CN106709663A - Method for determining human body stability in flood based on city image data - Google Patents

Method for determining human body stability in flood based on city image data Download PDF

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CN106709663A
CN106709663A CN201710002224.XA CN201710002224A CN106709663A CN 106709663 A CN106709663 A CN 106709663A CN 201710002224 A CN201710002224 A CN 201710002224A CN 106709663 A CN106709663 A CN 106709663A
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夏军强
果鹏
陈倩
周美蓉
李洁
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Abstract

The invention discloses a method for determining human body stability in flood based on city image data. The method comprises the following steps of firstly proposing a method for determining a scale relationship between a human body in the data and an actual human body according to whether a reference object with a known length exists in a video or a picture or not, and determining water depth of the position in which the human body is located; for video data with a floating object, determining flow velocity of a water surface according to a moving distance of the floating object in a period of time, considering a relationship between the flow velocity of the water surface and average flow velocity of a vertical line, and calculating average flow velocity of water flow in front of the human body; for the picture or video data without the floating object, measuring backwater height of the position in which the human body is located, and calculating flow velocity of the position in which the human body is located by adopting a Bernoulli equation; and finally checking the reliability of the method by utilizing a human body instability curve in the flood and existing human body instability data. The method provided by the invention facilitates the establishment of instability standards of the human body in the flood and provides reference bases for city flood risk analysis and management.

Description

A kind of method that human body stability in flood is determined based on city image data
Technical field
The present invention relates to hydraulic engineering technical field, particularly relate to one kind and people in flood is determined based on city image data The method of body stability.
Background technology
China is always one of deep country threatened by flood damage, the personnel that the super standard flood caused by heavy rain is caused Injures and deaths are very serious.According to incompletely statistics, between 1950-2000, every year because the directly dead number of flood is about 5 200 People.From after 2000, because the direct death toll of big flood drops to average annual about 1 600 people.But with the swift and violent growth of current census, The continuous expansion of mankind's activity scope, and global warming is the climate change of principal character, increases flood generation Probability, the life security of personnel is still faced with very stern challenge.For example, there is extra torrential rain flood in July, 2012 Beijing Water, causes 79 people dead in 2d.As can be seen here, the easy unstability of human body under flood effect, pedestrian washes away that rear pole has by flood can Can be directly dead.The unstability standard of human body in flood is hence set up, it is significant to flood risk assessment.
With the development of science and technology, shooting, photograph have turned into indispensable one such as urban transportation and constituent parts security work Part, is also the important means for recording peb process.Human body Instability in image data has reacted actual flood regime, more Be conducive to the development of correlative study.Therefore, how human body stability in flood is determined according to city image data, it will help build The unstability standard of human body in vertical flood, can more promote extending to vehicle, house etc. and obtained by object instability condition is flooded, and will be city City's risk analysis on flood and management provide reference frame.
The content of the invention
To be to estimate it is an object of the present invention to provide a kind of method that human body stability in flood is determined based on city image data Human body degree of danger, the escape for instructing masses suffering from disaster and cities'flood hazard analysis provide scientific basis in calculation flood.
Principle of the invention is：Have between object length and actual object length in the flood coherent video data of city Certain proportionate relationship, determines therefrom that the ratio chi of map range and actual range, and then calculate the depth of water of human body position；Again According to the floating distance of object in a period of time in video, or in photo the human body position depth of water heap soil or fertilizer over and around the roots it is high with Bernoulli Jacob side Journey, determines the flow velocity size of human body position.The present invention is based on existing image data, it is determined that than chi relation, calculating human body The depth of water and flow velocity of unstability, using the curve of human body unstability in flood, the accuracy of human body unstability data in verifying data.Propose A kind of method that human body stability in flood is determined based on city image data.
The present invention provides a kind of method that human body stability in flood is determined based on city image data, including following step Suddenly：
Step (1), proposes the method than chi relation of human body and actual human body in image data, and then determines human body place The depth of water size of position, comprises the following steps that：
Step (1.1), if having the object of reference of known physical length near human body in image data, according to object of reference Physical length determines proportionate relationship with the upper length of figure；
Step (1.2), if not having that there is the object of reference of known physical length in image data, with image data location Average height be reference frame, using the relation of height and the brachium of human body, determine the arm length of human body, then determine data Middle object physical length and the proportionate relationship for scheming upper length；
Step (1.3), according to the proportionate relationship that step (1.1) or step (1.2) determine, calculates and carrys out flowing water depth accordingly；
Step (2), the video data with floating object, picture information and video without floating object are divided into by image data Data, then calculates the flow rate of water flow in video data, according to Bernoulli equation according to floating object displacement in video data The flow rate of water flow in picture or the video data without floating object is calculated, is comprised the following steps that：
Step (2.1), for the video data with floating object, the distance that can be moved according to floating object in a period of time is true Determine water surface flow velocity, it is considered to water surface flow velocity and the relation of mean velocity in vertical, calculate the mean flow rate of human body front current；
Step (2.2), for picture or the video data without floating object, it is measurable go out human body position choke water height Degree, then the mean flow rate of the current in front of human body is solved using Bernoulli equation；
Step (3), using the reliability of the human body unstability curve method of inspection in the flood set up, comprises the following steps that：
Step (3.1), by theory analysis, sets up the critical flow velocity curve of human body unstability, and use model human body unstability Tank data calibration formula relevant parameter；
Step (3.2), using the formula of calibration in step (3.1), real human body unstability in the case of drafting different water depth Curve；
Step (3.3), by the test data of human body unstability in the flood for obtaining in step (1) and step (2), other people The curve drawn with step (3.2) of test data of true man's unstability contrasted, check the reliability of the above method.
In the step (1.1), image data is than chi S：
Wherein, LpIt is the physical length of the object of reference of known length in image data, LsIt is known length in image data Length on the figure of object of reference；The object of reference of the known length of selection should be close to the human body in flood.
In the step (1.2), image data is than chi S：
S=LaP/LaS
Wherein, LaPIt is the actual brachium of human body in image data, LaP=HPavg× 34.4%, HPavgWhere image data The actual average height of the human body in region, LaSIt is the figure upperarm length of human body in image data.
In the step (1.3), if having the object of reference of known physical length, actual water in image data in image data Deep H is：
H=Hp-HbPOUT
Wherein, HPIt is the actual height of human body in image data, HP=LaP÷ 34.4%, LapIt is human body in image data Actual brachium；HbPOUTIt is the actual height that human body in image data surfaces, HbPOUT=HbSOUT× S, S are image data Than chi, this is determined than chi using step (1.1) methods described, HbSOUTLength on the figure surfaced for human body in image data.
In the step (1.3), if without the object of reference of known physical length in image data, it is actual in image data Depth of water H is：
H=HPavg-HbPOUT
Wherein, HPavgIt is the actual average height of the human body of image data region；HbPOUTIt is human body in image data The actual height for surfacing；HbPOUT=HbSOUT× S, S are the ratio chi of image data, and this uses step (1.2) described side than chi Method determination, HbSOUTLength on the figure surfaced for human body in image data.
In the step (2.1), with the mean velocity in vertical U near human body in video dataVLIt is approximate to represent human body front The mean flow rate U of current, the computing formula of the mean flow rate U of human body front current is in video data：
Wherein, UmaxIt is the actual flow velocity of the water surface in video data,Δ T be the time period, Δ L be Move distance in the time period of Δ T on figure；S is the ratio chi of image data.
In the step (2.2), the height of swell Δ H of human body position is first measured, then asked using Bernoulli equation The mean flow rate of solution human body front current：
Wherein, Δ H is the height of swell, and g is acceleration of gravity, and S is the ratio chi of image data.
The inventive method, its advantage is：
(1) determination method of 2 kinds of actual objects with image data than chi relation is proposed.As having really near human body in data The object of measured length, the ratio using the upper length of physical length and figure is used as than chi；As do not determined length near human body in data Object, the average height of data location is taken for reference value, according to the relation between human body brachium and height, it is determined that actual The ratio of brachium and figure upperarm length is used as than chi；
(2) depth of water and flow velocity are determined according to than chi relation, the computational methods of flow velocity are divided into 2 kinds.For video data, The distance that can be moved according to floating object in a period of time determines water surface flow rate of water flow, it is considered to the pass of water surface flow velocity and mean flow rate System, calculates the mean flow rate of current current；For picture information, it is measurable go out human body position the height of swell, then The flow velocity of human body position is solved using Bernoulli equation.
(3) using the reliability of the human body unstability curve method of inspection in the flood set up.The method of proposition will be helpful to The unstability standard of human body in flood is set up, while also will be that the risk analysis on flood such as city, Tan Qu, flood storage and detention basin and management are provided Reference frame.
Brief description of the drawings
The flow chart of Fig. 1 the inventive method；
Partes corporis humani divides linear measure longimetry schematic diagram in Fig. 2 floods；
Two sectional schematic diagrams in Fig. 3 Bernoulli equations；
The human body unstability data that Fig. 4 human body unstability curves and the present invention are obtained compare.
Specific embodiment
Below in conjunction with the accompanying drawings, the invention will be further described.As Figure 1-Figure 4, it is a kind of to be based on city image data The method for determining human body stability in flood, comprises the following steps：
Step (1), proposes the method than chi relation of human body and actual human body in image data, and then determines human body place The depth of water size of position, comprises the following steps that：
Step (1.1), if having the object of reference of known length near human body in image data, according to the reality of object of reference Length determines proportionate relationship with the upper length of figure；
Consider shooting angle, apart from the problems such as, it is known that the object of reference of physical length should be close to flood in human body.It is assumed that shadow As the physical length of the object of reference of known physical length in data is Lp, length is L on figures, then the image data is than chi S：
Step (1.2), if the not object of reference with known length in image data, as shown in Fig. 2 with image data institute Average height in area is reference frame, using height and the relation of brachium of human body, the arm length of human body is determined, in terms of Calculate object physical length and the ratio chi for scheming upper length in image data；
Gordon et al. (1989) researchs show that the brachium of people is about the 34.3% of height, takes Fig. 2 regions Human body actual average height be HPavg, then the actual brachium L of human bodyaPFor：
LaP=HPavg× 34.4% (2)
And human arm bending in Fig. 2, L can be divided intoa1And La2Two parts, thus calculate the figure upperarm length L of human bodyaSFor：
LaS=La1+La2 (3)
So it is than chi S:
S=LaP/LaS (4)
Step (1.3), the ratio chi relation S of map range and actual range is determined according to step (1.1) or step (1.2), Calculate again and carry out flowing water depth accordingly.
If there is the object of reference of known physical length, then in survey calculation Fig. 2 first on the figure of human body in image data Brachium LaS, it is a length of further according to the actual arm that human body is calculated than chi：
LaP=LaS×S (5)
So actual height H of human bodyPFor：
HP=LaP÷ 34.4% (6)
Human body surfaces partly in Fig. 2 bending, can be divided into Lb1、Lb2And Lb33 parts, then scheme upper human body and surface Length be HbSOUTFor：
HbSOUT=Lb1+Lb2+Lb3 (7)
Calculate the actual height H that human body surfacesbPOUTFor：
HbPOUT=HbSOUT×S (8)
So actual depth of water H is the difference of the actual height that the actual height of human body surfaces with human body：
H=Hp-HbPOUT (9)
If without the object of known physical length in image data, then also according to the length that the upper human body of figure surfaces Degree and the length surfaced than chi calculating actual human body, simply calculate the depth of water and are changed to following formula：
H=HPavg-HbPOUT (10)
Step (2), the video data with floating object, picture information and video without floating object are divided into by image data Data, then calculates the flow rate of water flow in video data, according to Bernoulli equation according to floating object displacement in video data The flow rate of water flow in picture or the video data without floating object is calculated, is comprised the following steps that：
Step (2.1), for the video data with floating object, can according to a period of time in floating object movement away from From determination water surface flow velocity, it is considered to water surface flow velocity and the relation of mean velocity in vertical, the mean flow rate of human body front current is calculated；
If there is certain floating object in video data, the distance of Δ L is moved on figure in Δ T time section, then the water surface Actual flow velocity UmaxFor:
Now there are some researches show the Peak Flow Rate at the water surface is bigger than mean velocity in vertical by 16%, therefore mean velocity in vertical UVLFor:
What above formula was calculated is the mean velocity in vertical near human body in video data, therefore the flow velocity can approximate representative The mean flow rate of body front current, i.e. mean flow rate in front of human body is：
U=UVL (13)
Step (2.2), for picture or for the video data without floating object, such as Fig. 3 first measures human body institute in place The height of swell Δ H for putting, then the mean flow rate of human body front current is solved using Bernoulli equation.
Position of the human body in water is as shown in figure 3, the Bernoulli equation for section 1-1 ' and 2-2 ' is：
In formula, the physical significance that equation or so is 3 is respectively level head, pressure head and kinetic head.ρ is that current are close Degree, g is local acceleration of gravity.1-1 ' sections have：Z1It is the absolute altitude in certain point relative datum face in section 1-1 ', P1It is the point Pressure, U1It is the flow velocity of the point.Corresponding 2-2 ' sections have, Z2It is the absolute altitude in certain point relative datum face in section 2-2 ', P2It is The pressure of the point, U2It is the flow velocity of the point.
Invention is approximately considered current for constant gradually varied flow, takes the mean flow rate phase of human body front mean flow rate and section 1-1 ' Deng the flow velocity U of section 2-2 ' where human body2=0m/s, so section 2-2 ' piezometric heads (level head and pressure head it With) increase, produce choking water for Δ H.The depth of water of two sections of 1-1 ' and 2-2 ' is respectively H in Fig. 31、H2(Δ H=H2-H1).Gradually It is constant that the cross-section of river of unsteady flow has piezometric head, and flow rate of water flow is uniformly distributed vertical, is mean flow rate.In Fig. 3 Take face on the basis of ground, then the piezometric head of 1-1 ' and 2-2 ' sections is respectively：
1-1 ' sections：
2-2 ' sections：
Substitute into and use Bernoulli equation (formula 14), the mean flow rate in the actual flood of solution in front of human body, i.e.,：
In formula, g is local acceleration of gravity.Can be obtained through equation conversion：
Step (3), using the reliability of the human body unstability curve method of inspection in the flood set up, comprises the following steps that：
Step (3.1), by theory analysis, sets up the critical flow velocity formula of human body unstability in flood, and use model person The relevant parameter of the tank data calibration formula of body unstability, the critical song of human body unstability in flood is drawn using the formula after calibration Line；
Xia etc. (2014) establishes height HP, body weight MPHuman body tumble unstability critical flow velocity computing formula：
In formula：ρ is jet density, a1, b1, a2, b2It is the parameter related to the physical trait of people, is computed that a can be obtained1= 0.633、b1=0.367, a2=1.015 × 10-3m3/kg、b2=-4.937 × 10-3m3.α and β is needed according to manikin unstability Flume test result calibration, calculate α=3.472, β=0.188.
Step (3.2), using the formula of calibration in step (3.1), real human body unstability in the case of drafting different water depth Curve；
Step (3.3), the test data of human body unstability is (during human body unstability in the flood that step (1) and step (2) are obtained Flow rate of water flow and the depth of water), the test data (flow rate of water flow and the depth of water during human body unstability) of other people true man's unstability with step Suddenly the curve that (3.2) draw is contrasted, and checks the reliability of the above method.
By human body unstability curve, flood acts on the flow condition data of lower human body unstability, and Abt to Fig. 4 in image data (1989), Karvonen (2000), Field, the experimental data of the true unstabilitys of Chanson (2014) are contrasted, it can be seen that Xia etc. (2013) propose unstability standard curve it is relatively low, be because formula carries out calibration using model human body flume test result, The corrective action of human body is not considered.The data of human body unstability are more leaned on the data of other true man's flume tests in image data Closely, it is believed that method is reliable.

Claims (7)

1. a kind of method that human body stability in flood is determined based on city image data, it is characterised in that comprise the following steps：
Step (1), proposes the method than chi relation of human body and actual human body in image data, and then determines human body position Depth of water size, comprise the following steps that：
Step (1.1), if having the object of reference of known physical length near human body in image data, according to the reality of object of reference Length determines proportionate relationship with the upper length of figure；
Step (1.2), if not having that there is the object of reference of known physical length in image data, with the flat of image data location Equal height is reference frame, using height and the relation of brachium of human body, determines thing in the arm length of human body, then determination data Body physical length and the proportionate relationship for scheming upper length；
Step (1.3), according to the proportionate relationship that step (1.1) or step (1.2) determine, calculates and carrys out flowing water depth accordingly；
Step (2), by image data be divided into the video data with floating object, picture information and without floating object video money Material, then calculates the flow rate of water flow in video data, according to Bernoulli equation meter according to floating object displacement in video data Flow rate of water flow in nomogram piece or the video data without floating object, comprises the following steps that：
Step (2.1), for the video data with floating object, the distance that can be moved according to floating object in a period of time determines water Surface current speed, it is considered to water surface flow velocity and the relation of mean velocity in vertical, calculates the mean flow rate of human body front current；
Step (2.2), for picture or the video data without floating object, it is measurable go out human body position the height of swell, The mean flow rate of the current in front of human body is solved using Bernoulli equation again；
Step (3), using the reliability of the human body unstability curve method of inspection in the flood set up, comprises the following steps that：
Step (3.1), by theory analysis, sets up the critical flow velocity curve of human body unstability, and using the water of model human body unstability Slot number according to calibration formula relevant parameter；
Step (3.2), using the formula of calibration in step (3.1), draws the curve of real human body unstability in the case of different water depth；
Step (3.3), by the test data of human body unstability in the flood for obtaining in step (1) and step (2), other people true The curve that the test data of people's unstability is drawn with step (3.2) is contrasted, and checks the reliability of the above method.
2. the method for human body stability in flood being determined based on city image data according to claim 1, it is characterised in that：
In the step (1.1), image data is than chi S：
S = L P L S
Wherein, LpIt is the physical length of the object of reference of known length in image data, LsIt is the reference of known length in image data Length on the figure of thing；The object of reference of the known length of selection should be close to the human body in flood.
3. the method for human body stability in flood being determined based on city image data according to claim 1, it is characterised in that：
In the step (1.2), image data is than chi S：
S=LaP/LaS
Wherein, LaPIt is the actual brachium of human body in image data, LaP=HPavg× 34.4%, HPavgIt is image data region Human body actual average height, LaSIt is the figure upperarm length of human body in image data.
4. the method for human body stability in flood being determined based on city image data according to claim 1, it is characterised in that：
In the step (1.3), if having the object of reference of known physical length, actual depth of water H in image data in image data For：
H=Hp-HbPOUT
Wherein, HPIt is the actual height of human body in image data, HP=LaP÷ 34.4%, LapIt is the reality of human body in image data Brachium；HbPOUTIt is the actual height that human body in image data surfaces, HbPOUT=HbSOUT× S, S are the ratio chi of image data, This is than chi using the determination of step (1.1) methods described, HbSOUTLength on the figure surfaced for human body in image data.
5. the method for human body stability in flood being determined based on city image data according to claim 1, it is characterised in that：
In the step (1.3), if without the object of reference of known physical length, the actual depth of water in image data in image data H is：
H=HPavg-HbPOUT
Wherein, HPavgIt is the actual average height of the human body of image data region；HbPOUTFor human body exposes in image data The actual height of the water surface；HbPOUT=HbSOUT× S, S are the ratio chi of image data, and this is more true using step (1.2) methods described than chi It is fixed, HbSOUTLength on the figure surfaced for human body in image data.
6. the method for human body stability in flood being determined based on city image data according to claim 1, it is characterised in that：
In the step (2.1), with the mean velocity in vertical U near human body in video dataVLIt is approximate to represent human body front current Mean flow rate U, the computing formula of mean flow rate U of human body front current is in video data：
U = U V L = U max 1 + 16 %
Wherein, UmaxIt is the actual flow velocity of the water surface in video data,Δ T is the time period, and Δ L is in Δ T Time period in move distance on figure；S is the ratio chi of image data.
7. the method for human body stability in flood being determined based on city image data according to claim 1, it is characterised in that：
In the step (2.2), the height of swell Δ H of human body position is first measured, then people is solved using Bernoulli equation The mean flow rate of body front current：
U = 2 g S Δ H
Wherein, Δ H is the height of swell, and g is acceleration of gravity, and S is the ratio chi of image data.
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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP3703009A4 (en) * 2017-10-27 2021-06-23 ASICS Corporation Motion state evaluation system, motion state evaluation device, motion state evaluation server, motion state evaluation method, and motion state evaluation program
CN113314013A (en) * 2021-05-17 2021-08-27 武汉大学 Testing device and testing method for escaping from underground space by flood along variable-gradient stairs

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2008110909A2 (en) * 2007-03-15 2008-09-18 Universita' Degli Studi Di Palermo Measurement method for measuring the peak flow discharges and the channel bed roughness in a natural or artificial water course and related system
US20100088077A1 (en) * 2008-10-02 2010-04-08 Geza Kisch Accurate methods for modeling the spatial distribution for irrigation systems for land scapes
CN105808859A (en) * 2016-03-11 2016-07-27 武汉大学 Method for judging stability degree of vehicle under action of flood

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2008110909A2 (en) * 2007-03-15 2008-09-18 Universita' Degli Studi Di Palermo Measurement method for measuring the peak flow discharges and the channel bed roughness in a natural or artificial water course and related system
US20100088077A1 (en) * 2008-10-02 2010-04-08 Geza Kisch Accurate methods for modeling the spatial distribution for irrigation systems for land scapes
CN105808859A (en) * 2016-03-11 2016-07-27 武汉大学 Method for judging stability degree of vehicle under action of flood

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
夏军强 等: "现有洪水中人体失稳标准的评价及改进", 《同济大学学报（自然科学版）》 *
曹留伟: "人在洪水中临界失稳判定公式的对比及分析", 《人民长江》 *

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP3703009A4 (en) * 2017-10-27 2021-06-23 ASICS Corporation Motion state evaluation system, motion state evaluation device, motion state evaluation server, motion state evaluation method, and motion state evaluation program
US11182599B2 (en) 2017-10-27 2021-11-23 Asics Corporation Motion state evaluation system, motion state evaluation device, motion state evaluation server, motion state evaluation method, and motion state evaluation program
CN113314013A (en) * 2021-05-17 2021-08-27 武汉大学 Testing device and testing method for escaping from underground space by flood along variable-gradient stairs
CN113314013B (en) * 2021-05-17 2022-03-04 武汉大学 Testing device and testing method for escaping from underground space by flood along variable-gradient stairs

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