CN111047209A - Decision-making method and system for pavement preventive maintenance technology - Google Patents
Decision-making method and system for pavement preventive maintenance technology Download PDFInfo
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Abstract
The invention provides a decision-making method and a decision-making system for a pavement preventive maintenance technology, which comprise the following steps: determining a plurality of candidate preventive maintenance measures, and evaluation factors and evaluation grades of preventive maintenance technologies; establishing a fuzzy evaluation matrix of each candidate preventive maintenance measure according to the evaluation factors and the evaluation grades; acquiring the comprehensive weight of each evaluation factor in the evaluation of preventive maintenance measures; obtaining a fuzzy comprehensive evaluation result of the candidate preventive maintenance measures according to the fuzzy evaluation matrix and the comprehensive weight of the candidate preventive maintenance measures; and selecting the candidate preventive maintenance measure with the highest comprehensive evaluation as the target maintenance measure according to the fuzzy comprehensive evaluation results of all the candidate preventive maintenance measures. The invention can solve the problems of one-sided decision factors, experience and the like in decision of the current maintenance technology.
Description
Technical Field
The invention relates to the technical field of pavement maintenance, in particular to a decision-making method and a decision-making system for a pavement preventive maintenance technology.
Background
At present, the preventive maintenance technology of the asphalt pavement is various in types, and the common technologies comprise: crack pouring, asphalt reduction treatment, fog seal, micro-surfacing, slurry seal, fiber synchronous chip seal, ultra-thin wearing layer and the like. However, when the preventive maintenance technology is applied, the optimal maintenance effect and economic benefit can be realized only by adopting the preventive maintenance technology at any time and in any road condition mainly by means of subjective experience, and the road workers are troubled.
The currently common preventive maintenance decision methods are: a cost benefit analysis method, a life cycle cost method, a decision tree method and a decision matrix method.
The cost benefit analysis method refers to that when a specific purpose is achieved, a plurality of economic technical schemes can be selected, the schemes are different in the effect of achieving the purpose and the cost of consumption, and the scheme with the highest benefit cost ratio can be determined through utility analysis.
Life cycle cost analysis is a method of analyzing the economic benefit of a project using the life cycle of the project as the period of cost accounting.
The decision tree method is characterized in that decision is assisted through a tree-shaped graph as the name suggests, each branch represents a specific condition set (such as road surface type, damage type and degree, traffic volume, function level and the like), and maintenance strategies are finally determined according to the condition sets.
The decision matrix method is very similar to the decision tree method, and essentially depends on a series of rules and standards to select a proper maintenance strategy, the biggest difference is that the decision tree method provides a graphical tool, and the decision matrix method provides a table to reduce the space for storing data.
However, the methods for selecting preventive maintenance measures all have respective inevitable disadvantages, such as a cost benefit analysis method, which usually selects measures only from an economic perspective and considers less road conditions; life cycle cost methods often neglect consideration of long-term road performance for preventative maintenance measures; the decision tree and decision matrix methods have poor portability and are difficult to consider the combination of various factors.
Disclosure of Invention
The invention aims to provide a decision method and a decision system for a pavement preventive maintenance technology, which are used for solving the problem that decision factors are one-sided in the prior art.
The technical scheme provided by the invention is as follows:
a decision-making method of a pavement preventive maintenance technology comprises the following steps: determining a plurality of candidate preventive maintenance measures, and evaluation factors and evaluation grades of preventive maintenance technologies; establishing a fuzzy evaluation matrix of each candidate preventive maintenance measure according to the evaluation factors and the evaluation grades; acquiring the comprehensive weight of each evaluation factor in the evaluation of preventive maintenance measures; obtaining a fuzzy comprehensive evaluation result of the candidate preventive maintenance measures according to the fuzzy evaluation matrix of the candidate preventive maintenance measures and the comprehensive weight; and selecting the candidate preventive maintenance measure with the highest comprehensive evaluation as the target maintenance measure according to the fuzzy comprehensive evaluation results of all the candidate preventive maintenance measures.
Further, the determining the evaluation factors of the preventive maintenance technology comprises: determining the evaluation factors of the preventive maintenance technology from the following road surface damage conditions which can be solved by the preventive maintenance technology: transverse cracks, longitudinal cracks, deformation, peeling, pits, water damage, rutting, sinking.
Further, the obtaining of the comprehensive weight of each evaluation factor in the evaluation of the preventive maintenance measures includes: and (4) obtaining the comprehensive weight of each evaluation factor in the evaluation of preventive maintenance measures by using an analytic hierarchy process.
Further, the obtaining of the comprehensive weight of each evaluation factor in the evaluation of the preventive maintenance measures by using the analytic hierarchy process specifically includes: obtaining a pairwise comparison judgment matrix by pairwise comparison of each evaluation factor; calculating the eigenvectors of the pairwise comparison judgment matrix; carrying out consistency check on the pairwise comparison judgment matrixes; and when the two comparison judgment matrixes are judged to have satisfactory consistency according to the check result, the characteristic vector is used as the comprehensive weight of each evaluation factor in the evaluation of preventive maintenance measures.
Further, the calculating the feature vector of the pairwise comparison and judgment matrix includes: multiplying the elements of each row in the pairwise comparison judgment matrix to obtain a product value M of each rowi(ii) a Calculating the eigenvector W of the pairwise comparison judgment matrix according to the following formula:
W＝[W1,W2,...,Wm]T，
wherein m is the order of the pairwise comparison judgment matrix.
Further, the consistency check on the pairwise comparison judgment matrix includes: calculating the maximum characteristic root of the pairwise comparison judgment matrix; calculating a matrix consistency judgment index of the pairwise comparison judgment matrix according to the maximum feature root; and when the matrix consistency judgment index is smaller than a preset threshold, comparing every two matrixes to judge that the matrixes have satisfactory consistency.
The invention also provides a decision-making system of the pavement preventive maintenance technology, which comprises the following components: the candidate measure setting module is used for determining a plurality of candidate preventive maintenance measures; the evaluation factor setting module is used for determining evaluation factors of the preventive maintenance technology; the evaluation grade setting module is used for determining the evaluation grade of the preventive maintenance technology; the evaluation matrix construction module is used for establishing a fuzzy evaluation matrix of each candidate preventive maintenance measure according to the evaluation factors and the evaluation grades; the comprehensive weight acquisition module is used for acquiring the comprehensive weight of each evaluation factor in the evaluation of preventive maintenance measures; the comprehensive evaluation module is used for obtaining a fuzzy comprehensive evaluation result of the candidate preventive maintenance measures according to the fuzzy evaluation matrix of the candidate preventive maintenance measures and the comprehensive weight; and selecting the candidate preventive maintenance measure with the highest comprehensive evaluation as the target maintenance measure according to the fuzzy comprehensive evaluation results of all the candidate preventive maintenance measures.
Further, the comprehensive weight obtaining module is further used for obtaining the comprehensive weight of each evaluation factor in the preventive maintenance measure evaluation by using an analytic hierarchy process.
Further, the comprehensive weight obtaining module further includes: the comparison and judgment matrix calculation unit is used for obtaining a pairwise comparison and judgment matrix by pairwise comparison of each evaluation factor; the feature vector calculation unit is used for calculating the feature vectors of the pairwise comparison judgment matrix; the consistency checking unit is used for carrying out consistency checking on the pairwise comparison judgment matrixes; and when the two comparison judgment matrixes are judged to have satisfactory consistency according to the check result, the characteristic vector is used as the comprehensive weight of each evaluation factor in the evaluation of preventive maintenance measures.
Further, the consistency check unit is further configured to calculate a maximum feature root of the pairwise comparison and determination matrix; calculating a matrix consistency judgment index of the pairwise comparison judgment matrix according to the maximum feature root; and when the matrix consistency judgment index is smaller than a preset threshold, comparing every two matrixes to judge that the matrixes have satisfactory consistency.
The decision method and the decision system for the pavement preventive maintenance technology provided by the invention can bring the following beneficial effects:
1. according to the invention, the evaluation result of each evaluation object is obtained by fuzzy comprehensive evaluation of a plurality of evaluation factors, and then the most suitable preventive maintenance measures are determined, so that the one-sidedness of preventive maintenance measure selection is avoided.
2. The invention combines the analytic hierarchy process and the fuzzy mathematics comprehensive evaluation process, applies to the decision of the pavement preventive maintenance technology, and improves the comprehensiveness and scientificity of the preventive maintenance measure selection.
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The above features, technical features, advantages and implementations of a method and system for determining preventive maintenance of a pavement will be further described in the following detailed description of preferred embodiments in a clearly understandable manner with reference to the accompanying drawings.
FIG. 1 is a flow chart of one embodiment of a decision-making method of a preventive maintenance technique for roadways of the present invention;
FIG. 2 is a flow chart of another embodiment of a decision-making method of a preventive maintenance technique for roadways of the present invention;
FIG. 3 is a flow chart of the chromatography process of FIG. 2;
FIG. 4 is a schematic structural diagram of an embodiment of a decision system of a preventive maintenance technique for a road surface according to the present invention;
FIG. 5 is a schematic diagram of an embodiment of the integrated weight acquisition module of FIG. 4;
the reference numbers illustrate:
100. the system comprises a candidate measure setting module, a 200 evaluation factor setting module, a 300 evaluation grade setting module, a 400 evaluation matrix construction module, a 500 comprehensive weight acquisition module, a 600 comprehensive evaluation module, a 510 comparison and judgment matrix calculation unit, a 520 eigenvector calculation unit and a 530 consistency check unit.
Detailed Description
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following description will be made with reference to the accompanying drawings. It is obvious that the drawings in the following description are only some examples of the invention, and that for a person skilled in the art, other drawings and embodiments can be derived from them without inventive effort.
For the sake of simplicity, the drawings only schematically show the parts relevant to the present invention, and they do not represent the actual structure as a product. In addition, in order to make the drawings concise and understandable, components having the same structure or function in some of the drawings are only schematically illustrated or only labeled. In this document, "one" means not only "only one" but also a case of "more than one".
In one embodiment of the present invention, as shown in fig. 1, a method for deciding a preventive maintenance technology for a road surface includes:
step S100, determining a plurality of candidate preventive maintenance measures, and evaluation factors and evaluation grades of preventive maintenance technologies;
step S200, establishing a fuzzy evaluation matrix of each candidate preventive maintenance measure according to the evaluation factors and the evaluation grades;
step S300, acquiring the comprehensive weight of each evaluation factor in the evaluation of preventive maintenance measures;
step S400, obtaining a fuzzy comprehensive evaluation result of the candidate preventive maintenance measures according to the fuzzy evaluation matrix of the candidate preventive maintenance measures and the comprehensive weight;
and S500, selecting the candidate preventive maintenance measure with the highest comprehensive evaluation as the target maintenance measure according to the fuzzy comprehensive evaluation results of all the candidate preventive maintenance measures.
Specifically, the preventive maintenance measures are decided by fuzzy mathematical comprehensive evaluation, and the processing process is as follows:
1) and determining a plurality of candidate preventive maintenance measures according to historical empirical data, and taking each preventive maintenance measure as an evaluation object.
2) Determining an evaluation factor for preventative maintenance techniques
And determining evaluation factors according to the pavement damage condition which can be solved by the preventive maintenance technology. Various evaluation factors constitute an evaluation factor set, such as an evaluation factor set U ═ lateral cracks, longitudinal cracks, deformation, peeling, pits, water damage, rutting }, that is: U-U1, U2, U3, U4, U5, U6, U7.
Optionally, the type of the pavement disease is obtained according to the targeted regional history data. And taking the type of the pavement diseases as evaluation factors of the preventive maintenance technology, and selecting a plurality of evaluation factors to form an evaluation factor set.
3) Determining an evaluation rating for preventative maintenance techniques
And determining the evaluation grade according to various historical evaluation results of the user on the preventive maintenance technology. The various rating levels form a rating level set, e.g., rating level set V ═ { E-valid, M-more valid, N-not recommended, Q-requiring higher technical requirements and quality control, T-invalid }, i.e.: v ═ V1, V2, V3, V4, V5 }.
4) Construction judgment matrix
And starting from a single evaluation factor, performing single-factor fuzzy evaluation on each candidate preventive maintenance technical measure, namely, considering the membership degree of each evaluation object to the evaluation grade set V from a single factor. For example, starting from the single factor ui, the single factor fuzzy evaluation is performed on the evaluation object A to obtain a corresponding single factor evaluation set ri＝(ri1，ri2，…rin)，rijThe evaluation object a is a degree of membership to the evaluation scale Vj (j is 1,2, … n) in view of the single factor ui.
And obtaining a corresponding fuzzy evaluation matrix R according to the single-factor evaluation set of all the evaluation factors of each evaluation object. Thus, each evaluation object determines a fuzzy evaluation matrix R from U to V, namely:
5) determining the comprehensive weight of each evaluation factor in the evaluation of preventive maintenance measures:
there are various methods, such as expert estimation, in which each expert gives a weight of each evaluation factor independently, and then the average of the weights of each evaluation factor is taken as the final integrated weight. Optionally, an analytic hierarchy process is used to obtain the comprehensive weight of each evaluation factor in the evaluation of preventive maintenance measures. The integrated weight of all the rating factors constitutes an integrated weight vector a ═ ai)1×m＝(a1,a2,...,am) Wherein a isiIs the comprehensive weight of the ith evaluation factor.
6) Establishing a fuzzy comprehensive evaluation model to obtain fuzzy comprehensive evaluation results of each evaluation object, and then carrying out comprehensive evaluation.
The fuzzy comprehensive evaluation model B comprises the following steps:
representing a fuzzy synthesis operator. And synthesizing the comprehensive weight vector A and the fuzzy evaluation matrix R through a proper fuzzy synthesis operator to obtain fuzzy comprehensive evaluation results of all the rating objects.
And analyzing the fuzzy comprehensive evaluation result, for example, adopting a maximum membership principle, obtaining a corresponding comprehensive score according to the fuzzy comprehensive evaluation result of each evaluation object to obtain a comprehensive score of each candidate preventive maintenance measure, and selecting the candidate preventive maintenance measure with the highest comprehensive score as a target maintenance measure.
In the embodiment, the evaluation results of the evaluation objects are obtained by fuzzy comprehensive evaluation of a plurality of evaluation factors, and then the most suitable preventive maintenance measures are determined, so that the one-sidedness of preventive maintenance measure selection is avoided.
In another embodiment of the present invention, as shown in fig. 2 and 3, a method for deciding a preventive maintenance technology of a road surface includes:
step S100, determining a plurality of candidate preventive maintenance measures, and evaluation factors and evaluation grades of preventive maintenance technologies;
step S200, establishing a fuzzy evaluation matrix of each candidate preventive maintenance measure according to the evaluation factors and the evaluation grades;
step S310, acquiring comprehensive weight of each evaluation factor in preventive maintenance measure evaluation by using an analytic hierarchy process;
step S400, obtaining a fuzzy comprehensive evaluation result of the candidate preventive maintenance measures according to the fuzzy evaluation matrix of the candidate preventive maintenance measures and the comprehensive weight;
and S500, selecting the candidate preventive maintenance measure with the highest comprehensive evaluation as the target maintenance measure according to the fuzzy comprehensive evaluation results of all the candidate preventive maintenance measures.
Wherein, step S310 includes:
step S311, comparing each evaluation factor pair by pair to obtain a comparison judgment matrix pair by pair;
step S312, calculating the eigenvector of the pairwise comparison judgment matrix;
step S313, consistency check is carried out on the pairwise comparison judgment matrixes;
and S314, when the two comparison judgment matrixes are judged to have satisfactory consistency according to the verification result, taking the characteristic vector as the comprehensive weight of each evaluation factor in the evaluation of preventive maintenance measures.
Specifically, the analytic hierarchy process is used for obtaining the comprehensive weight of each evaluation factor in the evaluation of preventive maintenance measures, and the calculation process is as follows:
assume that there are m evaluation factors.
1) And comparing every two evaluation factors, and obtaining a every two comparison judgment matrix C according to the every two comparison results, wherein the judgment matrix C is as follows:
wherein, cijTo evaluate the result of the comparison of the importance of factor i to the target and the importance of the ranking factor j to the target, cji＝1/cij. E.g. cij1 indicates that the evaluation factor i is as important as the ranking factor j for the target, cij3 indicates that the evaluation factor i and the ranking factor j are slightly important.
2) Calculating the characteristic vector of the pairwise comparison judgment matrix:
(1) calculating the product M of each row of elements of the judgment matrixi：
Mi＝Πcij(j＝1,2,...m)；
(2) Calculate the m-th square root w of Mii：
(3) For vector wiAnd (3) carrying out normalization treatment:
then W is ═ W1,W2,...,Wm]TThe feature vector is obtained.
3) And (3) carrying out consistency check on the pairwise comparison judgment matrixes:
since the two-by-two comparison judgment matrix cannot guarantee complete consistency, consistency check needs to be carried out on the matrix, and the specific process of the check is as follows:
(1) calculating maximum characteristic root lambda of pairwise comparison judgment matrixmax：
(2) Calculating a consistency index CI:
CI＝(λmax-m)/(m-1)。
wherein CI is 0, there is complete identity; CI is close to 0, and the consistency is satisfactory; the larger the CI value, the greater the degree of deviation of the pairwise comparison determination matrix from complete consistency.
(3) Calculating a matrix consistency judgment index CR: CR is CI/RI.
Considering that the deviation of consistency may be caused by random reasons, when checking whether the judgment matrix has satisfactory consistency, the CR is calculated by comparing CI with the random consistency index RI.
The RI is related to the rank m of the pairwise comparison determination matrix, and may be determined by table lookup, and the corresponding relationship is shown in table 1:
TABLE 1 average random consistency index RI standard value
(4) Determining the consistency of the matrix
When CR is less than 0.1, the two comparison judgment matrixes are considered to have satisfactory consistency, otherwise, the two comparison judgment matrixes need to be adjusted to have satisfactory consistency.
4) And when the two comparison judgment matrixes are judged to have satisfactory consistency according to the check result, taking the feature vector W as a comprehensive weight vector A.
An example is given below, taking preventive maintenance of asphalt pavements as an example:
according to the commonly used preventive maintenance measures of Pudong in Shanghai, a reducing agent seal layer, a fog seal layer, a gravel fog seal layer, a micro-surfacing and a thin-layer cover are selected as preventive maintenance measures, then the implementation effect, the construction difficulty degree, the economic benefit and other aspects of the preventive maintenance measures are comprehensively selected according to the practical engineering experience, and the candidate preventive maintenance measures are determined to be the reducing agent seal layer, the fog seal layer, the slurry seal layer and the micro-surfacing.
Through specific data of investigation, the concentrated manifestation of the road surface diseases of the Pudong road is shown as follows: transverse cracks, longitudinal cracks, ruts, sinkers, and craters.
Firstly, establishing an evaluation factor set as U ═ transverse cracks, longitudinal cracks, ruts, subsidence and pits }, namely: u ═ U1, U2, U3, U4, U5 }.
Establishing an evaluation grade set as follows: v ═ E-valid, M-more valid, N-less recommended, Q-requiring higher technical requirements and quality control, T-invalid }, i.e.: v ═ V1, V2, V3, V4, V5 }.
And constructing a judgment matrix, and carrying out fuzzy judgment on the single factor to obtain fuzzy judgment matrixes corresponding to the fog seal, the reducing agent seal, the slurry seal and the micro-meter in sequence, namely R1, R2, R3 and R4.
The comprehensive weight vector A of each evaluation factor obtained by the analytic hierarchy process in the evaluation of preventive maintenance measures is as follows: a ═ 0.0799,0.1119,0.1865,0.0622,0.05595 }.
Establishing a fuzzy comprehensive evaluation model, carrying out comprehensive evaluation, carrying out fuzzy synthesis and normalization to obtain:
B1＝{0.4172,0.2468,0.1231,0.1949,0.2055}；
B2＝{0.4319,0.2631,0.1615,0.1435,0.2055}；
B3＝{0.4638,0.3600,0.1582,0.018,0.0576}；
B4＝{0.5458,0.2462,0.1138,0.0942,0.0364}。
through fuzzy comprehensive judgment, for example, the maximum membership principle is adopted, and 0.5458 is greater than 0.4638 is greater than 0.4319 is greater than 0.4172, so that the applicability of the micro-surfacing measures is better than that of other preventive maintenance technical measures.
In the embodiment, an analytic hierarchy process and a fuzzy mathematics comprehensive evaluation method are combined with each other and applied to the decision of the pavement preventive maintenance technology. The analytic hierarchy process is a multi-criterion decision-making process combining qualitative analysis and quantitative analysis, and the combination of the analytic hierarchy process and the fuzzy comprehensive judgment process is to divide an evaluation index system into hierarchical structures, determine the weight of each index by using the analytic hierarchy process, and perform fuzzy comprehensive judgment hierarchically, so that the comprehensiveness and the scientificity of the selection of preventive maintenance measures are improved.
In one embodiment of the present invention, as shown in fig. 4, a decision system for a road surface preventive maintenance technology includes:
a candidate measure setting module 100 for determining a plurality of candidate preventive maintenance measures;
an evaluation factor setting module 200 for determining evaluation factors of the preventive maintenance technology;
an evaluation level setting module 300 for determining an evaluation level of the preventive maintenance technique;
a judgment matrix construction module 400, configured to establish a fuzzy judgment matrix for each candidate preventive maintenance measure according to the evaluation factor and the evaluation level;
the comprehensive weight obtaining module 500 is used for obtaining the comprehensive weight of each evaluation factor in the evaluation of preventive maintenance measures;
the comprehensive evaluation module 600 is configured to obtain a fuzzy comprehensive evaluation result of the candidate preventative maintenance measures according to the fuzzy evaluation matrix of the candidate preventative maintenance measures and the comprehensive weight; and selecting the candidate preventive maintenance measure with the highest comprehensive evaluation as the target maintenance measure according to the fuzzy comprehensive evaluation results of all the candidate preventive maintenance measures.
Specifically, the preventive maintenance measures are decided by fuzzy mathematical comprehensive evaluation, and the processing process is as follows:
1) and determining a plurality of candidate preventive maintenance measures according to historical empirical data, and taking each preventive maintenance measure as an evaluation object.
2) Determining an evaluation factor for preventative maintenance techniques
And determining evaluation factors according to the pavement damage condition which can be solved by the preventive maintenance technology. Various evaluation factors constitute an evaluation factor set, such as an evaluation factor set U ═ lateral cracks, longitudinal cracks, deformation, peeling, pits, water damage, rutting }, that is: U-U1, U2, U3, U4, U5, U6, U7.
Optionally, the type of the pavement disease is obtained according to the targeted regional history data. And taking the type of the pavement diseases as evaluation factors of the preventive maintenance technology, and selecting a plurality of evaluation factors to form an evaluation factor set.
3) Determining an evaluation rating for preventative maintenance techniques
And determining the evaluation grade according to various historical evaluation results of the user on the preventive maintenance technology. The various rating levels form a rating level set, e.g., rating level set V ═ { E-valid, M-more valid, N-not recommended, Q-requiring higher technical requirements and quality control, T-invalid }, i.e.: v ═ V1, V2, V3, V4, V5 }.
4) Construction judgment matrix
And starting from a single evaluation factor, performing single-factor fuzzy evaluation on each candidate preventive maintenance technical measure, namely, considering the membership degree of each evaluation object to the evaluation grade set V from a single factor. For example, starting from the single factor ui, the single factor fuzzy evaluation is performed on the evaluation object A to obtain a corresponding single factor evaluation set ri＝(ri1，ri2，…rin)，rijThe evaluation object a is a degree of membership to the evaluation scale Vj (j is 1,2, … n) in view of the single factor ui.
And obtaining a corresponding fuzzy evaluation matrix R according to the single-factor evaluation set of all the evaluation factors of each evaluation object. Thus, each evaluation object determines a fuzzy evaluation matrix R from U to V, namely:
5) determining the comprehensive weight of each evaluation factor in the evaluation of preventive maintenance measures:
there are various methods, such as expert estimation method, in which each expert gives the weight of each evaluation factor independently, and then the average value of the weights of each evaluation factor is taken as the final totalAnd (4) combining the weights. Optionally, an analytic hierarchy process is used to obtain the comprehensive weight of each evaluation factor in the evaluation of preventive maintenance measures. The integrated weight of all the rating factors constitutes an integrated weight vector a ═ ai)1×m＝(a1,a2,...,am) Wherein a isiIs the comprehensive weight of the ith evaluation factor.
6) Establishing a fuzzy comprehensive evaluation model to obtain fuzzy comprehensive evaluation results of each evaluation object, and then carrying out comprehensive evaluation.
The fuzzy comprehensive evaluation model B comprises the following steps:
representing a fuzzy synthesis operator such as a matrix multiplication operation. And synthesizing the comprehensive weight vector A and the fuzzy evaluation matrix R through a proper fuzzy synthesis operator to obtain fuzzy comprehensive evaluation results of all the rating objects.
And analyzing the fuzzy comprehensive evaluation result, for example, adopting a maximum membership principle, obtaining a corresponding comprehensive score according to the fuzzy comprehensive evaluation result of each evaluation object to obtain a comprehensive score of each candidate preventive maintenance measure, and selecting the candidate preventive maintenance measure with the highest comprehensive score as a target maintenance measure.
In the embodiment, the evaluation results of the evaluation objects are obtained by fuzzy comprehensive evaluation of a plurality of evaluation factors, and then the most suitable preventive maintenance measures are determined, so that the one-sidedness of preventive maintenance measure selection is avoided.
In another embodiment of the present invention, as shown in fig. 4 and 5, a decision system for a road surface preventive maintenance technology includes:
a candidate measure setting module 100 for determining a plurality of candidate preventive maintenance measures;
an evaluation factor setting module 200 for determining evaluation factors of the preventive maintenance technology;
an evaluation level setting module 300 for determining an evaluation level of the preventive maintenance technique;
a judgment matrix construction module 400, configured to establish a fuzzy judgment matrix for each candidate preventive maintenance measure according to the evaluation factor and the evaluation level;
the comprehensive weight obtaining module 500 is used for obtaining the comprehensive weight of each evaluation factor in the evaluation of preventive maintenance measures by using an analytic hierarchy process;
the comprehensive evaluation module 600 is configured to obtain a fuzzy comprehensive evaluation result of the candidate preventative maintenance measures according to the fuzzy evaluation matrix of the candidate preventative maintenance measures and the comprehensive weight; and selecting the candidate preventive maintenance measure with the highest comprehensive evaluation as the target maintenance measure according to the fuzzy comprehensive evaluation results of all the candidate preventive maintenance measures.
The comprehensive weight obtaining module 500 further includes:
a comparison and judgment matrix calculation unit 510, configured to obtain a pairwise comparison and judgment matrix by pairwise comparison of each evaluation factor;
a feature vector calculation unit 520, configured to calculate feature vectors of the pairwise comparison determination matrix;
a consistency check unit 530, configured to perform consistency check on the pairwise comparison determination matrices; and when the two comparison judgment matrixes are judged to have satisfactory consistency according to the check result, the characteristic vector is used as the comprehensive weight of each evaluation factor in the evaluation of preventive maintenance measures.
Specifically, the analytic hierarchy process is used for obtaining the comprehensive weight of each evaluation factor in the evaluation of preventive maintenance measures, and the calculation process is as follows:
assume that there are m evaluation factors.
1) And comparing every two evaluation factors, and obtaining a every two comparison judgment matrix C according to the every two comparison results, wherein the judgment matrix C is as follows:
wherein, cijTo evaluate the result of the comparison of the importance of factor i to the target and the importance of the ranking factor j to the target, cji＝1/cij. E.g. cij1 indicates that the evaluation factor i is as important as the ranking factor j for the target, cij3 indicates that the evaluation factor i and the ranking factor j are slightly important.
2) Calculating the characteristic vector of the pairwise comparison judgment matrix:
(2) calculating the product M of each row of elements of the judgment matrixi：
Mi＝Πcij(j＝1,2,...m)；
(2) Calculate the m-th square root w of Mii：
(3) For vector wiAnd (3) carrying out normalization treatment:
then W is ═ W1,W2,...,Wm]TThe feature vector is obtained.
5) And (3) carrying out consistency check on the pairwise comparison judgment matrixes:
since the two-by-two comparison judgment matrix cannot guarantee complete consistency, consistency check needs to be carried out on the matrix, and the specific process of the check is as follows:
(1) calculating maximum characteristic root lambda of pairwise comparison judgment matrixmax：
(2) Calculating a consistency index CI:
CI＝(λmax-m)/(m-1)。
wherein CI is 0, there is complete identity; CI is close to 0, and the consistency is satisfactory; the larger the CI value, the greater the degree of deviation of the pairwise comparison determination matrix from complete consistency.
(3) Calculating a matrix consistency judgment index CR: CR is CI/RI.
Considering that the deviation of consistency may be caused by random reasons, when checking whether the judgment matrix has satisfactory consistency, the CR is calculated by comparing CI with the random consistency index RI. Wherein, RI is related to the order number m of the comparison and judgment matrix of two pairs, and can be determined by looking up a table.
(4) Determining the consistency of the matrix
When CR is less than 0.1, the two comparison judgment matrixes are considered to have satisfactory consistency, otherwise, the two comparison judgment matrixes need to be adjusted to have satisfactory consistency.
6) And when the two comparison judgment matrixes are judged to have satisfactory consistency according to the check result, taking the feature vector W as a comprehensive weight vector A.
An example is given below, taking preventive maintenance of asphalt pavements as an example:
according to the commonly used preventive maintenance measures of Pudong in Shanghai, a reducing agent seal layer, a fog seal layer, a gravel fog seal layer, a micro-surfacing and a thin-layer cover are selected as preventive maintenance measures, then the implementation effect, the construction difficulty degree, the economic benefit and other aspects of the preventive maintenance measures are comprehensively selected according to the practical engineering experience, and the candidate preventive maintenance measures are determined to be the reducing agent seal layer, the fog seal layer, the slurry seal layer and the micro-surfacing.
Through specific data of investigation, the concentrated manifestation of the road surface diseases of the Pudong road is shown as follows: transverse cracks, longitudinal cracks, ruts, sinkers, and craters.
Firstly, establishing an evaluation factor set as U ═ transverse cracks, longitudinal cracks, ruts, subsidence and pits }, namely: u ═ U1, U2, U3, U4, U5 }.
Establishing an evaluation grade set as follows: v ═ E-valid, M-more valid, N-less recommended, Q-requiring higher technical requirements and quality control, T-invalid }, i.e.: v ═ V1, V2, V3, V4, V5 }.
And constructing a judgment matrix, and carrying out fuzzy judgment on the single factor to obtain fuzzy judgment matrixes corresponding to the fog seal, the reducing agent seal, the slurry seal and the micro-meter in sequence, namely R1, R2, R3 and R4.
The comprehensive weight vector A of each evaluation factor obtained by the analytic hierarchy process in the evaluation of preventive maintenance measures is as follows: a ═ 0.0799,0.1119,0.1865,0.0622,0.05595 }.
Establishing a fuzzy comprehensive evaluation model, carrying out comprehensive evaluation, carrying out fuzzy synthesis and normalization to obtain:
B1＝{0.4172,0.2468,0.1231,0.1949,0.2055}；
B2＝{0.4319,0.2631,0.1615,0.1435,0.2055}；
B3＝{0.4638,0.3600,0.1582,0.018,0.0576}；
B4＝{0.5458,0.2462,0.1138,0.0942,0.0364}。
through fuzzy comprehensive judgment, for example, the maximum membership principle is adopted, and 0.5458 is greater than 0.4638 is greater than 0.4319 is greater than 0.4172, so that the applicability of the micro-surfacing measures is better than that of other preventive maintenance technical measures.
In the embodiment, an analytic hierarchy process and a fuzzy mathematics comprehensive evaluation method are combined with each other and applied to the decision of the pavement preventive maintenance technology. The analytic hierarchy process is a multi-criterion decision-making process combining qualitative analysis and quantitative analysis, and the combination of the analytic hierarchy process and the fuzzy comprehensive judgment process is to divide an evaluation index system into hierarchical structures, determine the weight of each index by using the analytic hierarchy process, and perform fuzzy comprehensive judgment hierarchically, so that the comprehensiveness and the scientificity of the selection of preventive maintenance measures are improved.
It should be noted that the above embodiments can be freely combined as necessary. The foregoing is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and decorations can be made without departing from the principle of the present invention, and these modifications and decorations should also be regarded as the protection scope of the present invention.
Claims (10)
1. A decision method for a pavement preventive maintenance technology is characterized by comprising the following steps:
determining a plurality of candidate preventive maintenance measures, and evaluation factors and evaluation grades of preventive maintenance technologies;
establishing a fuzzy evaluation matrix of each candidate preventive maintenance measure according to the evaluation factors and the evaluation grades;
acquiring the comprehensive weight of each evaluation factor in the evaluation of preventive maintenance measures;
obtaining a fuzzy comprehensive evaluation result of the candidate preventive maintenance measures according to the fuzzy evaluation matrix of the candidate preventive maintenance measures and the comprehensive weight;
and selecting the candidate preventive maintenance measure with the highest comprehensive evaluation as the target maintenance measure according to the fuzzy comprehensive evaluation results of all the candidate preventive maintenance measures.
2. The method for deciding on a preventive maintenance technique for a pavement according to claim 1, wherein the determining of the evaluation factors for the preventive maintenance technique comprises:
determining the evaluation factors of the preventive maintenance technology from the following road surface damage conditions which can be solved by the preventive maintenance technology:
transverse cracks, longitudinal cracks, deformation, peeling, pits, water damage, rutting, sinking.
3. The method for deciding on preventive maintenance of a pavement according to claim 1, wherein the obtaining of the comprehensive weight of each evaluation factor in the evaluation of preventive maintenance measures comprises:
and (4) obtaining the comprehensive weight of each evaluation factor in the evaluation of preventive maintenance measures by using an analytic hierarchy process.
4. The decision method for the preventive maintenance technology of the pavement according to claim 3, wherein the comprehensive weight of each evaluation factor in the evaluation of the preventive maintenance measures is obtained by using an analytic hierarchy process, and the method specifically comprises the following steps:
obtaining a pairwise comparison judgment matrix by pairwise comparison of each evaluation factor;
calculating the eigenvectors of the pairwise comparison judgment matrix;
carrying out consistency check on the pairwise comparison judgment matrixes;
and when the two comparison judgment matrixes are judged to have satisfactory consistency according to the check result, the characteristic vector is used as the comprehensive weight of each evaluation factor in the evaluation of preventive maintenance measures.
5. The decision method for the preventive maintenance of a pavement according to claim 4, wherein the calculating the eigenvectors of the pairwise comparison determination matrix comprises:
multiplying the elements of each row in the pairwise comparison judgment matrix to obtain a product value M of each rowi；
Calculating the eigenvector W of the pairwise comparison judgment matrix according to the following formula:
W＝[W1,W2,...,Wm]T，
wherein m is the order of the pairwise comparison judgment matrix.
6. The decision method for the preventive maintenance of a pavement according to claim 5, wherein the consistency check of the pairwise comparison judgment matrix comprises:
calculating the maximum characteristic root of the pairwise comparison judgment matrix;
calculating a matrix consistency judgment index of the pairwise comparison judgment matrix according to the maximum feature root;
and when the matrix consistency judgment index is smaller than a preset threshold, comparing every two matrixes to judge that the matrixes have satisfactory consistency.
7. A decision-making system for preventive maintenance of a pavement, comprising:
the candidate measure setting module is used for determining a plurality of candidate preventive maintenance measures;
the evaluation factor setting module is used for determining evaluation factors of the preventive maintenance technology;
the evaluation grade setting module is used for determining the evaluation grade of the preventive maintenance technology;
the evaluation matrix construction module is used for establishing a fuzzy evaluation matrix of each candidate preventive maintenance measure according to the evaluation factors and the evaluation grades;
the comprehensive weight acquisition module is used for acquiring the comprehensive weight of each evaluation factor in the evaluation of preventive maintenance measures;
the comprehensive evaluation module is used for obtaining a fuzzy comprehensive evaluation result of the candidate preventive maintenance measures according to the fuzzy evaluation matrix of the candidate preventive maintenance measures and the comprehensive weight; and selecting the candidate preventive maintenance measure with the highest comprehensive evaluation as the target maintenance measure according to the fuzzy comprehensive evaluation results of all the candidate preventive maintenance measures.
8. The decision making system for preventive maintenance of a pavement according to claim 7, wherein:
the comprehensive weight obtaining module is further used for obtaining the comprehensive weight of each evaluation factor in the preventive maintenance measure evaluation by using an analytic hierarchy process.
9. The decision making system for preventive maintenance of a pavement according to claim 8, wherein the comprehensive weight obtaining module further comprises:
the comparison and judgment matrix calculation unit is used for obtaining a pairwise comparison and judgment matrix by pairwise comparison of each evaluation factor;
the feature vector calculation unit is used for calculating the feature vectors of the pairwise comparison judgment matrix;
the consistency checking unit is used for carrying out consistency checking on the pairwise comparison judgment matrixes; and when the two comparison judgment matrixes are judged to have satisfactory consistency according to the check result, the characteristic vector is used as the comprehensive weight of each evaluation factor in the evaluation of preventive maintenance measures.
10. The decision making system for preventive maintenance of a pavement according to claim 5, wherein:
the consistency checking unit is further used for calculating the maximum characteristic root of the pairwise comparison judgment matrix; calculating a matrix consistency judgment index of the pairwise comparison judgment matrix according to the maximum feature root; and when the matrix consistency judgment index is smaller than a preset threshold, comparing every two matrixes to judge that the matrixes have satisfactory consistency.
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| CN116596378A (en) * | 2023-05-17 | 2023-08-15 | 安徽建筑大学 | Low-grade rural highway pavement maintenance management decision method, equipment and storage medium |
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