CN112414648A - Bridge damage and vehicle load simultaneous identification method based on macrostrain second-order difference - Google Patents
Bridge damage and vehicle load simultaneous identification method based on macrostrain second-order difference Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- 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
- G01M5/0008—Investigating the elasticity of structures, e.g. deflection of bridges or air-craft wings of bridges
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01G—WEIGHING
- G01G19/00—Weighing apparatus or methods adapted for special purposes not provided for in the preceding groups
- G01G19/02—Weighing apparatus or methods adapted for special purposes not provided for in the preceding groups for weighing wheeled or rolling bodies, e.g. vehicles
- G01G19/03—Weighing apparatus or methods adapted for special purposes not provided for in the preceding groups for weighing wheeled or rolling bodies, e.g. vehicles for weighing during motion
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01G—WEIGHING
- G01G19/00—Weighing apparatus or methods adapted for special purposes not provided for in the preceding groups
- G01G19/02—Weighing apparatus or methods adapted for special purposes not provided for in the preceding groups for weighing wheeled or rolling bodies, e.g. vehicles
- G01G19/03—Weighing apparatus or methods adapted for special purposes not provided for in the preceding groups for weighing wheeled or rolling bodies, e.g. vehicles for weighing during motion
- G01G19/035—Weighing apparatus or methods adapted for special purposes not provided for in the preceding groups for weighing wheeled or rolling bodies, e.g. vehicles for weighing during motion using electrical weight-sensitive devices
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- G—PHYSICS
- G01—MEASURING; TESTING
- 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
- G01M5/0033—Investigating the elasticity of structures, e.g. deflection of bridges or air-craft wings by determining damage, crack or wear
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Abstract
The invention discloses a bridge damage and vehicle load simultaneous identification method based on a macrostrain second order difference, which comprises the following steps: continuously installing n macro strain sensors below the bridge along the bridge span direction; each macro strain sensor respectively collects macro strain response of the bridge when a single vehicle passes by; carrying out second-order difference on each macro strain response in a time domain to obtain a second-order difference curve; recognizing the speed and the wheelbase of the vehicle according to the physical distance between the sensors and the characteristics of the second-order difference curve; counting local minimum values of the second-order difference curves corresponding to the sensors, and identifying the axle load of the vehicle by utilizing the calibration of a reference vehicle; and comparing the minimum value of the corresponding second-order difference curve of each sensor with the reference value to obtain the damage position and the damage degree of the bridge. The invention can effectively and accurately identify the vehicle speed, the wheel base and the axle weight and judge the damage position and degree of the structure based on the same set of sensor and collected data, and effectively reduces the hardware cost on the premise of realizing two functions.
Description
Technical Field
The invention relates to a bridge health monitoring technology, in particular to a method for simultaneously identifying bridge damage and vehicle load based on macrostrain second-order difference.
Background
Because the performance of the bridge is gradually reduced under the action of the load of the upper vehicle reciprocating for a long time, the safety of upper traffic personnel and vehicles is guaranteed in order to avoid the occurrence of potential accidents, and the bridge needs to be detected in real time. The conventional method is completed through manual detection, and the practice shows that the manual detection efficiency is low, the operation time is long, and the bridge damage is difficult to find in time, so that a bridge rapid damage identification algorithm based on health monitoring is particularly necessary. Meanwhile, for bridge health monitoring, monitoring of the upper load is indispensable, the statistical characteristic of the upper load is known, accurate evaluation of bridge performance is carried out on the premise, and meanwhile, maintenance service can be better served for bridge maintenance. Bridge damage identification and vehicle load identification are the most important and indispensable two parts of bridge health monitoring. However, the two existing methods are based on independent and different sensor data and algorithms, and when the two methods are applied to a bridge, the problems of sensor system redundancy, high hardware cost, difficult post-processing and the like can be caused.
Disclosure of Invention
The purpose of the invention is as follows: in order to solve the technical problems, the invention provides a method for simultaneously identifying bridge damage and vehicle load based on a macrostrain second-order difference.
The technical scheme is as follows: in order to solve the technical problem, the invention provides a method for simultaneously identifying bridge damage and vehicle load based on a second-order difference of macrostrain, which comprises the following steps:
step 1: continuously installing n macro strain sensors S1, S2 and … Sn in the bridge span direction below the bridge;
step 2: the macro strain sensors respectively acquire macro strain responses MR1, MR2 and … MRn of the bridge when a single vehicle passes;
and step 3: carrying out second-order difference on the macro strain response acquired by each macro strain sensor in a time domain to obtain a second-order difference curve;
and 4, step 4: recognizing the speed and the wheelbase of the vehicle according to the physical distance between the sensors and the characteristics of the second-order difference curve;
and 5: counting local minimum values of all wave troughs of the second-order difference curves corresponding to all the sensors, and identifying the axle load of the vehicle by utilizing the calibration of a reference vehicle;
step 6: and comparing the minimum value of the corresponding second-order difference curve of each sensor with the reference value to obtain the damage position and the damage degree of the bridge.
Preferably, in step 1, the macro strain refers to an integral of strain at each point in a section of the surface of the bridge structure, and a relationship between the macro strain and the point strain is as follows:
wherein,
for macrostrain,. epsilon. (x) is the point strain.
Preferably, the macro strain sensor in step 1 is a large-gauge resistive strain gauge or a fiber grating macro strain sensor.
Preferably, in step 3, the second order difference curve is calculated as:
wherein, TDC is a second order difference curve, Δ t is a sampling time interval,
the macro strain acquired by the sensor is obtained, and t is a certain data acquisition moment.
Preferably, the vehicle speed calculation formula of the vehicle in step 4 is:
wherein D is the distance between two adjacent sensors S (m +1) and Sm,
and v is the vehicle speed at the time point corresponding to the ith local minimum value on the TDC curve corresponding to Sm.
Preferably, the wheel base calculation formula of the vehicle in the step 4 is as follows:
where WB is the wheelbase and v is the identified vehicle speed.
Preferably, the calculation formula of the vehicle axle weight in the step 5 is as follows:
wherein AWiTo axle weight, peakiIs the value of the ith extreme point, peak, on the second order difference curveRefFor reference to the extreme points of the second order differential curve, W, obtained when the vehicle passesRefFor reference to the axle weight of the vehicle.
Preferably, in step 6, normalizing all vectors of extreme points of the second-order difference curve by using the extreme points of the second-order difference curve corresponding to the sensors closest to the bridge support, wherein after normalization, the position of the vector element deviating from-1 is the damage position of the bridge, and the calculation formula of the damage degree β is as follows:
has the advantages that: the invention can effectively and accurately identify the vehicle speed, the wheel base and the axle weight and judge the damage position and degree of the structure based on the same set of sensor and collected data, and effectively reduces the hardware cost on the premise of realizing two functions.
Drawings
FIG. 1 is a schematic flow chart illustrating steps of a method for identifying bridge damage and vehicle load simultaneously based on a second-order difference of macrostrain according to the present invention;
FIG. 2 is a schematic view of vehicle speed identification;
FIG. 3 is a schematic view of vehicle wheel base identification;
FIG. 4 is a schematic view of vehicle axle weight identification;
FIG. 5 is a schematic view of the application of the method as a vehicle passes through an intact bridge;
FIG. 6 is a schematic diagram of the application of the method when a vehicle passes through a damaged bridge.
Detailed Description
The present invention will be described in detail below with reference to the accompanying drawings.
As shown in fig. 1, the method for simultaneously identifying bridge damage and vehicle load based on second order difference of macrostrain of the present invention includes the following steps:
step 1: continuously installing n macro strain sensors in the bridge span direction below the bridge, wherein the macro strain sensors are S1, S2 and … Sn; the optimal scheme of the arrangement of the n macrostrain sensors is that the macrostrain sensors are connected end to end and are distributed on the whole span of the bridge, as shown in figure 2. It may also be arranged only in critical areas of the structure, such as midspan, quarter-span, etc., when the cost is limited. The macro strain sensor can be a large-scale-distance resistance type strain gauge, a fiber grating macro strain sensor or other sensing equipment which can be used for measuring macro strain.
Step 2: acquiring Macro-strain response (MR) of a bridge when a single vehicle passes through, wherein the MR is MR1, MR2 and … MRn;
and step 3: performing second-order difference on macro strain responses acquired by each sensor in a time domain to obtain a second-order difference curve Two-order difference current (TDC), as shown in FIG. 2; the second order difference curve calculation formula is as follows:
where Δ t is the sampling interval.
And 4, step 4: identifying the vehicle speed (figure 2) and the wheel base (figure 3) of the vehicle according to the physical distance between the sensors and the TDC curve characteristics; the vehicle speed calculation formula is as follows:
speed:
wherein D is the distance between two adjacent sensors S (m +1) and Sm,
is the time point corresponding to the ith local minimum value on the TDC curve corresponding to Sm.
The vehicle wheel base calculation formula is as follows:
wheelbase:
where v is the identified vehicle speed.
And 5: counting local minimum values of TDC curves corresponding to the sensors, and identifying the vehicle axle weight by utilizing the reference vehicle calibration, as shown in FIG. 4; the axle weight calculation formula is as follows:
axle weight:
wherein, peakiIs the value of the ith extreme point, peak, on the TDCRefFor reference to TDC extremes, W, obtained during passage of the vehicleRefFor reference to the axle weight of the vehicle.
Step 6: and normalizing the minimum value and the reference value of the TDC corresponding to each sensor to obtain the position and the degree of the bridge damage, as shown in fig. 5 and 6. Specifically, normalizing all TDC extreme point vectors by using a TDC curve extreme point corresponding to a sensor at a bridge bearing, wherein after normalization, the position of a vector element deviating from-1 is the damage position of the bridge, and the calculation formula of the damage degree beta is as follows:
degree of damage:
in the invention, a macro strain influence line equation is firstly deduced according to the definition of a strain influence line in structural mechanics. According to the structural mechanics, the strain influence line equation at any section xi of the simply supported beam is as follows:
wherein (EI)iH represents the neutral axis height, which is the section stiffness at section xi. According to the definition of macro strain, the transformation relationship between the macro strain in the scale distance range of the mth sensor and the strain value of each point of the structure in the scale distance range is as follows:
wherein lg is the gauge length of the macro strain sensor, and m · lg and (m +1) · lg are the coordinates of the left end and the right end of the mth macro strain sensor respectively. Therefore, the macro strain influence line expression in the mth gauge length range can be obtained:
wherein,
representing the equivalent bending stiffness of the structure in the gauge length of the sensor.
The process of moving the axle over the bridge can just be described in terms of influence lines when reducing a single axle of the vehicle to a concentrated force. The position x of the moving force at this time needs to be represented by time t. How to express is completely dependent on the traveling speed of the vehicle, when the vehicle travels at a constant speed, the moving force position function may be expressed as x (t) v · t. For most highway bridges, because they are dominated by small and medium-span bridges with limited span, the vehicles pass through the bridges with short time, and the speed is basically hard to change greatly in the period, so when the vehicles pass through the upper part of the bridge, the bridges can be basically regarded as passing at a constant speed. Therefore, when a constant moving axle acts on the bridge, the time course of the static macro strain generated in the mth sensor segment can be expressed as:
generally, a real vehicle usually has at least two axles, and because the bridge is still in the elastic phase under the action of traffic load, the superposition principle is still satisfied, so that the static macro-strain response generated by the real vehicle can be represented as the linear superposition of the responses generated by each single axle force after considering the time difference caused by each axle distance, as shown in fig. 4. For a vehicle i with n (i) axles, the total static macrostrain response in the m-th sensor gauge length is generated when it travels across the bridge at speed v (i)
Can be represented by the sum of the responses produced by all the axles, as follows:
wherein,
representing the wheelbase between the kth axle and the 1 st axle of the vehicle i,
represents the axle weight of the kth axle of the vehicle i, and n (i) represents the total number of axles of the vehicle i.
Second order differencing of macrostrain response
The local extreme points of the second-order difference curve TDC can be obtained and are linearly related to the axle load of the vehicle, the local extreme points can be obtained through vehicle equal ratio reference calculation, meanwhile, the positions where the local extreme points appear correspond to the driving positions of the vehicle one by one, and therefore the vehicle speed and the axle distance can be obtained through calculation of the relative positions of the extreme points and the distance between sensors.
Meanwhile, TDC is also inversely proportional to the average stiffness of the structure over the sensor coverage. Based on this relationship, it can be found that this value can be used as a damage indicator to identify structural damage conditions. Through normalization, the minimum value of the TDC is always less than or equal to-1, and the TDC can be compared with each other under different random traffic flow conditions, is not influenced by the traffic flow conditions and is only related to the distribution condition of the longitudinal rigidity of the bridge, namely, the structural damage condition. Due to the inverse proportional relation between the structural rigidity and the TDC minimum value point, when the structure in a certain sensor scale distance is damaged, the structural rigidity is reduced, and the corresponding extreme value can reduce and represent the structural damage position.
For the structural damage degree, assuming that the degree of stiffness degradation in the ith gauge length is β, the structural damage degree can be calculated by the following formula according to the definition of TDC:
wherein,
representing the structural stiffness in the mth sensor gauge,
the stiffness is when the structure is intact.
The above description is only of the preferred embodiments of the present invention, and it should be noted that: it will be apparent to those skilled in the art that various modifications and adaptations can be made without departing from the principles of the invention and these are intended to be within the scope of the invention.
Claims (8)
1. A bridge damage and vehicle load simultaneous identification method based on a macrostrain second order difference is characterized by comprising the following steps:
step 1: continuously installing n macro strain sensors S1, S2 and … Sn in the bridge span direction below the bridge;
step 2: the macro strain sensors respectively acquire macro strain responses MR1, MR2 and … MRn of the bridge when a single vehicle passes;
and step 3: carrying out second-order difference on the macro strain response acquired by each macro strain sensor in a time domain to obtain a second-order difference curve;
and 4, step 4: recognizing the speed and the wheelbase of the vehicle according to the physical distance between the sensors and the characteristics of the second-order difference curve;
and 5: counting the minimum value of each wave trough of the second-order difference curve corresponding to each sensor, and identifying the axle load of the vehicle by utilizing the calibration of a reference vehicle;
step 6: and comparing the minimum value of the corresponding second-order difference curve of each sensor with the reference value to obtain the damage position and the damage degree of the bridge.
2. The method for simultaneously identifying bridge damage and vehicle load based on second order difference of macrostrain according to claim 1, characterized in that: in step 1, macro strain refers to the integral of strain of each point in a section of the surface of the bridge structure, and the relationship between macro strain and point strain is as follows:
wherein,
for macrostrain,. epsilon. (x) is the point strain.
3. The method for simultaneously identifying bridge damage and vehicle load based on second order difference of macrostrain according to claim 1, characterized in that: the macro strain sensor in the step 1 is a large-scale-distance resistance type strain gauge or a fiber grating macro strain sensor.
4. The method for simultaneously identifying bridge damage and vehicle load based on second order difference of macrostrain according to claim 1, characterized in that: in step 3, the second order difference curve calculation formula is:
wherein, TDC is a second order difference curve, Δ t is a sampling time interval,
the macro strain acquired by the sensor is obtained, and t is a certain data acquisition moment.
5. The method for simultaneously identifying bridge damage and vehicle load based on second order difference of macrostrain according to claim 1, characterized in that: the vehicle speed calculation formula of the vehicle in the step 4 is as follows:
wherein D is the distance between two adjacent sensors S (m +1) and Sm,
and v is the vehicle speed at the time point corresponding to the ith local minimum value on the TDC curve corresponding to Sm.
6. The method for simultaneously identifying bridge damage and vehicle load based on second order difference of macrostrain according to claim 1, characterized in that: the wheel base calculation formula of the vehicle in the step 4 is as follows:
where WB is the wheelbase and v is the identified vehicle speed.
7. The method for simultaneously identifying bridge damage and vehicle load based on second order difference of macrostrain according to claim 1, characterized in that: in the step 5, the calculation formula of the vehicle axle weight is as follows:
wherein AWiTo axle weight, peakiIs the value of the ith extreme point, peak, on the second order difference curveRefFor reference to the extreme points of the second order differential curve, W, obtained when the vehicle passesRefFor reference to the axle weight of the vehicle.
8. The method for simultaneously identifying bridge damage and vehicle load based on second order difference of macrostrain according to claim 1, characterized in that: in step 6, normalizing all second-order difference curve extreme point vectors by using the second-order difference curve extreme point corresponding to the sensor closest to the bridge support, wherein after normalization, the position of a vector element deviating from-1 is the damage position of the bridge, and the damage degree beta calculation formula is as follows:
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