Bridge damage monitoring method and system based on laser gyroscope

Abstract

The invention discloses a bridge damage monitoring method and system based on a laser gyroscope, and belongs to the technical field of bridge engineering. According to the method, the first vibration sequence is subtracted from the second vibration sequence and the reference vibration sequence to obtain the damage vibration sequence, track irregularity interference signals and real-time meteorological interference signals are eliminated, and the accuracy of bridge damage monitoring is improved. The damage position and the damage degree are determined by performing wavelet decomposition and reconstruction on the damage vibration sequence, and the internal damage of the bridge is reflected. And predicting a monitoring vector of the next monitoring period according to the monitoring matrix, if the monitoring vector of the next monitoring period is abnormal, calculating the maximum deformation angle of the bridge according to the first vibration sequence and the second vibration sequence, and reflecting the settlement degree of the bridge according to the maximum deformation angle. By monitoring the damage position, the damage degree and the maximum deformation angle of the bridge, the comprehensiveness, the intuition and the sensitivity of bridge damage monitoring are realized.

Description

Technical Field

[0001] The present invention relates to the technical field of engineering monitoring, and in particular to a bridge damage monitoring method and system based on a laser gyroscope. Background Art

[0002] Long-term use of bridges, geological activities and other factors cause deformation and settlement of bridges, which seriously affect the safety of bridges. By detecting the damage inside the deformation and settlement area of ​​the bridge and the change in the stiffness of the bridge, the damage of the bridge can be reflected. The Chinese patent application with publication number CN116698318A discloses a bridge crack identification method based on acceleration monitoring data. The method obtains the kurtosis characteristics of acceleration through statistical analysis of acceleration time-history data, and further determines whether cracks occur in the bridge structure based on the kurtosis characteristics of acceleration, thereby realizing real-time capture of the formation and development process of cracks. The above method does not take into account the interference of uneven track and real-time meteorological interference of the bridge, and the error is large. The Chinese patent application with publication number CN105067209A discloses a method for determining the change in stiffness of a bridge structure based on bridge health monitoring deformation data. The method constructs a relationship model between the change in stiffness of bridge components and the normal distribution curve of deformation, and obtains the change in bridge stiffness by the change law of bridge deformation value. The change of bridge stiffness cannot directly reflect the settlement and damage degree of the bridge, and it is impossible to reflect the damage of the bridge by monitoring the change of bridge stiffness. Therefore, it is necessary to propose a new bridge damage monitoring method. Summary of the invention

[0003] In order to solve the defects of the above-mentioned prior art, the present invention proposes a bridge damage monitoring method and system based on laser gyroscope. The present invention obtains abnormal vibration signals through damage vibration sequence, predicts the damage location and damage degree, and accurately monitors bridge damage. Furthermore, the present invention calculates the maximum deformation angle of the bridge based on real-time strain, thereby realizing bridge damage prediction.

[0004] The technical solution of the present invention is achieved in this way: A bridge damage monitoring method based on laser gyroscope includes the following steps: Step 1: Build a monitoring network on the bridge. The monitoring network includes multiple monitoring nodes. Select one monitoring node as a sensitive monitoring point. Step 2: Install the first laser gyro at the sensitive monitoring point, and install the second laser gyro at the bridge support closest to the sensitive monitoring point; Step 3: If the mobile load enters the bridge, obtain the number of mobile loads and the mass of each mobile load, collect the first vibration signal of the first laser gyro and the second vibration signal of the second laser gyro, collect the real-time strain of each monitoring node and generate a monitoring vector until all mobile loads leave the bridge; Step 4: Generate a reference vibration sequence of the bridge according to the vibration excitation function of each moving load, generate a first vibration sequence according to a plurality of first vibration signals, generate a second vibration sequence according to a plurality of second vibration signals, and generate a monitoring matrix according to a plurality of monitoring vectors; Step 5: Calculate the damaged vibration sequence according to the first vibration sequence, the second vibration sequence, and the reference vibration sequence, obtain the high-frequency wavelet coefficient component according to the damaged vibration sequence, and obtain the extreme value moment of the abnormal vibration signal according to the high-frequency wavelet coefficient component; Step 6: Determine the damage position of the bridge according to the position of each moving load at the extreme value moment, and calculate the damage degree according to the damage vibration sequence and the reference vibration sequence; Step 7: If the damage degree is greater than the damage threshold, the damage location and damage degree are output and the process goes to step 8. Otherwise, the sensitive monitoring point is re-determined according to the damage location and the process goes back to step 2. Step 8: Predict the monitoring vector of the next monitoring cycle based on the monitoring matrix. If the monitoring vector of the next monitoring cycle is abnormal, calculate the maximum deformation angle of the bridge based on the first vibration sequence and the second vibration sequence, output the maximum deformation angle and send out an alarm signal to end the task, otherwise return to step 3.

[0005] In the present invention, in step 3, a strain sensor is installed at the monitoring node, an infrared sensor and a gravity sensor are installed at the bridge entrance and the bridge exit respectively, the amount of the moving load of the bridge is determined according to the infrared sensor, and the mass of the moving load is measured according to the gravity sensor.

[0006] In the present invention, in step 3, a coordinate system oxyz is established with the sensitive monitoring point as the origin o, the length direction of the bridge as the x-axis direction, the direction on the horizontal plane perpendicular to the x-axis as the y-axis direction, and the direction perpendicular to the horizontal plane as the z-axis direction. The first vibration signal includes vibration acceleration components in three directions in the coordinate system.

[0007] In the present invention, in step 4, the vibration excitation function of the mobile load r is F r =g1(m r ,s r ), m r is the mass of the moving load r, s r is the position of the moving load r, and the base vibration w of the bridge at time t 0t satisfy , is the reference vibration w 0t The first derivative of is the reference vibration w 0t is the second-order derivative of , M is the mass of the bridge, c is the damping coefficient of the bridge, k is the stiffness of the bridge, and R is the number of moving loads.

[0008] In the present invention, in step 5, according to the first vibration sequence {w 11 ,...,w 1t ,...,w 1T}, the second vibration sequence {w 21 ,...,w 2t ,...,w 2T} and the reference vibration sequence {w 01 ,...,w 0t ,...,w 0T}Calculate the third vibration sequence {w 31 ,...,w 3t ,...,w 3T},w 3t =w 1t -w 2t -w 0t , extract the vibration acceleration component of the third vibration sequence in the z-axis direction to obtain the damage vibration sequence {a 31z ,...,a 3tz ,...,a 3Tz}, t is the time of the monitoring period, and T is the total number of times of the monitoring period.

[0009] In the present invention, in step 5, the damaged vibration sequence is decomposed and reconstructed according to the wavelet basis function to obtain the high-frequency wavelet coefficient component of the first layer, and the abnormal vibration signal is a vibration signal when the amplitude of the high-frequency wavelet coefficient component exceeds the allowable amplitude.

[0010] In the present invention, in step 6, according to the time t of the mobile load r entering the bridge r Predict the position s of the moving load r r , the damage location of the bridge , predict the average energy E1 of the damaged vibration sequence and the average energy E2 of the benchmark vibration sequence, and the damage degree u=|E2-E1| / E2.

[0011] In the present invention, in step 8, a prediction model is trained according to the monitoring matrix to generate a monitoring vector for the next monitoring cycle. If the maximum real-time strain of the monitoring vector is greater than the settlement threshold, the monitoring vector for the next monitoring cycle is abnormal.

[0012] In the present invention, in step 8, a fourth vibration sequence {w 41 ,...,w 4t ,...,w 4T},w 4t =w 1t -w 2t , according to the fourth vibration sequence, the angular velocity sequence {v1,...,vt ,...,v T}, according to the angular velocity vector v at time t-1 t-1 and the angular velocity vector v at time t t Get the real-time deformation angle θ at time t t , and then generate the deformation sequence {θ1,...,θ t ,...,θ T}, the maximum deformation angle is the maximum modulus of the real-time deformation angle in the deformation sequence.

[0013] A monitoring system for implementing the bridge damage monitoring method based on laser gyroscope includes: an infrared sensor, a gravity sensor, a strain sensor, a first laser gyroscope, a second laser gyroscope, a historical database, a data processing unit, a data analysis unit and a data output unit, wherein: Infrared sensors are used to monitor the amount of moving load on the bridge; Gravity sensors are used to measure the mass of a moving load; The strain sensor is used to measure the real-time strain of each monitoring node; The first laser gyro is used to collect a first vibration sequence; The second laser gyro is used for collecting a second vibration sequence; The historical database is used to store the vibration excitation function of the moving load; The data processing unit is used to predict the damage location and damage extent; The data analysis unit is used to predict the maximum deformation angle of the bridge; The data output unit is used to output the damage location, damage degree and maximum deformation angle.

[0014] The bridge damage monitoring method and system based on laser gyroscope implemented in the present invention has the following beneficial effects: the present invention obtains the first vibration sequence and the second vibration sequence by installing the first laser gyroscope and the second laser gyroscope, and obtains the damage vibration sequence by subtracting the first vibration sequence from the second vibration sequence and the reference vibration sequence, thereby eliminating the interference signal of the uneven road surface and the real-time environmental interference, and improving the accuracy of bridge damage monitoring. The present invention determines the damage location and damage degree based on the abnormal vibration signal, reflecting the internal damage of the bridge. At the same time, the monitoring vector of the next monitoring cycle is predicted based on the monitoring matrix, and the maximum deformation angle of the bridge is calculated, which reflects the settlement degree of the bridge. A comprehensive prediction of bridge damage is achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a flow chart of the bridge damage monitoring method based on laser gyroscope of the present invention; Figure 2 is a schematic diagram of the bridge structure of the present invention; Figure 3is a schematic diagram of the coordinate system of the present invention; Figure 4 It is a schematic diagram of the first layer high frequency wavelet coefficient component of the present invention; Figure 5 The block diagram of the monitoring system of the bridge damage monitoring method based on the laser gyroscope of the present invention.

[0016] Reference numerals in the accompanying drawings are: 101 bridge span, 102 support, 103 bridge pier, 104 abutment, 105 cap, 106 strain sensor, 107 infrared sensor. DETAILED DESCRIPTION

[0017] In order to more clearly understand the purpose, technical solutions and advantages of the present application, the present application is described and illustrated below in conjunction with the accompanying drawings and embodiments.

[0018] When cracks and other damage are on the surface of the bridge, they can be measured by ultrasound, radiation, etc., but when the cracks are inside the bridge, the measurement process is complicated and the measurement results are inaccurate. Therefore, the damage location and damage degree are obtained by measuring the vibration angular acceleration before and after the bridge is damaged. The changes inside the bridge are reflected by monitoring the damage location and damage degree. According to the monitoring matrix, a multivariate time series prediction model is established to predict the monitoring vector of the next monitoring cycle. If the monitoring vector of the next monitoring cycle is abnormal, the maximum deformation angle of the bridge is calculated according to the first vibration sequence and the second vibration sequence, and the settlement degree of the bridge is reflected according to the maximum deformation angle. By monitoring the damage location, damage degree and maximum deformation angle of the bridge, the comprehensiveness, intuitiveness and sensitivity of bridge damage monitoring can be achieved. Embodiment 1

[0019] like Figures 1 to 4 As shown, the bridge damage monitoring method based on laser gyroscope of the present invention includes the following steps.

[0020] Step 1: Build a monitoring network on the bridge. The monitoring network includes multiple monitoring nodes. Select one monitoring node as a sensitive monitoring point. Figure 2 As shown, the bridge includes a span 101, a support 102, a pier 103, an abutment 104, and a cap 105, and the monitoring node is located on the side of the span 101. The sensitive monitoring point means the monitoring node closest to the damage location.

[0021] Step 2: Install the first laser gyro at the sensitive monitoring point and the second laser gyro at the bridge support closest to the sensitive monitoring point. The first laser gyro is used to obtain the change in the vibration frequency of the bridge when the moving load enters the bridge, and the bridge damage is obtained by monitoring the change in the vibration frequency of the bridge. The second laser gyro is used to obtain the impact of real-time meteorology on the vibration frequency of the bridge as a comparison with the first laser gyro to improve the accuracy of bridge damage monitoring.

[0022] Step 3: If the mobile load enters the bridge, obtain the number of mobile loads and the mass of each mobile load, collect the first vibration signal of the first laser gyroscope and the second vibration signal of the second laser gyroscope, collect the real-time strain of each monitoring node and generate a monitoring vector until all mobile loads leave the bridge. If the mobile load enters the bridge, it is a cyclic judgment process until the condition is met and the loop ends. The movement of the mobile load will cause damage to the bridge, which will cause the vibration frequency of the bridge to change. The vehicle is monitored by infrared sensors to determine the start time of the monitoring network. Figure 2 As shown, strain sensors are installed at monitoring nodes, infrared sensors and gravity sensors are installed at the entrance and exit of the bridge respectively, the amount of the bridge moving load is determined by the infrared sensor, and the mass of the moving load is measured by the gravity sensor. The strain sensor 106 is installed on the side of the bridge span 101, and the infrared sensor 107 is located at the port of the bridge span 101. Figure 3 As shown, a coordinate system oxyz is established, with the sensitive monitoring point as the origin o, the length direction of the bridge as the x-axis direction, the direction perpendicular to the x-axis on the horizontal plane as the y-axis direction, and the direction perpendicular to the horizontal plane as the z-axis direction. The first vibration signal contains vibration acceleration components in three directions in the coordinate system, and the vibration acceleration is an angular acceleration. The real-time strain is only in the z-axis direction, indicating the settlement displacement of the bridge. When the bridge is damaged, the real-time strain at the damaged position of the bridge is not zero, and the damage is, for example, a crack.

[0023] Step 4: Generate a reference vibration sequence of the bridge according to the vibration excitation function of each mobile load, generate a first vibration sequence according to multiple first vibration signals, generate a second vibration sequence according to multiple second vibration signals, and generate a monitoring matrix according to multiple monitoring vectors. The first vibration sequence and the second vibration sequence are sequences formed by multiple data collected from the time when the mobile load enters the bridge to the time when it completely exits the bridge. When the collection interval is small, the first vibration sequence and the second vibration sequence are both a continuously changing broken line. The monitoring matrix is ​​composed of multiple monitoring vectors, which reflects the process of real-time strain changes of each monitoring node over time. The influence of the movement of the mobile load on the settlement degree of the bridge is monitored through the monitoring matrix. The reference vibration sequence is the vibration sequence caused by the mobile load entering the bridge when the bridge is not damaged. The specific method for generating a reference vibration sequence of the bridge according to the vibration excitation function is shown in Example 3.

[0024] Step 5: Calculate the damaged vibration sequence according to the first vibration sequence, the second vibration sequence, and the reference vibration sequence, obtain the high-frequency wavelet coefficient component according to the damaged vibration sequence, and obtain the extreme value moment of the abnormal vibration signal according to the high-frequency wavelet coefficient component. 11 ,...,w 1t ,...,w 1T}, the second vibration sequence {w21 ,...,w 2t ,...,w 2T} and the reference vibration sequence {w 01 ,...,w 0t ,...,w 0T}Calculate the third vibration sequence {w 31 ,...,w 3t ,...,w 3T},w 3t =w 1t -w 2t -w 0t , extract the vibration acceleration component of the third vibration sequence in the z-axis direction to obtain the damage vibration sequence {a 31z ,...,a 3tz ,...,a 3Tz}, t is the time of the monitoring cycle, and T is the total number of time of the monitoring cycle. The damaged vibration sequence is denoised, and the wavelet basis function is selected. Then, the damaged vibration sequence is decomposed and reconstructed according to the wavelet basis function to obtain the high-frequency wavelet coefficient component of the first layer. The abnormal vibration signal is the vibration signal when the amplitude of the high-frequency wavelet coefficient component exceeds the allowable amplitude. The allowable amplitude is generally 0.1×10 -3 Meters per second squared, the denoising algorithm is, for example, a frequency domain denoising algorithm, a time domain denoising algorithm, a frequency domain denoising algorithm, etc. In this embodiment, the damaged vibration sequence is denoised by a time domain denoising algorithm, and the dbN wavelet basis function is selected to perform a 1-layer decomposition on the damaged vibration sequence to obtain the following Figure 4 The first layer of high-frequency wavelet coefficient components is shown. Figure 4 The signal in the middle rectangular box is an abnormal vibration signal, and the extreme value moment is the moment corresponding to the maximum amplitude of the abnormal vibration signal. Figure 4 The extreme value time is t1.

[0025] Step 6: Determine the damage position of the bridge according to the position of each moving load at the extreme value moment, and calculate the damage degree according to the damage vibration sequence and the reference vibration sequence. The damage position is the position where the damage has the greatest impact on the bridge. r The specific method for predicting the damage location of the bridge is shown in Example 3. This embodiment discloses a method for calculating the average energy using a single integral method. The vibration velocity is first calculated based on the vibration acceleration, and then the kinetic energy of the vibration is calculated to determine the average energy. In addition, the initial kinetic energy entering the bridge entrance can also be predicted, and then the average energy is calculated based on the change in the initial kinetic energy, which will not be described in detail here. The average energy of the damage vibration sequence Since the moving load has displacement only in the z-axis direction, the vibration acceleration component of the reference vibration sequence in the z-axis direction {a 01z ,...,a0tz ,...,a 0Tz}, the average energy of the reference vibration sequence , the damage degree u=|E2-E1| / E2. The greater the damage degree, the greater the energy of the abnormal vibration signal, that is, the greater the range of amplitude fluctuation of the first layer high-frequency wavelet coefficient component.

[0026] Step 7: If the damage degree is greater than the damage threshold, the damage location and damage degree are output and the process goes to step 8. Otherwise, the sensitive monitoring point is re-determined according to the damage location and the process goes back to step 2. The present invention does not limit the selection method of the sensitive monitoring point. In this embodiment, if the damage degree is less than the damage threshold, the monitoring node closest to the damage location is selected as the sensitive monitoring point. The damage threshold is generally 0.5.

[0027] Step 8: Predict the monitoring vector of the next monitoring cycle according to the monitoring matrix. If the monitoring vector of the next monitoring cycle is abnormal, calculate the maximum deformation angle of the bridge according to the first vibration sequence and the second vibration sequence, output the maximum deformation angle and send an alarm signal, and end the task, otherwise return to step 3. Train the prediction model according to the monitoring matrix, and regenerate the monitoring vector of the next monitoring cycle. If the maximum real-time strain of the monitoring vector of the next monitoring cycle is greater than the settlement threshold, the monitoring vector of the next monitoring cycle is abnormal. This embodiment uses a vector autoregression model to predict the monitoring vector of the next monitoring cycle. The settlement threshold represents the maximum allowable settlement value of the bridge, which is 0.2 meters. The prediction model is a multivariate time series prediction model, S=AX, X is the monitoring matrix, A is the prediction matrix, and S is the monitoring vector of the next monitoring cycle. The multivariate time series prediction model is a model for processing and predicting multiple related time series data, taking into account the interaction between different time series to provide more accurate prediction results, such as a vector autoregression model, a cointegration model, and a multivariate deep learning model.

[0028] Generate a fourth vibration sequence {w 41 ,...,w 4t ,...,w 4T}, and generate an angular velocity sequence {v1,...,v t ,...,v T},w 4t =w 1t -w 2t , v t =w 4t × , is the time interval between time t-1 and time t, the angular velocity sequence includes multiple angular velocity vectors, each angular velocity vector includes angular velocity components in three directions, and the quaternion matrix B at time t is calculated based on the angular velocity vectors at time t-1 and time tt , and then obtain the real-time deformation angle θ at time t t , generating a deformation sequence {θ1,...,θ t ,...,θ T}, the maximum deformation angle is the maximum modulus of the real-time deformation angle in the deformation sequence, and the specific generation process is shown in Example 2. Embodiment 2

[0029] Reference Figure 2 as well as Figure 3 , this embodiment further discloses a method for generating a maximum deformation angle.

[0030] First, define the quaternion matrix B at time t t In the first monitoring cycle, the quaternion matrix at t=1 is initialized to the unit matrix. In other monitoring cycles, the quaternion matrix at t=1 takes the end value B of the previous monitoring cycle. T The quaternion matrix at time t is , Transpose of representation .

[0031] Then, the angular velocity vector v at time t-1 in the same monitoring period is extracted t-1 The angular velocity component v xt-1 、v yt-1 、v zt-1 And the angular velocity vector v at time t t The angular velocity component v xt 、v yt 、v zt .

[0032] The incremental matrix is ​​iteratively calculated based on the angular velocity vector at time t-1 and time t in the same monitoring cycle and the quaternion matrix at time t-1, and then the quaternion matrix at time t is calculated. ; . It is the time interval between time t-1 and time t, that is, the clock cycle of the monitoring node.

[0033] Then calculate the real-time deformation angle θ t , Among them, β xt =arctan2(2b 2t b 3t +2b 0t b 1t , b 3t 2 -b 2t 2 -b 1t 2 +b 0t2 );β yt =arcsin(2b 1t b 3t -2b 0t b 2t );β zt =arctan2(2b 1t b 2t +2b 0t b 3t , b 1t 2 -b 0t 2 -b 3t 2 +b 2t 2 ). Thus, we obtain the deformation sequence {θ1,..., θ t ,..., θ T}.

[0034] Real-time deformation angle θ t The modulus length = Euler angle norm = , the maximum deformation angle is the maximum modulus of the real-time deformation angle in the deformation sequence. The maximum modulus reflects the maximum settlement of the bridge. This embodiment adopts the equal increment method, calculates the increment matrix according to the angular velocity vectors at two adjacent moments, and then calculates the quaternion matrix at the next moment in combination with the increment matrix. This method can reduce the amount of calculation and improve the system response speed. In a further embodiment, the differential equation of the quaternion matrix can be fitted, and the second-order Runge-Kutta method can be used to solve the quaternion matrix and the real-time deformation angle. Embodiment 3

[0035] This embodiment further discloses a method for determining a reference vibration sequence and damage location of a bridge according to the present invention.

[0036] Due to factors such as road noise and uneven load of moving loads, each moving load has vibration excitation on the bridge, and all vibration excitations together form the reference vibration of the bridge. The vibration excitation is related to the mass (pressure) of the moving load and the position of the moving load (road roughness). The vibration excitation of the moving load can be predicted based on historical vibration data. The vibration excitation function F of the moving load r is r =g1(m r ,s r ). The total vibration excitation of the bridge at time t is , R is the number of moving loads. According to the vibration model , the reference vibration w of the bridge at time t can be determined 0t , is the reference vibration w 0t The first derivative of is the reference vibration w 0tThe second derivative of , M is the mass of the bridge, c is the damping coefficient of the bridge, and k is the stiffness of the bridge. Furthermore, the vibration excitation can also be predicted by the vibration model of the moving load (such as a vehicle). , m r is the mass of the moving load r, c r is the damping coefficient of the vehicle, k r is the stiffness of the vehicle, is the first-order derivative of vehicle vibration β1, is the second-order derivative of vehicle vibration β1, is the first-order derivative of the road vibration β2. Both the vehicle vibration β1 and the road vibration β2 can be expressed as a random vibration process, for example , D is the amplitude of vehicle suspension, is the vibration phase angle of the vehicle suspension, and ω is the vibration frequency of the vehicle suspension.

[0037] In the present invention, the concentrated position of the moving load at the extreme moment is the damage position L of the bridge. The concentrated position of the moving load is determined by the weighted centroid of the R moving loads located on the bridge, that is, the damage position of the bridge .s r is the position of the mobile load r, that is, the distance between the mobile load r and the bridge entrance. In this embodiment, the position of the mobile load s r =V r t r , V r is the speed of the moving load r, t r is the time it takes for the mobile load r to enter the bridge. In this embodiment, it can be assumed that the speed of the mobile load is a fixed value. In a more general embodiment, the speed of the mobile load is a variable, and its value is affected by the number of mobile loads R on the bridge. The speed function V of the mobile load can be predicted based on the historical traffic flow model. r =g2(R), then , t1 is the extreme value moment, t2 is the time when the mobile load r enters the bridge entrance, t r =t1-t2. Embodiment 4

[0038] like Figure 5As shown, the monitoring system of the bridge damage monitoring method based on the laser gyro of the present invention includes: an infrared sensor, a gravity sensor, a strain sensor, a first laser gyro, a second laser gyro, a historical database, a data processing unit, a data analysis unit, a data output unit and an alarm unit. The infrared sensor and the gravity sensor are installed at the entrance and exit of the bridge to realize real-time monitoring of the state of the moving load. The infrared sensor is used to monitor the number of moving loads on the bridge, and the gravity sensor is used to measure the mass of the moving load. The strain sensor is installed at the monitoring node, and the monitoring nodes are arranged at equal intervals on the side of the bridge span. The strain sensor is used to measure the real-time strain of each monitoring node. The first laser gyro and the second laser gyro are respectively installed at the sensitive monitoring node and the support closest to the sensitive monitoring node. The initial sensitive monitoring node can be the midpoint of the bridge or the load weak point determined by mechanical analysis, and the subsequent sensitive monitoring node is the monitoring node closest to the damage position. The first laser gyro is used to collect the first vibration sequence, and the second laser gyro is used to collect the second vibration sequence. The historical database is used to store the vibration excitation function of the moving load. In a more specific embodiment, the historical database also stores historical traffic flow models, speed functions, random vibration models, etc. The historical database can continuously update the corresponding vibration excitation function and prediction model according to the continuous use of the bridge. The data processing unit is, for example, a computer module, used to predict the damage location and damage degree of the bridge. The data analysis unit is used to predict the maximum deformation angle of the bridge. The data output unit is, for example, a display, used to output the damage location, damage degree and maximum deformation angle. The alarm unit is, for example, a warning light or a signal transceiver connected to a remote control center.

[0039] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A bridge damage monitoring method based on laser gyroscope, characterized in that: The following steps are involved: Step 1: Build a monitoring network on the bridge. The monitoring network includes multiple monitoring nodes. Select one monitoring node as a sensitive monitoring point. Step 2: Install the first laser gyro at the sensitive monitoring point, and install the second laser gyro at the bridge support closest to the sensitive monitoring point; Step 3: If the mobile load enters the bridge, obtain the number of mobile loads and the mass of each mobile load, collect the first vibration signal of the first laser gyro and the second vibration signal of the second laser gyro, collect the real-time strain of each monitoring node and generate a monitoring vector until all mobile loads leave the bridge; Step 4: Generate a reference vibration sequence of the bridge according to the vibration excitation function of each moving load, generate a first vibration sequence according to a plurality of first vibration signals, generate a second vibration sequence according to a plurality of second vibration signals, and generate a monitoring matrix according to a plurality of monitoring vectors; Step 5: Calculate the damaged vibration sequence according to the first vibration sequence, the second vibration sequence, and the reference vibration sequence, obtain the high-frequency wavelet coefficient component according to the damaged vibration sequence, and obtain the extreme value moment of the abnormal vibration signal according to the high-frequency wavelet coefficient component; Step 6: Determine the damage position of the bridge according to the position of each moving load at the extreme value moment, and calculate the damage degree according to the damage vibration sequence and the reference vibration sequence; Step 7: If the damage degree is greater than the damage threshold, the damage location and damage degree are output and the process goes to step 8. Otherwise, the sensitive monitoring point is re-determined according to the damage location and the process goes back to step 2. Step 8: Predict the monitoring vector of the next monitoring cycle based on the monitoring matrix. If the monitoring vector of the next monitoring cycle is abnormal, calculate the maximum deformation angle of the bridge based on the first vibration sequence and the second vibration sequence, output the maximum deformation angle and send out an alarm signal to end the task, otherwise return to step 3.

2. The bridge damage monitoring method based on laser gyro according to claim 1 is characterized in that: In step 3, strain sensors are installed at monitoring nodes, infrared sensors and gravity sensors are installed at bridge entrances and bridge exits respectively, the amount of the moving load of the bridge is determined according to the infrared sensor, and the mass of the moving load is measured according to the gravity sensor.

3. The bridge damage monitoring method based on laser gyro according to claim 1 is characterized in that: In step 3, a coordinate system oxyz is established with the sensitive monitoring point as the origin o, the length direction of the bridge as the x-axis direction, the direction on the horizontal plane perpendicular to the x-axis as the y-axis direction, and the direction perpendicular to the horizontal plane as the z-axis direction. The first vibration signal contains vibration acceleration components in three directions in the coordinate system.

4. The bridge damage monitoring method based on laser gyro according to claim 1 is characterized in that: In step 4, the vibration excitation function of the moving load r is F r =g1(m r ,s r ), m r is the mass of the moving load r, s r is the position of the moving load r, and the base vibration w of the bridge at time t 0t satisfy , is the reference vibration w 0t The first derivative of is the reference vibration w 0t is the second-order derivative of , M is the mass of the bridge, c is the damping coefficient of the bridge, k is the stiffness of the bridge, and R is the number of moving loads.

5. The bridge damage monitoring method based on laser gyro according to claim 4 is characterized in that: In step 5, according to the first vibration sequence {w 11 ,...,w 1t ,...,w 1T }, the second vibration sequence {w 21 ,...,w 2t ,...,w 2T } and the reference vibration sequence {w 01 ,...,w 0t ,...,w 0T }Calculate the third vibration sequence {w 31 ,...,w 3t ,...,w 3T },w 3t =w 1t -w 2t -w 0t , extract the vibration acceleration component of the third vibration sequence in the z-axis direction to obtain the damage vibration sequence {a 31z ,...,a 3tz ,...,a 3Tz }, t is the time of the monitoring period, and T is the total number of times of the monitoring period.

6. The bridge damage monitoring method based on laser gyro according to claim 5 is characterized in that: In step 5, the damaged vibration sequence is subjected to wavelet decomposition and reconstruction according to the wavelet basis function to obtain the high-frequency wavelet coefficient component of the first layer, and the abnormal vibration signal is a vibration signal when the amplitude of the high-frequency wavelet coefficient component exceeds the allowable amplitude.

7. The bridge damage monitoring method based on laser gyro according to claim 6 is characterized in that: In step 6, the time t that the mobile load r enters the bridge is calculated based on the time t that the mobile load r enters the bridge. r Predict the position s of the moving load r r , the damage location of the bridge , predict the average energy E1 of the damaged vibration sequence and the average energy E2 of the benchmark vibration sequence, and the damage degree u=|E2-E1| / E2.

8. The bridge damage monitoring method based on laser gyro according to claim 7 is characterized in that: In step 8, the prediction model is trained according to the monitoring matrix, and the monitoring vector of the next monitoring cycle is generated. If the maximum real-time strain of the monitoring vector is greater than the settlement threshold, the monitoring vector of the next monitoring cycle is abnormal.

9. The bridge damage monitoring method based on laser gyro according to claim 8 is characterized in that: In step 8, a fourth vibration sequence {w 41 ,...,w 4t ,...,w 4T },w 4t =w 1t -w 2t , according to the fourth vibration sequence, the angular velocity sequence {v1,...,v t ,...,v T }, according to the angular velocity vector v at time t-1 t-1 and the angular velocity vector v at time t t Get the real-time deformation angle θ at time t t , and then generate the deformation sequence {θ1,...,θ t ,...,θ T }, the maximum deformation angle is the maximum modulus of the real-time deformation angle in the deformation sequence.

10. A monitoring system for implementing the bridge damage monitoring method based on laser gyroscope according to claim 1, characterized in that: include: Infrared sensor, gravity sensor, strain sensor, first laser gyro, second laser gyro, historical database, data processing unit, data analysis unit and data output unit, wherein: Infrared sensors are used to monitor the amount of moving load on the bridge; Gravity sensors are used to measure the mass of a moving load; The strain sensor is used to measure the real-time strain of each monitoring node; The first laser gyro is used to collect a first vibration sequence; The second laser gyro is used for collecting a second vibration sequence; The historical database is used to store the vibration excitation function of the moving load; The data processing unit is used to predict the damage location and damage extent; The data analysis unit is used to predict the maximum deformation angle of the bridge; The data output unit is used to output the damage location, damage degree and maximum deformation angle.

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