Intelligent coating-based combined structure bridge shear key state monitoring method and system

Abstract

The application discloses a kind of based on intelligent coating's combination structure bridge shear key state monitoring method and system, method includes: S1, the crack damage information of monitoring object is acquired;S2, the crack damage information obtained is handled;S3, the crack damage information after processing is analyzed, and the structural crack damage condition is determined in combination with structural system features;S4, the crack damage condition of structure is combined with the expert experience database of specific engineering structure, and the state of monitoring object is evaluated.The application realizes the real-time quality monitoring of the combination structure bridge shear key that is difficult to monitor, effectively avoids the life reduction of combination structure bridge and security risk caused by bridge shear key damage.

Description

Technical Field

[0001] This invention belongs to the field of bridge non-destructive testing technology, specifically relating to a method and system for monitoring the shear key condition of a composite structure bridge based on intelligent coating. Background Technology

[0002] With the continuous advancement of bridge construction technology in my country, steel-concrete composite bridges have become an important component of bridge construction. Shear keys are crucial components in steel-concrete composite bridges, preventing slippage and separation between the steel and concrete structures at the interface, ensuring they function as a unified whole. However, in recent years, shear key cracking has become increasingly common, significantly impacting bridge lifespan and posing certain safety hazards.

[0003] Shear keys, located between steel and concrete structures, are difficult to detect using conventional methods. Methods such as impact echo methods cannot monitor the health status of shear keys in real time, failing to detect damage in its early stages and posing significant safety hazards. Coating sensors utilize the evolutionary relationship between crack propagation and electric potential field distribution to achieve real-time monitoring of the structure under test. However, currently, coating sensors are mostly used in the aerospace field, and a complete monitoring system and method are lacking for bridge steel structures. Summary of the Invention

[0004] To address the aforementioned technical problems in the existing technology, this invention provides a method and system for monitoring the shear key status of composite structure bridges based on intelligent coatings, which can perform real-time monitoring of shear keys in steel-concrete composite bridges.

[0005] The technical solution adopted in this invention is:

[0006] A method for monitoring the shear key condition of a composite structure bridge based on a smart coating, characterized by the following steps:

[0007] S1. Obtain crack damage information of the monitored object;

[0008] S2. Process the acquired crack damage information;

[0009] S3. Analyze the processed crack damage information and determine the structural crack damage status in combination with the characteristics of the structural system.

[0010] S4. Combine the structural crack damage status with the expert experience database of specific engineering structures to assess the status of the monitored object.

[0011] A shear key condition monitoring system for composite structure bridges based on intelligent coatings, characterized in that it includes:

[0012] The sensor module senses and collects crack damage information of the monitored object, and transmits the collected crack damage information to the intelligent signal acquisition module.

[0013] The intelligent signal acquisition module receives crack damage information from the sensor module and processes the data.

[0014] The real-time crack damage identification module receives data information processed by the signal intelligent acquisition module, and performs data processing through a calibrated crack damage identification method to determine the structural crack damage status and obtain the damage identification result.

[0015] The structural condition assessment module combines the damage identification results obtained above with the expert experience database of specific engineering structures to assess the health of the structure.

[0016] Furthermore, the sensor module includes a driving layer tightly integrated with the structural substrate, an information sensing layer, and a protective layer, wherein the protective layer, sensing layer, and driving layer are sequentially disposed on the structural substrate from top to bottom; wherein:

[0017] The driving layer is solidified into the structural matrix and the sensing layer respectively, and has good matrix-substrate attached damage characteristics. At the same time, it plays the role of isolating the structural matrix and the sensing layer. Under the action of the driving layer, the resistance of the sensing layer will change significantly and regularly, so as to synchronously reflect the crack development trend of the driving layer.

[0018] The protective layer is used to protect the driving layer and the sensing layer.

[0019] Furthermore, the specific signal processing flow of the intelligent signal acquisition module is as follows:

[0020] The system performs signal separation, filtering, amplification, A / D conversion, sampling control, and preprocessing to complete the basic functions of signal acquisition.

[0021] Furthermore, the structural crack damage condition includes the location, extent, and type of crack damage.

[0022] Furthermore, the structural condition assessment module assesses the health of the structure by analyzing its working condition, predicting its service life, evaluating the reliability of the assessment results, and proposing appropriate health maintenance strategies for existing crack damage.

[0023] Furthermore, the sensing layer should have suitable resistance characteristics.

[0024] Compared with the prior art, the beneficial effects of the present invention are reflected in:

[0025] 1. This invention has strong applicability and realizes real-time monitoring of shear keys in various types of steel-concrete composite bridges, effectively avoiding the reduction in the service life of steel-concrete composite bridges and a series of safety problems caused by shear key cracking.

[0026] 2. When crack propagation causes a change in the resistance of the sensor module, this invention utilizes a signal intelligent acquisition module to transmit the electrical signal to a real-time crack damage identification module, achieving real-time monitoring of the cracks in the monitored matrix. Furthermore, the identification results are fed into a structural condition assessment module to assess the health of the monitored matrix. Attached Figure Description

[0027] The accompanying drawings, which form part of this invention, are used to aid in understanding the invention. The content provided in the drawings and their relevant descriptions in this invention can be used to explain the invention, but do not constitute an undue limitation of the invention. In the drawings:

[0028] Figure 1 This is a flowchart illustrating the working principle of intelligent coating.

[0029] Figure 2 A schematic diagram of the application of intelligent coating for steel bar shear keys. Detailed Implementation

[0030] The present invention will now be clearly and completely described in conjunction with the accompanying drawings. Those skilled in the art will be able to implement the present invention based on these descriptions. Before describing the present invention in conjunction with the accompanying drawings, it should be particularly noted that:

[0031] The technical solutions and features provided in the various parts of this invention, including the following description, can be combined with each other without conflict.

[0032] Furthermore, the embodiments of the present invention described below are generally only some, not all, of the embodiments of the present invention. Therefore, all other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort should fall within the scope of protection of the present invention.

[0033] Regarding the terminology and units used in this invention: The term "comprising" and any variations thereof in the specification, claims, and related parts of this invention are intended to cover a non-exclusive inclusion.

[0034] Example 1

[0035] refer to Figure 1 The present invention provides a method for monitoring the shear key state of a composite structure bridge based on a smart coating, which specifically includes the following steps:

[0036] S1. Obtain crack damage information of the monitored object;

[0037] S2. Process the acquired crack damage information;

[0038] S3. Analyze the processed crack damage information and determine the structural crack damage status in combination with the characteristics of the structural system.

[0039] S4. Combine the structural crack damage status with the expert experience database of specific engineering structures to assess the status of the monitored object.

[0040] Based on engineering experience, this invention selects the most vulnerable area of ​​the shear key in a composite bridge and installs a sensor module on it. When crack propagation causes a change in the resistance of the sensor module, an intelligent signal acquisition module transmits the electrical signal to a real-time crack damage identification module, enabling real-time monitoring of cracks in the monitored matrix. The identification results are then fed into a structural condition assessment module to evaluate the health of the monitored matrix.

[0041] Specifically, such as Figure 1 , Figure 2 As shown, taking a rebar shear key as an example, according to engineering experience, the most vulnerable area for a rebar shear key is the connection point between the rebar and the steel plate.

[0042] Sensor modules are installed in vulnerable areas. The sensor modules are installed by applying a layered coating to the area adjacent to the connection point between the reinforcing bars and the steel plate using a spraying technique.

[0043] A thin wire is used to connect the sensor module and the intelligent signal acquisition module, thereby enabling the connection between the signal input end and the signal processing end.

[0044] The structural health assessment criteria can be entered into the structural condition assessment module, and a cracking threshold can be set. The cracking data is then compared with the results of the signal intelligent acquisition module and the real-time crack damage identification module. An alarm is issued when the cracking data exceeds the cracking threshold, thus realizing automatic intelligent early warning of shear key damage.

[0045] The method in this embodiment involves many algorithms well known to those skilled in the art, such as:

[0046] 1. Sensor Data Acquisition and Conversion: In step S1, sensors are used to sense and acquire crack damage information of the monitored object. This process may involve signal conversion algorithms to convert physical quantities (such as strain, displacement, etc.) into electrical or digital signals for subsequent processing.

[0047] 2. Information Processing and Filtering: In step S2, the acquired crack damage information needs to be processed. This typically includes data cleaning, filtering, and feature extraction. Filtering algorithms (such as low-pass filtering, high-pass filtering, and band-pass filtering) can be used to remove noise and interference, improving the accuracy and reliability of the data. Feature extraction algorithms are used to extract useful information from the raw data, such as crack length, width, and depth.

[0048] 3. Damage Assessment and Analysis: In step S3, the processed crack damage information needs to be analyzed, and the structural crack damage status needs to be determined in conjunction with the characteristics of the structural system. This process may involve professional knowledge in fields such as structural mechanics and fracture mechanics, as well as corresponding algorithms and formulas. For example, the stress intensity factor formula in fracture mechanics can be used to assess crack stability; the finite element method (FEM) can be used to simulate and analyze the stress distribution and crack propagation of the structure, etc.

[0049] 4. Condition Assessment and Decision-Making: In step S4, the condition of the structural crack damage is combined with an expert experience database of the specific engineering structure to assess the condition of the monitored object. This process may involve algorithms and formulas from fields such as data mining and machine learning. For example, classification algorithms can be used.

[0050] These algorithms and formulas play an important role in data processing, damage assessment, and analysis.

[0051] Example 2

[0052] refer to Figure 2 The present invention provides a shear key condition monitoring system for composite structure bridges based on intelligent coatings, comprising:

[0053] The sensor module senses and collects crack damage information of the monitored object, and transmits the collected crack damage information to the intelligent signal acquisition module.

[0054] The intelligent signal acquisition module receives crack damage information from the sensor module and processes the data.

[0055] The real-time crack damage identification module receives data information processed by the signal intelligent acquisition module, and performs data processing through a calibrated crack damage identification method to determine the structural crack damage status and obtain the damage identification result.

[0056] The structural condition assessment module combines the damage identification results obtained above with the expert experience database of specific engineering structures to assess the health of the structure.

[0057] In one embodiment, the sensor module includes a driving layer tightly integrated with the structural substrate, an information sensing layer, and a protective layer, wherein the protective layer, sensing layer, and driving layer are sequentially disposed on the structural substrate from top to bottom; wherein:

[0058] The driving layer is solidified into the structural matrix and the sensing layer, respectively, and has good matrix-associated damage characteristics. At the same time, it plays the role of isolating the structural matrix and the sensing layer. Under the action of the driving layer, the resistance of the sensing layer will change significantly and regularly, so as to synchronously reflect the crack development trend of the driving layer.

[0059] The protective layer is used to protect the driving layer and the sensing layer.

[0060] Specifically, the driving layer is composed of polymers, nano-inorganic mineral powders, and modifiers, and is cured integrally with the component substrate and sensing layer. It exhibits excellent substrate adhesion damage characteristics and simultaneously isolates the substrate from the sensing layer, ensuring that the electrical parameters of the sensing layer are not interfered with by the substrate. The sensing layer, composed of polymers, nano-conductive particles, and modifiers, exhibits a significant and regular change in resistance upon the formation and propagation of cracks under the influence of the driving layer, synchronously reflecting the crack development trend in the driving layer. The protective layer is mainly modified from nano-topcoat and heavy-duty protective paint, serving to protect both the driving layer and the sensing layer.

[0061] In one embodiment, the specific signal processing flow of the intelligent signal acquisition module is as follows:

[0062] The system performs signal separation, filtering, amplification, A / D conversion, sampling control, and preprocessing to complete the basic functions of signal acquisition.

[0063] In one embodiment, the structural crack damage condition includes the location, extent, and type of crack damage.

[0064] In one embodiment, the structural condition assessment module assesses the health of the structure by: analyzing the working state of the structure, predicting the service life of the structure, assessing the reliability of the assessment results, and proposing appropriate health maintenance strategies for existing crack damage.

[0065] In one embodiment, the sensing layer should have suitable resistance characteristics.

[0066] The foregoing has described the relevant content of the present invention. Those skilled in the art will be able to implement the present invention based on these descriptions. All other embodiments obtained by those skilled in the art based on the above description of the present invention without inventive effort should fall within the scope of protection of the present invention.

Claims

1. A method for monitoring the shear key condition of a composite structure bridge based on a smart coating, characterized in that, Specifically, the following steps are included: S1. Obtain crack damage information of the monitored object by sensing and collecting crack damage information of the monitored object through sensors; S2. Process the acquired crack damage information; S3. Analyze the processed crack damage information and determine the structural crack damage status in combination with the characteristics of the structural system. S4. Combine the structural crack damage status with the expert experience database of specific engineering structures to assess the status of the monitored object; The monitoring systems used in implementing the monitoring methods include: The sensor module senses and collects crack damage information of the monitored object, and transmits the collected crack damage information to the intelligent signal acquisition module. The intelligent signal acquisition module receives crack damage information from the sensor module and processes the data. The real-time crack damage identification module receives data information processed by the signal intelligent acquisition module, and performs data processing through a calibrated crack damage identification method to determine the structural crack damage status and obtain the damage identification result. The structural condition assessment module combines the damage identification results obtained above with the expert experience database of specific engineering structures to assess the health of the structure. The sensor module includes a driving layer tightly integrated with the structural substrate, an information sensing layer, and a protective layer, which are sequentially disposed on the structural substrate from top to bottom; wherein: The driving layer is solidified into the structural matrix and the sensing layer, respectively, and has good matrix-associated damage characteristics. At the same time, it plays the role of isolating the structural matrix and the sensing layer. Under the action of the driving layer, the resistance of the sensing layer will change significantly and regularly, so as to synchronously reflect the crack development trend of the driving layer. The protective layer is used to protect the driving layer and the sensing layer.

2. The method for monitoring the shear key state of a composite structure bridge based on intelligent coating as described in claim 1, characterized in that, The specific signal processing flow of the intelligent signal acquisition module is as follows: The system performs signal separation, filtering, amplification, A / D conversion, sampling control, and preprocessing to complete the basic functions of signal acquisition.

3. The method for monitoring the shear key state of a composite structure bridge based on intelligent coating as described in claim 1, characterized in that, The structural crack damage condition includes the location, extent, and type of crack damage.

4. The method for monitoring the shear key state of a composite structure bridge based on intelligent coating as described in claim 1, characterized in that, The structural condition assessment module assesses the health of the structure by analyzing its working condition, predicting its service life, evaluating the reliability of the assessment results, and proposing appropriate health maintenance strategies for existing crack damage.

5. The method for monitoring the shear key state of a composite structure bridge based on intelligent coating as described in claim 1, characterized in that, The sensing layer should have suitable resistivity characteristics.

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