CN104866899A - Leakage detection method based on hydraulic model calibration of urban water supply network - Google Patents

Abstract

The invention discloses a leakage detection method based on hydraulic model calibration of an urban water supply network. The method comprises the following steps: A) establishing a pressure-related leakage positioning model; B) determining a leakage detection target function; C) determining a constraint condition; and D) solving the pressure-related leakage positioning model. Urban water supply pipeline leakage is avoided, problems in a traditional leakage detection method are solved, the pressure-related leakage detection model is established on the basis of model calibration by a Cuckoo optimization algorithm, and the leakage detection method is quick and effective. In addition, a new pressure-related leakage detection method can detect leakage which is difficult to detect by a traditional method. A situation that a leakage area is detected before the engineers go to a scene is very useful for engineers, and the engineers can carry out intensive examination in a predicted area and can quickly detect an accurate position of a leakage hot water spot.

Description

A kind of dropout detection method of checking based on public supply mains hydraulic model

Technical field

The invention belongs to dropout detection technical field, be specifically related to a kind of dropout detection method of checking based on public supply mains hydraulic model.

Background technology

Leakage is the ubiquitous serious problems of water supply industry.In recent ten years, although need reorganization and expansion and newly-built many water supply networks according to urban development, change a large amount of aging pipelines, still had numerous pipeline that should be retired in operation, make China's city water-supply pipe network leak rate general higher.Not only cause huge economic loss, the life of returning people brings ill effect, and concrete manifestation form is as follows:

(1) income is reduced.Although water is cheap resource, water leakage remains very high to cost water supply cause.Along with the growth of the time limit, the deterioration gradually of water supply network running status.Therefore, the economic loss brought due to water leakage is increasing, and reducing water leakage is most field likely in water resource improvement field.

(2) energy dissipation is caused.Treated structures treated water generally enters the distribution system of water supply after water pump lifting, be finally assigned to every family, and the water yield of missing in water supply network also provides by water pump, the electric power energy of this process need at substantial.

(3) reliability of water delivery is reduced.The growth of pipe leak have impact on continuity and the security of water supply, not only reduces the use water pressure of user, even may interrupt supplying water; The water supply network of corrosion too increases the chance of secondary pollution, and water supply quality is declined.

In sum, in the distribution system of water supply in worldwide, solve leakage still Challenge.The mankind are faced with more and more serious water resource shortage problem, and meanwhile, the sustainability of change to water resource of environment also creates threat.Reduce the wastage in the distribution system of water supply, not only can bring society and environmental benefit, simultaneously also can significantly saving water resource and economic investment, the service level of water supply cause can also be improved, promote the development of national economy and urban construction.How to reduce the leakage problem of water in water distribution system, water undertaking is faced with the increasing pressure, and therefore, reducing water leakage is a needs urgent problem.

Both at home and abroad to present Research and the analysis of dropout detection: the decades in past, dropout detection has become the focus of great research.Various technology, comprises power model analysis against the current, Bayesian system identification method, traffic statistics analysis and the expert system based on primitive rule.Wherein power model analysis is most active research direction against the current.

Sage once proposed a kind of dropout detection method being called Posi-Tect.It is redistributing based on the leakage water yield, achieves successfully in the dropout detection of some district managements (DMA).Total leakage water yield of a DMA is that the difference of the inflow water yield and water requirement by calculating this block region obtains.Wastage between each DMA is prorated on node according to the number of nodal community or the length of main pipe that is connected with each node.The leakage of local is considered to be missed by background and happen suddenly, and leakage forms.The background leakage of each node and pipeline section is calculated by experimental formula, and experimental formula is the function in pipe age based on interior condition coefficient (ICF).ICF is the numerical value between 0 ~ 1.Pipe is larger for age, and ICF value is larger, and therefore, background leakage is larger.The difference of total leakage and background leakage is considered to burst leakage.But Posi-Tect method has a lot of limiting factors, as described below.

1) the method can not distinguish the difference of a large circulation zone and group of mean people's circulation zone.

2) dropout detection simulation process is separated from Model Checking process, but in theory, dropout detection should be included in Model Checking.

3) wastage not representative pressure determine the water yield.

4) the method is not a part with the modeling software bag of good support and maintenance

Liggett and Chen first proposed the inverse Transient Technique of dropout detection and check in 1994, the method is the subsequent iteration a position based on transient wave or pulse.More research afterwards starts to carry out in this field.The pressure transducer of corresponding position setting height(from bottom) sensitivity in distribution system of water supply system, transient propagation pressure signal, the transient pressure detected is used to determine the parameter of model, comprises wastage and the pipeline coefficient of roughness.1999, Brunone confirmed that in a survey report Long-distance Pipeline for Water Conveyance is against the reliability of transient analysis and validity.2000, genetic algorithm was used in the inverse transient model of the piping system of a hypothesis by the people such as Vitkovsky, is calculated the change of water requirement (wastage) by the minimum value of the difference between stress seeking transient simulation value and measured value.Within 2003, Ferrante and Brunone is deduced the frequency spectrum analytical expression of pipe downstream terminal pressure head in transient process, and detects with wavelet transformation the local singular value that exists pressure time sequence in the independent pipeline system of leakage.The people such as Nixon in 2006 conscientiously have studied the scope of inverse transient model validity, find that its applicability to be only confined in the configuration-system of simple reservoir-pipe network-valve types or reservoir-pipe network-water reservoir system in instantaneous small amplitude fluctuation situation.But, generally speaking, inverse transient model is detected local leakage and successful application still Challenge as a general method.This is mainly because the distribution system of water supply normally height Cheng Huan, and containing a lot of valve, pond and water pump, wherein any one will cause transient phenomena deep fades, except decay, the method is difficult to distinguish the transient wave response caused because of leakage and responds with pipe fitting and those transient waves caused because of the change of water requirement.Therefore accurately against the correct initial flow condition that transient analysis needs steady-state model to provide, this model must be checked the leakage of distribution system of water supply system.In other words, the result of the transient analysis utilizing inaccurate starting condition to obtain is insecure, and, in steady-state model, do not consider wastage.In a word, the pressure surge of any degree, comprise transient affairs of those premeditated designs and the pressure surge that causes is worthless, because these fluctuations trigger new leakage possibly and expand leakage mouth on leakage pipeline section, this makes dropout detection become a very difficult job.

In the past few decades, many optimization methods based on Model Checking are developed rapidly.2007, Wu Zhengyi proposed the pressure-driven node flow detected water supply network circulation zone and optimizes (PDD) model, uses genetic algorithm to solve, and this solution is flexibly with effective.But the solving speed of genetic algorithm is very slow, and the method can not be used for the water system of bulky complex.

Summary of the invention

The object of the invention is to solve public supply mains pipe leak and Problems existing in leak hunting method in the past thereof, providing a kind of cuckoo optimized algorithm build-up pressure on the basis of Model Checking that utilizes to be correlated with the dropout detection method of checking based on public supply mains hydraulic model of dropout detection model.

In order to achieve the above object, the present invention by the following technical solutions: a kind of based on public supply mains hydraulic model check dropout detection method, the method comprises the following steps:

A, build-up pressure relevant leakage location model: public supply mains hydraulic model node water requirement is made up of two parts, be respectively user's water requirement and wastage, in order to determine leakage node or circulation zone, need to set up Optimized model to optimize the jet coefficient of node, by the jet coefficient K optimized _ithe one judged as possibility circulation zone characterizes, as the jet coefficient K of certain node optimization _iwhen being greater than zero, think that this node exists the pipeline of missing or being connected with this node and may there is leakage;

B, determine dropout detection objective function: quality or the adaptability objective function of dropout detection solving result are assessed, objective function is defined as the difference between the analogue value of model node pressure and pipeline flow and field observation value, consider the dimension equivalence of node pressure and pipeline flow, carried out suitable nondimensionalization process, then convert node pressure and pipeline flow to nondimensional fitness value by self-defining two conversion factors and calculate optimum, objective function is defined as follows:

$F\left(\stackrel{\→}{X}\right)=\underset{t=1}{\overset{T}{\mathrm{\Σ}}}(\underset{i=1}{\overset{N}{\mathrm{\Σ}}}{\left(\frac{{\mathrm{Hs}}_i\left(t\right)-{\mathrm{Ho}}_i\left(t\right)}{H_x}\right)}^2+\underset{j=1}{\overset{M}{\mathrm{\Σ}}}{\left(\frac{{\mathrm{Qs}}_j\left(t\right)-{\mathrm{Qo}}_j\left(t\right)}{Q_x}\right)}^2)$

In above formula,

Ho _ithe observed reading of (t)---node i node pressure when time step t;

Hs _ithe analogue value of (t)---node i model node pressure when time step t;

Qo _j(t)---the observed reading of pipeline section j flow when time step t;

Qs _j(t)---the analogue value of pipeline section j flow when time step t;

H _x---node pressure conversion factor;

Q _x---pipeline flow conversion factor;

N---the number of node pressure observed reading;

M---the number of Flow Observation value;

C, determine constraint condition: when the too much water yield is assigned on a node, the pressure of node may occur negative value, the node that therefore must ensure to exist in optimizing process negative pressure is not entered during follow-on optimization calculates by selecting,

Decision variable: $\stackrel{\→}{X}=(K_1,K_2,...,K_n);$

Objective function:

Constraint condition: 1≤i≤n

P _i＞0，1≤i≤n

Continuity equation

Energy equation

In above formula, K _i---the jet coefficient at node i place;

N---pipe network interstitial content;

---the jet coefficient that node i place is maximum;

P _i---the pressure at node i place;

Solving of D, pressure correlation leakage location model: use cuckoo optimized algorithm to solve model.

Further, step D comprises following calculation procedure:

A, determine optimized algorithm parameter, intake pipeline model data: given every cuckoo lays eggs quantity bound, population size, maximum iteration time, number of clusters, maximum cuckoo quantity, algorithm end condition; Intake pipeline model data: pipe range, ground elevation, node rated flow, caliber, known node hydraulic pressure, total supply and other pipeline model data;

B, calculate the original pressure of each node: pipeline model compensating computation, draws the original pressure of each node;

C, cuckoo Population Initialization: utilize random function to generate arbitrarily an initial population;

D, determine lay eggs quantity and the radius of laying eggs of every cuckoo, reject the cuckoo ovum identified by host, egg hatching is also grown into ripe cuckoo and is namely produced colony K _i;

E, calculate the wastage K of each node _ih _i ⁿ;

F, by Q _i+ K _ih _i ⁿgive corresponding each node respectively;

G, model compensating computation;

H, computing environment fitness value, judge whether population number is less than or equal to environmental adaptation angle value, if so, then continue next calculation procedure; If not, meet population number after rejecting the little cuckoo of fitness when being less than or equal to environmental adaptation angle value, then continue next calculation procedure;

I, cuckoo population cluster;

J, cuckoo migration;

K, judge whether to meet termination of iterations condition: find optimum individual in this generation, if current optimal-adaptive angle value is less than specified accuracy, then calculate end, display result of calculation; If not, circulation step d, until meet termination of iterations condition.

Hinge structure of the present invention has beneficial effect: the invention solves public supply mains pipe leak and Problems existing in leak hunting method in the past thereof, utilizing cuckoo optimized algorithm build-up pressure on the basis of Model Checking to be correlated with dropout detection model, is one dropout detection method fast and effectively.In addition, new pressure correlation dropout detection method can also detect and be difficult to by traditional way the leakage that detects.Before going to scene, detect that circulation zone is very useful to slip-stick artist, the inspection that they can concentrate in the region of prediction, the accurate location of missing focus can be determined rapidly.

Accompanying drawing explanation

Fig. 1 is the process flow diagram of cuckoo optimized algorithm;

Fig. 2 is the 3D figure of 3 dimension Rastrigin functions;

Fig. 3 is fitness value change comparison diagram in three kinds of Algorithm for Solving Rastrigin functions (10 dimension) process;

Fig. 4 is that cuckoo optimized algorithm of the present invention solves pressure correlation leakage location model computing block diagram;

Fig. 5 is the distribution system of water supply schematic diagram of the embodiment of the present invention 1;

Fig. 6 is the true leakage loss node of the embodiment of the present invention 1 and the comparison diagram optimizing the leakage loss node calculated.

Embodiment

Below in conjunction with the drawings and specific embodiments, the invention will be further described.

Cuckoo optimized algorithm used in the present invention is the inspiration receiving cuckoo population life style.The mode that what cuckoo population was special lay eggs and cultivate offspring constitutes the basic thought of cuckoo optimized algorithm.In this algorithm there are two kinds of forms in cuckoo population: grow up cuckoo and cuckoo ovum.Grow up cuckoo by under ovum in the nest of other birds, if these ovum are not found by host or kill, these ovum will grow into adult cuckoo.The migration of living environment and cuckoo population will make them assemble and find most suitable environment to breed, cultivates offspring, and the environment of this optimum existence is exactly the global maximum of objective function.Cuckoo optimized algorithm process flow diagram as shown in Figure 1.

In order to ensure the survival rate that cuckoo ovum is maximum, cuckoo need find optimal region and lay eggs, by the time egg hatching after growing into ripe cuckoo, just define the colony of some, each colony have belong to them perch scope.Habitat best in all colonies will be the target of other migrations, and they will move toward this habitat, and perch in the scope near this habitat.Consider the number that every cuckoo lays eggs and the distance between cuckoo habitat and best habitat, define cuckoo and to lay eggs radius.Then, lay eggs in host's nest that cuckoo is random in its radius of laying eggs, by the time fitness value reaches maximum and all colonies when all focusing on this value neighbouring, and this process stops.

In order to better embody the advantage of cuckoo optimized algorithm, three kinds of optimized algorithms are tested as reference function with the Rastrigin function of 10 dimensions.This function has many minimal points, therefore seeks the very difficult of global minimum change, is also even like this when 3 dimension.The 3D figure (-5.12<x, y<5.12) of 3 dimension Rastrigin functions as shown in Figure 2.As can be seen from Figure 2, a challenging problem really of Rastrigin functional minimum value problem, apply cuckoo optimized algorithm, genetic algorithm and particle cluster algorithm respectively to solve this problem, initial population size and maximum iteration time are set to 20 and 100 respectively.In three kinds of Algorithm for Solving Rastrigin function (10 dimension) processes, fitness value change comparison diagram as shown in Figure 3.When can significantly find out that genetic algorithm and particle cluster algorithm proceed to maximum iteration time from Fig. 3, do not search global minimum, and cuckoo optimized algorithm just converges to global minimum when the 43rd iteration.In this functional minimum value solves, cuckoo optimized algorithm shows powerful advantage, can do one estimate more accurately the minimum value of reality.

As shown in Figure 4, the present invention is based on the dropout detection method that public supply mains hydraulic model is checked, the method comprises the following steps:

A, build-up pressure relevant leakage location model: public supply mains hydraulic model node water requirement is made up of two parts, be respectively user's water requirement and wastage, in order to determine leakage node or circulation zone, need to set up Optimized model to optimize the jet coefficient of node, by the jet coefficient K optimized _ithe one judged as possibility circulation zone characterizes, as the jet coefficient K of certain node optimization _iwhen being greater than zero, think that this node exists the pipeline of missing or being connected with this node and may there is leakage;

B, determine dropout detection objective function: quality or the adaptability objective function of dropout detection solving result are assessed, objective function is defined as the difference between the analogue value of model node pressure and pipeline flow and field observation value, consider the dimension equivalence of node pressure and pipeline flow, carried out suitable nondimensionalization process, then convert node pressure and pipeline flow to nondimensional fitness value by self-defining two conversion factors and calculate optimum, objective function is defined as follows:

$F\left(\stackrel{\&RightArrow;}{X}\right)=\underset{t=1}{\overset{T}{\mathrm{\&Sigma;}}}(\underset{i=1}{\overset{N}{\mathrm{\&Sigma;}}}{\left(\frac{{\mathrm{Hs}}_i\left(t\right)-{\mathrm{Ho}}_i\left(t\right)}{H_x}\right)}^2+\underset{j=1}{\overset{M}{\mathrm{\&Sigma;}}}{\left(\frac{{\mathrm{Qs}}_j\left(t\right)-{\mathrm{Qo}}_j\left(t\right)}{Q_x}\right)}^2)$

In above formula,

Ho _ithe observed reading of (t)---node i node pressure when time step t;

Hs _ithe analogue value of (t)---node i model node pressure when time step t;

Qo _j(t)---the observed reading of pipeline section j flow when time step t;

Qs _j(t)---the analogue value of pipeline section j flow when time step t;

H _x---node pressure conversion factor;

Q _x---pipeline flow conversion factor;

N---the number of node pressure observed reading;

M---the number of Flow Observation value;

C, determine constraint condition: when the too much water yield is assigned on a node, the pressure of node may occur negative value, the node that therefore must ensure to exist in optimizing process negative pressure is not entered during follow-on optimization calculates by selecting,

Decision variable: $\stackrel{\&RightArrow;}{X}=(K_1,K_2,...,K_n);$

Objective function:

Constraint condition: 1≤i≤n

P _i＞0，1≤i≤n

Continuity equation

Energy equation

In above formula, K _i---the jet coefficient at node i place;

N---pipe network interstitial content;

---the jet coefficient that node i place is maximum;

P _i---the pressure at node i place;

Solving of D, pressure correlation leakage location model: use cuckoo optimized algorithm to solve model, concrete calculation procedure is as follows:

A, determine optimized algorithm parameter, intake pipeline model data: given every cuckoo lays eggs quantity bound, population size, maximum iteration time, number of clusters, maximum cuckoo quantity, algorithm end condition; Intake pipeline model data: pipe range, ground elevation, node rated flow, caliber, known node hydraulic pressure, total supply and other pipeline model data;

B, calculate the original pressure of each node: pipeline model compensating computation, draws the original pressure of each node;

C, cuckoo Population Initialization: utilize random function to generate arbitrarily an initial population;

D, determine lay eggs quantity and the radius of laying eggs of every cuckoo, reject the cuckoo ovum identified by host, egg hatching is also grown into ripe cuckoo and is namely produced colony K _i;

E, calculate the wastage K of each node _ih _i ⁿ;

F, by Q _i+ K _ih _i ⁿgive corresponding each node respectively;

G, model compensating computation;

H, computing environment fitness value, judge whether population number is less than or equal to environmental adaptation angle value, if so, then continue next calculation procedure; If not, meet population number after rejecting the little cuckoo of fitness when being less than or equal to environmental adaptation angle value, then continue next calculation procedure;

I, cuckoo population cluster;

J, cuckoo migration;

K, judge whether to meet termination of iterations condition: find optimum individual in this generation, if current optimal-adaptive angle value is less than specified accuracy, then calculate end, display result of calculation; If not, circulation step d, until meet termination of iterations condition.

Embodiment 1

Use a simple pipe network to illustrate, seek the process of distribution system of water supply leakage points with cuckoo optimized algorithm, the distribution system of water supply used as shown in Figure 5.

Assuming that circulation zone is concentrated and used pressure correlation injection flow to replace, suppose that node J-11, J-28 and J-32 place exists leakage, jet coefficient is 0.8L/s/m ^0.5, ejection fraction is 0.5.Assuming that the C value of the Hai Sen of all pipeline sections-William's formula is 130, the analogue value (as shown in table 1) of node J-1, J-13, J-19, J-35 and J-9 place's pressure and pipeline section P-40 and P-20 place flow is taken as site observation date and is used for detection node J-11, leakage points that J-28 and J-32 tri-is known.

Table 1 model monitoring point data observed reading

Element	Attribute	Value
			J-1	Pressure (m)	40.09
J-13	Pressure (m)	38.56
			J-19	Pressure (m)	37.80
J-35	Pressure (m)	37.74
			J-9	Pressure (m)	36.98
P-40	Flow (L/S)	42.66
			P-20	Flow (L/S)	-50.14

Cuckoo optimized algorithm setting correlation parameter: Population Size is 30, every minimum laying of cuckoo is 2, maximum laying is 5, and maximum iteration time is 50, and cuckoo population clusters number is 2, solving precision is 1e-10, the cuckoo maximum number that environment allows is 60, and radius controling parameters of laying eggs is 1, fitness tolerance 0.001, the jet coefficient of node, within the scope of 0-1, represents in this point and there is leakage loss phenomenon; If jet coefficient is zero, so there is not leakage loss phenomenon in this point.Table 2 is for obtaining the jet coefficient K value situation of leakage loss point and correspondence after optimization calculating.

The optimization result of calculation of the jet coefficient K value of table 2 node

Node	Jet coefficient optimal value	Node	Jet coefficient optimal value
				J-1	0	J-20	0
J-2	0	J-21	0
				J-3	0	J-22	0
J-4	0	J-23	0
				J-5	0	J-24	0
J-6	0	J-25	0
				J-7	0.31	J-26	0
J-8	0.16	J-27	0.34
				J-9	0	J-28	0.137
J-10	0	J-29	0
				J-11	0	J-30	0
J-12	0.14	J-31	0.21
				J-13	0	J-32	0.43
J-14	0	J-33	0
				J-15	0	J-34	0
J-16	0	J-35	0
				J-17	0	J-36	0
J-18	0	J-37	0
				J-19	0	J-38	0

As can be seen from Table 2, may there is leakage in node J-7, J-8, J-21, J-27, J-28, J-31, J-32 place.The comparison diagram of the leakage loss node that real leakage loss node calculates with optimization as shown in Figure 6.

As can be seen from Figure 6, result of calculation and actual leak position have very large correlativity.The method of this pressure correlation dropout detection is more efficient compared with the method reported before.In addition, new pressure correlation dropout detection method can also detect and be difficult to by traditional way the leakage that detects.Before going to scene, detect that circulation zone is very useful to slip-stick artist, the inspection that they can concentrate in the region of prediction, the accurate location of missing focus can be determined rapidly.

Claims (2)

1., based on the dropout detection method that public supply mains hydraulic model is checked, it is characterized in that the method comprises the following steps:

A, build-up pressure relevant leakage location model: public supply mains hydraulic model node water requirement is made up of two parts, be respectively user's water requirement and wastage, in order to determine leakage node or circulation zone, need to set up Optimized model to optimize the jet coefficient of node, by the jet coefficient K optimized _ithe one judged as possibility circulation zone characterizes, as the jet coefficient K of certain node optimization _iwhen being greater than zero, think that this node exists the pipeline of missing or being connected with this node and may there is leakage;

B, determine dropout detection objective function: quality or the adaptability objective function of dropout detection solving result are assessed, objective function is defined as the difference between the analogue value of model node pressure and pipeline flow and field observation value, consider the dimension equivalence of node pressure and pipeline flow, carried out suitable nondimensionalization process, then convert node pressure and pipeline flow to nondimensional fitness value by self-defining two conversion factors and calculate optimum, objective function is defined as follows:

$F\left(\stackrel{\&RightArrow;}{X}\right)=\underset{t=1}{\overset{T}{\mathrm{\&Sigma;}}}(\underset{i=1}{\overset{N}{\mathrm{\&Sigma;}}}{\left(\frac{{\mathrm{Hs}}_i\left(t\right)-{\mathrm{Ho}}_i\left(t\right)}{H_x}\right)}^2+\underset{j=1}{\overset{M}{\mathrm{\&Sigma;}}}{\left(\frac{{\mathrm{Qs}}_j\left(t\right)-{\mathrm{Qo}}_j\left(t\right)}{Q_x}\right)}^2)$

In above formula,

Ho _ithe observed reading of (t)---node i node pressure when time step t;

Hs _ithe analogue value of (t)---node i node pressure when time step t;

Qo _j(t)---the observed reading of pipeline section j flow when time step t;

Qs _j(t)---the analogue value of pipeline section j flow when time step t;

H _x---node pressure conversion factor;

Q _x---pipeline flow conversion factor;

N---the number of node pressure observed reading;

---the number of Flow Observation value;

C, determine constraint condition: when the too much water yield is assigned on a node, the pressure of node may occur negative value, the node that therefore must ensure to exist in optimizing process negative pressure is not entered during follow-on optimization calculates by selecting,

Decision variable: $\stackrel{\&RightArrow;}{X}=(K_1,K_2,...,K_n);$

Objective function:

Constraint condition: 1≤i≤n

P _i＞0，1≤i≤n

Continuity equation

Energy equation

In above formula, K _i---the jet coefficient at node i place;

N---pipe network interstitial content;

---the jet coefficient that node i place is maximum;

P _i---the pressure at node i place;

Solving of D, pressure correlation leakage location model: use cuckoo optimized algorithm to solve model.

2., based on the dropout detection method that public supply mains hydraulic model is checked, it is characterized in that step D comprises following calculation procedure:

A, determine optimized algorithm parameter, intake pipeline model data: given every cuckoo lays eggs quantity bound, population size, maximum iteration time, number of clusters, maximum cuckoo quantity, algorithm end condition; Intake pipeline model data: pipe range, ground elevation, node rated flow, caliber, known node hydraulic pressure, total supply and other pipeline model data;

B, calculate the original pressure of each node: pipeline model compensating computation, draws the original pressure of each node;

C, cuckoo Population Initialization: utilize random function to generate arbitrarily an initial population;

D, determine lay eggs quantity and the radius of laying eggs of every cuckoo, reject the cuckoo ovum identified by host, egg hatching is also grown into ripe cuckoo and is namely produced colony K _i;

E, calculate the wastage K of each node _ih _i ⁿ;

F, by Q _i+ K _ih _i ⁿgive corresponding each node respectively;

G, model compensating computation;

H, computing environment fitness value, judge whether population number is less than or equal to environmental adaptation angle value, if so, then continue next calculation procedure; If not, meet population number after rejecting the little cuckoo of fitness when being less than or equal to environmental adaptation angle value, then continue next calculation procedure;

I, cuckoo population cluster;

J, cuckoo migration;

K, judge whether to meet termination of iterations condition: find optimum individual in this generation, if current optimal-adaptive angle value is less than specified accuracy, then calculate end, display result of calculation; If not, circulation step d, until meet termination of iterations condition.