of the equipment are visually displayed together, and the SO2The historical emission mean is shown by a curve.
3. The intelligent management system for consumption reduction of circulation pump according to claim 1, wherein a discharge target value is set by the computing platform, and a dynamic target discharge curve is displayed by the display device.
4. The intelligent management system for consumption reduction of the circulating pump according to claim 1, wherein the online knowledge network establishes different knowledge groups according to different equipment working conditions, and calculates and evaluates the optimal equipment operation track in each group according to the operation effect.
5. The intelligent management system for consumption reduction of a circulation pump according to claim 4, wherein the online knowledge network provides fast retrieval capability, data tracking capability and data tracing capability.
6. The intelligent management system for consumption reduction of the circulating pump according to claim 5, wherein the online knowledge network provides an optimal equipment operation track of the current equipment working condition state as an operation suggestion according to the current equipment working condition state.
7. The intelligent management system for consumption reduction of a circulation pump according to claim 6, wherein the online knowledge network provides operation advice across operating conditions.
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| CN201811095896.0A CN109276990B (en) | 2018-09-19 | 2018-09-19 | Circulating pump consumption reduction intelligent management system |
| PCT/CN2019/089296 WO2020057171A1 (en) | 2018-09-19 | 2019-05-30 | Smart management system for consumption reduction of circulating pump |
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| CN201811095896.0A CN109276990B (en) | 2018-09-19 | 2018-09-19 | Circulating pump consumption reduction intelligent management system |
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| CN109276990B true CN109276990B (en) | 2021-05-28 |
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|---|---|---|---|---|
| CN103017560A (en) * | 2012-10-29 | 2013-04-03 | 中国石油化工股份有限公司 | Remote monitoring and furnace transfer decision-making specialist system for burning state of heating furnace |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH0919623A (en) * | 1995-07-07 | 1997-01-21 | Babcock Hitachi Kk | Wet type waste gas desulfurizing method and device therefor |
| JP3997340B2 (en) * | 1997-11-28 | 2007-10-24 | 株式会社Ｉｈｉ | Method of controlling the number of absorption tower circulation pumps in flue gas desulfurization equipment |
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| CN103017560A (en) * | 2012-10-29 | 2013-04-03 | 中国石油化工股份有限公司 | Remote monitoring and furnace transfer decision-making specialist system for burning state of heating furnace |
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