WO2023151681A1 - 一种无源激振式桥梁探伤装置 - Google Patents

一种无源激振式桥梁探伤装置 Download PDF

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Publication number
WO2023151681A1
WO2023151681A1 PCT/CN2023/075733 CN2023075733W WO2023151681A1 WO 2023151681 A1 WO2023151681 A1 WO 2023151681A1 CN 2023075733 W CN2023075733 W CN 2023075733W WO 2023151681 A1 WO2023151681 A1 WO 2023151681A1
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Prior art keywords
excitation
damage
stiffness
bridge
frequency
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PCT/CN2023/075733
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English (en)
French (fr)
Inventor
林萍
郭河
乔磊
夏兴佳
宋浩
王世成
胡祝友
向志海
陆秋海
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中交基础设施养护集团有限公司
中交路桥检测养护有限公司
清华大学
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Publication of WO2023151681A1 publication Critical patent/WO2023151681A1/zh

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N29/00—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
    • G01N29/04—Analysing solids
    • G01N29/045—Analysing solids by imparting shocks to the workpiece and detecting the vibrations or the acoustic waves caused by the shocks
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N29/00—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
    • G01N29/36—Detecting the response signal, e.g. electronic circuits specially adapted therefor
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N29/00—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
    • G01N29/44—Processing the detected response signal, e.g. electronic circuits specially adapted therefor
    • G01N29/46—Processing the detected response signal, e.g. electronic circuits specially adapted therefor by spectral analysis, e.g. Fourier analysis or wavelet analysis
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2291/00—Indexing codes associated with group G01N29/00
    • G01N2291/02—Indexing codes associated with the analysed material
    • G01N2291/023—Solids
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2291/00—Indexing codes associated with group G01N29/00
    • G01N2291/02—Indexing codes associated with the analysed material
    • G01N2291/028—Material parameters
    • G01N2291/0289—Internal structure, e.g. defects, grain size, texture
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2291/00—Indexing codes associated with group G01N29/00
    • G01N2291/26—Scanned objects
    • G01N2291/269—Various geometry objects

Definitions

  • the invention belongs to the technical field of bridge detection, and in particular relates to a passive excitation bridge flaw detection device.
  • the uniformly distributed excitation teeth on a single excitation wheel perform passive excitation with a fixed excitation frequency on the bridge deck, and the vibration is collected by an acceleration sensor.
  • the acceleration signal transmitted from the surface of the bridge to the excitation wheel by considering the influence of the derivative term of the equivalent stiffness to time on the acceleration amplitude, the stiffness change edge is obtained, and the stiffness is analyzed in the time domain controlled by the second derivative of the equivalent stiffness to time The moment of sudden change, and then look for the inflection point in the power spectrum near this moment to determine the position of the bridge disease and evaluate the degree of disease.
  • the application number is CN201810339418.3
  • the invention patent titled "A Passive Percussion Type Material Damage Detection Device and Method” proposes a self-balancing inspection vehicle, which replaces the double wheels of the self-balancing vehicle with surface-mounted excitation teeth.
  • the excitation wheel knocks on the surface of the material while driving, and the sensor collects the signal of the detection area, calculates the damage indication value of the detection surface by collecting the spectrum envelope of the detection signal, and calculates the position where the damage indication value suddenly drops Determine the location of the damage, and measure the degree of damage by the size of the mutation.
  • the damage indication value determination method leads to a large amount of calculation and is complicated.
  • the design of the double excitation wheel also leads to the interference between the feedback signals due to the different tapping positions, which increases the While signal analysis is difficult, it also reduces the accuracy of detection results.
  • the present invention provides a passive excitation bridge flaw detection device, which utilizes evenly distributed excitation teeth on a single excitation wheel to passively excite the bridge deck with a fixed excitation frequency, and collects bridge surface data through an acceleration sensor.
  • the acceleration signal transmitted to the excitation wheel, the stiffness change edge is obtained by considering the influence of the derivative term of the equivalent stiffness to time on the acceleration amplitude, and the stiffness mutation moment is analyzed in the time domain controlled by the second derivative of the equivalent stiffness to time , and then look for the inflection point in the power spectrum near this time to determine the bridge The location of the disease and assess the extent of the disease.
  • a passive excitation vibration bridge flaw detection device comprising: an excitation part, a damage location and evaluation part and a counterweight connection part, characterized in that,
  • the excitation part includes an excitation wheel with evenly distributed excitation teeth on the surface, which is used to passively excite the bridge deck with a fixed excitation frequency.
  • the two ends of the center bearing of the excitation wheel are fixed with a fixed piece with a rectangular end surface.
  • the fixed piece It is fixed in the end groove of the strapping plate through bolt connection, and an acceleration sensor is arranged on the axle, which is used to collect the acceleration signal transmitted from the surface of the bridge to the exciting teeth;
  • the damage location and evaluation part determines the moment when the sudden change in stiffness is detected by the maximum value point of the equivalent acceleration extracted from the time-frequency analysis result, and determines the damage position of the bridge corresponding to the inflection point in the power spectrum diagram and evaluates the damage degree;
  • the counterweight connection part includes a square groove member and a strap, and the square groove member connects the driving part of the front body and the excitation part of the rear body through slots and bolts; the strap is welded and fixed on the square groove member, and includes a Top fret joints and support arms for increased torsional rigidity, and bottom square steel joints for increased bending stiffness.
  • damage localization steps of the damage localization and evaluation part are as follows:
  • loc s ⁇ i
  • Q i > ⁇ Q +B ⁇ Q ,i 1,2,...,n ⁇ ;
  • B is noise interference degree
  • G and H are dimensionless coefficients calibrated in advance.
  • the evenly distributed excitation teeth on the excitation wheel of the present invention perform passive excitation with a fixed excitation frequency on the bridge deck, which simplifies the detection structure and avoids interference between excitation sources, and determines the rigidity mutation through the power spectrum corresponding to the acceleration peak mutation time Point, the detection method is simple and efficient, and improves the detection accuracy.
  • Fig. 1 is the front view of the body of the bridge flaw detection vehicle
  • Fig. 2 is a side view of the body of the bridge flaw detection vehicle
  • Figure 3 is a schematic diagram of the assembly of the excitation part and the counterweight connection part
  • Fig. 4 is the schematic diagram of counterweight connecting part
  • Fig. 5 is the schematic diagram of boarding
  • Fig. 6 is the schematic diagram of square groove member
  • Fig. 7 is the schematic diagram of excitation part
  • Fig. 8 is a schematic diagram of a basic model of the percussion scanning method
  • Fig. 9 is a schematic diagram of a damaged beam model
  • Fig. 10 is the natural frequency distribution form diagram of the trolley when the beam has a sudden change in stiffness
  • Fig. 12 is a distribution diagram of the section moment of inertia, wherein Fig. 12 (a) is the actual stiffness ratio curve, and Fig. 12 (b) is the weighted stiffness ratio curve;
  • Figure 13 is the distribution diagram of ⁇ w under different window lengths, where the window length in Figure 13(a) is 2m, the window length in Figure 13(b) is 1m, and the window length in Figure 13(c) is 0.5m;
  • Figure 15 is when considering the extreme point at the abrupt change of stiffness, where, Figure 15(a) is and the distribution data point diagram of ⁇ , Fig. 15 is (b) is a quadratic curve fitted according to the data points in Fig. 15(a), and Fig. 15(c) is and the distribution data point diagram of ⁇ s , Fig. 15(d) is a quadratic curve diagram fitted according to the data points in Fig. 15(c);
  • Fig. 17 (a) is the structural representation of experimental beam
  • Fig. 17 (b) is the side view of experimental beam
  • Figure 18 is the natural frequency spectrum of the test car model
  • Fig. 19(a) is a curve diagram of detection vehicle acceleration
  • Fig. 19(b) is a corresponding power spectral density diagram
  • Figure 20(a) is the distribution of the equivalent acceleration Y max of the detection vehicle and the detection points, and Figure 20(b) is the corresponding power spectral density diagram;
  • Figure 21 is a distribution diagram of the equivalent acceleration of the detection vehicle
  • Fig. 22(a) the vertical vibration frequency is ⁇ 78Hz.
  • Fig. 22(a-1) is the side-view modal simulation diagram of the rear of the monitoring vehicle, and Fig. 22(a-2) is the upward-view modal simulation of the rear of the monitoring vehicle. picture;
  • Figure 22(b) the vertical vibration frequency ⁇ 103Hz
  • Figure 22(b-1) is the side view modal simulation diagram of the monitoring vehicle rear
  • Figure 22(b-2) is the upward view modal simulation of the monitoring vehicle rear picture
  • Fig. 22(c) the vertical vibration frequency ⁇ 117Hz
  • Fig. 22(c-1) is the simulation diagram of the front-view mode of the rear of the monitoring vehicle
  • Fig. 22(c-2) is the rear-view modality of the monitoring car’s rear simulation diagram
  • Fig. 22(d) the vertical vibration frequency is ⁇ 254Hz.
  • Fig. 22(d-1) is the simulation diagram of the front view modal of the rear of the monitoring vehicle, and Fig. 22(d-2) is the rear view modal of the monitoring car rear. simulation diagram;
  • Fig. 22(e) the vertical vibration frequency ⁇ 339Hz
  • Fig. 22(e-1) is the simulation diagram of the front view mode of the rear of the monitoring vehicle
  • Fig. 22(e-2) is the rear view mode of the monitoring vehicle rear simulation diagram
  • Fig. 23(a) is the modal simulation diagram of the whole vehicle when the vertical vibration frequency ⁇ 60 Hz;
  • Fig. 23(b) is the modal simulation diagram of the whole vehicle when the vertical vibration frequency ⁇ 69 Hz;
  • Fig. 23(c) is a modal simulation diagram of the whole vehicle when the vertical vibration frequency ⁇ 74Hz;
  • Fig. 23(d) is the modal simulation diagram of the whole vehicle when the vertical vibration frequency ⁇ 87Hz;
  • Fig. 23(e) is a modal simulation diagram of the whole vehicle when the vertical vibration frequency ⁇ 101 Hz;
  • Fig. 23(f) is the modal simulation diagram of the whole vehicle when the vertical vibration frequency ⁇ 152Hz;
  • Fig. 24 is a schematic diagram of the working mode of the detection vehicle
  • the invention provides a body structure of a bridge flaw detection vehicle, which includes: a driving part, an exciting part and a counterweight connecting part.
  • the driving part includes two driving wheels 1 installed on the frame 3, two 10-inch 500W hub motors, a suspension system 2 and a hardware box 4.
  • the suspension system 2 may include a hydraulic nitrogen shock absorber, which is used to reduce the noise of the driving wheel to reduce the interference to the excitation signal.
  • the top of the vehicle frame 3 is provided with an installation position for installing an attitude sensor, and the attitude sensor is used to realize semi-supervised inertial navigation.
  • a battery and a control system can be arranged in the hardware box 4 .
  • the counterweight connection part 6 is composed of a square groove member 7 and a strap 8 .
  • Lap plate 8 is welded and fixed on the square groove member 7 .
  • the square groove member 7 connects the driving part of the front body and the excitation part of the rear body through four slots 10 and bolts.
  • the strap 8 includes a top character connection part and a support arm for enhancing torsional rigidity, and a bottom square steel connection part for enhancing bending rigidity, and the bottom square steel connection part is provided with two end grooves 11 .
  • the excitation part 9 includes an excitation wheel 13 with uniformly distributed excitation teeth on its surface.
  • a flange 14 is arranged in the hub ring of the excitation wheel 13, and the center bearing 12 of the flange 14 is inserted into the round shaft to fix it.
  • the two ends of the center bearing 12 are fixed with a fixing piece 16 with a rectangular end surface, and the fixing piece 16 is fixed on the strap through bolt connection. 8 in the end groove 11.
  • the center bearing 12 may be a deep groove ball bearing.
  • a sensor mounting position 15 is arranged on the circular shaft, and the sensor may be an IEPE accelerometer.
  • the exciting wheel 13 can be made of a rubber tire with a hardness of 75A and an aluminum hub.
  • the parameters of the excitation wheel 13 are as follows, the radius r is 125 mm, the width is 50 mm, and the number n of patterns of the rubber tire is 72.
  • the characteristic point corresponding to the derivative term is found by using the degree of sudden change of the stiffness mutation point on the beam to approximate the quadratic relationship with the square root of the acceleration amplitude or power spectral density of the trolley Carry out disease localization.
  • the rapid bridge stiffness abnormal point detection mode of the bridge flaw detection vehicle is the rapid bridge stiffness abnormal point detection mode of the bridge flaw detection vehicle
  • each module can be divided into user end, control mode selection, upper computer, lower computer and underlying hardware from top to bottom.
  • the user end needs to select the control method according to the needs.
  • the lower computer can be directly controlled by short-distance remote control to realize quick steering or U-turn; while in the inspection process, the semi-supervised inertial navigation method is adopted, that is, the inspection vehicle mainly The inertial navigation is used to detect at a fixed speed, but if the inertial navigation sensor has a large deviation due to expansion joints on the way, the user can correct it.
  • the functions of the upper computer include receiving and processing instructions from the client, collecting inertial navigation sensor data and detection data, and analyzing and storing detection data.
  • the upper computer after receiving user instructions, sends the tasks required for detection implementation to the lower computer for execution, receives feedback from the lower computer, and finally feeds back the processed detection results to the client for viewing.
  • the function of the lower computer is mainly to complete various hardware control tasks, including driving the motor, speed collection, power and temperature monitoring, and emergency stop for obstacle avoidance.
  • Fig. 8 is the basic model of the percussion scanning method, in which the bending stiffness of the Euler-Bernoulli beam is EI, the mass per unit length is m, and the damping coefficient is ⁇ B .
  • the trolley is simplified as a combination of a rigid body of mass M V and wheels of mass M W .
  • the joint stiffness between the body and the wheels is k V , and the damping coefficient is ⁇ V .
  • the contact stiffness of the wheel and beam is kW and the damping coefficient is ⁇ W .
  • the roughness of the road surface is represented by r(x).
  • the excitation tooth of the wheel can be regarded as a layer of contact interface without thickness (that is, the displacement of the excitation tooth is the displacement of the beam there), and its stiffness and damping are converted into kW and ⁇ W .
  • the inertial force generated by the mass MT of the excitation tooth is the passive knocking force FT .
  • the force F V acting on the vehicle body is exactly the active percussion force.
  • all displacements and forces take the y direction as the positive direction; the subscripts V, W, T and B represent the body, wheel, excitation tooth and beam, respectively.
  • a and ⁇ s represent the knocking force generated on the smooth surface and the rough disturbance respectively, and their magnitude is determined by the axle load and vehicle speed.
  • ⁇ s is the noise generated by the wheel sliding.
  • ⁇ 0 represents the duration of the exciting force
  • the tapping circle frequency is determined by the following formula:
  • the frequency of the tapping force F T is mainly ⁇ 0 .
  • ⁇ 0 will be set at a relatively high frequency.
  • the bridge displacement can be expressed as:
  • ⁇ j (x) sin (j ⁇ x/L) is the jth order mode of the bridge; q Bj (t) is the mode coordinates.
  • ⁇ Bj is the jth order natural circular frequency of the bridge:
  • (22) is a second-order linear ordinary differential equation with variable coefficients.
  • the force In the scientific model the actual damaged beam + non-destructive trolley is equivalent to the non-damaged beam + damaged trolley, that is, k is considered to be related to the suspension stiffness k V of the trolley and the damage of the contact point beam, so the equivalent natural frequency in (22) is function of time.
  • D varies with the position, it is a quadratic polynomial of ⁇ outside the damaged area, and a quartic polynomial of ⁇ inside the damaged area, and takes the extreme value at the center of the damaged area.
  • ⁇ V in (22) is a piecewise function.
  • the stiffness distribution of the trolley is as above, other parameters remain unchanged
  • the excitation frequency is 141Hz and 131Hz respectively
  • the influence of ⁇ V and its derivatives on the acceleration is shown in Figure 11.
  • d 2 ⁇ V /dt 2 has the greatest influence on the amplitude, but the smallest influence range (as shown in the arrow position in Figure 11), and ⁇ V has less influence on the amplitude but the largest influence range.
  • the scope of influence is mainly determined by the width of each quantity in the time domain with a large mutation value in Figure 10, that is, the influence only exists within the length range of the stiffness change section, so the stiffness can be located by analyzing the change of the acceleration amplitude of the trolley changing position.
  • PSD max is the maximum value of the power spectral density in the frequency domain at each moment
  • Y max is related to the window function used in STFT analysis, so the variable ⁇ in (32) also needs to be added according to the actual analysis.
  • window, at this time, one-to-one correspondence with Y max is the weighted stiffness value within the width of the window function.
  • the weighted stiffness ratio ⁇ w has anti-symmetry, so for 6m in Figure 12(a)
  • the window length will change the position of this type of inflection point, mainly affecting the position of the inflection point when the sliding window gradually leaves the stage of the abrupt change in stiffness, as shown in Fig. 13 at the inflection points at 6.75m, 6.375m, and 6.25m.
  • the value of the position of the inflection point generated when the window length has less influence on entering the sudden change point is recorded as ⁇ s (the inflection point at 5.75m, 5.875m, and 5.937m), that is, the first inflection point is used as a measure of where The index of the abrupt change of stiffness, and for the gradual stiffness at about 8.5m as shown in Figure 12(a), the value of the inflection point (the first inflection point) which is less affected by the window length is also taken as the measurement index.
  • ⁇ s is equivalent to ⁇ without windowing.
  • the acceleration of the car is shown in Figure 14. If the influence of the derivative term on the acceleration amplitude is considered (stiffness change edge, data points shown in Figure 14), the peak point near the stiffness abrupt edge (the area controlled by the second-order derivative term can be determined according to Figure 10) can be analyzed, while For the power spectrum diagram, since the width of the sudden change signal is small, it is smoothed after windowing, and it is difficult to judge directly. Therefore, first determine the time of the characteristic point of the time domain signal, and then look for the inflection point in the power spectrum diagram near this moment.
  • ⁇ >1 the stiffness of the damaged segment increases, and the sign of the second derivative in the affected area changes.
  • the non-monotonic relationship between the amplitude of the feature point and ⁇ is that the inflection point of the approximate quadratic curve is in the right half plane. This is because the terms containing the second derivative have different influence directions on the magnitude of the acceleration at different times, resulting in the transformation of the feature points.
  • the degree of abrupt change in stiffness on the beam is approximately in a quadratic relationship with the square root of the acceleration amplitude of the trolley or the power spectral density, and the key is to find the characteristic point corresponding to the derivative term.
  • the acceleration is easily affected by low-frequency noise, so the power spectral density can be used for analysis.
  • the following algorithm is proposed for division:
  • loc s ⁇ i
  • Q i > ⁇ Q +B ⁇ Q ,i 1,2,...,n ⁇ (33)
  • the dimensionless coefficients G and H are calibrated by the test beam, so for the position of sudden change in stiffness, the degree of sudden change can be determined by the following formula:
  • the test specimen is a 12.16m long T-beam simply supported at both ends.
  • the beam has a central partition, and its two sides are symmetrical in structure. After a 2.55m long constant thickness web, there is a 2.15m long variable thickness web, and finally a 0.85m long web. Long webs of equal thickness are connected to the end diaphragms.
  • Figure 12 shows the distribution of the equivalent bending stiffness of the test beam cross section.
  • the rear part of the inspection vehicle weighs 75kg and has a single rear wheel structure, including the excitation wheel, round shaft and counterweight, etc.
  • the number of teeth of the excitation wheel is 72, which is composed of rubber and aluminum alloy. Made of stainless steel.
  • the acceleration collection point is on the circular axis, 20mm away from the midpoint of the rear axle.
  • the natural frequency of the detection vehicle is about 138Hz.
  • the testing vehicle travels on the test beam at a speed of about 1.5m/s from west to east, and the frequency of the exciting force generated is 138Hz. A total of 20 valid data were recorded.
  • the first axle acceleration signal and power spectral density are shown in Figure 19. It can be seen that the average acceleration of the car is about 0.5g.
  • the marked point in Figure 19(a) is the moment when the trolley passes the expansion joint, and the right side is the position of the expansion joint from the starting point of the trolley.
  • the difference between the two coordinates is about 12.1m, which is consistent with the length of the beam, so it can be based on the first
  • the position of the expansion joint positioning trolley on the bridge, and the abscissa of the subsequent results are based on the first expansion joint.
  • B be set to 1, and the processing result shown in Figure 20(a) can be obtained, where the line is Y max , and the circles are the abnormal points of stiffness mutation obtained after filtering. This result can be compared with that in Figure 20(a).
  • the marked points in 12 (b) are compared, and the statistical values of each position point are as shown in Table 1. It can be seen that the detection equipment and method adopted by the present invention can find the test beam at positions 1, 2, The sudden change point of stiffness corresponding to position 3 and 5, find the sudden change point of stiffness corresponding to position 4 with a 60% success rate.
  • Figure 21 shows the distribution of the equivalent acceleration at each position in Table 1 with the abrupt change in stiffness ⁇ s as the abscissa, where the data points are the mean and standard deviation of the equivalent acceleration corresponding to the five positions.
  • This distribution form is similar to the distribution in Figure 15.
  • ⁇ s is large (position 2.
  • ⁇ s 1.068
  • Y max is relatively large, Therefore, the overall quadratic function can be used to describe the relationship between Y max and ⁇ s .
  • Figure 22 shows the modal analysis of the rear axle under specific geometric parameters.
  • the boundary conditions are: the contact part between the excitation wheel and the ground is a fixed constraint, and the front surface of the square groove constrains the horizontal movement.
  • the main vibration elements of the mode in Figure 22(c) are the wheel shaft and the excitation wheel, and it is a vertical vibration mode with a frequency of 117Hz, which meets the requirements of the detection method.
  • the mode in Fig. 22(a), (b)(d) is the rotational vibration of the exciting wheel around its fixed point. This type of mode is mainly related to the shear stiffness of the exciting wheel and the relationship between the exciting wheel and the ground.
  • the mode in Figure 22(e) is the mode of bending and torsional coupling of the overall structure, and its frequency is 339Hz, which is much higher than the frequency of the mode in Figure 22(c). When the operating frequency is around 140Hz, the mode state will not interfere with the signal.
  • Figure 23 shows the modal analysis including the front body, and the constraint condition is the contact part between each wheel and the ground, which is a fixed constraint.
  • the mode in Figure 23(e) is a vertical vibration mode that meets the detection requirements, and the mode in Figure 23(d), which is similar to it, is the rotation mode of the excitation wheel, and the interference to the detection is reduced as mentioned above .
  • the frequency of the mode in Figure 23(f) is 152Hz, which is 51Hz different from the frequency of the mode in Figure 23(e). When the excitation frequency is near the frequency of the mode in Figure 23(e), the mode will not is excited and therefore does not interfere with the detection signal.

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Abstract

一种无源激振式桥梁探伤装置，包括：激励部分（9）、损伤定位和评估部分和配重连接部分（6），其中，激励部分（9）包括一个表面设置有均匀分布激励齿的激振轮（13），用于对桥面进行固定激振频率的无源激励，激振轮（13）的中心轴承（12）两端固定具有矩形端面的固定件（16），固定件（16）通过螺栓连接固定于搭板（8）的端槽（11）中，轮轴上设置有加速度传感器，用于采集桥梁表面传递到激振齿的加速度信号；损伤定位和评估部分通过从时频分析结果中提取的等效加速度的极大值点确定检测到刚度突变时刻，对应功率谱图中的拐点确定桥梁损伤位置并评估损伤程度。

Description

一种无源激振式桥梁探伤装置 技术领域
本发明属于桥梁检测技术领域，特别涉及一种无源激振式桥梁探伤装置，单一激振轮上均匀分布的激振齿对桥面进行固定激振频率的无源激励，并通过加速度传感器采集桥梁表面传递到激振轮的加速度信号，通过考虑等效刚度对时间的导数项对加速度幅值的影响得到刚度变化边缘，通过在等效刚度对时间的二阶导数项控制的时域内分析刚度突变时刻，再在该时刻附近寻找功率谱图中的拐点以确定桥梁病害位置并评估病害程度。
背景技术
伴随着过去30多年的经济快速发展，公路桥梁基建规模也随之快速增长。目前，国内已经投入使用的公路桥梁超过80多万座，总里程超过4000万米，在促进经济发展的同时，难以避免的随着时间推移，产生例如，建造工艺，材料，过载荷作用或环境等因素导致的不同程度的损伤，需要及时进行养护维修。
目前，公路桥梁的病害发现主要依靠人工识别，而庞大的桥梁数量和里程基数对桥梁养护工作提出了极大的挑战，若不能及时发现病害并对其程度进行评估进而制定应对策略，很可能造成安全事故及生命财产损失。因此，通过自动化检测提高检测效率和准确度是桥梁病害检测的必由之路。
申请号为CN201810339418.3，名称为“一种无源敲击式材料损伤检测装置及方法”的发明专利提出了一种自平衡检测车，将自平衡车的双轮替换成表面设置激振齿的激振轮，行驶时对材料表面进行敲击，传感器对检测区域的信号进行采集，通过采集检测信号的谱图包络线计算检测表面的损伤指示值，并将损伤指示值突然下降的位置判定为损伤位置，以突变大小衡量损伤的程度。然而，由于非损伤位置的损伤指示值是接近的，因此损伤指示值判定法导致计算量大且复杂，双激励轮的设计也导致由于敲击位置不同使得反馈信号之间容易形成干扰，增加了信号分析难度的同时，也降低了检测结果的准确性。
发明内容
针对上述问题，本发明提供一种无源激振式桥梁探伤装置，利用单一激振轮上均匀分布的激振齿对桥面进行固定激振频率的无源激励，并通过加速度传感器采集桥梁表面传递到激振轮的加速度信号，通过考虑等效刚度对时间的导数项对加速度幅值的影响得到刚度变化边缘，通过在等效刚度对时间的二阶导数项控制的时域内分析刚度突变时刻，再在该时刻附近寻找功率谱图中的拐点以确定桥梁 病害位置并评估病害程度。
一种无源激振式桥梁探伤装置，包括：激励部分、损伤定位和评估部分和配重连接部分，其特征在于，
所述激励部分包括一个表面设置有均匀分布激励齿的激振轮，用于对桥面进行固定激振频率的无源激励，激振轮中心轴承两端固定具有矩形端面的固定件，固定件通过螺栓连接固定于搭板的端槽中，所述轮轴上设置有加速度传感器，用于采集桥梁表面传递到激振齿的加速度信号；
所述损伤定位和评估部分通过从时频分析结果中提取的等效加速度的极大值点确定检测到刚度突变时刻，对应功率谱图中的拐点确定桥梁损伤位置并评估损伤程度；
所述配重连接部分包括方槽构件和搭板，所述方槽构件通过插槽和螺栓连接前车身驱动部分和后车身激励部分；所述搭板焊接固定在方槽构件上，并且包括用于增强扭转刚度的顶部品字连接部分和支撑臂，以及用于增强弯曲刚度的底部方钢连接部分。
进一步的，所述损伤定位和评估部分对加速度信号进行滤波步骤如下:
首先对加速度信号进行时频分析得到n个信号，每个信号对应于一个特定时刻，有对应的频谱向量Yi,i＝1,2,…,n，先对各向量进行求和得到该时刻的总能量Ei，然后再求所有时刻能量的均值和标准差计算i时刻频谱向量的均值与标准差进而得到衡量该时刻频谱的波动情况的变异系数Qi＝σi/μi，以及所有时刻的变异系数的均值和标准差变异系数波动代表损伤导致的刚度突变。
进一步的，所述损伤定位和评估部分的损伤定位步骤如下:
首先，记录根据滤波算法除掉噪声后的位置点向量locs：
locs＝{i|Ei>μE+B×σE||Qi>μQ+B×σQ,i＝1,2,...,n}；
其中，B为噪声干扰度；
然后，计算所述等效加速度得到二维曲线，选取极大值点，将其位置统计到向量locpeak，其中PSDmax为每个时刻中功率谱密度在频域中的最大值，则存在明显的刚度突变的损伤位置为locf＝locs∩locpeak。
进一步的，所述损伤定位和评估部分的对损伤程度的评估通过下式确定：
其中，G和H为事先标定的无量纲系数。
本发明激振轮上均匀分布的激振齿对桥面进行固定激振频率的无源激励，简化了检测结构并避免了激励源之间的干扰，通过加速度峰值突变时间对应功率谱确定刚性突变点，检测方法简单高效，并提高了检测准确率。
附图说明
图1是桥梁探伤车车身的前视图；
图2是桥梁探伤车车身的侧视图；
图3是激励部分和配重连接部分组装示意图；
图4是配重连接部分的示意图；
图5是搭板的示意图；
图6是方槽构件的示意图；
图7是激励部分的示意图；
图8是敲击扫描方法的基本模型示意图；
图9是损伤梁模型示意图；
图10是梁有刚度突变时小车的固有频率分布形式图；
图11是时变ωVd对加速度的影响图，其中，图11(a)的激振频率＝141Hz，图11(b)的激振频率＝131Hz；
图12是截面惯性矩的分布情况图，其中，图12(a)是实际刚度比曲线图，图12(b)是加权刚度比曲线图；
图13是不同窗长情况下θw的分布图，其中，图13(a)的窗长为2m，图13(b)的窗长为1m，图13(c)的窗长为0.5m；
图14(a)是θ＝1/1.07时小车的加速度曲线图，其中，图14(b)是θ＝1/1.07时小车的功率谱密度图；
图15是考虑刚度突变处的极值点时，其中，图15(a)是与θ的分布数据点图，图15是(b)是根据图15(a)中的数据点拟合出的二次曲线图，图15(c)是与θs的分布数据点图，图15(d)是根据图15(c)中的数据点拟合出的二次曲线图；
图16是不同θ下二阶导数影响区域内特征点的转换，其中，图16(a)中θ＝1/1.2，图16(b)中θ＝1/1.07，图16(c)中θ＝1，图16(d)中θ＝1.03，图16(e)中θ＝1.07，图16(f)中θ＝1.2；
图17(a)是实验梁的结构示意图；图17(b)是实验梁的侧视图；
图18是检测车模型的固有频率图谱；
图19(a)是检测车加速度曲线图，图19(b)是对应的功率谱密度图；
图20(a)是检测车等效加速度Ymax分布和检测点，图20(b)是对应的功率谱密度图；
图21是检测车等效加速度的分布情况图；
图22(a)中竖直振动频率≈78Hz，图22(a-1)为监测车后部的侧视模态仿真图，图22(a-2)为监测车后部的仰视模态仿真图；
图22(b)中竖直振动频率≈103Hz，图22(b-1)为监测车后部的侧视模态仿真图，图22(b-2)为监测车后部的仰视模态仿真图；
图22(c)中竖直振动频率≈117Hz，图22(c-1)为监测车后部的前视模态仿真图，图22(c-2)为监测车后部的后视模态仿真图；
图22(d)中竖直振动频率≈254Hz，图22(d-1)为监测车后部的前视模态仿真图，图22(d-2)为监测车后部的后视模态仿真图；
图22(e)中竖直振动频率≈339Hz，图22(e-1)为监测车后部的前视模态仿真图，图22(e-2)为监测车后部的后视模态仿真图；
图23(a)为竖直振动频率≈60Hz时整车的模态仿真图；
图23(b)为竖直振动频率≈69Hz时整车的模态仿真图；
图23(c)为竖直振动频率≈74Hz时整车的模态仿真图；
图23(d)为竖直振动频率≈87Hz时整车的模态仿真图；
图23(e)为竖直振动频率≈101Hz时整车的模态仿真图；
图23(f)为竖直振动频率≈152Hz时整车的模态仿真图；
图24是检测车的工作模式示意图；
附图标记说明：
1-驱动轮、2-悬挂系统、3-车架、4-硬件箱、5-姿态传感器、6-配重连接部分、7-方槽构件、8-搭板、9-激励部分、10-插槽、11-端槽、12-中心轴承、13-激振轮、14-法兰、15-传感器安装位、16-固定件。
具体实施方式
为使本领域的技术人员更好地理解本发明的技术方案，下文将对检测装置的结构和无源激振式桥梁探伤方法的原理进行详细描述。
本发明提供了一种桥梁探伤车车身构造，包括：驱动部分、激励部分和配重连接部分。如图1和2中桥梁探伤车车身示意图所示，驱动部分包括安装于车架3上的两个驱动轮1、两个10寸500W的轮毂电机，悬挂系统2和硬件箱4。悬挂系统2可以包括液压氮气减震器，用于降低驱动轮噪声以减小对激励信号的干扰。车架3顶部设置有用于安装姿态传感器的安装位，姿态传感器用于实现半监督式惯性导航。硬件箱4内可设置电池和控制系统。
如图4所示，配重连接部分6由方槽构件7和搭板8构成。搭板8焊接固定在方槽构件7上。如图2、3和6所示，方槽构件7通过4个插槽10和螺栓连接前车身驱动部分和后车身激励部分。如图5所示，搭板8包括用于增强扭转刚度的顶部品字连接部分和支撑臂，以及用于增强弯曲刚度的底部方钢连接部分，底部方钢连接部分设置有两个端槽11。
如图7所示，激励部分9包括一个表面设置有均匀分布激励齿的激振轮13。激振轮13的轮毂圈内设置法兰14，法兰14的中心轴承12套入圆轴固定，中心轴承12两端固定具有矩形端面的固定件16，固定件16通过螺栓连接固定于搭板8的端槽11中。中心轴承12可以是深沟球轴承。圆轴上设置有传感器安装位15，传感器可以是IEPE加速度计。激振轮13可由75A硬度的橡胶轮胎和铝材轮毂构成。例如，激振轮13的参数如下，半径r为125mm，宽度为50mm，橡胶轮胎的花纹数n为72。激振频率与以上参数的关系为f＝vn/2πr，因此，当检测速度为1.5m/s时，激振频率约为138Hz。
上述桥梁探伤车车身构造安装加速度传感器和探伤信号分析元件后，利用梁上刚度突变点的突变程度近似与小车加速度幅值或功率谱密度的平方根呈二次曲线关系，找到导数项对应的特征点进行病害定位。
桥梁探伤车的快速桥梁刚度异常点检测模式：
本方法的工作模式如图24所示，按照指令传输时序可将各模块从上至下分为用户端、控制方式选择、上位机、下位机以及底层硬件。
针对使用的场景，用户端需分别根据需要选择控制方式。比如：在待检测场地需快速移动设备时，采用近距离遥控的方式直接控制下位机，可实现快速转向或掉头；而在实施检测过程时，采用半监督式惯性导航的方式，即检测车主要由惯性导航的方式以固定速度进行检测，但若途中因伸缩缝导致惯性导航传感器有较大偏差时，用户端可对其进行修正。
上位机的功能包含用户端的指令接收与处理、惯性导航传感器数据和检测数据的采集、检测数据的分析与存储。控制流方面，在接收到用户指令后上位机将检测实施时所需任务发送给下位机进行执行，并接受下位机的反馈，最后将处理的检测结果反馈到用户端进行查看。
下位机的功能主要是完成各项硬件控制的任务，包含驱动电机、转速采集、电量和温度监控，以及避障急停。
考虑非定常效应的梁式结构刚度识别算法原理：图8是敲击扫描方法的基本模型，其中Euler-Bernoulli梁的弯曲刚度为EI，单位长度质量为m，阻尼系数为μB。小车简化为一个质量为MV的刚性车身和质量为MW的车轮的联合体。车身和车轮之间的连接刚度为kV，阻尼系数为μV。车轮和梁的接触刚度为kW，阻尼系数为μW。路面粗糙度用r(x)表示。车轮的激励齿可被看作一层没有厚度的接触界面(即激励齿的位移就是该处梁的位移)，其刚度和阻尼折算到kW和μW中。激励齿的质量MT所产生的惯性力就是被动敲击力FT。而作用在车身的力FV就是主动敲击力。以下推导中，所有位移和力以y方向为正方向；下标V、W、T和B分别代表车身、车轮、激励齿和梁。对此系统可以在梁的局部坐标系(x,y)中x＝vt处建立以下平衡方程(车身以和自重平衡的状态为原点)：



其中：F为梁对车轮的y方向支承力；该式中上加点代表对时间t求导；右上标'代表对x求导。只考虑车轮和梁表面紧密连接这种情况，则上式中yT＝yB，根据(3)式可知：
车轮接触界面有质量为MT的激励齿，则就代表车轮对梁的敲击力FT，(1)～(3)式是被动敲击扫描方法的车桥耦合方程。
若车轮无动力减振现象，则将上述模型进一步简化为单自由度系统，可将方程简化为：


因为小车以速度v匀速运动，而且激振轮的轮齿是均匀分布的，每次敲击过程中的脉冲激励近似为半正弦波，所以可假设F为：
假设梁的表面形貌是在一个光滑表面上叠加一个粗糙扰动组成，则A和εs分别代表在光滑表面和粗糙扰动上产生的敲击力，其大小由轴重和车速决定。εs是由车轮滑动产生的噪声。τ0表示激振力的持续时间，半正弦波的圆频率满足ωF＝π/τ0，T＝2π/ω0则为激振力的周期，当激振轮的半径为r，其上花纹的齿数为n时，敲击圆频率由下式决定：
记激励齿的占空比为η，则：
于是：
若齿轮的齿深相对于路面粗糙度足够大，则A>>εs。进一步忽略滑动的影响，则(9)式可以利用傅里叶级数展开，最终得到：
可见随着n的增加高阶项迅速减小。所以通常敲击力FT，的频率主要是ω0。而且为了避免环境噪声的干扰，ω0会设定在一个比较高的频率，此时高阶频率的敲击力离小车的敏感频率很远。所以以下只讨论n＝1的情况，此时：
特别地，当2η＝1时：
根据(6)～(8)式，可得到激振轮处梁的原点位移阻抗：
于是可知小车的加速度和原点位移阻抗有关，因此包含了局部损伤的信息：
由于桥梁的刚性很大，可以认为在小车的敲击作用下桥梁的变形很小，振动响应是线性的。所以，桥梁位移可以表示为：
其中：φj(x)＝sin(jπx/L)是桥梁的第j阶模态；qBj(t)是模态坐标。
将(16)式代入(6)～(8)式，然后在等式两边同乘以φj(x)后再沿梁的长度积分可得：
其中，ωBj是桥梁的第j阶自然圆频率：
在小车低速运动的前提下，容易满足于是可以忽略(17)式中的另外，FT>>MTg，可忽略MTg，所以可得到解耦的方程。将(13c)式代入该方程，并运用Duhamel积分可得强迫振动解(注：因为轻微的局部损伤不会使ωBj发生很大的改变，所以认为下式中的ωBj是常数；另外，认为梁的初位移和初速度为零)：
其中：
将(16)式代入(6)式，得到：
其中：2nV＝μV/MV；k与梁上的位置有关，因此等效固有频率为时间的函数：
可见，(22)式是一个变系数的二阶线性常微分方程。为了推导解析解，此力 学模型将实际的损伤梁+无损小车等效为无损梁+损伤小车，即认为k与小车的悬挂刚度kV和接触点梁的损伤情况有关，因此(22)式中的等效固有频率为时间的函数。
假设带损伤的梁刚度分布如图9所示，则根据刚度等效模型可知：


其中：θ＝(EI)2/(EI)1，α＝a/L，β＝b/L以及γ＝c/L。D随位置变化，在损伤区外是γ的二次多项式，在损伤区内是γ的四次多项式，并在损伤区中心取极值。
根据以上分析，可以认为(22)式中的ωV是分段函数。此时可以用分段Duhamel积分来求解小车的强迫振动位移。假设从x＝a处开始出现损伤：
当0≤vt<a时，梁无损伤，小车的初位移和初速度都为零：

当a≤vt时，梁有损伤，小车的初位移和初速度分别为yV(a/v)和

下面根据(27)式和(29)式定性分析刚度变化对加速度的影响。
取梁参数为E＝27.5GPa，I＝0.12m4，m＝4800kg/m，L＝25m，仅考虑前十阶次模态，其前两阶频率分别为2.084Hz、8.336Hz，取该两阶模态阻尼比为0.03时对应的Rayleigh阻尼系数α＝0.6285，β＝0.0009165。令单自由度模型中小车参数为k＝5.5×107N/m，MV＝75kg，因此小车固有频率为fV＝136.29Hz；令小车车轮半径为0.125m，阻尼比μV＝0.01；激振力参数设为激振频率f0＝141Hz，敲击力的占空比η＝0.5，幅值为A＝2Mg。
考虑刚度突变的情况，若在突变刚度位置处小车固有频率的分布形式为β函数：
取p＝0.99995，x＝[0,5×10-4]的曲线形式描述小车频率的变化趋势，但仍根据(23)式计算梁刚度变化引起的固有频率大小的改变。若记ked＝kd|max(abs(kd/k-1))，则在已知损伤段参数的情况下，可计算出ked，并根据对称性可令固有频率及其对时间的导数分布为(见图10)：
当刚度变化段长度为0.5m，位置参数为α＝0.5，引起的小车刚度变化最大值为ked＝1.01k，小车的刚度分布如上，其余参数不变，激振频率分别为141Hz和131Hz时，ωV及其各阶导数对加速度的影响如图11所示。其中d2ωV/dt2对幅值的影响最大，但影响范围最小(如图11中箭头位置)，ωV对幅值影响较小但影响范围最大。而影响范围主要由图10中各个量具有较大突变值在时域上的宽度决定，即该影响只存在于刚度变化段的长度范围内，因此可通过分析小车加速度幅值的变化定位发生刚度变化的位置。
因为N<<1，且ND<<1，所以(23)～(25)式可知：ωVd≈ωV(1-ND/2)、于是可知(27)式和(29)式中N最高次项为二次，并结合N＝θ-1，可得到小车加速度近似与梁刚度变化系数的关系：
在实际检测中，低频段的噪声对时域信号的干扰较大，因此通常利用STFT处理方法分析较高敏感频段的信号。根据量纲分析可记等效加速度其中PSDmax为每个时刻中功率谱密度在频域中的最大值，则Ymax与STFT分析时使用的窗函数有关，因此对(32)式中的变量θ也需要根据实际分析加对应的窗，此时与Ymax一一对应的为窗函数宽度内的加权刚度值。若梁的弯曲刚度分布如图12(a)，并记5m处的弯曲刚度为参考值(EI)ref，取1m的汉明窗时，加权刚度变化如图12(b)。由于无法对实际的梁给定参考值，因此后文中均以前一个单元的加权刚度作为基准值(EI)w1，当前单元的加权刚度为(EI)w2，并令θw＝(EI)w2/(EI)w1，则不同窗长情况下θw的分布如图13，θw的拐点近似为该损伤区最敏感的点。当加权刚度具有对称性时，加权刚度比值θw具有反对称性，因此对于如图12(a)中6m 处的突变刚度，在图中会出现两个反对称的拐点。窗长会改变这类拐点的位置，主要影响滑动窗逐渐离开刚度突变点阶段时产生的拐点的位置，如图13中6.75m，6.375m，6.25m处的拐点。对于突变刚度，取窗长的影响较小的刚进入突变点时产生拐点位置的值记为θs(5.75m，5.875m，5.937m处的拐点)，也即第一个拐点作为衡量该处刚度突变的指标，而对于如图12(a)中约8.5m处的渐变刚度，也取受窗长影响小的拐点的值(第一个拐点)作为衡量指标。
基于上述对θs的取法，可以得到刚度变化拐点处突变程度的描述，可进一步分析不同突变程度对加速度幅值以及功率谱密度的影响。
对于图9中仅存在一个损伤段的情况，取刚度变化的位置为跨中即α＝0.5，刚度变化的宽度为0.5m，激振力参数为fi＝136Hz，其余参数同上。
对于时域幅值，不加窗时θs相当于θ。当θ＝1/1.07时，小车的加速度如图14所示。若考虑导数项对加速度幅值的影响(刚度变化边缘，如图14所示数据点)，可分析刚度突变边缘附近的峰值点(二阶导数项控制的区域，可根据图10确定)，而对于功率谱图，由于突变信号的宽度较小，在加窗之后被平滑，很难直接判断，因此首先确定时域信号的特征点的时刻，再在该时刻附近寻找功率谱图中的拐点。
对于二阶导数影响区域内的特征点，加速度幅值与θ、等效加速度Ymax与θs的变化关系如图15所示，其中实线是基于θ＝1附近的数据点得到的二次函数关系拟合的曲线，相关系数R2＝0.9438。当θ>1时，损伤段刚度增加，影响区域内二阶导数变号，此时特征点的幅值与θ之间的非单调关系也即近似二次曲线的拐点在右半平面。这是由于包含二阶导数的项对不同时刻的加速度的幅值影响方向不同，导致了特征点的转换。如图16，根据图10可知二阶导数项在8.425s后起作用，当θ逐渐增大时，8.431s的峰值点的加速度逐渐减小，而对于8.428s时刻，加速度逐渐增大，因此二阶导数项影响区域内的波峰波谷会存在交换。而交换的过程中存在峰值小于θ＝1情况的峰值的点，因此二次曲线并不关于θ＝1对称。对于图15可发现数据点的对称性较弱，但对于θs∈[0.99,1.06]范围内仍具有二次曲线关系，相关系数R2＝0.7668。
基于以上原理，可见梁上刚度突变点的突变程度近似与小车加速度幅值或功率谱密度的平方根呈二次曲线关系，关键在于找到导数项对应的特征点。对于实际的桥梁，加速度易受到低频噪声的影响，因此可采用功率谱密度进行分析，而为区分不同程度的刚度突变，提出如下算法进行划分：
1)利用短时傅里叶变换STFT得到n个信号，采用窗长为1m的汉明窗，相邻窗的数据重叠率为0.875；
2)取敏感频段(敏感频率附近的K个点，通常为±5Hz)的向量Yi,i＝1,2,…,n.，对各向量进行求和，得到该时刻的总能量Ei，及所有时刻的均值和标准差并计算该时刻向量的均值与标准差进而得到变异系数Qi＝σi/μi以及所有时刻变异系数的均值和标准差变异系数用于衡量该点频谱的波动情况，若波动较大则可能出现刚度突变；
3)记录根据滤波算法除掉噪声后的位置点向量locs：
locs＝{i|Ei>μE+B×σE||Qi>μQ+B×σQ,i＝1,2,...,n}      (33)
4)计算等效加速度得到二维曲线，选取极大值点，将其位置统计到向量locpeak；
则存在较明显的刚度突变的位置为locf＝locs∩locpeak
5)对于θ在1附近的情况，若用无量纲表达等效加速度，并结合(32)式，则
其中无量纲系数G和H由试验梁标定，所以对于刚度突变位置，其突变程度可用下式确定：
实施例
试验试件为一根两端简支的12.16m长T梁。如图17所示，该梁有一块中隔板，其两侧结构是对称的，在一段2.55m长的等厚度腹板之后紧接着一段2.15m长的变厚度腹板，最后是一段0.85m长的等厚度腹板和端隔板相连。假设梁上各处的混凝土弹性模量都是E＝43.698GPa，则图12就显示了试验梁横截面等效弯曲刚度的分布。
如图3，检测车后部重75kg，为单后轮结构，包括激振轮、圆轴和配重等，激振轮齿数为72，由橡胶和铝合金组成，圆轴和配重均为不锈钢材质。加速度采集点在圆轴上，离后轴中点20mm。检测车的固有频率约138Hz。
试验时，检测车自西向东以约1.5m/s的速度在试验梁上行驶，产生的激振力的频率为138Hz。一共记录了20次有效数据。其中第一次的车轴加速度信号以及功率谱密度如图19所示，可见小车的加速度平均值在0.5g左右。
图19(a)中标记点为小车经过伸缩缝的时刻，右侧则为伸缩缝距离小车起始点的位置，两坐标之差约为12.1m，与梁的长度符合，因此可基于第一条伸缩缝定位小车在桥梁的位置，后续结果的横坐标均已第一条伸缩缝为基准。根据上文原理部分描述的算法，令B取为1，可得到如图20(a)的处理结果，其中线条为Ymax，圈点为滤波后得到的刚度突变的异常点，该结果可与图12(b)中的标记点进行对照，各位置点的统计值如表1所示，可看出本发明采用的检测设备和方法能够以90％的成功率找到试验梁在位置1、2、3、5对应的刚度突变点，以60％的成功率找到位置4对应的刚度突变点。
表1激振频率为138Hz时的检测结果
如图21为表1中各位置处以刚度突变程度θs为横坐标的等效加速度的分布情况，其中数据点为五个位置对应的等效加速度的均值和标准差。该分布形式与图15的分布情况相似，在θs＝1附近处数据点(位置1、3、4、5)较集中，Ymax呈现近似单调下降的趋势，但当θs较大(位置2，θs＝1.068)时Ymax相对较大， 因此总体可用二次函数描述Ymax与θs的关系。
如图22为对特定几何参数下后轴的模态分析，其边界条件为：激振轮与地面接触部分为固定约束，方槽前端面约束了水平方向的运动。其中，图22(c)中的模态主要振动元件是轮轴和激振轮，且为竖直振动模态，频率为117Hz，满足检测方法的要求。图22(a)，(b)(d)中的模态为激振轮绕其固定点的旋转振动，这种类型的模态主要与激振轮的剪切刚度以及激振轮和地面的接触条件有关，由于激振轮的转动使接触条件不断改变，这类模态并不稳定；另外，这类情况下，信号测量点的振动方向主要为水平方向，对竖直方向的干扰较小。图22(e)中的模态为整体结构弯曲和扭转耦合的模态，其频率为339Hz，远远高于图22(c)模态的频率，当工作频率在频率140Hz附近时，该模态不会对信号产生干扰。
如图23为包含前车身的模态分析，约束条件为各车轮与地面的接触部分，为固定约束。其中图23(e)中模态为满足检测要求的竖直振动模态，与其相近的图23(d)中模态为激振轮的旋转模态，如前文所述对检测的干扰减小。图23(f)中模态的频率为152Hz，与图23(e)中模态的频率相差51Hz，当激振频率在图23(e)中模态的频率附近时，该模态不会被激发，因此不会对检测信号产生干扰。
上面结合实施例对本发明的实例作了详细说明，但是本发明并不限于上述实例，在本领域普通技术人员所具备的知识范围内，还可以在不脱离本发明宗旨的前提下作出的各种变化，也应视为本发明的保护范围。

Claims (4)

  1. 一种无源激振式桥梁探伤装置，包括：激励部分、损伤定位和评估部分和配重连接部分，其特征在于，
    所述激励部分包括一个表面设置有均匀分布激励齿的激振轮，用于对桥面进行固定激振频率的无源激励，激振轮中心轴承两端固定具有矩形端面的固定件，固定件通过螺栓连接固定于搭板的端槽中，所述轮轴上设置有加速度传感器，用于采集桥梁表面传递到激振齿的加速度信号；
    所述损伤定位和评估部分通过从时频分析结果中提取的等效加速度的极大值点确定检测到刚度突变时刻，对应功率谱图中的拐点确定桥梁损伤位置并评估损伤程度；
    所述配重连接部分包括方槽构件和搭板，所述方槽构件通过插槽和螺栓连接前车身驱动部分和后车身激励部分；所述搭板焊接固定在方槽构件上，并且包括用于增强扭转刚度的顶部品字连接部分和支撑臂，以及用于增强弯曲刚度的底部方钢连接部分。
  2. 根据权利要求1所述的无源激振式桥梁探伤装置，其特征在于，所述损伤定位和评估部分对加速度信号进行滤波步骤如下:
    首先对加速度信号进行时频分析得到n个信号，每个信号对应于一个特定时刻，有对应的频谱向量Yi,i＝1,2,…,n，先对各向量进行求和得到该时刻的总能量Ei，然后再求所有时刻能量的均值和标准差 计算i时刻频谱向量的均值与标准差进而得到衡量该时刻频谱的波动情况的变异系数Qi＝σi/μi，以及所有时刻的变异系数的均值和标准差变异系数波动代表损伤导致的刚度突变。
  3. 根据权利要求2所述的无源激振式桥梁探伤装置，其特征在于，所述损伤定位和评估部分的损伤定位步骤如下:
    首先，记录根据滤波结果除掉噪声后的位置点向量locs：
    locs＝{i|Ei＞μE+B×σE||Qi＞μQ+B×σQ,i＝1,2,...,n}；
    其中，B为噪声干扰度；
    然后计算时频图上等效加速度随时间变化的曲线，选取极大值点并且将其位置统计到向量locpeak，其中PSDmax为每个时刻中功率谱密度在频域中的最大值，则存在明显的刚度突变的损伤位置为locf＝locs∩locpeak。
  4. 根据权利要求3所述的无源激振式桥梁探伤装置，其特征在于，所述损伤定位和评估部分的对损伤程度的评估通过下式确定：
    其中，G和H为事先标定的无量纲系数。
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CN117949129B (zh) * 2024-03-27 2024-06-04 深圳市城市公共安全技术研究院有限公司 群柱轴力检测方法、装置、设备及存储介质

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