CN113532772B - Real-time online monitoring and early warning method, device and medium for rail transit bridge state - Google Patents
Real-time online monitoring and early warning method, device and medium for rail transit bridge state Download PDFInfo
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- CN113532772B CN113532772B CN202110800551.6A CN202110800551A CN113532772B CN 113532772 B CN113532772 B CN 113532772B CN 202110800551 A CN202110800551 A CN 202110800551A CN 113532772 B CN113532772 B CN 113532772B
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- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
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- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
- G01M5/00—Investigating the elasticity of structures, e.g. deflection of bridges or air-craft wings
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- G—PHYSICS
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- G01M5/0058—Investigating the elasticity of structures, e.g. deflection of bridges or air-craft wings by determining deflection or stress by means of external apparatus, e.g. test benches or portable test systems of elongated objects, e.g. pipes, masts, towers or railways
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Abstract
The invention discloses a real-time online monitoring and early warning method, equipment and a medium for the state of a rail transit bridge, which are used for monitoring rollover risks and fracture risks of the rail transit bridge when the rail transit bridge is in an operating state, evaluating a corresponding structural comprehensive risk coefficient of the rail transit bridge in the operating state according to a monitoring result, comparing the structural comprehensive risk coefficient with a set value, and early warning when the structural comprehensive risk coefficient is larger than the set value, thereby realizing the safety monitoring of the self structural stability of the rail transit bridge, expanding the safety monitoring index of the rail transit bridge, leading related managers to know the potential safety hazard of the self structural stability of the rail transit bridge in time, greatly avoiding the occurrence of safety accidents caused by the danger of the self structure of the rail transit bridge, ensuring the operation safety of the rail transit bridge in the operating state on the one hand, on the other hand, the safety of the target operation subject running on the rail transit bridge is guaranteed.
Description
Technical Field
The invention belongs to the technical field of bridge monitoring, particularly relates to a rail transit bridge monitoring technology, and particularly relates to a rail transit bridge state real-time online monitoring and early warning method, device and medium.
Background
With the rapid development of the urbanization process in China, the rail transit bridge becomes an important component of urban public transport development due to the advantages of less engineering investment, short construction period and the like, and the occurrence of the rail transit bridge greatly relieves the pressure of urban traffic, so that the safety importance of the bridge is improved accordingly.
Because the track traffic bridge is used for the track traffic of passing through, it is different with ordinary bridge in the structure, consequently can not monitor with the monitoring index of ordinary bridge completely in carrying out the safety monitoring process to the track traffic bridge, however at present its monitoring index is mostly to bridge shock resistance when carrying out the safety monitoring to the track traffic bridge, neglected the monitoring to track traffic bridge self structural stability, when the track traffic bridge is in the operation state, the operating parameter of track traffic can exert an influence to the stability of bridge self structure, embody following two aspects specifically:
1. when the rail transit runs on a rail paved by a bridge, the running speed and the self weight of the rail transit cause certain impact on the rails on two sides, and when the impact on the two sides is inconsistent, the bridge is likely to turn over;
2. when the rail transit runs on a rail paved by a bridge, the bearing force borne by the bridge is fluctuated due to different position areas of the rail transit passing through the bridge in the running process, and when the fluctuation is uneven, the bridge is likely to break.
Therefore, when the rail transit bridge is in an operating state, the safety monitoring on the structural stability of the bridge is very necessary.
Disclosure of Invention
In order to achieve the purpose, the invention provides a real-time online monitoring and early warning method, a device and a medium for the state of a rail transit bridge, which are used for monitoring rollover risks and fracture risks corresponding to the rail transit bridge in real time when the rail transit bridge is in an operating state, and further evaluating a structural comprehensive risk coefficient corresponding to the rail transit bridge in the operating state according to a monitoring result, so that the safety monitoring of the structural stability of the rail transit bridge is realized.
The purpose of the invention can be realized by the following technical scheme:
the invention provides a real-time online monitoring and early warning method for the state of a rail transit bridge, which comprises the following steps:
firstly, arranging track detection points, namely respectively arranging detection points at the positions of anti-creepers on the tracks on the two corresponding sides of the track traffic bridge so as to obtain the detection points arranged on the tracks on the sides;
acquiring a road shape type, namely acquiring the road shape type corresponding to the rail transit bridge;
thirdly, analyzing the linear side turning danger coefficient, namely acquiring the pressure of each detection point corresponding to each side rail when the rail transit bridge is in an operation state if the road shape is linear, analyzing the acquired pressure of each detection point on each side rail, and counting the linear side turning danger coefficient corresponding to the rail transit bridge;
step four, analyzing the curve rollover risk coefficients, namely if the road shape is a curve, respectively determining the centrifugal force corresponding to each side rail when the rail transit bridge is in the operation state, analyzing the centrifugal force corresponding to each side rail, and counting the rollover risk coefficients of the curve corresponding to the rail transit bridge;
acquiring a target monitoring time period, namely acquiring a target monitoring time period corresponding to the rail transit bridge when the rail transit bridge is in an operation state;
dividing a target monitoring time period into each acquisition time point according to a set acquisition time interval, thereby acquiring the distance of a target operation main body passing through the rail transit bridge at each acquisition time point, recording the distance as a target bearing length, further comparing the target bearing length with the total length corresponding to the rail transit bridge, and counting the fracture risk coefficient corresponding to the rail transit bridge;
evaluating a structural comprehensive risk coefficient, namely evaluating the corresponding structural comprehensive risk coefficient when the rail transit bridge is in an operation state by synthesizing the linear side turning risk coefficient or the curved side turning risk coefficient and the fracture risk coefficient corresponding to the rail transit bridge;
and step eight, danger early warning, namely comparing the corresponding structural comprehensive danger coefficient of the rail transit bridge in the operation state with the set minimum structural comprehensive danger coefficient, and if the structural comprehensive danger coefficient is larger than the minimum structural comprehensive danger coefficient, early warning is carried out.
According to a manner that can be realized in the first aspect of the present invention, the first step further includes numbering each detection point that is laid, and a specific numbering method is as follows;
s1, marking the tracks at the two sides paved on the rail transit bridge as a track A and a track A' respectively;
s2, sequentially numbering the detection points arranged on the track A as 1,2, i, n;
and S3, marking the detection points distributed on the track A ' as 1 ', 2 ', 1., i ', n ' respectively according to the symmetrical relation of the detection points corresponding to the tracks on the two sides.
According to a manner that can be realized by the first aspect of the invention, the specific statistical method for the rail transit bridge corresponding to the linear rollover risk coefficient comprises the following steps:
h1 forming pressure set F of detection points on track A from pressure of detection points on track AA(F1, F2,. multidot.,. fi.,. multidot.,. fn) forming the pressure of each detection point on the track A 'into a track A' detection point pressure set FA′(f1′,f2′,...,fi′,...,fn′)；
H2, respectively carrying out mean value calculation on the track A detection point pressure set and the track A 'detection point pressure set to obtain the average pressure corresponding to the track A and the average pressure corresponding to the track A', which are respectively recorded as
And
h3, comparing the pressures of the detection points on the track A with each other, screening out the detection point number corresponding to the maximum pressure and the detection point number corresponding to the minimum pressure, similarly, comparing the pressures of the detection points on the track A' with each other, and screening out the detection point number corresponding to the maximum pressure and the detection point number corresponding to the minimum pressure;
h4, comparing the number of the detection points corresponding to the maximum pressure on the track A with the number of the detection points corresponding to the maximum pressure on the track A 'to obtain the number of interval detection points corresponding to the maximum pressure, and comparing the number of the detection points corresponding to the minimum pressure on the track A with the number of the detection points corresponding to the minimum pressure on the track A' to obtain the number of interval detection points corresponding to the minimum pressure;
h5, counting the side turning danger coefficients of the rail transit bridge corresponding to the straight line according to the average pressure corresponding to the rail A and the rail A', the number of interval detection points corresponding to the maximum pressure and the number of interval detection points corresponding to the minimum pressure, wherein the calculation formula is
Eta is the side turning danger coefficient of the corresponding linear type of the rail transit bridge, and X, Z is the interval detection corresponding to the maximum pressure respectivelyThe number of the measuring points and the number of the interval measuring points corresponding to the minimum pressure.
According to an implementation manner of the first aspect of the present invention, a specific determination method of the centrifugal force corresponding to each side track is as follows:
r1, acquiring the radius of the curve arc of each side track;
r2, detecting the running speed and the bearing capacity of the target operation main body of each detection point corresponding to each side rail when the rail transit bridge is in an operation state;
r3, respectively carrying out average value calculation on the running speed and the bearing capacity of the target operation main body of each side track corresponding to each detection point to obtain the average running speed and the average bearing capacity of the target operation main body corresponding to each side track;
r4, calculating the centrifugal force corresponding to each side track according to the radius of the curve arc of each side track, the average running speed and the average bearing force of the target operation main body, wherein the calculation formula of the centrifugal force corresponding to the track A is
FFrom AExpressed as the corresponding centrifugal force of the track a,
respectively expressed as the average running speed and the average bearing capacity r of the target operation body corresponding to the track AAThe radius of the curve arc of the track A is expressed, g is expressed as the gravity acceleration, wherein the centrifugal force corresponding to the track A' is calculated according to the formula
FFrom A'Indicated as the corresponding centrifugal force of the track a',
respectively expressed as the average running speed and the average bearing capacity r of the target operation body corresponding to the track AA′Indicated as the radius on the curve arc on which the track a' lies.
According to an implementation mode of the first aspect of the present invention, the specific statistical method for the curve-type rollover risk coefficient of the rail transit bridge is as follows:
d1, comparing the centrifugal force corresponding to the track A with the safe centrifugal force corresponding to the track A, and calculating the rollover risk value corresponding to the track A
σAIs represented as a rollover risk value, F ', corresponding to track A'Separation device′AExpressed as the safe centrifugal force corresponding to the track a;
d2, comparing the centrifugal force corresponding to the track A 'with the safe centrifugal force corresponding to the track A', and calculating the rollover risk value corresponding to the track A
σA′Is represented as a rollover risk value, F ', corresponding to the track A'Separation device′AExpressed as the safe centrifugal force for the track a';
d3, calculating the rollover risk coefficient of the curve type corresponding to the rail traffic bridge according to the rollover risk value corresponding to the rail A and the rollover risk value corresponding to the rail A', wherein the calculation formula is
And xi is expressed as the rollover danger coefficient of the corresponding curve type of the rail transit bridge.
According to an implementation manner of the first aspect of the present invention, the target monitoring time period corresponding to the rail transit bridge is an operation time period of a target operation subject in the rail transit bridge.
According to a manner that can be realized by the first aspect of the present invention, the specific statistical method for the corresponding fracture risk coefficient of the rail transit bridge comprises the following steps:
u1, numbering the divided acquisition time points according to the time sequence, and marking the divided acquisition time points as 1,2, a.
U2 comparing the target bearing length and total length corresponding to the rail transit bridge at each acquisition time point to calculate the target bearing length at each acquisition time pointFracture risk value corresponding to rail transit bridge
δtIs expressed as a fracture risk value l corresponding to the rail transit bridge at the t-th acquisition time pointt targetThe target bearing length corresponding to the rail transit bridge at the t-th acquisition time point is represented, and L is represented as the total length of the rail transit bridge;
u3 calculating the fracture risk coefficient corresponding to the rail transit bridge according to the fracture risk value corresponding to the rail transit bridge at each acquisition time point, wherein the calculation formula is
And chi is expressed as a fracture risk coefficient corresponding to the track traffic bridge, and T is expressed as a target monitoring time period corresponding to the track traffic bridge.
According to a mode capable of being realized by the first aspect of the invention, the calculation formula of the structural comprehensive risk coefficient corresponding to the rail transit bridge in the operation state is
The comprehensive danger coefficient is expressed as a corresponding structural comprehensive danger coefficient when the rail transit bridge is in an operating state, lambda is expressed as a rollover danger coefficient corresponding to the rail transit bridge, the value of lambda can be eta or xi, and a and b are respectively expressed as weight proportion coefficients corresponding to rollover and breakage.
A second aspect of the present invention provides an apparatus, including a processor, and a memory and a network interface connected to the processor; the network interface is connected with a nonvolatile memory in the server; and the processor calls a computer program from the nonvolatile memory through the network interface during running and runs the computer program through the memory so as to execute the real-time online monitoring and early warning method for the rail transit bridge state.
The third aspect of the invention provides a storage medium, wherein a computer program is burned in the storage medium, and when the computer program runs in a memory of a server, the real-time online monitoring and early warning method for the rail transit bridge state is realized.
Based on any one of the aspects, the invention has the beneficial effects that:
1. the invention monitors the rollover danger and the fracture danger of the rail transit bridge when the rail transit bridge is in the operating state, further evaluating the corresponding structural comprehensive risk coefficient of the rail transit bridge in the operation state according to the monitoring result, finally comparing the structural comprehensive risk coefficient with the set minimum structural comprehensive risk coefficient, when the comprehensive danger coefficient is larger than the minimum structural comprehensive danger coefficient, early warning is carried out, the safety monitoring of the structural stability of the rail transit bridge is realized, the safety monitoring index of the rail transit bridge is expanded, make relevant managers can in time know the self structural stability potential safety hazard that the track traffic bridge exists, avoided greatly because of there is dangerous emergence that causes the incident in track traffic bridge self structure, ensured the operation safety when the track traffic bridge is in the operation state on the one hand, on the other hand has ensured the safety of the target operation subject of operation on the track traffic bridge.
2. When rollover danger monitoring is carried out on the rail transit bridge, the rollover danger monitoring is carried out by acquiring the road shape type corresponding to the rail transit bridge and adopting a targeted monitoring mode according to the road shape type, so that the rollover danger monitoring is more practical and practical, and the reliability of the monitoring result is higher.
Drawings
The invention is further illustrated by means of the attached drawings, but the embodiments in the drawings do not constitute any limitation to the invention, and for a person skilled in the art, without inventive effort, further drawings may be derived from the following figures.
FIG. 1 is a flow chart of the method steps of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, in a first aspect of the present invention, a real-time online monitoring and early warning method for a rail transit bridge state is provided, including the following steps:
firstly, arranging track detection points, namely respectively arranging detection points at the positions of anti-creepers on tracks on two corresponding sides of a track traffic bridge to obtain the detection points arranged on the tracks on the sides, and numbering the arranged detection points, wherein the specific numbering method is as follows;
s1, marking the tracks at the two sides paved on the rail transit bridge as a track A and a track A' respectively;
s2, sequentially numbering the detection points arranged on the track A as 1,2, i, n;
s3, marking the detection points distributed on the track A ' as 1 ', 2 ', according to the symmetrical relation of the detection points corresponding to the tracks on the two sides;
the anti-creeper mentioned in the embodiment is installed under the rail to prevent the longitudinal creeping of the steel rail caused by the rolling of the wheels, and the anti-creeper is symmetrically distributed on the rails at two sides;
acquiring a road shape type, namely acquiring the road shape type corresponding to the rail transit bridge, wherein the road shape type comprises a linear type and a curve type;
step three, analyzing a linear side turning danger coefficient, namely acquiring the pressure of each detection point corresponding to each side rail when the rail transit bridge is in an operation state if the road shape is linear, wherein the operation state refers to the state of the rail transit bridge when the rail transit passes through the rail transit bridge, and recording the rail transit currently running on the rail transit bridge as a target operation subject;
and analyzing the acquired pressure of each detection point on each side rail, and counting the corresponding linear side turning danger coefficient of the rail transit bridge, wherein the specific statistical method comprises the following steps:
h1 forming pressure set F of detection points on track A from pressure of detection points on track AA(f1,f2,...,fi,...,fn) And fi is the pressure of the ith detection point on the track A, and the pressure of each detection point on the track A' is formed into a detection point pressure set F of the track AA′(f1 ', f2 ',. as, fi ',. as, fn '), fi ' being expressed as the pressure at the ' i ' th detection point of track a;
h2, respectively carrying out mean value calculation on the track A detection point pressure set and the track A 'detection point pressure set to obtain the average pressure corresponding to the track A and the average pressure corresponding to the track A', which are respectively recorded as
And
wherein
H3, comparing the pressures of the detection points on the track A with each other, screening out the detection point number corresponding to the maximum pressure and the detection point number corresponding to the minimum pressure, similarly, comparing the pressures of the detection points on the track A' with each other, and screening out the detection point number corresponding to the maximum pressure and the detection point number corresponding to the minimum pressure;
h4, comparing the number of the detection points corresponding to the maximum pressure on the track A with the number of the detection points corresponding to the maximum pressure on the track A ' to obtain the number of interval detection points corresponding to the maximum pressure, wherein the larger the number of the interval detection points corresponding to the maximum pressure is, the longer the interval distance between the detection point corresponding to the maximum pressure on the track A and the detection point corresponding to the maximum pressure on the track A ' is, that is, the maximum stress point on the track A is not matched with the maximum stress point on the track A ', and simultaneously comparing the number of the detection points corresponding to the minimum pressure on the track A with the number of the detection points corresponding to the minimum pressure on the track A ' to obtain the number of interval detection points corresponding to the minimum pressure, wherein the larger the number of the interval detection points corresponding to the minimum pressure is, the longer the interval distance between the detection point corresponding to the minimum pressure on the track A and the detection point corresponding to the minimum pressure on the track A ' is, the minimum stress point on the track A is not matched with the minimum stress point on the track A';
h5, counting the side turning danger coefficient of the rail transit bridge corresponding to the straight line according to the average pressure corresponding to the rail A and the rail A', the number of interval detection points corresponding to the maximum pressure and the number of interval detection points corresponding to the minimum pressure, wherein the calculation formula is
Eta is expressed as a linear rollover risk coefficient corresponding to the rail transit bridge, X, Z is respectively expressed as the number of interval detection points corresponding to the maximum pressure and the number of interval detection points corresponding to the minimum pressure, wherein the larger the comparison difference value of the average pressures corresponding to the rail A and the rail A', the larger the number of interval detection points corresponding to the maximum pressure and the larger the number of interval detection points corresponding to the minimum pressure, the larger the rollover risk coefficient is, and the higher the rollover risk degree is;
and step four, analyzing the curve type rollover risk coefficient, namely respectively determining the centrifugal force corresponding to each side rail when the rail transit bridge is in an operation state if the road type is the curve type, wherein the specific determination method of the centrifugal force corresponding to each side rail is as follows:
r1, acquiring the radius of the curve arc of each side track;
r2, detecting the running speed and the bearing capacity of the target operation main body of each detection point corresponding to each side rail when the rail transit bridge is in an operation state;
r3, respectively carrying out average value calculation on the running speed and the bearing capacity of the target operation main body of each side track corresponding to each detection point to obtain the average running speed and the average bearing capacity of the target operation main body corresponding to each side track;
r4, calculating the centrifugal force corresponding to each side track according to the radius of the curve arc of each side track, the average running speed and the average bearing force of the target operation main body, wherein the centrifugal force corresponding to the track AForce is calculated as
FFrom AExpressed as the corresponding centrifugal force of the track a,
respectively expressed as the average running speed and the average bearing capacity r of the target operation body corresponding to the track AAThe radius of the curve arc of the track A is expressed, g is expressed as the gravity acceleration, wherein the centrifugal force corresponding to the track A' is calculated according to the formula
FFrom A'Indicated as the corresponding centrifugal force of the track a',
respectively expressed as the average running speed and the average bearing capacity r of the target operation body corresponding to the track AA′Expressed as the radius on the curve arc of the track a';
and analyzing the centrifugal force corresponding to each side rail, and counting the rollover risk coefficient of the curve corresponding to the rail transit bridge, wherein the specific statistical method is as follows:
d1, comparing the centrifugal force corresponding to the track A with the safe centrifugal force corresponding to the track A, and calculating the rollover risk value corresponding to the track A
σAIs represented as a rollover risk value, F ', corresponding to track A'Separation device′AThe safe centrifugal force corresponding to the track A is expressed, wherein the larger the centrifugal force is, the larger the rollover danger value is;
d2, comparing the centrifugal force corresponding to the track A 'with the safe centrifugal force corresponding to the track A', and calculating the rollover risk value corresponding to the track A
σA′Expressed as the rollover risk value corresponding to the track a',F′separation device′AExpressed as the safe centrifugal force for the track a';
d3, calculating the rollover risk coefficient of the curve type corresponding to the rail traffic bridge according to the rollover risk value corresponding to the rail A and the rollover risk value corresponding to the rail A', wherein the calculation formula is
Xi is represented as a rollover danger coefficient of the corresponding curve type of the rail transit bridge;
when rollover danger monitoring is performed on a rail transit bridge, rollover danger monitoring is performed by acquiring a road shape type corresponding to the rail transit bridge and adopting a targeted monitoring mode according to the road shape type, so that rollover danger monitoring is more practical and practical, unreasonable monitoring caused by rollover danger monitoring in a uniform monitoring mode is avoided, and the reliability of a monitoring result is influenced;
acquiring a target monitoring time period corresponding to the rail transit bridge when the rail transit bridge is in an operating state, wherein the target monitoring time period refers to an operating time period of a target operating subject in the rail transit bridge, namely the interval duration between a time point when the head of the target operating subject enters the rail transit bridge and a time point when the tail of the target operating subject leaves the rail transit bridge;
dividing a target monitoring time period into each acquisition time point according to a set acquisition time interval, thereby acquiring the distance of a target operation main body passing through the rail transit bridge at each acquisition time point, recording the distance as a target bearing length, further comparing the target bearing length with the total length corresponding to the rail transit bridge, and counting the fracture risk coefficient corresponding to the rail transit bridge according to the result, wherein the specific statistical method comprises the following steps:
u1, numbering the divided acquisition time points according to the time sequence, and marking the divided acquisition time points as 1,2, a.
U2, carrying out acquisition on the target bearing length and the total length corresponding to the rail transit bridge at each acquisition time pointComparing to calculate the corresponding fracture danger value of the rail transit bridge at each acquisition time point
δtIs expressed as a fracture risk value l corresponding to the rail transit bridge at the t-th acquisition time pointt targetThe target bearing length corresponding to the rail transit bridge at the t-th acquisition time point is represented, and L is represented as the total length of the rail transit bridge, wherein the larger the comparison difference between the target bearing length corresponding to the rail transit bridge and the total length is, the shorter the distance the rail transit bridge passes by is, that is, the shorter the length of the rail transit bridge is under the bearing capacity of the rail transit, so that the fracture risk value is larger;
u3 calculating the fracture risk coefficient corresponding to the rail transit bridge according to the fracture risk value corresponding to the rail transit bridge at each acquisition time point, wherein the calculation formula is
X is a fracture risk coefficient corresponding to the rail transit bridge, and T is a target monitoring time period corresponding to the rail transit bridge;
step seven, evaluating the structural comprehensive danger coefficient, namely evaluating the structural comprehensive danger coefficient corresponding to the rail transit bridge in an operation state by synthesizing the linear side turning danger coefficient or the curve side turning danger coefficient and the fracture danger coefficient corresponding to the rail transit bridge,
the comprehensive danger coefficient is expressed as a corresponding structural comprehensive danger coefficient when the rail transit bridge is in an operating state, lambda is expressed as a rollover danger coefficient corresponding to the rail transit bridge, the value of lambda can be eta or xi, and a and b are respectively expressed as weight proportion coefficients corresponding to rollover and breakage;
and step eight, performing danger early warning, namely comparing the corresponding structural comprehensive danger coefficient of the rail transit bridge in the operation state with the set minimum structural comprehensive danger coefficient, and performing early warning if the structural comprehensive danger coefficient is larger than the minimum structural comprehensive danger coefficient.
The embodiment monitors the rollover danger and the fracture danger of the rail transit bridge when the rail transit bridge is in the operating state, further evaluating the corresponding structural comprehensive risk coefficient of the rail transit bridge in the operation state according to the monitoring result, finally comparing the structural comprehensive risk coefficient with the set minimum structural comprehensive risk coefficient, when the structural comprehensive danger coefficient is larger than the minimum structural comprehensive danger coefficient, early warning is carried out, the safety monitoring of the structural stability of the rail transit bridge is realized, the safety monitoring index of the rail transit bridge is expanded, make relevant managers can in time know the self structural stability potential safety hazard that track traffic bridge exists, avoided greatly because of there is dangerous emergence that causes the incident in track traffic bridge self structure, guaranteed the operation safety when track traffic bridge is in the operation state on the one hand, on the other hand has ensured the safety of the target operation main part of operation on track traffic bridge.
A second aspect of the present invention provides an apparatus, including a processor, and a memory and a network interface connected to the processor; the network interface is connected with a nonvolatile memory in the server; the processor calls the computer program from the nonvolatile memory through the network interface during running and runs the computer program through the memory so as to execute the real-time online monitoring and early warning method for the rail transit bridge state.
The third aspect of the invention provides a storage medium, wherein a computer program is burned in the storage medium, and when the computer program runs in a memory of a server, the real-time online monitoring and early warning method for the rail transit bridge state is realized.
The foregoing is merely exemplary and illustrative of the present invention and various modifications, additions and substitutions may be made by those skilled in the art to the specific embodiments described without departing from the scope of the invention as defined in the following claims.
Claims (9)
1. The rail transit bridge state real-time online monitoring and early warning method is characterized by comprising the following steps of:
firstly, arranging track detection points, namely respectively arranging detection points at the positions of anti-creepers on the tracks on the two corresponding sides of the track traffic bridge so as to obtain the detection points arranged on the tracks on the sides;
acquiring a road shape type, namely acquiring the road shape type corresponding to the rail transit bridge;
thirdly, analyzing the linear side-turning danger coefficient, namely if the road shape is linear, acquiring the pressure of each side rail corresponding to each detection point when the rail transit bridge is in an operating state, analyzing the acquired pressure of each detection point on each side rail, and counting the linear side-turning danger coefficient corresponding to the rail transit bridge;
the specific statistical method for the linear side-turning danger coefficient corresponding to the rail transit bridge executes the following steps:
h1 forming pressure set F of detection points on track A from pressure of detection points on track AA(F1, F2,. multidot.,. fi.,. multidot.,. fn) forming the pressure of each detection point on the track A 'into a track A' detection point pressure set FA′(f1′,f2′,...,fi′,...,fn′)；
H2, respectively carrying out mean value calculation on the track A detection point pressure set and the track A 'detection point pressure set to obtain the average pressure corresponding to the track A and the average pressure corresponding to the track A', which are respectively recorded as
And
h3, comparing the pressures of the detection points on the track A with each other, screening out the detection point number corresponding to the maximum pressure and the detection point number corresponding to the minimum pressure, similarly, comparing the pressures of the detection points on the track A' with each other, and screening out the detection point number corresponding to the maximum pressure and the detection point number corresponding to the minimum pressure;
h4, comparing the number of the detection points corresponding to the maximum pressure on the track A with the number of the detection points corresponding to the maximum pressure on the track A 'to obtain the number of interval detection points corresponding to the maximum pressure, and comparing the number of the detection points corresponding to the minimum pressure on the track A with the number of the detection points corresponding to the minimum pressure on the track A' to obtain the number of interval detection points corresponding to the minimum pressure;
h5, counting the side turning danger coefficients of the rail transit bridge corresponding to the straight line according to the average pressure corresponding to the rail A and the rail A', the number of interval detection points corresponding to the maximum pressure and the number of interval detection points corresponding to the minimum pressure, wherein the calculation formula is
Eta is the side turning danger coefficient of the corresponding linear type of the rail transit bridge, and X, Z is respectively expressed as the number of interval detection points corresponding to the maximum pressure and the number of interval detection points corresponding to the minimum pressure;
step four, analyzing the curve rollover risk coefficients, namely if the road shape is a curve, respectively determining the centrifugal force corresponding to each side rail when the rail transit bridge is in the operation state, analyzing the centrifugal force corresponding to each side rail, and counting the rollover risk coefficients of the curve corresponding to the rail transit bridge;
acquiring a target monitoring time period, namely acquiring a target monitoring time period corresponding to the rail transit bridge when the rail transit bridge is in an operation state;
dividing a target monitoring time period into each acquisition time point according to a set acquisition time interval, thereby acquiring the distance of a target operation main body passing through the rail transit bridge at each acquisition time point, recording the distance as a target bearing length, further comparing the target bearing length with the total length corresponding to the rail transit bridge, and counting the fracture risk coefficient corresponding to the rail transit bridge;
evaluating a structural comprehensive risk coefficient, namely evaluating the structural comprehensive risk coefficient corresponding to the rail transit bridge in an operating state by synthesizing the linear side turning risk coefficient or the curved side turning risk coefficient and the fracture risk coefficient corresponding to the rail transit bridge;
and step eight, performing danger early warning, namely comparing the corresponding structural comprehensive danger coefficient of the rail transit bridge in the operation state with the set minimum structural comprehensive danger coefficient, and performing early warning if the structural comprehensive danger coefficient is larger than the minimum structural comprehensive danger coefficient.
2. The rail transit bridge state real-time online monitoring and early warning method according to claim 1, characterized in that: the first step also comprises numbering each detection point arranged, and a specific numbering method is as follows;
s1, marking the tracks at the two sides paved on the rail transit bridge as a track A and a track A' respectively;
s2, sequentially numbering the detection points arranged on the track A as 1,2, i, n;
and S3, marking the detection points distributed on the track A ' as 1 ', 2 ', i ', n ' according to the symmetrical relation of the detection points corresponding to the tracks on the two sides.
3. The rail transit bridge state real-time online monitoring and early warning method according to claim 1, characterized in that: the specific determination method of the centrifugal force corresponding to each side track is as follows:
r1, acquiring the radius of the curve arc of each side track;
r2, detecting the running speed and the bearing capacity of the target operation main body of each detection point corresponding to each side rail when the rail transit bridge is in an operation state;
r3, respectively carrying out average value calculation on the running speed and the bearing capacity of the target operation main body of each side track corresponding to each detection point to obtain the average running speed and the average bearing capacity of the target operation main body corresponding to each side track;
r4, calculating the centrifugal force corresponding to each side track according to the radius of the curve arc of each side track, the average running speed and the average bearing force of the target operation main body, wherein the centrifugal force corresponding to the track A is calculated as a common forceIs of the formula
FFrom AExpressed as the corresponding centrifugal force of the track a,
respectively expressed as the average running speed and the average bearing capacity r of the target operation body corresponding to the track AAThe radius of the curve arc of the track A is expressed, g is expressed as the gravity acceleration, wherein the centrifugal force corresponding to the track A' is calculated according to the formula
FFrom A'Indicated as the corresponding centrifugal force of the track a',
respectively expressed as the average running speed and the average bearing capacity r of the target operation body corresponding to the track AA′Indicated as the radius on the curve arc on which the track a' lies.
4. The rail transit bridge state real-time online monitoring and early warning method according to claim 1, characterized in that: the specific statistical method of the curve-type rollover risk coefficient corresponding to the rail transit bridge is as follows:
d1, comparing the centrifugal force corresponding to the track A with the safe centrifugal force corresponding to the track A, and calculating the rollover risk value corresponding to the track A
σAIs represented as a rollover risk value, F 'corresponding to the track A'From AExpressed as the safe centrifugal force corresponding to the track a;
d2, comparing the centrifugal force corresponding to the track A 'with the safe centrifugal force corresponding to the track A', and calculating the rollover risk value corresponding to the track A
σA′Is represented as a rollover risk value, F ', corresponding to the track A'From AExpressed as the safe centrifugal force for the track a';
d3, calculating the rollover risk coefficient of the curve type corresponding to the rail traffic bridge according to the rollover risk value corresponding to the rail A and the rollover risk value corresponding to the rail A', wherein the calculation formula is
And xi is expressed as the rollover danger coefficient of the corresponding curve type of the rail transit bridge.
5. The real-time online rail transit bridge state monitoring and early warning method according to claim 1, characterized in that: the target monitoring time period corresponding to the rail transit bridge is the operation time period of the target operation main body in the rail transit bridge.
6. The rail transit bridge state real-time online monitoring and early warning method according to claim 4, characterized in that: the specific statistical method for the corresponding fracture risk coefficient of the rail transit bridge comprises the following steps:
u1, numbering the divided acquisition time points according to the time sequence, and marking the divided acquisition time points as 1,2, a.
U2, comparing the target bearing length and the total length corresponding to the rail transit bridge at each acquisition time point, and calculating the fracture risk value corresponding to the rail transit bridge at each acquisition time point
δtIs expressed as a fracture risk value l corresponding to the rail transit bridge at the t-th acquisition time pointt targetThe target bearing length corresponding to the rail transit bridge at the t-th acquisition time point is represented, and L is represented as the total length of the rail transit bridge;
u3, calculating the fracture risk value corresponding to the rail transit bridge according to the fracture risk value corresponding to the rail transit bridge at each acquisition time pointThe risk coefficient is calculated by the formula
And chi is expressed as a fracture risk coefficient corresponding to the track traffic bridge, and T is expressed as a target monitoring time period corresponding to the track traffic bridge.
7. The rail transit bridge state real-time online monitoring and early warning method according to claim 6, characterized in that: the calculation formula of the structural comprehensive risk coefficient corresponding to the rail transit bridge in the operation state is
The comprehensive danger coefficient is expressed as a corresponding structural comprehensive danger coefficient when the rail transit bridge is in an operating state, lambda is expressed as a rollover danger coefficient corresponding to the rail transit bridge, the value of lambda is eta or xi, and a and b are respectively expressed as weight proportion coefficients corresponding to rollover and breakage.
8. An apparatus, characterized by: the system comprises a processor, a memory and a network interface, wherein the memory and the network interface are connected with the processor; the network interface is connected with a nonvolatile memory in the server; the processor, when running, retrieves a computer program from the non-volatile memory via the network interface and runs the computer program via the memory to perform the method of any of claims 1-7.
9. A storage medium, characterized by: the storage medium is burned with a computer program, which when run in the memory of the server implements the method of any of the above claims 1-7.
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