CN111896629A - Rapid detection method for tunnel structure surface layer diseases - Google Patents
Rapid detection method for tunnel structure surface layer diseases Download PDFInfo
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Abstract
The invention relates to a method for rapidly detecting surface diseases of a tunnel structure, which comprises the following steps: 1) detecting the potential peeling and stripping of the tunnel lining caused by material aging and reinforcing steel bar rust expansion by comprehensively using a sound vibration method, an infrared detection technology, a three-dimensional laser scanning technology and the like, and judging the potential peeling and stripping possibility; 2) and integrating the acquired tunnel lining surface layer disease information including potential stripping possibility, stripping amount and steel bar rust expansion positions in a data acquisition and processing system, and drawing a spatial information distribution map of the tunnel lining surface layer disease corresponding to the milepost number. Compared with the prior art, the method has the advantages of conveniently and effectively detecting the surface diseases of the tunnel structure and the like.
Description
Technical Field
The invention relates to a method for rapidly detecting surface diseases of a tunnel structure.
Background
At present, most highway tunnels in China are in a maintenance stage, and meanwhile, most newly built tunnels start to be transited from a construction period to an operation management period. Under the influence of a plurality of factors such as engineering geological conditions, construction quality control, supervision and maintenance and the like, the tunnel structure is exposed to the problem of diseases with different degrees after being used for a long time or even a short time. The tunnel diseases have a certain evolution process, part of the appearance diseases such as cracking of the lining, water leakage, concrete block falling and the like are generated from the further evolution of the lining surface diseases, the surface layer diseases mainly occur in the range that the intrados of the tunnel structure extends to the inside by 5-10 cm, and the tunnel lining potential peeling and stripping caused by concrete material aging and reinforcement rust swelling are included. When the surface layer diseases develop to a certain degree, the surface layer diseases can evolve into apparent diseases, and the generation and development of other diseases can be aggravated, so that the performance of the tunnel structure is continuously deteriorated, the safety of the structure is threatened, and safety accidents are caused. Therefore, if the surface layer diseases can be effectively detected and targeted treatment measures can be taken, not only the potential safety hazards can be effectively eliminated, but also the generation of a series of induced diseases can be slowed down and prevented. Therefore, the method has important research significance on effectively monitoring and reasonably evaluating the surface layer diseases of the tunnel structure.
The detection of the surface layer diseases of the tunnel structure mainly aims at the potential peeling and stripping of the lining caused by material aging and reinforcing steel bar rust expansion. On one hand, the potential peeling of the tunnel surface layer is peeling caused by material aging, so that qualitative and quantitative detection of crack defects of the tunnel surface layer is required. In the detection technology for the defects inside the tunnel, the currently common detection methods are a tapping method, a geological radar method, a sound wave detection method, an infrared thermal imaging technology and the like. The knocking method mainly depends on manual detection, and is low in efficiency, time-consuming and labor-consuming; the geological radar method and the acoustic vibration method are nondestructive detection methods, the geological thunder method utilizes electromagnetic waves with strong penetrability to detect lining quality, back cavities, the quantity and distribution conditions of reinforcing steel bars and the like, and is mainly suitable for detecting diseases in deeper parts inside the lining, and the detection precision of the diseases on the surface of the lining is low; the acoustic wave detection method is more suitable for detecting surface layer or shallow layer defects, but at present, a contact type sensor is mainly used for detection, and the existing method and device can only carry out qualitative analysis on defects and defects, and do not have effective quantitative evaluation on defect size, defect range and the like. In the detection technology for the reinforcement rust expansion in the reinforced concrete structure, a commonly used method comprises an analytical method, an electrochemical method, a resistance probe method, an ray method and the like, but the method is not suitable for a tunnel structure with a complex internal environment, and the position and the degree of the reinforcement rust expansion are not quickly and accurately determined. In conclusion, how to adopt a targeted and effective comprehensive detection method for the potential peeling and peeling of the tunnel lining caused by material aging and reinforcing steel bar rust is a technical problem which needs to be solved at present.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide a method and a device for rapidly detecting the surface defects of the tunnel structure.
The purpose of the invention can be realized by the following technical scheme:
a method for rapidly detecting surface diseases of a tunnel structure comprises the following steps:
firstly, constructing a rapid detection device for the surface diseases of the tunnel structure;
the system comprises a vehicle-mounted walking device, a detection device and an information acquisition and processing system, and the vehicle-mounted walking device is used for loading the detection device and the information acquisition and processing system and conveying the detection device and the information acquisition and processing system to each detection point of a tunnel.
Step two, implementing a detection process:
step 1
The method comprises the steps of detecting two recessive diseases of potential peeling and stripping of the tunnel lining and reinforcing steel bar rust expansion by respectively using a sound vibration method and an infrared detection technology, and simultaneously storing recessive disease information and milepost numbers in an information acquisition system.
Step 2
The acquired tunnel lining surface layer disease information comprises tunnel lining potential stripping caused by material aging and reinforcing steel bar corrosion and expansion, the information is integrated in a data acquisition and processing system, a spatial information distribution diagram of the tunnel lining surface layer disease corresponding to the milepost number is drawn, and the potential stripping possibility, range, size and depth and reinforcing steel bar corrosion and expansion position and range are marked in the diagram, so that comprehensive and rapid detection of the tunnel lining surface layer disease is realized, and a visual graph which visually reflects the disease information is obtained.
The step 1 specifically includes:
step 1-1
And detecting the hidden defects on the surface of the tunnel lining by adopting a sound vibration method, and determining the stripping range, stripping amount, stripping depth and stripping layer volume of the hidden defects on the surface of the tunnel lining.
Step 1-1
The method comprises the following steps of (1) regarding cracks and void layers in a shallow tunnel lining layer as surface hidden defects, simplifying a potential spalling and stripping concrete structure induced by the cracks and the void layers into a thin plate structure, defining a cylinder with the diameter D and the thickness h as a thin plate unit, defining an air layer between the thin plate and the whole tunnel structure as the surface hidden defects, defining the air layer as a defect unit, and assuming that the range of the defects is consistent with that of the thin plate, namely the radius is R and the thickness is D; determining the resonant frequency f corresponding to different sheet sizes by formula 1i(i ═ 1, 2, … …, n, n are sheet size categories);
equation 1:
in formula 1: f. ofiThe theoretical resonant frequency of the thin plate unit under different sizes is h, the thickness of the thin plate unit, D, the diameter of the thin plate unit, E, the elastic modulus of concrete at the thin plate unit, rho, the density of concrete at the thin plate unit and v, the Poisson ratio of concrete at the thin plate unit.
Step 1-1-2, comprising:
step 1-1-2-1
Adding or subtracting the theoretical resonant frequency within a certain range, wherein the range is the input range of the frequency sweep signal of the subsequent signal transmitter and is expressed as Uik＝[fik-x，fik+x]；
Step 1-1-2
Establishing a relation curve of the vibration speed and different sweep frequency signals, and respectively recording the relation curve as Fik1(fika，vik1)、Fik2(fikb，vik2) And Fik3(fikc，vik3)；
Steps 1-1-2-3
Vibration velocity-sweep signal relationship F at the center point (i.e., 1 st point) of the sheetik1(fika，vik1) Finding out the maximum vibration velocity vik1mAnd corresponding sweep frequency signal fikamThe frequency sweep signal famSequentially substituting the vibration speed-sweep frequency signal relation curves F of the 2 nd and the 3 rd pointsik2(fikb，vik2) And Fik3(fikc，vik3) To obtain a corresponding frequency sweep signal fikbm-1、fikcm-1And a vibration velocity vik2m-1、vik3m-1。
Step 1-1-3 binding body surface vibration velocity
Step 1-1-3-1
Repeating the steps 1-1-2-1 to 1-1-2-3 to obtain the effective input of what range sweep frequency signal, the vibration speed which must be depended on under a specific size and the contour size under the vibration speed.
Step 1-1-3-2
Under the condition that the thickness h of the thin plate and the thickness D of the defect are constant, establishing a functional relation G between the diameter D of the thin plate and the vibration speed of the 1 st point1(D，vik1m-1) Simultaneously, taking and collecting the sweep frequency signals corresponding to all the 1 st point vibration speeds respectively and recording as W1(ii) a Establishing a functional relation G between the thickness h of the thin plate and the vibration speed of the 1 st point under the condition that the diameter D of the thin plate and the size D of the defect are constant2(h，vik1m-1) Simultaneously, taking and collecting the sweep frequency signals corresponding to all the 1 st point vibration speeds respectively and recording as W2(ii) a Under the condition of certain sheet diameter D and sheet thickness h, establishing a functional relation G between the defect thickness D and the 1 st point vibration speed3(d，vik1m-1) Simultaneously, taking and collecting the sweep frequency signals corresponding to all the 1 st point vibration speeds respectively and recording as W3；
Steps 1-1-3
Collecting the sweep frequency signals W in the steps 1-1-3-21、W2And W3Taking a union set, and extracting the maximum value f of the obtained sweep frequency signal setmaxAnd minimum value fminThe sweep frequency signal range of the maximum value and the minimum value envelope is recorded as M ═ fmin，fmax]；
Steps 1-1-4 (on-site)
Inputting the sweep frequency signal range M determined in the steps 1-1-3-3 into a signal transmitter, amplifying the signal by a power amplifier, transmitting sound waves to the surface of the tunnel lining by a long-distance sound wave transmitter, performing point separation scanning on the surface of the tunnel lining by adopting a two-dimensional scanning Doppler laser vibrometer, collecting vibration speeds of all points, drawing a vibration speed and heat distribution diagram of the scanning points in the region in a data analysis system, extracting the vibration speed of characteristic points in the diagram, and substituting the distribution into the functional relationship G of the diameter D of the thin plate, the thickness h of the thin plate and the thickness D of the defect in the step 2-1-3-21(D，vik1m-1，vik2m-1) And G2(h，vik1m-1，vik2m-1) And (3) determining the diameter D of the thin plate, the thickness h of the thin plate and the thickness D of the defect, and correspondingly substituting the parameters into the formulas (2) to (5) to basically determine the peeling range, the peeling amount, the peeling depth and the peeling layer volume of the hidden defect on the surface of the tunnel lining.
Equation (2), peel range a:
formula (3), peeling amount V1：
Equation (4), void depth H (the vertical distance of the geometric center of the air space from the tunnel lining surface):
formula (5), void layer volume V2：
Equation (6), void layer perimeter C: c ═ pi D
Namely the stripping amount, the stripping depth and the perimeter of a stripping layer of the potential stripping defects of the surface layer of the tunnel lining.
Steps 1-1 to 5
Detecting the crack characteristics of the spalled and stripped part by using a high-definition camera according to the potential spalled and stripped part of the surface layer of the tunnel lining detected in the step 1-1-4, and analyzing to obtain the total crack length C of the spalled and stripped part on the surface of the lining1。
Steps 1-1 to 6
Based on the crack characteristics and the perimeter of the stripping layer of the potential stripping part of the surface layer of the tunnel lining detected in the steps 1-1-4 and 1-1-5, the ratio C of the total length of the cracks on the surface layer of the tunnel lining to the perimeter of the gap of the surface layer is obtained by taking the ratio of the crack characteristics and the perimeter of the stripping layer as a ratio2The concrete formula is as follows:
equation (7), the ratio of the total length of the tunnel lining face cracks to the perimeter of the skin voids C2:
according to the ratio C of the total length of the surface cracks of the tunnel lining to the perimeter of the surface gaps2The peeling possibility of the part is judged by the following specific judging method:
(1) when the ratio of the total length of the surface cracks of the tunnel lining to the perimeter of the surface gap is C2 to 2/3, stripping of the detected part is about to occur, and immediately taking corrective measures;
(2) when the ratio of the total length of the surface cracks of the tunnel lining to the perimeter of the surface void is not less than 1/3 and C2 is less than 2/3, the detected part is likely to be stripped and corrective measures should be taken in time;
(3) when the ratio C2 of the total length of the surface cracks of the tunnel lining to the perimeter of the surface void is less than 1/3, the detected part may be peeled off in the future, long-term tracking detection should be performed on the part, and corrective measures should be taken in time if the part develops.
Step 1-2
The potential reinforcement bar rusty expansion position and the steel degree of the tunnel lining are detected by using an infrared detection technology, and the width and the length of a rusty expansion crack are measured by using a shooting method.
Step 1-2-1
Establishing the steel bar rusty degree S and the rusty part average temperature TavgThe relationship of (1).
Step 1-2-1
Acquiring temperature distribution characteristic T + delta T displayed by the steel bar rusty scale part in each infrared thermographiPresetting a temperature threshold value range U for judging the steel bar rust disease partT＝[T+ΔTmin，T+ΔTmax]；
Step 1-2-1-2
Based on the acquired temperature distribution characteristics T + delta T of the steel bar rusty parts of the test piecesiCalculating the average temperature T of the partavg＝(T+ΔTi) /2, thereby establishing the degree of reinforcement bar corrosion and the average temperature T of the portionavgThe fitting formula is shown as formula (6), and the steel bar rust expansion degree S is: a is1+A2Tavg+A3Tavg 2In formula (6): a. the1、A2And A3Are constants obtained by fitting based on experimental data.
Step 1-2-1-3
According to the set temperature threshold value range UT＝[T+ΔTmin，T+ΔTmax]Potential reinforcement bar rusty expansion positions and the average temperature of the positions are extracted from the infrared thermograph of the actual tunnel lining surface, and the reinforcement bar rusty expansion degree S is preliminarily determined based on the established first relation curve.
Step 1-2
Inspection by means of three-dimensional laser scannersDeformation determination interval U for measuring generation of critical rusty expansion cracks between adjacent rusty expansion reinforcing steel barsAnd defining a preliminary criterion of potential stripping possibility caused by reinforcement bar rust expansion.
The preliminary criterion of the potential stripping possibility caused by the reinforcement corrosion expansion is as follows:
(1) incremental deformation of lining surface at rusted rebar
And max1，2There is no potential for peel-off peeling;
(2) the deformation increment of the lining surface at the rusted steel bar belongs to UGreat or > max1，2There is a potential for peel-off peeling; steps 1-2-3
Based on the preliminary determination of the potential peeling and stripping caused by the steel bars in the step 1-2-2, if the possibility of peeling and stripping exists, the development trend of the potential peeling and stripping is further determined by taking the crack characteristics of the tunnel lining surface of the rusty part by means of a high-definition camera, wherein the crack characteristics comprise a down-web crack and a longitudinal crack, and the total length D of the down-web crack is recorded at the same time1And total longitudinal crack length D2。
The development trend criterion of the potential peeling and stripping caused by the reinforcement bar rust expansion is specifically as follows:
(1) when the total length of the downweb crack is less than 1/3 which is the sum of the lengths of the downweb and longitudinal cracks, D1＜(D1+D2) The detected part is likely to peel off in the future, long-term tracking detection is carried out on the part, and corrective measures are taken in time if the part is developed;
(2) when the total length of the longitudinal slit is between 1/3 and 2/3 of the sum of the longitudinal slit length and the longitudinal slit length, that is (D)1+D2)/3≤D1＜2(D1+D2) The detected part is likely to be stripped, and a treatment measure is taken in time;
(3) d when the total length of the downweb cracks is greater than or equal to 2/3 which is the sum of the lengths of the downweb cracks and the longitudinal cracks1≥2(D1+D2) /3, peeling of the site to be detected should occurImmediately taking remedial measures;
steps 1-2-4
In the field test, the tunnel lining surface to be tested is heated to the temperature upper limit threshold value T + delta T by using a high-power infrared pulse thermal excitation sourcemaxAcquiring an original infrared thermography reflecting the temperature distribution condition of the surface of the lining, enhancing the original infrared thermography to obtain an infrared thermography highlighting the temperature distribution characteristics, and based on the temperature threshold value range U in the step 1-2-1-1TJudging the potential reinforcement bar rust expansion position, and determining the reinforcement bar rust expansion degree S according to the first curve relation in the step 1-2-1-3Measuring。
After the steel bar rusty expansion part is preliminarily determined, detecting the deformation of the lining surface of the rusty expansion steel bar part by means of a three-dimensional laser scanner, and preliminarily determining the possibility of potential peeling and stripping caused by steel bar rusty expansion based on the deformation determination interval U when the adjacent rusty expansion steel bars in the step 1-2-2 generate critical rusty expansion cracks. If the possibility of potential peeling and peeling caused by steel bar rust expansion exists, determining the development trend of peeling and peeling based on the development trend criterion of potential peeling and peeling caused by steel bar rust expansion in the steps 1-2-3 by adopting a shooting method.
Compared with the prior art, the invention has the following beneficial effects:
1) the rapid judgment and quantitative detection of the potential stripping of the tunnel lining caused by material aging and reinforcement rust expansion are realized through the vehicle-mounted device platform, and compared with manual detection or other detection means, the efficiency and the precision of detecting surface layer diseases are improved;
2) the rust expansion positioning, rust expansion degree and potential peeling defect positioning and degree of the reinforcing steel bar in the structure are quantitatively determined by comprehensively using a sound vibration method, an infrared detection technology, a shooting method, a three-dimensional laser scanning and a mobile positioning technology, the detection precision is high, the automation degree is high, the detection is comprehensive, and the detection result is visual;
3) a tunnel disease spatial information distribution map is established based on the tunnel structure surface layer disease information, the types, the number and the like of the diseases can be visually and accurately acquired, and the operation, maintenance and maintenance of the structure at the later stage are facilitated.
Drawings
FIG. 1 is a flow chart of the method of the present application
FIG. 2 embodiment tunnel structure surface layer disease's quick detection device
FIG. 3 is a topological diagram of a technical structure of a detecting device according to an embodiment of the present invention
FIG. 4 is a schematic flow chart of a method for detecting potential peeling and void defects of a tunnel lining by using a sound vibration method
FIG. 5 shows a model of a thin slab with hidden defects on the surface of a tunnel lining and a defective unit
FIG. 6 is a schematic diagram of detecting hidden defects on the surface of a tunnel lining by using a sound vibration method according to an embodiment of the invention
FIG. 7 is a graph of the relationship between the vibration speed of the scanning point and the frequency of the sweep signal
FIG. 8 is a graph of the relationship between the sheet diameter (sheet thickness or defect thickness) and the vibration speed in the example
FIG. 9 is a schematic diagram of a two-dimensional scanning Doppler laser vibrometer according to an embodiment
FIG. 10 is a graph showing the heat distribution of the acoustic wave vibration velocity of a hidden defect region on the surface of a tunnel lining in an embodiment
FIG. 11 is a flowchart illustrating an infrared detection of potential reinforcement rust on the surface of a tunnel lining
FIG. 12 illustrates a schematic diagram of an infrared detection of rusted steel bars
FIG. 13 is a sectional view of a reinforced concrete sample in which the reinforcing bars have been rusted
FIG. 14 is a graph showing the relationship between the average temperature of the tunnel surface measurement points and the degree of reinforcement bar corrosion
FIG. 15 is a diagram illustrating a distribution of spatial information of a tunnel lining surface defect according to an embodiment
FIG. 16 is a schematic diagram showing the influence range of the steel bar rust expansion of the reinforced concrete test block on the deformation of the test block
FIG. 17 schematic diagram of crack characteristic analysis of steel bar rusty area
In the figure: 33 is a vehicle-mounted device, 34 is an information acquisition and processing system, 35 is power supply equipment, 36 is a synchronous control machine, 38 is lighting equipment, 39 is a sound vibration method detection device, 40 is an infrared detection device, 41 is a high-definition camera, and 42 is a three-dimensional laser scanner;
in fig. 9: 16 is a y-axis rotating guide wheel, 17 is an x-axis rotating guide wheel, 18 is an acoustic wave emitter rotating guide wheel, 19 is a shallow disease area, and 20 is a tunnel lining surface;
in fig. 12: 24 is an infrared signal generator, 25 is an infrared pulse excitation source, 26 is an optical lens, 27 is infrared rays, 28 is a steel bar, 29 is a heating area, 30 is an object to be detected, 31 is a thermal infrared imager, and 32 is a data acquisition and analysis system;
in fig. 13: 21 is a steel bar corrosion area, 22 is a steel bar original section, and 23 is concrete; (in the figure D)SteelThe diameter of the steel bar without rusty expansion, and the diameter increment of the steel bar with rusty expansion);
in fig. 15: 43, 44, and 45, wherein the information is the tunnel, the information is the potential stripping characteristic information caused by the reinforcement bar rust swelling, and the information is the potential stripping characteristic information caused by the material aging;
in fig. 16: 21 is a steel bar corrosion area, 22 is a steel bar original section, 46 is a rust expansion crack, and 47 is a steel bar rust expansion deformation influence area;
in fig. 17: 48 are longitudinal cracks and 49 are down-web cracks
Detailed Description
The invention is described in detail below with reference to the figures and specific embodiments. The present embodiment is implemented on the premise of the technical solution of the present invention, and a detailed implementation manner and a specific operation process are given, but the scope of the present invention is not limited to the following embodiments.
The embodiment provides a method for rapidly detecting a surface layer disease of a tunnel structure, and a specific flow is shown in fig. 1, and the method includes:
step one, constructing a rapid detection device for the surface layer diseases of the tunnel structure as shown in fig. 2, and constructing a technical structure topological diagram of the detection device as shown in fig. 3, specifically comprising:
and the vehicle-mounted walking device is used for loading the detection equipment and the information acquisition and processing system and conveying the detection equipment and the information acquisition and processing system to each detection point of the tunnel.
Check out test set and information acquisition and processing system and, lay on-vehicle running gear for data acquisition and processing are connected with these check out test set of sound vibration method detection device, infrared detection device, lighting apparatus, synchronous controller, laser encoder and power supply unit, wherein:
the sound vibration method detection device is arranged on the vehicle-mounted walking device, is connected with the synchronous controller and the information acquisition and processing system, and is used for detecting the potential peeling and peeling of the surface layer of the tunnel, the related components comprise a signal generator, a power amplifier, a sound wave transmitter and a two-dimensional scanning Doppler laser vibrometer, and the functional relationship between the signal generator, the power amplifier, the sound wave transmitter and the two-dimensional scanning Doppler laser vibrometer is as follows:
under the cooperative control of the synchronous controller,
the sound wave signal generator is used for emitting a pulse electric signal, and the power amplifier is used for amplifying the pulse electric signal to drive the sound wave emitter; and at the same time
The sound wave transmitter is used for transmitting sound waves to the surface of the tunnel, and the two-dimensional scanning type Doule laser vibration meter is used for measuring the vibration speed of the surface of the tunnel.
The infrared detection device is arranged on the vehicle-mounted device, is connected with the synchronous controller and the information acquisition and processing system, and is used for detecting the rust expansion of the surface steel bars of the tunnel, the involved components comprise an infrared signal generator, an infrared pulse excitation device, an optical lens and an infrared thermal imager, and the functional relationship between the infrared signal generator, the infrared pulse excitation device, the optical lens and the infrared thermal imager is as follows:
under the cooperative control of the synchronous controller,
the infrared signal generator is used for emitting an infrared excitation signal, and the infrared pulse excitation device is used for heating the surface of the tunnel lining; and at the same time
The thermal infrared imager is used for collecting the infrared thermal image of the surface of the lining, and the optical lens is used for condensing light.
The high-definition camera is used for detecting crack characteristics of a tunnel lining potential spallation stripping surface.
The three-dimensional laser scanner is used for scanning the profile of the section and determining the deformation value of the rusted steel bar corresponding to the surface of the tunnel lining.
And the lighting device is used for providing illumination for the tunnel detection process.
And the laser encoder is used for acquiring the mileage position of the tunnel detection point and is connected with the synchronous controller and the information acquisition and processing system.
And the power supply equipment is arranged on the vehicle-mounted walking device and used for supplying power to the information acquisition and processing system, the sound vibration method detection device, the infrared detection device, the synchronous controller, the laser encoder, the high-definition camera, the three-dimensional laser scanner and the lighting equipment.
Step two, implementing a detection process:
step 1
The method comprises the steps of detecting two recessive diseases of potential peeling and stripping of the tunnel lining and reinforcing steel bar rust expansion by respectively using a sound vibration method and an infrared detection technology, and simultaneously storing recessive disease information and milepost numbers in an information acquisition system.
Step 1-1
Detecting the hidden defects on the surface of the tunnel lining by adopting a sound vibration method, and determining the stripping range, the stripping amount, the stripping depth and the stripping layer volume of the hidden defects on the surface of the tunnel lining, wherein the specific flow is shown in figure 4.
Step 1-1-1 theoretical value
Considering cracks and void layers inside a shallow layer of a tunnel lining as surface hidden defects, simplifying a potential spalling and stripping concrete structure induced by the cracks and the void layers into a thin plate structure, defining a cylinder with the diameter D and the thickness h as a thin plate unit, defining an air layer between the thin plate and the whole tunnel structure as the surface hidden defects, defining the air layer as a defect unit, prefabricating concrete test blocks with defects of different thin plate sizes and different defect sizes on the assumption that the defects are consistent with the thin plate range, namely the radius is R and the thickness is D, and determining theoretical resonant frequency f corresponding to the different thin plate sizes through formula 1 as shown in figure 5(a)i(i ═ 1, 2, … …, n, n are sheet size categories);
in fig. 5: 6 is a defect unit, 11 is a thin plate unit, 12 is a concrete sample with defects, 13 is a 1 st scanning point, 14 is a 2 nd scanning point, and 15 is a 3 rd scanning point; in the figure: h is the thickness of the thin plate unit, D is the diameter of the thin plate unit, and D is the depth of the defective unit behind the thin plate.
Equation 1:
in formula 1: f. ofiThe theoretical resonant frequency of the thin plate unit under different sizes is h, the thickness of the thin plate unit, D, the diameter of the thin plate unit, E, the elastic modulus of concrete at the thin plate unit, rho, the density of concrete at the thin plate unit and v, the Poisson ratio of concrete at the thin plate unit. )
Steps 1-1-2 (verification, measured value)
Step 1-1-2-1
From the step 1-1-1, it can be known that under the same sheet size, the concrete test blocks with defects of different defect sizes correspond to the same theoretical resonant frequency, so as to carry out further test tests, on the premise of the test, the concrete test blocks with defects (denoted as the ik test block, i denotes a certain sheet size, k denotes a certain defect size, and the same below) with the same sheet and the same defect size are selected for testing, the theoretical resonant frequency is added or subtracted within a certain range, and the range is the input range of the sweep frequency signal of the subsequent signal transmitter and denoted as Uik＝[fik-x，fik+x]；
Step 1-1-2
The sweep frequency signal range U determined in the step 1-1-2-1ikInputting the sound wave into a signal transmitter, amplifying the sound wave by a power amplifier, transmitting the sound wave to a concrete test block with defects by a long-distance sound wave transmitter, scanning a preset scanning point (comprising 3 points, the 1 st is the center point of the surface of the thin plate, the 2 nd is a boundary point on the circumference of the thin plate, and the 3 rd is a point in a range without defects on the back of the surface of the test block by a Doppler laser vibrometer, as shown in figure 5 (b)), keeping the transmitting direction of the sound wave transmitter consistent with the laser transmitting direction of the laser vibrometer during the test, and keeping a laser incident line vertical to the lining surface, wherein the specific detection method principle is shown in figure 6 (in figure 6, 1 is a signal transmitter, 2 is a power amplifier, 3 is a long-distance sound wave transmitter, 4 is a sound wave, 5 is a deflection vibration, 6 is a defect unit, 7 is a detector, 8 is a laser, 9 is a Doppler sound wave transmitter, 10 is an information acquisition and processing system), the vibration speeds of 3 characteristic points are sequentially acquired,and establishing a relation curve of the vibration speed and different sweep frequency signals, which is respectively marked as Fik1(fika，vik1)、Fik2(fikb，vik2) And Fik3(fikc，vik3) As shown in fig. 7 as an example, the graph is only the relationship curve of the vibration speed of a certain scanning point and different frequency sweep signal frequencies.
Steps 1-1-2-3
Vibration velocity-sweep signal relationship F at the center point (i.e., 1 st point) of the sheetik1(fika，vik1) Finding out the maximum vibration velocity vik1mAnd corresponding sweep frequency signal fikamThe frequency sweep signal famSequentially substituting the vibration speed-sweep frequency signal relation curves F of the 2 nd and the 3 rd pointsik2(fikb，vik2) And Fik3(fikc，vik3) To obtain a corresponding frequency sweep signal fikbm-1、fikcm-1And a vibration velocity vik2m-1、vik3m-1。
Steps 1-1-3 combine body surface vibration velocity (core)
Step 1-1-3-1
Repeating the steps 1-1-2-1 to 1-1-2-3, detecting the concrete test blocks with the defects of different sheet sizes and different defect sizes, and obtaining the maximum vibration speed v at the 1 st point in the steps 1-1-2-3ik1mAnd the corresponding swept frequency signal fikamAnd the frequency sweep signal f is converted into a frequency sweep signalikamSubstituting into the relationship curve F of vibration speed and sweep frequency signal of the 2 nd point and the 3 rd point in the steps 1-1-2-3ik2(fikb，vik2) And Fik3(fikc，vik3) To find out the corresponding vibration speed vik2m-1、vik3m-1；
Thereby obtaining an effective input for what range sweep signal, the shock velocity that must be relied upon at a particular size, and the profile size at that shock velocity.
Step 1-1-3-2
According to the test data of the step 1-1-3-1, under the condition that the thickness h of the thin plate and the thickness d of the defect are certain, establishing the straight plateFunctional relation G between diameter D and vibration speed of point 11(D，vik1m-1) Simultaneously, taking and collecting the sweep frequency signals corresponding to all the 1 st point vibration speeds respectively and recording as W1(ii) a Establishing a functional relation G between the thickness h of the thin plate and the vibration speed of the 1 st point under the condition that the diameter D of the thin plate and the size D of the defect are constant2(h，vik1m-1) Simultaneously, taking and collecting the sweep frequency signals corresponding to all the 1 st point vibration speeds respectively and recording as W2(ii) a Under the condition of certain sheet diameter D and sheet thickness h, establishing a functional relation G between the defect thickness D and the 1 st point vibration speed3(d，vik1m-1) Simultaneously, taking and collecting the sweep frequency signals corresponding to all the 1 st point vibration speeds respectively and recording as W3(ii) a The three functional relationships are graphically illustrated in fig. 8.
Steps 1-1-3
Collecting the sweep frequency signals W in the steps 1-1-3-21、W2And W3Taking a union set, and extracting the maximum value f of the obtained sweep frequency signal setmaxAnd minimum value fminThe sweep frequency signal range of the maximum value and the minimum value envelope is recorded as M ═ fmin，fmax]；
Steps 1-1-4 (actual measurement on site, speed, other quantities calculated in G1, G2, G3)
The actual field measurement and detection principle are different from those in fig. 6 in that the incident position of the doppler laser vibrometer is adjusted, a shaft synchronous rotating reflector parallel to the laser axis is added, a rotating shaft is also arranged on the sound wave emitter and rotates synchronously with the reflector, so as to ensure that the direction of the sound wave emitted by the long-distance sound wave emitter is consistent with the laser scanning direction, as shown in fig. 9 in detail and referred to as a two-dimensional scanning doppler laser vibrometer hereinafter
Inputting the sweep frequency signal range M determined in the steps 1-1-3-3 into a signal transmitter, amplifying by a power amplifier, transmitting sound waves to the surface of the tunnel lining by a long-distance sound wave transmitter, performing point-spaced scanning on the surface of the tunnel lining by adopting a two-dimensional scanning Doppler laser vibrometer, collecting the vibration speed of each point, and drawing the heat quantity of the vibration speed of the scanning point in the region in a data analysis systemA distribution graph, as shown in FIG. 10, extracting vibration velocity of the feature points in the graph, and substituting the distribution into the functional relation G of the sheet diameter D, the sheet thickness h and the defect thickness D in the step 2-1-3-21(D，vik1m-1，vik2m-1) And G2(h，vik1m-1，vik2m-1) And (3) determining the diameter D of the thin plate, the thickness h of the thin plate and the thickness D of the defect, and correspondingly substituting the parameters into the formulas (2) to (5) to basically determine the peeling range, the peeling amount, the peeling depth and the peeling layer volume of the hidden defect on the surface of the tunnel lining.
Equation (2), peel range a:
formula (3), peeling amount V1：
Equation (4), void depth H (the vertical distance of the geometric center of the air space from the tunnel lining surface):
formula (5), void layer volume V2：
Equation (6), void layer perimeter C: c ═ pi D
Namely the stripping amount, the stripping depth and the perimeter of a stripping layer of the potential stripping defects of the surface layer of the tunnel lining.
Steps 1-1 to 5
Detecting the crack characteristics of the spalled and stripped part by using a high-definition camera according to the potential spalled and stripped part of the surface layer of the tunnel lining detected in the step 1-1-4, and analyzing to obtain the total crack length C of the spalled and stripped part on the surface of the lining1。
Steps 1-1 to 6
Based on the detection in steps 1-1-4 and 1-1-5Obtaining the crack characteristics and the perimeter of a void layer of the potential spalling and stripping part of the surface layer of the tunnel lining, and obtaining the ratio C of the total length of the cracks on the surface of the tunnel lining to the perimeter of the void of the surface layer by taking the ratio of the crack characteristics and the perimeter of the void of the surface layer of the tunnel lining as a ratio2The concrete formula is as follows:
equation (7), the ratio of the total length of the tunnel lining face cracks to the perimeter of the skin voids C2:
according to the ratio C of the total length of the surface cracks of the tunnel lining to the perimeter of the surface gaps2The peeling possibility of the part is judged by the following specific judging method:
(1) when the ratio of the total length of the surface cracks of the tunnel lining to the perimeter of the surface gap is C2 to 2/3, stripping of the detected part is about to occur, and immediately taking corrective measures;
(2) when the ratio of the total length of the surface cracks of the tunnel lining to the perimeter of the surface void is not less than 1/3 and C2 is less than 2/3, the detected part is likely to be stripped and corrective measures should be taken in time;
(3) when the ratio C2 of the total length of the surface cracks of the tunnel lining to the perimeter of the surface void is less than 1/3, the detected part may be peeled off in the future, long-term tracking detection should be performed on the part, and corrective measures should be taken in time if the part develops.
Step 1-2
The potential reinforcement bar rusty expansion position and the steel degree of the tunnel lining are detected by using an infrared detection technology, the width and the length of a rusty expansion crack are measured by using a shooting method, and the specific flow is shown in fig. 11.
Step 1-2-1
Carrying out an indoor model test, adopting an infrared detection technology, analyzing to obtain a temperature characteristic criterion of the reinforcement bar rust expansion in an infrared thermograph, and establishing a reinforcement bar rust expansion degree S and an average temperature T of a rust expansion partavgThe relationship of (1).
Step 1-2-1
Manufacturing reinforced concrete test pieces with different reinforcement rust expansion degrees consistent with actual tunnel lining structure parameters for experimental analysis, wherein the infrared detection principle is shown in figure 12, the section of the test piece is shown in figure 13, and the method adoptsHeating the surface of each test piece to a certain temperature T by high-power infrared pulse thermal excitation, and acquiring the temperature distribution characteristics T + delta T displayed by the steel bar rusty expansion part in each infrared thermographiThereby presetting the temperature threshold value range U for judging the steel bar rust disease partT＝[T+ΔTmin，T+ΔTmax]；
Step 1-2-1-2
Based on the acquired temperature distribution characteristics T + delta T of the steel bar rusty parts of the test piecesiCalculating the average temperature T of the partavg＝(T+ΔTi) /2, thereby establishing the degree of reinforcement bar corrosion and the average temperature T of the portionavgIs marked as a first relation, as shown in fig. 14, the fitting formula is shown as formula (6), and the degree of reinforcement corrosion is: a is1+A2Tavg+A3Tavg 2In formula (6): a. the1、A2And A3Are constants obtained by fitting based on experimental data.
Step 1-2-1-3
According to the set temperature threshold value range UT＝[T+ΔTmin，T+ΔTmax]Potential reinforcement bar rusty expansion positions and the average temperature of the positions are extracted from the infrared thermograph of the actual tunnel lining surface, and the reinforcement bar rusty expansion degree S is preliminarily determined based on the established first relation curve.
Step 1-2
Deformation determination interval U for detecting critical rusty cracks generated between adjacent rusty reinforcing steel bars by means of three-dimensional laser scannerAnd defining a preliminary criterion of potential stripping possibility caused by reinforcement bar rust expansion.
Deformation determination section U when rusty cracks are generated between adjacent rusty-swollen reinforcing steel barsThe specific determination process of (2) is as follows:
(1) manufacturing a reinforced concrete test block, wherein the test block comprises two main bars, and measuring the deformation S from the main bars to the surface of the test block by means of a three-dimensional laser scanner10And S20；
(2) The reinforcing steel bars of the reinforced concrete test block are rusted and expanded at an accelerated speed by adopting a semi-wet electrified method until the corrosion resistance between two reinforcing steel bars is increasedGenerating rusty cracks on the surface of the test block between the main ribs, detecting the deformation from the two main ribs to the surface of the test block by means of a three-dimensional laser scanner, and respectively recording the deformation as S11And S21；
(3) Defining respective deformation increment of critical rusty crack generated between adjacent rusty reinforcing steel bars as1And2wherein1＝S11-S10，2＝S21-S20And is connected with UAs a deformation zone between adjacent auxetic bars that creates a critical auxetic crack, where U＝[min{1，2}，max{1，2}]。
The preliminary criterion of the potential stripping possibility caused by the reinforcement corrosion expansion is as follows:
(1) incremental deformation of lining surface at rusted rebar
And max1，2There is no potential for peel-off peeling;
(2) the deformation increment of the lining surface at the rusted steel bar belongs to UGreat or > max1，2There is a potential for peel-off peeling;
FIG. 16 is a schematic diagram showing the influence range of the steel bar rust expansion of the reinforced concrete test block on the deformation of the test block.
Steps 1-2-3
Based on the preliminary determination of the potential peeling and stripping caused by the steel bars in the step 1-2-2, if the possibility of peeling and stripping exists, the development trend of the potential peeling and stripping is further determined by taking the crack characteristics of the tunnel lining surface of the rusty part by means of a high-definition camera, wherein the crack characteristics comprise a down-web crack and a longitudinal crack, and the total length D of the down-web crack is recorded at the same time1And total longitudinal crack length D2。
The development trend criterion of the potential peeling and stripping caused by the reinforcement bar rust expansion is specifically as follows:
(1) when the total length of the downweb crack is less than 1/3 which is the sum of the lengths of the downweb and longitudinal cracks, D1＜(D1+D2) The detected part isIf peeling or peeling occurs, long-term tracking detection should be performed on the part, and if the part is developed, corrective measures should be taken in time;
(2) when the total length of the longitudinal slit is between 1/3 and 2/3 of the sum of the longitudinal slit length and the longitudinal slit length, that is (D)1+D2)/3≤D1＜2(D1+D2) The detected part is likely to be stripped, and a treatment measure is taken in time;
(3) d when the total length of the downweb cracks is greater than or equal to 2/3 which is the sum of the lengths of the downweb cracks and the longitudinal cracks1≥2(D1+D2) (iii)/3, immediately taking corrective measures when the detected part is about to be stripped;
fig. 17 is a schematic diagram of crack characteristic analysis of a steel bar rusty area.
Steps 1-2-4
In the field test, the tunnel lining surface to be tested is heated to the temperature upper limit threshold value T + delta T by using a high-power infrared pulse thermal excitation sourcemaxAcquiring an original infrared thermography reflecting the temperature distribution condition of the surface of the lining, enhancing the original infrared thermography in a gray level correction, noise reduction filtering and edge segmentation mode to obtain the infrared thermography highlighting the temperature distribution characteristics, and based on the temperature threshold value range U in the step 1-2-1-1TJudging the potential reinforcement bar rust expansion position, and determining the reinforcement bar rust expansion degree S according to the first curve relation in the step 1-2-1-3Measuring。
After the steel bar rusty expansion part is preliminarily determined, detecting the deformation of the lining surface of the rusty expansion steel bar part by means of a three-dimensional laser scanner, and preliminarily determining the possibility of potential peeling and stripping caused by steel bar rusty expansion based on the deformation determination interval U when the adjacent rusty expansion steel bars in the step 1-2-2 generate critical rusty expansion cracks. If the possibility of potential peeling and peeling caused by steel bar rust expansion exists, determining the development trend of peeling and peeling based on the development trend criterion of potential peeling and peeling caused by steel bar rust expansion in the steps 1-2-3 by adopting a shooting method.
Step 2
The collected tunnel lining surface layer disease information comprises tunnel lining surface layer disease information caused by material aging and reinforcing steel bar rust expansionAnd (3) potential stripping, integrating the information in a data acquisition and processing system, drawing a spatial information distribution diagram of the tunnel lining surface layer diseases corresponding to the milepost numbers, and marking potential stripping possibility, range, size and depth, and reinforcing steel bar rusty expansion positions and ranges in the diagram as shown in fig. 15, so that the comprehensive and rapid detection of the tunnel lining surface layer diseases is realized, and a visual graph which visually reflects disease information can be obtained. K in FIG. 15i+ Num1 and Km+ Num2 each represents a mileage stake number.
Claims (2)
1. A rapid detection method for surface layer diseases of a tunnel structure is characterized by comprising the following steps:
firstly, constructing a rapid detection device for the surface diseases of the tunnel structure;
the system comprises a vehicle-mounted walking device, a detection device and an information acquisition and processing system, and the vehicle-mounted walking device is used for loading the detection device and the information acquisition and processing system and conveying the detection device and the information acquisition and processing system to each detection point of a tunnel.
Step two, implementing a detection process:
step 1
The method comprises the steps of detecting two recessive diseases of potential peeling and stripping of the tunnel lining and reinforcing steel bar rust expansion by respectively using a sound vibration method and an infrared detection technology, and simultaneously storing recessive disease information and milepost numbers in an information acquisition system.
Step 2
The acquired tunnel lining surface layer disease information comprises tunnel lining potential stripping caused by material aging and reinforcing steel bar corrosion and expansion, the information is integrated in a data acquisition and processing system, a spatial information distribution diagram of the tunnel lining surface layer disease corresponding to the milepost number is drawn, and the potential stripping possibility, range, size and depth and reinforcing steel bar corrosion and expansion position and range are marked in the diagram, so that comprehensive and rapid detection of the tunnel lining surface layer disease is realized, and a visual graph which visually reflects the disease information is obtained.
2. The rapid detection method according to claim 1, wherein the step 1 specifically comprises:
step 1-1
And detecting the hidden defects on the surface of the tunnel lining by adopting a sound vibration method, and determining the stripping range, stripping amount, stripping depth and stripping layer volume of the hidden defects on the surface of the tunnel lining.
Step 1-1
The method comprises the following steps of (1) regarding cracks and void layers in a shallow tunnel lining layer as surface hidden defects, simplifying a potential spalling and stripping concrete structure induced by the cracks and the void layers into a thin plate structure, defining a cylinder with the diameter D and the thickness h as a thin plate unit, defining an air layer between the thin plate and the whole tunnel structure as the surface hidden defects, defining the air layer as a defect unit, and assuming that the range of the defects is consistent with that of the thin plate, namely the radius is R and the thickness is D; determining the resonant frequency f corresponding to different sheet sizes by formula 1i(i ═ 1, 2, … …, n, n are sheet size categories);
equation 1:
in formula 1: f. ofiThe theoretical resonant frequency of the thin plate unit under different sizes is h, the thickness of the thin plate unit, D, the diameter of the thin plate unit, E, the elastic modulus of concrete at the thin plate unit, rho, the density of concrete at the thin plate unit and v, the Poisson ratio of concrete at the thin plate unit.
Step 1-1-2, comprising:
step 1-1-2-1
Adding or subtracting the theoretical resonant frequency within a certain range, wherein the range is the input range of the frequency sweep signal of the subsequent signal transmitter and is expressed as Uik＝[fik-x，fik+x]；
Step 1-1-2
Establishing a relation curve of the vibration speed and different sweep frequency signals, and respectively recording the relation curve as Fik1(fika，vik1)、Fik2(fikb，vik2) And Fik3(fikc，vik3)；
Steps 1-1-2-3
Vibration velocity-sweep signal relationship F at the center point (i.e., 1 st point) of the sheetik1(fika，vik1) Finding out the maximum vibration velocity vik1mAnd corresponding sweep frequency signal fikamThe frequency sweep signal famSequentially substituting the vibration speed-sweep frequency signal relation curves F of the 2 nd and the 3 rd pointsik2(fikb，vik2) And Fik3(fikc，vik3) To obtain a corresponding frequency sweep signal fikbm-1、fikcm-1And a vibration velocity vik2m-1、vik3m-1。
Step 1-1-3 binding body surface vibration velocity
Step 1-1-3-1
Repeating the steps 1-1-2-1 to 1-1-2-3 to obtain the effective input of what range sweep frequency signal, the vibration speed which must be depended on under a specific size and the contour size under the vibration speed.
Step 1-1-3-2
Under the condition that the thickness h of the thin plate and the thickness D of the defect are constant, establishing a functional relation G between the diameter D of the thin plate and the vibration speed of the 1 st point1(D，vik1m-1) Simultaneously, taking and collecting the sweep frequency signals corresponding to all the 1 st point vibration speeds respectively and recording as W1(ii) a Establishing a functional relation G between the thickness h of the thin plate and the vibration speed of the 1 st point under the condition that the diameter D of the thin plate and the size D of the defect are constant2(h，vik1m-1) Simultaneously, taking and collecting the sweep frequency signals corresponding to all the 1 st point vibration speeds respectively and recording as W2(ii) a Under the condition of certain sheet diameter D and sheet thickness h, establishing a functional relation G between the defect thickness D and the 1 st point vibration speed3(d，vik1m-1) Simultaneously, taking and collecting the sweep frequency signals corresponding to all the 1 st point vibration speeds respectively and recording as W3；
Steps 1-1-3
Collecting the sweep frequency signals W in the steps 1-1-3-21、W2And W3Taking a union set, and extracting the maximum value f of the obtained sweep frequency signal setmaxAnd minimum value fminThe sweep frequency signal range of the maximum value and the minimum value envelope is recorded as M ═ fmin，fmax]；
Steps 1-1-4 (on-site)
Inputting the sweep frequency signal range M determined in the steps 1-1-3-3 into a signal transmitter, amplifying the signal by a power amplifier, transmitting sound waves to the surface of the tunnel lining by a long-distance sound wave transmitter, performing point separation scanning on the surface of the tunnel lining by adopting a two-dimensional scanning Doppler laser vibrometer, collecting vibration speeds of all points, drawing a vibration speed and heat distribution diagram of the scanning points in the region in a data analysis system, extracting the vibration speed of characteristic points in the diagram, and substituting the distribution into the functional relationship G of the diameter D of the thin plate, the thickness h of the thin plate and the thickness D of the defect in the step 2-1-3-21(D，vik1m-1，vik2m-1) And G2(h，vik1m-1，vik2m-1) And (3) determining the diameter D of the thin plate, the thickness h of the thin plate and the thickness D of the defect, and correspondingly substituting the parameters into the formulas (2) to (5) to basically determine the peeling range, the peeling amount, the peeling depth and the peeling layer volume of the hidden defect on the surface of the tunnel lining.
Equation (2), peel range a:
formula (3), peeling amount V1：
Equation (4), void depth H (the vertical distance of the geometric center of the air space from the tunnel lining surface):
formula (5), void layer volume V2：
Equation (6), void layer perimeter C: c ═ pi D
Namely the stripping amount, the stripping depth and the perimeter of a stripping layer of the potential stripping defects of the surface layer of the tunnel lining.
Steps 1-1 to 5
Detecting the crack characteristics of the spalled and stripped part by using a high-definition camera according to the potential spalled and stripped part of the surface layer of the tunnel lining detected in the step 1-1-4, and analyzing to obtain the total crack length C of the spalled and stripped part on the surface of the lining1。
Steps 1-1 to 6
Based on the crack characteristics and the perimeter of the stripping layer of the potential stripping part of the surface layer of the tunnel lining detected in the steps 1-1-4 and 1-1-5, the ratio C of the total length of the cracks on the surface layer of the tunnel lining to the perimeter of the gap of the surface layer is obtained by taking the ratio of the crack characteristics and the perimeter of the stripping layer as a ratio2The concrete formula is as follows:
equation (7), the ratio of the total length of the tunnel lining face cracks to the perimeter of the skin voids C2:
according to the ratio C of the total length of the surface cracks of the tunnel lining to the perimeter of the surface gaps2The peeling possibility of the part is judged by the following specific judging method:
(1) when the ratio of the total length of the surface cracks of the tunnel lining to the perimeter of the surface gap is C2 to 2/3, stripping of the detected part is about to occur, and immediately taking corrective measures;
(2) when the ratio of the total length of the surface cracks of the tunnel lining to the perimeter of the surface void is not less than 1/3 and C2 is less than 2/3, the detected part is likely to be stripped and corrective measures should be taken in time;
(3) when the ratio C2 of the total length of the surface cracks of the tunnel lining to the perimeter of the surface void is less than 1/3, the detected part may be peeled off in the future, long-term tracking detection should be carried out on the part, and corrective measures should be taken in time if development exists;
step 1-2
Detecting the potential reinforcement bar rust expansion part and the steel degree of the tunnel lining by using an infrared detection technology, and measuring the width and the length of a rust expansion crack by using a shooting method;
step 1-2-1
Establishing the degree of reinforcement Rust Swell SAnd the mean temperature T of the rusty partsavgThe relationship curve of (1);
step 1-2-1
Acquiring temperature distribution characteristic T + delta T displayed by the steel bar rusty scale part in each infrared thermographiPresetting a temperature threshold value range U for judging the steel bar rust disease partT＝[T+ΔTmin，T+ΔTmax]；
Step 1-2-1-2
Based on the acquired temperature distribution characteristics T + delta T of the steel bar rusty parts of the test piecesiCalculating the average temperature T of the partavg＝(T+ΔTi) /2, thereby establishing the degree of reinforcement bar corrosion and the average temperature T of the portionavgThe fitting formula is shown as formula (6), and the steel bar rust expansion degree S is: a is1+A2Tavg+A3Tavg 2In formula (6): a. the1、A2And A3Are constants obtained by fitting based on experimental data.
Step 1-2-1-3
According to the set temperature threshold value range UT＝[T+ΔTmin，T+ΔTmax]Potential reinforcement bar rusty expansion positions and the average temperature of the positions are extracted from the infrared thermograph of the actual tunnel lining surface, and the reinforcement bar rusty expansion degree S is preliminarily determined based on the established first relation curve.
Step 1-2
Deformation determination interval U for detecting critical rusty cracks generated between adjacent rusty reinforcing steel bars by means of three-dimensional laser scannerAnd defining a preliminary criterion of potential stripping possibility caused by reinforcement bar rust expansion.
The preliminary criterion of the potential stripping possibility caused by the reinforcement corrosion expansion is as follows:
(1) incremental deformation of lining surface at rusted rebar
And max1，2There is no potential for peel-off peeling;
(2) the deformation increment of the lining surface at the rusted steel bar belongs to UGreat or > max1，2There is a potential for peel-off peeling;
steps 1-2-3
Based on the preliminary determination of the potential peeling and stripping caused by the steel bars in the step 1-2-2, if the possibility of peeling and stripping exists, the development trend of the potential peeling and stripping is further determined by taking the crack characteristics of the tunnel lining surface of the rusty part by means of a high-definition camera, wherein the crack characteristics comprise a down-web crack and a longitudinal crack, and the total length D of the down-web crack is recorded at the same time1And total longitudinal crack length D2。
The development trend criterion of the potential peeling and stripping caused by the reinforcement bar rust expansion is specifically as follows:
(1) when the total length of the downweb crack is less than 1/3 which is the sum of the lengths of the downweb and longitudinal cracks, D1＜(D1+D2) The detected part is likely to peel off in the future, long-term tracking detection is carried out on the part, and corrective measures are taken in time if the part is developed;
(2) when the total length of the longitudinal slit is between 1/3 and 2/3 of the sum of the longitudinal slit length and the longitudinal slit length, that is (D)1+D2)/3≤D1＜2(D1+D2) The detected part is likely to be stripped, and a treatment measure is taken in time;
(3) d when the total length of the downweb cracks is greater than or equal to 2/3 which is the sum of the lengths of the downweb cracks and the longitudinal cracks1≥2(D1+D2) (iii)/3, immediately taking corrective measures when the detected part is about to be stripped;
steps 1-2-4
In the field test, the tunnel lining surface to be tested is heated to the temperature upper limit threshold value T + delta T by using a high-power infrared pulse thermal excitation sourcemaxAcquiring an original infrared thermography reflecting the temperature distribution condition of the surface of the lining, enhancing the original infrared thermography to obtain an infrared thermography highlighting the temperature distribution characteristics, and based on the temperature threshold value range U in the step 1-2-1-1TJudging the potential reinforcement bar rust expansion position, and determining the reinforcement bar rust expansion process according to the first curve relation in the step 1-2-1-3Degree SMeasuring。
After the steel bar rusty expansion part is preliminarily determined, detecting the deformation of the lining surface of the rusty expansion steel bar part by means of a three-dimensional laser scanner, and preliminarily determining the possibility of potential peeling and stripping caused by steel bar rusty expansion based on the deformation determination interval U when the adjacent rusty expansion steel bars in the step 1-2-2 generate critical rusty expansion cracks. If the possibility of potential peeling and peeling caused by steel bar rust expansion exists, determining the development trend of peeling and peeling based on the development trend criterion of potential peeling and peeling caused by steel bar rust expansion in the steps 1-2-3 by adopting a shooting method.
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| CN113899886A (en) * | 2021-10-11 | 2022-01-07 | 广东粤海珠三角供水有限公司 | Joint detection method based on concrete lining void standard body |
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| CN113008990A (en) * | 2021-03-12 | 2021-06-22 | 清华大学 | Non-contact nondestructive testing system and method for steel-concrete immersed tube tunnel |
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| CN112684443B (en) * | 2021-03-15 | 2021-05-28 | 中国铁建重工集团股份有限公司 | Lining structure disease detection method, device and medium |
| CN113899886A (en) * | 2021-10-11 | 2022-01-07 | 广东粤海珠三角供水有限公司 | Joint detection method based on concrete lining void standard body |
| CN113984288A (en) * | 2021-10-22 | 2022-01-28 | 中国能源建设集团江苏省电力设计院有限公司 | Cable tunnel lining water leakage detection device and method |
| CN113984288B (en) * | 2021-10-22 | 2024-05-03 | 中国能源建设集团江苏省电力设计院有限公司 | Device and method for detecting leakage water of cable tunnel lining |
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