CN111397821A - Bridge structure damage positioning method based on cross correlation of axle signals - Google Patents

Bridge structure damage positioning method based on cross correlation of axle signals Download PDF

Info

Publication number
CN111397821A
CN111397821A CN202010257451.9A CN202010257451A CN111397821A CN 111397821 A CN111397821 A CN 111397821A CN 202010257451 A CN202010257451 A CN 202010257451A CN 111397821 A CN111397821 A CN 111397821A
Authority
CN
China
Prior art keywords
bridge
damage
vehicle
signals
correlation
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN202010257451.9A
Other languages
Chinese (zh)
Inventor
聂振华
谢永康
马宏伟
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Jinan University
University of Jinan
Original Assignee
Jinan University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Jinan University filed Critical Jinan University
Priority to CN202010257451.9A priority Critical patent/CN111397821A/en
Publication of CN111397821A publication Critical patent/CN111397821A/en
Pending legal-status Critical Current

Links

Images

Classifications

    • 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
    • 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
    • G01M5/0066—Investigating the elasticity of structures, e.g. deflection of bridges or air-craft wings by exciting or detecting vibration or acceleration
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G06F17/15—Correlation function computation including computation of convolution operations

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Pure & Applied Mathematics (AREA)
  • Data Mining & Analysis (AREA)
  • Theoretical Computer Science (AREA)
  • Mathematical Analysis (AREA)
  • Mathematical Optimization (AREA)
  • Aviation & Aerospace Engineering (AREA)
  • Mathematical Physics (AREA)
  • Computational Mathematics (AREA)
  • Algebra (AREA)
  • Databases & Information Systems (AREA)
  • Software Systems (AREA)
  • General Engineering & Computer Science (AREA)
  • Computing Systems (AREA)
  • Testing Of Devices, Machine Parts, Or Other Structures Thereof (AREA)

Abstract

The invention discloses a bridge structure damage positioning method based on axle signal cross correlation, which comprises the following steps: arranging a vertical acceleration sensor at any position on the bridge; a vertical acceleration sensor is arranged on a vehicle, and the vehicle passes through a bridge at a constant speed; respectively collecting acceleration signals a of the bridge in the process that vehicles drive through the bridgeb(i) And acceleration signal a of the vehiclev(i) The method includes the steps of defining a time window with the length of L, synchronously and respectively intercepting obtained acceleration signals, defining an axle signal cross-correlation damage index COR (i) for indicating a damage position of a bridge, moving the time window to obtain a windowed COR (i) time sequence, determining a time point when a vehicle passes through the damage position of the bridge according to a sudden change position of a COR (i) curve, and calculating to obtain the damage position of the bridgeThe bridge damage positioning can be realized, the operation is simple, and the cost is reduced.

Description

Bridge structure damage positioning method based on cross correlation of axle signals
Technical Field
The invention relates to the technical field of structural safety monitoring, in particular to a bridge structure damage positioning method based on axle signal cross correlation.
Background
The current bridge structure damage detection has the problems of too many monitoring points and structural health data loss. In the existing bridge structure damage detection system, a large number of sensors are usually installed on a bridge structure to collect signals, and the health condition of the bridge is detected by comparing the signal characteristics in real time and in a healthy state. On one hand, the installation and maintenance cost of a large amount of sensor equipment can greatly increase the engineering cost; on the other hand, most bridges with long operation time lack the reference data in the initial health state.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides a bridge structure damage positioning method based on the cross correlation of axle signals. The method is based on a data driving principle, does not need reference data in a bridge health state, and can realize bridge damage positioning only by using measured data of a single mobile sensor on a vehicle and a sensor on a bridge.
The purpose of the invention can be achieved by adopting the following technical scheme:
a bridge structure damage positioning method based on axle signal cross correlation comprises the following steps:
s1, arranging an acceleration sensor for measuring vertical acceleration at any position on the bridge to be measured;
s2, mounting an acceleration sensor with the vertical measuring direction on the vehicle, and driving the vehicle to pass through the bridge to be measured at a constant speed;
s3, respectively collecting acceleration signals a of the bridge in the process that the vehicle drives across the bridgeb(i) And acceleration signal a of the vehiclev(i) Where i is 1,2, …, N is the sample point length;
s4, defining a time window with the length of L, synchronously and respectively intercepting acceleration signals of the bridge and the vehicle to obtain a signal a in the windowbL(n) and avL(n), wherein n is 1,2, … L;
s5, defining an axle signal cross-correlation damage index COR (i) indicating the damage position of the bridge:
COR(i)＝max{Rvb(i)}
wherein R isvb(i) For ith versus time of vehicle and bridgeCross-correlation sequences of window signals, i ═ 1,2, …, N-L + 1;
s6, moving a time window, wherein the moving step length is a sampling interval, obtaining a time sequence of a windowed damage index COR (i), and determining a time point when a vehicle passes through the damage position of the bridge according to the sudden change position of a COR (i) curve;
and S7, multiplying the determined damage time point by the moving speed of the vehicle to calculate the damage position of the bridge, and realizing the damage positioning of the bridge structure by utilizing the mechanism.
Further, according to the fragrance concentration sampling theorem, the length L of the time window is determined as follows:
Figure BDA0002437922390000031
wherein f issFor signal sampling frequency, f1The fundamental frequency of the acceleration of the bridge to be measured is obtained from a spectrogram of the measured signal after fast Fourier transform.
Further, in the step S5, the i-th pair of time window signals of the vehicle and the bridge are cross-correlated with each other by the sequence Rvb(i) The determination is as follows:
Figure BDA0002437922390000032
wherein τ is a delay time, i is 1,2, …, N-L + 1.
Compared with the prior art, the invention has the following advantages and effects:
1) the method does not need reference data in a bridge health state, can realize the damage positioning of the bridge structure by only directly analyzing the measured acceleration signal, belongs to a data driving method, and is suitable for the engineering application of an actual bridge. The traditional detection method which needs comparison of the reference data of the structural health condition is not suitable for bridges which are long in construction time and lack of original health data, and a large amount of engineering cost is consumed for detection and storage of bridge health state data. In addition, most bridge monitoring systems are installed after being operated for a certain time, and have no early-stage basic data.
2) The invention is a complete data-driven method without establishing a finite element model of a bridge structure, and can achieve the purpose of damage diagnosis only by the measured data during detection. For the traditional model-based method needing to establish a structural finite element model, an accurate finite element model needs to be established, and then model correction is carried out, but the gap that the finite element model and a real structure have errors cannot be spanned, so that the accuracy of the model-based method often cannot meet the engineering requirements. The method eliminates the process.
3) The method can realize the bridge damage positioning by only utilizing one mobile sensor on the vehicle and one sensor on the bridge, thereby avoiding the process of arranging a large number of sensors on the bridge in the traditional monitoring method, greatly reducing the number of monitoring sensors and the storage quantity of monitoring data, effectively solving the problem that the structural damage detection needs a large number of sensors and mass data is difficult to process, and greatly reducing the system construction cost.
Drawings
FIG. 1 is a flow chart of a method for locating damage to a bridge structure based on cross-correlation of axle signals as disclosed in the present invention;
FIG. 2 is a simplified schematic illustration of a simple beam bridge model according to an embodiment;
FIG. 3 is a schematic diagram of the measured acceleration signal (30% damage) and time window of the bridge in the example;
FIG. 4 is a spectrum diagram of a measured bridge acceleration signal (30% damage) in an example;
FIG. 5 is a graph of the cross-correlation sequence COR (i) for sensor 1 and vehicle sensor for an embodiment of a bridge damage of 30%;
FIG. 6 is a graph of the cross-correlation sequence COR (i) for sensor 1 and vehicle sensor for an embodiment of a bridge damage of 50%;
FIG. 7 is a graph of the cross-correlation sequence COR (i) for sensor 2 and vehicle sensors for an embodiment of a bridge damage of 30%;
fig. 8 is a graph of the cross correlation sequence cor (i) of sensor 2 and vehicle sensor with 50% beam bridge damage in the example.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention clearer and clearer, the present invention is further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. 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.
Examples
As shown in fig. 1, fig. 1 is a flowchart of a method for positioning damage to a bridge structure based on cross-correlation of axle signals according to an embodiment of the present invention. The steel bridge model used in this example is shown in schematic diagram 2, the length l of the model beam is 40m, and the sampling frequency fsIs 1000 Hz. In order to illustrate the effectiveness of the method, 30% and 50% section loss rates are respectively set at the position of 0.4l of the beam length to simulate two damage working conditions, and 2 acceleration sensors at different positions are mounted on the bridge to verify the effectiveness and reliability of the sensors at different positions on the bridge. The specific implementation process is as follows:
s1, arranging a vertical acceleration sensor on the bridge to be measured; to illustrate the effectiveness of the method in mounting the sensors at different locations, acceleration sensor 1 and acceleration sensor 2 are mounted at the bridge 3/10 and 8/10, respectively, as shown in fig. 2;
s2, mounting an acceleration sensor with the vertical measuring direction on the vehicle, and enabling the vehicle to pass through the bridge at a constant speed of v-1 m/S;
s3, respectively collecting acceleration signals a of the bridge in the process that the vehicle drives across the bridgeb(i) And acceleration signal a of the vehiclev(i) Where i is 1,2, … N, N is the sample point length, as shown in fig. 3; here, the sampling length N ═ lfs/v＝40000；
S4, defining a time window with the length of L, synchronously and respectively intercepting acceleration signals of the bridge and the vehicle to obtain a signal a in the windowbL(n) and avL(n), wherein n is 1,2, … L;
in step S4, the length L of the time window is determined according to the fragrance concentration sampling theorem as follows:
Figure BDA0002437922390000061
wherein f issFor signal sampling frequency, f1The fundamental frequency of the acceleration of the bridge to be measured is obtained from the spectrogram after fast Fourier transform of the measured signal, the spectrogram after FFT transform under the condition of 30% damage is shown in FIG. 4, and it can be known from the figure that the fundamental frequency is 2.136Hz, the window length L is 1000/2.136 is 468.165, and the whole is 468.
S5, defining an axle signal cross-correlation damage index COR (i) indicating the damage position of the bridge:
COR(i)＝max{Rvb(i)}
wherein R isvb(i) Is the cross-correlation sequence of two signals in the ith time window of the vehicle and the bridge, i is 1,2, …, 39533;
in step S5, the cross-correlation sequence R of the two signals in the ith time window of the vehicle and the bridgevb(i) The determination is as follows:
Figure BDA0002437922390000062
where τ is the delay time, i is 1,2, …, 39533. The delay time is selected according to unbiased estimation correlation calculation, and the obtained cross-correlation sequence Rvb(i) Is a column vector of length 2L-1.
S6, moving a time window, as shown in fig. 3, obtaining a time sequence of a windowed damage index COR (i), and determining a time point when the vehicle passes through the damage position of the bridge according to a COR (i) curve; if the bridge is damaged, the COR (i) curve generates jumping mutation when the vehicle passes through the damaged position; under healthy conditions, no mutation occurs in the COR (i) curve. The damage time corresponding to the mutation position under the working conditions of 30% damage and 50% damage is t-16000/1000 Hz-16 s;
and S7, multiplying the determined damage time point by the moving speed of the vehicle, and calculating to obtain the damage position of the bridge as 16S × 1m/S as 16m, namely at the position of the beam length of 0.4 l. Fig. 5 and 6 are graphs of cross-correlation indexes cor (i) of signals measured by the vehicle sensor and the bridge sensor 1 under two working conditions, and fig. 7 and 8 are graphs of cross-correlation indexes cor (i) of signals measured by the vehicle sensor and the bridge sensor 2 under two working conditions, which accurately position damage.
In summary, the bridge structure damage positioning method based on the axle signal cross correlation provided by the invention does not need reference data in a bridge health state and a structural finite element model, and can realize bridge damage positioning by only using measured data of a single mobile sensor on a vehicle and a sensor on a bridge.

Claims (3)

1. A bridge structure damage positioning method based on axle signal cross correlation is characterized by comprising the following steps:
s1, arranging an acceleration sensor at any position on the bridge to be measured, and measuring an acceleration signal in the vertical direction;
s2, mounting an acceleration sensor with the vertical measuring direction on the vehicle, and driving the vehicle to pass through the bridge to be measured at a constant speed;
s3, respectively collecting acceleration signals a of the bridge in the process that the vehicle drives across the bridgeb(i) And acceleration signal a of the vehiclev(i) Where i is 1,2, …, N is the sample point length;
s4, defining a time window with the length of L, synchronously and respectively intercepting acceleration signals of the bridge and the vehicle to obtain a signal a in the windowbL(n) and avL(n), wherein n is 1,2, …, L;
s5, defining an axle signal cross-correlation damage index COR (i) indicating the damage position of the bridge:
COR(i)＝max{Rvb(i)}
wherein R isvb(i) The cross correlation coefficient sequence of two signals in the ith time window of the vehicle and the bridge is i, wherein i is 1,2, …, N-L + 1;
s6, moving a time window, wherein the moving step length is a sampling interval, obtaining a time sequence of a windowed damage index COR (i), and determining a time point when a vehicle passes through the damage position of the bridge according to the sudden change position of a COR (i) curve;
and S7, multiplying the determined damage time point by the moving speed of the vehicle to calculate the damage position of the bridge, and realizing the damage positioning of the bridge structure by utilizing the mechanism.
2. The method for locating damage to a bridge structure based on cross-correlation of axle signals of claim 1, wherein the length L of the time window is determined as follows:
Figure FDA0002437922380000021
wherein f issFor signal sampling frequency, f1The base frequency is the base frequency of the acceleration of the bridge to be detected, and the base frequency is obtained from a spectrogram of the acceleration signal of the bridge to be detected after fast Fourier transform.
3. The method for locating structural damage to a bridge based on the cross-correlation between axle signals of claim 1, wherein in step S5, the cross-correlation sequence R of two signals in the ith time window of the vehicle and the bridgevb(i) The determination is as follows:
Figure FDA0002437922380000022
wherein τ is a delay time, i is 1,2, …, N-L + 1.
CN202010257451.9A 2020-04-03 2020-04-03 Bridge structure damage positioning method based on cross correlation of axle signals Pending CN111397821A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202010257451.9A CN111397821A (en) 2020-04-03 2020-04-03 Bridge structure damage positioning method based on cross correlation of axle signals

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202010257451.9A CN111397821A (en) 2020-04-03 2020-04-03 Bridge structure damage positioning method based on cross correlation of axle signals

Publications (1)

Publication Number Publication Date
CN111397821A true CN111397821A (en) 2020-07-10

Family

ID=71434838

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202010257451.9A Pending CN111397821A (en) 2020-04-03 2020-04-03 Bridge structure damage positioning method based on cross correlation of axle signals

Country Status (1)

Country Link
CN (1) CN111397821A (en)

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106802222A (en) * 2017-01-13 2017-06-06 重庆大学 A kind of bridge damnification diagnostic method based on Vehicle-Bridge Coupling System
CN107167559A (en) * 2017-08-01 2017-09-15 暨南大学 A kind of method that beam type bridge structure damage reason location is carried out using dual sensor
CN108982029A (en) * 2018-06-01 2018-12-11 大连理工大学 The damage positioning method of beam type bridge structure based on move vehicle
CN109839440A (en) * 2019-03-20 2019-06-04 合肥工业大学 A kind of bridge damnification localization method based on standing vehicle testing

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106802222A (en) * 2017-01-13 2017-06-06 重庆大学 A kind of bridge damnification diagnostic method based on Vehicle-Bridge Coupling System
CN107167559A (en) * 2017-08-01 2017-09-15 暨南大学 A kind of method that beam type bridge structure damage reason location is carried out using dual sensor
CN108982029A (en) * 2018-06-01 2018-12-11 大连理工大学 The damage positioning method of beam type bridge structure based on move vehicle
CN109839440A (en) * 2019-03-20 2019-06-04 合肥工业大学 A kind of bridge damnification localization method based on standing vehicle testing

Similar Documents

Publication Publication Date Title
CN109357822B (en) Bridge rapid testing and evaluating method based on time-varying power characteristic change of axle coupling system
US10753827B2 (en) Method and system for measuring vertical wheel impact force in real-time based on tire pressure monitoring
CN102401685B (en) Method and device for carrying out online verification/calibration on open channel flowmeter
CN108573224A (en) A kind of Bridge Structural Damage localization method of mobile reconstruct principal component using single-sensor information
CN104133950B (en) A kind of cantilever beam operational modal analysis experimental method and device
Nåvik et al. Variation in predicting pantograph–catenary interaction contact forces, numerical simulations and field measurements
CN109839441B (en) Bridge modal parameter identification method
CN113295310A (en) Bridge damage determination method based on strain stiffness representative value
CN110530509B (en) High-speed motor train unit axle box vibration dominant frequency prediction method based on maximum entropy spectrum analysis
CN107167559B (en) A method of beam type bridge structure damage reason location is carried out using dual sensor
CN108520227A (en) A kind of Bridge Structural Damage localization method of the transfer entropy based on dual sensor information
CN113343541B (en) Vortex-induced vibration early warning method, device and terminal for long and large bridge span
CN104165742A (en) Cross spectral function-based operational modal analysis experiment method and apparatus
CN104880172A (en) Road surface flatness measuring method and device based on Kalman filtering
CN113324648A (en) Portable high-speed railway wheel rail vibration space-time synchronization test method and system
CN108287076B (en) Resistance curve testing method and device
CN106885617A (en) A kind of liquid level gauge detection means and its detection method
CN105387841B (en) Height detecting device, load driving apparatus and height detection method
CN103606240A (en) Method for fire alarming through distributed type fiber optical temperature sensor system
KR100972278B1 (en) Apparatus and Method for Measuring Dynamic Displacement and Velocity History from Measured Acceleration of Structure
CN111397821A (en) Bridge structure damage positioning method based on cross correlation of axle signals
CN107330264A (en) A kind of verification method of bridge monitoring data reliability
CN112964165B (en) Bridge displacement reconstruction method under action of moving load
CN103293007B (en) A kind of agricultural vehicle performance detection method and detecting instrument thereof
CN109406075A (en) A kind of beam bridge structure damage positioning method of the mobile first principal component using single-sensor information

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
RJ01 Rejection of invention patent application after publication
RJ01 Rejection of invention patent application after publication

Application publication date: 20200710