CN109190259A - Based on the digital microcurrent-controlled failure of chip restorative procedure for improving dijkstra's algorithm and IPSO combination - Google Patents
Based on the digital microcurrent-controlled failure of chip restorative procedure for improving dijkstra's algorithm and IPSO combination Download PDFInfo
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Abstract
Based on the digital microcurrent-controlled failure of chip restorative procedure for improving dijkstra's algorithm and IPSO combination, it is related to digital microcurrent-controlled failure of chip and repairs field, in order to solve the problems, such as use duration, the low efficiency of existing digital microcurrent-controlled failure of chip restorative procedure.This method comprises: Step 1: based on the shortest path improved between dijkstra's algorithm two drops to be mixed of calculating；Improving dijkstra's algorithm is to introduce cost function in existing dijkstra's algorithm, cost function guide existing dijkstra's algorithm to it is most short to starting point distance, to terminal apart from most short and scanned for the longest direction of fault point distance；Step 2: calculating movement routine based on IPSO, realizes that drop moving distance is most short under conditions of guaranteeing that mixing is completed, complete fault restoration.The present invention is suitable for repairing the failure of digital microcurrent-controlled chip.
Description
Technical field
The present invention relates to digital microcurrent-controlled failure of chip to repair field.
Background technique
With the development of science and technology, field of automatic testing is expanded to from the test to analog circuit or digital circuit to microcomputer
The test of electric system MEMS (Micro-Electromechanical Systems).Micro-fluidic chip is also referred to as on piece laboratory
(Lab-on-a-chip), can be completed on one piece several square centimeters of chip biology laboratory and conventional chemical examine it is each
Kind function.Has the characteristics that miniaturization, high sensitive, low cost, integrated.First generation microflow controlled biochip has permanent carve
Micro-valve, Micropump and the fluid channel of erosion are all based on continuous fluid as concrete operations and flow.Micro-fluidic technologies and manufacturing process
Development pushed the generation of digital microcurrent-controlled chip, digital microcurrent-controlled chip manipulates discrete liquid on two-dimentional micro-fluidic array
Drop has the system architecture that can substantially extend.
Digital microcurrent-controlled chip is emphasized to disperse liquid to turn to micro drop and is operated compared with continuous fluid controls,
Each drop is individually controlled, and energy consumption is very low, especially suitable for needing high-performance and operating more complex biochemical analysis.With biography
The Biochemical Analyzer of system mode is compared, and digital microcurrent-controlled chip is with reusable, size is small, high degree of automation, integrates
Spend high advantage.It has the ability accurate driving micro liquid (down to microlitre even other liquid of nanoliter level), stream is completed on chip
The operation such as transport, storage, separation and mixing of body completes overdelicate biochemistry detection with low cost, can significantly reduce survey
It tries time and lab space and increases the stability and accuracy of result due to reducing manual operation process.Therefore facing
Bed diagnosis, biologic medical, health examination, pharmacodiagnosis, the detection of air quality etc. all have wide practical use, and have
Important meaning.
At this stage, the application of digital microcurrent-controlled chip is concentrated mainly on biology, field of medicaments, and various body fluid can be in number
It is analyzed in word micro-fluidic chip, can also realize more complicated biochemical test, extraction, duplication and amplification including DNA,
Cell analysis and immunoassays etc..And with the continuous extension of micro-fluidic chip application field, we are faced in the same core
On piece realizes more processes, the great demand more reacted.But since minute yardstick processing technology has fragile link, with green wood
Material continually introduces, and this kind of chip is all made to be easier to face failure risk.Incipient fault risk leads to the uncertainty in chip service life,
Further develop to limit its, and the raising of the stability of DMFB and reliability can significantly expanding digital micro-fluidic chip
Application field.Therefore, in order to guarantee the validity of chip, chip after fault detection, fault diagnosis will to failure into
Row is repaired, and guarantees going on smoothly for experiment, and design error failure restorative procedure is to guarantee chip steady operation, extend chip service life
Indispensable important means.
The fault repairing method of digital microcurrent-controlled chip is redesigned to faulty chip, is ensured in failure core
On piece can complete biochemical test.However, use duration, the low efficiency of existing fault repairing method.
Summary of the invention
The purpose of the present invention is to solve use duration, the low efficiencys of existing digital microcurrent-controlled failure of chip restorative procedure
The problem of, to provide based on the digital microcurrent-controlled failure of chip restorative procedure for improving dijkstra's algorithm and IPSO combination.
The digital microcurrent-controlled failure of chip reparation side of the present invention combined based on improvement dijkstra's algorithm and IPSO
Method, this method comprises:
Step 1: based on improve dijkstra's algorithm calculate two drops to be mixed between shortest path, make two to
It mixes drop and same position is moved to according to the shortest path；
Improving dijkstra's algorithm is that cost function is introduced in existing dijkstra's algorithm, and cost function guidance is existing
Dijkstra's algorithm is to most short to starting point distance, most short and scan for the longest direction of fault point distance to terminal distance；
Step 2: calculating movement routine based on IPSO, realize that drop moving distance is most under conditions of guaranteeing that mixing is completed
It is short, fault restoration is completed, the movement routine is to complete needed for mixing from the same position of step 1 to two drops to be mixed
Path.
Preferably, cost function fcost(Dk,i) are as follows:
Wherein, dis (Dk,i,Dk,i,start) it is distance of the current point to starting point, dis (Dk,i,Dk,i,end) it is current point to eventually
The distance of point, min [dis (Dk,i,Ef)] it is current point to nearest the distance between fault point, α, β and γ are weight system
Number.
Preferably, step 1 includes:
Step 1 one, setting set S, set S are shortest path sequence, and the initial value in set S only includes rising for drop
Point position, i.e. S={ pos1}；
Step 1 two generates set S', and S' includes that the drop in S at newest element is meeting constraint condition at present for the moment
Carve the position pos that can move intot+1, S' contains up to five elements, it is assumed that the electrode unit position that drop is currently located is Ei
(mi+1,ni), post+1Are as follows: post+1=Ei(mi+1,ni), post+1=Ei(mi+2,ni), post+1=Ei(mi,ni), post+1=
Ei(mi+1,ni- 1), post+1=Ei(mi+1,ni+ 1), miFor columns, niFor line number；
Step 1 three, the cost function for calculating each element in S',
Step 1 four selects the smallest position of cost function as pos from S'2, update shortest path access order S, S
={ pos1,pos2}；
Step 1 two is repeated to step 1 four, until liquid drop movement to terminal, obtains S={ pos1,pos2,pos3……}。
Preferably, step 2 specifically:
Step 2 one, setting IPSO parameter, including maximum number of iterations Gen, acceleration constant c1、c2And c3, with speed phase
The random number r of pass1、r2And r3；
Step 2 two, the directional velocity for calculating i-th of particle t moment
mk、mu、md、mlAnd mrRespectively correspond holding, upward, downward, directional velocity to the left and to the right, Ui tTable
Show that drop corresponding to i-th of particle of t moment can be with the set of moving direction when meeting constraint condition；
Step 2 three, the directional velocity for updating i-th of particle t moment
xgb tFor the position of the particle of t moment global optimum, xlb tFor the position of the particle of t moment local optimum, r7For with
The random number that machine generates；
Step 2 four, update i-th of particle the t+1 moment position vector Xi t+1:
It repeats step 2 two and is transferred to step 2 five until mixability reaches 100% to step 2 four；
Step 2 five, determine local optimum particle position vector Xlb T
Xlb T=(xlb 1,xlb 2,...,xlb T)
T is the experiment deadline；
Step 2 six, determine global optimum particle position vector Xgb T；
Xgb T=(xgb 1,xgb 2,...,xgb T)；
Step 2 two is repeated to step 2 six, until the number of iterations reaches Gen times, output meets the global optimum of condition
The position vector of particle, obtains movement routine.
Preferably, constraint condition includes failure constraint condition, static constraint condition and dynamic constrained condition；
Failure constraint condition is that fault electrode unit is not used within the experiment deadline；
Static constraint condition is that two drops cannot be in direct neighbor or diagonally adjacent electrode unit position；
Dynamic constrained condition is when one electrode unit of distance between two drops, and two drops can not be simultaneously where it
Straight line does movement in the same direction.
Preferably, the mathematical model of failure constraint condition are as follows:
Wherein, Ea f(ma,na) it is fault electrode unit, EfFor the set of fault electrode unit, TrealWhen being completed for experiment
Between,
BatFor binary variable, the case where indicating that electrode unit is used in each timeslice, if in the t time, a-th
Electrode unit Ea(ma,na) used, then BatIt is 1, otherwise BatIt is 0；maFor columns, n where a-th of electrode unitaIt is a-th
Line number where electrode unit.
Preferably, in t time, kthaAnd kjThe position of a drop is respectivelyWithIt is static
The mathematical model of constraint condition are as follows:
maAnd mjRespectively a-th and j-th of electrode unit place columns, naAnd njRespectively a-th and j-th of electrode
Line number where unit, DtFor the set of droplet position.
Preferably, in the t time, the position of two drops is respectivelyWithTwo drops
It is respectively by the movement done in the t timeWithElectrode unit where two drops is respectively Ea(ma,na) and Ej(mj,nj),
The vector that two electrode unit positions are constituted is expressed as Indicate two vectors it
Between angle, the mathematical model of dynamic constrained condition are as follows:
maAnd mjRespectively a-th and j-th of electrode unit place columns, naAnd njRespectively a-th and j-th of electrode
Line number where unit.
Preferably, before step 1 further include: the mathematical model for establishing digital microcurrent-controlled chip, according between operation
Sequencing determine the operation sequence diagram of digital microcurrent-controlled chip；
One is executed the step to after step 2, step 1 is repeated to step 2, until completing all according to the sequence of operation
Operation.
The present invention utilizes the path planning problem and mixing for improving dijkstra's algorithm and IPSO solution fault repairing method
Path design problem introduces cost function in existing dijkstra's algorithm and this method is carried out didactic improvement, all
Preferentially the direction that more likely there are optimal solution is scanned in node, it is expected quickly to search out the shortest distance between two o'clock
And the algorithm is avoided to fall into locally optimal solution.Repair time of the invention is short, and remediation efficiency is high.
Detailed description of the invention
Fig. 1 is that there are structural schematic diagrams when fault electrode unit in chip；
It (a) (b) is to use fault electrode for fault electrode is not used；
Fig. 2 is the schematic diagram of static fluid constraint；
(a) for before two droplet coalescences, (b) for after two droplet coalescences；
Fig. 3 is the schematic diagram of dynamic fluid constraint；
(a) before for the movement of two drops, it is (b) during two drops are mobile, is (c) after two drops are mobile；
Fig. 4 is the block diagram of the fault repairing method based on module；
Fig. 5 is dynamic disorder path planning schematic diagram；
Fig. 6 is the mathematical model of electrod-array；
Fig. 7 is flow chart of the invention.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, those of ordinary skill in the art without creative labor it is obtained it is all its
His embodiment, shall fall within the protection scope of the present invention.
It should be noted that in the absence of conflict, the feature in embodiment and embodiment in the present invention can phase
Mutually combination.
The present invention will be further explained below with reference to the attached drawings and specific examples, but not as the limitation of the invention.
Principle of the present invention is as follows:
1, digital microcurrent-controlled chip liquid drop driving method and fault type
The mode of digital microcurrent-controlled chip drives microfluid is dielectric wetting driving.Electricity is applied to drop by electrod-array
Surface tension change is consolidated to change its surface tension, in the liquid that hydrophobic polymer surface utilizes to drive drop in field.In order to make liquid
Drop movement, driving voltage is added on adjacent electrode unit, using dielectric electro-wetting principle, so that accumulating electricity on the surface of drop
Amount, to generate the surface tension gradient of covering adjacent electrode in droplet surface, when the tension be greater than upper and lower surface and drop it
Between resistance when, the mobile driving of drop can be completed, this is to control the mobile most basic method of drop.By corresponding
Apply contact potential series on electrod-array, it will be able to it realizes and realizes basic operation in biochemistry detection on chip, such as: liquid droplet distribution,
Transport, storage, mixing and separation etc..
Digital microcurrent-controlled failure of chip type is divided into two kinds: parametric failure and permanent fault.Parametric failure is main
It generates, is caused by dimensional parameters error in the production process, when electrod-array is not horizontal, not parallel between two layers of surface or electrode
When in uneven thickness, the driving of digital drop will be affected, and influence of such failure to experimental result shows as generating larger
Deviation is severely impacted the performance of chip.
Permanent fault is caused by the circuit break and short circuit between chip electrode unit, these failures, which are probably derived from, to be made
Cheng Zhong, or as control voltage it is improper caused by caused by electrode degradation.Permanent fault will lead to drop and rest on event
Hinder unit, cannot advance according to design route, be unable to complete experiment and be moved to waste liquid pool, lead to the failure of biochemistry detection, pacify
The application in the complete demanding field of property can generate great adverse effect.The present invention be directed to the online failures of permanent fault to repair
It is multiple.
2. the fault repairing method of digital microcurrent-controlled chip
Fault repairing method be according to biochemical test process meet constraint under conditions of directly to the movement routine of drop
Be designed, in order to realize that fault correction function, drop cannot pass through fault electrode in the process of movement, otherwise will be unable to after
Continue movement and stops at fault electrode.As shown in Figure 1, drop does not pass through fault electrode in Fig. 1 (a), can be accessible press
It is moved according to design path, realizes the operations such as mixing, separation.Drop is moved to fault electrode in Fig. 1 (b), stops at failure
At electrode, it can not be carried out so as to cause subsequent operations.
3. the mathematical model of fault repairing method constraint condition
Digital microcurrent-controlled chip DMFB fault restoration is to be needed in a failure situation according to biochemical test to chip
Design is reconstructed, target be guarantee experiment the deadline it is most short, on chip realize fault restoration by failure constrain and when
Between constrain.The actual experiment deadline is no more than longest finishing time required by biochemical test, maximum experiment deadline
It is expressed as Tupperlimit, operation total number is K, and completing the time that operation l needs is Tl, then deadline T is testedrealIt is expressed as
Formula (1), and meet Tupperlimit≥Treal。
Failure constraint is to guarantee that all fault points are not used, it is ensured that and all operations will not utilize fault electrode,
The case where definition binary variable such as formula (2) indicate that electrode is used in each timeslice, if electrode a is made in the t time
With then BatIt is 1, otherwise BatIt is 0, wherein M is the total columns of electrode, and N is the total line number of electrode, and formula is as follows:
Then electrode Ea(ma,na) number that is used during the experiment isThen fault electrode is when testing completion
Between TrealInside being not used needs to meet:
Objective function is that the experiment deadline is most short after repairing, and is indicated are as follows:
Tmin=min { Treal} (4)
When mobile there are more drops on DMFB, drop walking will follow certain rule, as confines fluid condition.Stream
Body constraint condition is divided into static constraint condition and dynamic constrained condition.When test droplets and experiment drop closer apart, two liquid
Drop is easy to appear mixing phenomena.Therefore static fluid constraint condition need to be taken, needs to maintain a certain distance between two drops, with
There is unexpected fusion in anti-two drops.
When two drops are closer apart, such as shown in Fig. 2 (a), two drops can be fused into the drop in Fig. 2 (b).
For confines fluid founding mathematical models, two drops cannot be in direct neighbor or diagonally adjacent electrode position
It sets, otherwise will lead to drop and unexpected fusion occur.In the t time, kthaAnd kjThe position of a drop is respectivelyWithThe mathematical model of static constraint condition are as follows:
maAnd mjRespectively a-th and j-th of electrode unit place columns, naAnd njRespectively a-th and j-th of electrode
Line number where unit, DtFor the set of droplet position.
Static constraint condition shows the position constraint for needing to meet between the drop on electrod-array, dynamic constrained
Condition illustrates the constraint condition that two drops need to meet during exercise, as shown in figure 3, distance is an electricity between two drops
When pole as shown in Fig. 3 (a), if two drops move to the right simultaneously, needs the shade electrode in Fig. 3 (a) to apply voltage, cause
Right side drop breakup is at two drops, and unexpected mixing occurs for a part therein and left side drop, becomes in Fig. 3 (c)
The case where.
Dynamic constrained condition is when one electrode unit of distance between two drops, and two drops can not be simultaneously where it
Straight line does movement in the same direction.It is respectively in the position of t time, two dropsWithTwo drops are in t
The movement done is respectively by the timeWithElectrode unit where two drops is respectively Ea(ma,na) and Ej(mj,nj), two
The vector that a electrode unit position is constituted is expressed as It indicates between two vectors
Angle, the mathematical model of dynamic constrained condition are as follows:
maAnd mjRespectively a-th and j-th of electrode unit place columns, naAnd njRespectively a-th and j-th of electrode
Line number where unit.
4. the fault repairing method based on module
Path fault repairing method deletes the concept of resource module, allows to operate through any one on array
The operation of biochemical test is completed on electrode sequence.The operation for needing to carry out path design is hybrid manipulation, dilution operation and separation
Operation, in restructural operation, only mixing and the dilution operation for needing to be designed droplet path, dilution operation is by mixing
Operation and lock out operation are constituted, so the present invention needs to carry out hybrid manipulation the design of droplet path, to complete biochemical test.
Such as the fault repairing method flow chart that Fig. 4 is module.
Hybrid manipulation needs to complete two steps, and design path makes two liquid drop movements to be mixed to same position first,
Then the mixing drop is moved according to free routing, to complete hybrid manipulation.In a first step, it needs to find two
Shortest path between drop, fault electrode present on chip and other drops can be considered obstacle, then the problem can be equivalent to
Dynamic disorder path planning problem.The problem is np hard problem, because the obstacle location moment on chip changes, although failure is electric
The position of pole will not change, but the position of other drops can time changing.The present invention is using improvement dijkstra's algorithm (Di Jie
Si Tela algorithm) existing shortest path between two drops is calculated, complete mixed first step.
The movement routine of drop is designed during second step to complete hybrid manipulation, the present invention utilizes improvement particle swarm algorithm
(Improved Particle Swarm Optimization, IPSO) carries out path design, and PSO algorithm belongs to evolution algorithm
One kind, it is found optimal solution from RANDOM SOLUTION, by iteration, the excellent of solution is evaluated using fitness function, rule of evolving
It is then simple, by follow current search to global and local optimal value determine globally optimal solution.PSO algorithm is due to higher
Concurrency, which has the characteristics that realize, to be easy, restrains fast, is suitable for solving extensive path planning problem.
It being combined by improving dijkstra's algorithm and IPSO, the present invention realizes heuristic path fault repairing method,
And using body fluid test experience as confirmatory experiment, by different body fluid carry out the various experimental applications of different detections in based on path and
Based on modular digital microcurrent-controlled chip DMFB fault repairing method.
(1) based on the paths planning method for improving dijkstra's algorithm
Mathematical simulation is carried out to digital micro-fluidic chip obstacle using Grid Method, indicates digital microcurrent-controlled chip with grid
Electrode, the grid tag comprising barrier be obstacle grid, on the contrary it is then be free grid.Using Grid Method to faulty core
Piece founding mathematical models, fault electrode are the obstacle grid in map, by confines fluid condition, are designing mobile road for certain drop
When diameter, electrode and its adjacent electrode are obstacle grid where other drops in addition to wait operate drop.Drop needs are hidden
Obstacle grid completes corresponding operating function.
In numerous path search algorithms, dijkstra's algorithm can calculate the specified origin-to-destination from figure most
Short path.A dijkstra's algorithm is run, it is available from starting point to the interior shortest path by all nodes of figure, but in reality
In the application of border, it would however be of interest to the case where shortest path between certain two specific node rather than starting point are to every other,
The application of dijkstra's algorithm is excessively huge due to search space and is restricted.The present invention is based on existing dijkstra's algorithm into
Row improve, on the basis of existing algorithm introduce the intelligent search factor, cost function is added in route searching, by cost function Lai
Diameter strategy is sought in decision, is preferentially scanned for the direction that more likely there are optimal solution in all nodes.It is expected quickly to find
To the shortest distance between two o'clock and the algorithm is avoided to fall into locally optimal solution.
The existing each point of dijkstra's algorithm can only access once, and the thought based on greedy algorithm, find process every time
In all selection guarantee the shortest node of current path.Introducing cost function carries out this method heuristic in dijkstra's algorithm
Improvement, altogether include two kinds of fault points on map: electrode and its adjacent electrode where fault electrode and other drops.Failure electricity
The position of pole does not change over time, but the position of other drops changes over time, and in adjacent timeslice, drop is most
An electrode can only be moved, it is shortest next that dijkstra's algorithm in current time piece according to current failure mode searches out path
Position may be due to closely falling into locally optimal solution from failure, such as Fig. 5 institute since future time piece abort situation changes excessively
Show, which currently walks to the right, other drops are walked downwards in continuous two timeslices, and the drop is in order to avoid other liquid of entrance
The isolated location of drop causes unexpected mixing, needs to wait or get around other drops in the original location, leads to planning path
Extend.Due to failure dynamic change, each point only accesses primary it is possible that shortest path can not be found.
It when carrying out the next position path computing, needs to consider three parts content altogether: firstly, considering that selection guarantees current road
The shortest point of diameter；Secondly, to terminal apart from shortest point when considering selection fault-free；Finally, selecting the fortune farthest from fault point
Dynamic position.Introduce cost function, so that it may all directions be found into the equal breadth-first search mechanism of probability and be modified to direction
The depth-first search mechanism of property, the influence of many factors is combined during selection, is avoided in dynamic fault situation
Fall into locally optimal solution.
Cost function to estimate the point to terminal cost number.The value of cost function is bigger, and the path is selected to carry out
The path of path planning may be longer, continues that optimal solution may be deviateed along the path that the path scans for, or fall into
Local optimum.The value of cost function is smaller, and continuation scans for being more likely to get shortest path in the direction.Cost function is fixed
Justice are as follows:
Wherein, dis (Dk,i,Dk,i,start) it is distance of the current point to starting point, dis (Dk,i,Dk,i,end) it is current point to eventually
The distance of point, min [dis (Dk,i,Ef)] it is current point to nearest the distance between fault point, α, β and γ are weight system
Number.Closer to starting point, terminal, the cost function value of the point remoter to fault point distance is smaller, easier to be preferential selected.
It is as follows based on the process for improving the shortest path between dijkstra's algorithm two drops to be mixed of calculating:
One, set S is set, set S is shortest path sequence, and the initial value in set S only includes the start position of drop,
That is S={ pos1}；
Two, set S' is generated, S' includes drop in S at the newest element subsequent time possibility when meeting constraint condition
The position pos being moved tot+1, S' contains up to five elements, it is assumed that the electric motor units position that drop is currently located is Ei(mi+1,
ni), post+1Are as follows: post+1=Ei(mi+1,ni), post+1=Ei(mi+2,ni), post+1=Ei(mi,ni), post+1=Ei(mi+
1,ni- 1), post+1=Ei(mi+1,ni+ 1), miFor columns, niFor line number；
Three, the cost function of each element in S' is calculated,
Four, select the smallest position of cost function as pos from S'2, update shortest path access order S, S=
{pos1,pos2}；
One to four is repeated, until liquid drop movement to terminal, obtains S={ pos1,pos2,pos3……}。
Improved dijkstra's algorithm realizes that the difference with existing dijkstra's algorithm is to introduce cost function, preferably
Bootstrap algorithm is to most short to starting point distance, most short and scan for the longest direction in fault distance position to terminal distance.It is existing
There is dijkstra's algorithm to stop search behind all positions in traversing graph, due to the presence of dynamic fault, each position is only accessed
Optimal solution may be unable to get one time, improved dijkstra's algorithm repeats to search for, until moving to final position.
(2) based on the paths planning method of IPSO
Droplets mixing path design problem is to design droplet travel paths under conditions of guaranteeing that mixing is completed, and realizes liquid
Drip the shortest target of moving distance.It in drop moving process, needs to avoid by fault electrode, and avoids droplets from and other liquid
Unnecessary mixing occurs for drop, other drops are in different positions in different time piece, so the problem is dynamic fault item
Path planning problem under part, the present invention, which selects, improves particle swarm algorithm searching optimal path.
The predation of PSO simulation flock of birds.In PSO, each feasible solution corresponds to a bird in search space, and food is corresponding
The optimal solution of optimization problem.In particle swarm algorithm, each individual is known as one " particle ", and PSO is initialized as a group random particles
(feasible solution that each particle represents problem).Each particle has the adaptive value determined by majorized function, has speed
Vector determines the direction and distance that they search in next step.The pole that per generation particle is arrived according to the speed of particle oneself, particle search
The optimum point (for globally optimal solution) searched out in value point (referred to as individual optimal solution) and population determines its velocity vector direction,
Position is updated according to velocity vector during iteration, gradually close to optimal solution.The speed expanded of particle oneself the searching of particle
Suo Nengli improves the performance of global optimization；Particle search to extreme point be local optimum, particle has memory function,
When carrying out location updating, it is contemplated that the influence of local optimum；Global optimum part embodies the shared of information between particle, often
The globally optimal solution in generation is closest to the feasible solution of optimal solution, while particle utilizes global optimum's information, with reference to other information,
The common update for determining subsequent time position, prevents algorithm from rapidly converging to locally optimal solution.
For as follows, the maximum number of iterations Gen that improves particle swarm algorithm founding mathematical models, when iteration is to the m times, n particle
Position be expressed as xn m, the velocity vector of particle is expressed asxlb mIndicate the optimal solution that the particle is found, xgb mIndicate global
Optimal solution particle, in the m+1 times iteration, speed and position vector renewal speed are as follows:
It includes three parts that speed, which updates:It indicates the current speed of particle, has and expand region of search, explore new sky
Between, random search the characteristics of, which ensure that the algorithm for the coverage rate of solution space, ensures ability of searching optimum, adjust
Balance between global search and local search；xlb m-xn mIndicate " memory section " of particle, particle is searched according to itself
History optimal solution is updated speed, embodies the learning ability that particle finds process to itself in an iterative process, ensures
The local search ability of particle；xgb m-xn mInformation is shared between expression population, is " population part ", is particle to entire kind
The learning ability of group's optimization process.c1And c2Indicate the acceleration constant of particle, the value usually in [0,2] section, for balancing
Influence degree of the individual optimal and global optimum to particle rapidity.r1And r2It is the random number in [0,1] section, in setting
c1And c2On the basis of constantly change with iteration, enhance the randomness and ability of searching optimum of algorithm.
As previously mentioned, fault restoration is to be designed under the conditions of faulty to droplet travel paths.Droplets mixing road
Diameter design is to design movement routine under conditions of faulty point and other dynamic mobile drops, is completed in the shortest possible time mixed
Closing operation, so the output of the algorithm is test droplets electrode sequence number locating for each time.It tests drop and passes through each electricity
The time of pole unit is 0.01s, it is possible to will complete mixed path design problem with the shortest time and be converted into shortest path
Complete path design.In order to which particle swarm algorithm is applied to current problem, need to improve particle swarm algorithm, the position of particle
It sets and speed need to be redefined.
xi tIndicate electrode sequence number of the particle i locating for t moment, Xi T=(xi 1,xi 2,...,xi T) be particle position to
Amount indicates that i-th of particle is the movement routine of drop design, Xgb T=(xgb 1,xgb 2,...,xgb T) indicate global optimum grain
The position vector of son, Xlb T=(xlb 1,xlb 2,...,xlb T) indicate local optimum particle position vector.
The digital microcurrent-controlled failure of chip reparation side of the present invention combined based on improvement dijkstra's algorithm and IPSO
Method, this method comprises:
Step 1: establishing the mathematical model of digital microcurrent-controlled chip, the fault restoration of digital microcurrent-controlled chip is that having event
Chip is designed under conditions of barrier, guarantees that biochemical test is completed within defined maximum time on faulty chip.
Digital microcurrent-controlled chip is a series of electrod-array that electrodes press that certain layout type is formed, and only considers shape in present embodiment
Rule, the DMFB chip that electrod-array is rectangle.To DMFB electrod-array founding mathematical models, as shown in fig. 6, being arranged by 5 rows 5
The electrod-array that totally 25 electrodes are constituted is equivalent to the form in figure.
Step 2: determining the biochemical test to be completed of chip, determined according to the sequencing between operation digital microcurrent-controlled
Chip operation sequence chart is expressed as G (O, B).O indicates that the set of all nodes, running node number are expressed as K, then O={ Ol|
L ∈ N*, 1≤l≤K }, the l in sequence chart grasps Operational node OlIt indicates。Directed line segment between node indicates that two operations carry out
Sequencing, by OlNode is directed toward OsThe directed line segment of node is denoted as Bls(Ol,Os), indicate OlAfter operation is fully finished, OsBehaviour
Work can just start to operate.
Step 3: based on improve dijkstra's algorithm calculate two drops to be mixed between shortest path, make two to
It mixes drop and same position is moved to according to the shortest path；
Improving dijkstra's algorithm is that cost function is introduced in existing dijkstra's algorithm, and cost function guidance is existing
Dijkstra's algorithm is to most short to starting point distance, most short and scan for the longest direction of fault point distance to terminal distance；
Step 4: calculating movement routine based on IPSO, realize that drop moving distance is most under conditions of guaranteeing that mixing is completed
It is short, fault restoration is completed, the movement routine is to complete needed for mixing from the same position of step 3 to two drops to be mixed
Path.
Step 4 one, setting IPSO parameter, including maximum number of iterations Gen, acceleration constant c1、c2And c3, with speed phase
The random number r of pass1、r2And r3；
Step 4 two, the directional velocity for calculating particleWith expansion region of search, explore new space, random
The characteristics of search, the part ensure that the algorithm for the coverage rate of solution space, ensures ability of searching optimum, adjusts global search
Balance between local search；
The direction of motion of drop, is expressed as Vi t, in the case where no failure, drop each moment there are five types of movement can
Can: it keeps, upwards, downwards, to the left and to the right, respectively corresponds Vi tFive kinds of values may, be respectively defined as mk、mu、md、mlWith
mr.But in the presence of faulty and other drops, the direction of motion of drop receives limitation, definition set Ui t, indicate
In time t, drop designed by particle i can be in pos in moment t for particle with the set of moving directiont=Ei(mi+1,
ni) particle, set Ui tMethod for building up it is as follows:
(1) if electrode Ei(mi+1,ni) in t moment and t+1 moment all in the state that is not used, then drop can be protected
Hold it is static, by mkIt is put into set Ui t；
(2) if electrode Ei(mi,ni) in t moment and t+1 moment all in state is not used, then drop can be to the left
It is mobile, by mlIt is put into set Ui t；
(3) if electrode Ei(mi+2,ni) at t moment and t+1 moment all in the state that is not used, then drop can be to
It moves right, by mrIt is put into set Ui t；
(4) if electrode Ei(mi+1,ni- 1) at t moment and t+1 moment all in the state that is not used, then drop can be with
It moves down, by mdIt is put into set Ui t；
(5) if electrode Ei(mi+1,ni+ 1) at t moment and t+1 moment all in the state that is not used, then drop can be with
It moves up, by muIt is put into set Ui t。
The directional velocity of i-th of particle t moment
mk、mu、md、mlAnd mrRespectively correspond holding, upward, downward, directional velocity to the left and to the right, Ui tTable
Show that drop corresponding to i-th of particle of t moment can be with the set of moving direction when meeting constraint condition；
Step 4 three, the directional velocity for updating i-th of particle t moment
Then
xgb tFor the position of the particle of t moment global optimum, xlb tFor the position of the particle of t moment local optimum, r7For with
The random number that machine generates；
Step 4 four, update i-th of particle the t+1 moment position vector Xi t+1:
Xi T=(xi 1,xi 2,...,xi t) be particle t moment position vector, then Xi t+1=(xi 1,xi 2,...,xi t,xi t +1)；
It repeats step 4 two and is transferred to step 4 five until mixability reaches 100% to step 4 four；
Step 4 five, determine local optimum particle position vector Xlb T
Xlb T=(xlb 1,xlb 2,...,xlb T)
T is the experiment deadline；
Step 4 six, determine global optimum particle position vector Xgb T；
Xgb T=(xgb 1,xgb 2,...,xgb T)；
Step 4 two is repeated to step 4 six, until the number of iterations reaches Gen times, output meets the global optimum of condition
The position vector of particle, obtains movement routine.
Step 3 is repeated to step 4, until completing all operations according to the sequence of operation.
Claims (9)
1. based on the digital microcurrent-controlled failure of chip restorative procedure for improving dijkstra's algorithm and IPSO combination, which is characterized in that
This method comprises:
Step 1: based on improve dijkstra's algorithm calculate two drops to be mixed between shortest path, make two it is to be mixed
Drop moves to same position according to the shortest path；
Improving dijkstra's algorithm is that cost function is introduced in existing dijkstra's algorithm, and cost function guidance is existing
Dijkstra's algorithm is to most short to starting point distance, most short and scan for the longest direction of fault point distance to terminal distance；
Step 2: calculating movement routine based on IPSO, realize that drop moving distance is most short under conditions of guaranteeing that mixing is completed,
Fault restoration is completed, the movement routine is to complete road needed for mixing from the same position of step 1 to two drops to be mixed
Diameter.
2. according to claim 1 repaired based on the digital microcurrent-controlled failure of chip for improving dijkstra's algorithm and IPSO combination
Compound method, which is characterized in that the cost function fcost(Dk,i) are as follows:
Wherein, dis (Dk,i,Dk,i,start) it is distance of the current point to starting point, dis (Dk,i,Dk,i,end) it is that current point arrives terminal
Distance, min [dis (Dk,i,Ef)] it is current point to nearest the distance between fault point, α, β and γ are weight coefficient.
3. according to claim 2 repaired based on the digital microcurrent-controlled failure of chip for improving dijkstra's algorithm and IPSO combination
Compound method, which is characterized in that the step 1 includes:
Step 1 one, setting set S, set S are shortest path sequence, and the initial value in set S only includes the point of drop
It sets, i.e. S={ pos1}；
Step 1 two generates set S', and S' includes that subsequent time can when meeting constraint condition for drop in S at newest element
The position pos that can be moved tot+1, S' contains up to five elements, it is assumed that the electrode unit position that drop is currently located is Ei(mi+
1,ni), post+1Are as follows: post+1=Ei(mi+1,ni), post+1=Ei(mi+2,ni), post+1=Ei(mi,ni), post+1=Ei(mi
+1,ni- 1), post+1=Ei(mi+1,ni+ 1), miFor columns, niFor line number；
Step 1 three, the cost function for calculating each element in S',
Step 1 four selects the smallest position of cost function as pos from S'2, update shortest path access order S, S=
{pos1,pos2}；
Step 1 two is repeated to step 1 four, until liquid drop movement to terminal, obtains S={ pos1,pos2,pos3……}。
4. according to claim 1 repaired based on the digital microcurrent-controlled failure of chip for improving dijkstra's algorithm and IPSO combination
Compound method, which is characterized in that step 2 specifically:
Step 2 one, setting IPSO parameter, including maximum number of iterations Gen, acceleration constant c1、c2And c3, relevant to speed
Random number r1、r2And r3；
Step 2 two, the directional velocity for calculating i-th of particle t moment
mk、mu、md、mlAnd mrRespectively correspond holding, upward, downward, directional velocity to the left and to the right, Ui tIndicate t
Drop corresponding to i-th of particle of moment can be with the set of moving direction when meeting constraint condition；
Step 2 three, the directional velocity for updating i-th of particle t moment
xgb tFor the position of the particle of t moment global optimum, xlb tFor the position of the particle of t moment local optimum, r7To generate at random
Random number；
Step 2 four, update i-th of particle the t+1 moment position vector Xi t+1:
It repeats step 2 two and is transferred to step 2 five until mixability reaches 100% to step 2 four；
Step 2 five, determine local optimum particle position vector Xlb T
Xlb T=(xlb 1,xlb 2,...,xlb T)
T is the experiment deadline；
Step 2 six, determine global optimum particle position vector Xgb T；
Xgb T=(xgb 1,xgb 2,...,xgb T)；
Step 2 two is repeated to step 2 six, until the number of iterations reaches Gen times, output meets the particle of the global optimum of condition
Position vector, obtain movement routine.
5. according to claim 3 or 4 based on the digital microcurrent-controlled chip event for improving dijkstra's algorithm and IPSO combination
Hinder restorative procedure, which is characterized in that the constraint condition includes failure constraint condition, static constraint condition and dynamic constrained item
Part；
Failure constraint condition is that fault electrode unit is not used within the experiment deadline；
Static constraint condition is that two drops cannot be in direct neighbor or diagonally adjacent electrode unit position；
Dynamic constrained condition is when one electrode unit of distance between two drops, and two drops can not be simultaneously along straight line where it
Do movement in the same direction.
6. according to claim 5 repaired based on the digital microcurrent-controlled failure of chip for improving dijkstra's algorithm and IPSO combination
Compound method, which is characterized in that the mathematical model of the failure constraint condition are as follows:
Wherein, Ea f(ma,na) it is fault electrode unit, EfFor the set of fault electrode unit, TrealTo test the deadline,
BatFor binary variable, the case where indicating that electrode unit is used in each timeslice, if in the t time, a-th of electrode
Unit Ea(ma,na) used, then BatIt is 1, otherwise BatIt is 0；maFor columns, n where a-th of electrode unitaFor a-th of electrode
Line number where unit.
7. according to claim 5 repaired based on the digital microcurrent-controlled failure of chip for improving dijkstra's algorithm and IPSO combination
Compound method, which is characterized in that in the t time, kthaAnd kjThe position of a drop is respectivelyWithIt is quiet
The mathematical model of modal constraint condition are as follows:
maAnd mjRespectively a-th and j-th of electrode unit place columns, naAnd njRespectively a-th and j-th of electrode unit institute
In line number, DtFor the set of droplet position.
8. according to claim 5 repaired based on the digital microcurrent-controlled failure of chip for improving dijkstra's algorithm and IPSO combination
Compound method, which is characterized in that be respectively in the position of t time, two dropsWithTwo drops
It is respectively by the movement done in the t timeWithElectrode unit where two drops is respectively Ea(ma,na) and Ej(mj,nj),
The vector that two electrode unit positions are constituted is expressed as Indicate two vectors it
Between angle, the mathematical model of dynamic constrained condition are as follows:
maAnd mjRespectively a-th and j-th of electrode unit place columns, naAnd njRespectively a-th and j-th of electrode unit institute
In line number.
9. according to claim 1 repaired based on the digital microcurrent-controlled failure of chip for improving dijkstra's algorithm and IPSO combination
Compound method, which is characterized in that before step 1 further include: the mathematical model for establishing digital microcurrent-controlled chip, according to operation
Between sequencing determine the operation sequence diagram of digital microcurrent-controlled chip；
One is executed the step to after step 2, step 1 is repeated to step 2, until completing all operations according to the sequence of operation.
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