CN109569809A - A kind of desulfurization based on big data grinds system steel ball method of adjustment and system - Google Patents
A kind of desulfurization based on big data grinds system steel ball method of adjustment and system Download PDFInfo
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- CN109569809A CN109569809A CN201811346257.7A CN201811346257A CN109569809A CN 109569809 A CN109569809 A CN 109569809A CN 201811346257 A CN201811346257 A CN 201811346257A CN 109569809 A CN109569809 A CN 109569809A
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- steel ball
- grinding machine
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- current
- electric current
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Classifications
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B02—CRUSHING, PULVERISING, OR DISINTEGRATING; PREPARATORY TREATMENT OF GRAIN FOR MILLING
- B02C—CRUSHING, PULVERISING, OR DISINTEGRATING IN GENERAL; MILLING GRAIN
- B02C17/00—Disintegrating by tumbling mills, i.e. mills having a container charged with the material to be disintegrated with or without special disintegrating members such as pebbles or balls
- B02C17/18—Details
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B02—CRUSHING, PULVERISING, OR DISINTEGRATING; PREPARATORY TREATMENT OF GRAIN FOR MILLING
- B02C—CRUSHING, PULVERISING, OR DISINTEGRATING IN GENERAL; MILLING GRAIN
- B02C25/00—Control arrangements specially adapted for crushing or disintegrating
Abstract
The present invention provides a kind of desulfurization based on big data to grind system steel ball method of adjustment, and the desulfurization based on big data grinds system steel ball method of adjustment and includes the following steps: to carry out the grinding machine in power plant the operation data of operation monitoring and optimization monitoring to acquire grinding machine；Operation data based on the grinding machine acquired in real time and the history data for combining grinding machine, analyze the logical relation between each data, and the abrasion condition of network analysis steel ball is recommended to add steel ball scheme according to history optimizing and machine learning algorithm.Method of the invention overcomes prior art ball mill and steel ball is added mainly to judge by artificial experience, to personnel requirement height, and judge more rough disadvantage, by big data analysis, can accurate optimization steel ball matching, reduce system power consumption, realize fining operation operation, while reaching national requirements for environmental protection, realizes that enterprise operation is energy-saving, promote social resources rational exploitation and utilization.
Description
Technical field
The present invention relates to power plant for energy conservation environmental technology field, in particular to a kind of desulfurization based on big data grinds system steel
Ball method of adjustment and system.
Background technique
It proposes to push internet, big data, artificial intelligence and real economy depth integration at present, lead in innovation, green
The fields such as low-carbon, shared economy cultivate new growing point, form new kinetic energy；It is advanced to realize internet, big data, artificial intelligence etc.
The depth integration of technology and the manufacturing of Traditional Environmental-protection equipment, operation management pushes company's transition；Environmental protection equipment expert is established to determine
Plan system is learnt by the artificial intelligence of product practice and historical data, real by real-time theoretical calculation and history optimizing
Existing equipment refinement running optimizatin guidance, it is ensured that " environmental protection optimizes " and " economy maximizes ".
The information disclosed in the background technology section is intended only to increase the understanding to general background of the invention, without answering
When being considered as recognizing or imply that the information constitutes the prior art already known to those of ordinary skill in the art in any form.
Summary of the invention
The purpose of the present invention is to provide a kind of desulfurization based on big data to grind system steel ball method of adjustment and system, from
And the shortcomings that overcoming the prior art.
The present invention provides a kind of desulfurization based on big data grind system steel ball method of adjustment, it is described based on big data
Desulfurization grinds system steel ball method of adjustment and includes the following steps:
Operation monitoring and optimization monitoring are carried out to acquire the operation data of grinding machine to the grinding machine in power plant, wherein the grinding machine
Operation data include: grinding machine electric current, the instantaneous feeding coal of Weighing feeder, ingress filtering water flow, recycling tank filtered water stream amount,
Lime stone slurry density and grinding machine operating condition；
Operation data based on the grinding machine acquired in real time and the history data for combining grinding machine, the logic analyzed between each data are closed
System, the abrasion condition of network analysis steel ball are recommended to add steel ball scheme according to history optimizing and machine learning algorithm；
Wherein, described plus steel ball scheme specifically: when grinding machine resistance becomes smaller, when the electric current of mill main motor is too low, provides and add
Add steel ball suggestion；
And wherein, the history data of the grinding machine includes: that the historical data of grinding machine electric current, Weighing feeder are instantaneously fed
The historical data of amount, the historical data of ingress filtering water flow, the historical data of recycling tank filtered water stream amount, lime stone slurry
The historical data of density and the historical data of grinding machine operating condition.
Preferably, it in above-mentioned technical proposal, when grinding machine resistance becomes smaller, when the electric current of mill main motor is too low, provides and adds
Steel ball suggestion is added to specifically comprise the following steps:
When the electric current of mill main motor is lower than grinding machine lower current limit, prompts the too low numerical value of electric current and suggest the steel ball quantity of addition
Amount, or prompt check whether grinding machine breaks down.
Preferably, in above-mentioned technical proposal, wherein the calculation formula of addition steel ball amount are as follows:
Steel ball additive amount=(optimal grinding machine running current target value-current flow)/steel ball per ton increases the magnitude of current.
Preferably, in above-mentioned technical proposal, wherein the initial value that the steel ball per ton increases the magnitude of current is 0.5A/ tons, and
And wherein, the subsequent numerical value that the steel ball per ton increases the magnitude of current can be by the adaptive determination of machine learning dynamically to entangle
Partially.
The present invention provides a kind of desulfurization based on big data to grind system steel ball adjustment system, described based on big data
Desulfurization grinds system steel ball adjustment system
For carrying out operation monitoring and optimization monitoring to the grinding machine in power plant to acquire the unit of the operation data of grinding machine, wherein
The operation data of the grinding machine includes: grinding machine electric current, the instantaneous feeding coal of Weighing feeder, ingress filtering water flow, recycling tank
Filtered water stream amount, lime stone slurry density and grinding machine operating condition；
For the operation data based on the grinding machine acquired in real time and the history data of grinding machine is combined, analyzes patrolling between each data
The relationship of collecting, the abrasion condition of network analysis steel ball recommend the list for adding steel ball scheme according to history optimizing and machine learning algorithm
Member；
Wherein, described plus steel ball scheme specifically: when grinding machine resistance becomes smaller, when the electric current of mill main motor is too low, provides and add
Add steel ball suggestion；
And wherein, the history data of the grinding machine includes: that the historical data of grinding machine electric current, Weighing feeder are instantaneously fed
The historical data of amount, the historical data of ingress filtering water flow, the historical data of recycling tank filtered water stream amount, lime stone slurry
The historical data of density and the historical data of grinding machine operating condition.
Preferably, it in above-mentioned technical proposal, when grinding machine resistance becomes smaller, when the electric current of mill main motor is too low, provides and adds
Steel ball suggestion is added to specifically comprise the following steps:
When the electric current of mill main motor is lower than grinding machine lower current limit, prompts the too low numerical value of electric current and suggest the steel ball quantity of addition
Amount, or prompt check whether grinding machine breaks down.
Preferably, in above-mentioned technical proposal, wherein the calculation formula of addition steel ball amount are as follows:
Steel ball additive amount=(optimal grinding machine running current target value-current flow)/steel ball per ton increases the magnitude of current.
Preferably, in above-mentioned technical proposal, wherein the initial value that the steel ball per ton increases the magnitude of current is 0.5A/ tons, and
And wherein, the subsequent numerical value that the steel ball per ton increases the magnitude of current can be by the adaptive determination of machine learning dynamically to entangle
Partially.
Compared with prior art, the invention has the following beneficial effects: be based on machine learning, clustering, track following
Etc. big datas technology, line opertions engineering teacher lower to various operating conditions the real-time operation record of equipment, equipment running status are carried out
Machine autonomous learning and real-time monitoring；Equipment normal operation rules are concluded in realization, optimal by history optimizing and theory
Calculating combines, and provides environmentally friendly island equipment refinement equipment running optimizatin guiding opinion for line opertions engineering teacher；Realize machine
Learn aid decision.It is the measuring points such as feeding coal, confluent, Main motor current of taking advantage of a situation that support, which is ground, and each operation equipment operation
The real-time visual function of state provides judgement support for operator.It realizes and task is ground with the completion of alap energy consumption.
Monitor material-water ratio reasonable disposition；The current strength of mill main motor is monitored, determines and adds steel ball opportunity, reach energy-saving effect.Currently
Ball mill adds steel ball mainly to judge by artificial experience, and to personnel requirement height, and judgement is more rough, passes through big data point
Analysis, can accurate optimization steel ball matching, reduce system power consumption, realize fining operation operation, reaching the same of national requirements for environmental protection
When, realize that enterprise operation is energy-saving.Promote social resources rational exploitation and utilization.
Detailed description of the invention
By reading the following detailed description of the preferred embodiment, various other advantages and benefits are common for this field
Technical staff will become clear.The drawings are only for the purpose of illustrating a preferred embodiment, and is not considered as to the present invention
Limitation.And throughout the drawings, the same reference numbers will be used to refer to the same parts.In the accompanying drawings:
Fig. 1 is that the desulfurization based on big data of embodiment according to the present invention grinds the method flow of system steel ball method of adjustment
Figure.
Specific embodiment
The illustrative embodiments of the disclosure are more fully described below with reference to accompanying drawings.Although showing this public affairs in attached drawing
The illustrative embodiments opened, it being understood, however, that may be realized in various forms the disclosure without the reality that should be illustrated here
The mode of applying is limited.It is to be able to thoroughly understand the disclosure on the contrary, providing these embodiments, and can be by this public affairs
The range opened is fully disclosed to those skilled in the art.
In operation, steel ball is constantly worn grinding machine, and the steel ball consumption in cylinder is serious.The big size imbalance of steel ball, steel ball
Impact force weaken, grind lime stone cannot well.Grinding machine electric current is shown as lower than normal value, wet ball mill power output
Lower than design conditions, power consumption is increased.A kind of desulfurization based on big data is needed to grind system steel ball method of adjustment.
Fig. 1 is that the desulfurization based on big data of embodiment according to the present invention grinds the method stream of system steel ball method of adjustment
Cheng Tu.As shown, the method for the present invention includes following steps:
Step 101: operation monitoring and optimization monitoring being carried out to acquire the operation data of grinding machine to the grinding machine in power plant, wherein institute
The operation data for stating grinding machine includes: grinding machine electric current, the instantaneous feeding coal of Weighing feeder, ingress filtering water flow, recycling tank mistake
Drainage flow, lime stone slurry density and grinding machine operating condition；
Step 102: the operation data based on the grinding machine acquired in real time and the history data for combining grinding machine are analyzed between each data
Logical relation, the abrasion condition of network analysis steel ball recommends plus steel ball scheme according to history optimizing and machine learning algorithm；
Wherein, described plus steel ball scheme specifically: when grinding machine resistance becomes smaller, when the electric current of mill main motor is too low, provides and add
Add steel ball suggestion；
And wherein, the history data of the grinding machine includes: that the historical data of grinding machine electric current, Weighing feeder are instantaneously fed
The historical data of amount, the historical data of ingress filtering water flow, the historical data of recycling tank filtered water stream amount, lime stone slurry
The historical data of density and the historical data of grinding machine operating condition.
Preferably, it in above-mentioned technical proposal, when grinding machine resistance becomes smaller, when the electric current of mill main motor is too low, provides and adds
Steel ball suggestion is added to specifically comprise the following steps:
When the electric current of mill main motor is lower than grinding machine lower current limit, prompts the too low numerical value of electric current and suggest the steel ball quantity of addition
Amount, or prompt check whether grinding machine breaks down.
Preferably, in above-mentioned technical proposal, wherein the calculation formula of addition steel ball amount are as follows:
Steel ball additive amount=(optimal grinding machine running current target value-current flow)/steel ball per ton increases the magnitude of current.
Preferably, in above-mentioned technical proposal, wherein the initial value that the steel ball per ton increases the magnitude of current is 0.5A/ tons, and
And wherein, the subsequent numerical value that the steel ball per ton increases the magnitude of current can be by the adaptive determination of machine learning dynamically to entangle
Partially.
The present invention provides a kind of desulfurization based on big data to grind system steel ball adjustment system, described based on big data
Desulfurization grinds system steel ball adjustment system
For carrying out operation monitoring and optimization monitoring to the grinding machine in power plant to acquire the unit of the operation data of grinding machine, wherein
The operation data of the grinding machine includes: grinding machine electric current, the instantaneous feeding coal of Weighing feeder, ingress filtering water flow, recycling tank
Filtered water stream amount, lime stone slurry density and grinding machine operating condition；
For the operation data based on the grinding machine acquired in real time and the history data of grinding machine is combined, analyzes patrolling between each data
The relationship of collecting, the abrasion condition of network analysis steel ball recommend the list for adding steel ball scheme according to history optimizing and machine learning algorithm
Member；
Wherein, described plus steel ball scheme specifically: when grinding machine resistance becomes smaller, when the electric current of mill main motor is too low, provides and add
Add steel ball suggestion；
And wherein, the history data of the grinding machine includes: that the historical data of grinding machine electric current, Weighing feeder are instantaneously fed
The historical data of amount, the historical data of ingress filtering water flow, the historical data of recycling tank filtered water stream amount, lime stone slurry
The historical data of density and the historical data of grinding machine operating condition.
Preferably, it in above-mentioned technical proposal, when grinding machine resistance becomes smaller, when the electric current of mill main motor is too low, provides and adds
Steel ball suggestion is added to specifically comprise the following steps:
When the electric current of mill main motor is lower than grinding machine lower current limit, prompts the too low numerical value of electric current and suggest the steel ball quantity of addition
Amount, or prompt check whether grinding machine breaks down.
Preferably, in above-mentioned technical proposal, wherein the calculation formula of addition steel ball amount are as follows:
Steel ball additive amount=(optimal grinding machine running current target value-current flow)/steel ball per ton increases the magnitude of current.
Preferably, in above-mentioned technical proposal, wherein the initial value that the steel ball per ton increases the magnitude of current is 0.5A/ tons, and
And wherein, the subsequent numerical value that the steel ball per ton increases the magnitude of current can be by the adaptive determination of machine learning dynamically to entangle
Partially.
In several embodiments provided by the present invention, it should be understood that disclosed device and method can pass through it
Its mode is realized.For example, the apparatus embodiments described above are merely exemplary, for example, the division of the unit, only
Only a kind of logical function partition, there may be another division manner in actual implementation, such as multiple units or components can be tied
Another system is closed or is desirably integrated into, or some features can be ignored or not executed.Another point, it is shown or discussed
Mutual coupling, direct-coupling or communication connection can be through some interfaces, the INDIRECT COUPLING or logical of device or unit
Letter connection can be electrical property, mechanical or other forms.
The unit as illustrated by the separation member may or may not be physically separated, aobvious as unit
The component shown may or may not be physical unit, it can and it is in one place, or may be distributed over multiple
In network unit.It can select some or all of unit therein according to the actual needs to realize the mesh of this embodiment scheme
's.
It, can also be in addition, the functional units in various embodiments of the present invention may be integrated into one processing unit
It is that each unit physically exists alone, can also be integrated in one unit with two or more units.Above-mentioned integrated list
Member both can take the form of hardware realization, can also realize in the form of hardware adds SFU software functional unit.
The above-mentioned integrated unit being realized in the form of SFU software functional unit can store and computer-readable deposit at one
In storage media.Above-mentioned SFU software functional unit is stored in a storage medium, including some instructions are used so that a computer
It is each that equipment (can be personal computer, server or the network equipment etc.) or processor (processor) execute the present invention
The part steps of embodiment the method.And storage medium above-mentioned includes: USB flash disk, mobile hard disk, read-only memory (Read-
Only Memory, ROM), random access memory (Random Access Memory, RAM), magnetic or disk etc. it is various
It can store the medium of program code.
Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention., rather than its limitations；To the greatest extent
Pipe present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that: its according to
So be possible to modify the technical solutions described in the foregoing embodiments, or to some or all of the technical features into
Row equivalent replacement；And these are modified or replaceed, various embodiments of the present invention technology that it does not separate the essence of the corresponding technical solution
The range of scheme.
Claims (8)
1. a kind of desulfurization based on big data grinds system steel ball method of adjustment, it is characterised in that: described de- based on big data
Sulphur grinds system steel ball method of adjustment and includes the following steps:
Operation monitoring and optimization monitoring are carried out to acquire the operation data of grinding machine to the grinding machine in power plant, wherein the grinding machine
Operation data include: grinding machine electric current, the instantaneous feeding coal of Weighing feeder, ingress filtering water flow, recycling tank filtered water stream amount,
Lime stone slurry density and grinding machine operating condition；
Operation data based on the grinding machine acquired in real time and the history data for combining grinding machine, the logic analyzed between each data are closed
System, the abrasion condition of network analysis steel ball are recommended to add steel ball scheme according to history optimizing and machine learning algorithm；
Wherein, described plus steel ball scheme specifically: when grinding machine resistance becomes smaller, when the electric current of mill main motor is too low, provides and add
Add steel ball suggestion；
And wherein, the history data of the grinding machine includes: that the historical data of grinding machine electric current, Weighing feeder are instantaneously fed
The historical data of amount, the historical data of ingress filtering water flow, the historical data of recycling tank filtered water stream amount, lime stone slurry
The historical data of density and the historical data of grinding machine operating condition.
2. the desulfurization based on big data grinds system steel ball method of adjustment as described in claim 1, it is characterised in that: when grinding
Machine resistance becomes smaller, and when the electric current of mill main motor is too low, provides addition steel ball suggestion and specifically comprises the following steps:
When the electric current of mill main motor is lower than grinding machine lower current limit, prompts the too low numerical value of electric current and suggest the steel ball quantity of addition
Amount, or prompt check whether grinding machine breaks down.
3. the desulfurization based on big data grinds system steel ball method of adjustment as claimed in claim 2, it is characterised in that: wherein,
Add the calculation formula of steel ball amount are as follows:
Steel ball additive amount=(optimal grinding machine running current target value-current flow)/steel ball per ton increases the magnitude of current.
4. the desulfurization based on big data grinds system steel ball method of adjustment as claimed in claim 3, it is characterised in that: wherein,
The initial value that the steel ball per ton increases the magnitude of current is 0.5A/ tons, and wherein, the steel ball per ton increases the subsequent of the magnitude of current
Numerical value can be by the adaptive determination of machine learning with dynamic correcting.
5. a kind of desulfurization based on big data grinds system steel ball adjustment system, it is characterised in that: described de- based on big data
Sulphur grinds system steel ball adjustment system
For carrying out operation monitoring and optimization monitoring to the grinding machine in power plant to acquire the unit of the operation data of grinding machine, wherein
The operation data of the grinding machine includes: grinding machine electric current, the instantaneous feeding coal of Weighing feeder, ingress filtering water flow, recycling tank
Filtered water stream amount, lime stone slurry density and grinding machine operating condition；
For the operation data based on the grinding machine acquired in real time and the history data of grinding machine is combined, analyzes patrolling between each data
The relationship of collecting, the abrasion condition of network analysis steel ball recommend the list for adding steel ball scheme according to history optimizing and machine learning algorithm
Member；
Wherein, described plus steel ball scheme specifically: when grinding machine resistance becomes smaller, when the electric current of mill main motor is too low, provides and add
Add steel ball suggestion；
And wherein, the history data of the grinding machine includes: that the historical data of grinding machine electric current, Weighing feeder are instantaneously fed
The historical data of amount, the historical data of ingress filtering water flow, the historical data of recycling tank filtered water stream amount, lime stone slurry
The historical data of density and the historical data of grinding machine operating condition.
6. the desulfurization based on big data grinds system steel ball adjustment system as claimed in claim 5, it is characterised in that: when grinding
Machine resistance becomes smaller, and when the electric current of mill main motor is too low, provides addition steel ball suggestion and specifically comprises the following steps:
When the electric current of mill main motor is lower than grinding machine lower current limit, prompts the too low numerical value of electric current and suggest the steel ball quantity of addition
Amount, or prompt check whether grinding machine breaks down.
7. the desulfurization based on big data grinds system steel ball adjustment system as claimed in claim 6, it is characterised in that: wherein,
Add the calculation formula of steel ball amount are as follows:
Steel ball additive amount=(optimal grinding machine running current target value-current flow)/steel ball per ton increases the magnitude of current.
8. the desulfurization based on big data grinds system steel ball adjustment system as claimed in claim 7, it is characterised in that: wherein,
The initial value that the steel ball per ton increases the magnitude of current is 0.5A/ tons, and wherein, the steel ball per ton increases the subsequent of the magnitude of current
Numerical value can be by the adaptive determination of machine learning with dynamic correcting.
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| CN201811346257.7A CN109569809A (en) | 2018-11-13 | 2018-11-13 | A kind of desulfurization based on big data grinds system steel ball method of adjustment and system |
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| CN109847866A (en) * | 2019-04-23 | 2019-06-07 | 山东钢铁股份有限公司 | A kind of grinding machine ball adding control method and system |
| CN111871589A (en) * | 2020-08-06 | 2020-11-03 | 保定正德电力技术有限公司 | Intelligent control method for wet ball mill pulping system |
| CN116832912A (en) * | 2023-09-01 | 2023-10-03 | 国能龙源环保有限公司 | Method, device and equipment for determining steel ball addition amount of wet ball mill |
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