A Reservoir Water Leakage Detection Method Based on Interval Membership

Abstract

This invention discloses a reservoir water leakage detection method based on interval membership. The lower limit c of the leakage point with respect to the i-th index interval is calculated respectively. i L and upper limit c i U Regarding the membership degree r of the j-th evaluation level ij L and r ij U Substitute the interval numbers of the hydrochemical indicators at the seepage point into the corresponding membership function formula to calculate the membership degree interval evaluation level vector for each hydrochemical indicator at the seepage point. Combine the membership interval evaluation level vectors of multiple indicators to form an interval number evaluation matrix R. Based on matrix R, calculate the integrated relationship membership degree evaluation result of the seepage point with respect to groundwater, reservoir water, and mixed water levels. When the result is -1... j U When b ≤ 0, the seepage point and the grade show an opposing relationship, and the seepage point is judged not to belong to this grade; when b j L <0 j U At that time, the seepage point and the level of that grade have both similarities and differences; when b j L When the value is greater than 0, the seepage point is determined to belong to that category. This invention is highly reliable, yields accurate conclusions, and saves manpower and resources.​​

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of water conservancy and hydropower engineering, and particularly relates to a reservoir water leakage discrimination method based on interval membership. BACKGROUND

[0002] Many existing reservoirs in China have reservoir water leakage problems to varying degrees, reservoir water leakage not only causes safety hazards in power station operation, but also wastes water resources, so finding out the leakage channel of reservoir water becomes a very important work. At present, the methods for discriminating reservoir water leakage mainly include conventional seepage research methods, temperature tracing methods, environmental isotope and water chemical tracing methods, artificial tracing methods and geophysical exploration methods. Although there are many methods for finding out the leakage channel at present, the above-mentioned methods have the disadvantage of large consumption of manpower and material resources in practical application. SUMMARY

[0003] The application aims to provide a reservoir water leakage discrimination method based on interval membership. The application has strong reliability, high accuracy of conclusion and saves manpower and material resources.

[0004] The technical scheme of the application is as follows: a reservoir water leakage discrimination method based on interval membership, according to the water chemical test results of samples, interval membership in fuzzy comprehensive evaluation method is applied to discriminate reservoir water leakage, including the following steps:

[0005] (1) For reservoir leakage, whether the seepage point is reservoir water leakage, there are three relationships of identity, difference and opposition, set A=(a1, a2, …, am) as m evaluation indexes affecting the evaluation of reservoir water leakage, the state of reservoir water leakage has V=(v1, v2, …, vn) a total of n evaluation grades; set the index value a m i of the seepage point about the i-th index a n i=[a i i i L ,a i U ];first, calculate the interval lower limit c i L and the upper limit c i U of the seepage point about the i-th index respectively, the connection membership r ij L and r ij U about the j-th evaluation grade, the calculation formula is as follows:

[0006]

[0007] In the formula, r ij is the connection membership, r ij∈ [-1, 1] represents the lower limit and upper limit of the index interval of the water seepage point with respect to the water chemical index, which includes the ion concentration of Cl - , Ca 2+ , SO4 2- , and the pH value of the water sample; x is the water chemical index of the water seepage point; M k-1 , M k , M k+1 , M k+2 are the water chemical index limits divided according to the evaluation grades of groundwater, reservoir water, and mixed water;

[0008] (2) The interval number of the water chemical index of the water seepage point is substituted into the corresponding membership function formula, i.e. formula (1), to calculate the membership interval evaluation grade vector of each water chemical index of the water seepage point. The membership interval evaluation grade vectors of multiple indexes are integrated to form an interval number judgment matrix R as follows:

[0009]

[0010] (3) After calculating the interval number judgment matrix R, the integrated contact membership evaluation result of the water seepage point with respect to the grades of groundwater, reservoir water, and mixed water is calculated by the following formula:

[0011]

[0012] In the formula, b j U represents the upper limit of the interval membership evaluation result interval, b j L represents the lower limit of the interval membership evaluation result interval, and j = 1, 2, …, m.

[0013] According to the concept of contact membership, the evaluation method can be determined as follows: when -1 < b j U ≤ 0, the water seepage point and the grade show opposite relationship, and it is determined that the water seepage point does not belong to the grade; when b j L < 0 < b j U < 0, the water seepage point and the grade show both same and different relationship; and when b j L > 0, the water seepage point and the grade show same relationship, and it is determined that the water seepage point belongs to the grade.

[0014] In step (3) of the aforementioned reservoir water leakage discrimination method based on interval membership, the interval membership with same relationship in the evaluation result interval is compared according to the maximum membership principle, and the greater the value is, the greater the fitting degree with the grade is.

[0015] In the aforementioned reservoir water leakage discrimination method based on interval membership degree, the water chemical test of the sample is specifically as follows:

[0016] Reservoir seepage points, underground water and reservoir water are collected respectively as water samples; water chemical determination is carried out on the water samples, including determination of ion concentrations of Cl - , Ca 2+ and SO4 2- in the water samples and pH value.

[0017] In the aforementioned reservoir water leakage discrimination method based on interval membership degree, the ion concentrations of Cl - and SO4 2- are determined by ion chromatography.

[0018] In the aforementioned reservoir water leakage discrimination method based on interval membership degree, the ion concentration of Ca 2+ is determined by EDTA titration.

[0019] In the aforementioned reservoir water leakage discrimination method based on interval membership degree, the pH value is determined by a Lei magnet table-type acidity meter.

[0020] In the aforementioned reservoir water leakage discrimination method based on interval membership degree, the determination error of the water sample is within ±5.0%.

[0021] Beneficial effects

[0022] Compared with the prior art, the water chemical tracing method is combined with the fuzzy comprehensive evaluation method, and finally a reservoir water leakage discrimination method is obtained; through water chemistry, atmospheric precipitation, reservoir water and underground water can be traced, and then through analysis of water chemical components of seepage water, underground water and reservoir water, it can be determined whether the seepage water is reservoir water or underground water or mixed water of the two, and the position and range of the seepage can be determined. In the application, water chemical [(Cl - , Ca 2+ , SO4 2- ) ion concentration, pH value] data are used as background data; Cl - in water has stable properties and is used as a conservative geochemical tracer; SO4 2- value reflects anion evolution process and component distribution ratio change; Ca 2+ represents contribution of carbonates to water body; and pH value represents the degree of strength of water acid-base and is a chemical property of water. Through water chemistry [(Cl - , Ca 2+ , SO4 2-) ion concentration, pH value] data distinguish whether the leakage water is closely related to the reservoir water, so as to analyze whether the leakage water is the leakage recharge of the reservoir water. Then the invention adopts interval membership in fuzzy evaluation method to evaluate, which is different from clustering analysis. The clustering number of the clustering analysis is limited by human being, so that the classification result is not clear enough. The data in the clustering result which is classified into one class with the reservoir water cannot clearly show the connection relationship between the data and the reservoir water. The interval membership adopted by the invention expresses the relationship between the seepage point and the reservoir water by interval number, analyzes the connection between the single seepage point and the reservoir water in turn, and expresses the evaluation result by interval range value. The interval membership with the same relationship in the evaluation result vector can be compared according to the maximum membership principle. The greater the interval membership is, the greater the fitting degree with the grade is, and then the accuracy of the evaluation result is increased.

[0023] The reservoir leakage is a complex water mixing event. In each stage of each annual cycle of the reservoir operation, the leakage changes due to the influence of climate, hydrogeology and other conditions. Due to the complexity of the water head, temperature and water chemical composition, the conclusion interval of the interval membership adopted by the invention is more reliable, manpower and material resources are saved, and the method is more scientific. DETAILED DESCRIPTION

[0024] The invention is further explained below in combination with the drawings and examples, but is not taken as the basis for limiting the invention.

[0025] Example 1. A reservoir water leakage discrimination method based on interval membership, comprising the following steps:

[0026] Step 1: Collect samples, collect seepage points, underground water and reservoir water in the reservoir area.

[0027] Step 2: Test data, measure water chemical [(Cl - , Ca 2+ , SO4 2- ) ion concentration, pH value] data.

[0028] The detection items of the sample water chemical include chloride ion (Cl - ), calcium ion (Ca 2+ ), sulfate ion (SO4 2- ) ion concentration and pH value. The Cl - and SO4 2- are measured by ion chromatography (HJ / T84-2001), the Ca 2+ is measured by EDTA titration method (GB / T7476-1987), and the pH value is measured by a Leici benchtop acidity meter (model PHSJ-6L). The sample analysis error is within ±5.0%.

[0029] Step 3: According to the water chemistry test results of the sample, the interval membership degree in the fuzzy comprehensive evaluation method is applied to determine the reservoir water leakage, and the steps are as follows:

[0030] (1) For reservoir water leakage, whether the seepage point is reservoir water leakage, there are three relationships of identity, difference and opposition, set A=(a1, a2, …, a m ) as m evaluation indexes affecting the evaluation of reservoir water leakage, and V=(v1, v2, …, v n ) as n evaluation grades of reservoir water leakage, set the index value of the seepage point about the i-th index a i =[a i L ,a i U ], first calculate the interval lower limit c i L and upper limit c i U of the seepage point about the i-th index, and the connection membership degrees r ij L and r ij U about the j-th evaluation grade. The calculation formula is as follows.

[0031] In the formula, r ij is the connection membership degree, r ij ∈[-1, 1]; can represent the lower limit and upper limit of the index interval of the seepage point about the water chemistry [(Cl - , Ca 2+ , SO4 2- ) ion concentration, pH value] index, and x is the water chemistry value of the seepage point; M k-1 , M k , M k+1 , M k+2 are the water chemistry index limits divided according to the evaluation grades of groundwater, reservoir water and mixed water.

[0032]

[0033] (2) Substitute the interval number of the seepage point water chemistry [(Cl - , Ca 2+ , SO4 2- ) ion concentration, pH value] index into the corresponding membership function formula, i.e. formula (1), calculate the membership degree interval evaluation grade vector of each water chemistry index (Cl - , Ca 2+ , SO4 2- , pH value) of the seepage point, and the membership interval evaluation grade vector of multiple indexes, i.e. the interval number judgment matrix R is:

[0034]

[0035] (3) After calculating the interval number evaluation matrix R, the evaluation results of the integrated relationship membership degree of the seepage point with respect to the groundwater, reservoir water, and mixed water grades are calculated using the following formula:

[0036]

[0037] (4) Based on the concept of membership degree, the evaluation method can be determined as: -1 j U When b ≤ 0, the seepage point and the grade show an opposing relationship and do not have the same degree, so it can be determined that the seepage point does not belong to this grade; when b j L <0 j U At that time, the seepage point and the level of that grade have both similarities and differences; when b j L When the value is greater than 0, there is a common relationship between the seepage point and the grade, and it can be determined that the seepage point belongs to that grade. On the other hand, the membership degree of intervals with the same relationship in the evaluation result vector can also be compared according to the principle of maximum membership degree; the larger the value, the greater the degree of fit with the grade.

[0038] ​​The present application can effectively determine the recharge source and discharge relationship of a water body by using a water chemical tracing method, and based on the research on the water chemical characteristics of reservoir water, groundwater and seepage water, the hydraulic connection between the reservoir water and the seepage point is found out, and the seepage channel of the reservoir water is found out; meanwhile, the present application can convert the qualitative evaluation into quantitative evaluation according to the membership theory of fuzzy mathematics, that is, the fuzzy mathematics is used to make an overall evaluation on the things or objects which are restricted by multiple factors; the interval connection membership in the fuzzy clustering analysis reflects the certain and uncertain conversion relationship between things and things, and through the fuzzy comprehensive evaluation method of the interval membership, the quantitative and objective classification is carried out on the basis of comprehensively considering multiple factors according to the characteristics of the research object (sample or variable); and then the reservoir water seepage discrimination method based on the interval membership of the present application is finally formed. Specifically, the method carries out mathematical statistics analysis on the water chemical data, and uses the interval membership in the fuzzy comprehensive discrimination method to evaluate the reservoir water seepage; according to the concept of the connection membership, the discrimination mode can be determined as follows: when the interval membership evaluation result interval upper limit is-1

[0039] Embodiment 2. Taking a reservoir as an example, a reservoir water seepage discrimination method based on interval membership comprises the following steps:

[0040] Step 1: collect samples, collect seepage points in the reservoir area, groundwater and reservoir water.

[0041] Step 2: test data, test water chemical [(Cl - , Ca 2+ , SO4 2- ) ion concentration, pH value] data.

[0042] The detection items of the sample water chemical include chloride ion (Cl - ), calcium ion (Ca 2+ ), sulfate radical (SO4 2- ) and pH value. Among them, Cl - , SO4 2- are determined by ion chromatography (HJ / T84-2001), and Ca 2+The EDTA titration method (GB / T7476-1987) was used to determine the pH value, which was determined by a Regermagnet table-type acidity meter (model PHSJ-6L). The sample analysis error was within ±5.0%. The test data are shown in Table 1.

[0043] Table 1 Water quality analysis table of power station

[0044]

[0045] Step 3: According to the water chemical test results of the sample, the interval membership degree in the fuzzy comprehensive evaluation method was used to determine the reservoir water leakage, and the steps were as follows:

[0046] Based on the interval membership degree evaluation model, the leakage of the upper reservoir of a power station was analyzed, and the water chemical [(Cl - , Ca 2+ , SO4 2- ) ion concentration, pH value] indicators were used as evaluation indicators in the model. The index data of the sampling points of the power station were arranged as shown in Table 1, and the second maximum value was used by removing the maximum value and the minimum value. According to the water chemical data of the power station area for many years, the index division of the underground water, reservoir water and mixed water was determined as shown in Table 2.

[0047] Table 2 Index division of underground water, reservoir water and mixed water

[0048]

[0049] Taking the right bank drainage gallery numbered 1 in Table 1 as an example, the interval evaluation matrix R was calculated by using formula (1):

[0050]

[0051] In the formula: r ij is the connection membership degree, r ij ∈[-1,1]; x is the value of the seepage point, which can represent the lower limit and upper limit of the index interval number of Cl - mg / L about the right bank drainage gallery; M k-1 , M k , M k+1 , M k+2 (5.18, 22.10, 32.70, 35.10) are the lower limit and upper limit of the index interval number of Ca 2+ mg / L; M k-1 , M k , M k+1 , M k+2 (18.22, 41.10, 72.10, 72.90) are the lower limit and upper limit of the index interval number of SO4 2- mg / L; M k-1 , M k , Mk+1 , M k+2 (24.75, 78.70, 141.00, 145.00) Lower and upper limit of index interval about pH value; M k-1 , M k , M k+1 , M k+2 (6.75, 6.90, 8.34, 8.64) are all limits divided according to evaluation grades (groundwater, reservoir water, mixed water).

[0052]

[0053] The evaluation grade vector of membership interval of multiple indexes is substituted into formula (2), and the interval number judgment matrix R of No. 1 right bank drainage gallery is formed as follows:

[0054]

[0055] In the calculation process, if the boundary exceeds the division of each index, the interval length of the previous grade can be extended outward to determine the exceeded boundary, such as M k+2 = M k+1 +(M k+1 -M k ). Here, the difference in the influence of each index on the result is not considered, so the weight vector W = [0.25, 0.25, 0.25, 0.25] is set.

[0056]

[0057] Then the evaluation result of No. 1 right bank drainage gallery can be calculated according to formula (3) as follows:

[0058] B1 = ([-0.1309, -0.7209] [0.2716, 0.44316] [0.0503, 0.5084])

[0059] The evaluation result vectors of other numbers in Table 1 can be calculated in the same way, and the arrangement is shown in Table 3.

[0060] Table 3 Evaluation result of interval membership degree

[0061]

[0062] According to the concept of connection membership degree, the evaluation method can be determined as follows: when -1 < b j U < 0 < b j L < 0 < b j UAt that time, the seepage point and the level of that grade have both similarities and differences; when b j L When the value is greater than 0, there is a common relationship between the seepage point and the grade, and it can be determined that the seepage point belongs to that grade. On the other hand, the membership degree of intervals with the same relationship in the evaluation result vector can also be compared according to the principle of maximum membership degree; the larger the value, the greater the degree of fit with the grade.

[0063] Based on the aforementioned interval membership evaluation method:

[0064] ① The upper and lower limits of the membership degree of the right bank drainage gallery relative to groundwater (b) j L b j U All values ​​less than 0 indicate an antagonistic relationship between the research object and the groundwater, meaning the groundwater is not a recharge source for the seepage point. The upper and lower limits of the interval membership degree (b) of the right bank drainage corridor relative to the reservoir water. j L b j U If both are greater than 0, it indicates a shared relationship between the research object and the reservoir water, suggesting a strong hydraulic connection between the seepage point and the reservoir water, originating from reservoir leakage. The upper and lower limits of the interval membership degree b of the right bank drainage corridor relative to the mixed water. j L b j U All values ​​are greater than 0, indicating that the right bank drainage corridor not only receives water from reservoir seepage but also from other types of water, such as precipitation.

[0065] ② The upper and lower limits of the interval membership degree b of the reservoir bottom corridor weir relative to groundwater. j L b j U If both are less than 0, it indicates an antagonistic relationship between the research object and the groundwater, meaning the groundwater is not a recharge source for the seepage point. The upper and lower limits of the interval membership degree b between the reservoir bottom corridor weir and the reservoir water. j L b j U All values ​​greater than 0 indicate a shared relationship between the research object and the reservoir water, suggesting a strong hydraulic connection between the seepage point and the reservoir water, originating from reservoir leakage. The interval membership degree b of the reservoir bottom corridor weir relative to the mixed water is also relevant. j L <0 j U This indicates that the seepage point and the mixed water are both similar and different, suggesting that the reservoir bottom corridor weir not only accepts reservoir water seepage, but also the mixture of other types of water such as precipitation.

[0066] ​The upper and lower limits of the interval membership degree of B2 high-pressure branch pipe gallery relative to groundwater b j L , b j U Both are less than 0, indicating that the research object has an opposite relationship with the groundwater, and the groundwater is not the recharge source of the seepage point. The upper and lower limits of the interval membership degree of B2 high-pressure branch pipe gallery relative to reservoir water b j L , b j U Both are greater than 0, indicating that the research object has a same relationship with the reservoir water, and the seepage point has a great hydraulic connection with the reservoir water, and the seepage is from the reservoir water. The upper and lower limits of the interval membership degree of B2 high-pressure branch pipe gallery relative to mixed water b j L <0<b j U , indicating that the seepage point has both same and different with mixed water, indicating that B2 high-pressure branch pipe gallery not only accepts seepage from the reservoir water, but also accepts mixed water such as precipitation.

[0067] ④The upper and lower limits of the interval membership degree of 1# construction branch hole relative to groundwater b j L , b j U Both are less than 0, indicating that the research object has an opposite relationship with the groundwater, and the groundwater is not the recharge source of the seepage point. The upper and lower limits of the interval membership degree of 1# construction branch hole relative to reservoir water b j L , b j U Both are greater than 0, indicating that the research object has a same relationship with the reservoir water, and the seepage point has a great hydraulic connection with the reservoir water, and the seepage is from the reservoir water. The upper and lower limits of the interval membership degree of 1# construction branch hole relative to mixed water b j L , b j U Both are greater than 0, indicating that 1# construction branch hole not only accepts seepage from the reservoir water, but also has mixed water such as precipitation.

[0068] ⑤The interval membership degree of 5# construction branch hole relative to groundwater b j L <0<b j U , indicating that the seepage point has both same and different with mixed water, indicating that 5# construction branch hole not only accepts seepage from the groundwater, but also accepts mixed water from the reservoir. The upper and lower limits of the interval membership degree of 5# construction branch hole relative to reservoir water b j L , b j UAll are greater than 0, which indicates that the research object and the reservoir water have the same relationship, the seepage point has great hydraulic connection with the reservoir water, and comes from the reservoir water. j L <0<b j U , which indicates that the seepage point and the mixed water have both same and different, which indicates that the 5# construction branch hole not only receives the reservoir water seepage, but also receives the mixed water such as groundwater and precipitation.

[0069] The above only describes the preferred embodiments of the present application and is not used to limit the present application, and any modification, equivalent replacement and improvement within the spirit and principle of the present application should be included in the protection scope of the present application.

Claims

1. A reservoir water leakage discrimination method based on interval membership degree, characterized in that, According to the sample water chemical test results, the interval membership degree in fuzzy comprehensive evaluation method is applied to distinguish the reservoir water leakage, including the following steps: (1) For reservoir seepage, there are three relationships between seepage points and reservoir seepage, which are identity, difference and opposition. Let A=(a1, a2, …, a m ) be m evaluation indexes affecting the evaluation of reservoir seepage, and V=(v1, v2, …, vn) be n evaluation grades of reservoir seepage. n ) be n evaluation grades of reservoir seepage. Let a i = [a i L ,a i U ]; first, calculate the lower limit c i L and the upper limit c i U of the i-th index interval respectively, and then calculate the contact membership r ij L and r ij U of the j-th evaluation grade, the calculation formula is as follows: wherein: r ij is the membership degree, r ij ∈[-1,1], represents the lower and upper limits of the index interval of the water seepage point with respect to the water chemical index, which includes the ion concentrations of Cl - , Ca 2+ , SO4 2- , and the pH value of the water sample; x is the water chemical index of the water seepage point; M k-1 , M k , M k+1 , M k+2 are the water chemical index limits divided according to the evaluation grades of groundwater, reservoir water, and mixed water; (2) The interval number of the water chemical index of the water seepage point is substituted into the corresponding membership function formula, that is, formula (1), the membership degree interval evaluation grade vector of each water chemical index of the water seepage point is calculated, and the membership interval evaluation grade vectors of multiple indexes are comprehensively evaluated, that is, the interval number evaluation matrix R is formed as follows: (3) After the interval number evaluation matrix R is calculated, the integrated contact membership degree evaluation result of the water seepage point about the underground water, reservoir water and mixed water grade is calculated by the following formula: where b j U denotes the interval membership evaluation result interval upper limit, b j L denotes the interval membership evaluation result interval lower limit, j = 1, 2, …, m; According to the concept of connection membership, the evaluation mode can be determined as follows: -1 < b j U When b j L <0 < b j U , the water permeation point and the grade have both same and different relations; when b j L > 0, the water permeation point and the grade have same relation, and it is determined that the water permeation point belongs to the grade.

2. The interval membership degree based reservoir leakage discrimination method according to claim 1, characterized in that, In step (3), the interval membership degrees with the same relationship in the evaluation result interval are compared according to the maximum membership degree principle, and the greater the degree is, the greater the fitting degree with the grade is.

3. The interval membership degree based reservoir leakage discrimination method according to claim 1, characterized in that, The specific sample water chemical test is as follows: Water samples were collected from seepage points, groundwater and reservoir water in the reservoir area, respectively; water chemistry determination was performed on the water samples, including determination of ion concentrations of Cl - , Ca 2+ and SO4 2- and pH value in the water samples.

4. The interval membership degree-based reservoir leakage discrimination method according to claim 3, characterized in that, Cl - and SO4 2- Ion concentrations were determined by ion chromatography.

5. The interval membership degree-based reservoir leakage discrimination method according to claim 3, characterized in that, Ca 2+ The ion concentration of Ca was determined by EDTA titration.

6. The interval membership degree based reservoir leakage discrimination method according to claim 3, characterized in that, The pH value is determined by using the acidimeter of Leici.

7. The interval membership degree based reservoir leakage discrimination method according to claim 3, characterized in that, The determination error of the water sample is within ±5.0%.

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