CN112833852A - Method for drawing up hydropower station concrete dam deformation safety monitoring index - Google Patents

Method for drawing up hydropower station concrete dam deformation safety monitoring index Download PDF

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CN112833852A
CN112833852A CN202110218111.XA CN202110218111A CN112833852A CN 112833852 A CN112833852 A CN 112833852A CN 202110218111 A CN202110218111 A CN 202110218111A CN 112833852 A CN112833852 A CN 112833852A
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汪俊波
程帅
章春香
南江
牛瑞杰
裴海林
陈少华
彭金宁
李志华
夏绍云
刘诚威
俞年年
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Xian Thermal Power Research Institute Co Ltd
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
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Abstract

The invention discloses a method for drawing up deformation safety monitoring indexes of a concrete dam of a hydropower station. The method includes the steps that historical data of deformation monitoring points of typical dam sections are sorted, gross error and abnormal data are removed, then characteristic values are counted and calculated respectively, distribution inspection is conducted on historical extreme values, finally deformation monitoring indexes of the typical dam sections are calculated through a small probability method, and the monitoring indexes are comprehensively drawn up by combining the historical extreme values. The dam deformation monitoring method has guiding significance for calculating monitoring indexes of dam deformation monitoring data, and can provide basis for dam operation management and state evaluation.

Description

Method for drawing up hydropower station concrete dam deformation safety monitoring index
Technical Field
The invention belongs to the field of hydropower station dam monitoring data analysis, and particularly relates to a method for drawing up hydropower station concrete dam deformation safety monitoring indexes.
Background
The dam safety monitoring index is a limit value of normal state and abnormal state specified by the effect quantity of the dam in service. The method has the advantages that index planning is carried out on monitoring data of the dam in the operation period, monitoring indexes or early warning values are reasonably determined, and the method has important guiding significance for dam operation management and state evaluation.
At present, the main methods for setting up the safety monitoring indexes of the dam comprise: 1) the confidence interval estimation method based on the statistical model has strong specialization, needs professionals to compile professional software for calculation and analysis, is difficult to master by common power station workers, and cannot meet and adapt to the requirement of regular updating of monitoring indexes; 2) the extreme balance method is a calculation method adopted in a design stage, and the actual construction and operation in the later stage have deviation with the design stage and cannot necessarily reflect the actual condition; 3) finite element analysis. The method needs to determine and simplify complex boundary conditions, the material parameters are different from actual parameters, and the calculation result precision is low. 4) Typical small probability methods. The monitoring indexes drawn up by the existing reference documents by a typical small probability method are mainly normal distribution, few test methods and calculation cases of lognormal distribution and extreme value I-type distribution exist, the test and calculation processes are not disclosed in detail, and a system is not formed.
There is no relevant patent and announcement at present in respect of the aspect of drawing up the dam safety monitoring index or early warning value.
Disclosure of Invention
The invention aims to overcome the defects of large calculation amount and complex process of the conventional dam safety monitoring index planning, and provides a method for planning the hydropower station concrete dam deformation safety monitoring index. According to the method, on the premise of existing observation data, deformation monitoring indexes or early warning values of typical dam sections of the dam are drawn up through methods of gross error identification and elimination, statistics and calculation of characteristic values, distribution inspection, extreme value calculation and the like, the operation is simple, the realization is easy, the economy is good, and a method and a way can be provided for drawing up the early warning values of the deformation of the concrete dam of the hydropower station.
In order to achieve the purpose, the invention adopts the technical scheme that:
a method for drawing up deformation safety monitoring indexes of a concrete dam of a hydropower station comprises the following steps:
step 1) selecting deformation measuring points of a typical dam section to be drawn up, sorting related historical data, preliminarily eliminating gross errors according to a process line method and a '3 sigma' criterion, and counting the maximum value and the minimum value every year to obtain a group of samples: x ═ xm1，xm2，…，xmn}；
Step 2) calculating the characteristic value of the sample statistic, and estimating the statistical characteristic value of the statistical sample by using the following formula according to the n observed values of the known random variable x, the mean value mu, the standard deviation sigma and the variation coefficient delta of the statistical sample:
Figure BDA0002954729540000021
Figure BDA0002954729540000022
Figure BDA0002954729540000023
step 3) carrying out distribution test on the sample statistics by using a K-S test method, and determining a distribution function F (x) of the probability density f (x);
sorting the values of the monitored quantities, x1＜x2＜x3...＜xnAnd calculating the empirical distribution:
Figure BDA0002954729540000024
respectively programming and calculating theoretical distribution F (x) of hypothetical normal distribution, log-normal distribution and extreme value I-type distribution function according to the following formulask)；
Figure BDA0002954729540000025
Figure BDA0002954729540000026
In the formula
Figure BDA0002954729540000031
F(xk)＝exp[-exp(-a(x-u))] (7)
Wherein, alpha is 1.28255/sigma, u is mu-0.57722/alpha;
empirical distribution F of samplesn(xk) And the assumed theoretical distribution F (x)k) Establishing statistics:
Figure BDA0002954729540000032
according to the significance level, looking up a K-S inspection critical value table to obtain Dn，0.05If D isn＜Dn，0.05Then it is assumed to be accepted, if Dn＞Dn，0.05Then the hypothesis is rejected;
step 4) determining the probability of the extreme value of the dam according to the grade and the importance of the dam, and further calculating the extreme value under the corresponding probability;
and 5) comprehensively considering the monitoring indexes of the deformation projects from the aspects of a probability statistical method and a time interval extreme value, and selecting the maximum value or the minimum value of the numerical values in principle on the premise of meeting the application conditions of the two methods.
The invention has the further improvement that the typical dam sections in the step 1) generally refer to the highest dam section, the geologically weak dam section, the closure dam section and the dam section with the measured value continuously developing along with the time in daily observation; the monitoring data of the selected dam section is integrally reliable, credible and good in regularity; if the dam is in the first year of operation, deformation is great along with reservoir retaining change, and follow-up data is relatively stable, when making statistics, rejects the data of first year from the operation to the end of the year, and the statistics age is no less than 5 natural years.
The invention further improves that the process line method in the step 1) directly eliminates the measured value of the obvious abnormal jitter by an intuitive method, wherein sigma in the '3 sigma' criterion is the standard deviation of the measured value series, if the measured value is out of the range of [ mu-3 sigma, mu +3 sigma ], the measured value is considered to be abnormal and should be eliminated, and mu is the series average value.
A further development of the invention is that in step 2) the random variable x is a statistical characteristic value, wherein the maximum value and the minimum value are calculated separately.
The invention is further improved in that the K-S test method in the step 3) is realized by statistical calculation software SPSS, matlab or programming a calculation program.
The further improvement of the invention is that in the step 4), the probability of the extreme value of the dam is determined according to the grade and the importance of the dam, the dam with the grade more than three is determined, the probability of the primary early warning value is 1 percent, and the probability of the secondary early warning value is 5 percent.
The invention is further improved in that step 4) the final calculation and drawing up of the monitoring index is as follows:
(1) normal distribution calculation formula:
maximum value is μ +1.645 σ; minimum value is mu-1.645 sigma; 5% probability;
maximum value μ +2.3267 σ; minimum value μ -2.3267 σ; 1% probability;
(2) formula for calculating lognormal distribution:
maximum value exp (λ +1.645 ξ); minimum value ═ exp (λ -1.645 ξ); 5% probability;
maximum value exp (λ +2.3267 ξ); a minimum value ═ exp (λ -2.3267 ξ); 1% probability;
(3) the extreme value type I distribution calculation formula is as follows:
Figure BDA0002954729540000041
the parameter calculation in the formula refers to step 2) and step 3), where R denotes the recurrence period, and R is 20 when the probability is 5% and 100 when the probability is 1%.
The method is further improved in that the maximum value and the minimum value of a certain measuring point determined in the step 5) are final monitoring indexes or early warning values which are drawn under the occurred historical load and condition and are used as references and basis in later operation, and correction is carried out once every 3-5 years along with the continuous change of the operation condition of the dam.
The invention has at least the following beneficial technical effects:
compared with the prior art, the method has the advantages that in the traditional probability distribution K-S inspection process of the historical extreme value of dam deformation, the distribution inspection and calculation method of the extreme value type I is added, the calculation system of the typical small probability method of concrete dam deformation is further enriched and perfected, the condition that the historical extreme value is not suitable for normal distribution and log-normal distribution is made up, and the established dam deformation monitoring index is closer to reality. The method is convenient to operate and easy to realize, and can provide a method for drawing up the early warning value of the deformation of the concrete dam of the hydropower station.
Drawings
Fig. 1 is a screening chart of abnormal data process lines of a dam survey value.
Fig. 2 is a screening chart of abnormal data process lines of a strain measurement value of a dam.
FIG. 3 is a flow chart of monitoring index development.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples.
The basic idea of the invention is as follows: selecting historical data needing analysis and calculation, preliminarily removing gross errors, as shown in figures 1 and 2, further removing the gross errors through a '3 sigma' criterion on the basis, and counting the maximum value and the minimum value of each year. And (3) counting and calculating the characteristic value of the extreme value sample, carrying out distribution inspection on the historical extreme value, finally calculating the deformation monitoring index of the typical dam section by a small probability method, and comprehensively drawing up the monitoring index by combining the historical extreme value.
Referring to fig. 1 to 3, in combination with the embodiments in tables 1 to 3, the method for developing the hydropower station concrete dam deformation safety monitoring index provided by the invention comprises the following steps:
step 1) selecting deformation measuring points of a typical dam section to be drawn up, sorting related historical data, preliminarily eliminating gross errors according to a process line method and a '3 sigma' criterion, and counting the maximum value and the minimum value every year to obtain a group of samples: x ═ xm1，xm2，…，xmn}; specific data samples are shown in table 1.
Step 2) calculating the characteristic value of the sample statistic, and estimating the statistical characteristic value of the statistical sample by using the mean value mu, the standard deviation sigma and the variation coefficient delta of the statistical sample of the n observed values of the known random variable x according to the following formula:
Figure BDA0002954729540000051
Figure BDA0002954729540000052
Figure BDA0002954729540000053
and 3) carrying out distribution test on the sample statistics by using a K-S test method, and determining a distribution function F (x) of the probability density f (x).
Sorting the values of the monitored quantities, x1＜x2＜x3...＜xnAnd calculating the empirical distribution:
Figure BDA0002954729540000061
respectively programming and calculating theoretical distribution F (x) of hypothetical normal distribution, log-normal distribution and extreme value I-type distribution function according to the following formulask)；
Figure BDA0002954729540000062
Figure BDA0002954729540000063
In the formula
Figure BDA0002954729540000064
F(xk)＝exp[-exp(-a(x-u))]
Wherein, alpha is 1.28255/sigma, u is mu-0.57722/alpha; where μ and σ are calculated as in step 2).
Empirical distribution F of samplesn(xk) And the assumed theoretical distribution F (x)k) Establishing statistics:
Figure BDA0002954729540000065
according to the significance level (taking 0.05), looking up a K-S inspection critical value table to obtain Dn，0.05If D isn＜Dn，0.05Then the assumption is accepted. If D isn＞Dn，0.05The hypothesis is rejected.
The results of the distribution test are shown in Table 2.
And 4) determining the probability of the extreme value of the dam according to the grade and the importance of the dam, and further calculating the extreme value under the corresponding probability.
And 5) comprehensively considering the monitoring indexes of the deformation project mainly from two aspects of a probability statistical method and a time interval extreme value, and selecting the maximum value or the minimum value of the numerical values in principle on the premise of meeting the application conditions of the two methods. The finally drawn up monitoring index (early warning value) is shown in table 3.
The typical dam sections in the step 1) generally refer to the highest dam section, the geologically weak dam section, the closure dam section of a concrete dam, the dam section with measured values continuously developing along with time in daily observation and other dam sections needing attention. The monitoring data of the selected dam section should be reliable, credible and regular. In the historical data selected in the step 1), if the dam is in the first year of operation, the deformation is greatly changed along with the water storage of the reservoir, the subsequent data is relatively stable, the data in the first year (from the time of operation to the end of the current year) is removed during statistics, and the statistical age is not less than 5 natural years.
In the process line method in the step 1), the measured value of the obvious abnormal jitter is directly removed by an intuitive method, wherein sigma in a '3 sigma' criterion is the standard deviation of the measured value series, if the measured value is out of the range of [ mu-3 sigma, mu +3 sigma ], the measured value is considered to be abnormal and should be removed, and mu is the series average value.
In the step 2), the random variable x is a statistical characteristic value, wherein the maximum value and the minimum value are calculated respectively.
D in the step 3)n，0.05The specific value conditions are as follows: when n is 5, Dn，0.050.563; when n is 6, Dn，0.050.519; when n is 7, Dn，0.050.483; when n is 8, Dn，0.050.454; when n is 9, Dn，0.050.430; when n is 10, Dn，0.050.409; when n is 11, Dn，0.050.391; when n is 12, Dn，0.050.375, etc.
The K-S inspection method in the step 3) can be realized by statistical calculation software SPSS, matlab, calculation program programming or the like.
In the step 4), the probability of the extreme value of the dam is determined according to the grade and the importance of the dam, the general grade of the dam is more than three, the probability of the primary early warning value is preferably 1%, and the probability of the secondary early warning value is preferably 5%.
The final calculation and drawing up of the monitoring indexes in the step 4) are as follows:
(1) normal distribution calculation formula:
maximum value is μ +1.645 σ; minimum value is mu-1.645 sigma; (5% probability)
Maximum value μ +2.3267 σ; minimum value μ -2.3267 σ; (1% probability)
(2) Formula for calculating lognormal distribution:
maximum value exp (λ +1.645 ξ); minimum value exp (λ -1.645 ξ) (5% probability)
Maximum value exp (λ +2.3267 ξ); minimum value exp (λ -2.3267 ξ) (1% probability)
(3) Formula for calculating extremum type I distribution:
Figure BDA0002954729540000081
the parameter calculation in the formula refers to step 2) and step 3), where R denotes the recurrence period, and R is 20 when the probability is 5% and 100 when the probability is 1%.
The maximum value and the minimum value of a certain measuring point determined in the step 5) are final monitoring indexes or early warning values drawn under the occurred historical load and conditions, and can be used as references and bases in later-stage operation.
The method is implemented by taking the steps of drawing a certain concrete dam monitoring index as an example:
table 1 shows the extreme value statistics of the deformation history of a typical dam section of a concrete dam;
table 2 shows the distribution test condition of the extreme value samples in the history of deformation of the concrete dam;
table 3 shows the final results of the deformation monitoring index.
Table 1:
Figure BDA0002954729540000082
table 2:
Figure BDA0002954729540000083
Figure BDA0002954729540000091
table 3:
Figure BDA0002954729540000092
the basic principle features and specific implementation of the present invention are described in the above steps, tables and drawings, but the present invention is not limited to the above specific implementation, and any simple modifications, form changes, equivalent structural changes, etc. made to the above embodiments according to the technical essence of the present invention still fall within the protection scope of the technical solution of the present invention.

Claims (8)

1. A method for drawing up deformation safety monitoring indexes of a concrete dam of a hydropower station is characterized by comprising the following steps:
step 1) selecting deformation measuring points of a typical dam section to be drawn up, sorting related historical data, preliminarily eliminating gross errors according to a process line method and a '3 sigma' criterion, and counting the maximum value and the minimum value every year to obtain a group of samples: x ═ xm1，xm2，…，xmn}；
Step 2) calculating the characteristic value of the sample statistic, and estimating the statistical characteristic value of the statistical sample by using the following formula according to the n observed values of the known random variable x, the mean value mu, the standard deviation sigma and the variation coefficient delta of the statistical sample:
Figure FDA0002954729530000011
Figure FDA0002954729530000012
Figure FDA0002954729530000013
step 3) carrying out distribution test on the sample statistics by using a K-S test method, and determining a distribution function F (x) of the probability density f (x);
sorting the values of the monitored quantities, x1＜x2＜x3…＜xnAnd calculating the empirical distribution:
Figure FDA0002954729530000014
respectively programming and calculating theoretical distribution F (x) of hypothetical normal distribution, log-normal distribution and extreme value type I distribution function according to the following formulask)；
Figure FDA0002954729530000015
Figure FDA0002954729530000016
In the formula
Figure FDA0002954729530000017
F(xk)＝exp[-exp(-a(x-u))] (7)
Wherein, alpha is 1.28255/sigma, u is mu-0.57722/alpha;
empirical distribution F of samplesn(xk) And the assumed theoretical distribution F (x)k) Establishing statistics:
Figure FDA0002954729530000021
according to the significance level, looking up a K-S inspection critical value table to obtain Dn,0.05If D isn＜Dn,0.05Then it is assumed to be accepted, if Dn>Dn,0.05Then the hypothesis is rejected;
step 4) determining the probability of the extreme value of the dam according to the grade and the importance of the dam, and further calculating the extreme value under the corresponding probability;
and 5) comprehensively considering the monitoring indexes of the deformation projects from the aspects of a probability statistical method and a time interval extreme value, and selecting the maximum value or the minimum value of the numerical values in principle on the premise of meeting the application conditions of the two methods.
2. The method for developing the hydropower station concrete dam deformation safety monitoring index according to claim 1, wherein the typical dam sections in the step 1) generally refer to the highest dam section, the geologically weak dam section, the closure dam section and the dam section with the measured value continuously developing along with time in daily observation; the monitoring data of the selected dam section is integrally reliable, credible and good in regularity; if the dam is in the first year of operation, deformation is great along with reservoir retaining change, and follow-up data is relatively stable, when making statistics, rejects the data of first year from the operation to the end of the year, and the statistics age is no less than 5 natural years.
3. The method for developing the deformation safety monitoring index of the concrete dam of the hydropower station according to claim 1, wherein the process line method in the step 1) directly eliminates the measured value of the obvious abnormal jumping by a visual method, wherein the sigma in the '3 sigma' criterion is the standard deviation of the measured value series, and if the measured value is out of the range of [ mu-3 sigma, mu +3 sigma ], the measured value is considered to be abnormal and should be eliminated, wherein mu is the mean value of the series.
4. The method for developing the hydropower station concrete dam deformation safety monitoring index according to claim 1, wherein the random variable x in the step 2) is a statistical characteristic value, and the maximum value and the minimum value are calculated respectively.
5. The method for developing the hydropower station concrete dam deformation safety monitoring index according to claim 1, wherein the K-S test method in the step 3) is realized by statistical calculation software SPSS, matlab or programming a calculation program.
6. The method for developing the deformation safety monitoring index of the concrete dam of the hydropower station according to claim 1, wherein the probability of the extreme value of the dam is determined in the step 4) according to the grade and the importance of the dam, the dam with the grade of more than three is determined, the probability of the primary early warning value is selected to be 1%, and the probability of the secondary early warning value is selected to be 5%.
7. The method for formulating the hydropower station concrete dam deformation safety monitoring index as claimed in claim 1, wherein the final calculation and formulation of the monitoring index in the step 4) are as follows:
(1) normal distribution calculation formula:
maximum value is μ +1.645 σ; minimum value is mu-1.645 sigma; 5% probability;
maximum value μ +2.3267 σ; minimum value μ -2.3267 σ; 1% probability;
(2) formula for calculating lognormal distribution:
maximum value exp (λ +1.645 ξ); minimum value ═ exp (λ -1.645 ξ); 5% probability;
maximum value exp (λ +2.3267 ξ); a minimum value ═ exp (λ -2.3267 ξ); 1% probability;
(3) the extreme value type I distribution calculation formula is as follows:
Figure FDA0002954729530000031
the parameter calculation in the formula refers to step 2) and step 3), where R denotes the recurrence period, and R is 20 when the probability is 5% and 100 when the probability is 1%.
8. The method for drawing up the hydropower station concrete dam deformation safety monitoring index according to claim 1, wherein the maximum value and the minimum value of a certain measuring point determined in the step 5) are final monitoring indexes or early warning values drawn up under the occurred historical load and condition, and are used as references and bases in later operation, and the maximum value and the minimum value are corrected every 3-5 years along with the continuous change of the dam operation condition.
CN202110218111.XA 2021-02-26 2021-02-26 Method for drawing up hydropower station concrete dam deformation safety monitoring index Pending CN112833852A (en)

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Publication number Priority date Publication date Assignee Title
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Publication number Priority date Publication date Assignee Title
CN109035730A (en) * 2018-07-16 2018-12-18 河海大学 It is a kind of to consider that the concrete dam that Service Environment influences damages dynamic warning method
CN109255180A (en) * 2018-09-07 2019-01-22 国网湖南省电力有限公司 A kind of similar operating condition comparison analytic approach of dam safety monitoring deformation extreme value
CN111256754A (en) * 2020-01-19 2020-06-09 河海大学 Concrete dam long-term operation safety early warning method
CN111508216A (en) * 2020-04-28 2020-08-07 水利部交通运输部国家能源局南京水利科学研究院 Intelligent early warning method for dam safety monitoring data

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Application publication date: 20210525