Safety evaluation method for clustering earth and rockfill dams according to items and parts

Abstract

The invention discloses a sub-item and sub-part clustering earth and rockfill dam safety evaluation method. The method comprises the following steps: step 1, constructing a sub-item and sub-part earth and rockfill dam safety evaluation index system; 2, determining subjective and objective index weights of each item and each part; 3, adjusting the weight according to a game theory method to obtain an adjusted combined weight; 4, the historical earth and rockfill dam health level is determined; 5, calculating the membership degree of each index according to the monitoring data; 6, obtaining an evaluation coefficient according to the membership degree, and obtaining an evaluation result through clustering analysis in combination with the health level; in order to solve the problem that the actual guidance of the current dam health evaluation conclusion is not strong, the earth and rockfill dam is refined and itemized according to the difference of the structure sum and damage characteristics, the game theory is adopted to carry out dynamic index system adjustment and modification on subjective and objective weights, the clustering method is adopted to analyze the inter-annual result characteristics, and the evaluation accuracy is improved. And safety evaluation results of different parts and projects are given.

Description

Technical Field

[0001] The invention relates to the technical field of dam safety, and in particular to a clustering earth-rock dam evaluation method based on sub-items and sub-positions. Background Art

[0002] The safety evaluation of earth-rock dams is to give a comprehensive evaluation of the dam's operating performance through the study of the dam's structure and operation, point out the main problems of the dam, and determine the key parts and weak links of the dam's safety. The main methods currently include expert evaluation and risk and comprehensive evaluation.

[0003] Organizing experts to conduct a comprehensive evaluation of dams is currently the most commonly used and reliable method for dam safety evaluation, and regular dam safety inspections every five years are even more necessary. However, this method requires a lot of manpower and material resources, is time-consuming, and is difficult to achieve real-time, dynamic, and process-based evaluation of dam safety, and has certain safety hazards.

[0004] The risk analysis method considers the possibility of dam failure and the superposition of its consequences, including five links: risk identification, risk estimation, risk assessment, risk transfer and risk decision-making. Risk identification is to propose possible dam failure paths through in-depth analysis of the geology of the dam site area and the dam structure; risk estimation is to calculate the probability of dam failure and downstream economic losses, life losses, social and environmental damage, etc.; risk assessment is to superimpose dam failure risks and losses, and then conduct an assessment; risk transfer is a measure to reduce risk losses through consequence transfer; risk decision-making is to propose several feasible risk treatment plans after repeating the above steps. In recent years, the dam risk analysis method has been widely studied and applied in the dam engineering community, but it starts from the possible mode of dam failure and considers the results of risks and losses. Its concept is clear and has strong guidance. However, the calculation includes quantitative and non-quantitative parts, the initial model is complex to establish, and professional institutions are required to perform simulation calculations. It is not easy for ordinary engineers to get started and it is difficult to realize real-time.

[0005] The idea of ​​the comprehensive evaluation method is: determine the evaluation system according to the evaluation purpose and the possibility of quantitative implementation of indicators; determine the weights and membership functions of the indicators; and use the evaluation calculation method to evaluate the target. This method has been widely used in many fields such as water conservancy, civil engineering, mining, and environment due to its clear ideas and clear indicator system. However, it has the following problems: the indicator designation and weight determination in the evaluation method are highly subjective; the boundaries of the deformation indicators during the construction period of earth-rock dams are difficult to determine; the evaluation conclusions are given by scores, and then the safety levels are divided according to the boundaries, which has little guiding significance for the specific engineering. Summary of the invention

[0006] In view of the problems existing in the prior art, the present invention provides an evaluation method for earth-rock dams based on clustering of sub-items and sub-positions.

[0007] The technical solution adopted by the present invention is: a clustering earth-rock dam evaluation method based on sub-items and sub-positions, comprising the following steps:

[0008] Step 1: Construct a safety evaluation index system for earth-rock dams by item and section;

[0009] Step 2: Determine the weights of subjective and objective indicators for each item and department; determine the objective indicator weight ω2 based on monitoring data, and determine the subjective indicator weight ω1 based on preset expert experience;

[0010] Step 3: Adjust the weights according to the game theory method to obtain the adjusted combined weight ω;

[0011] Step 4: Determine the health level of the historical earth-rock dam;

[0012] Step 5: Calculate the degree of membership of each indicator based on the monitoring data;

[0013] Step 6: Obtain the evaluation coefficient based on the membership degree obtained in step 5, and use cluster analysis to obtain the evaluation result in combination with the health level in step 4.

[0014] Furthermore, the safety index evaluation system of the layered earth-rock dam is:

[0015] The safety evaluation set of earth-rock dam is denoted as C = {C1, C2, ..., C n}, C i is the project layer, n is the number of projects; C i ={c i1 , c i2 , …, c im}, where c ij is the jth evaluation index of the i-th layer, and m is the number of indicators;

[0016] The project layer includes flood resistance, structural stability, seepage stability, seismic safety and metal structure; flood resistance includes dam crest height review and downstream flood review; structural stability includes dam slope stability, dam body deformation, impermeable body deformation, other structural deformation, contact deformation, and bank slope near the dam; seepage stability includes seepage pressure, seepage gradient, seepage volume and seepage water quality; seismic safety includes dam seismic safety factor and soil liquefaction possibility; metal structure includes the working condition of steel gates and hoist.

[0017] Furthermore, the calculation method of the combined weight is as follows:

[0018] ω=δ k ω1+(1-δ k )ω2

[0019] Among them, δ k is the weight allocation coefficient of objective weight and subjective weight, δ kDetermined based on game theory methods.

[0020] Furthermore, the subjective indicator weight ω1 and the objective indicator weight ω2 are determined according to the entropy weight method.

[0021] Furthermore, the evaluation coefficient calculation process is as follows:

[0022] Calculation project layer C i Membership degree x i :

[0023]

[0024] Where: x ij The indicator c ij The corresponding membership degree, ω ij The indicator c ij The corresponding weights;

[0025] Evaluation coefficient T1 is

[0026]

[0027] Where: δT is the adjustment coefficient, which is determined according to the safety evaluation index of earth-rock dam.

[0028] Furthermore, in step 6, the inter-annual correlation of the earth-rock dam safety evaluation index is obtained according to the clustering method, and the inter-annual correlation is combined with the evaluation coefficient T1 to determine the evaluation result.

[0029] Furthermore, the inter-annual correlation of the earth-rock dam safety evaluation index is obtained, and the process of determining the evaluation result by combining the inter-annual correlation with the evaluation coefficient T1 is as follows:

[0030] Calculate the membership degree of the safety evaluation index in year a, and establish the original data matrix T based on the calculated membership degree;

[0031] Normalize the original data matrix and construct the fuzzy judgment matrix R;

[0032] According to the fuzzy judgment matrix, the data between different years are calculated by the quantitative product method to obtain the similarity λ between different years;

[0033] The similarity λ is compared with a preset threshold, and if the similarity exceeds the threshold, it is determined that there is a turning point in that year;

[0034] Obtain the membership degree of each safety evaluation index in that year, and determine whether it is dangerous based on the membership degree.

[0035] The beneficial effects of the present invention are:

[0036] (1) The present invention establishes an evaluation system according to the failure modes of earth-rock dams, which is in line with the actual situation;

[0037] (2) The present invention addresses the problem of strong subjectivity in indicator designation and weight determination in existing comprehensive evaluation methods, and adopts game theory to dynamically adjust and modify the weights;

[0038] (3) The present invention uses a clustering method to cluster the results between years and gives a safety evaluation result based on a comprehensive subjective and objective conclusion. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 It is a schematic diagram of the process of the present invention.

[0040] Figure 2 It is a schematic diagram of the safety evaluation index system of layered earth-rock dam in the present invention. DETAILED DESCRIPTION

[0041] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0042] like Figure 1 As shown, a clustering earth-rock dam evaluation method based on sub-items and sub-locations includes the following steps:

[0043] Step 1: Construct a safety evaluation index system for earth-rock dams by item and location;

[0044] According to the existing specifications and failure modes of earth-rock dams, a comprehensive health diagnosis and evaluation system for the safety of high earth-rock dams is constructed from different parts such as the dam crest, wave-breaking wall, water-facing slope protection, water surface near the dam, water-retaining slope protection, drainage system, dam foundation, and dam shoulders on both sides according to sub-items such as flood resistance, structural stability, seepage stability, seismic safety, and metal structure, namely, the layered earth-rock dam safety indicator evaluation system of the present invention.

[0045] Safety index evaluation system for layered earth-rock dams Figure 2 Shown are:

[0046] The earth-rock dam safety assessment set is denoted as C i ={c i1 , c i2 , …, c im}, C i is the project layer, n is the number of projects; C i ={c i1 , c i2 , …, c im}, where c ij is the jth evaluation index of the i-th layer, and m is the number of indicators;

[0047] The project layer includes flood resistance, structural stability, seepage stability, seismic safety and metal structure. Flood resistance includes two indicators: dam crest height review and downstream flood review; structural stability includes the following indicators: dam slope stability, dam body deformation, impermeable body deformation, other structural deformation, contact deformation, and bank slope near the dam. Seepage stability includes the following indicators: seepage pressure, seepage gradient, seepage volume and seepage water quality; seismic safety includes the following indicators: dam seismic safety factor and soil liquefaction possibility; metal structure includes the working condition of steel gates and hoist.

[0048] Step 2: Determine the weights of subjective and objective indicators for each item and each part; determine the objective indicator weight ω2 based on the monitoring data, and determine the subjective indicator weight ω1 based on the preset expert experience;

[0049] Subjective weights are obtained using existing preset empirical values. Generally, experts are invited to obtain all indicator weight libraries based on their own experience according to various situations, and empirical values ​​are obtained according to the situation. The specific determination process is as follows:

[0050] Establish an evaluation table for indicators and projects, issue expert scores, and obtain project and indicator weights. ij (c i ),c ik (c j ) are compared pairwise to obtain their relative importance value α ijk (α ij ), forming a weight judgment matrix A = (α ijk ) m×m Or A=(α ij ) n×n The obtained importance indices are shown in Table 1.

[0051] Table 1. Importance score comparison table

[0052]

[0053] According to the weight judgment matrix A, the maximum eigenvalue λ of the judgment matrix is ​​obtained max , according to the characteristic equation AW = λ max W is calculated to get the eigenvector W, and the indicator weight can be obtained after normalizing the eigenvector.

[0054] The calculated indicator weights are checked for consistency, and the function for judging the consistency of the matrix is ​​as follows:

[0055]

[0056] When R=0, the matrix is ​​consistent. The larger the R value is, the higher the inconsistency of the judgment matrix A is.

[0057] Using sub-samples, the critical values ​​of R obtained for different n were selected, and the results are shown in Table 2.

[0058] Table 2. Critical value selection

[0059]

[0060] The objective indicator weight ω2 is determined according to the entropy weight method, and the process is as follows:

[0061] The average amount of information after excluding redundancy is called "information entropy". According to the information entropy theory, the index c ij The information entropy of is calculated as follows:

[0062]

[0063] Divide the information into n intervals and calculate the index c based on K intervals ij The membership degree is denoted as C ijk . By information entropy E ij The evaluation index c ij The entropy weight calculation process is as follows:

[0064]

[0065] Step 3: Adjust the weights according to the game theory method to obtain the adjusted combined weight ω;

[0066] ω=δ k ω1+(1-δ k )ω2

[0067] Among them, δ k is the weight allocation coefficient of objective weight and subjective weight, δ k Determined based on game theory methods.

[0068] Comprehensive safety evaluation index system for high earth-rock dams For example, when the monitoring data of a certain part changes little and the trend is stable, it means that the structural safety here is good. At this time, the ω2 obtained through the monitoring data is small and the change is stable, so the attention is small. k The subjective importance of the structure itself is mainly assigned; when the monitored value fluctuates or even rises significantly, ω2 is large and the change is stable, it means that the structure is unstable and needs to be paid more attention to. At this time, more attention should be paid to the objective weight. The traditional method mainly uses artificial assignment to balance the subjective and objective weights. This method introduces game theory to calculate δ k To adjust the ratio between subjective and objective.

[0069] Game theory is a powerful tool for solving competitive problems between things. It can be used to analyze the rational behavior of multiple decision-making entities and their decision-making equilibrium when their behaviors influence each other. The basic idea of ​​using game theory to adjust weights according to the changes in subjective and objective sequences is to seek the equilibrium point between the results of different weight solutions, so that the sum of the deviations between the combined weight and the results of various weight solutions is minimized, thereby screening out the optimal combined weight.

[0070] Assuming that there are a total of r methods for solving weights, the number of evaluation indicators is m, and the corresponding weight vector construction method, the constructed minimum deviation optimization model is shown in the following formula. The model integrates the weight information of various weighting methods and can realize the unification of subjective and objective weighting methods.

[0071]

[0072] The above model is solved by the Lagrangian function, which is as follows:

[0073]

[0074] Among them: λ is the introduced parameter, respectively Taking the derivatives of each component with λ, we can simplify it to get:

[0075]

[0076] The above formula contains an r+1-dimensional linear equation system with unknown variables. Its coefficient determinant is not equal to zero, indicating that it has a unique solution. The solution vector is the weight distribution coefficient of each weighting method. The final combined weight value can be obtained by weighting with the indicator weights obtained by various weighting methods. The basic weighting method used is to calculate the objective weights of indicators at each level based on monitoring data and determine the subjective weights of each level based on expert opinions, so r=2.

[0077] Step 4: Determine the health grade of earth-rock dam based on the experience of large dam evaluation and regular inspection results;

[0078] According to the "Regulations on the Safety Management of Dam Operation of Hydropower Stations", the dam safety level is divided into three levels: normal dam, sick dam and dangerous dam. As shown in Table 3:

[0079] Table 3. Table of dam safety levels classified according to the regulations on dam operation safety management of hydropower stations

[0080]

[0081]

[0082] The intervals specified in the present invention are:

[0083] N = {[1, 0.8], (0.8, 0.6], (0.6, 0]} = {normal dam (class 1 dam), sick dam (class 2 dam), dangerous dam (class 3 dam)}

[0084] Where N is the classification of earth-rock dams. For high earth-rock dams, key indicators are important for dam safety. According to the calculation mode of the indicator system, it is easy to overwhelm the influence of a single indicator. For this reason, the key indicators of stability and seepage damage indicators are determined. When the indicator is 0, the global adjustment coefficient δT is introduced as 0.6. When a certain indicator is in the warning range, the adjustment coefficient δT is 0.8, and the remaining adjustment coefficients δT are 1, corresponding to the dam level. The adjustment coefficients here are used to calculate the evaluation coefficients. Here, the indicators in step 1 are quantified and then judged. The quantification method is the existing method.

[0085] Step 5: Calculate the degree of membership of each indicator based on the monitoring data;

[0086] The degree of membership is calculated based on the project level and specific safety evaluation indicators.

[0087] (1) Flood resistance

[0088] The flood control capacity is to review the design flood and calculate the flood control based on the hydrological data during the operation period, and evaluate whether the dam's flood control capacity meets the existing standards and flood control requirements. The main indicators include elevation review indicators and downstream flood review indicators.

[0089] The membership function of the elevation review index is:

[0090]

[0091] Where: h 实 is the actual dam crest elevation, h 规 It is the dam crest elevation required by current specifications.

[0092] Flood discharge capacity membership:

[0093]

[0094] Where: Q 泄 To calculate the maximum possible discharge of the dam, Q 允 The maximum discharge flow allowed downstream.

[0095] (2) Stable structure

[0096] The purpose of structural safety assessment is to review whether the deformation, strength and stability of the dam (including the reservoir bank near the dam) under static conditions meet the requirements according to the current national standards.

[0097] 1) Anti-slip and stable

[0098] The membership degree of anti-sliding stability is:

[0099]

[0100] Where: K is the dam slope stability safety factor calculated based on the measured pressure, K A , K C is the dam slope stability threshold, determined according to current specifications.

[0101] 2) Dam deformation

[0102] The membership degree of the deformed evaluation is:

[0103]

[0104] Where: s is the measured value of deformation, s a 、s c is the deformation threshold.

[0105] According to the regulations, the maximum settlement of the earth-rock dam crest after completion shall not exceed 1% of the dam height. This value can be used as the upper critical value, and the lower critical value can be included in a certain redundancy. The present invention initially proposes to multiply the upper limit allowable value by a reduction factor of 0.9, which can be appropriately adjusted for different projects.

[0106] There is no specific control standard for deformation during construction. The existing technology has obtained an empirical relationship between the settlement S and the dam height H after the rockfill dam project tends to stabilize:

[0107]

[0108] Where: S is the settlement and H is the dam height.

[0109] Assuming that the rockfill body has completely completed the deformation caused by its own weight during the construction period, the diffusion of water pressure in the dam is linear, and the stress and deformation are in a linear relationship, the vertical deformation prediction formula of the rockfill dam is:

[0110] S=0.0001245H 2

[0111] The above-mentioned rockfill dam deformation prediction formula is mainly aimed at vertical deformation, and does not include estimation methods for several other deformations. To this end, the present invention adopts numerical simulation combined with engineering statistics to establish a prediction formula for the maximum deformation of the dam surface during the construction period of the earth-rock dam. The three-dimensional finite element numerical simulation scheme is shown in Table 4:

[0112] Table 4. Three-dimensional finite element numerical simulation of earth-rock dam deformation

[0113]

[0114]

[0115] The soil constitutive model adopts the Duncan-Zhang EB model, and the material parameters are shown in Table 5.

[0116] Table 5. Material parameters of three-dimensional finite element numerical simulation scheme for earth-rock dam deformation

[0117]

[0118]

[0119] According to the above-mentioned multi-scheme numerical simulation and deformation monitoring results of several high core rockfill dams, the following empirical formula for calculating the maximum deformation of the dam surface is obtained through statistical fitting of the maximum deformation of the dam surface:

[0120] Maximum vertical deformation of dam surface:

[0121] y=215.94+2.859H+1.706H d

[0122] The maximum downstream horizontal deformation of the dam surface is:

[0123] y=48.852+1.465H+0.362H d

[0124] Maximum axial horizontal deformation of the dam surface:

[0125] y=±(-7.934+1.08H+0.431H d )

[0126] 3) Deformation of the impermeable body

[0127] For the soil core wall, the membership function can be established by considering its arch effect. The calculation formula is:

[0128]

[0129] Where: G is the arch effect coefficient, σ is the measured soil pressure, γ is the soil bulk density, and h is the dam height.

[0130] The foundation anti-seepage wall is mostly made of concrete anti-seepage wall, and the membership function can be established according to the strength:

[0131]

[0132] Where: T is the actual strength measured by the steel bar meter or stress gauge, T c is the strength danger threshold, initially proposed to be the strength value multiplied by a reduction factor of 0.9, T a is the allowable strength value of the material.

[0133] 4) Other structural deformation

[0134] Other structures of earth-rock dams mainly include observation corridors, water diversion and flood discharge facilities, etc. These structures are mostly made of concrete materials and are equipped with steel bar gauges and strain gauges. Their membership functions can be established through strength standards, and the calculation method is such as C23.

[0135] 5) Contact deformation

[0136] Contact deformation is determined by analyzing whether there is abnormal deformation and whether the deformation trend converges. Its membership function is:

[0137]

[0138] Where: n 异 To determine the confidence level of abnormal deformation and trend judgment, abnormal deformation is identified using the structural anomaly recognition method, and deformation trend is identified using the first-order and second-order derivatives.

[0139] 6) Slope deformation near the dam

[0140] The safety of the bank slope near the dam area can be calculated by calculating the corresponding index membership through slope stability calculation and slope deformation rate. The slope stability membership is the same as the dam stability membership. The slope deformation rate membership function is:

[0141]

[0142] Where: c is the deformation rate monitored by the multi-point displacement meter, c a is the empirical allowable value of deformation rate, determined based on experience.

[0143] The rock slope construction period is 1mm / d, the operation period is 0.5mm / d, the soil slope construction period is 5mm / d, the operation period is 1mm / d; c c In order to consider the critical value of redundant deformation, it is initially proposed to multiply the allowable value by a reduction factor of 0.9.

[0144] (3) Stable seepage

[0145] The purpose of seepage stability evaluation is to verify whether the seepage control measures originally designed and constructed and the current actual seepage status can ensure the safe operation of the dam according to the design conditions.

[0146] 1) Seepage pressure

[0147] The penetration pressure can be compared with the design value to establish the membership function:

[0148]

[0149] Where: P 实 is the measured osmotic pressure value, P 设 is the seepage design value.

[0150] 2) Infiltration slope

[0151] The membership of the seepage slope is determined by comparing the calculated value of the seepage measurement point with the allowable seepage slope of the soil:

[0152]

[0153] Where: i is the infiltration slope, i a To allow for infiltration slope; i c In order to consider the critical value of the seepage slope with redundancy, it is initially proposed to multiply the allowable value by a reduction factor of 0.95.

[0154] 3) Seepage

[0155] The seepage rate membership function can be established by comparing the monitored value with the design value:

[0156]

[0157] Where: Q is the seepage volume of the dam, Q a is the design seepage rate, Q c In order to consider the critical value of redundant seepage, it is initially proposed to multiply the allowable value by a reduction factor of 0.9.

[0158] 4) Water quality

[0159] Water quality is mainly determined through manual inspections and experiments, and qualitative conclusions are drawn:

[0160]

[0161] (4) Earthquake resistance and stability

[0162] The purpose of the seismic safety review of earth-rock dams is to review whether the current status of the dam project meets the seismic requirements according to the current specifications. The objects of the seismic safety review include permanent water retaining structures and water discharge and water delivery structures related to dam safety, as well as foundations and reservoir banks near the dam.

[0163] 1) Dam seismic safety

[0164] The dam slope stability can be obtained by using the quasi-static method or finite element dynamic calculation considering earthquake acceleration, and the membership function is the same as that of the dam slope stability.

[0165] 2) Soil liquefaction safety

[0166] Soil liquefaction is determined by soil type, standard penetration test, relative density, soil property index, dynamic triaxial test, dynamic shear strength, etc. The membership function can be determined based on the standard penetration test:

[0167]

[0168] Where: N is the standard penetration point d below the ground during engineering applications Number of penetration blows at depth, N cr The standard number of penetration hammer blows for determining liquefaction.

[0169] (5) Metal structure

[0170] The purpose of metal structure safety assessment is to verify whether the steel gates, hoists and pressure pipes of the reservoir dam discharge and water delivery structures can operate safely according to the design conditions under the current situation.

[0171] 1) Working condition of steel gate

[0172] The steel gate is mainly checked to see whether its strength and rigidity meet the requirements. Its membership function is calculated in the same way as the evaluation coefficient T1.

[0173] 2) Working condition of gate hoist

[0174] The working condition of the gate hoist mainly analyzes whether the gate hoist's opening and closing capacity meets the requirements. Its membership function is:

[0175]

[0176] In the formula: q is the opening and closing capacity of the gate hoist, and L is the opening and closing load.

[0177] Another review of the gate hoist is to evaluate whether it can ensure the normal opening and closing of the equipment in an emergency. This is evaluated by engineers and experts.

[0178] Step 6: Obtain the evaluation coefficient based on the membership degree obtained in step 5, and obtain the evaluation result in combination with the health level in step 4.

[0179] The evaluation coefficient calculation process is as follows:

[0180] Calculation project layer C i Membership degree x i :

[0181]

[0182] Where: x ij The indicator c ij The corresponding membership degree, ω ij The indicator c ij The corresponding weights;

[0183] Evaluation coefficient T1 is

[0184]

[0185] Where: δT is the adjustment coefficient, which is determined according to the safety evaluation index of earth-rock dam.

[0186] In order to make the evaluation more accurate, the clustering method is used to obtain the inter-annual correlation of the earth-rock dam safety evaluation index. The inter-annual correlation is combined with the evaluation coefficient T1 to determine the evaluation result. The process is as follows:

[0187] Set up earth-rock dam safety assessment project layer c i The indicator c ij The membership degree in year a is X ija , abbreviated as x ja , establish the original data matrix T;

[0188]

[0189] The original data matrix is ​​normalized by translation and extreme value transformation to construct the fuzzy judgment matrix R; different years are compared, and the number product method is used to calculate the similarity τ between different years ij =F(x i ,x j ); F is the similarity discriminant function, where x i is a row vector in T, x j is the column vector in T, calculated using the Euclidean distance method:

[0190] τ ij =1-βd(x i ,x j )

[0191] Among them, β is a parameter, d is a distance, and the calculation process is as follows:

[0192]

[0193] The fuzzy similarity matrix established above is not necessarily transitive. Generally, the transitive closure method is used to transform the matrix to generate the final fuzzy equivalent matrix, and then the clustering relationship over time is judged according to the distance λ. Where λ = τ ij .

[0194] The similarity λ is compared with a preset threshold, and if the similarity exceeds the threshold, it is determined that there is a turning point in that year;

[0195] Obtain the membership degree of each safety evaluation index in that year, and determine whether it is dangerous based on the membership degree.

[0196] The present invention will be further described below in conjunction with specific embodiments.

[0197] According to a specific project, judge according to the above method.

[0198] Step 1: Construct a safety evaluation index system for earth-rock dams by item and location;

[0199] Step 2: Determine the weights of subjective and objective indicators for each item and each part; determine the objective indicator weight ω2 based on the monitoring data, and determine the subjective indicator weight ω1 based on the preset expert experience;

[0200] Step 3: Adjust the weights according to the game theory method to obtain the adjusted combined weight ω;

[0201] The subjective weight, objective weight, and comprehensive weight after adjustment by game theory are shown in Table 6. In the subjective weight, the proportion of anti-sliding stability (C21), dam deformation (C22), and anti-seepage body deformation (C23) is relatively high, which are 0.22, 0.29, and 0.13 respectively. The proportion of deformation of other dam auxiliary structures (C24) is relatively small, which is 0.15. In the objective weight, since the calculated membership of dam slope stability has not changed significantly in 4 years, the weight value is relatively small, which is 0.13. However, due to the large change in the membership of the auxiliary structure, the weight is relatively large, which is 0.19. Through calculation, it can be seen that information entropy can reflect the activity of indicators. When some indicators become less active, the weight becomes smaller, and vice versa, it increases, which can be used as a beneficial balance of traditional weights.

[0202] Table 6. Subjective and objective weight table

[0203]

[0204] Step 4: Determine the health grade of earth-rock dam based on the empirical coefficient of dam evaluation;

[0205] Step 5: Calculate the membership of each indicator based on the monitoring data; the present invention calculates the membership results from 2010 to 2013, where the indicator determination process is shown in Table 7, and the calculated membership is shown in Table 8. For indicators such as seepage and deformation, the abnormality of a single measuring point cannot fully reflect the problem of the entire indicator. The following method is used to calculate multiple indicators:

[0206]

[0207] Where: ∑C ij C ij s is the degree of membership, and s is the instrument failure rate.

[0208] Table 7. Safety index membership calculation table

[0209]

[0210]

[0211] Table 8. Safety index membership calculation table

[0212]

[0213]

[0214] Step 6: Obtain the evaluation coefficient based on the membership degree obtained in step 5, and obtain the evaluation result in combination with the health level in step 4.

[0215] According to the comprehensive evaluation method, the scores from 2010 to 2014 were 0.975, 0.972, 0.981, and 0.984. The dam was in good condition and was a normal dam or a Class I dam. The scores continued to increase over time, and the clustering results were obtained. The similarity of dam safety in 2010 and 2011 was 0.96; the similarity between 2012 and 2013 was 0.94, and the overall similarity was 0.81, indicating that the safety conditions in 2010 and 2011 were basically similar, and the safety conditions in 2012 and 2013 were basically similar. The reasons were analyzed as follows: the flood control index, seismic stability index, and metal structure index of the dam all met the requirements, with a membership degree of 1. Some measured values ​​of seepage pressure were high, but there were no major abnormalities. Therefore, the clustering results were mainly affected by the structural stability index C. 22 , C 24 , C 25 In the observation corridor stress, cracks appeared in the corridor after 2008, and the stress exceeded the standard. Before 2011, the change rate was large, 0.02MPa / d. After 2011, the change value decreased to 0.01MPa / d, and it has been basically stable so far. This has caused C 24 The indicators before and after 2011 are quite different. The deformation of the dam body and the contact deformation also change greatly during the construction period and the water storage period, and change steadily during the operation period. Therefore, 2011 can be used as a change segment boundary, which is consistent with the cluster analysis structure. From the above evaluation, it can be concluded that the core wall dam belongs to a normal dam or a Class I dam, with overall stable operation and improved safety over time. After 2011, the indicators are more normal.

[0216] Assuming that the anti-sliding stability index in 2010 is reduced to 0, it is obviously a dangerous dam or a Class III dam according to the specification. The calculation result obtained by the traditional method is 0.942, and the result obtained by the method of the present invention is 0.565, which is more in line with reality.

[0217] Compared with the traditional evaluation method, the method proposed in the present invention establishes an evaluation system according to the failure mode of earth-rock dams by item and part. The index system of the present invention is determined according to the historical experience of earth-rock dam accidents, dam failure modes and relevant specifications. Common failure modes of earth-rock dams mainly include dam slope instability, core wall splitting, dam body and foundation seepage damage, dam overflow, etc. The paths of these dam failures are often manifested as local problems gradually expanding and leading to overall failure. For example, local leakage may cause overall seepage damage in a certain part. At the same time, the patent adopts a part-by-part and part-by-item index system to more accurately capture the potential safety hazards of each part, and establish a cluster diagnosis method to continuously and qualitatively evaluate the development process of hazards. With this index system, through the push of point-line-surface-body, we can see the big picture from the small, identify risks early, and avoid evaluation blind spots.

[0218] In view of the strong subjectivity of indicator formulation and weight determination in the comprehensive evaluation method, the present invention adopts game theory to dynamically adjust and modify the weights, and objectively assigns values ​​according to interannual changes. For example, if the objective continuous changes are large, it means that the objective information is active. Game theory will increase the importance of the objective, which is in line with general understanding. At the same time, in view of the buried situation of membership information, the key indicators are adjusted globally, and finally the results are clustered by clustering ideas, and the safety diagnosis results are given by combining subjective and objective conclusions.

Claims

1. A clustering earth-rock dam safety assessment method based on sub-items and sub-parts, characterized in that: The following steps are involved: Step 1: Construct a safety evaluation index system for earth-rock dams by item and section; Step 2: Determine the weights of subjective and objective indicators for each item and department; determine the objective indicator weight ω2 based on monitoring data, and determine the subjective indicator weight ω1 based on preset expert experience; Step 3: Adjust the weights according to the game theory method to obtain the adjusted combined weight ω; Step 4: Determine the health level of the historical earth-rock dam; Step 5: Calculate the degree of membership of each indicator based on the monitoring data; Step 6: Obtain the evaluation coefficient based on the membership degree obtained in step 5, and use cluster analysis to obtain the evaluation result in combination with the health level in step 4.

2. The clustering earth-rock dam evaluation method based on sub-items and sub-locations according to claim 1 is characterized in that: The safety index evaluation system of layered earth-rock dam is as follows: The safety evaluation set of earth-rock dam is denoted as C = {C1, C2, ..., C n }, C i is the project layer, n is the number of projects; C i ={c i1 , c i2 , …, c im }, where c ij is the jth evaluation index of the i-th layer, and m is the number of indicators; The project layer includes flood resistance, structural stability, seepage stability, seismic safety and metal structure; flood resistance includes dam crest height review and downstream flood review; structural stability includes dam slope stability, dam body deformation, impermeable body deformation, other structural deformation, contact deformation, and bank slope near the dam; seepage stability includes seepage pressure, seepage gradient, seepage volume and seepage water quality; seismic safety includes dam seismic safety factor and soil liquefaction possibility; metal structure includes the working condition of steel gates and hoist.

3. The method for safety assessment of earth-rock dams based on improved weighting based on game theory according to claim 2 is characterized in that: The calculation method of the combined weight is as follows: ω=d k ω1+(1-δ k )ω2 Among them, δ k is the weight allocation coefficient of objective weight and subjective weight, δ k Determined based on game theory methods.

4. The clustering earth-rock dam evaluation method based on sub-items and sub-locations according to claim 3 is characterized in that: The subjective indicator weight ω1 and the objective indicator weight ω2 are determined according to the entropy weight method.

5. The clustering earth-rock dam evaluation method based on sub-items and sub-locations according to claim 2 is characterized in that: The evaluation coefficient calculation process is as follows: Calculation project layer C i Membership degree x i ; Where: x ij The indicator c ij The corresponding membership degree, ω ij The indicator c ij The corresponding weights; Evaluation coefficient T1 is Where: δT is the adjustment coefficient, which is determined according to the safety evaluation index of earth-rock dam.

6. The clustering earth-rock dam evaluation method based on sub-items and sub-locations according to claim 5 is characterized in that: In step 6, the inter-annual correlation of the earth-rock dam safety evaluation index is obtained according to the clustering method, and the inter-annual correlation is combined with the evaluation coefficient T1 to determine the evaluation result.

7. The clustering earth-rock dam evaluation method based on sub-items and sub-locations according to claim 6 is characterized in that: The process of obtaining the inter-annual correlation of the earth-rock dam safety evaluation index and determining the evaluation result by combining the inter-annual correlation with the evaluation coefficient T1 is as follows: Calculate the membership degree of the safety evaluation index in year a, and establish the original data matrix T based on the calculated membership degree; Normalize the original data matrix and construct the fuzzy judgment matrix R; According to the fuzzy judgment matrix, the data between different years are calculated by the quantitative product method to obtain the similarity λ between different years; The similarity λ is compared with a preset threshold, and if the similarity exceeds the threshold, it is determined that there is a turning point in that year; Obtain the membership degree of each safety evaluation index in that year, and determine whether it is dangerous based on the membership degree.

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