A prestressed structure detection device and detection method based on piezoelectric wave method

Abstract

The present invention belongs to the technical field of prestressed structure detection, and specifically relates to a prestressed structure detection device and detection method based on a piezoelectric wave method. The present invention sets corresponding stress wave drivers and stress wave sensors on the polygonal nut and pad of the prestressed structure. The stress wave driver sends stress waves, which are transmitted inside the prestressed structure. Then, the stress wave sensor receives feedback signals, thereby calculating and analyzing the prestress loss inside the prestressed structure. The detection structure and method disclosed in the present invention can quickly and accurately obtain the prestress loss inside the prestressed structure, so that the internal prestress of the prestressed structure can be kept within a reasonable range to avoid prestress failure.

Description

Technical Field

[0001] The present invention belongs to the technical field of prestressed structure detection, and in particular relates to a prestressed structure detection device and a detection method based on a piezoelectric wave method. Background Art

[0002] Prestressed concrete structures are widely used in the field of engineering construction. The principle of prestressed concrete is to artificially pre-apply a stress in the opposite direction of the component's own internal stress before the component is used, thereby improving the component's ability to resist displacement and deformation during use. Prestressed concrete structures can effectively alleviate the lack of inherent tensile strength of concrete, but because the fine-rolled threaded steel bars are generally short, they may produce large shrinkage losses during anchoring; and the fine-rolled threaded steel bars are prone to loss of vertical prestress or even failure due to improper human operation or shrinkage creep of the concrete itself and relaxation of the steel bars during tensioning; in actual applications, the cracking problem caused by insufficient vertical prestressing of prestressed concrete structures has affected its development and application.

[0003] Therefore, accurate detection of vertical prestress is of great significance to the reliability of prestressed concrete structures. If the effective vertical prestress of a prestressed concrete structure is too high, the actual value will be much greater than the theoretical value, resulting in a safety hazard to the structure; if the effective vertical prestress is too low, the vertical prestressed tendons will have excessive performance and will not be able to fully exert their effects. However, the prior art lacks a fast and accurate method for detecting vertical prestress of prestressed concrete structures. Summary of the invention

[0004] The technical problem to be solved by the present invention is to overcome the lack of a method for quickly and accurately detecting the vertical prestress of a prestressed concrete structure in the prior art, which limits the reliability of the prestressed concrete structure, thereby providing a prestressed structure detection device and detection method based on a piezoelectric wave method.

[0005] A prestressed structure detection device based on a piezoelectric wave method comprises a plurality of groups of correspondingly arranged stress wave drivers and stress wave sensors; the prestressed tendons are arranged inside a component and the ends thereof extend out, a polygonal nut is arranged at the ends of the prestressed tendons in threaded cooperation with the prestressed tendons, and a pad is fixed to the surface of the component; a stress wave driver is arranged and fixed on each surface of the polygonal nut, a plurality of stress wave sensors are fixed and arranged on the outer surface of the pad in correspondence with the stress wave sensors, and the stress wave sensors are arranged in the direction facing the surface of the polygonal nut where the stress wave driver is located.

[0006] Furthermore, it also includes a collector, which is connected to the stress wave driver and the stress wave sensor respectively, and is used to send an excitation signal to the stress wave driver and obtain a feedback signal from the stress wave sensor.

[0007] Furthermore, it also includes a signal amplifier, which is connected to the collector and the stress wave driver respectively and is used to amplify the excitation signal.

[0008] A prestressed structure detection method based on a piezoelectric wave method comprises the following steps:

[0009] Step S1: the stress wave driver sends a stress wave;

[0010] Step S2: the stress wave sensor receives the stress wave and outputs a feedback signal;

[0011] Step S3: Analyze the feedback signal to obtain the prestress loss degree of the prestressed structure.

[0012] Furthermore, the step S3 includes:

[0013] Step S3.1: performing wavelet packet energy analysis on the feedback signal to obtain an average wavelet packet energy value;

[0014] Step S3.2: Calculating the damage index according to the average wavelet packet energy value;

[0015] Step S3.3: Substitute the damage index into a preset theoretical model to obtain the prestress loss rate.

[0016] Furthermore, in step S3.1, the average wavelet packet energy value is an average value of energy values ​​obtained by performing wavelet packet energy analysis on feedback signals obtained by each group of the stress wave driver and the stress wave sensor.

[0017] Furthermore, in step S3.2, the damage index is calculated as follows:

[0018]

[0019] Among them, F DI is the damage index, and its value range is (0~1); E l is the average wavelet packet energy value when effective prestress is lost; E f is the average wavelet packet energy value when the effective prestress is in full load state.

[0020] Furthermore, in step S3.3, the theoretical model is:

[0021]

[0022] Among them, x is the damage index of the wavelet packet energy collected under different prestress; y is the loss rate of prestress; a, b, and c are unknown coefficients, and the values ​​of the coefficients need to be determined based on historical experimental data;

[0023] The calculation formula of the prestress loss rate is:

[0024]

[0025] Among them, ρ is the effective prestress loss rate, and its value range is (0~1); F max is the effective prestress at full load (kN); F i is the effective prestress after loss (kN).

[0026] Furthermore, the method further comprises the following steps:

[0027] Step S4: performing wavelet packet energy analysis on the feedback signals obtained from each group of the stress wave driver and the stress wave sensor to obtain the wavelet packet energy value of each group;

[0028] The lower threshold and the upper threshold of the wavelet packet energy value are set according to the average wavelet packet energy value;

[0029] The inclination of the nut is determined according to the lower threshold and the upper threshold.

[0030] Beneficial effect: The present invention sets corresponding stress wave drivers and stress wave sensors on the polygonal nuts and pads of the prestressed structure. The stress wave driver sends stress waves, which are transmitted inside the prestressed structure. Then, the stress wave sensor receives feedback signals, thereby calculating and analyzing the prestress loss inside the prestressed structure. The detection structure and method disclosed in the present invention can quickly and accurately obtain the prestress loss inside the prestressed structure, thereby maintaining the internal prestress of the prestressed structure within a reasonable range and avoiding prestress failure. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0032] Description of reference numerals:

[0033] Figure 1 It is a schematic diagram of the overall structure of the present invention;

[0034] Figure 2 It is a schematic diagram of the overall structure of the present invention from another angle;

[0035] Figure 3 It is a schematic diagram of signal transmission of the present invention;

[0036] Figure 4 It is a schematic diagram of the prestressed structure of the present invention.

[0037] 11. Stress wave driver; 12. Stress wave sensor; 2. Component; 3. Prestressed tendons; 4. Polygonal nuts; 5. Pads; 6. Collector; 7. Signal amplifier. DETAILED DESCRIPTION

[0038] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are described in detail below in conjunction with the accompanying drawings. In the following description, many specific details are set forth to facilitate a full understanding of the present application. However, the present application can be implemented in many other ways different from those described herein, and those skilled in the art can make similar improvements without violating the connotation of the present application, so the present application is not limited by the specific embodiments disclosed below.

[0039] Embodiment 1:

[0040] Reference Figure 1 and Figure 2 As shown, this embodiment discloses a prestressed structure detection device based on the piezoelectric wave method, including a plurality of groups of correspondingly arranged stress wave drivers 11 and stress wave sensors 12; the prestressed tendon 3 is arranged inside the component 2 and the end thereof extends out, the polygonal nut 4 is threadedly matched with the prestressed tendon 3 and is arranged at the end of the prestressed tendon 3, and the pad 5 is fixed to the surface of the component 2; a stress wave driver 11 is arranged and fixed on each surface of the polygonal nut 4, and a plurality of stress wave sensors 12 are fixedly arranged on the outer surface of the pad 5 corresponding to the stress wave sensors 12 one by one, and the stress wave sensors 12 are arranged in the direction facing the surface of the polygonal nut 4 where the stress wave driver 11 is located.

[0041] Reference Figure 3 As shown, it also includes a collector 6, which is respectively connected to the stress wave driver 11 and the stress wave sensor 12, and is used to send an excitation signal to the stress wave driver 11 and obtain a feedback signal from the stress wave sensor 12. It also includes a signal amplifier 7, which is respectively connected to the collector 6 and the stress wave driver 11, and is used to amplify the excitation signal.

[0042] Specifically, in this embodiment, the component 2 is concrete, the prestressed tendons 3 are prestressed steel bars, and the pad 5 is a metal pad. In this embodiment, the stress wave driver 11 is a piezoelectric ceramic driver, the stress wave sensor 12 is a piezoelectric ceramic sensor, and the piezoelectric ceramic driver and the piezoelectric ceramic sensor are made by welding shielding wires on the positive and negative electrodes of the piezoelectric ceramic sheet, respectively. As a preferred embodiment of this embodiment, the model of the piezoelectric ceramic sheet is PZT-5, the positive and negative electrodes are located on the same side, the size is 15×5×2mm, the negative electrode width is 5mm, the positive electrode width is 8mm, and the interval between the positive and negative electrodes is 2mm; the shielding wire is stripped of the insulating shell at both ends with a wire stripper, exposing a 1cm long wire.

[0043] Before fixing the stress wave driver 11 and the stress wave sensor 12, the polygonal nut 4 and the pad 5 are subjected to rust removal treatment. The rust removal treatment includes spraying a special rust remover on the surface of the polygonal nut 4 and the pad 5 for wiping, and then polishing the surface of the test point to keep it as flat as possible, and then cleaning it with medical alcohol. When fixing the stress wave driver 11 and the stress wave sensor 12, apply a layer of epoxy resin glue on the surface of the test point, and then apply 502 strong glue on the surface for insulation treatment. Finally, paste the prepared piezoelectric ceramic sheet on the surface and press for 3 minutes until the glue solidifies and then release it. After the stress wave driver 11 and the stress wave sensor 12 are pasted, use a multimeter to check whether there is a passage to check whether the pasting is successful.

[0044] In this embodiment, the polygonal nut 4 is a hexagonal nut, and the outer shape of the hexagonal nut is an equilateral hexagon; six stress wave drivers 11 are provided, and the six stress wave drivers 11 are respectively fixed at the centers of the six faces of the side of the hexagonal nut, and six stress wave sensors 12 are fixed on the upper side of the pad 5 close to the corresponding positions of each stress wave driver 11.

[0045] As a preferred embodiment of the present invention, the acquisition instrument 6 is preferably NIUSB-6361, and the signal amplifier 7 is preferably a high-frequency power amplifier of model number Xintianming E2022. The NIUSB-6361 acquisition instrument 6 has 16 channel ports. In the present embodiment, the acquisition program is written in combination with LabView to realize the visualization of signal acquisition; the excitation signal is a pulse signal excited by the LabView program, and the amplitude range is -10V-10V; the signal amplifier 7 amplifies the excitation signal by 30 times, applies it to the prestressed driver, and finally the prestressed sensor receives the signal. The NIUSB-6361 acquisition instrument 6 is used as a signal acquisition device, and the NIUSB-6361 acquisition instrument 6 and the laptop are connected via a USB data cable, and the detected data is saved in real time to the computer, and the computer performs calculation and analysis.

[0046] Embodiment 2:

[0047] This embodiment discloses a prestressed structure detection method based on a piezoelectric wave method, and the prestressed structure detection method based on a piezoelectric wave method provided in Application Example 1 includes the following steps:

[0048] Step S1: the stress wave driver 11 sends a stress wave;

[0049] Step S2: the stress wave sensor receives the stress wave and outputs a feedback signal;

[0050] Step S3: Analyze the feedback signal to obtain the prestress loss degree of the prestressed structure.

[0051] The step S3 comprises:

[0052] Step S3.1: performing wavelet packet energy analysis on the feedback signal to obtain an average wavelet packet energy value;

[0053] Step S3.2: Calculating the damage index according to the average wavelet packet energy value;

[0054] Step S3.3: Substitute the damage index into a preset theoretical model to obtain the prestress loss rate.

[0055] In this embodiment, the calculation method of the wavelet packet energy analysis is: the collected feedback signal is first decomposed by wavelet packets to form sub-signals of different frequency bands, and the energy of each sub-signal sub-band is calculated, and the sum is the wavelet packet energy value.

[0056] In the step S3.1, the average wavelet packet energy value is the average value of energy values ​​obtained by performing wavelet packet energy analysis on the feedback signals obtained by each group of the stress wave driver 11 and the stress wave sensor 12.

[0057] The following steps are also included:

[0058] Step S4: performing wavelet packet energy analysis on the feedback signals obtained from each group of the stress wave driver 11 and the stress wave sensor 12 to obtain the wavelet packet energy value of each group;

[0059] The lower threshold and the upper threshold of the wavelet packet energy value are set according to the average wavelet packet energy value;

[0060] The inclination of the nut is determined according to the lower threshold and the upper threshold.

[0061] In step S3.2, the damage index is calculated as follows:

[0062]

[0063] Among them, F DI is the damage index, and its value range is (0~1); E l is the average wavelet packet energy value when effective prestress is lost; E f is the average wavelet packet energy value when the effective prestress is in full load state. The damage index F of wavelet packet energy DI The damage degree of prestress can be effectively characterized, and the loss degree of effective prestress can be preliminarily determined; the prestress full load state can be set according to different detection conditions.

[0064] In this embodiment, the E f The average wavelet packet energy value when the effective prestress is in the full load state is a predicted value. In advance, six sets of stress wave drivers 11 and stress wave sensors 12 are installed in the system without prestress loss, and the average value of the corresponding wavelet packet energy values ​​is measured, which is the average wavelet packet energy value in the full load state.

[0065] In step S3.3, the theoretical model is:

[0066]

[0067] Among them, x is the damage index of the wavelet packet energy collected under different prestress; y is the loss rate of prestress; a, b, and c are undetermined coefficients, and the values ​​of the coefficients need to be determined based on historical experimental data. In this embodiment, the values ​​of the coefficients are determined based on historical experimental data, a=-92.41, b=0.07, and c=93.93;

[0068] The theoretical model can effectively fit the relationship between the damage index of the wavelet packet energy and the loss rate of the prestress. In other embodiments of the present invention, the theoretical model can be formed by fitting other expressions.

[0069] The calculation formula of the prestress loss rate is:

[0070]

[0071] Among them, ρ is the effective prestress loss rate, and its value range is (0~1); F max is the effective prestress at full load (kN); F i is the effective prestress after loss (kN). In this embodiment, Fmax is the effective prestress at full load according to the design value of the prestress.

[0072] In this embodiment, the method for constructing the theoretical model is:

[0073] Taking 600kN as the state of full prestressing, the prestress under other working conditions is regarded as the effective prestress after prestressing loss, which is divided into 7 groups of working conditions, namely 0kN, 25kN, 50kN, 100kN, 200kN, 400kN, and 600kN; three repeated tests are carried out, and before each test, the prestressed tendons 3, polygonal nuts 4 and gaskets 5 are completely replaced; the damage index of wavelet energy and the damage index of wavelet energy average value obtained by historical experiments are used to calculate the effective prestressing loss rate under different working conditions.

[0074] By setting the damage index F DI The nonlinear fitting analysis of the damage rate ρ of the prestress is carried out to obtain the fitting curves of three tests and the average of three tests:

[0075]

[0076] Where: x is the damage index of wavelet packet energy collected under different prestress; y is the loss rate of prestress;

[0077] The loss index obtained from the signal collected in the test was substituted into the fitting curve, and the relative error was within ±15%, indicating that the accuracy of the fitting result was feasible and met the needs of actual engineering. Finally, the average fitting curve of three tests was selected as the final damage indicator-the theoretical model of prestress loss rate.

[0078] In this embodiment, the following steps are also included:

[0079] Step S4: performing wavelet packet energy analysis on the feedback signals obtained from each group of the stress wave driver 11 and the stress wave sensor 12 to obtain the wavelet packet energy value of each group;

[0080] The lower threshold and the upper threshold of the wavelet packet energy value are set according to the average wavelet packet energy value;

[0081] The inclination of the polygonal nut 4 is determined according to the lower threshold and the upper threshold.

[0082] Specifically, six groups of feedback signals obtained by the stress wave driver 11 and the stress wave sensor 12 are set to perform wavelet packet energy analysis to obtain wavelet packet energy values ​​of each group, which are X1, X2, X3, X4, X5, and X6; the average wavelet packet energy value is And set the X lower limit threshold to 95% The upper threshold is 105% We can get:

[0083] Xn (n = 1, 2, 3, 4, 5, 6) is 95% When , it means that there is no inclination between the polygonal nut 4 and the backing plate 5 at this position;

[0084] Xn (n = 1, 2, 3, 4, 5, 6) > upper threshold 105% When , it means that the inclination angle of the polygonal nut 4 at this position is biased towards the backing plate 5;

[0085] Xn (n = 1, 2, 3, 4, 5, 6) < lower threshold 95% When , it indicates that the inclination angle of the polygonal nut 4 at this position is biased away from the backing plate 5;

[0086] Therefore, the inclination condition between the polygonal nut 4 and the backing plate 5 can be obtained through step S4, and leveling can be performed according to the inclination condition.

[0087] In this embodiment, corresponding stress wave drivers 11 and stress wave sensors 12 are arranged on the polygonal nut 4 and the pad 5 of the prestressed structure. The stress wave driver 11 sends stress waves, which are transmitted inside the prestressed structure. Then, the feedback signal is received by the stress wave sensor 12, so as to calculate and analyze the prestress loss inside the prestressed structure. The detection structure and method disclosed in the present invention can quickly and accurately obtain the prestress loss inside the prestressed structure, so as to keep the internal prestress of the prestressed structure within a reasonable range and avoid prestress failure.

[0088] Reference Figure 4As shown, the tension force in the prestressed structure is transmitted to the nut through the engagement of the component 2 and the prestressed tendon 3, and the nut squeezes the pad 5 and then transmits the pressure generated by the squeezing to the component 2. In this embodiment, the change of prestress will directly affect the contact pressure between the polygonal nut 4 and the pad 5, so that the actual contact area between the polygonal nut 4 and the pad 5 will change with the change of prestress. When the prestress increases, the actual contact area between the polygonal nut 4 and the pad 5 will increase accordingly, so that when the high-frequency stress wave generated by the piezoelectric ceramic driver is transmitted between the nut and the pad 5, the propagation of the stress wave is also easier as the actual contact area increases; therefore, the energy received by the piezoelectric sensor gradually increases as the actual contact area increases. As the prestress increases, the actual contact area between the polygonal nut 4 and the pad 5 increases, and the signal received by the piezoelectric sensor is also enhanced. This embodiment can detect prestress by analyzing the difference in received signals under different working conditions.

[0089] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0090] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be construed as limiting the scope of the patent application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent application shall be subject to the attached claims.

Claims

1. A prestressed structure detection device based on piezoelectric wave method, characterized in that: It comprises a plurality of groups of correspondingly arranged stress wave drivers (11) and stress wave sensors (12); a prestressed tendon (3) is arranged inside a component (2) and its end extends out, a polygonal nut (4) is threadedly matched with the prestressed tendon (3) and arranged at the end of the prestressed tendon (3), and a pad (5) is fixed to the surface of the component (2); one stress wave driver (11) is arranged and fixed on each surface of the polygonal nut (4), and a plurality of stress wave sensors (12) are fixed and arranged on the outer surface of the pad (5) corresponding to the stress wave sensors (12), and the stress wave sensors (12) are arranged in the direction facing the surface of the polygonal nut (4) where the stress wave driver (11) is located; The stress wave driver (11) is used to send stress waves, and the stress wave sensor (12) is used to receive stress waves and output feedback signals; The prestressed structure detection device is used to obtain an average wavelet packet energy value by performing wavelet packet energy analysis on the feedback signal, calculate a damage index according to the average wavelet packet energy value, substitute the damage index into a preset theoretical model, and obtain a prestress loss rate; The prestressed structure detection device is used to perform wavelet packet energy analysis based on feedback signals obtained from the stress wave driver (11) and the stress wave sensor (12) to obtain a wavelet packet energy value, set a lower threshold and an upper threshold of the wavelet packet energy value based on an average wavelet packet energy value, and judge the inclination of the nut based on the lower threshold and the upper threshold.

2. A prestressed structure detection device based on piezoelectric wave method according to claim 1, characterized in that: It also comprises a data collector (6), which is respectively connected to the stress wave driver (11) and the stress wave sensor (12) and is used to send an excitation signal to the stress wave driver (11) and obtain a feedback signal from the stress wave sensor (12).

3. A prestressed structure detection device based on piezoelectric wave method according to claim 2, characterized in that: It also comprises a signal amplifier (7), wherein the signal amplifier (7) is respectively connected to the acquisition instrument (6) and the stress wave driver (11) and is used to amplify the excitation signal.

4. A prestressed structure detection method based on piezoelectric wave method, characterized in that: The device according to any one of claims 1 to 3 comprises the following steps: Step S1: the stress wave driver (11) sends a stress wave; Step S2: the stress wave sensor (12) receives the stress wave and outputs a feedback signal; Step S3: analyzing the feedback signal to obtain the prestress loss degree of the prestressed structure; The step S3 comprises: Step S3.1: performing wavelet packet energy analysis on the feedback signal to obtain an average wavelet packet energy value; Step S3.2: Calculating the damage index according to the average wavelet packet energy value; Step S3.3: Substituting the damage index into a preset theoretical model to obtain a prestress loss rate; The following steps are also included: Step S4: performing wavelet packet energy analysis on the feedback signals obtained from each group of the stress wave driver (11) and the stress wave sensor (12) to obtain the wavelet packet energy value of each group; The lower threshold and the upper threshold of the wavelet packet energy value are set according to the average wavelet packet energy value; The inclination of the nut is determined according to the lower threshold and the upper threshold.

5. A prestressed structure detection method based on piezoelectric wave method according to claim 4, characterized in that: In the step S3.1, the average wavelet packet energy value is the average value of energy values ​​obtained by performing wavelet packet energy analysis on the feedback signals obtained by each group of the stress wave driver (11) and the stress wave sensor (12).

6. A prestressed structure detection method based on piezoelectric wave method according to claim 5, characterized in that: In step S3.2, the damage index is calculated as follows: Among them, F DI is the damage index, and its value range is (0~1); E l is the average wavelet packet energy value when effective prestress is lost; E f is the average wavelet packet energy value when the effective prestress is in full load state.

7. A prestressed structure detection method based on piezoelectric wave method according to claim 6, characterized in that: In step S3.3, the theoretical model is: Among them, x is the damage index of the wavelet packet energy collected under different prestress; y is the loss rate of prestress; a, b, and c are unknown coefficients, and the values ​​of the coefficients need to be determined based on historical experimental data; The calculation formula of the prestress loss rate is: Among them, ρ is the effective prestress loss rate, and its value range is (0~1); F max is the effective prestress at full load (kN); F i is the effective prestress after loss (kN).

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