CN105824998B - A kind of development blasting construction intelligent design system and method - Google Patents
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Abstract
The present invention relates to a kind of development blasting construction intelligent design system and methods.The system comprises man-machine interface, inference machine and knowledge base.Man-machine interface carries out human-computer dialogue for user and the system；Knowledge base includes expertise knowledge base, typical case knowledge base and explosion rule-based knowledge base.The present invention realizes the intelligent design of development blasting construction by establishing knowledge base and inference machine.Knowledge base covers the knowledge such as expertise, typical case, explosion rule, and knowledge quantity is big, broad covered area, with strong points, and it is practical to meet field engineering application.Inference machine can be realized the reasoning based on expertise, typical case, explosion rule.All inference schemes carry out the inspection of shotfiring safety specification by the reasoning based on explosion rule.User can be compared the scheme obtained by different inference modes, select one of scheme, can also be modified by parameter of the reasoning results access interface to scheme part, finally obtain the blasting design scheme of optimization.
Description
Technical field
The invention belongs to blast working design fields, and in particular to a kind of development blasting construction intelligent design system and side
Method.
Background technique
Blast working is an important link of tunneling construction, and the quality of blast working quality has follow-up work very big
It influences.The quality of blast working quality depends primarily on two aspects: explosion design and blast working operation.Explosion designer
It can carry out optimal explosion design according to the actual situation and work out accurate construction regulations appropriate to be to obtain good explosion matter
The premise of amount.
Currently, there are two ways to determining blasting parameter in blast working design: one is theoretical type methods.It is from mechanics
Angle is set out, the development process after describing explosive charge with numerical simulation in rock mass, according to analog result and Dynamic stress field
Distribution carries out explosion design；Or the distribution from blasting energy in rock mass, the transforming relationship of analysing energy.By its think of
Road, optimal explosion design should be such that explosion energy is sufficiently uniformly distributed in rock mass, and most of energy is made to be converted into rock mass
In crushing work；Or can be with process data at high speeds using computer the characteristics of, design program is established by empirical equation, is passed through
Compare different schemes, reaches optimal selection.Another kind is practical method, it is grown up recent years using artificial
The Intelligentized method that intelligent Theory is established.This method can quantitatively locate the method for many important parameter statistical methods or classification
Reason also can be used many rules accumulated in knowledge base that designer is assisted to make inferences judgement, to formulate best design.
Both the above method respectively has its advantage and deficiency.Theoretical type method lays particular emphasis on the research of blast mechanism, it is intended to pass through
Stress field or energy density distribution instruct explosion to design, but this method is complex, need many theoretic hypothesis and big
The field condition of amount, it is difficult to obtain input variable, it is made to seem heavy in hand.Practical method generally stresses the meter of economic indicator
It calculates, substantially using computer, rule of thumb formula or semiempirical formula are calculated, not in terms of mine fragmentation mechanism
How research obtains best crushing effect, only a kind of complementary design means.In short, theoretical type method has with practical application
Certain gap, and practical method lacks certain theoretical basis.
Summary of the invention
In order to solve the above-mentioned problems in the prior art, the present invention proposes a kind of development blasting construction intelligent design system
System and method, establish knowledge base and inference machine, according to the raw process parameter data of input, by calling knowledge base to make inferences to obtain
Target design scheme, to realize the intelligent design of development blasting construction.
In order to achieve the above objectives, the present invention adopts the following technical scheme:
A kind of development blasting construction intelligent design system, comprising: man-machine interface, inference machine, knowledge base.The man-machine interface
Human-computer dialogue is carried out for user (designer) and the system；The knowledge base includes expertise knowledge base, typical case
Example knowledge base and explosion rule-based knowledge base.Knowledge in the expertise knowledge base and typical case knowledge base splits into one
Item have precondition rule after be stored in the explosion rule-based knowledge base.The inference machine include parameter interactive module,
Explosion reasoning module, result display module and preservation read module.Wherein:
The parameter interactive module realizes the editor to reasoning supplemental characteristic and modification for receiving, handling initial data.
The matching that the explosion reasoning module passes through the initial parameter of calculating input and the precondition of knowledge in knowledge base
Degree extracts the maximum knowledge of matching degree, and the theoretical calculation for carrying out parameter obtains the reasoning results.User is to based on different knowledge bases
The scheme that reasoning obtains is compared, optimizes, and obtains final blasting design scheme.
The result display module is for showing the reasoning results.
The read module that saves saves the initial data inputted, the ephemeral data of system-computed with data mode and is
The reasoning results of system.
A kind of development blasting construction Intelligentized design method, comprising the following steps:
Determine the main indicator for influencing demolition effect.
According to identified index by the raw process parameter data of man-machine interface input blasting scheme.
Inference machine is according to raw process parameter data, by calling knowledge base to carry out reasoning based on expertise, based on typical case
The reasoning of case and reasoning based on explosion rule, carry out safety to first two reasoning using the reasoning based on explosion rule respectively
Specification is examined, if the reasoning results of first two reasoning have exceeded the range of rule requirement, using rule as the reasoning results, is otherwise protected
Stay the reasoning results.
The scheme that user obtains the reasoning based on expertise and the scheme that the reasoning based on typical case obtains carry out
Compare, select one of scheme as final blasting design scheme, or parameter is carried out by the reasoning results access interface
Amendment, the blasting design scheme optimized.
Compared with prior art, the invention has the following advantages that
(1) present invention realizes the intelligent design of development blasting construction by establishing knowledge base and inference machine.The knowledge
Library covers the knowledge such as expertise, typical case, explosion rule, and knowledge quantity is big, abundant in content, broad covered area, with strong points,
It is practical to meet field engineering application, can satisfy most of development blasting engineering design requirements.The inference machine can be realized
Reasoning based on expertise, typical case, explosion rule.All inference schemes are carried out by the reasoning based on explosion rule
Shotfiring safety specification is examined.User can be compared the scheme obtained by different inference modes, select one of scheme,
It can also be modified by parameter of the reasoning results access interface to scheme part, finally obtain the explosion design side of optimization
Case.
(2) present invention determines explosion design objective using weight distribution, the existing theories integration of this method, and can be towards reality
Border application, can accurately determine it is less maximum index, explicit physical meaning are influenced on explosion, data are easy to obtain,
Convenient for theoretical knowledge, weaker technical staff is used.
Detailed description of the invention
Fig. 1 is the block diagram of development blasting construction intelligent design system；
Fig. 2 is the flow chart of development blasting construction Intelligentized design method.
Specific embodiment
The present invention will be further described with reference to the accompanying drawings and examples.
A kind of development blasting construction intelligent design system, composition are as shown in Figure 1, comprising: man-machine interface, inference machine are known
Know library.Man-machine interface carries out human-computer dialogue for user and the system；Knowledge base includes expertise knowledge base, typical case
Knowledge base and explosion rule-based knowledge base.Expertise knowledge base and expertise in typical case knowledge base and theoretical model are torn open
Be divided into a rule with precondition rule after be stored in explosion rule-based knowledge base.Inference machine include parameter interactive module,
Explosion reasoning module, result display module and preservation read module.Wherein:
Parameter interactive module realizes the editor to reasoning supplemental characteristic and modification for receiving, handling initial data.
Explosion reasoning module is mentioned by the matching degree of the initial parameter of calculating input and the precondition of knowledge in knowledge base
The maximum knowledge of matching degree is taken, and the theoretical calculation for carrying out parameter obtains the reasoning results.User is to based on different Analysis of Knowledge Bases Reasoning
The scheme obtained is compared, optimizes, and obtains final blasting design scheme.
As a result display module is used for display systems the reasoning results.Purpose is to user's rationally clearly reasoning of expression system
Scheme, and effective blast working is carried out based on inference schemes.
Save ephemeral data and the reasoning results that read module is used to save the initial data of input, calculating.It saves
All the elements are stored with data mode, pass through whenever and wherever possible convenient for user and the data saved is called to check inference schemes.
Man-machine interface includes engineering information access interface, Inference Conditions access interface, knowledge base access interface and reasoning knot
Fruit access interface.Wherein:
Engineering information access interface is for inputting physical message relevant to blasting engineering, including designer's name, engineering
The essential informations such as title, storing path.So that the engineering information that user inputs before accesses knowledge base.
Inference Conditions access interface is for inputting raw process parameter data.According to the requirement of system, user can be directly inputted
Real data can also be selected according to prompt.
Knowledge base access interface is for being managed and safeguarding to knowledge base.With the progress of blasting technique, user
It should be constantly improve and more new knowledge base by the management to knowledge base.
The reasoning results access interface is used to access the scheme comprising all explosion design parameters that reasoning obtains, and to portion
Point parameter is adjusted.In order to preferably embody the practicability of system, user can adjust partial parameters using the interface
It is whole, so that system draws blasting engineering figure automatically, preferably instruct practical blasting.
The data of expertise knowledge base are mainly derived from explosion domain expert theory and field engineering technical staff's experience
Knowledge, analysis and summary explosion related fields science monograph, paper, technical report, identification achievement；The data of typical case knowledge base
It is mainly derived from typical explosion design and construction case；The data of explosion rule-based knowledge base are mainly derived from national sector standard, ground
Square professional standard and industry standard.
The system also includes subsystem is explained, the problem of for answering user, process for using and principle expository writing are provided
Shelves.
The system also includes the drawing subsystems for drawing blast working chart.
A kind of development blasting construction Intelligentized design method, comprising the following steps:
Determine the main indicator for influencing demolition effect.
According to identified index by the raw process parameter data of man-machine interface input blasting scheme.
Inference machine is according to raw process parameter data, by calling knowledge base to carry out reasoning based on expertise, based on typical case
The reasoning of case and reasoning based on explosion rule, carry out safety to first two reasoning using the reasoning based on explosion rule respectively
Specification is examined, if the reasoning results of first two reasoning have exceeded the range of rule requirement, using rule as the reasoning results, is otherwise protected
Stay the reasoning results.
The scheme that user obtains the reasoning based on expertise and the scheme that the reasoning based on typical case obtains carry out
Compare, select one of scheme as final blasting design scheme, or parameter is carried out by the reasoning results access interface
Amendment, the blasting design scheme optimized.
Determine influence explosion refer mainly to calibration method the following steps are included:
Step 1, the index having an impact to demolition effect is chosen.
Step 2, the weight for the index that step 1 is chosen is determined, the specific method is as follows:
Step 2.1, according to the correlation and final problem to be solved between index, described problem is carried out preliminary
Analysis, divides the index with common trait into one group, and using the common trait as indicator combination at higher level；According to phase
Same method operates the higher level, forms higher；Aforesaid operations are repeated, are made of until formation single index
It is top.
Step 2.2, the significance level of the index in more same level, and assignment is carried out by the size of significance level, it obtains
To trip current.Trip current are as follows:
P=(bij)n×n
Wherein, P is trip current；I=1,2 ..., n, j=1,2 ..., n, n be index number, bijIndicate i-th of finger
Mark the important degree of than j-th index, bji=1/bij。bijValue be integer 1~9 and 1~9 inverse；Wherein:
1 expression two indices are compared, and have no less important；
3 expression two indices are compared, and an index is slightly more important than another index；
5 expression two indices are compared, and an index is obviously more important than another index；
7 expression two indices are compared, and an index is strongly more important than another index；
9 expression two indices are compared, and an index is more extremely important than another index；
2,4,6,8 significance levels indicated are respectively positioned between significance level represented by its adjacent integer.
Step 2.3, the feature vector of trip current is normalized to obtain the weight of each index.Seek trip current
Maximum eigenvalue and calculate coincident indicator and random consistency ratio, adjustment trip current until each index weight meet
Coherence request.The specific method is as follows:
Calculate the product M of each row element of trip currenti:
Wherein, bijFor the value that the i-th row jth of trip current P arranges, the important journey of than j-th index of i-th of index is indicated
Degree, i=1,2 ..., n, j=1,2 ..., n, n be index number；
Calculate MiN times root
To vectorIt is normalized, obtains characteristic vector W=[W1, W2, Λ, Wn]T, from
And obtain the sequencing weight of each index；
Calculate the Maximum characteristic root λ of trip current Pmax:
Wherein, (pW)iFor i-th of element of vector pW；
Calculate coincident indicator CI and random consistency ratio CR:
CI=(λmax-n)/(n-1)
CR=CI/RI
Wherein, RI is Aver-age Random Consistency Index, and RI is chosen by following method: when n is 1,2,3,4,5,6,7,8,9,
When 10,11,12, RI is respectively as follows: 0.00,0.00,0.58,0.90,0.12,0.24,0.32,0.41,0.46,0.49,0.52,
0.54。
If CR is less than the threshold value of setting, the result of Mode of Level Simple Sequence meets coherence request；Otherwise, again more same
The importance of index in level simultaneously carries out assignment, obtains new trip current, recalculates weight and carries out compliance evaluation,
Until CR is less than the threshold value of setting.
Step 3, each index is ranked up by weight size, chooses several indexs of maximum weight to influence demolition effect
Index.
Reasoning based on expertise the following steps are included:
Input raw process parameter data.
Calculate the matching degree of the precondition of certain knowledge in the initial parameter and expertise knowledge base of input；According to
Judge whether to match with degree size.
Matched expertise knowledge is extracted, the reasoning results are obtained.
Reasoning based on typical case the following steps are included:
Input raw process parameter data.
According to the requirement and primary condition of problem, the precondition phase with current problem is extracted from typical case knowledge base
As case.
The matching degree of initial parameter and all similar cases is calculated, and matching degree is ranked up by size.
The maximum typical case of matching degree is extracted, the blasting parameter of the typical case is obtained, obtains the reasoning results.
Reasoning based on explosion rule the following steps are included:
Input raw process parameter data；
The matching degree for calculating the initial parameter of precondition and input regular in explosion rule-based knowledge base, according to matching degree
Size judges whether to match, and finds and the matched rule of initial parameter；
It is made inferences according to matched rule, obtains the reasoning results.
The present invention is not limited to the above embodiments, made any to above embodiment aobvious of those skilled in the art and
The improvement or change being clear to, all protection scope without departing from design of the invention and appended claims.
Claims (4)
- The Intelligentized design method 1. a kind of development blasting is constructed, which is characterized in that the described method comprises the following steps:Determine the main indicator for influencing demolition effect；According to identified index by the raw process parameter data of man-machine interface input blasting scheme；Inference machine is according to raw process parameter data, by calling knowledge base to carry out reasoning based on expertise, based on typical case Reasoning and reasoning based on explosion rule, safety standard is carried out respectively to first two reasoning using the reasoning based on explosion rule It examines, if the reasoning results of first two reasoning have exceeded the range of rule requirement, using rule as the reasoning results, otherwise retains and push away Manage result；The scheme that user obtains the reasoning based on expertise and the scheme that the reasoning based on typical case obtains are compared, One of scheme is selected to be modified as final blasting design scheme, or by the reasoning results access interface to parameter, The blasting design scheme optimized；Wherein it is determined that influence explosion refer mainly to calibration method the following steps are included:Step 1, the index having an impact to demolition effect is chosen；Step 2, the weight for the index that step 1 is chosen is determined, the specific method is as follows:Step 2.1, according to the correlation and final problem to be solved between the index, described problem is carried out preliminary Analysis, divides the index with common trait into one group, and using the common trait as indicator combination at higher level；According to phase Same method operates the higher level, forms higher；Aforesaid operations are repeated, are made of until formation single index It is top；Step 2.2, the significance level of the index in more same level, and assignment is carried out by the size of significance level, sentenced Set matrix；The trip current are as follows:P=(bij)n×nWherein, P is trip current；I=1,2 ..., n, j=1,2 ..., n, n be index number, bijIndicate i-th of index ratio The important degree of j-th of index, bji=1/bij；bijValue be integer 1~9 and 1~9 inverse；Wherein:1 expression two indices are compared, and have no less important；3 expression two indices are compared, and an index is slightly more important than another index；5 expression two indices are compared, and an index is obviously more important than another index；7 expression two indices are compared, and an index is strongly more important than another index；9 expression two indices are compared, and an index is more extremely important than another index；2,4,6,8 significance levels indicated are respectively positioned between significance level represented by its adjacent integer；Step 2.3, the feature vector of trip current is normalized to obtain the weight of each index；Seek trip current most Big characteristic value simultaneously calculates coincident indicator and random consistency ratio, and adjustment trip current is until the weight of each index meets unanimously Property require；The specific method is as follows:Calculate the product M of each row element of trip currenti:Wherein, bijFor the value that the i-th row jth of trip current P arranges, the important degree of than j-th index of i-th of index, i=are indicated 1,2 ..., n, j=1,2 ..., n, n be index number；Calculate MiN times rootTo vectorIt is normalized, obtains characteristic vector W=[W1, W2, Λ, Wn]T, thus To the sequencing weight of each index；Calculate the Maximum characteristic root λ of trip current Pmax:Wherein, (pW)iFor i-th of element of vector pW；Calculate coincident indicator CI and random consistency ratio CR:CI=(λmax-n)/(n-1)CR=CI/RIWherein, RI is Aver-age Random Consistency Index, and RI is chosen by following method: when the n is 1,2,3,4,5,6,7,8,9, When 10,11,12, RI is respectively as follows: 0.00,0.00,0.58,0.90,0.12,0.24,0.32,0.41,0.46,0.49,0.52, 0.54；If CR is less than the threshold value of setting, the result of Mode of Level Simple Sequence meets coherence request；Otherwise, more same level again In index importance and carry out assignment, obtain new trip current, recalculate weight and carry out compliance evaluation, until CR is less than the threshold value of setting；Step 3, each index is ranked up by weight size, several indexs for choosing maximum weight are the finger for influencing demolition effect Mark.
- The Intelligentized design method 2. development blasting according to claim 1 is constructed, which is characterized in that described to be based on expertise Reasoning the following steps are included:Input raw process parameter data；Calculate the matching degree of the precondition of certain knowledge in the initial parameter and expertise knowledge base of input；According to matching degree Size judges whether to match；Matched expertise knowledge is extracted, the reasoning results are obtained.
- The Intelligentized design method 3. development blasting according to claim 1 is constructed, which is characterized in that described to be based on typical case Reasoning the following steps are included:Input raw process parameter data；According to the requirement and primary condition of problem, extracted from typical case knowledge base similar with the precondition of current problem Case；The matching degree of initial parameter and all similar cases is calculated, and matching degree is ranked up by size；The maximum typical case of matching degree is extracted, the blasting parameter of the typical case is obtained, obtains the reasoning results.
- The Intelligentized design method 4. development blasting according to claim 1 is constructed, which is characterized in that described based on explosion rule Reasoning the following steps are included:Input raw process parameter data；The matching degree of the initial parameter of precondition and input regular in explosion rule-based knowledge base is calculated, it is big according to matching degree It is small, judge whether to match, find and the matched rule of initial parameter；It is made inferences according to matched rule, obtains the reasoning results.
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Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2007096734A1 (en) * | 2006-02-20 | 2007-08-30 | Institute Of Communications And Information Technologies, Kyrgyz-Russian Slavic University | Method for drilling-and-blasting operations at open pits |
| CN104318086A (en) * | 2014-10-11 | 2015-01-28 | 同济大学 | Channel smooth blasting quality evaluation prediction method |
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Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2007096734A1 (en) * | 2006-02-20 | 2007-08-30 | Institute Of Communications And Information Technologies, Kyrgyz-Russian Slavic University | Method for drilling-and-blasting operations at open pits |
| CN104318086A (en) * | 2014-10-11 | 2015-01-28 | 同济大学 | Channel smooth blasting quality evaluation prediction method |
Non-Patent Citations (3)
| Title |
|---|
| 杨仁树等.煤矿巷道掘进***智能设计***及应用.《煤炭学报》.2013,第38卷(第7期),第1131页第1.1-1.2节、第1132页第1.4节-1133页第2.3节，第1134页第3.3节第（1）部分，附图2-5，表1-3. * |
| 煤矿巷道掘进***智能设计***及应用;杨仁树等;《煤炭学报》;20130731;第38卷(第7期);第1131页第1.1-1.2节、第1132页第1.4节-1133页第2.3节，第1134页第3.3节第（1）部分，附图2-5，表1-3 * |
| 隧道掘进***设计智能***研究;肖清华;《中国博士学位论文全文数据库 工程科技Ⅱ辑》;20071015(第4期);正文第35页第1段，第40页第3.2.5节，第61页倒数第2段，第150页第8.3.1节 * |
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