CN102867110A - Rainstorm disaster risk evaluation method for foundation slope of transmission line tower - Google Patents
Rainstorm disaster risk evaluation method for foundation slope of transmission line tower Download PDFInfo
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Abstract
The invention discloses a rainstorm disaster risk evaluation method for a foundation slope of a transmission line tower. The method comprises the following steps of: obtaining disaster causing factors controlling the rainstorm risk of the foundation slope of the transmission line tower according to extensive disaster statistics and artificial rain slope corrosion test statistics; and performing quantification and normalization processing on the disaster causing factors and slope stability, and calculating a weight vector of influence of each disaster causing factor on the disaster causing of rainstorm by adopting an improved hierarchical analysis calculation program; establishing a mapping relationship between the disaster causing factors and a slope stability safety coefficient by adopting an artificial intelligence method and an improved back propagation (BP) network to obtain a mathematical model for evaluating the rainstorm landslide risk of the foundation slope of the transmission power tower; quantifying vulnerability factors, obtaining a weight vector of influence of each vulnerability factor on the disaster causing risk of the rainstorm by adopting an expert analysis method, and establishing a rainstorm risk evaluation mathematical model for the foundation slope of the transmission line tower according to a relationship that the risk is equal to a product of danger and vulnerability; and accurately evaluating the rainstorm risk of the foundation slope of a specified transmission line tower.
Description
Technical field
The present invention relates to a kind of side slope Rainfall Disaster methods of risk assessment, especially relate to a kind of electric power line pole tower basis side slope Rainfall Disaster methods of risk assessment.
Background technology
Transmission line of electricity is the important component part of electrical network, and the safe and stable operation of transmission line of electricity directly has influence on stability and the power supply reliability of electrical network.Current, land resource is day by day valuable, and mountain route is more and more, and power department faces a large amount of slope projects inevitably, and Problems of Slope Stability becomes and becomes increasingly conspicuous.Because heavy rain causes soil erosion, the broad sense landslide disasters such as closely-related slope wash, landslide, slump happen occasionally with it, jeopardize electric power line pole tower safety, severe patient even cause circuit to fall rod disconnection.Therefore, prevent electric power line pole tower basis side slope Rainfall Disaster accident, a very important job that guarantees the transmission line of electricity safe and stable operation, being subject to gradually the attention of Electric Design department, power supply management department, is the basis that prevents the Rainfall Disaster accident and carry out the side slope Rainfall Disaster risk assessment of electric power line pole tower basis, early warning.
It is generally acknowledged, for different purposes or service object, can carry out dissimilar disaster risk assessment, according to landslide disaster scope of assessment or area, the assessment of side slope risk can be divided into an assessment, face assessment and regional assessment.For the transmission line foundation side slope, way is that concrete side slope is formed evaluating system more accurate, that quantize preferably, for combat a natural disaster, the disaster relief and enforcement prevention and cure project provide foundation, belong to an assessment category, need to consider the factors such as overhead line structures foundation structure feature, topography and landform character, formation lithology, tectonic structure and vegetation feature.In addition, although the slope instability that heavy rain causes belongs to the slope project research range, its methods of risk assessment can not be copied mechanically and applied indiscriminately existing slope stability estimation method, and it is relevant with rainfall on slope land intensity etc.
At present, in the technology both domestic and external, the method for evaluation studies does not appear also carrying out because of the risk that heavy rain brings to electric power line pole tower basis side slope.
Summary of the invention
Technical matters to be solved by this invention just provides a kind of electric power line pole tower basis side slope Rainfall Disaster methods of risk assessment that is applicable to design and the supervision and management of electric power line pole tower basis, mountain area side slope.
Solve the problems of the technologies described above, the technical solution used in the present invention is:
A kind of electric power line pole tower basis side slope Rainfall Disaster methods of risk assessment may further comprise the steps:
S1 determines to cause the calamity factor:
From comprise critical rainfall amount, the gradient, sloping height, domatic morphologic characteristics, formation lithology, tectonic structure, soil body characterisitic parameter and slope vegetation feature, according to a large amount of regional disaster statisticses and rainmaking slope erosion test findings statistics, choose successively at least 4 by causing the most serious factor sequence of calamity;
S2 quantizes causing the calamity factor, slope stability, normalization and weight are determined:
S2-1 quantizes to adopt Delphi method, statistical analysis method, membership function method and information Contents Method, and one of them carries out, preferred membership function method: each qualitative index is divided into 3 grades, give boundary value by giving each grade, then determine its subordinate function by the method for linear difference, finish the quantification of qualitative index;
The data that S2-2 quantizes are carried out normalized take the sigmoid function as activation function, the data that quantize are converted into [0.1-0.9] interval numerical value;
The classification of S2-3 slope stability: stable, basicly stable, unstable, carry out normalized take the sigmoid function as activation function, slope stability is converted into [0.1-0.9] interval safety coefficient;
S2-4 makes up and to comprise the hierarchy Model that destination layer, rule layer, three levels of solution layer consist of, and destination layer is upper, rule layer in, solution layer is lower; Destination layer is slope stability, and solution layer adopts and improves the weight vectors that level analytical calculation program obtains each level for respectively causing the calamity factor;
S3 determines the risk assessment model:
Take a large amount of regional disaster statisticses and rainmaking slope erosion test findings as training sample, adopt the BP Artificial Neural Network, weight vectors between the given BP network number of plies and the equivalent layer, adopt the modified BP neural network calculation procedure neural network to be trained until reach error requirements, acquisition causes the mapping relations of the calamity factor and safety factor of slope stability, i.e. the mathematical model of electric power line pole tower basis side slope heavy rain Landslide hazard assessment;
S4 determines the risk assessment models:
Quantize and obtain each vulnerability degree factor pair heavy rain by the analysis expert method to cause the weight vectors that the calamity risk affects according to electric power line pole tower type of foundation, disaster district and the vulnerability degree factors such as pole and tower foundation distance and transmission line of electricity electric pressure, with in the world comparatively the approval the risk expression formula: risk=risk factor * vulnerability degree, be that risk comprises the possibility (risk factor) of risk generation and the degree of damage (vulnerability degree) that risk is brought, obtain electric power line pole tower basis side slope heavy rain risk assessment mathematical model;
S5 assesses:
According to the risk mathematical model evaluate, input concrete electric power line pole tower basis side slope to be assessed and rainfall amount and assess and obtain assessment result.
The tectonic structure of described step S1 obtains according to a large amount of disaster statisticses as causing the calamity factor, comprises single-layer medium side slope, multilayered medium side slope (such as the side slope of granite residual soil, completely weathered granite composition).
Among the described step S4, the quantification of each vulnerability degree factor and weight are to obtain according to expert's point system, and vulnerability degree V calculates as follows:
V=ω
iX
i
ω in the formula
iBe the weight of each vulnerability degree factor, X
iQuantized value for each vulnerability degree factor.
Principle of the present invention is: the related factors of determining control electric power line pole tower basis side slope Rainfall Disaster danger, adopt artificial intelligence method to set up the mapping relations that cause the calamity factor and safety factor of slope stability, obtain the mathematical model of electric power line pole tower basis side slope heavy rain Landslide hazard assessment, according in the world comparatively the approval the risk expression formula: risk=risk factor * vulnerability degree, be that risk comprises the possibility (risk factor) of risk generation and the degree of damage (vulnerability degree) that risk is brought, set up electric power line pole tower basis side slope heavy rain risk assessment mathematical model, realize specifying the accurate evaluation of electric power line pole tower basis side slope heavy rain risk.
Advantage of the present invention is, assessment is based on a large amount of disaster field investigation and rainmaking slope erosion test findings statistics is carried out, assessment result to electric power line pole tower basis side slope Rainfall Disaster risk is more true and reliable, has more specific aim, realizes the assessment to concrete side slope.Of the present invention applying, will effectively help Electric Design department, power supply management department, science, exactly electric power line pole tower basis side slope Rainfall Disaster risk is assessed, take targetedly early warning and prophylactico-therapeutic measures to improve it and combat a natural disaster performance, more with becoming more meticulous the management electrical network.
Description of drawings
Accompanying drawing is process flow diagram of the present invention.
Embodiment
Below, in conjunction with accompanying drawing of the present invention embodiment is further described.
As shown in drawings, a kind of electric power line pole tower basis side slope Rainfall Disaster methods of risk assessment that the present invention proposes in force, specifically may further comprise the steps:
(1) causes determining of the calamity factor
Analyze Rainfall Disaster influence factor, to determine to cause the calamity factor be the first step of carrying out the Rainfall Disaster risk assessment.The influence factor of Rainfall Disaster comprises critical rainfall amount, the gradient, sloping height, domatic morphologic characteristics, formation lithology, tectonic structure, soil body characterisitic parameter, slope vegetation feature etc., determine to cause the calamity factor, set up difference and local geographic entity that evaluation system will take into full account the zone.The present invention adds up the major control factor that draws electric power line pole tower basis side slope Rainfall Disaster risk according to a large amount of regional disaster statisticses and rainmaking slope erosion test findings, chooses successively at least 4 by causing the most serious factor sequence of calamity.
(2) slope stability classification
In conjunction with electric power line pole tower basis side slope Rainfall Disaster risk criteria for classification, slope stability is divided into 3 grades, stable, basicly stable, unstable.
(3) quantize causing the calamity factor, slope stability, the determining of normalization and weight
The quantitative target that causes the calamity factor directly according to actual value to weigh, Delphi method, statistical analysis method, membership function method and information Contents Method are adopted in the quantification of qualitative index, and one of them carries out, preferred membership function method, each qualitative index is divided into 3 grades, give boundary value by giving each grade, then determine its subordinate function by the method for linear difference, finish the quantification of qualitative index.
The data that quantize are carried out normalized take the sigmoid function as activation function, be translated into [0.1-0.9] interval numerical value.
Structure comprises the hierarchy Model that three levels of destination layer, rule layer, solution layer consist of, and destination layer is upper, rule layer in, solution layer is lower; Destination layer is slope stability, and solution layer adopts and improves the weight vectors that level analytical calculation program obtains each level for respectively causing the calamity factor.
(4) the BP artificial neural network is determined the risk assessment model
Take a large amount of regional disaster statisticses and rainmaking slope erosion test findings as training sample, adopt the BP Artificial Neural Network, weight vectors between the given BP network number of plies and the equivalent layer, adopt the modified BP neural network calculation procedure neural network to be trained until reach error requirements, acquisition causes the mapping relations of the calamity factor and safety factor of slope stability, determines the mathematical model of electric power line pole tower basis side slope heavy rain Landslide hazard assessment.
(5) risk assessment models
Quantize and obtain each vulnerability degree factor pair heavy rain by the analysis expert method to cause the weight vectors that the calamity risk affects according to electric power line pole tower type of foundation, disaster district and the vulnerability degree factors such as pole and tower foundation distance and transmission line of electricity electric pressure, the quantification of each vulnerability degree factor and weight are to obtain according to expert's point system, and vulnerability degree V calculates as follows:
V=ω
iX
i
ω in the formula
iBe the weight of each vulnerability degree factor, X
iQuantized value for each vulnerability degree factor.
With in the world comparatively the approval the risk expression formula: risk=risk factor * vulnerability degree, be that risk comprises the possibility (risk factor) of risk generation and the degree of damage (vulnerability degree) that risk is brought, obtain electric power line pole tower basis side slope heavy rain risk assessment mathematical model.
(6) assess
According to the risk mathematical model evaluate, input parameter to be assessed to specifying electric power line pole tower basis side slope to carry out the heavy rain risk assessment, obtain assessment result.
As an example, the present invention carries out the heavy rain risk assessment to an electric power line pole tower basis, somewhere side slope.
This grade of side slope: 41 °, sloping high 16.2m, soil body dry density: 1650kg/m
2, formation lithology: granite residual soil, α: 38%, electric power line pole tower type of foundation: digging foundation, disaster district and pole and tower foundation distance: 2.5m, transmission line of electricity electric pressure: 500kV.
Table 1 is the major control factor and the corresponding quantitative criteria of this area's Rainfall Disaster risk.
Table 1 somewhere electric power line pole tower basis side slope cause the calamity factor and corresponding quantitative criteria
Remarks: α is≤the shared ratio of 0.075mm granular mass
Table 2 is the subnetwork training sample data after the normalization.Output (0.9,0.1,0.1) represents stability of slope, and it is basicly stable that (0.1,0.9,0.1) represents side slope, and it is unstable that (0.1,0.1,0.9) represents side slope.
Part BP training sample data after table 2 normalization
Utilize the BP network of training that certain basic side slope is carried out the heavy rain assessment of risks, sample data is: slope angle: 41 °, rainfall amount: 50 years maximum raininess 235mm/h * 2h(and 3h), dry density: 1650kg/m2, lithology: granite residual soil, α: 38%, the high 16.2m in slope, the result of assessment is respectively (0.1043,0.8251,0.1020) and (0.1015,0.1026,0.8954), illustrate that unstability the landslide appears and in continuous rainfall 3h this electric power line pole tower basis side slope possibly under local 50 years maximum raininess conditions.
Table 3 is quantification and the weight of this area's vulnerability degree factor.The vulnerability degree that calculates this electric power line pole tower basis side slope is 5, and under local 50 years maximum raininess conditions, during continuous rainfall 3h, hazard assessment is: (0.1015,0.1026,0.8954) * 5 show that danger classes is high.
Quantification and the weight of electric power line pole tower basis, the table 3 somewhere side slope vulnerability degree factor
Claims (4)
1. electric power line pole tower basis side slope Rainfall Disaster methods of risk assessment may further comprise the steps:
S1 determines to cause the calamity factor:
From comprise critical rainfall amount, the gradient, sloping height, domatic morphologic characteristics, formation lithology, tectonic structure, soil body characterisitic parameter and slope vegetation feature, according to a large amount of regional disaster statisticses and rainmaking slope erosion test findings statistics, choose successively at least 4 by causing the most serious factor sequence of calamity;
S2 quantizes causing the calamity factor, slope stability, normalization and weight are determined:
S3 determines the risk assessment model:
Take a large amount of regional disaster statisticses and rainmaking slope erosion test findings as training sample, adopt the BP Artificial Neural Network, weight vectors between the given BP network number of plies and the equivalent layer, adopt the modified BP neural network calculation procedure neural network to be trained until reach error requirements, acquisition causes the mapping relations of the calamity factor and safety factor of slope stability, i.e. the mathematical model of electric power line pole tower basis side slope heavy rain Landslide hazard assessment;
S4 determines the risk assessment models:
Quantize and obtain each vulnerability degree factor pair heavy rain by the analysis expert method to cause the weight vectors that the calamity risk affects according to electric power line pole tower type of foundation, disaster district and the vulnerability degree factors such as pole and tower foundation distance and transmission line of electricity electric pressure, with in the world comparatively the approval the risk expression formula: risk=risk factor * vulnerability degree, be that risk comprises the possibility of risk generation and the degree of damage that risk is brought, obtain electric power line pole tower basis side slope heavy rain risk assessment mathematical model;
S5 assesses:
According to the risk mathematical model evaluate, input concrete electric power line pole tower basis side slope to be assessed and rainfall amount and assess and obtain assessment result.
2. electric power line pole tower according to claim 1 basis side slope Rainfall Disaster methods of risk assessment, it is characterized in that: the tectonic structure of described step S1 obtains according to a large amount of disaster statisticses as causing the calamity factor, comprises single-layer medium side slope, multilayered medium side slope.
3. electric power line pole tower according to claim 1 basis side slope Rainfall Disaster methods of risk assessment, it is characterized in that: described step S2 comprises following substep:
S2-1 quantizes to adopt Delphi method, statistical analysis method, membership function method and information Contents Method, and one of them carries out, preferred membership function method: each qualitative index is divided into 3 grades, give boundary value by giving each grade, then determine its subordinate function by the method for linear difference, finish the quantification of qualitative index;
The data that S2-2 quantizes are carried out normalized take the sigmoid function as activation function, the data that quantize are converted into [0.1-0.9] interval numerical value;
The classification of S2-3 slope stability: stable, basicly stable, unstable, carry out normalized take the sigmoid function as activation function, slope stability is converted into [0.1-0.9] interval safety coefficient;
S2-4 makes up and to comprise the hierarchy Model that destination layer, rule layer, three levels of solution layer consist of, and destination layer is upper, rule layer in, solution layer is lower; Destination layer is slope stability, and solution layer adopts and improves the weight vectors that level analytical calculation program obtains each level for respectively causing the calamity factor.
4. electric power line pole tower according to claim 1 basis side slope Rainfall Disaster methods of risk assessment, it is characterized in that: among the described step S4, the quantification of each vulnerability degree factor and weight are that vulnerability degree V calculates as follows according to the acquisition of expert's point system:
V=ω
iX
i
ω in the formula
iBe the weight of each vulnerability degree factor, X
iQuantized value for each vulnerability degree factor.
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| CN114066165A (en) * | 2021-10-20 | 2022-02-18 | 国网黑龙江省电力有限公司电力科学研究院 | Improved power transmission line high-order landslide risk evaluation system and method |
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| CN115510669A (en) * | 2022-10-11 | 2022-12-23 | 昆明理工大学 | Power transmission line seismic loss assessment method based on GIS fuzzy analysis |
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