CN105389638B - Retired uranium tailings pond environmental stability analysis and prediction method based on uncertain theory - Google Patents
Retired uranium tailings pond environmental stability analysis and prediction method based on uncertain theory Download PDFInfo
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Abstract
The retired uranium tailings pond environmental stability analysis and prediction method based on uncertain theory that disclosed herein is a kind of, stability analysis include the foundation of uranium tailings pond environmental stability index system, the calculating of each index stable region, the analysis of each monolith ambient stable rate of uranium tailings pond；Environmental stability prediction includes prediction the time required to being converted into unstable state by stable state, is converted into stable state required time prediction by unstable state.The stable region of uranium tailings pond Environmental Pollution index is obtained, and calculate the ambient stable rate of uranium tailings pond in different time points, the fuzzy conception of uranium tailings pond environmental stability is defined with accurate mathematical linguistics, the combination for realizing to the qualitative analysis of uranium tailings pond environmental stability and quantitatively calculating, for retired uranium tailings pond safety management and Analysis of Policy Making provide theoretical foundation.
Description
Technical field
The invention belongs to the energy and technical field of information processing, are related to a kind of retired uranium tailings pond based on uncertain theory
Environmental stability analysis and prediction method.
Background technique
Demand with China to the energy will generate a large amount of Uranium tailings and barren rock, for storing Uranium tailings and barren rock
Uranium tailings pond is very prominent to the potential safety problem of environment and the public, and (uranium tailings pond, which refers to build a dam, intercepts the mouth of a valley or exclosure composition
, to store up the industrial site of uranium ore barren rock, tailings).Although its surrounding enviroment quality and ecological shape after Remediation
Condition has obtained apparent improvement, but the phase due to its radionuclide and other chemical toxic elements after hole is administered and closed in covering
When still spreading, migrating through a variety of ways in long-time, the accidents such as dam break, landslide happen occasionally, and seriously threaten public's life
Property safety；On the other hand due to land resource scarcity, it need to be restored to the level of the ecological environment before adopting smelting as early as possible, it is ensured that retired uranium
Therefore the sustainable development of mining and metallurgy facility region accelerates the safety and stability process of uranium tailings pond to become Uranium facility
The important subject of Remediation.
Either from the perspective of preserving the ecological environment or ensureing public's security of the lives and property, to retired uranium tailings pond
Stabilisation process carries out research and analysis and all has a very important significance.However, the analysis to uranium tailings pond stability at present
Only only considered the mechanical stability of tailing dam, only using the mechanical stability index of dam body as retired uranium tailings pond safety with
No evaluation index can no longer meet the needs of retired uranium tailings pond ecological environmental protection and sustainable development.It is asked for above-mentioned
The Environmental Status of topic and uranium tailings pond, this research propose a kind of retired uranium tailings pond environmental stability based on uncertain theory
Analysis and prediction method is further enriched and improves retired uranium tailings pond Comprehensive Assessment Technology, to the Remediation of uranium tailings pond
There are positive meaning and influence with environmental effect.Wherein, uncertain theory be from measure theory viewpoint, have it is normative,
Self-duality, monotonicity, subadditivity and product measure axiom mathematic system.The prior art is with the following method:
1. the analysis of uranium tailings pond environmental stability.
Each index Asymptotic Stability section is obtained using expectation in probability theory and the theory of variance, with cutting in probability statistics
Stable region than avenging husband's inequality, when finding out the probability of stability for influencing each environmental index more than or equal to α.
It defines 1: setting stochastic variable X as the observed value of some index, the value of X is x1,x2,L,xn, Yk(k=1,2, Λ,
It n) is some index in time [t1,t2] in continuous k observed value composition sequence of random variables, if YkMathematic expectaion EYkWith
Variance DYkAll exist, and to arbitrary α ∈ [0,1], there are ε > 0, so that inequality
P(|Yk-EYk|<ε)>=α establishment,
Then claim the index in [t1,t2] on (α, ε) stablize, claim [EYk-ε,EYk+ ε] it is the index in time [t1,t2] in it is right
Answering probability is the stable region of α.In conjunction with Chebyshev inequality and index viStable definition, it can be deduced that the pass between α, ε
System isI.e.
In order to which the environmental stability to uranium tailings pond carries out quantitative analysis, definition and the calculating side of ambient stable rate are given
Method.
It defines 2: setting xiFor the observed value of each index at a time, wiFor the weight of each environmental index,For each index
The indicative function of stable region,For index AiThe lower limit value of stable region,For index AiThe upper limit value of stable region, ring
Border coefficient of stabilization ρ is the extent of stability of a certain moment tailing lab environment, and
Wherein, indicative function is represented by
It defines 3: setting time [t1,tk] in certain environmental index sequence of random variables YkCorresponding stable regionIf sectionSo that
It sets up,
Then claim section [a*,b*] be the index stability elastic section.
2. the prediction of uranium tailings pond environmental stability
The ambient stable process of retired uranium tailings pond is predicted, be exactly to the stabilisation trend of each environmental index into
Row prediction obtains the stable region of each index by construction stochastic variable and sequence of random variables, and structure forecast function calculates new
Stable region make comparisons with original stable region, predict that environmental index by stable state is converted into unstable state and by not
Time needed for stable state is converted into stable state.Only considered directly by the anticipation function that stable state is converted into unstable state
Line growth form, exponential increase type and mechanical periodicity type, if new stable region is contained in original stable region, the index is still
In stable state, if new stable region breaches original stable region, which has been converted into unstable state；By
The anticipation function that unstable state is converted into stable state only considers exponential damping type, if original stable region be contained in it is new
Stable region, then the index is still in unstable state, if new stable region enters original stable region, the index
Have been converted into stable state.The relational expression point that time s needed for index breaks through or enters stable region in the case of two kinds need to meet
Not are as follows:
Or
Wherein: EYiThe mathematic expectaion of i month monitor values before expression environmental index, k indicate k-th of environmental index monitoring
Month, while being also the start time of environmental stability prediction, indicate the elastic range of index stable region, it is corresponding
SectionThe referred to as stable elastic section of index.
It is existing to only account for certain environmental factors mostly for research relevant in terms of uranium tailings pond environment, not yet from one
Big angle, which is set out, to be carried out comprehensively and the analysis of system, and there is also suitable for the analysis and research to uranium tailings pond environmental stability
Big blank out, current some evaluation methods and theory can not also solve this technical problem.
Application of the uncertain theory in Tailings Dam field is also only confined to tailing dam body slope stability, faces uranium tail
The increasingly serious environmental problem in mine library and influence factor complicated and changeable, it is clear that this can no longer meet uranium tailings pond Remediation
Ecological, environmental protective and sustainable development demand, how its stable state effectively to be analyzed and be predicted to be also current research
Bottleneck.
Summary of the invention
The retired uranium tailings pond environmental stability analysis that the object of the present invention is to provide a kind of based on uncertain theory and pre-
Survey method, solves problems of the prior art, realizes to the qualitative analysis of uranium tailings pond environmental stability and quantitative scoring
The combination of calculation is converted into unstable state by stable state to uranium tailings pond environmental index and is converted by unstable state
It is predicted the time required to for stable state.
The technical scheme adopted by the invention is that a kind of retired uranium tailings pond environmental stability based on uncertain theory point
Analysis and prediction technique, which is characterized in that follow the steps below:
Step 1: environmental stability is analyzed；
1) foundation of uranium tailings pond environmental stability index system；
2) calculating of each index stable region；
3) analysis of each monolith ambient stable rate of uranium tailings pond；
Step 2: environmental stability is predicted；
1) it is predicted the time required to being converted into unstable state by stable state；
2) it is predicted the time required to being converted into stable state by unstable state.
It is of the invention to be further characterized in that, further, in the step 1, uranium tailings pond environmental stability index system
It establishes, the weight of each environmental index is sought using analytic hierarchy process (AHP), is specifically followed the steps below:
Step 1: Judgement Matricies；
Element value in judgment matrix is the quantitative indices of each element relative importance judgement, the judgment matrix C of construction
=(Cij)n×nAs shown in table a；
Table a
| Criterion Bk | C1 | C2 | Λ | Cn |
| C1 | C11 | C12 | Λ | C1n |
| C2 | C21 | C22 | Λ | C2n |
| Μ | Μ | Μ | Λ | Μ |
| Cn | Cn1 | Cn2 | Λ | Cnn |
Judgment matrix C has the property that (1) Cij>0；(2)Cij=1/Cji(i≠j)；(3)Cii=1 (i, j=1,2,
Λ,n)；The numerical value of each element is judged to each factor relative importance in judgment matrix, then will according to ratio scale
Judge quantification and obtain, using 1~9 method of scales, judgment matrix scale and its meaning are shown in Table b；
Table b
| Serial number | Importance rate | CijAssignment |
| 1 | Two element of i, j is of equal importance | 1 |
| 2 | I element ratio j element is slightly important | 3 |
| 3 | I element ratio j element is obviously important | 5 |
| 4 | I element ratio j element is strongly important | 7 |
| 5 | I element ratio j element is extremely important | 9 |
| 6 | I element ratio j element is slightly inessential | 1/3 |
| 7 | I element ratio j element is obviously inessential | 1/5 |
| 8 | I element ratio j element is strongly inessential | 1/7 |
| 9 | I element ratio j element is extremely inessential | 1/9 |
MiFor the product of each row element, if aijFor in judgment matrix the i-th row jth arrange element value, then
Wherein, i=1,2 ... n；
Step 2: calculating MiN times root
Step 3: to vectorNormalized, normalization formula are
wiFor the weight of each index, then w=[w1,w2,Λ,wn]TAs required feature vector；
Step 4: calculating the Maximum characteristic root λ of judgment matrixmax(if Cw)iIndicate i-th of element of vector Cw, then
Further, to judgment matrix progress consistency check, steps are as follows:
Step 1: calculating consistency check index CI；
If λmaxJudgment matrix maximum eigenvalue, then
Step 2: corresponding Aver-age Random Consistency Index RI being searched according to table 1, wherein n indicates the order of judgment matrix；
Table 1
| n | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 |
| RI | 0 | 0 | 0.58 | 0.90 | 1.12 | 1.24 | 1.32 | 1.41 | 1.45 | 1.49 | 1.51 |
Step 3: calculating random consistency ratio CR, calculation formula is
As CR < 0.10, that is, thinks that judgment matrix has satisfied consistency, otherwise just need to adjust the member of judgment matrix
Plain value, with satisfied consistency.
Further, in the step 1, the calculating of each index stable region is followed the steps below:
Algorithm 1.1: the algorithm of stable region；
Step 1: input X=[x1,x2,Λ,xk], stochastic variable X is the monitor value of certain index, xk>=0, xkIndicate certain index
The monitor value in k-th of month, α=0.95；
Step 2: calculating EYkAnd DYk, wherein
Wherein: EYkFor environmental index sequence of random variables YkMathematic expectaion, DYkFor environmental index sequence of random variables Yk
Variance, k indicate environmental index monitoring k-th of month, while be also environmental stability prediction start time；
Step 3: calculating εk, εkIt is the intermediate variable of parameter stable region, has reacted different monitoring moment stable regions
Deviate the degree of sequence of random variables desired value, wherein
Step 4: calculating ak, bk；ak, bkThe lower limit of stable region corresponding to k month index and upper before respectively indicating
It limits, wherein ak=EYk-εk, bk=EYk+εk；
Step 5: output [ak,bk]；It calculates
Then calculated result [a, b] is required preceding k month stable region.
Further, the analysis of each monolith ambient stable rate of uranium tailings pond is carried out using following steps:
The algorithm that the environmental monitoring data in each monolith multiple months is substituted into stable region, obtains the stable region of each index
Between, in conjunction with the calculation formula of ambient stable rate, obtain each monolith ambient stable rate ρ versus time curve；
Wherein, the definition of ambient stable rate and calculation formula are as follows:
If xiFor the observed value of each index at a time, wiFor the weight of each environmental index,For each index stable region
Between indicative function,For index AiThe lower limit value of stable region,For index AiThe upper limit value of stable region, ambient stable
Rate ρ is the extent of stability of a certain moment tailing lab environment, and
Wherein, indicative function is represented by
Further, the step 2, by stable state be converted into the time required to unstable state prediction specifically according to
Lower step carries out:
Assuming that tkThe initial value a of moment index0For the mean value of stable region, i.e. a0=EYk, predict that monitor value is pressed respectively
Straight line variation, time needed for breaking through stable region when index variation and mechanical periodicity；
Unstable state is converted by stable state, new stable region breaks through what original stable elastic section need to meet
Relational expression are as follows:
Wherein: yi indicates the monitor value in the index each month, and as 1≤i≤k, yi is equal to the monitor value in preceding k month,
As i > k, yiThree kinds of Growth Functions are respectively corresponded, and
The elastic section of 1.2 parameter of algorithm for design, 1.3 parameter of algorithm are converted into unstable shape by stable state
Time needed for state；
Algorithm 1.2: the algorithm in index elasticity section；
Step 1-1: input εk, a, b, l；Wherein, a, b respectively indicate the lower limit value and upper limit value of index stable region, and l is
The coefficient of elasticity in elastic section；
Step 1-2: a is calculated*, b*,Wherein i=1,2, Λ, k；a*, b*Point
Not Biao Shi index elasticity section lower limit value and upper limit value；
Step 1-3: output [a*,b*]；
Wherein [a*,b*] it is elastic section corresponding to preceding k month certain index stable region；
Algorithm 1.3: the algorithm the time required to stable state to unstable state；
Step 2-1: input X=[x1,x2,Λ,xk] and a month stable region [a of preceding kk,bk]；K month before X is indicated
The set that certain Monitoring Indexes value is constituted；
Step 2-2: x (n+1)=f (t is calculatedn+1), x=f (t) is the concentration variation function of construction；Update X=[x1,x2,
Λ,xk,xk+1]；
Step 2-3: corresponding stable region [a is calculated using algorithm 1.1k+1,bk+1], ifIt then calculates end and to export kth+1 beginning unstable；Conversely, then exporting kth
+ 1 month stabilization, and k=k+1 is updated, step 2-2 cycle calculations are returned to, until exporting crank-up time；
The step 2, by unstable state be converted into prediction the time required to stable state it is specific according to the following steps into
Row:
Assuming that the initial value a of certain index0For the maximum value y of Historical Monitoring datamax, prediction index monitors on this basis
Time needed for entering stable region when value is by exponential damping；
Stable state is converted by unstable state, new stable region, which reenters original stable elastic section, to expire
The relational expression of foot are as follows:
Wherein, yiIndicate the observation in the index each month；As 1≤i≤k, yiMonitor value equal to preceding k months；Work as i >
When k, yi=EYk+(a0-EYk)·e-mi, wherein m >=0；I=0,1,2 ... s；E indicates natural logrithm；a0Indicate the first of certain index
Beginning monitor value；M is the damped expoential of anticipation function.
The invention has the advantages that the environmental stability that uncertain theory applies to uranium tailings pond is analyzed and predicted,
On the one hand the quantitative analysis to uranium tailings pond environmental stability is realized, the environmental stability for having obtained each moment Tailings Dam is dynamic
State changing rule overcomes the defect of traditional evaluation analysis method, analyzes the stable calculation of uranium tailings pond more reasonable；It is another
Aspect, by indetermination theory the environmental stability of uranium tailings pond is predicted, and fully considered from stable state
A variety of situations of change to unstable state and from unstable state to stable state, and program and obtained environmental index not
With the time needed for breaking through stable state in situation and coming back to stable state, to realize to uranium tailings pond ambient stable
The prediction of property, stability that is more scientific and accurately analyzing Tailings Dam.
Detailed description of the invention
Fig. 1 is uranium tailings pond environmental stability index system figure.
Fig. 2 is leap dam ambient stable rate changing rule figure.
Fig. 3 is the dam Nan Po ambient stable rate changing rule figure.
Fig. 4 is pine forest dam ambient stable rate changing rule figure.
Fig. 5 is western eyebrow dam ambient stable rate changing rule figure.
Fig. 6 is time diagram needed for straight line growth form breaks through stable region.
Fig. 7 is time diagram needed for index growth form breaks through stable region.
Fig. 8 is time diagram needed for mechanical periodicity type breaks through stable region.
Fig. 9 is time diagram needed for index attenuation type enters stable region.
Specific embodiment
The following describes the present invention in detail with reference to the accompanying drawings and specific embodiments.
A kind of retired uranium tailings pond environmental stability analysis and prediction method based on uncertain theory, including ambient stable
Property analysis with environmental stability predict.
Step 1, environmental stability analysis.
1) foundation of uranium tailings pond environmental stability index system；
The environmental contaminants of uranium tailings pond mainly pass through the flowing of water and the diffusive migration of atmosphere, influence periphery pool,
Stream Systems of The Xiang Jiang River and soil and atmosphere have obtained the main indicator for influencing environment according to principal component analysis and correlation technique, and have tied
The actual conditions for closing Uranium tailings, have chosen 12 in terms of Tailings Dam infiltration, Tailings Dam atmospheric environment, radioactive pollution three
Environmental impact indicators, as shown in Figure 1, the Remediation atmospheric environment index and radioactive pollution index by early period have reached
National limit standard simultaneously substantially tends towards stability, thus the index of uranium tailings pond infiltration be influence environmental stability it is main because
Element.
Since retired uranium tailings pond stabilizes, evaluation data are limited, can not be each using the method analysis of objective mathematical statistics
The regularity of distribution of a factor index weight, can only determine the weight of each index according to artificial subjective judgement, and step analysis
Method positive (AHP) overcomes well these deficiencies, various shortage data can be suitble to support, the situation of index system complexity, and have
The advantages of qualitative and quantitative analysis combines can judge result and expressed by way of quantity and carry out science artificial
Processing analysis can comprehensively reflect problem, therefore determine to carry out weight assignment using analytic hierarchy process (AHP).
The weight of each environmental index is sought using analytic hierarchy process (AHP), the specific steps of which are as follows:
Step 1: Judgement Matricies.(the definition of judgment matrix: the relative importance of each factor of level each in system
Judging result showed with numerical value, being write as matrix form is exactly judgment matrix).Element value in judgment matrix is each element
The quantitative indices of relative importance judgement, the judgment matrix C=(C of constructionij)n×nAs shown in table a.
Table a judgment matrix general type
| Criterion Bk | C1 | C2 | Λ | Cn |
| C1 | C11 | C12 | Λ | C1n |
| C2 | C21 | C22 | Λ | C2n |
| Μ | Μ | Μ | Λ | Μ |
| Cn | Cn1 | Cn2 | Λ | Cnn |
Judgment matrix C has the property that (1) Cij>0；(2)Cij=1/Cji(i≠j)；(3)Cii=1 (i, j=1,2,
Λ,n)。
The numerical value of each element is to be judged by expert group to each factor relative importance in judgment matrix, then root
Quantification will be judged according to certain ratio scale and is obtained.Generally use 1~9 method of scales, judgment matrix scale and its meaning
It is shown in Table b.
Table b judgment matrix scale and its meaning
| Serial number | Importance rate | CijAssignment |
| 1 | Two element of i, j is of equal importance | 1 |
| 2 | I element ratio j element is slightly important | 3 |
| 3 | I element ratio j element is obviously important | 5 |
| 4 | I element ratio j element is strongly important | 7 |
| 5 | I element ratio j element is extremely important | 9 |
| 6 | I element ratio j element is slightly inessential | 1/3 |
| 7 | I element ratio j element is obviously inessential | 1/5 |
| 8 | I element ratio j element is strongly inessential | 1/7 |
| 9 | I element ratio j element is extremely inessential | 1/9 |
The product M of each row elementiIf aijFor in judgment matrix the i-th row jth arrange element value, then
Wherein, i=1,2 ... n；
Step 2: calculating MiN times root
Step 3: to vectorNormalized, normalization formula are
wiFor the weight of each index, then w=[w1,w2,Λ,wn]TAs required feature vector；
Step 4: calculating the Maximum characteristic root λ of judgment matrixmax(if Cw)iIndicate i-th of element of vector Cw, then
Consistency check: the reasonability in order to guarantee conclusion needs to carry out consistency check to judgment matrix.To judging square
Battle array carries out consistency check, and steps are as follows:
Step 1: calculating consistency check index CI；
If λmaxJudgment matrix maximum eigenvalue, then
Step 2: being put down accordingly according to table 1 (note: table 1 is existing public technology, and all RI are unified) lookup
Equal random index RI, wherein n indicates the order of judgment matrix.
1 Aver-age Random Consistency Index of table
| n | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 |
| RI | 0 | 0 | 0.58 | 0.90 | 1.12 | 1.24 | 1.32 | 1.41 | 1.45 | 1.49 | 1.51 |
Step 3: calculating random consistency ratio CR, calculation formula is
As CR < 0.10, that is, thinks that judgment matrix has satisfied consistency, otherwise just need to adjust the member of judgment matrix
Plain value (needing to rethink model or reconfigure the biggish pairwise comparison matrix of those consistency ratios CR), is allowed to have
There is satisfied consistency.
Two are carried out through environmental index of expert group's (being made of the scientific research personnel and staff in the field) to uranium tailings pond
Two compare, and ultimately constructed judgment matrix A is as follows:
Carry out consistency check according to above step: CR=0.0044 < 0.1 is met the requirements.
Finally obtain the weight vectors of each index: w=(0.2352 0.3162 0.1568 0.0784 0.0958
0.1176)。
2) calculating of each index stable region；
According to the definition of stable region and algorithm 1.1, the fetching target probability of stability is 0.95, i.e. α=0.95, then can calculate
The stable region for dam, Nan Poba, pine forest dam and each index of Xi Meiba of leaping, is shown in Table 2.
Algorithm 1.1: the algorithm of stable region
Step 1: input X=[x1,x2,Λ,xk], (note: stochastic variable X is the monitor value of certain index, with above) xk≥0
(xkIndicate the monitor value in k-th of month of certain index), α=0.95；
Step 2: calculating EYkAnd DYk, wherein
Wherein: EYkFor environmental index sequence of random variables YkMathematic expectaion, DYkFor environmental index sequence of random variables Yk
Variance, k indicate environmental index monitoring k-th of month, while be also environmental stability prediction start time；
Step 3: calculating εk(εkIt is the intermediate variable of parameter stable region, has reacted different monitoring moment stable regions
Deviate the degree of sequence of random variables desired value), wherein
Step 4: calculating ak, bk(ak, bkThe lower limit of stable region corresponding to k month index and upper before respectively indicating
Limit), wherein ak=EYk-εk, bk=EYk+εk；
Step 5: output [ak,bk]；It calculates
Then calculated result [a, b] is required preceding k month stable region.
The stable region of each monolith main environment index of table 2
3) analysis of each monolith ambient stable rate of uranium tailings pond；
2010-2012 leap dam, the dam Nan Po, pine forest dam, the western 36 months environmental monitoring datas in eyebrow dam are substituted into algorithm
1.1 obtain the stable region of each index, and it is steady that each monolith environment can be obtained in conjunction with the calculation formula for defining environment coefficient of stabilization in 2
Determine rate ρ versus time curve, calculated result is as Figure 2-Figure 5.
Leap dam total environment steadiness was preferable as shown in Figure 2, in addition to 12nd month, the 30th month and 33rd month
In addition, the ambient stable rate in remaining month is 1, thus illustrates the main environment Monitoring Indexes value in leap dam most of month all
In stable state, environmental stability is preferable.
The dam Nan Po total environment steadiness is poor as shown in Figure 3, and 36 middle of the month only have 13 months ambient stable rates etc.
In 1, remaining in month ambient stable rate be respectively less than 1, and the fluctuation of coefficient of stabilization curve is larger, thus illustrates the dam Nan Po most of month
Main environment Monitoring Indexes value all has exceeded stable state, and environmental stability is poor.
Pine forest dam total environment steadiness is preferable as shown in Figure 4, and 36 middle of the month have 29 months ambient stable rates to be equal to
1, the ambient stable rate in remaining month less than 1, coefficient of stabilization curve in certain months there are fluctuation within a narrow range, but overall situation compared with
It is good, thus illustrate that pine forest dam environment lies substantially in stable state.
Western eyebrow dam total environment steadiness is very poor as shown in Figure 5, and 36 middle of the month only have 6 months ambient stable rates and are equal to
1, remaining in month ambient stable rate be respectively less than 1, the coefficient of stabilization in certain months is even less than 0.5, and the width of coefficient of stabilization curve fluctuation
Degree and range are all very big, illustrate that leap dam environment is in extremely unstable state.
Step 2: environmental stability is predicted；
1) it is predicted the time required to being converted into unstable state by stable state；
The monitor value accumulation tribute that unstable state is primarily due to uranium tailings pond following a period of time is become from stable state
It offers and breaks through original stable region, it is assumed that tkThe initial value a of moment index0For the mean value of stable region, i.e. a0=EYk, herein
On the basis of predict that monitor value is changed by straight line respectively, the time needed for breaking through stable region when index variation and mechanical periodicity.It is real
Straight line growth form corresponds to stable emissions in border, and exponential increase is corresponding to accelerate discharge, and mechanical periodicity type corresponds to regular discharge etc.,
Growth Function yiRespectively as shown in figs 6-8.
Unstable state is converted by stable state, new stable region breaks through what original stable elastic section need to meet
Relational expression are as follows:
Wherein: yiThe monitor value for indicating the index each month, as 1≤i≤k, yiEqual to the monitor value in preceding k month, when
When i > k, yiThree kinds of Growth Functions are respectively corresponded, andK=36 in this test case.
According to calculating and analytic process, devise the elastic section of 1.2 parameter of algorithm, 1.3 parameter of algorithm by
Time needed for stable state is converted into unstable state.
The algorithm in 1.2 index elasticity section of algorithm；
Step 1: input εk, a, b, l；(a, b respectively indicate the lower limit value and upper limit value of index stable region, and l is elastic region
Between coefficient of elasticity)
Step 2: calculating a*, b*,Wherein i=1,2, Λ, k；(a*, b*Point
Not Biao Shi index elasticity section lower limit value and upper limit value)
Step 3: output [a*,b*]。
Wherein [a*,b*] it is elastic section corresponding to preceding k month certain index stable region.
Algorithm the time required to 1.3 stable state to unstable state of algorithm；
Step 1: input X=[x1,x2,Λ,xk] and a month stable region [a of preceding kk,bk]；
(X is consistent with the X meaning in algorithm 1.1 herein, the set that k month Monitoring Indexes value is constituted before indicating)
Step 2: calculating x (n+1)=f (tn+1), x=f (t) is the concentration variation function of construction；Update X=[x1,x2,Λ,
xk,xk+1]；
Step 3: calculating corresponding stable region [a using algorithm 1.1k+1,bk+1], ifIt then calculates end and to export kth+1 beginning unstable；Conversely, then exporting kth
+ 1 month stabilization, and k=k+1 is updated, second step cycle calculations are returned to, until exporting crank-up time.
Now by taking 2010-2012 leap dam F ion as an example, detailed data was listed by table 3, according to 36 months in table 3
Monitoring data predict the time needed for becoming unstable state from stable state when F ion monitor value is changed by Fig. 6-8, then initially
Moment tk=t36, calculate [t1,t36] the stable region root of F ion in the time
The range of F ion l is determined according to the condition defined in 3, because after stable region determines, it is known that preceding 36 months average areas are close
Section [a36,b36], make so choosing lOrUtilize algorithm
1.2 calculate elastic section [a corresponding to stable region*,b*]。
3 2010-2012 leap dam F ion monitoring data of table
Sequence of random variables Y is calculated by 36 monitoring data of F ion in table 336Mathematic expectaion EY36With variance DY36, with
And a0Initial value be respectively as follows:
EY36=1.6295, DY36=1.0759, a0=1.6295.
Assuming that the new stable region of F ion breaches the stable region of original 36 months monitor values just after s months, then have
Wherein, yiThe observation for indicating F ion each month, as 1≤i≤36, yiEqual to preceding 36 months monitor values, work as i
When > 36, yiIt can be acquired by Growth Function, and
According to the monitoring data in algorithm 1.3 and table 3, C is utilized++Language is programmed, using dam of leaping as example, to three kinds
In the case of F ion unstable state is become from stable state required for the time predicted that detailed results are shown in Table shown in 4-6,
The time needed for breaking through stable region when leap other indexs of dam are increased by straight line similarly can be predicted, just do not list one by one herein.
Table 4, which is leaped, breaks through the time prediction of stable region when dam F ion is increased by straight line
| M value | Predicted time (moon) | M value | Predicted time (moon) |
| ≤0.01 | 157 | 0.13~0.14 | 12 |
| 0.02 | 75 | 0.14~0.15 | 11 |
| 0.03 | 47 | 0.16~0.17 | 10 |
| 0.04 | 37 | 0.18~0.20 | 9 |
| 0.05 | 29 | 0.21~0.23 | 8 |
| 0.06 | 25 | 0.24~0.28 | 7 |
| 0.07 | 21 | 0.29~0.35 | 6 |
| 0.08 | 19 | 0.36~0.47 | 5 |
| 0.09 | 17 | 0.48~0.67 | 4 |
| 0.10 | 15 | 0.68~1.09 | 3 |
| 0.11 | 14 | 1.10~2.43 | 2 |
| 0.12 | 13 | ≥2.44 | 1 |
The time prediction of stable region is broken through when the leap of table 5 dam F ion is exponentially-increased
Table 6, which is leaped, breaks through the time prediction of stable region when dam F ion presses mechanical periodicity
| M value | Predicted time (moon) | M value | Predicted time (moon) |
| 0.01 | 17 | 0.88~1.30 | 8 |
| 0.02 | 15 | 1.31~1.43 | 7 |
| 0.03~0.04 | 14 | =1.44 | 6 |
| 0.05~0.06 | 13 | 1.45~1.50 | 5 |
| 0.07~0.11 | 12 | 1.51~1.74 | 4 |
| 0.12~0.21 | 11 | 1.75~2.44 | 3 |
| 0.22~0.44 | 10 | 2.45~4.87 | 2 |
| 0.45~0.87 | 9 | =4.88 | 1 |
2) it is predicted the time required to being converted into stable state by unstable state；
From unstable state become stable state need monitor value constantly accumulate reduction just can enter original stable region,
Assuming that the initial value a of certain index0For the maximum value y of Historical Monitoring datamax, prediction index monitor value presses index on this basis
Time needed for entering stable region when decaying, exponential damping type corresponds to self-purification and manual intervention etc. in practice, decaying
Function yiAs shown in Figure 9.
Stable state is converted by unstable state, new stable region, which reenters original stable elastic section, to expire
The relational expression of foot are as follows:
Wherein, yiIndicate the observation in the index each month.As 1≤i≤k, yiMonitor value equal to preceding k months；Work as i >
When k, yi=EYk+(a0-EYk)·e-mi, wherein m >=0；I=0,1,2 ... s；(e indicates natural logrithm, is approximately equal to 2.72；a0Table
Show the initial monitor value of certain index；M is the damped expoential of anticipation function), k=36, the y in instance analysis in testi=EYk+
(ymax-EYk)·e-mi, andWherein, 1≤i≤k.ymaxFor the maximum value of certain metric history monitoring data.
By taking the dam 2010-2012 Nian Ximei F ion as an example, index was pressed according to 36 months in table 7 monitoring data prediction F ions
Time needed for becoming stable state from unstable state when decaying, then initial time tk=t36, calculate [t1,t36] F in the time
The stable region of ionAccording to the range for defining determining l, line-like
Growth form has calculated the elastic section [a of F ion stability using algorithm 1.2*,b*]。
7 dam 2010-2012 Nian Ximei F ion monitoring data of table
Sequence of random variables Y is calculated by 36 monitoring data of F ion in table 736Mathematic expectaion EY36With variance DY36,
And a0Initial value be respectively
EY36=3.64, DY36=16.89, a0=25.25.
Assuming that the new stable region of F ion enters the stable region of 36 months original monitor values just after s months, according to
Previous analysis is available such as lower inequality
Wherein, yiIndicate the observation in F ion each month.As 1≤i≤36, yiEqual to the monitor value in preceding 36 month,
As i > 36, yi=3.64+21.61e-mi, and
According to the primary monitoring data in algorithm 1.3 and table 7, C is utilized++Language is programmed, to the west of for eyebrow dam, to F
Time required for ion becomes stable state from unstable state is predicted that detailed results are shown in Table 8, and western eyebrow similarly can be predicted
It time needed for entering stable region when other indexs of dam are by exponential damping, does not just list one by one herein.
Enter the time prediction of stable region when 8 western eyebrow dam F ion of table is by exponential damping
| M value | Predicted time (moon) | M value | Predicted time (moon) |
| 0.15 | 149 | =0.80 | 47 |
| 0.20 | 117 | =0.85 | 46 |
| 0.25 | 98 | =0.90 | 45 |
| 0.30 | 85 | =0.95 | 44 |
| 0.35 | 76 | =1.00 | 43 |
| 0.40 | 70 | 1.05~1.10 | 42 |
| 0.45 | 64 | =1.15 | 41 |
| 0.50 | 60 | 1.20~1.30 | 40 |
| 0.55 | 57 | 1.35~1.45 | 39 |
| 0.60 | 54 | 1.50~1.65 | 38 |
| 0.65 | 52 | 1.70~1.95 | 37 |
| 0.70 | 50 | 2.00~2.75 | 36 |
| 0.75 | 48 | =2.80 | 35 |
Key point of the invention is uncertain theory to the quantitative analysis of retired uranium tailings pond environmental stability and retired
The stable prediction with the unstable state time of uranium tailings pond environmental index.Ambient stable process prediction to retired uranium tailings pond
Mainly have that environmental index by stable state is converted into unstable state and unstable state is converted into two kinds of predictions of stable state
Theoretical method can predict time and the index under unstable state that the index under stable state enters unstable state
Into the time of stable state, theoretical foundation is provided for Tailings Dam environmental improvement.
The present invention has obtained the stable region of uranium tailings pond Environmental Pollution index using correlation techniques such as probability analyses
Between, and the ambient stable rate of uranium tailings pond in different time points is calculated, uranium tailings pond ring is defined with accurate mathematical linguistics
The fuzzy conception of border stability, the combination for realizing to the qualitative analysis of uranium tailings pond environmental stability and quantitatively calculating.
It is predicted the time required to being converted into unstable state by stable state to uranium tailings pond environmental index, and considers environment and refer to
Time needed for breaking through stable region when marking monitor value by straight line growth, exponential increase and mechanical periodicity；Meanwhile also to Uranium tailings
Lab environment index is predicted the time required to being converted into stable state by unstable state, and considers environmental index monitor value
Time needed for entering stable region when changing by exponential damping, for retired uranium tailings pond safety management and Analysis of Policy Making provide
Theoretical foundation.
Claims (4)
1. a kind of retired uranium tailings pond environmental stability analysis and prediction method based on uncertain theory, which is characterized in that press
It is carried out according to following steps:
Step 1: environmental stability is analyzed；
1) foundation of uranium tailings pond environmental stability index system；
2) calculating of each index stable region；
Each index refers to: U, PH, Ra, F-、NH4- N index；
Described U, PH, Ra, F-、NH4- N is followed successively by uranium element, the pH value for indicating pH value, radium element, fluorine ion, ammonia nitrogen；
3) analysis of each monolith ambient stable rate of uranium tailings pond；
Step 2: environmental stability is predicted；
1) it is predicted the time required to being converted into unstable state by stable state；
2) it is predicted the time required to being converted into stable state by unstable state；
In the step 1, the calculating of each index stable region is followed the steps below:
Algorithm 1.1: the algorithm of stable region；
Step 1: input X=[x1,x2,…,xk], stochastic variable X is the monitor value of certain index in each index, xk>=0, xkIndicate each
The monitor value in k-th of month of certain index, α=0.95 in index；
Step 2: calculating EYkAnd DYk, wherein
Wherein: EYkFor environmental index sequence of random variables YkMathematic expectaion, DYkFor environmental index sequence of random variables YkSide
Difference, k indicate k-th of month of environmental index monitoring, while being also the start time of environmental stability prediction；
Step 3: calculating εk, εkIt is the intermediate variable of parameter stable region, has reacted different monitoring moment stable regions and deviateed
The degree of sequence of random variables desired value, wherein
Step 4: calculating ak, bk；ak, bkThe lower and upper limit of stable region corresponding to k-th of month index are respectively indicated, wherein
ak=EYk-εk, bk=EYk+εk；
Step 5: output [ak,bk]；The intersection for calculating stable region corresponding to preceding k month index is [a, b]；
Then calculated result [a, b] is required preceding k month stable region.
2. a kind of retired uranium tailings pond environmental stability analysis and prediction based on uncertain theory according to claim 1
Method, which is characterized in that in the step 1, the foundation of uranium tailings pond environmental stability index system utilizes analytic hierarchy process (AHP)
The weight for seeking each environmental index, specifically follows the steps below:
Step 1: Judgement Matricies；
Element value in judgment matrix is the quantitative indices of each element relative importance judgement, the judgment matrix C=of construction
(Cij)n×n；
Then
Judgment matrix C has the property that (1) Cij> 0；(2) as i ≠ j, Cij=1/Cji；(3)Cii=1；Wherein i, j=1,
2,…,n；
The numerical value of each element is judged to each factor relative importance in judgment matrix, then will be sentenced according to ratio scale
Conclude quantization and obtain, using 1~9 method of scales, judgment matrix scale and its meaning are as follows:
When two element of i, j is of equal importance, C is takenij=1；When i element ratio j element is slightly important, C is takenij=3；I element ratio j element is obvious
When important, C is takenij=5；When i element ratio j element is strongly important, C is takenij=7；When i element ratio j element is extremely important, C is takenij=
9；When i element ratio j element is slightly inessential, C is takenij=1/3；When i element ratio j element is obviously inessential, C is takenij=1/5；I element
When strongly more inessential than j element, C is takenij=1/7；When i element ratio j element is extremely inessential, C is takenij=1/9；
MiFor the product of each row element, if aijFor in judgment matrix the i-th row jth arrange element value, then
Wherein, i=1,2 ... n；
Step 2: calculating MiN times root
Step 3: to vectorNormalized, normalization formula are
wiFor the weight of each index, then w=[w1,w2,…,wn]TAs required feature vector；
Step 4: calculating the Maximum characteristic root λ of judgment matrixmax(if Cw)iIndicate i-th of element of vector Cw, then
3. a kind of retired uranium tailings pond environmental stability analysis and prediction based on uncertain theory according to claim 2
Method, which is characterized in that carrying out consistency check to judgment matrix, steps are as follows:
Step 1: calculating consistency check index CI；
If λmaxJudgment matrix maximum eigenvalue, then
Step 2: the value of corresponding Aver-age Random Consistency Index RI is searched according to the value of n, wherein n indicates the rank of judgment matrix
The corresponding relationship of number, n and RI are as follows:
When n is respectively 1,2,3,4,5,6,7,8,9,10,11, the value of RI is corresponding in turn to as 0,0,0.58,0.90,1.12,
1.24、1.32、1.41、1.45、1.49、1.51
Step 3: calculating random consistency ratio CR, calculation formula is
As CR < 0.10, that is, think that judgment matrix has satisfied consistency, the element for otherwise just needing to adjust judgment matrix takes
Value, with satisfied consistency.
4. a kind of retired uranium tailings pond environmental stability analysis and prediction based on uncertain theory according to claim 1
Method, which is characterized in that the analysis of each monolith ambient stable rate of uranium tailings pond is carried out using following steps:
The algorithm that the environmental monitoring data in each monolith multiple months is substituted into stable region, obtains the stable region of each index, then
The calculation formula of combining environmental coefficient of stabilization obtains each monolith ambient stable rate ρ versus time curve；
Wherein, the definition of ambient stable rate and calculation formula are as follows:
If xiFor the observed value of each index at a time, wiFor the weight of each environmental index,For each index stable region
Indicative function,For index AiThe lower limit value of stable region,For index AiThe upper limit value of stable region, ambient stable rate ρ are
The extent of stability of a certain moment tailing lab environment, and
Wherein, indicative function is represented by
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