土石坝安全监测资料分析评价方法研究
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摘要
我国有相当部分的大、中、小型水库大坝存在着不同程度的安全问题,其中以土石坝绝对居多。因而,根据上石坝原型观测资料,运用更成熟、更合适的理论和方法,对观测资料进行分析,对土石坝的实测性态作出正确评价,就显得尤为重要了。本文应用回归分析、遗传算法、人工神经网络、灰理论和多级模糊模式识别理论,结合土石坝的特点,对土石坝实测性态进行了研究。本文的主要成果如下:
1.对土石坝原型观测资料中误差的成因进行了分析,并介绍了识别方法;分析了土石坝测压管水位滞后性的原因和测压管水位的定性分析方法;通过对土石坝渗流进行成因分析,建立了测压管水位的统计模型;分析了影响土石坝沉降的因素;根据土石坝沉降的特点和各种函数的数学特性,探讨了土石坝的模型选择;最后用陆浑水库观测资料对库水位和测压管水位进行了定性分析。
2.介绍了土石坝原型观测资料分析中常用的回归分析方法:一元线性回归、可化为一元线性回归的曲线回归、多元线性回归及逐步回归分析方法。针对常用的基于最小二乘法的回归分析方法不能抵御粗差的不足,作者引入了稳健回归中常用的M估计,它能有效的消除异常值的影响。介绍了M估计的原理和求解步骤,从理论上说明了稳健回归的优点和最小二乘法的不足:最后用渗流资料建模进行了验证。
3.引入遗传算法,考虑到实际问题,针对简单遗传法不易求解高精度问题及求解效率不高的不足,对简单遗传算法加以改进。针对遗传算法局部搜索能力较差的不足,引入模拟退火算法,为了提高搜索效率对模拟退火算法加以改进。结合土石坝的沉降规律,建立了土石坝沉降的遗传算法和遗传模拟退火算法模型。水利工程影响因素众多,是个高度复杂的非线性问题,将人工神经网络中的BP网络模型引入到土石坝观测资料分析中,建立了土石坝渗流和沉降的BP网络模型。大量分析研究表明,土石坝时效变形具有一定的单调性,针对这一特点,引入灰理论,对土石坝时效变形建立了能反映工程动态变化的GM(1,1)模型。最后用实测资料对上述方法进行了对比分析和验证。
4.土石坝实测性态是一个多层次、多指标的复杂分析评价问题,针对传统的大坝实测性态评价方法不能反映土石坝整体性态的不足,提出了土石坝实测性态综合评价问题的研究体系,该体系研究内容包括综合评价指标的设置、评价指标的度量方法和综合评价途径,并进行了比较深入的探讨;同时针对土石坝实测性态评价的特点,引入了多级模糊模式识别理论,建立了土石坝实测性态多级模糊模式识别方法,并应用到实例中。
5.运用陆浑水库实测资料和本论文的主要研究内容,结合Visual Basic数据库编程和软件开发技术,开发出了陆浑水库安全监测分析评价系统。
In our country there are a great many large ,medium and minitype reservoirs and dams have safety problems of different degree, especially do the earth-rockfill dam. Therefore, it is very important that using even mature and suitable theory and method analyzing prototype observed data and evaluating the condition, according to prototype observed data of earth-rockfill dam.In this thesis by means of regression analysis, genetic algorithms, artificial neural network,grey theory and multi-pole fuzzy pattern recognition theory, together with the characteristics of earth-rockfill, it is researched the observed behavior of earth-rockfill dam. The main contents are as follows:1. The genetic analysis for error of the prototype observed data of earth-rockfill dam is carried out and recognition methods of error is introduced. The reason of hysteresis quality and qualitative analysis of piezometric level is analyzed. The statistic model of piezometric level is established through genetic analysis for seepage of earth-rockfill dam.The influence factor of settlement of earth-rockfill dam is analyzed. The selection of settlement model is discussed,according to the characteristics of earth-rockfill dam and the features of various functions. Combining the measured seepage data of LuHun dam, qualitative analysis is carried out.2. The regression analysis method is introduced,such as simple regression analysis, curve regression which can be changed into simple regression analysis, multi-variate regression analysis and stepwise regression analysis. In the light of the problem of conventional regression analysis method based on least-squares method being unable to resist gross error interference ,we adopt M-estimator in common use in robust regression, which can conquer the influence of outliers in observed data effectively. The theory and solution procedure of M-estimator is summaried.At last we proof the above theory and method by applying it to observed data analysis for piezometric level of earth-rockfill dam.3. Genetic algorithms is introduced and improved ,which in considered of the physical problem of earth-rockfill dam.In light of the search capability of genetic algorithms is not powerful,we introduce simulated annealing algorithms,and improve it in order to improve it's search efficiency. Combining the settlement characteristics of earth-rockfill dam, the model of genetic algorithms and genetic simulated annealing algorithms is established. Hydraulic engineering has a lot of influence factor,which is a complex and high nonliner problem.The BP network model of artificial neural network is introduced and the BP network model of seepage and settlement is established.A lot of analysis and research indicate the aging deformation of earth-rockfill dam has monotonicity. Point this feature, we indraft gray theory, create the now information model of the GM(1,1), by using its characteristics that it can
reflect the engineer's dynamic change .Finally we analyze and proof the above theory and method by applying it to observed data.4. The observed behavior of earth-rockfill dam is a complex multi- hierarchy and multi-object evaluation problem.In light of the deficiency of traditional evalution method unable to reflect integral behavior,we present and profound discuss the research body system of observed behavior of earth-rockfill dam which include the location of integral evaluation index,the measuring method of integral evaluation index and the path of integral evaluation. The multi-pole fuzzy pattern recognition theory is indrafted based on the characteristic of earth-rockfill dam evalution ,the model of multi-pole fuzzy pattern recognition theory for earth-rockfill dam is built and we apply it to example which analysis show that it is reasonable and feasible.5. Applying observed data of Luhun dam and the research of this thesis?together with database programming of Visual Basic and the development technique of software, we develop safety monitoring analysis and evaluation system of Luhun dam.
1.对土石坝原型观测资料中误差的成因进行了分析,并介绍了识别方法;分析了土石坝测压管水位滞后性的原因和测压管水位的定性分析方法;通过对土石坝渗流进行成因分析,建立了测压管水位的统计模型;分析了影响土石坝沉降的因素;根据土石坝沉降的特点和各种函数的数学特性,探讨了土石坝的模型选择;最后用陆浑水库观测资料对库水位和测压管水位进行了定性分析。
2.介绍了土石坝原型观测资料分析中常用的回归分析方法:一元线性回归、可化为一元线性回归的曲线回归、多元线性回归及逐步回归分析方法。针对常用的基于最小二乘法的回归分析方法不能抵御粗差的不足,作者引入了稳健回归中常用的M估计,它能有效的消除异常值的影响。介绍了M估计的原理和求解步骤,从理论上说明了稳健回归的优点和最小二乘法的不足:最后用渗流资料建模进行了验证。
3.引入遗传算法,考虑到实际问题,针对简单遗传法不易求解高精度问题及求解效率不高的不足,对简单遗传算法加以改进。针对遗传算法局部搜索能力较差的不足,引入模拟退火算法,为了提高搜索效率对模拟退火算法加以改进。结合土石坝的沉降规律,建立了土石坝沉降的遗传算法和遗传模拟退火算法模型。水利工程影响因素众多,是个高度复杂的非线性问题,将人工神经网络中的BP网络模型引入到土石坝观测资料分析中,建立了土石坝渗流和沉降的BP网络模型。大量分析研究表明,土石坝时效变形具有一定的单调性,针对这一特点,引入灰理论,对土石坝时效变形建立了能反映工程动态变化的GM(1,1)模型。最后用实测资料对上述方法进行了对比分析和验证。
4.土石坝实测性态是一个多层次、多指标的复杂分析评价问题,针对传统的大坝实测性态评价方法不能反映土石坝整体性态的不足,提出了土石坝实测性态综合评价问题的研究体系,该体系研究内容包括综合评价指标的设置、评价指标的度量方法和综合评价途径,并进行了比较深入的探讨;同时针对土石坝实测性态评价的特点,引入了多级模糊模式识别理论,建立了土石坝实测性态多级模糊模式识别方法,并应用到实例中。
5.运用陆浑水库实测资料和本论文的主要研究内容,结合Visual Basic数据库编程和软件开发技术,开发出了陆浑水库安全监测分析评价系统。
In our country there are a great many large ,medium and minitype reservoirs and dams have safety problems of different degree, especially do the earth-rockfill dam. Therefore, it is very important that using even mature and suitable theory and method analyzing prototype observed data and evaluating the condition, according to prototype observed data of earth-rockfill dam.In this thesis by means of regression analysis, genetic algorithms, artificial neural network,grey theory and multi-pole fuzzy pattern recognition theory, together with the characteristics of earth-rockfill, it is researched the observed behavior of earth-rockfill dam. The main contents are as follows:1. The genetic analysis for error of the prototype observed data of earth-rockfill dam is carried out and recognition methods of error is introduced. The reason of hysteresis quality and qualitative analysis of piezometric level is analyzed. The statistic model of piezometric level is established through genetic analysis for seepage of earth-rockfill dam.The influence factor of settlement of earth-rockfill dam is analyzed. The selection of settlement model is discussed,according to the characteristics of earth-rockfill dam and the features of various functions. Combining the measured seepage data of LuHun dam, qualitative analysis is carried out.2. The regression analysis method is introduced,such as simple regression analysis, curve regression which can be changed into simple regression analysis, multi-variate regression analysis and stepwise regression analysis. In the light of the problem of conventional regression analysis method based on least-squares method being unable to resist gross error interference ,we adopt M-estimator in common use in robust regression, which can conquer the influence of outliers in observed data effectively. The theory and solution procedure of M-estimator is summaried.At last we proof the above theory and method by applying it to observed data analysis for piezometric level of earth-rockfill dam.3. Genetic algorithms is introduced and improved ,which in considered of the physical problem of earth-rockfill dam.In light of the search capability of genetic algorithms is not powerful,we introduce simulated annealing algorithms,and improve it in order to improve it's search efficiency. Combining the settlement characteristics of earth-rockfill dam, the model of genetic algorithms and genetic simulated annealing algorithms is established. Hydraulic engineering has a lot of influence factor,which is a complex and high nonliner problem.The BP network model of artificial neural network is introduced and the BP network model of seepage and settlement is established.A lot of analysis and research indicate the aging deformation of earth-rockfill dam has monotonicity. Point this feature, we indraft gray theory, create the now information model of the GM(1,1), by using its characteristics that it can
reflect the engineer's dynamic change .Finally we analyze and proof the above theory and method by applying it to observed data.4. The observed behavior of earth-rockfill dam is a complex multi- hierarchy and multi-object evaluation problem.In light of the deficiency of traditional evalution method unable to reflect integral behavior,we present and profound discuss the research body system of observed behavior of earth-rockfill dam which include the location of integral evaluation index,the measuring method of integral evaluation index and the path of integral evaluation. The multi-pole fuzzy pattern recognition theory is indrafted based on the characteristic of earth-rockfill dam evalution ,the model of multi-pole fuzzy pattern recognition theory for earth-rockfill dam is built and we apply it to example which analysis show that it is reasonable and feasible.5. Applying observed data of Luhun dam and the research of this thesis?together with database programming of Visual Basic and the development technique of software, we develop safety monitoring analysis and evaluation system of Luhun dam.
引文
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[2] 白永年、吴士宁等.土石坝加固[M].北京:水利电力出版社,1992.
[3] 张启岳等.土石坝加固技术[M].北京:中国水利水电出版社,1999.
[4] 钱正英.中国水利[M].北京:水利电力出版社,1991。
[5] 陈久宇.应用实测位移资料研究刘家峡重力坝横缝的结构作用[J].水利学报,1982(12).
[6] 吴中如.混凝土坝观测物理量的数学模型及其应用[J].华东水利学院学报,1984(3).
[7] 吴中如、沈长松等.论混凝土坝变形统计模型的因子选择[J].河海大学学报,1988(6).
[8] 吴中如、张明歧.用组合流变模型研究地下洞室周壁变形的时间效应[J].河海大学学报,1986(2).
[9] 加拿大大坝安全协会(CDSA)主编,大坝安全导则及其评注.
[10] Thun JLV. Application of decision analysis techniques in dam safety evalvation and modification. Proc of the ICOSD, C2. 2, Rotterdam, 1984: 265～271.
[11] 李君纯.水库大坝安全评判的研究[J].水利水运科学研究,1999(1).
[12] 杨志超.误差理论[M].中南工业大学出版社,1987.
[13] 郦能惠.土石坝安全监测分析评价预报系统[M].中国水利水电出版社,2003.
[14] 吴中如、顾冲时.大坝安全综合评价专家系统[M].北京科学技术出版社,1997.
[15] 薛桂玉、李珍照等.水工建筑物观测数据概率分布的模糊识别方法研究[J].大坝观测与土工测试,1997(4).
[16] 全国化工系统高校数学协作组.概率统计[M].河南科学技术出版社,1996.
[17] 肖明耀.误差理论与应用[M].计量出版社,1985.
[18] 刘洵、方朝阳.土石坝测压管水位观测资料分析[J].中国农村水利水电,2001(7).
[19] 吴中如.水工建筑物安全监控理论及其应用[M].北京:高等教育出版社,2003.
[20] 赵志仁、黄艳菊、刘家凯.土石坝变形监测中安全监控指标的研究[J].水利水电工程设计,2002(1).
[21] 中国地质大学(武汉)工程学院等.河南伊河陆浑水库坝基渗透稳定性研究.1999.
[22] 周纪芗.实用回归分析方法[M].上海:上海科学技术出版社,1990.
[23] 陈希孺、王松桂.近代回归分析——原理方法即应用[M].合肥:安徽教育出版社,1987.
[24] 白新桂.数据分析与试验优化设计[M].北京:清华大学出版社,1986.
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