A method for monitoring the vibration characteristics of a cavity or crack disease of an engineering structure

Abstract

The present application belongs to the technical field of cavity and crack disease monitoring of engineering structure, and particularly relates to a kind of cavity and crack disease targeted vibration characteristic monitoring method of engineering structure, which adopts double-targeting technical route, and through DAS vibration demodulation and BOTDA strain / stress and temperature demodulation, the monitoring of the whole engineering structure is transferred to the monitoring of the implanted armored composite optical fiber tendon in the engineering structure, which not only solves the problem of mass data acquisition and analysis, but also realizes the close consolidation and coordination of the three from the implantation method, so that the monitoring data are highly coupled, the internal condition of the engineering structure is truly deeply perceived, the shortcomings of the prior art are overcome, the existing optical fiber sensing unit cannot be deeply embedded in the structure, the coupling of the collected data is poor, the deformation is not coordinated when pasting, embedding and shallow burying in the structure, the data is greatly deviated, the detection rate is low, the optical fiber sensing unit is easily damaged, the long-term durability is poor, there is no integrated active excitation source, and the passive source signal is weak, so the signal cannot be monitored.

Description

Technical Field

[0001] This invention relates to the technology for monitoring voids and cracks in engineering structures, specifically a method for monitoring the targeted vibration characteristics of voids and cracks in engineering structures. Background Technology

[0002] In the field of modern engineering construction and maintenance, the presence of defects such as voids and gaps within engineering structures seriously threatens the safety and durability of buildings, bridges, tunnels, and other facilities. However, existing methods for monitoring voids and cracks in engineering structures monitor the entire structural surface, resulting in massive and complex data collection, numerous interference factors, a large amount of useless data, and useful signals easily drowned out by noise. The deployment method of sensing units is extremely important, determining the data coupling. Existing methods mostly involve surface bonding, embedding, or shallow burial, and there is still no method that can be durablely and consistently implanted into the structure over a long period. The monitored data is superficial, unable to reveal the strong logical correlation between internal structural changes and defects, and cannot provide long-term trend data, resulting in a low detection rate. Summary of the Invention

[0003] In view of this, the purpose of this invention is to provide a method for targeted vibration characteristic monitoring of voids and cracks in engineering structures, which solves the problems of existing fiber optic sensing units being unable to penetrate deep into the structure, poor data coupling, inconsistent deformation, large data offset, low detection rate, easy damage, poor long-term durability, lack of integrated active excitation source, and weak passive source signal that cannot be detected.

[0004] To solve the above problems, the technical solution adopted by the present invention is as follows:

[0005] A method for targeted vibration characteristic monitoring of voids and cracks in engineering structures, the key of which includes the following steps:

[0006] S1. Drill holes in the surface of the engineering structure, then insert the armored composite optical fiber reinforcement into the holes, apply a preset stress, and grout with cement slurry and / or resin adhesive to make the armored composite optical fiber reinforcement tightly bonded to the engineering structure.

[0007] S2: An integrated micro vibration source is provided at the end of the armored composite optical fiber tendon to provide an adjustable active excitation source;

[0008] S3: Connect the optical fiber in the armored composite optical fiber reinforcement to the demodulator, start the vibration of the integrated micro vibration source, and synchronously target and upload data to the terminal intelligent platform through the demodulator. In the terminal intelligent platform, according to the actual monitoring project, an intelligent data analysis and early warning system, as well as a multi-source database of basic vibration, a database of targeted defect characteristics, and a database of background noise are pre-established.

[0009] S4: The intelligent data analysis and early warning system compares and analyzes the data uploaded in step S3 with the multi-source database of basic vibration, the database of targeted defect characteristics, and the database of background noise, and outputs the status judgment, trend trend and early warning results.

[0010] Optionally, the engineering structure includes any one of slope, roadbed, beam, large-volume concrete and pile foundation.

[0011] Optionally, the holes drilled on the surface of the engineering structure are spatial holes.

[0012] Optionally, the armored composite optical fiber reinforcement includes optical fiber and reinforcement, wherein the reinforcement is one or more combinations of composite steel strand, steel rod, structural steel, and fiber material.

[0013] Optionally, the demodulator includes a strain / stress, temperature fiber optic demodulator and a DAS vibration demodulator.

[0014] Optionally, the DAS data collected by the DAS vibration demodulator includes the frequency, time, location, and intensity of the vibration event; voids and cracks in the engineering structure are manifested as a decrease in stiffness / density, causing strong reflection and scattering of the vibration frequency of the armored composite optical fiber tendons within the influence range of the voids / cracks, which appear as a "V" shape, hyperbola, or distorted curve on the DAS image, accompanied by signal energy attenuation.

[0015] Optionally, the intelligent data analysis and early warning system is an adaptive learning data analysis system trained with multi-source data, used to realize the functions of state assessment, trend analysis and early warning of engineering structures.

[0016] Optionally, the initial state is calibrated according to the actual monitoring project. By establishing an engineering structure simulation calibration specimen, the engineering structure simulation calibration specimen is basically consistent with the actual working conditions and geological conditions, without voids or cracks. The armored composite fiber optic tendons are implanted into the simulation calibration specimen, and the multi-source data of foundation vibration under the preset stress is calibrated to form the multi-source database of foundation vibration.

[0017] Based on the actual monitoring project, by establishing engineering structure simulation comparison specimens, artificially setting voids and cracks as targeted defect features, collecting and extracting the vibration features of the targeted defects of the armored composite optical fiber tendons, collecting data, and establishing the targeted defect feature database.

[0018] Based on the actual monitoring project, noise data generated by passive excitation sources in the on-site environment are collected. The passive excitation sources include natural noise or other vibrations, such as vibrations caused by strong winds, rain, water flow, and vehicles. The corresponding data are collected to establish the background noise database.

[0019] Optionally, the demodulator employs the Brillouin scattering principle, spectrum analysis, dynamic strain monitoring, and coherent Rayleigh scattering principle to acquire and transmit multi-source data to the terminal intelligent platform from both spatial and temporal dimensions.

[0020] Alternatively, according to:

[0021]

[0022] The natural frequency f1 of the armored composite optical fiber force is determined, and the natural frequency f1 and its multiple higher-order frequencies are used as initial target frequencies to construct the foundation vibration multi-source database, the target defect feature database, and the background noise database; where: L is the length of the armored composite optical fiber force bar, T is the tension on a single force bar after applying a preset stress, and μ is the mass per unit length.

[0023] Compared with the prior art, the present invention has the following beneficial effects:

[0024] 1. Employing a dual-targeting technology approach, combining DAS vibration demodulation and BOTDA strain / stress and temperature demodulation, the monitoring of the overall engineering structure is shifted to the targeted monitoring of the armored composite fiber optic reinforcement implanted inside the structure. This solves the problem of massive data acquisition and analysis, and achieves tight consolidation and coordination among the three technologies through the implantation method, resulting in highly coupled monitoring data and a truly in-depth understanding of the internal condition of the engineering structure. Simultaneously, the other target focuses on voids and cracks, which pose the greatest threat to the structure and are most prone to occur. Through the calibration of simulated specimens, vibration characterization is extracted, significantly reducing and simplifying the difficulty and complexity of the algorithm model, ensuring an effective detection rate and avoiding the drawbacks of missed detections.

[0025] 2. By targeting and monitoring voids and cracks, the monitoring range and the characteristics of the measured data are significantly reduced, which reduces the difficulty of hardware and algorithms. It can achieve no blind spots. One or more optical fibers can be distributed to cover the entire engineering structure, enabling 24 / 7 unattended automated monitoring of voids and cracks.

[0026] 3. By using an integrated micro vibration source to provide an active excitation source, the problem of insufficient vibration frequency and amplitude (intensity) of existing cavities and cracks for single-sensor detection can still be solved. Data can still be collected for analysis and comparison. The active source excitation compensates for the defects of weak and undetectable passive source signals, enabling refined detection and ensuring effective detection rate.

[0027] 4. Applying a preset stress to the armored composite fiber optic tendons is equivalent to tightening the armored composite fiber optic tendons. Then, by using the natural frequency formula, the initial target frequency can be quickly located, improving the efficiency of the early database construction and the efficiency of later defect detection. Attached Figure Description

[0028] Figure 1 A schematic diagram showing the drilling direction on the surface of an engineering structure.

[0029] Figure 2 A schematic diagram of an actual situation where holes are drilled into the surface of an engineering structure.

[0030] Figure 3 This is a schematic diagram of the structure of the armored composite optical fiber reinforcement.

[0031] Figure 4 A schematic diagram of a structure with an integrated micro vibration source for the armored composite optical fiber reinforcement.

[0032] Figure 5 This is a schematic diagram of data under ambient noise conditions (passive source).

[0033] Figure 6 This is a schematic diagram of data from an integrated micro vibration source active excitation source.

[0034] Figure 7 The time-domain and frequency-domain curves of the actual DAS monitoring data;

[0035] Figure 8 Vibration early warning analysis curve based on actual DAS monitoring data;

[0036] Figure 1 The components are: 1. Armored composite optical fiber reinforcement; 2. Integrated miniature vibration source; 3. Connecting optical fiber; 4. Demodulator. Detailed Implementation

[0037] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0038] This embodiment provides a targeted vibration characteristic monitoring method for voids and cracks in engineering structures, which can be applied to slopes, roadbeds, beams, large-volume concrete, or pile foundations. The method specifically includes the following steps:

[0039] S1, such as Figure 1 , Figure 2 As shown, holes are drilled on the surface of the engineering structure; these are typically spatial holes, and then... Figure 3 The armored composite fiber optic tendon 1 shown is implanted into the hole, a preset stress is applied, and the armored composite fiber optic tendon is tightly bonded to the engineering structure by grouting with cement slurry and / or resin adhesive.

[0040] S2: An integrated micro vibration source 2 is set at the end of the armored composite optical fiber tendon. In the case of signal loss or relatively weak passive vibration source, an adjustable active excitation source is provided to facilitate monitoring of vibration signal.

[0041] S3: Will Figure 4 The optical fiber 3 inside the armored composite optical fiber rib 1 shown is connected to the demodulator 4. The integrated micro vibration source 2 is started to vibrate. The demodulator 4 synchronously collects and uploads data to the terminal intelligent platform. In the terminal intelligent platform, according to the actual monitoring project, an intelligent data analysis and early warning system, as well as a multi-source database of basic vibration, a database of targeted defect characteristics, and a database of background noise are pre-established.

[0042] S4: The intelligent data analysis and early warning system compares and analyzes the data uploaded in step S3 with the multi-source database of foundation vibration, the database of targeted defect features, and the database of background noise, and outputs the state judgment, trend trend and early warning results. The intelligent data analysis and early warning system here is an adaptive learning data analysis system trained on multi-source data, which is used to realize the state assessment, trend analysis and early warning functions of engineering structures.

[0043] By pre-setting stress to enhance the multi-order natural frequencies and strain transfer efficiency of the armored composite fiber optic reinforcement, the sensitivity of the DAS to vibrations in specific frequency bands (especially high frequencies) is improved. Then, grouting with cement grout or resin-based adhesives ensures a tight bond between the armored composite fiber optic reinforcement and the engineering structure. After consolidation, within the demodulator's accuracy monitoring range, this portion of the engineering structure and the armored composite fiber optic reinforcement can be viewed as a new integrated whole. The vibration characterization of the armored composite fiber optic reinforcement is directly influenced by it, thus transferring vibration / strain monitoring from the engineering structure to the armored composite fiber optic reinforcement. In the targeted monitoring of vibration / strain, the armored composite fiber optic reinforcement, which includes both optical fiber and reinforcement, needs to be deformed in a coordinated manner with the optical fiber, reinforcement, and engineering structure. Under constant excitation energy, the stiffness of the reinforcement is increased by a preset tension, which in turn strengthens the vibration frequency and reduces the loss during vibration propagation. When voids or cracks appear within a certain range at the junction of the reinforcement and the embedded structure, the stiffness of the structure and reinforcement combination within the monitoring range decreases. The voids and cracks cause the vibration signal to be reflected and the energy to be attenuated. The demodulator will capture the abnormal vibration signal of the armored composite fiber optic reinforcement itself.

[0044] During implementation, it can be done according to:

[0045] ,

[0046] The natural frequency f1 (Hz) of the armored composite fiber force was determined, and the natural frequency f1 and its multiple higher-order frequencies were used as initial target frequencies to construct the foundation vibration multi-source database, the targeted defect feature database, and the background noise database. Wherein: higher-order frequencies: f2 = 2f1, f3 = 3f1 (theoretically integer multiples, but slightly deviating due to stiffness); L is the length of the armored composite fiber force rib, taken as 30m in this example; T is the tension (N) on a single force rib after applying a preset stress; μ is the mass per unit length, μ = 1.101 kg / m in this example. During the experiment, the calculation results shown in Table 1 were obtained by configuring different tensions.

[0047] Table 1: Natural frequencies of armored composite optical fiber under different tensions

[0048]

[0049] It can be seen that when the tension increases from 60kN to 150kN, the fundamental frequency increases by about 58% (3.89Hz → 6.15Hz).

[0050] The monitoring frequency range and accuracy of demodulators are limited. Low-frequency, low-amplitude, and low-speed vibrations are difficult to capture. Existing technologies use the structure as the monitoring target, requiring the acquisition of complex signals with significant noise and interference. Demodulators and algorithms struggle to handle the analysis of massive amounts of data. Furthermore, the sensing units are attached, embedded, or shallowly buried on the surface, resulting in poor overall integrity, low detection rates, and difficulties in trend judgment and early warning. One of the targeted aspects of this technology is that it focuses multi-source monitoring of structural vibration on the vibration characterization of the armored composite reinforcement. By using preset stress, it increases the multi-order vibration frequencies of the composite reinforcement itself, significantly reducing the operational burden on the demodulator's range and accuracy, allowing it to focus on the acquisition of targeted data.

[0051] In specific implementation, the DAS data collected by the DAS vibration demodulator includes the frequency, time, location and intensity of the vibration event; the voids and cracks in the engineering structure are manifested as a decrease in stiffness / density, causing strong reflection and scattering of the vibration frequency of the armored composite optical fiber tendons within the influence range of the voids / cracks, which appear as a "V" shape, hyperbola or distorted curve on the DAS image, accompanied by signal energy attenuation.

[0052] In addition, the demodulator uses the Brillouin scattering principle, spectrum analysis method, dynamic strain monitoring method, and coherent Rayleigh scattering principle to collect multi-source data from both spatial and temporal dimensions and transmit it to the intelligent data analysis and early warning system. The intelligent data analysis and early warning system uses a data comparison and screening model and adaptive algorithm to perform secondary processing on the demodulator data, thereby achieving targeted identification, trend determination, and early warning of voids and cracks.

[0053] Furthermore, the spectrum analysis method involves performing a fast Fourier transform on the DAS signal at each monitoring point to obtain its vibration spectrum; identifying features: above a cavity or a large cavity, the spectrum will show an abnormally high amplitude resonance peak, the frequency of which is related to the size and depth of the cavity and its spatial location.

[0054] Furthermore, the dynamic strain monitoring method directly observes the dynamic strain curve recorded by BOTDA demodulation; the identification feature is that under external loads such as rainfall or earthquakes, abnormal strain concentration will be observed around cracks and cavities.

[0055] In the early database construction phase, the initial state is calibrated according to the actual monitoring project. By establishing engineering structure simulation calibration specimens, the engineering structure simulation calibration specimens are basically consistent with the actual working conditions and geological conditions, without voids or cracks. The armored composite fiber optic tendons are implanted into the simulation calibration specimens, and the multi-source data of foundation vibration under the preset stress are calibrated to form the foundation vibration multi-source database.

[0056] Then, by establishing engineering structure simulation comparison specimens, artificially setting voids and cracks as targeted defect features, collecting and extracting the vibration features of the targeted defects of the armored composite optical fiber tendons, collecting data, and establishing the targeted defect feature database.

[0057] Meanwhile, by collecting noise data generated by passive excitation sources in the on-site environment, including natural noise or other vibrations, such as vibrations caused by strong winds, rain, water flow, and vehicles, the corresponding data are collected to establish the background noise database.

[0058] Fiber optic monitoring of strain, stress, and temperature is only a non-essential supplementary data for this project. The deterioration of voids and cracks is a complex process that develops gradually. Local or overall deformation and collapse may occur only after reaching a critical point. The causes of instability and collapse include, but are not limited to, the gradual development of voids and cracks. The absence of detected deformation does not mean that voids and cracks have not occurred in the structure, nor is it the target data of this technology. It is only used as a supplement to long-term monitoring.

[0059] By analyzing the frequency correspondence on the spectrogram based on the influence of spatial location, duration, intensity, and patterns, different modes can be effectively identified and distinguished.

[0060] Through the diagram Figure 5 , Figure 6 , Figure 7 , Figure 8 It can be seen that after removing environmental noise, focusing on the vibration signal of the armored composite reinforcement, and comparing it with the basic database and targeted defect characteristic data, can easily realize the monitoring of voids and cracks in engineering structures, and the verification effect is obvious.

[0061] In summary, this invention employs a dual-targeting technology approach, utilizing DAS vibration demodulation and BOTDA strain / stress and temperature demodulation to shift the focus from monitoring the overall engineering structure to monitoring the armored composite fiber optic reinforcement embedded within it. This solves the problem of massive data acquisition and analysis, and the implantation method ensures a tight and coordinated integration of the three components, resulting in highly coupled monitoring data and a truly in-depth understanding of the internal condition of the engineering structure. Simultaneously, the other target focuses on voids and cracks, which pose the greatest threat to the structure and are most prone to occur. Through the calibration of simulated specimens, vibration characterization is extracted, significantly reducing and simplifying the difficulty and complexity of the algorithm model, ensuring an effective detection rate and avoiding missed detections.

[0062] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

Claims

1. A method for targeted vibration characteristic monitoring of voids and cracks in engineering structures, characterized in that: Includes the following steps: S1. Drill holes in the surface of the engineering structure, then insert the armored composite optical fiber reinforcement into the holes, apply a preset stress, and grout with cement slurry and / or resin adhesive to make the armored composite optical fiber reinforcement tightly bonded to the engineering structure. S2: An integrated micro vibration source is provided at the end of the armored composite optical fiber tendon to provide an adjustable active excitation source; S3: Connect the optical fiber in the armored composite optical fiber reinforcement to the demodulator, start the vibration of the integrated micro vibration source, and synchronously target and upload data to the terminal intelligent platform through the demodulator. In the terminal intelligent platform, according to the actual monitoring project, an intelligent data analysis and early warning system, as well as a multi-source database of basic vibration, a database of targeted defect characteristics, and a database of background noise are pre-established. The basic vibration multi-source database, the targeted defect feature database, and the background noise database are constructed by determining the natural frequency f1 of the armored composite optical fiber tendon based on the applied preset stress, and using the natural frequency f1 and its multiple higher-order frequencies as the initial target frequency. S4: The intelligent data analysis and early warning system compares and analyzes the data uploaded in step S3 with the multi-source database of basic vibration, the database of targeted defect characteristics, and the database of background noise, and outputs the status judgment, trend trend and early warning results.

2. The method for targeted vibration characteristic monitoring of voids and cracks in engineering structures according to claim 1, characterized in that: The engineering structure includes any one of the following: slope, roadbed, beam, large-volume concrete, and pile foundation.

3. The method for targeted vibration characteristic monitoring of voids and cracks in engineering structures according to claim 1 or 2, characterized in that: Holes drilled into the surface of an engineering structure are called spatial holes.

4. The method for targeted vibration characteristic monitoring of voids and cracks in engineering structures according to claim 3, characterized in that: The armored composite optical fiber reinforcement includes optical fiber and reinforcement, wherein the reinforcement is one or more of the following: composite steel strand, steel rod, shaped steel, and fiber material.

5. The method for targeted vibration characteristic monitoring of voids and cracks in engineering structures according to claim 1 or 4, characterized in that: The demodulator includes a strain / stress and temperature fiber optic demodulator and a DAS vibration demodulator.

6. The method for targeted vibration characteristic monitoring of voids and cracks in engineering structures according to claim 5, characterized in that: The DAS data collected by the DAS vibration demodulator includes the frequency, time, location, and intensity of vibration events. The voids and cracks in the engineering structure are manifested as a decrease in stiffness / density, causing strong reflection and scattering of the vibration frequency of the armored composite optical fiber tendons within the influence range of the voids / cracks. On the DAS image, this appears as a "V" shape, a hyperbola, or a distorted curve, accompanied by signal energy attenuation.

7. The method for targeted vibration characteristic monitoring of voids and cracks in engineering structures according to claim 6, characterized in that: The intelligent data analysis and early warning system is an adaptive learning data analysis system trained on multi-source data, used to realize the functions of state assessment, trend analysis and early warning of engineering structures.

8. The method for targeted vibration characteristic monitoring of voids and cracks in engineering structures according to claim 6 or 7, characterized in that: The initial state is calibrated according to the actual monitoring project. By establishing an engineering structure simulation calibration specimen, the engineering structure simulation calibration specimen is basically consistent with the actual working conditions and geological conditions, without voids or cracks. The armored composite fiber optic tendons are implanted into the simulation calibration specimen, and the multi-source data of foundation vibration under the preset stress is calibrated to form the multi-source database of foundation vibration. Based on the actual monitoring project, by establishing engineering structure simulation comparison specimens, artificially setting voids and cracks as targeted defect features, collecting and extracting the vibration features of the targeted defects of the armored composite optical fiber tendons, collecting data, and establishing the targeted defect feature database. Based on the actual monitoring project, noise data generated by passive excitation sources in the on-site environment are collected. The passive excitation sources include natural noise or other vibrations, such as vibrations caused by strong winds, rain, water flow, and vehicles. The corresponding data are collected to establish the background noise database.

9. The method for targeted vibration characteristic monitoring of voids and cracks in engineering structures according to claim 8, characterized in that: The demodulator employs the Brillouin scattering principle, spectrum analysis, dynamic strain monitoring, and coherent Rayleigh scattering principle to acquire and transmit multi-source data to the terminal intelligent platform from both spatial and temporal dimensions.

10. The method for targeted vibration characteristic monitoring of voids and cracks in engineering structures according to claim 1, 2, 4, 6, 7, or 9, characterized in that, according to: The natural frequency f1 of the armored composite fiber optic tendon is determined, and the natural frequency f1 and its multiple higher-order frequencies are used as initial target frequencies to construct the foundation vibration multi-source database, the target defect feature database, and the background noise database; where: L is the length of the armored composite fiber optic tendon, T is the tension on a single tendon after applying a preset stress, and μ is the mass per unit length.

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