Microwave radar-based aircraft load bridge monitoring method and monitoring system

Abstract

The application provides a kind of microwave radar-based aircraft load bridge monitoring method and monitoring system, utilizes microwave radar real-time monitoring aircraft load bridge's dynamic displacement, utilizes video recognition technology to identify the aircraft passing through bridge, and compares with the flight information in airport data system, automatically confirms the model, mass and speed of the aircraft passing through bridge;Then the aircraft mass and speed obtained are given to aircraft model, an aircraft-bridge coupling vibration model considering bridge unevenness is established, and the dynamic displacement of bridge span is obtained by nonlinear numerical calculation when aircraft passes through aircraft load bridge;Again, the actual measured dynamic displacement is compared with the theoretically calculated dynamic displacement, to determine whether there is a safety problem in aircraft load bridge.The application can realize the automation and intelligentization of aircraft load bridge health monitoring, greatly improve the efficiency of aircraft load bridge monitoring and evaluation, save cost, and improve the accuracy of monitoring and evaluation.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of measurement test technology, in particular to a kind of aircraft load bridge monitoring method and monitoring system based on microwave radar. BACKGROUND

[0002] The aircraft load bridge can be divided into taxiway bridge and runway bridge. In the airport, the aircraft operation may cross the airport internal and external traffic, river, etc., and the aircraft load bridge becomes a commonly used structure form, mainly bearing the aircraft load, to ensure the normal operation of the aircraft during take-off, landing and parking process.

[0003] The aircraft load bridge is an important part of airport infrastructure, and its structural state needs to be monitored and evaluated, and a warning signal is issued when its structural state deteriorates seriously, to ensure its safety and use performance in real time and effectively.

[0004] The basic connotation of bridge health monitoring is to monitor and evaluate the bridge structure condition, to issue a warning signal when the bridge is in special weather, traffic conditions or abnormal bridge operation condition, and to provide basis and guidance for bridge maintenance and management decision.

[0005] The traditional bridge detection largely depends on the experience of managers and technical personnel, lacks scientific and systematic methods, often lacks comprehensive understanding of the bridge condition, and the information cannot be fed back in time. If the bridge disease is underestimated, the best maintenance opportunity may be missed, the bridge damage process may be accelerated, and the service life of the bridge may be shortened. If the bridge disease is overestimated, unnecessary waste of funds will occur, and the bearing capacity of the bridge cannot be fully utilized. In addition, manual detection is time-consuming and labor-intensive, and with the rise of labor cost, it will become increasingly uneconomical.

[0006] Since the 1960s, due to the serious degradation of bridges in developed countries, the continuous occurrence of safety accidents and the severity of the consequences, engineering and technical personnel have actively explored bridge structure monitoring. In recent years, some large bridges in China have also designed and installed structural health monitoring systems, such as the Humen Bridge in Guangdong, the Dafosi Bridge in Chongqing, the Haikou Century Bridge, the Nanjing Sanqiao Bridge, the Jiangyin Bridge and the Runyang Yangtze River Bridge, as well as the structural health monitoring system of the Sutong Yangtze River Bridge.

[0007] However, the existing domestic and foreign bridge health monitoring systems still have the problems of being unable to effectively identify traffic load and being difficult to conveniently measure bridge deflection, and the existing bridge health monitoring systems are all for highway bridges, railway bridges or pedestrian bridges, and there is still no health monitoring system specially for aircraft load bridges. The aircraft load bridge still uses manual periodic detection and special detection methods, and the degree of automation and intelligence is low, which is time-consuming and labor-intensive, and the detection results are greatly affected by subjective factors. SUMMARY

[0008] The present application is to solve the problem of aircraft load bridge monitoring, providing a microwave radar-based aircraft load bridge monitoring method and monitoring system, which uses microwave radar to monitor the dynamic displacement of the aircraft load bridge in real time, uses video recognition technology to identify the aircraft passing through the bridge, and compares with the flight information in the airport data system to automatically confirm the model, mass and speed of the aircraft passing through the bridge; then the obtained aircraft mass and speed are assigned to the aircraft model, an aircraft-bridge coupling vibration model considering the bridge surface irregularity is established, and the dynamic displacement of the bridge span is obtained by nonlinear numerical calculation when the aircraft passes through the aircraft load bridge; the actual measured dynamic displacement is compared with the theoretically calculated dynamic displacement to determine whether the aircraft load bridge has safety problems. The present application can realize the automation and intelligentization of aircraft load bridge health monitoring, greatly improve the efficiency of aircraft load bridge monitoring and evaluation, save cost, and improve the accuracy of monitoring and evaluation.

[0009] The present application provides a microwave radar-based aircraft load bridge monitoring method, comprising the following steps:

[0010] S1, obtaining monitoring data: the microwave radar transmits microwaves to the target and obtains the actual dynamic displacement of the aircraft load bridge in the span in real time according to the echo signal and outputs to the nonlinear numerical calculation module, and then obtains the actual dynamic displacement curve in the span; the visual recognition module obtains the aircraft model, aircraft speed and aircraft mass m1 from the aircraft video passing through the aircraft load bridge according to the camera shooting and outputs to the nonlinear numerical calculation module;

[0011] Respectively entering steps S2, S3 and S4;

[0012] S2, obtaining aircraft load component; by analyzing the stress condition of the aircraft, an aircraft load model is established to obtain the aircraft load component F V , entering step S5;

[0013] S3, obtaining bridge load vector: by discretizing the aircraft load bridge structure, the bridge load vector F B is obtained, entering step S5;

[0014] S4, obtaining bridge surface irregularity sample: according to the road surface irregularity power spectrum S(ω) of the aircraft load bridge, the road surface irregularity sample r(x) is simulated and obtained, entering step S5;

[0015] S5, aircraft-bridge coupling vibration analysis: according to the aircraft load component F V , the bridge load vector F BThe uneven road surface sample r(x) is coupled with the coordination condition that the displacement of the airplane wheel and the bridge contact point is the same and the interaction force is equal, an airplane-bridge coupling vibration model is established, and the cross coupling dynamic displacement and the cross coupling dynamic displacement curve of the airplane load bridge are obtained.

[0016] S6, monitoring result judgment and output: the nonlinear numerical calculation module compares the actual dynamic displacement in the span with the cross coupling dynamic displacement and judges whether the airplane load bridge needs to be repaired, and outputs the monitoring result.

[0017] Return to step S1, and continuously monitor.

[0018] As a preferred mode, in step S1, the nonlinear numerical calculation module obtains the airplane model and the airplane speed according to the airplane video, and then obtains the flight number and the airplane mass m1 by comparing with the flight information in the airport data system.

[0019] In step S2,

[0020] Wherein, M V is the mass matrix of the airplane, Y V is the displacement vector of the airplane, is the speed vector of the airplane, is the acceleration vector of the airplane, C V is the damping matrix of the airplane, and K V is the stiffness matrix of the airplane.

[0021] In step S3,

[0022] Wherein, M B is the mass matrix of the airplane load bridge, Y B is the displacement vector of the airplane load bridge, is the speed vector of the airplane load bridge, is the acceleration vector of the airplane load bridge, C B is the damping matrix of the airplane load bridge, and K B is the stiffness matrix of the airplane load bridge.

[0023] As a preferred mode, in step S2,

[0024]

[0025] Y V =[y1 y2 y3 y4] T .

[0026] Wherein, m2 is the mass of the rear wheel, m3 is the mass of the front wheel, J is the moment of inertia, l1 is the horizontal distance from the rear wheel to the center of mass of the aircraft, l2 is the horizontal distance from the front wheel to the center of mass of the aircraft, l is the wheelbase of the rear wheel, k1 is the stiffness coefficient of the interaction between the rear wheel and the bridge, k2 is the stiffness coefficient of the connection between the aircraft body and the rear wheel, k3 is the stiffness coefficient of the connection between the aircraft body and the front wheel, k4 is the stiffness coefficient of the interaction between the front wheel and the bridge, c1 is the damping coefficient of the interaction between the rear wheel and the bridge, c2 is the damping coefficient of the connection between the aircraft body and the rear wheel, c3 is the damping coefficient of the connection between the aircraft body and the front wheel, c4 is the damping coefficient of the interaction between the front wheel and the bridge, y1 is the vertical displacement of the rear wheel, y2 is the vertical displacement above the rear wheel at the rear end of the aircraft body, y3 is the vertical displacement above the front wheel at the front end of the aircraft body, and y4 is the vertical displacement of the front wheel.

[0027] The aircraft load bridge monitoring method based on the microwave radar, as a preferred mode, in step S3, the damping matrix C of the aircraft load bridge B The Rayleigh damping is used, and the external load damping is zero.

[0028] C B = alpha0M + beta0K;

[0029] Wherein, alpha0 = 2epsilon1omega 01 -beta0omega 01 omega 01 ;

[0030] omega 01 , omega 02 are the first-order natural frequency and the second-order natural frequency of the structure respectively, epsilon1 and epsilon2 are the first-order modal damping and the second-order modal damping of the structure respectively, M is the mass matrix, and K is the stiffness matrix.

[0031] The aircraft load bridge monitoring method based on the microwave radar, as a preferred mode, in step S4,

[0032] Wherein, omega0 is a reference spatial frequency, omega0 is 0.1m- 1 , omega is a spatial frequency, S is the power spectral density value under the reference spatial frequency, and beta is a coefficient proportional to the stiffness.

[0033] The road roughness sample r(x) is obtained by the trigonometric series superposition method, the quadratic filtering method, the AR model method and the ARMA model method.

[0034] In step S5, the coupled vibration equation of the aircraft-bridge coupled vibration model is:

[0035]

[0036] wherein f i (t) is the interaction force between the ith wheel and the bridge deck of the aircraft load bridge, k i is the stiffness corresponding to the ith row of the bridge deck stiffness matrix K, c i is the bridge deck irregularity damping coefficient corresponding to the ith wheel, is the vertical acceleration of the ith wheel relative to the bridge deck at time t, Δ i (t) is the vertical displacement of the ith wheel relative to the bridge deck at time t, y i is the vertical displacement of the ith wheel at time t, z i is the vertical displacement of the bridge deck at time t at the contact point between the ith wheel and the bridge deck, r i is the bridge deck irregularity sample value at the contact point between the ith wheel and the bridge deck.

[0037] The aircraft load bridge monitoring method based on the microwave radar, as a preferred mode, in step S4, the road surface irregularity sample r(x) is simulated by the trigonometric series superposition method;

[0038]

[0039] wherein α k is the amplitude of the cosine function, ω k is the frequency located in the power spectral density definition interval [ω l , ω u ], θ k is a random phase angle uniformly distributed between 0 and 2π, x is a local coordinate, x is the distance of a certain point on the bridge from the left end of the bridge, N is the number of points of the simulated random irregularity. S is the power spectral density function defined as a function of the spatial frequency of the road surface irregularity in the interval [ω l , ω u ];

[0040]

[0041] wherein α is the irregularity coefficient, and β is the index.

[0042] The aircraft load bridge monitoring method based on the microwave radar, as a preferred mode, in step S5,

[0043] The coupled vibration equation can be solved by the linear acceleration method, the New-mark-β method or the Wilson-0 method.

[0044] The aircraft load bridge monitoring method based on the microwave radar provided in the application, as a preferred mode, the standard for judging whether the aircraft load bridge needs to be overhauled in step S6 is that when the peak value of the actual dynamic displacement curve of the midspan is 10% higher than the peak value of the coupled dynamic displacement curve of the midspan, or the time integral of the actual dynamic displacement curve of the midspan is 20% higher than the time integral of the coupled dynamic displacement curve of the midspan, the aircraft load bridge has a safety problem and needs to be overhauled.

[0045] The application provides an aircraft load bridge monitoring system based on a microwave radar, which comprises a microwave radar arranged on a pier or abutment of an aircraft load bridge, a target arranged on a bottom surface of a midspan of the aircraft load bridge, a camera arranged on one side of the aircraft load bridge, and a control processing system electrically connected with the microwave radar and the camera.

[0046] The microwave radar is used for emitting microwaves to the target, obtaining the actual dynamic displacement of the midspan of the aircraft load bridge in real time through a return signal, and outputting the actual dynamic displacement to the control processing system and forming an actual dynamic displacement curve of the midspan; the camera is used for observing an aircraft passing through the aircraft load bridge and outputting a video to the control processing system; the control processing system is used for analyzing the video and identifying a model and a speed of the aircraft; the control processing system is used for comparing the identified model and speed of the aircraft with flight information in an airport data system to obtain a flight number and a mass of the aircraft; the control processing system is used for obtaining a coupled dynamic displacement of the midspan of the aircraft load bridge and a coupled dynamic displacement curve of the midspan according to the speed and mass of the aircraft; and the control processing system is used for comparing the actual dynamic displacement of the midspan with the coupled dynamic displacement of the midspan and judging whether the aircraft load bridge needs to be overhauled.

[0047] The aircraft load bridge monitoring system based on the microwave radar provided in the application, as a preferred mode, the control processing system comprises a visual identification module and a nonlinear numerical calculation module which are electrically connected, the visual identification module is electrically connected with the camera and the airport data system, and the nonlinear numerical calculation module is electrically connected with the microwave radar and the target.

[0048] The microwave radar is used for emitting microwaves to the target, obtaining the actual dynamic displacement of the midspan of the aircraft load bridge in real time through a return signal, and outputting the actual dynamic displacement to the control processing system and forming an actual dynamic displacement curve of the midspan; the camera is used for observing an aircraft passing through the aircraft load bridge and outputting a video to the control processing system; the control processing system is used for analyzing the video and identifying a model and a speed of the aircraft; the control processing system is used for comparing the identified model and speed of the aircraft with flight information in an airport data system to obtain a flight number and a mass of the aircraft; the control processing system is used for obtaining a coupled dynamic displacement of the midspan of the aircraft load bridge and a coupled dynamic displacement curve of the midspan according to the speed and mass of the aircraft; and the control processing system is used for comparing the actual dynamic displacement of the midspan with the coupled dynamic displacement of the midspan and judging whether the aircraft load bridge needs to be overhauled.

[0049] The present application has the following advantages:

[0050] The present application provides a health monitoring system for an aircraft load bridge, which applies microwave radar technology and video recognition technology to the health monitoring system of the aircraft load bridge, uses the microwave radar to monitor the dynamic displacement of the aircraft load bridge in real time, uses the video recognition technology to identify the aircraft passing through the bridge, and compares the flight information in the airport data system to automatically confirm the model, mass and speed of the aircraft passing through the bridge; then the obtained mass and speed of the aircraft are assigned to the aircraft model, an aircraft-bridge coupling vibration model considering the bridge surface irregularity is established, the dynamic displacement of the bridge span is obtained through nonlinear numerical calculation when the aircraft passes through the aircraft load bridge; and the actually measured dynamic displacement is compared with the theoretically calculated dynamic displacement to determine whether the aircraft load bridge has safety problems. The present application can realize the automation and intelligentization of the health monitoring of the aircraft load bridge, greatly improve the efficiency of the monitoring and evaluation of the aircraft load bridge, save the cost, and improve the accuracy of the monitoring and evaluation. BRIEF DESCRIPTION OF DRAWINGS

[0051] Figure 1 It is a flow chart of an aircraft load bridge monitoring method based on microwave radar;

[0052] Figure 2 It is an aircraft model diagram of an aircraft load bridge monitoring method based on microwave radar;

[0053] Figure 3 It is a road surface irregularity simulation sample diagram of an aircraft load bridge monitoring method based on microwave radar;

[0054] Figure 4 It is a structure diagram of an aircraft load bridge monitoring method and monitoring system based on microwave radar;

[0055] Figure 5 It is a bridge span dynamic displacement diagram of an aircraft load bridge monitoring method based on microwave radar.

[0056] Reference signs:

[0057] 1, microwave radar; 2, target; 3, camera; 4, control processing system; 41, visual recognition module; 42, nonlinear numerical calculation module. DETAILED DESCRIPTION

[0058] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all the embodiments.

[0059] Embodiment 1

[0060] AsFigure 1 As shown in the figure, a microwave radar-based aircraft load bridge monitoring method comprises the following steps:

[0061] S1, obtaining monitoring data: the microwave radar 1 transmits microwaves to the target 2 and obtains the actual dynamic displacement of the aircraft load bridge in real time according to the echo signal and outputs to the nonlinear numerical calculation module 42, and then obtains the actual dynamic displacement curve; the visual recognition module 41 obtains the aircraft model, aircraft speed and aircraft mass m1 according to the video of the aircraft passing through the aircraft load bridge shot by the camera 3 and outputs to the nonlinear numerical calculation module 42;

[0062] The nonlinear numerical calculation module 42 obtains the aircraft model and aircraft speed according to the aircraft video, and then compares with the flight information in the airport data system to obtain the flight number and aircraft mass m1 of the aircraft;

[0063] Respectively enter steps S2, S3, S4;

[0064] S2, obtaining the aircraft load component; by analyzing the force condition of the aircraft, an aircraft load model is established to obtain the aircraft load component F V ;

[0065]

[0066] Wherein, M V is the mass matrix of the aircraft, Y V is the displacement vector of the aircraft, is the speed vector of the aircraft, is the acceleration vector of the aircraft, C V is the damping matrix of the aircraft, K V is the stiffness matrix of the aircraft;

[0067]

[0068] Y V =[y1 y2 y3 y4] T .

[0069] Wherein, m2 is the mass of the rear wheel, m3 is the mass of the front wheel, J is the moment of inertia, l1 is the horizontal distance from the rear wheel to the center of mass of the aircraft, l2 is the horizontal distance from the front wheel to the center of mass of the aircraft, l is the wheelbase of the rear wheel, k1 is the stiffness coefficient of the interaction between the rear wheel and the bridge, k2 is the stiffness coefficient of the connection between the aircraft body and the rear wheel, k3 is the stiffness coefficient of the connection between the aircraft body and the front wheel, k4 is the stiffness coefficient of the interaction between the front wheel and the bridge, c1 is the damping coefficient of the interaction between the rear wheel and the bridge, c2 is the damping coefficient of the connection between the aircraft body and the rear wheel, c3 is the damping coefficient of the connection between the aircraft body and the front wheel, c4 is the damping coefficient of the interaction between the front wheel and the bridge, y1 is the vertical displacement of the rear wheel, y2 is the vertical displacement above the rear wheel at the rear end of the aircraft body, y3 is the vertical displacement above the front wheel at the front end of the aircraft body, and y4 is the vertical displacement of the front wheel.

[0070] Step S5 is entered.

[0071] S3, obtaining a bridge load vector: by discretizing the aircraft load bridge structure, a bridge load vector F is obtained B ,

[0072]

[0073] Wherein, M B is the mass matrix of the aircraft load bridge, Y B is the displacement vector of the aircraft load bridge, is the velocity vector of the aircraft load bridge, is the acceleration vector of the aircraft load bridge, C B is the damping matrix of the aircraft load bridge, K B is the stiffness matrix of the aircraft load bridge.

[0074] The damping matrix C B of the aircraft load bridge uses Rayleigh damping, and the external load damping is zero.

[0075] C B = α0M + β0K;

[0076] Wherein, α0 = 2ε1ω 01 - β0ω 01 ω 01 ; β0 = 2ε2ω 01 2 + ω 02 2;

[0077] ω 01 , ω 02 are the first and second order natural frequencies of the structure, respectively, ∈1, ∈2 are the first and second order modal damping of the structure, respectively, M is the mass matrix, and K is the stiffness matrix.

[0078] Step S5 is entered.

[0079] S4, obtaining the bridge unevenness sample: obtaining the road unevenness sample r(x) according to the road unevenness power spectrum S(ω) of the aircraft load bridge,

[0080]

[0081] Wherein, ω0 is the reference spatial frequency, ω0 is 0.1m -1 , ω is the spatial frequency, Sω0 is the power spectral density value at the reference spatial frequency, and β is the coefficient proportional to the stiffness;

[0082] The road unevenness sample r(x) is simulated by the trigonometric series superposition method, the quadratic filtering method, the AR model method and the ARMA model method;

[0083] The road unevenness sample r(x) is simulated by the trigonometric series superposition method;

[0084]

[0085] Wherein, α k is the amplitude of the cosine function, ω k is the frequency located in the power spectral density definition interval [ω l , ω u ], θ k is a random phase angle uniformly distributed between 0 and 2π, x is the local coordinate, x is the distance of a point on the bridge from the left end of the bridge, and N is the number of points of the simulated random unevenness. Sω k The power spectral density function is defined as a function of the spatial frequency of the road unevenness in the interval [ω l , ω u ];

[0086]

[0087] Wherein, α is the unevenness coefficient, and β is the index;

[0088] Enter step S5;

[0089] S5, aircraft-bridge coupling vibration analysis: according to the aircraft load component F V , the bridge load vector F B and the road unevenness sample r(x), the same displacement and the same interaction force size of the aircraft wheel and the bridge contact point are coupled, the aircraft-bridge coupling vibration model is established, and the cross coupling dynamic displacement and the cross coupling dynamic displacement curve of the aircraft load bridge are obtained;

[0090] The coupling vibration equation of the aircraft-bridge coupling vibration model is:

[0091]

[0092] Among them, f i (t) represents the interaction force between the i-th wheel and the bridge deck loaded by the aircraft, k i Let c be the stiffness corresponding to the i-th row of the bridge deck stiffness matrix K. i Let be the bridge deck roughness damping coefficient corresponding to the i-th wheel. Let Δ be the vertical acceleration of the i-th wheel relative to the bridge deck at time t. i (t) represents the vertical displacement of the i-th wheel relative to the bridge deck at time t, y i t represents the vertical displacement of the i-th wheel at time t, and z represents the vertical displacement of the wheel at time t. i t represents the vertical displacement of the bridge deck at time t at the contact point between the i-th wheel and the bridge deck, and r represents the vertical displacement of the bridge deck at time t. i Sample value of bridge deck irregularity at the contact point between the i-th wheel and the bridge deck;

[0093] The coupled vibration equations were solved using the linear acceleration method, the New-mark-β method, and the Wilson-0 method.

[0094] S6. Monitoring Result Judgment and Output: The nonlinear numerical calculation module 42 compares the actual dynamic displacement at mid-span with the coupled dynamic displacement at mid-span and determines whether the aircraft-loaded bridge needs maintenance before outputting the monitoring result.

[0095] The criteria for determining whether an aircraft-loaded bridge needs maintenance are as follows: when the peak value of the actual dynamic displacement curve at mid-span is 10% higher than the peak value of the coupled dynamic displacement curve at mid-span, or when the time integral of the actual dynamic displacement curve at mid-span is 20% higher than the time integral of the coupled dynamic displacement curve at mid-span, the aircraft-loaded bridge has safety issues and needs maintenance.

[0096] Return to step S1 and continue monitoring.

[0097] Example 2

[0098] like Figure 1 As shown, a method for monitoring aircraft loads on bridges based on microwave radar;

[0099] Simplify the aircraft as follows Figure 2 The aircraft model shown is simplified as a rigid body with mass m1 and moment of inertia J about its center of mass, with a distance l between its two axes. The masses of the wheels are m2 and m3, respectively. The interaction between the wheels and the ground, as well as the connection between the body and the wheels, are simulated using a spring-damped system. The stiffness and damping coefficients for the interaction between the wheels and the bridge deck are k1, c1 and k4, c4, respectively, and the stiffness and damping coefficients for the connection between the body and the wheels are k2, c2 and k3, c3, respectively. This model has eight degrees of freedom: vertical displacements y1 and y4 of the wheels, displacements z1 and z2 at the contact points between the wheels and the bridge deck, vertical displacements y2 and y3 at both ends of the body, and displacement and rotation angle y at the center of mass of the body. c, θ. Wherein z1, z2 and bridge displacement coupling, y c , θ as (2-1) formula can be represented by y3, y4:

[0100]

[0101] Therefore, the model is independent of four degrees of freedom, its displacement vector can be written as:

[0102] Y V = [y1 y2 y3 y4] Y (2-2) For each rigid body in the aircraft model force analysis, according to the d'Alembert principle can be listed in the aircraft vibration equation:

[0103]

[0104] The above formula for four degrees of freedom force balance equation, f1, f2, f3, f4 are four degrees of freedom on the size of the force.

[0105] For ease of programming, the equation is arranged in matrix form:

[0106] Wherein,

[0107]

[0108] From the load vector on the right side of (2-4) formula can be seen, the aircraft load contains due to bridge deformation caused by elastic force and damping force, the load component will be coupled with the aircraft vibration equation and bridge structure vibration equation, become a coupled vibration system.

[0109] (2) bridge model

[0110] The bridge structure is discretized, after discretization, the bridge dynamic equation can be written as:

[0111]

[0112] Wherein, The acceleration, velocity, displacement vector of the bridge structure, respectively. M B The mass matrix of the bridge structure, C B The damping matrix of the bridge structure, K B The stiffness matrix of the bridge structure. F B The load vector of the bridge structure, it includes two parts: one part is the force on the structure of the external environment (such as wind load, rain load, etc.), the other part is the node force of the aircraft on the bridge node. The external load in this project is 0.

[0113] c = a0M + β0K (2-6)

[0114] Rayleigh damping is used for the bridge structure. As shown in formula (2-6), the damping matrix of the structure is defined by two parameters, α0 and β0, as well as the stiffness matrix K and mass matrix M. α0 and β0 can be obtained from formulas (2-7) and (2-8):

[0115]

[0116] α0=2ε1ω 01 -β0ω 01 ω 01 (2-8)

[0117] Where, ω 01 ω 02 ∈1 and ∈2 represent the first and second natural frequencies of the structure, respectively. ∈1 and ∈2 represent the first and second modal damping of the structure, respectively.

[0118] (3) Bridge deck irregularity model

[0119] The unevenness of the bridge surface can excite moving aircraft, thereby altering their vibration state and causing random variations in wheel load. This effect cannot be ignored in the coupled vibration of the aircraft and the bridge; therefore, the influence of road surface irregularities should be considered in the analysis of coupled vibration of the aircraft and the bridge. Research results from relevant literature indicate that road surface irregularities on bridges can be described as a zero-mean stochastic process following a steady-state Gaussian distribution. The statistical characteristics of this stochastic process can be described by the power spectrum.

[0120]

[0121] In the formula, ω0 is the reference spatial frequency, taken as 0.1m. -1 ω is the spatial frequency, and S(ω0) is the power spectral density value at the reference spatial frequency.

[0122] Given the power spectrum of road surface irregularities, various methods can be used to simulate road surface irregularities, such as the trigonometric series superposition method, the quadratic filtering method, the AR model method, or the ARMA model method. The simulation of road surface irregularities using the trigonometric series superposition method is as follows:

[0123]

[0124] Δω=(ω u -ω l ) / N (2-13)

[0125] Where r(x) is the road surface irregularity sample function, α k Let ω be the amplitude of the cosine function. k It is located in the power spectral density defined range [ω l ωu ] the frequency of the road roughness. k is a random phase angle uniformly distributed between 0 and 2π, x is the local coordinate, which represents the distance from the left end of the bridge, N is the number of points of the simulated random roughness. S(ω k ) is the power spectral density function defined in the interval [ω l , ω u ] as a function of the spatial frequency of the road roughness:

[0126]

[0127] where α is the roughness coefficient, and the exponent β is taken as 1.94.

[0128] A program RP (Roadway Profile) for generating road roughness samples is developed by using the trigonometric series superposition method. Figure 3 are the sample curves of the road roughness on the bridge of the first, third and fifth grades, respectively, which correspond to the roughness of the bridge surface of the good, general and poor grades, respectively.

[0129] (4) Numerical analysis of the bridge-vehicle coupling vibration considering the roughness of the bridge surface

[0130] It is assumed that the aircraft is in direct contact with the bridge surface during the flight. The interaction force between the wheel and the bridge surface can be expressed as:

[0131]

[0132] where f i (t) is the interaction force between the i-th wheel and the bridge surface, k i is the stiffness of the i-th row of the bridge surface stiffness matrix K, c i is the roughness damping coefficient of the i-th wheel corresponding to the bridge surface, and the subscript i represents the contact point between the i-th wheel and the bridge surface. is the vertical acceleration of the i-th wheel at time t relative to the bridge surface, Δ i (t) is the vertical displacement of the i-th wheel at time t relative to the bridge surface, and its expression is:

[0133] Δ i (t) = y i (t) - z i (t) - r i

[0134] where y i (t) is the vertical displacement of the i-th wheel at time t, z i (t) is the vertical displacement of the bridge surface at time t at the contact point between the i-th wheel and the bridge surface, and r i is the sample value of the bridge surface roughness at the contact point between the i-th wheel and the bridge surface.

[0135] The aircraft vibration equation and the taxiway bridge equation are solved by the displacement of the contact point to establish the aircraft-taxiway bridge coupling vibration equation considering the road unevenness.

[0136]

[0137] The dynamic equations of the aircraft and the bridge are coupled by the coordination conditions that the displacements at the contact points of the wheels and the bridge surface are the same and the interaction forces are equal. Since the interaction forces between the aircraft and the bridge are related to the motion state of the aircraft and the deformation of the bridge, the two sets of coupled time-varying second-order differential equations need to be solved iteratively.

[0138] Obviously, the matrix equation is a time-varying equation that will change with the change of the wheel positions and the external load, and therefore needs to be solved by the step-by-step integration method.

[0139] There are mainly three methods for step-by-step integration: linear acceleration method, New-mark-β method and Wilson-0 method, which ignore the internal force imbalance of the time period, describe the initial time-varying characteristics at each time node, use the velocity and displacement of the seven points as the initial state of the next time period, and finally obtain the time history curve of the entire system.

[0140] Example 3

[0141] As shown in Figure 4 A microwave radar-based aircraft load bridge monitoring system includes a microwave radar 1 arranged on a pier or abutment of an aircraft load bridge, a target 2 arranged on the bottom surface of the midspan of the aircraft load bridge, a camera 3 arranged on one side of the aircraft load bridge, and a control processing system 4 electrically connected with the microwave radar 1 and the camera 3.

[0142] The microwave radar 1 is used to emit microwaves to the target 2 and obtain the actual dynamic displacement of the midspan of the aircraft load bridge in real time through the echo signal, and then output to the control processing system 4 and form the actual dynamic displacement curve of the midspan, the camera 3 is used to observe the aircraft passing through the aircraft load bridge and output the video to the control processing system 4, the control processing system 4 is used to analyze the video and identify the aircraft model and aircraft speed, the control processing system 4 is used to compare the identified aircraft model and aircraft speed with the flight information in the airport data system to obtain the aircraft flight number and aircraft mass, the control processing system 4 is used to obtain the coupling dynamic displacement of the midspan of the aircraft load bridge and the coupling dynamic displacement curve of the midspan according to the aircraft speed and the aircraft mass, and the control processing system 4 is used to compare the actual dynamic displacement of the midspan with the coupling dynamic displacement of the midspan and judge whether the aircraft load bridge needs to be repaired.

[0143] The control processing system 4 comprises a visual recognition module 41 and a nonlinear numerical calculation module 42 which are electrically connected, the visual recognition module 41 is electrically connected with the camera 3 and the airport data system, and the nonlinear numerical calculation module 42 is electrically connected with the microwave radar 1 and the target 2;

[0144] The microwave radar 1 is used for emitting microwaves to the target 2 and obtaining the actual dynamic displacement of the aircraft load bridge in real time through the echo signal, and then outputting to the nonlinear numerical calculation module 42 and forming the actual dynamic displacement curve of the aircraft load bridge, the camera 3 is used for observing the aircraft passing through the aircraft load bridge and outputting the video to the visual recognition module 41, the visual recognition module 41 is used for analyzing the video and identifying the aircraft model and the aircraft speed, and obtaining the aircraft flight number and the aircraft mass according to the flight information in the airport data system and outputting to the nonlinear numerical calculation module 42, the nonlinear numerical calculation module 42 is used for obtaining the coupling dynamic displacement of the aircraft load bridge and the coupling dynamic displacement curve of the aircraft load bridge according to the aircraft speed and the aircraft mass, and the nonlinear numerical calculation module 42 is used for comparing the actual dynamic displacement with the coupling dynamic displacement and judging whether the aircraft load bridge needs to be repaired.

[0145] Embodiment 4

[0146] As shown in Figures 4-5 , a microwave radar-based aircraft load bridge monitoring system comprises a microwave radar 1, a target 2, a camera 3, and a control processing system 4, the control processing system 4 comprises a data line, a computer, and a software system, the software system comprises a visual recognition module 41 and a nonlinear numerical calculation module 42 which are electrically connected;

[0147] The microwave radar 1 is installed on the pier or abutment of the aircraft load bridge; the target 2 is hung on the bottom surface of the bridge span; the camera 3 is installed near the bridge and can observe the aircraft passing through the bridge in real time; the data line connects the microwave radar 1 and the camera 3 to the computer; the software system is installed in the computer and is responsible for processing radar and video data and performing structural calculation.

[0148] The aircraft load bridge, the aircraft running thereon, and the radar, target, and camera structure are as shown in Figure 4 ;

[0149] The microwave radar 1 emits microwaves to the target 2 in real time, and the dynamic displacement of the aircraft load bridge span can be obtained in real time through the echo signal, and the dynamic displacement data of the bridge span are transmitted to the control processing system 4 through the data line, and the target at the bottom surface of the bridge span and the dynamic displacement data of the bridge span are as shown in Figure 5 .

[0150] Embodiment 5

[0151] As shown in Figure 4 , a microwave radar-based aircraft load bridge monitoring system comprises the following components:

[0152] 1. Microwave radar: installed on the piers or abutments of the aircraft load bridge, used to emit microwaves to the bottom surface of the bridge span and receive the reflected microwave signals, and analyze these echo signals to monitor the dynamic displacement of the bridge span in real time.

[0153] 2. Target: fixed on the bottom surface of the aircraft load bridge span, serving as a reflection target for the microwave radar to emit microwaves, ensuring accurate reception of signals.

[0154] 3. Camera: installed at a suitable position near the bridge, capable of clearly observing and recording the passing aircraft on the bridge, capturing image information of the aircraft.

[0155] 4. Control processing system: composed of two main modules: visual recognition module: electrically connected with the camera and airport data system, responsible for receiving video data transmitted by the camera, analyzing video content to identify the model and speed of the aircraft, and comparing these information with flight information in the airport data system to determine the flight number and quality of the aircraft.

[0156] Nonlinear numerical calculation module: electrically connected with the microwave radar and target, receiving the dynamic displacement data of the bridge span from the microwave radar, combining the aircraft information provided by the visual recognition module, and using nonlinear numerical calculation method to calculate the coupled dynamic displacement of the bridge span under the aircraft load and the corresponding displacement curve.

[0157] The control processing system integrates the actual dynamic displacement data and coupled dynamic displacement data to evaluate the health condition of the bridge and determine whether maintenance is needed. In addition, the control processing system also includes computer hardware and corresponding software system for data storage and processing, ensuring the accuracy of data and efficient operation of the system.

[0158] The above is only the preferred specific implementation of the present application, but the protection scope of the present application is not limited to this. Any skilled person in the art can make equivalent replacements or changes to the technical solution and inventive concept of the present application within the technical scope disclosed by the present application, which should be covered within the protection scope of the present application.

Claims

1. A method for monitoring aircraft loads on bridges based on microwave radar, characterized in that: Includes the following steps: S1. Obtain monitoring data: Set the microwave radar (1) on the pier or abutment of the aircraft load bridge, set the target (2) on the bottom surface of the mid-span of the aircraft load bridge, set the camera (3) on one side of the aircraft load bridge, and electrically connect the control processing system (4) to the microwave radar (1) and the camera (3). The control processing system (4) includes an electrically connected visual recognition module (41) and a nonlinear numerical calculation module (42). The microwave radar (1) emits microwaves to the target (2) and obtains the actual dynamic displacement of the bridge under aircraft load in real time based on the echo signal. The output is sent to the nonlinear numerical calculation module (42), and then the actual dynamic displacement curve at the mid-span is obtained. The visual recognition module (41) obtains the aircraft model, aircraft speed and aircraft mass m1 based on the video of the aircraft passing over the aircraft load bridge captured by the camera (3) and outputs it to the nonlinear numerical calculation module (42). Proceed to steps S2, S3, and S4 respectively; S2. Obtain the aircraft load components; establish an aircraft load model by analyzing the aircraft's stress conditions, and obtain the aircraft load components F. V Proceed to step S5; S3. Obtain the bridge load vector: By discretizing the bridge structure under aircraft load, the bridge load vector F is obtained. B Proceed to step S5; S4. Obtain bridge surface irregularity sample: Based on the power spectrum S(ω) of the bridge surface irregularity under aircraft load, obtain the surface irregularity sample r(x) and proceed to step S5. S5. Axle-coupled vibration analysis: Based on the aircraft load component F... V The bridge load vector F B Couple the aircraft wheel and bridge deck contact point with the road surface irregularity sample r(x) to establish a coupled aircraft-bridge vibration model under the condition that the displacements of the aircraft wheels and the interaction forces are the same and the magnitudes of the interaction forces are equal, and obtain the mid-span coupled dynamic displacement and mid-span coupled dynamic displacement curve of the aircraft-loaded bridge. S6. Monitoring result judgment and output: The nonlinear numerical calculation module (42) compares the actual dynamic displacement at mid-span with the coupled dynamic displacement at mid-span and judges whether the aircraft-loaded bridge needs to be inspected before outputting the monitoring result. Return to step S1 and continue monitoring.

2. The method for monitoring aircraft loads on bridges based on microwave radar according to claim 1, characterized in that: In step S1, the nonlinear numerical calculation module (42) obtains the aircraft model and the aircraft speed based on the aircraft video, and then obtains the aircraft flight number and the aircraft mass m1 by comparing it with the flight information in the airport data system. In step S2, Among them, M V Let Y be the mass matrix of the aircraft. V Let be the displacement vector of the aircraft. Let V be the velocity vector of the aircraft. Let C be the acceleration vector of the aircraft. V Let K be the damping matrix of the aircraft. V Here is the stiffness matrix of the aircraft; In step S3, Among them, M B Let Y be the mass matrix of the bridge under aircraft load. B Let be the displacement vector of the bridge under aircraft load. The velocity vector of the bridge under aircraft load. Let C be the acceleration vector of the bridge under aircraft load. B Let K be the damping matrix of the bridge under aircraft load. B This is the stiffness matrix of the bridge under aircraft load.

3. The method for monitoring aircraft loads on bridges based on microwave radar according to claim 2, characterized in that: In step S2, Y V =[y1 y2 y3 y4] T ; Wherein, m2 is the mass of the rear wheel, m3 is the mass of the front wheel, J is the moment of inertia, l1 is the horizontal distance from the rear wheel to the aircraft's center of gravity, l2 is the horizontal distance from the front wheel to the aircraft's center of gravity, l is the wheelbase of the rear wheel, k1 is the stiffness coefficient of the interaction between the rear wheel and the bridge deck, k2 is the stiffness coefficient of the connection between the aircraft body and the rear wheel, k3 is the stiffness coefficient of the connection between the aircraft body and the front wheel, k4 is the stiffness coefficient of the interaction between the front wheel and the bridge deck, c1 is the damping coefficient of the interaction between the rear wheel and the bridge deck, c2 is the damping coefficient of the connection between the aircraft body and the rear wheel, c3 is the damping coefficient of the connection between the aircraft body and the front wheel, c4 is the damping coefficient of the interaction between the front wheel and the bridge deck, y1 is the vertical displacement of the rear wheel, y2 is the vertical displacement of the rear end of the aircraft body above the rear wheel, y3 is the vertical displacement of the front end of the aircraft body above the front wheel, and y4 is the vertical displacement of the front wheel.

4. The method for monitoring aircraft loads on bridges based on microwave radar according to claim 2, characterized in that: In step S3, the damping matrix C of the aircraft load bridge B Rayleigh damping is used, and the external load damping is zero; C B =α0M+β0K; Among them, α0=2ε1ω 01 -b0ω 01 oh 01 ; ω 01 ω 02 ε1 and ε2 are the first and second natural frequencies of the structure, respectively; ε1 and ε2 are the first and second modal dampings of the structure, respectively; M is the mass matrix; and K is the stiffness matrix.

5. The method for monitoring aircraft loads on bridges based on microwave radar according to claim 1, characterized in that: In step S4, Where ω0 is the reference space frequency, and ω0 is 0.1m. -1 ω is the spatial frequency, S(ω0) is the power spectral density value at the reference spatial frequency, and β is a coefficient proportional to stiffness. The road surface irregularity sample r(x) was obtained by using the trigonometric series superposition method, the quadratic filtering method, the AR model method, and the ARMA model method. In step S5, the coupled vibration equation of the aircraft-bridge coupled vibration model is: Among them, f i (t) represents the interaction force between the i-th wheel and the bridge deck of the aircraft load, k i Let c be the stiffness corresponding to the i-th row of the bridge deck stiffness matrix K. i Let be the bridge deck roughness damping coefficient corresponding to the i-th wheel. Let Δ be the vertical acceleration of the i-th wheel relative to the bridge deck at time t. i (t) represents the vertical displacement of the i-th wheel relative to the bridge deck at time t, y i (t) represents the vertical displacement of the i-th wheel at time t, z i (t) represents the vertical displacement of the bridge deck at time t at the contact point between the i-th wheel and the bridge deck, r i Sample value of bridge deck irregularities at the contact point between the i-th wheel and the bridge deck.

6. The method for monitoring aircraft loads on bridges based on microwave radar according to claim 5, characterized in that: In step S4, the road surface irregularity sample r(x) is obtained by simulation using the trigonometric series superposition method; Where, α k Let ω be the amplitude of the cosine function. k For the power spectral density defined range [ω l ω u The frequency within θ k Let S(ω) be a random phase angle uniformly distributed between 0 and 2π, x be a local coordinate, x be the distance of a point on the bridge from the left end of the bridge, N be the number of simulated random irregularities, and S(ω) be the random phase angle. k The power spectral density function in the interval [ω] l ω u The value is defined as a function of the spatial frequency of road surface irregularities. Where α is the smoothness coefficient and β is the exponent.

7. The method for monitoring aircraft loads on bridges based on microwave radar according to claim 5, characterized in that: In step S5, The coupled vibration equations are solved using the linear acceleration method, the New-mark-β method, and the Wilson-0 method.

8. The method for monitoring aircraft loads on bridges based on microwave radar according to claim 1, characterized in that: In step S6, the criteria for determining whether the aircraft-loaded bridge needs maintenance are as follows: when the peak value of the actual dynamic displacement curve at the mid-span is 10% higher than the peak value of the coupled dynamic displacement curve at the mid-span, or when the time integral of the actual dynamic displacement curve at the mid-span is 20% higher than the time integral of the coupled dynamic displacement curve at the mid-span, the aircraft-loaded bridge has a safety problem and needs maintenance.

9. A monitoring system for a method of monitoring aircraft loads on bridges based on microwave radar according to any one of claims 1 to 8, characterized in that: The microwave radar (1) is used to emit microwaves to the target (2) and obtain the actual mid-span dynamic displacement of the aircraft load bridge in real time through the echo signal, and output it to the control and processing system (4) to form the actual mid-span dynamic displacement curve. The camera (3) is used to observe the aircraft passing over the aircraft load bridge and output the video to the control and processing system (4). The control and processing system (4) is used to analyze the video and identify the aircraft model and aircraft speed. The control and processing system (4) is used to compare the identified aircraft model and aircraft speed with the flight information in the airport data system to obtain the aircraft flight number and aircraft mass. The control and processing system (4) is used to obtain the mid-span coupled dynamic displacement and mid-span coupled dynamic displacement curve of the aircraft load bridge according to the aircraft speed and the aircraft mass. The control and processing system (4) is used to compare the actual mid-span dynamic displacement with the mid-span coupled dynamic displacement and determine whether the aircraft load bridge needs maintenance.

10. The monitoring system according to claim 9, characterized in that: The visual recognition module (41) is electrically connected to the camera (3) and the airport data system, and the nonlinear numerical calculation module (42) is electrically connected to the microwave radar (1) and the target (2). The microwave radar (1) is used to emit microwaves to the target (2) and obtain the actual mid-span dynamic displacement of the aircraft load bridge in real time through the echo signal, and output it to the nonlinear numerical calculation module (42) to form the actual mid-span dynamic displacement curve. The camera (3) is used to observe the aircraft passing over the aircraft load bridge and output the video to the visual recognition module (41). The visual recognition module (41) is used to analyze the video and identify the aircraft model and speed, and obtain the aircraft flight number and aircraft mass according to the flight information in the airport data system and output them to the nonlinear numerical calculation module (42). The nonlinear numerical calculation module (42) is used to obtain the mid-span coupled dynamic displacement and the mid-span coupled dynamic displacement curve of the aircraft load bridge according to the aircraft speed and the aircraft mass. The nonlinear numerical calculation module (42) is used to compare the actual mid-span dynamic displacement with the mid-span coupled dynamic displacement and determine whether the aircraft load bridge needs to be repaired.

Images