CN102937572A - Novel monitoring method for oil waste judgment - Google Patents
Novel monitoring method for oil waste judgment Download PDFInfo
- Publication number
- CN102937572A CN102937572A CN 201210444702 CN201210444702A CN102937572A CN 102937572 A CN102937572 A CN 102937572A CN 201210444702 CN201210444702 CN 201210444702 CN 201210444702 A CN201210444702 A CN 201210444702A CN 102937572 A CN102937572 A CN 102937572A
- Authority
- CN
- China
- Prior art keywords
- heavy metal
- separation
- metal ion
- monitoring
- enrichment
- 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.)
- Pending
Links
Landscapes
- Investigating Or Analyzing Non-Biological Materials By The Use Of Chemical Means (AREA)
Abstract
The invention relates to a novel monitoring method for oil waste judgment. The novel monitoring method uses a prediction technique to separate heavy metal ions and particularly relates to a prediction model for enrichment, separation and monitoring of the heavy metal ions and based on fuzzy control. A PEG 6000-(NH4)2SO4-H2O system is used for surveying enrichment and separation of oils, namely empirical rules simulating expert knowledge is generated from collected data under certain conditions, and a mapping relation of interference conditions on influencing factors of heavy metal particulars in the oils is built. A separation process can be forecasted through the rules by only setting a group of the conditions, best separation conditions are determined, and the best separation conditions comprise 10mL of 25% PEG6000, 5g of (NH4)2SO4, 2.5ml of 0.1g/ml KI solution in the pH of 2.0 and 0.5 ml of 5*10-3mol/L crystal violet solution. The new monitoring method simplifies relevant complex tests, is less in investment, high in metal ion recovery rate and simple and convenient to operate, basically controls discharge of the oils and reduces pollution of the heavy metal ions on the environment.
Description
Technical field
The present invention relates to oil product and declare useless a kind of new method, specifically a kind ofly utilize PEG2000-(NH by forecasting techniques
4)
2SO
4-H
2The O system is to the research method of heavy metal ion enrichment, makes it fast enrichment of heavy metal ion in the oil product and separates, and reduces the fluid discharging and environment is produced pollutes, and this method is used for the environmental protection treatment fields such as environmental protection, environmental monitoring, and effect is better.
Background technology
[0002] heavy metal ion is the problem that environmental protection treatment field back warp often runs into to environment generation pollution in the waste oil liquid discharge process.But separate and observation process because some parameters are very complicated, be difficult to control, so that the separation of some routines and monitoring method often are difficult to obtain the result that is satisfied with.Although the appearance of the sensitive developer that some are new makes the monitoring of the heavy metal ion of environmental pollution obtain very fast development, but still can't for a long time, stably drop into automatically operation, seriously restrict the further raising of monitoring automation level.In various Advanced Control Strategies, forecasting techniques is that a kind of of application potential arranged at present very much.It adopts the control strategies such as multi-step prediction, rolling optimization and feedback compensation, thereby controls effective.The present invention uses PEG2000-(NH
4)
2SO
4-H
2O system and forecasting techniques are determined some parameters in separating of heavy metal ion and the observation process, set up appropriate scheme fast monitored heavy metal particle.The method small investment, heavy metal removal rate height, simple to operation.
Summary of the invention
It is very complicated the present invention relates to a kind of some parameters for heavy metal ion monitoring and detachment process in the oil product, and unmanageable characteristics are so that the separation of some routines is difficult to obtain satisfied result.Propose the new method of a kind of separation of heavy metal ions and monitoring, proposed a kind of based on the separation of heavy metal ions of fuzzy control and the forecast model of monitoring.Utilize PEG6000-(NH
4)
2SO
4-H
2The O system under certain conditions namely, produces the empirical rule of simulation expertise to the research of the separation and concentration of heavy metal ion from the data that gather, set up disturbed condition to the mapping relations of the influence factor of micro heavy.As long as setting a set condition just can predict this detachment process by these rules.Concrete steps:
In the ground color comparison tube of 50ml, add successively the potassium iodide of 2.5ml0.1g/ml, concentration is 5 * 10
-3The crystal violet solution 0.5ml of mol/L, a certain amount of liquid to be measured that dissolved with zellon adds 25% PEG6000 solution 10ml again, shakes up, and adds buffer solution and regulates the pH value, and be diluted with water to 25ml.Then the ammonium sulfate solids that adds 5.0g was vibrated 5 minutes, left standstill, and after layering, the 50ml color comparison tube was put in lower floor's phase-splitting, was diluted with water to scale and measured zinc content.Upper strata PEG6000 is moved in the color comparison tube of 50ml mutually in addition, regulate acidity, be diluted with water to scale.Vibration shakes up, and with the cuvette of 1cm, measures in the 600nm place take corresponding reagent blank as reference, then finds corresponding cadmium, chromium and lead content from working curve.
The beneficial effect of the inventive method is to adopt forecasting techniques to carry out the heavy metal ion enrichment separation and monitor obtaining efficient, stable control effect.Adopt fuzzy prediction technology to make heavy metal particle just can determine the scheme of monitoring within very short time, its enrichment and monitoring degree can reach 100%, and separation efficiency is high, and small investment, heavy metal removal rate are up to 100%, simple to operation.Be suitable for the environment-friendly disposal systems such as environmental protection, environmental monitoring and carry out prevention initiatively and the pollution that controls environment.
Realization the object of the invention is further described:
The separation and concentration of heavy metal ion and observation process often have larger inertia and hysteresis, and become when being non-linear and slow.The PREDICTIVE CONTROL success is applied to the separation and concentration of heavy metal particle in the fluid and a key issue of observation process control.Adopt the forecast model of the separation and concentration condition of fuzzy control heavy metal particle.Namely on the basis of test, from the data that gather, produce the empirical rule of simulation expertise, set up the consumption of acidity, developer consumption, phase-splitting salt to the mapping relations of the influence factor of heavy metal monitoring.In trial stretch, just can predict this separation and observation process by these rules as long as set one group of condition to the heavy metal monitoring, thereby simplify relevant sophisticated testing like this.
When establishing the fuzzy variable that E is condition part, i.e. H
2SO
4The consumption of solution, the dilute strength of fluid to be measured, phase-splitting salt (NH
4)
2SO
4Consumption and the concentration of PEG6000; The fuzzy variable of the corresponding conclusion part of U, the i.e. content of heavy metal particle.Utilize fuzzy control technology, determine first input, output variable membership function, from existing test figure, set up fuzzy rule base; Final by the reverse gelatinization, dope the content of heavy metal ion.
In trial stretch, obtained at crystal violet solution consumption 0.5ml, phase-splitting salt (NH
4)
2SO
4The consumption 2.5mL of consumption 5g, KI solution and the concentration of PEG6000 be under 25% the condition, carry out the top condition of separation of heavy metal ions.Utilize fuzzy control technology to input, export the precision and quantity-variation obfuscation, set up fuzzy rule base, the non-linear of the two and the time become relation and reflect.Like this, when setting one group of data, just the top condition that heavy metal separates can be predicted out by this fuzzy control model.Top condition is: the 10mL of 25% PEG2000 and (NH
4)
2SO
4The KI solution, 5 * 10 of 5g, pH=2.0,2.5ml0.1g/ml
-3The crystal violet solution 0.5ml of mol/L.Between the relative error Jie Yu – 4～+ 4% of measured value and predicted value, present preferably anastomose property.
Claims (2)
1. an oil product heavy metal ion enrichment separates and the method for monitoring, it is characterized in that, has set up a kind of forecast model of the heavy metal ion enrichment separating monitoring based on fuzzy control, makes the very fast concentration and separation of heavy metal ion;
The method of concrete concentration and separation was divided into for two stages and carries out as follows:
Stage 1: utilize PEG6000-(NH
4)
2SO
4-H
2The O system uses the forecasting techniques fast monitored to affect the disturbance source of separation of heavy metal ions to the research of the separation and concentration of heavy metal ion, establishes suitable separating monitoring condition;
Stage 2: under appropriate separation condition, heavy metal ion is monitored separation.
2. the described heavy metal ion enrichment method of separating according to claim 1, it is characterized in that, in stage 1, according to the disturbance source that affects its separation in the separation of heavy metal ions enrichment process, set up a fuzzy mathematical model that comprises various disturbances, adopt forecasting techniques to monitoring and forecasting and the control of heavy metal ion in the oil product, establish suitable monitoring condition.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN 201210444702 CN102937572A (en) | 2012-11-09 | 2012-11-09 | Novel monitoring method for oil waste judgment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN 201210444702 CN102937572A (en) | 2012-11-09 | 2012-11-09 | Novel monitoring method for oil waste judgment |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN102937572A true CN102937572A (en) | 2013-02-20 |
Family
ID=47696483
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN 201210444702 Pending CN102937572A (en) | 2012-11-09 | 2012-11-09 | Novel monitoring method for oil waste judgment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN102937572A (en) |
-
2012
- 2012-11-09 CN CN 201210444702 patent/CN102937572A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Wang et al. | A deep learning based dynamic COD prediction model for urban sewage | |
| CN101382556A (en) | Soft measurement method for floating fine coal ash from slurry based on data drive | |
| CN104792529A (en) | Rolling bearing life prediction method based on state-space model | |
| CN105701559A (en) | Short-term load prediction method based on time sequence | |
| CN102778843B (en) | Operation control method of high magnetic grading process | |
| CN106125612B (en) | A kind of operation bucket number recognition methods and identification device for loading mechanical shovel and filling process | |
| CN104460721B (en) | Method for optimally controlling underflow concentration in hydrometallurgy dense washing process | |
| CN105224772A (en) | A kind of Nenjiang representative region Ecology methods of risk assessment based on system dynamics decision model | |
| CN104932488A (en) | Model predictive control performance evaluation and diagnosis method | |
| CN105278520A (en) | Complex industrial process running state evaluation method and application based on T-KPRM | |
| CN104848885A (en) | Method for predicting time of future failure of equipment | |
| CN106199174A (en) | Extruder energy consumption predicting abnormality method based on transfer learning | |
| CN102628856A (en) | Combination method for determining lacustrine nutriment reference state | |
| CN109523069A (en) | A method of filler intensive parameter is predicted using machine learning | |
| Matheri et al. | Sustainable circularity and intelligent data-driven operations and control of the wastewater treatment plant | |
| CN109885012B (en) | Real-time optimization compensation method for gold hydrometallurgy full flow | |
| CN109160581A (en) | Determine the methods and applications of the electrolysis time of electrochemical treatments high ammonia-nitrogen wastewater with high salt | |
| CN203772781U (en) | Characteristic variable-based sewage total phosphorus measuring device | |
| CN114757365A (en) | High-speed railway roadbed settlement prediction and early warning method based on deep learning | |
| CN103353295A (en) | Method for accurately predicating vertical deformation of dam body | |
| CN104263960B (en) | On-line prediction method for replacement rate and gold mud grade in gold hydrometallurgy replacement process | |
| CN102937572A (en) | Novel monitoring method for oil waste judgment | |
| CN107563656A (en) | The evaluation method of golden hydrometallurgy cyanidation-leaching process running status | |
| CN104296801B (en) | Hydrometallurgy thick washing process key variable detection method | |
| CN103713619B (en) | A kind of method of testing of grinding process progress control method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C02 | Deemed withdrawal of patent application after publication (patent law 2001) | ||
| WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20130220 |