A method for detecting the density of prestressed duct grouting

Abstract

This invention discloses a method for detecting the grout density of prestressed ducts, belonging to the field of non-destructive testing technology in civil engineering. The method includes: arranging an acoustic wave sensor on the outer surface of the prestressed duct to be tested; simultaneously activating the acoustic wave sensor by striking one end of the steel strand inside the prestressed duct to generate an acoustic wave; and collecting the first arrival wave of the acoustic wave signal during the sensor's movement; using the time delay of the first arrival wave to determine whether there are defects in the grout inside the prestressed duct; and calculating a comprehensive defect identification index to evaluate the grout density inside the prestressed duct. This invention places the acoustic wave sensor and the acoustic wave excitation point on adjacent surfaces. During the measurement process, the acoustic wave sensor moves along the propagation direction of the acoustic wave within the prestressed duct, avoiding excessive scattering and absorption of the acoustic wave by the medium material during propagation, thus improving the acoustic wave acquisition efficiency and the accuracy of measuring grout defects within the prestressed duct.

Description

Technical Field

[0001] This invention relates to the field of non-destructive testing technology in civil engineering, and in particular to a method for detecting the compactness of grouting in prestressed ducts. Background Technology

[0002] To ensure the durability and load-bearing capacity of the beam during construction, prevent corrosion of the prestressed steel strands, and ensure that they are tightly bonded to the surrounding concrete to form a whole to jointly withstand external forces, grouting needs to be carried out in the prestressed ducts in a timely manner after the prestressed steel strands are tensioned. The density of the grouting is one of the key factors affecting the performance of prestressed concrete bridges.

[0003] Currently, pulse-echo testing is the mainstream method for flaw detection: a voltage emitted by a pulse oscillator is applied to the probe (a detection element made of piezoelectric ceramic or quartz crystal). The ultrasonic pulse emitted by the probe enters the material through an acoustic coupling medium (such as machine oil or water) and propagates within it. Upon encountering a defect, some of the reflected energy returns to the probe along the original path, where it is converted back into an electrical pulse. This pulse is then amplified and displayed on the fluorescent screen of an oscilloscope. By analyzing the position and amplitude of the defect's reflected wave on the fluorescent screen (compared to the amplitude of the reflected wave from an artificial defect in a reference test block), the location and approximate size of the defect can be determined.

[0004] The defects of the above-mentioned existing technology are: the probe and the ultrasonic excitation position are on opposite sides, the position of the probe is fixed, the propagation path of the ultrasonic wave is long, and the concrete material scatters and absorbs too much ultrasonic wave, resulting in low signal-to-noise ratio and failing to guarantee the accuracy of grout density measurement. Summary of the Invention

[0005] This invention provides a method for detecting the grout density of prestressed ducts, which can solve the problem that the accuracy of grout density measurement cannot be guaranteed in the prior art.

[0006] This invention provides a method for detecting the grout density of prestressed ducts, comprising:

[0007] An acoustic wave sensor is placed on the outer surface of the prestressed duct; the acoustic wave sensor is activated at the same time as the sound wave is generated by striking one end of the steel strand inside the prestressed duct. The acoustic wave sensor collects the first and last waves of the sound wave signal during the movement.

[0008] Calculate the propagation time t1 of the sound wave in the steel strand and the propagation time t2 of the sound wave in the grouting material when there are no defects in the prestressed duct grouting. The first-to-last time of the sound wave signal is the sum of the propagation time t1 of the sound wave in the steel strand and the propagation time t2 of the sound wave in the grouting material.

[0009] When there are defects in the grouting of the prestressed duct to be tested, the time for the sound wave to propagate in the steel strand is t1' and the time for the sound wave to propagate in the grouting material is t2'. The time extension of the first-to-last time of the sound wave signal is calculated to determine whether there are defects in the grouting inside the prestressed duct: when the time extension is equal to 0, there are no defects in the grouting inside the prestressed duct; when the time extension is greater than 0, there are defects in the grouting inside the prestressed duct.

[0010] Based on the arrival time of the first wave, the first wave time identification index k1(x), the peak-to-peak value identification index k2(x), and the stress wave peak-to-peak value identification index k3(x) are calculated respectively. Then, the comprehensive defect identification index k(x) is calculated to evaluate the grouting density inside the prestressed duct.

[0011] Additionally, the acoustic sensor moves along the direction of acoustic wave propagation on the surface of the prestressed duct.

[0012] Furthermore, the time it takes for the sound wave to propagate within the steel strand is t1, and the time it takes for the sound wave to propagate within the grouting material is t2; if there are no defects in the grouting inside the prestressed duct, then

[0013] t1=(xa) / V 钢

[0014] t2=a / (sinβ×V 混 )

[0015] Where x is the horizontal distance between the position of the acoustic sensor and the acoustic emission point, and V 钢 V is the propagation speed of the shear wave in the steel strand. 混 denoted as the propagation velocity of the shear wave in the grouting material, α as the thickness of the grouting material outside the prestressed duct, and β as the angle between the propagation direction of the stress wave in the grouting material and the vertical direction.

[0016] Additionally, the method of calculating the time extension of the first-to-last wave time of the acoustic signal to determine whether there are defects in the grouting inside the prestressed duct includes: if there are defects in the grouting inside the prestressed duct, when the side of the defect blocks the propagation of the acoustic wave, t1 remains unchanged, but t2 will be extended due to diffraction of the acoustic wave, and the extended time is t2'.

[0017]

[0018] Where, a is the thickness of the grouting material outside the prestressed duct, b is the thickness of the grouting material inside the duct, c is the horizontal distance the stress wave travels through the grouting material inside the prestressed duct, d is the thickness of the grouting material outside the duct, β is the angle between the direction of stress wave propagation in the grouting material and the vertical direction, and V 混 This represents the propagation speed of the shear wave within the grouting material.

[0019] The time delay is:

[0020]

[0021] Where, a is the thickness of the grouting material outside the prestressed duct, b is the thickness of the grouting material layer inside the duct, c is the horizontal distance the stress wave travels through the grouting material inside the prestressed duct, d is the thickness of the grouting material layer outside the duct, β is the angle between the propagation direction of the stress wave in the grouting material and the vertical direction, and V 混 This represents the propagation speed of the shear wave within the grouting material.

[0022] When the long side of the defect blocks the propagation of the wave in that direction: if the wave is refracted from the steel strand to the grouting material at the origin of the defect and then diffracts to reach the acoustic sensor, then:

[0023] t1'=(xae) / V 钢

[0024] t2'={b+[(a+e) 2 +d 2 ] 1 / 2} / V 混

[0025] If the wave refracts from the steel strand to the grouting material at the end of the defect, and then diffracts to reach the acoustic sensor, then:

[0026] t1”=(x-a+f) / V 钢

[0027] t2”={b+[(fa) 2 +d 2 ] 1 / 2} / V 混

[0028] The time delay amounts in the two cases are as follows:

[0029]

[0030]

[0031] Where, a is the thickness of the grouting material outside the prestressed duct, b is the thickness of the grouting material inside the duct, c is the horizontal distance the stress wave travels through the grouting material inside the prestressed duct, d is the thickness of the grouting material layer outside the duct, f is the horizontal distance the stress wave travels through the grouting material inside the prestressed duct, e is the distance from the sound wave refraction point to the starting position when no defects are set, β is the angle between the propagation direction of the stress wave in the grouting material and the vertical direction, and V 混 V is the propagation velocity of the shear wave in the grouting material. 钢 denoted as the propagation speed of the shear wave in the steel strand.

[0032] Additionally, the lower of Δt1 and Δt2 is taken as the time extension value when the longer side of the defect blocks the propagation of the wave in that direction.

[0033] Additionally, if the horizontal distance between the acoustic sensor and the acoustic emission point is greater than the horizontal distance between the end of the defect and the acoustic emission point, and the defect can still be detected:

[0034] t1'=(x-a+f) / V 钢

[0035] t2'={[(b+d) 2 +(fa) 2 ] 1 / 2} / V 混

[0036] The time delay is:

[0037]

[0038] Where, a is the thickness of the grouting material outside the prestressed duct, β is the angle between the propagation direction of the stress wave in the grouting material and the vertical direction, f is the horizontal distance of the stress wave propagation in the grouting material inside the prestressed duct, and V 混 V is the propagation velocity of the shear wave in the grouting material. 钢 denoted as the propagation speed of the shear wave in the steel strand.

[0039] Additionally, the calculation of the first-arrival time identification index k1(x), peak-to-peak value identification index k2(x), and stress wave peak-to-peak value identification index k3(x) based on the first-arrival time, followed by the calculation of the comprehensive defect identification index k(x), to evaluate the grout density inside the prestressed duct includes:

[0040] First arrival time recognition index k1(x):

[0041] k1(x)=1-[T(x)-T0(x)-∑(T(x)-T0(x)) / (10n)] / (T(x)-T0(x))

[0042] Where x is the horizontal distance between the position of the acoustic sensor and the acoustic emission point, T0(x) is the first arrival time of the acoustic sensor at a horizontal distance x cm from the impact point when there is no defect, T(x) is the first arrival time of the acoustic sensor at a horizontal distance x cm from the impact point in any model, a is the width of the concrete in the duct, b is the width of the concrete in the duct, and the number of acoustic sensors is n.

[0043] Peak-to-peak value recognition index k2(x):

[0044] k2(x)=H(x) / H0(x)(0≤k2(x)≤1)

[0045] Where x is the horizontal distance between the position of the acoustic sensor and the acoustic emission point, H0(x) is the peak value of the acoustic sensor received at a horizontal distance x cm from the impact point when there is no defect, and H(x) is the peak value of the acoustic sensor received at a horizontal distance x cm from the impact point for any model.

[0046] Stress wave peak-to-peak value identification index k3(x):

[0047] k3(x)=U(x) / U0(x)(0≤k3(x)≤1)

[0048] Where x is the horizontal distance between the position of the acoustic sensor and the acoustic emission point, U0(x) is the first arrival wave peak received by the acoustic sensor at a horizontal distance x cm from the impact point when there is no defect, and U(x) is the peak value of the acoustic sensor at a distance x cm from the impact point for any model.

[0049] Defect identification index k(x):

[0050] k(x)=(k1(x)+k2(x)+k3(x)) / 3(0≤k(x)≤1)

[0051] Where x is the horizontal distance between the position of the acoustic sensor and the acoustic emission point, k1(x) is the first-to-the-wave time recognition index, k2(x) is the peak-to-peak recognition index, and k3(x) is the peak-to-peak recognition index.

[0052] When the value of the defect comprehensive identification index k(x) is closer to 1, it indicates that the grouting density is better and there is no grouting defect; when it is closer to 0, it indicates that the grouting density is worse and there is a greater possibility of grouting defect.

[0053] Additionally, the range of the first arrival time identification index k1(x) is 0≤k1(x)≤1; when T(x)-T0(x)=0, that is, there is no first arrival time extension, the default is k1(x)=1; the range of the peak-to-peak value identification index k2(x) is 0≤k2(x)≤1; and the range of the peak-to-peak value identification index k3(x) is 0≤k3(x)≤1.

[0054] Additionally, if the calculated values ​​of the first-to-last wave time identification index k1(x), peak-to-peak wave identification index k2(x), and peak-to-peak wave identification index k3(x) are greater than 1, then their values ​​are counted as 1.

[0055] The method for detecting the grout density of prestressed ducts provided in this embodiment of the invention has the following advantages compared with the prior art:

[0056] The invention collects the first arrival wave of a sound wave signal during the movement of an acoustic wave sensor. The first arrival wave time is the sum of the sound wave propagation time t1 within the steel strand and the sound wave propagation time t2 within the grouting material. When there are defects in the grouting of the prestressed duct, the sound wave propagation time t1 within the steel strand and the sound wave propagation time t2 within the grouting material will be prolonged, and the first arrival wave time will also be prolonged. Therefore, the existence of defects in the grouting inside the prestressed duct is determined by calculating the time extension of the first arrival wave time. This invention places the acoustic wave sensor and the sound wave excitation position on adjacent surfaces, avoiding excessive scattering and absorption of the sound wave by the medium material during propagation, thus improving the sound wave acquisition efficiency. During the measurement process, the acoustic wave sensor moves along the propagation direction of the sound wave within the prestressed duct, improving the accuracy of measuring grouting defects within the prestressed duct. Attached Figure Description

[0057] Figure 1 This is a schematic diagram of the instrument connection for a method of detecting the compactness of prestressed duct grouting in one embodiment;

[0058] Figure 2 A schematic diagram of the wave refraction law for a method of detecting the compactness of prestressed duct grouting provided in one embodiment;

[0059] Figure 3 This is a schematic diagram of wave propagation in one embodiment of a method for detecting the compactness of prestressed duct grouting.

[0060] Figure 4 This is a schematic diagram of a sound wave encountering a defect during transmission in a method for detecting the compactness of grouting in a prestressed duct, provided in one embodiment.

[0061] Figure 5 This is a schematic diagram of acoustic wave propagation at position 1 of an acoustic sensor, provided in one embodiment of a method for detecting the compactness of prestressed duct grouting.

[0062] Figure 6 This is a schematic diagram of acoustic wave propagation at position 2 of an acoustic sensor in a method for detecting the compactness of prestressed duct grouting, provided in one embodiment.

[0063] Figure 7 A schematic diagram of acoustic wave propagation at the location 3 of an acoustic sensor in a method for detecting the compactness of prestressed duct grouting, provided in one embodiment;

[0064] Figure 8 Three model template dimension diagrams for an indoor test of a method for detecting the compactness of prestressed duct grouting, as provided in one embodiment;

[0065] Figure 9This is a schematic diagram showing the defect arrangement locations of three models in an indoor test of a method for detecting the compactness of prestressed duct grouting, as provided in one embodiment.

[0066] Figure 10 This is a data graph showing the change of the first-to-wave time of the first six ducts as the position of the acoustic sensor changes during an indoor test of a method for detecting the compactness of prestressed duct grouting, provided in one embodiment.

[0067] Figure 11 This is a data graph showing the change in the first-to-last wave amplitude of the first six ducts as the position of the acoustic sensor changes, based on an indoor test of a method for detecting the compactness of prestressed duct grouting provided in one embodiment.

[0068] Figure 12 This is a data graph showing the change in peak value of the first six ducts as the position of the acoustic sensor changes during an indoor test of a method for detecting the compactness of prestressed duct grouting, provided in one embodiment.

[0069] Figure 13 This is a graph showing how three indicators of the acoustic signal of the seventh duct, as a result of the change in the position of the acoustic sensor, are obtained from an indoor test of a method for detecting the compactness of prestressed duct grouting in one embodiment.

[0070] Figure 14 The detection cloud map is a 3dmax detection method based on the defect comprehensive identification index to identify the defect location of Model 1 of a method for detecting the grout density of prestressed ducts provided in one embodiment.

[0071] Figure 15 The detection cloud map 1 shows the defect location identification using 3dmax based on the defect comprehensive identification index of Model 2 of a method for detecting the compactness of prestressed duct grouting provided in one embodiment.

[0072] Figure 16 The detection cloud map 1 shows the defect location identification based on the 3dmax index of a model No. 3 of a method for detecting the compactness of prestressed duct grouting provided in one embodiment. Detailed Implementation

[0073] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0074] In one embodiment, a method for detecting the density of grout in prestressed ducts is provided. The method includes: S1, the grouting material is concrete, and an acoustic sensor is arranged on the surface of the prestressed duct to be detected.

[0075] S2, such as Figure 1 As shown, a hammer is applied to one end of the steel strand in the prestressed duct to be tested, generating an elastic wave. The oscilloscope and acoustic wave sensor are then activated, and the acoustic wave sensor moves along the direction of sound wave propagation on the surface of the prestressed duct.

[0076] S3. The acoustic sensor collects acoustic signals during the movement and transmits the acoustic signals to the oscilloscope. The PC analyzes the signals to obtain the first-to-last time of the acoustic signals.

[0077] S4. In two scenarios—with and without defects in the grouting inside the prestressed duct—the time extension of the first-arrival time of two acoustic signals from the acoustic sensor differs. This time extension is used to determine whether defects exist in the grouting inside the prestressed duct. A comprehensive defect identification index is calculated based on the first-arrival time, providing a quantitative evaluation of the grouting density inside the prestressed duct.

[0078] The specific characteristic parameters in step S4 are: first-to-second wave time. According to Fermat's principle, light travels from one point to another in any medium along the path with the shortest travel time. This is also known as the principle of minimum time. The same applies to wave propagation. During the propagation of a wave carrier, if the medium changes, the direction of wave propagation will also change, i.e., wave refraction will occur. The angle of refraction changes according to the law of refraction, also known as Snell's law.

[0079] like Figure 2 As shown, let the speed of sound propagation in medium 1 be v1, and the speed of sound propagation in medium 2 be v2, then:

[0080]

[0081] Where i is the angle between the direction of sound wave propagation in the steel strand and the vertical direction, and r is the angle between the direction of sound wave propagation in the concrete and the vertical direction.

[0082] like Figure 3 As shown, the sound wave propagates from the steel strand, passes through the concrete, and reaches the sound wave receiving point. The sound wave undergoes refraction at the interface between the steel strand and the concrete. The refraction angles on both sides during this process can be calculated based on the sound wave velocity in the media on either side of the interface.

[0083] If there is a defect in the concrete, preventing sound waves from propagating, such as... Figure 4 As shown, this will affect the wave's propagation path and propagation time.

[0084] For the same defect, different locations of the acoustic sensor will cause different changes in the transmission path. The following section will explain the location of the acoustic sensor in detail, dividing it into three types.

[0085] When the acoustic sensor is in position 1, such as Figure 5 As shown, the characteristic of this type of defect is that the side of the defect blocks the propagation of the wave in that direction, causing the wave to diffract, which causes the acoustic sensor to receive the signal, resulting in a delay in signal reception.

[0086] The sound wave propagation time is calculated in two parts: the first part is the propagation of the sound wave within the steel strand, with a time of t1; the second part is the propagation of the sound wave within the concrete, with a time of t2. Let x be the horizontal distance between the location of the sound wave sensor and the sound wave emission point, a be the thickness of the concrete outside the prestressed duct, b and d represent the thickness of the concrete layers inside and outside the duct, respectively, c be the horizontal distance the stress wave travels within the prestressed duct concrete, and V be the distance the stress wave travels. 钢 V 混 These represent the propagation velocities of the shear wave in the steel strand and concrete, respectively, with β being the angle between the propagation direction of the stress wave in the concrete and the vertical direction. When no defects are present:

[0087] t1=(xa) / V 钢

[0088] t2=a / (sinβ×V 混 )

[0089] When a defect of the type shown in the figure is arranged, t1 remains unchanged, but t2 will be prolonged due to diffraction of the sound wave, resulting in an extended wave propagation time. Let this time be t2', then:

[0090]

[0091] Therefore, the time delay is:

[0092]

[0093] Where a is the thickness of the concrete outside the prestressed duct, β is the angle between the direction of stress wave propagation in the concrete and the vertical direction, b and d represent the thickness of the concrete layers inside and outside the duct, respectively, and c is the horizontal distance of stress wave propagation in the concrete inside the prestressed duct.

[0094] When the acoustic sensor is located at position 2, the characteristic of this type of defect is that the long side of the defect blocks the propagation of the wave in that direction, causing the wave to diffract, which causes the acoustic sensor to receive the signal, resulting in a delay in signal reception.

[0095] like Figure 6As shown, path 1 represents the wave refracting from the steel strand into the concrete at the beginning of the defect, and then diffracting to reach the acoustic sensor. Path 2 represents the wave refracting from the steel strand into the concrete at the end of the defect, and then diffracting to reach the acoustic sensor. The two paths correspond to different sound wave propagation times. The shorter of the two times is taken as the sound wave propagation time when the defect is present. By comparing this time with the time when the defect is absent, the time delay value can be obtained.

[0096] When there are no defects, let the sound wave propagation time in the steel strand be t1, the propagation time in the concrete be t2, e be the distance from the sound wave refraction point to the starting position when there are no defects, and f be the distance from the sound wave refraction point to the ending position of the defect. Then:

[0097] t1=(xa) / V 钢

[0098] t2=a / (sinβ×V 混 )

[0099] When the sound wave propagates along path 1, the propagation time is

[0100] t1'=(xae) / V 钢

[0101] t2'={b+[(a+e) 2 +d 2 ] 1 / 2} / V 混

[0102] When the sound wave propagates along path 2, the propagation time is

[0103] t1”=(x-a+f) / V 钢

[0104] t2”={b+[(fa) 2 +d 2 ] 1 / 2} / V 混

[0105]

[0106]

[0107] Finally, the obtained data are compared, and the lower value of △t1 and △t2 is taken as the time extension value.

[0108] When the acoustic sensor is located at position 3, there is a low-probability special case, such as... Figure 6 As shown, if the horizontal distance between the acoustic sensor and the acoustic emission point is greater than the horizontal distance between the end of the defect and the acoustic emission point, and the defect can still be detected, then:

[0109] t1'=(x-a+f) / V 钢

[0110] t2'={[(b+d) 2 +(fa) 2 ] 1 / 2} / V 混

[0111] At this time, the time extension Δt is

[0112]

[0113] like Figure 8 As shown, two uncovered test models measuring 0.8m × 0.45m × 0.12m and one test template measuring 2m × 0.12m × 0.12m were designed, with a template thickness of 0.01m.

[0114] like Figure 9 The diagram shows the location of defects in the constructed concrete model. By arranging different defect locations and diameters, the feasibility of the parallel seismic method for detecting grouting defects inside boreholes is verified.

[0115] like Figures 10-12 As shown, the first-to-last time, first-to-last amplitude, and peak-to-peak value of the detected acoustic signal are displayed. It can be seen that there is a significant decrease in amplitude at the defect location for the first-to-last amplitude and peak-to-peak value, and the larger the aperture, the greater the amplitude reduction. Due to the large difference between low and high amplitude areas in the actual testing process, the effect is not obvious. By magnifying the analysis diagram of the first-to-last amplitude and peak-to-peak value at the defect location, it can be seen that different apertures correspond to different amplitude changes.

[0116] like Figure 13 The figure shows the various indicators of the acoustic signal detected by the long model. It can be seen that when the model length is changed to 200cm, the three indicators can still detect the presence of the defect at the defect location. Compared with the model length of 80cm, the waveform values ​​at the defect location show the same trend, indicating that the increase in model length has no effect on the location of the defect.

[0117] By introducing a comprehensive defect analysis index, the three indicators are mathematically processed and then combined to further analyze the detailed location of defects. This ultimately ensures that the simulated defect location is essentially consistent with the actual defect location. Furthermore, the concepts of delayed detection distance and extended detection distance are introduced, further increasing the accuracy of defect analysis. This provides a reliable derivation of which locations of the acoustic sensor measurement points will detect defects during experiments.

[0118] Because there are many numerical indicators in the study, and the simulation results vary for different indicators, in order to more accurately study and identify the specific location of defects, mathematical processing is performed on the various numerical indicators near the defect. Here, the defect comprehensive identification index k is proposed as the research object for analysis:

[0119] This introduces the concept of delayed detection distance. Because sound waves refract when encountering different materials during propagation, when sound waves detect defects, the sound sensor will not detect the defect at the exact same location. This results in a discrepancy between the location of the defect detected by the sound sensor and the actual defect. Figure 10 As shown, the actual position of the acoustic sensor that detects the defect is slightly behind the defect, resulting in a detection delay. Calculations based on the material and model dimensions, using Snell's law, show that the angle between the sound wave propagation direction in the steel strand and the interface normal is approximately 88°, meaning it propagates almost horizontally. The angle between the sound wave propagation direction in the concrete and the horizontal direction of the interface is approximately 47.2°, corresponding to a tangent of 1.08. Therefore, the initial position of the defect detected by the acoustic sensor is approximately 2.16 cm behind the defect, which corresponds to a detection delay of 2.16 cm in the figure.

[0120] In addition to the concept of delayed detection distance, there is also the concept of extended detection distance. That is, the acoustic wave sensor above the location of the defect can still detect the presence of the defect. The principle is the same as that of delayed detection distance. The calculated extended detection distance is about 4cm. However, the path of the acoustic wave signal received by the acoustic wave sensor 4cm behind the end of the defect is analyzed. Since the refraction point is located at the end of the defect, the acoustic wave signal will be refracted from the end of the defect after propagating forward a short distance in the steel pipe. Since the sound wave propagates quickly in the steel pipe and the path of the sound wave signal is basically unaffected, it is believed that the acoustic wave sensor that should detect the defect is between 4cm behind the front end of the defect and 2cm behind the end of the defect.

[0121] When setting the analysis index for the first arrival time parameter, let T0(x) be the first arrival time received by the acoustic sensor at a horizontal distance x cm from the impact point when there is no defect, T(x) be the first arrival time received by the acoustic sensor at a distance x cm from the impact point for any model, a be the width of the concrete in the duct, b be the width of the concrete in the duct, the number of acoustic sensors be n, and the corresponding first arrival defect identification index be k1(x). Then, for this size model:

[0122] k1(x)=1-[T(x)-T0(x)-∑(T(x)-T0(x)) / (10n)] / (T(x)-T0(x))

[0123] Here, k1(x) can be used as the first arrival time identification index for the horizontal distance x cm from the impact point, and 0≤k1(x)≤1. When T(x)-T0(x)=0, that is, when there is no first arrival time extension, k1(x)=1 by default.

[0124] When setting the peak-to-peak value parameter for analysis, the peak-to-peak value received by the acoustic sensors at the locations corresponding to the defect sides appears higher than normal. This is because during the simulation, acoustic wave reflection at the defect causes stress concentration, resulting in a higher peak-to-peak value received by the acoustic sensors near the defect sides. Then, the peak-to-peak value decreases sharply with increasing horizontal distance from the acoustic sensors. This results in a peak-to-peak value at a certain location in the defect segment that is the same size as the corresponding location in the normal model. To avoid this, when studying the peak-to-peak value identification index, we adjust the peak-to-peak value: the peak-to-peak value at the location of the sudden increase is adjusted to the same location as the intact model. Other abnormal peak-to-peak values ​​within the range from the sudden increase location to the normal peak-to-peak value location are adjusted using interpolation. Other locations remain unchanged. Let H0(x) be the peak-to-peak value received by the acoustic sensor at a horizontal distance x cm from the impact point when there is no defect, H(x) be the peak-to-peak value received by the acoustic sensor at a distance x cm from the impact point in any model, and the peak-to-peak value identification index be k2(x). Then:

[0125] k2(x)=H(x) / H0(x)(0≤k2(x)≤1)

[0126] Here, k2(x) can be used as the peak-to-peak value recognition index at a horizontal distance of x cm from the point of impact.

[0127] When setting the analysis index for the first arrival wave peak parameter, if the first arrival wave peak at a certain point suddenly increases significantly beyond the normal model's first arrival wave peak, the outlier value will be processed. The data adjustment method is the same as for the peak value part, and the adjusted value is processed in the same way as the first arrival wave time. Let U0(x) be the first arrival wave peak received by the acoustic sensor at a horizontal distance x cm from the impact point when there is no defect, and U(x) be the peak value of the acoustic sensor received by the acoustic sensor at a distance x cm from the impact point for any model. Let the peak value recognition index be k3(x). Then, for this type of size model:

[0128] k3(x)=U(x) / U0(x)(0≤k3(x)≤1)

[0129] When the calculated values ​​of k1(x), k2(x), and k3(x) are greater than 1, their values ​​are taken as 1. Therefore, for the defect comprehensive identification index k... x The value can be:

[0130] k(x)=(k1(x)+k2(x)+k3(x)) / 3(0≤k(x)≤1)

[0131] When the value of the defect comprehensive identification index k(x) is closer to 1, it indicates that the grouting density is better and there are no defects. When it is closer to 0, it indicates that there are more likely defects.

[0132] For the first-to-last wave amplitude and peak-to-peak value data, because there will still be a small error in controlling the striking force with a small hammer, we normalized the first-to-last wave amplitude and peak-to-peak value measured at 3cm according to the control group. The threshold for k(x) is set to 0.6; k(x) greater than 0.6 indicates no defect, and k(x) less than 0.6 indicates a defect.

[0133] like Figure 14 , 15 Figures 1 and 16 show the defect identification cloud maps based on the comprehensive defect identification index for models 1, 2, and 3, respectively. The obtained comprehensive defect identification index data was used to draw cloud maps using the simplified material editor function in 3ds Max software. This results in a schematic diagram of the defect detection cloud map and its corresponding defect location arrangement. Dark gray represents the absence of defects, and white represents the presence of defects. The rectangular areas represent the specific locations of the defects. Comparing the 3ds Max defect detection schematic cloud map with the original defect location shows that the defect locations largely match the actual detected defect locations with minimal error. Therefore, the method of identifying defect locations using the parallel seismic method combined with the comprehensive defect identification index is feasible.

[0134] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A method for detecting the grout density of prestressed ducts, characterized in that, include: An acoustic wave sensor is placed on the outer surface of the prestressed duct; the acoustic wave sensor is activated at the same time as the sound wave is generated by striking one end of the steel strand inside the prestressed duct. The acoustic wave sensor collects the first and last waves of the sound wave signal during the movement. Calculate the propagation time of sound waves within the steel strand when there are no defects in the grouting of the prestressed ducts. t 1. The time it takes for sound waves to propagate within the grouting material t 2. The arrival time of the sound wave signal is the time it takes for the sound wave to propagate within the steel strand. t 1. The time it takes for sound waves to propagate within the grouting material t sum of 2; When defects are found in the grouting of the prestressed ducts to be inspected, the time it takes for sound waves to propagate within the steel strands is... The time it takes for sound waves to travel within the grouting material is The time extension of the first-to-last time of the acoustic signal is calculated to determine whether there are defects in the grouting inside the prestressed duct: when the time extension is equal to 0, there are no defects in the grouting inside the prestressed duct; when the time extension is greater than 0, there are defects in the grouting inside the prestressed duct. Calculate the first-to-first-wave time identification index based on the first-to-first-wave time. ( x Peak-to-peak value recognition index ( x Stress wave peak-to-peak value identification index ( x Then calculate the comprehensive defect identification index. k ( x The density of grouting inside the prestressed ducts is evaluated. The first-to-first-wave time identification index is calculated based on the first-to-first-wave time. ( x Peak-to-peak value recognition index ( x Stress wave peak-to-peak value identification index ( x Then calculate the comprehensive defect identification index. k ( x The evaluation of the grout density inside the prestressed ducts includes: First wave time recognition index ( x ): ( x )=1-[ / (10 n )] / ； in, The horizontal distance between the position of the acoustic sensor and the acoustic wave emission point. The horizontal distance from the point of impact when there is no defect The first arrival time of the acoustic wave received by the acoustic sensor at a distance of cm. For any model, the distance from the tapping point The first arrival time of the acoustic wave received by the acoustic sensor at a distance of cm. The width of the grouting material inside the duct. b The width of the grouting material inside the duct, and the number of acoustic sensors are... n ; Peak-to-peak recognition index ( x ): ( x )= H ( x ) / H 0 ( x )， ( x ) 1； in, The horizontal distance between the position of the acoustic sensor and the acoustic wave emission point. H 0 ( x () represents the horizontal distance from the point of impact when there are no defects. The peak value of the wave received by the acoustic sensor at a distance of cm. H ( x () represents the distance of any model from the tapping point. The peak value of the wave received by the acoustic sensor at a distance of cm; Stress wave peak-to-peak value identification index : ( x )= U ( x ) / U 0 ( x )， ( x ) 1； in, The horizontal distance between the position of the acoustic sensor and the acoustic wave emission point. U 0 ( x () represents the horizontal distance from the point of impact when there are no defects. The first arrival wave peak received by the acoustic sensor at a distance of cm. U ( x () represents the distance of any model from the tapping point. The peak value of the wave received by the acoustic sensor at a distance of cm; Defect Comprehensive Identification Index k ( x ): k ( x )= ，0 k ( x ) 1； in, The horizontal distance between the position of the acoustic sensor and the acoustic wave emission point. The first wave time identification index, The peak-to-peak value identification index. The peak-to-peak value identification index; When the comprehensive defect identification index k ( x The closer the value is to 1, the better the grout density and the absence of grouting defects; the closer it is to 0, the worse the grout density and the more likely there are grouting defects.

2. The method for detecting the grout density of prestressed ducts as described in claim 1, characterized in that, The acoustic sensor moves along the direction of acoustic wave propagation on the surface of the prestressed duct.

3. The method for detecting the grout density of prestressed ducts as described in claim 1, characterized in that, The time it takes for a sound wave to travel inside a steel strand is t 1. The time it takes for sound waves to propagate within the grouting material is... t 2; If there are no defects in the grouting inside the prestressed ducts, then: ； ； in, The horizontal distance between the position of the acoustic sensor and the acoustic wave emission point. Let be the propagation speed of the shear wave in the steel strand. The propagation speed of the shear wave in the grouting material. a The thickness of the grouting material outside the prestressed duct. It is the angle between the direction of stress wave propagation in the grouting material and the vertical direction.

4. The method for detecting the grout density of prestressed ducts as described in claim 3, characterized in that, The method of determining whether there are defects in the grouting inside the prestressed duct by calculating the time delay of the first-to-last wave of the acoustic signal includes: if there are defects in the grouting inside the prestressed duct, when the side of the defect blocks the propagation of the acoustic wave, t 1. No change. t 2. Due to diffraction of sound waves, the wave propagation time is prolonged, let the prolonged time be... : ； in, The thickness of the grouting material outside the prestressed duct. b The thickness of the grouting material inside the duct. c The horizontal distance that the stress wave travels through the grouting material within the prestressed duct is represented. d The thickness of the grouting material outside the duct. Let be the angle between the direction of stress wave propagation in the grouting material and the vertical direction. The propagation speed of the shear wave in the grouting material; The time delay is: ； in, The thickness of the grouting material outside the prestressed duct. b The thickness of the grouting material layer inside the duct. c The horizontal distance that the stress wave travels through the grouting material within the prestressed duct is represented. d The thickness of the grouting material layer outside the duct. Let be the angle between the direction of stress wave propagation in the grouting material and the vertical direction. The propagation speed of the shear wave in the grouting material; When the long side of the defect blocks the propagation of the wave in that direction: if the wave is refracted from the steel strand to the grouting material at the origin of the defect and then diffracts to reach the acoustic sensor, then: ； ； If the wave refracts from the steel strand to the grouting material at the end of the defect, and then diffracts to reach the acoustic sensor, then: ； ； The time delay amounts in the two cases are as follows: △ t 1= ； △ t 2= ； in, The thickness of the grouting material outside the prestressed duct. b The thickness of the grouting material inside the duct. c The horizontal distance that the stress wave travels through the grouting material within the prestressed duct is represented. d The thickness of the grouting material layer outside the duct. The horizontal distance that the stress wave travels through the grouting material within the prestressed duct is represented. e This represents the distance from the sound wave refraction point to the starting position when no defects are present. Let be the angle between the direction of stress wave propagation in the grouting material and the vertical direction. The propagation speed of the shear wave in the grouting material. denoted as the propagation speed of the shear wave in the steel strand.

5. The method for detecting the grout density of prestressed ducts as described in claim 4, characterized in that, Take △ t 1 and △ t The lower of the values ​​of 2 represents the time delay when the longer side of the defect prevents the wave from propagating in that direction.

6. The method for detecting the grout density of prestressed ducts as described in claim 3, characterized in that, If the horizontal distance between the acoustic sensor and the acoustic emission point is greater than the horizontal distance between the end of the defect and the acoustic emission point, and the defect can still be detected: ； ； The time delay is: ； in, The thickness of the grouting material outside the prestressed duct. Let be the angle between the direction of stress wave propagation in the grouting material and the vertical direction. The horizontal distance that the stress wave travels through the grouting material within the prestressed duct is represented. The propagation speed of the shear wave in the grouting material. denoted as the propagation speed of the shear wave in the steel strand.

7. The method for detecting the grout density of prestressed ducts as described in claim 1, characterized in that, First wave time recognition index The range is 0 1; when That is, when there is no first arrival time extension, the default is... Peak-to-peak value recognition index The range is 0 1; Peak-to-peak value recognition index The range is 0 1.

8. The method for detecting the grout density of prestressed ducts as described in claim 7, characterized in that, First wave time recognition index Peak-to-peak recognition index Peak-to-peak recognition index If the calculated value is greater than 1, then its value is counted as 1.

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