A building material structure performance grading progressive detection system and method

Abstract

The application discloses a kind of building material structural performance grading progressive detection method and system, belong to building structure detection technical field.The method includes three progressive detection steps: first, the appearance and coating of building bare steel structure are detected, if abnormal, mark as low-risk component and carry out next-level detection;Then, the geometric deformation, crack and stress state of low-risk component are detected, if abnormal, mark as high-risk component and carry out next-level detection;Finally, destructive detection is carried out on high-risk component, to verify its key performance, if abnormal, mark as unqualified component and immediately reinforce or replace.The method also includes environmental monitoring, life prediction and other functions, and is matched with the corresponding detection system.The application realizes early risk identification and accurate evaluation of building steel structure through grading progressive detection strategy, improves detection efficiency, reduces detection cost, and provides effective protection for building structure safety.

Description

Technical Field

[0001] The present invention belongs to the technical field of building material detection, and in particular relates to a system and method for grading and progressive detection of structural performance of building materials. Background Art

[0002] In the construction industry, structural performance testing of building materials is crucial, directly impacting the safety, stability, and service life of buildings. In exceptional circumstances, such as before work resumes on unfinished buildings, comprehensive and accurate testing and evaluation of the steel structure is essential. Steel in unfinished buildings is exposed to a variety of adverse factors, including rain, dust, and corrosive gases, for extended periods. These factors can lead to corrosion, coating damage, geometric deformation, cracking, and changes in stress states, which can affect the steel's mechanical properties and service life.

[0003] Traditional methods for testing the structural performance of building materials have numerous limitations. First, they are often limited, typically focusing on only one aspect of a building material's performance, such as testing only for steel corrosion or mechanical properties, without fully assessing the overall structural performance of the building material. This single-minded approach fails to accurately reflect the comprehensive condition of building materials in their actual use, leading to potential risks being overlooked.

[0004] Secondly, traditional inspection methods lack precision. Due to limitations in inspection methods and equipment, traditional methods struggle to accurately measure subtle changes and performance parameters in building materials. For example, when testing the thickness of rust layers and coating quality on steel, traditional methods may be unable to accurately capture subtle local variations, thus affecting the assessment of the steel's degree of degradation. Furthermore, when detecting geometric deformation and cracks, traditional methods also have limited measurement accuracy, potentially leading to inaccurate assessments of structural performance.

[0005] Furthermore, traditional testing methods lack flexibility. Different building materials and testing scenarios may require different testing methods and equipment, but traditional methods often lack adaptability and are difficult to adjust to specific circumstances. For example, for complex building structures or large-scale testing projects, traditional methods can be time-consuming and labor-intensive, resulting in low efficiency and difficulty meeting the needs of rapid testing and assessment.

[0006] Furthermore, traditional testing methods also suffer from irrational resource allocation. Lacking a hierarchical risk assessment and dynamic adjustment mechanism, traditional methods often apply the same testing process and resource allocation to all test objects. This results in wasted resources on low-risk or no-risk areas, while high-risk areas may not receive adequate attention and testing. This not only increases testing costs but also hinders the timely detection and resolution of high-risk issues.

[0007] Finally, traditional detection methods lack precision in providing early warnings and response plans. Because they cannot accurately assess the risk level of building materials, traditional methods struggle to develop appropriate response measures for different risk levels. When abnormalities occur, effective early warnings and response plans may not be provided in a timely manner, increasing the risk of building safety incidents.

[0008] In summary, in order to overcome the limitations of traditional detection methods, improve the efficiency, accuracy and flexibility of building material structural performance testing, and achieve efficient allocation of resources and precise control of risks, it is necessary to develop a new graded and progressive detection system and method for building material structural performance. Summary of the Invention

[0009] In order to solve the above-mentioned defects in the prior art, the present invention proposes a building material structural performance detection system and method.

[0010] The technical solution adopted in the present invention is as follows:

[0011] A hierarchical and progressive testing method for structural performance of building materials, comprising:

[0012] Step 1: Inspect the appearance and coating of the exposed steel structure of the building. If the test results are abnormal, mark the risk as a low-risk component and proceed to the next level of risk inspection;

[0013] Step 2: Further detect and quantify the damage of low-risk components. If the test results are abnormal, mark them as high-risk components and proceed to the next level of risk detection;

[0014] Step 3: Perform destructive testing on high-risk components to verify their key performance. If the test results are abnormal, mark them as unqualified components.

[0015] Preferably, step 1 specifically includes: testing the rust area ratio, rust layer color, coating thickness and coating adhesion of the exposed steel structure of the building. If the test results show that the rust area is less than 30%, the rust layer color is black rust, the coating thickness is greater than 50% of the design value, and the adhesion is greater than 3MPa, the test result is normal, and it is marked as a risk-free component and re-inspected every 12 months; otherwise, if the test result is abnormal, a risk mark is performed, and it is marked as a low-risk component, and the next level of risk detection is carried out.

[0016] Furthermore, the temperature and humidity of the environment where the risk-free components are located, the and Concentration is tested, if the relative humidity is greater than 80%, and or , the test result is judged to be abnormal, marked as corrosion acceleration area, and the re-inspection cycle is shortened to 3 months.

[0017] Preferably, the damage condition of the low-risk component in step 2 specifically includes: geometric deformation, cracks and stress state of the low-risk component.

[0018] Furthermore, the step 2 specifically includes:

[0019] Step 2.1: Measure the component wall thickness, record the thinning rate, scan the component morphology, calculate the deflection and node offset, and mark the component as a candidate for structural failure if the wall thickness thinning rate is greater than 15% or the deflection is greater than L / 300 or the offset is greater than H / 400. L is the span of the component and H is the vertical height of the component.

[0020] Step 2.2: Perform UT testing on welds and stress concentration areas at nodes, record the crack depth, perform MT testing on surface crack-sensitive areas, mark the crack length and distribution, and mark components with a risk of fracture if the crack depth is greater than 1 / 6 of the wall thickness or the crack length is greater than 10 mm.

[0021] Step 2.3: Install sensors on high-stress components and record the stress amplitude and vibration spectrum for 72 hours. If the stress amplitude is greater than 0.5f_y or the vibration frequency is close to the component's natural frequency, mark it as a candidate for dynamic instability, where f_y is the yield strength of the component material.

[0022] Step 2.4: Risk marking is performed on the structural failure candidate components, fracture risk components, and dynamic instability candidate components, and they are marked as high-risk components for the next level of risk detection.

[0023] Furthermore, the step 3 includes:

[0024] Step 3.1: Cut specimens from high-risk components and test yield strength, tensile strength, and impact toughness; if the measured yield strength and tensile strength are less than 85% of the design value or the impact toughness is less than 85% of the design value, , it is determined to be an unqualified component and needs to be reinforced or replaced immediately;

[0025] Step 3.2: If the measured yield strength is ≥ 85% of the design value or the impact toughness is The components are collected and input into the finite element analysis software, trained in the corrosion rate model, and the remaining bearing capacity and corrosion life of the components are calculated. If the remaining life is less than 5 years, it is marked as an emergency component and included in the renovation plan.

[0026] A building material structural performance graded progressive detection system for executing the above-mentioned detection method, specifically comprising: a main control device and a rust layer detection device, a coating detection device, an environmental detection device, a geometric deformation detection device, a crack detection device, a stress state detection device, a mechanical property detection device, a life prediction device, and a strategy formulation device connected to the main control device;

[0027] The rust layer detection device is used to detect the rust area ratio and rust layer color of the exposed steel structure of the building;

[0028] The coating detection device is used to detect the coating thickness and coating adhesion of the exposed steel structure of the building;

[0029] The environment detection device is used to detect the temperature and humidity of the environment, the and Concentration was tested;

[0030] The geometric deformation detection device is used to measure the wall thickness of the component, record the thinning rate, scan the component morphology, and calculate the deflection and node offset;

[0031] The crack detection device is used to perform UT testing on welds and stress concentration areas of nodes, record the crack depth, and perform MT testing on surface crack sensitive areas, marking the crack length and distribution;

[0032] The stress state detection device is used to detect the internal stress amplitude and vibration spectrum of the component within 72 hours;

[0033] The mechanical properties testing device is used to test yield strength, tensile strength, elongation, and impact toughness;

[0034] The life prediction device is used to predict the remaining bearing capacity and corrosion life of the calculated component;

[0035] The strategy formulation device is used to formulate a corresponding risk elimination strategy according to the risk level of the detected steel structure.

[0036] Preferably, the main control device controls the rust layer detection device and the strategy formulation device to be normally open, and controls the coating detection device, the environment detection device, the geometric deformation detection device, the crack detection device, the stress state detection device, the mechanical property detection device and the life prediction device to be normally closed;

[0037] The rust layer detection device detects the rust area ratio and rust layer color of the exposed steel structure of the building. If the detection result shows that the rust area is greater than 30% and the rust layer color is red rust, the steel structure has a large structural risk. The main control device controls the coating detection device to start and detect the coating thickness and coating adhesion. If the test result shows that the coating thickness is less than 50% of the design value or the adhesion is less than 3MPa, the test result is abnormal and a risk mark is performed. If it is marked as a low-risk component, the main control device controls the next level of risk detection;

[0038] The main control device controls the geometric deformation detection device, the crack detection device and the stress state detection device to start. The geometric deformation detection device measures the wall thickness of the component, records the thinning rate, scans the component morphology, calculates the deflection and the node offset. If the wall thickness thinning rate is greater than 15% or the deflection is greater than L / 300 or the offset is greater than H / 400, it is marked as a candidate component for structural failure; the crack detection device performs UT detection on the weld and the stress concentration area of ​​the node, records the crack depth, and performs MT detection on the surface crack sensitive area, marking the crack length and distribution. If the crack depth is greater than 1 / 6 of the wall thickness or the crack length is greater than 10mm, it is marked as a fracture risk component; the stress state detection device records the stress amplitude and vibration spectrum of the steel structure within 72 hours. If the stress amplitude is greater than 0.5f_y or the vibration frequency is close to the natural frequency of the component, it is marked as a dynamic instability candidate component; the structural failure candidate components, fracture risk components and dynamic instability candidate components are risk marked, marked as high-risk components, and the next level of risk detection is carried out;

[0039] The main control device controls the mechanical properties testing device to start, and the mechanical properties testing device tests the yield strength, tensile strength, and impact toughness; if the measured yield strength and tensile strength are less than 85% of the design value or the impact toughness is less than 85% of the design value, , determined to be an unqualified component;

[0040] If the measured yield strength is ≥ 85% of the design value or the impact toughness , the main control device controls the life prediction device to start, collects the data and inputs it into the finite element analysis software, trains it in the corrosion rate model, calculates the component's remaining bearing capacity and corrosion life, and if the remaining life is less than 5 years, it is marked as an emergency treatment component;

[0041] During the inspection process of steel structure materials, the main control device controls the strategy formulation device to start, and generates corresponding risk elimination strategies for steel structures with different inspection results.

[0042] Furthermore, if the test result of the rust layer detection device is normal, it is marked as a risk-free component. and Concentration is tested, if the relative humidity is greater than 80%, and or , the test result is judged to be abnormal, marked as corrosion acceleration area, and the re-inspection cycle is shortened to 3 months.

[0043] A storage medium stores a computer program, which, when run, executes a method for progressively detecting the structural performance of building materials.

[0044] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0045] This building material structural performance grading and progressive detection system is a comprehensive, multi-sensor system that integrates a range of hardware and software, including rust detection, strategy development, coating detection, environmental detection, geometric deformation detection, crack detection, stress state detection, mechanical property detection, and lifespan prediction. These devices enable a step-by-step, risk-based approach to steel performance testing in unfinished buildings, enabling timely identification of low-risk, medium-risk, high-risk, and emergency steel structures. Using multiple sensor technologies, it further tests internal and external parameters of areas at risk of aging, including abnormalities in rust, coatings, deformation, cracks, environmental parameters, stress state, and mechanical properties, and generates corresponding risk mitigation strategies based on the severity of the abnormality.

[0046] This hierarchical and progressive detection method and system leverages five core advantages: efficiency optimization, precision improvement, scenario adaptation, cost control, and technological expansion. It accurately assesses material risk levels and rapidly formulates response measures, improving material safety and extending service life. It also provides precise early warning and response plans for abnormal situations, addressing issues such as resource waste, insufficient precision, and poor flexibility inherent in traditional detection methods, ensuring efficient resource allocation and precise risk control. Its core value lies in achieving efficient, precise, and intelligent detection processes through hierarchical screening, dynamic adjustment, and resource focus. It is particularly suitable for complex systems, large-scale testing, or high-risk scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] The present invention will now be described by way of example with reference to the accompanying drawings, in which:

[0048] Figure 1 Flow chart of the detection method of the present invention;

[0049] Figure 2 is a logic flow chart of the detection method of the present invention;

[0050] Figure 3 Schematic diagram of the structure of the detection system in the present invention. DETAILED DESCRIPTION

[0051] The technical solutions of the present invention will be described clearly and completely below with reference to the accompanying drawings and embodiments. Obviously, the embodiments described are only some of the embodiments of the present invention, not all of them. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without inventive effort are also within the scope of protection of the present invention.

[0052] Example 1

[0053] When problems are discovered during the steel inspection process, it is necessary to follow the principles of "graded response, risk priority, and scientific disposal" and formulate targeted treatment plans based on the type of problem, severity, and component importance. The following is a redesigned graded risk-oriented inspection method for the performance inspection of unfinished steel in unfinished buildings. It defines the inspection content, tools, and priorities for the four levels of low risk, medium risk, high risk, and emergency to ensure efficient resource allocation and precise risk control.

[0054] A method for the progressive grading of structural performance of building materials, see Figure 1 、 2 , which consists of three stages:

[0055] Initial screening phase (non-destructive, rapid risk identification)

[0056] Detailed assessment phase (semi-destructive / non-destructive testing, quantification of damage)

[0057] Verification and confirmation phase (destructive testing, verification of key performance)

[0058] The specific steps include:

[0059] Step 1: Inspect the appearance and coating of the exposed steel structure of the building. If the test result is abnormal, mark the risk as a low-risk component and proceed to the next level of risk inspection.

[0060] Specifically, the rust area ratio, rust layer color, coating thickness and coating adhesion of the exposed steel structure of the building are tested. If the test results show that the rust area is less than 30%, the rust layer color is black rust, the coating thickness is greater than 50% of the design value, and the adhesion is greater than 3MPa, the test result is normal and it is marked as a risk-free component and re-inspected every 12 months; on the contrary, if the test result is abnormal, it is marked as a low-risk component and the next level of risk detection is carried out.

[0061] For steel structures marked as risk-free components, the ambient temperature and humidity, and the air and Concentration is tested, if the relative humidity is greater than 80%, and or

[0062] , the test result is judged to be abnormal, marked as corrosion acceleration area, and the re-inspection cycle is shortened to 3 months.

[0063] Step 2: Further detect and quantify the damage of low-risk components. If the test results are abnormal, mark the risk as a high-risk component and proceed to the next level of risk detection.

[0064] The damage condition of low-risk components specifically includes the geometric deformation, cracks, and stress state of the low-risk components. Step 2 specifically includes the following sub-steps:

[0065] Step 2.1: Measure the component wall thickness (measure one point every 100 mm), record the thinning rate (compared to the design value), scan the component morphology, calculate the deflection and node offset, and mark the component as a candidate for structural failure if the wall thickness thinning rate is greater than 15% or the deflection is greater than L / 300 or the offset is greater than H / 400.

[0066] In practice, an ultrasonic thickness gauge is used to measure the wall thickness of steel components, with measurement points set every 100 mm to ensure coverage of critical component areas. The thinning rate is calculated by comparing it with the designed wall thickness. Simultaneously, a 3D laser scanner is used to scan the overall component geometry, acquiring its actual geometry and calculating its deflection and node offsets.

[0067] For example, if a steel column with a designed wall thickness of 10 mm is measured to have an actual wall thickness of 8 mm at a certain point, the thinning rate is 20%, exceeding the 15% threshold and should be flagged as a structural failure candidate. Similarly, if a steel beam with a span of 6 m is measured to have a deflection of 25 mm, exceeding the limit of L / 300 (i.e., 20 mm), it should also be flagged as a structural failure candidate.

[0068] Step 2.2: Perform UT testing on stress concentration areas such as welds and nodes, record the crack depth, perform MT testing on surface crack-sensitive areas, mark the crack length and distribution, and if the crack depth is greater than t / 6 (t is the wall thickness) or the crack length is greater than 10mm, mark it as a component with fracture risk.

[0069] During this step, ultrasonic testing (UT) is used to inspect stress concentration areas such as welds and joints for internal defects, focusing on crack depth. Meanwhile, magnetic particle testing (MT) is used to inspect surface crack-sensitive areas, accurately measuring the length and distribution of surface cracks.

[0070] For example, if a UT test reveals a 2.5mm crack in the weld of a 12mm thick steel structure, exceeding the threshold of t / 6 (i.e., 2mm), the component should be marked as a fracture risk component. Similarly, if an MT test reveals a 15mm crack on the surface, exceeding the 10mm limit, the component should also be marked as a fracture risk component.

[0071] Step 2.3: Install sensors on high-stress components (such as column bases and beam ends) and record the stress amplitude and vibration spectrum for 72 hours. If the stress amplitude is greater than 0.5f_y (yield strength) or the vibration frequency is close to the component's natural frequency, mark the component as a candidate for dynamic instability.

[0072] In this step, strain gauges and accelerometers are installed in high-stress areas of the steel structure, such as column bases and beam ends, to continuously monitor stress changes and vibration characteristics over a 72-hour period. The stress amplitude and vibration spectrum are recorded using a data acquisition system and compared with the yield strength and natural frequency of the component material.

[0073] For example, for a component made of Q235 steel (yield strength f_y of 235 MPa), if the monitored maximum stress amplitude reaches 130 MPa, exceeding the threshold of 0.5 f_y (i.e., 117.5 MPa), the component should be marked as a candidate for dynamic instability. Similarly, if the component's natural frequency is 5 Hz, and the monitored primary vibration frequency is 4.8 Hz, close to the natural frequency, the component should also be marked as a candidate for dynamic instability.

[0074] Step 2.4: Risk marking is performed on the structural failure candidate components, fracture risk components, and dynamic instability candidate components, and they are marked as high-risk components for the next level of risk detection.

[0075] After completing the inspection of the above three sub-steps, all steel structural components marked as structural failure candidate components, fracture risk components or dynamic instability candidate components are uniformly marked as high-risk components and annotated in the Building Information Model (BIM) system to prepare for the next level of risk detection.

[0076] Step 3: Conduct destructive testing on high-risk components to verify their key performance. If the test results are abnormal, mark them as unqualified components and reinforce or replace them immediately.

[0077] Step 3.1: Cut specimens from high-risk components and test yield strength, tensile strength, and impact toughness; if the measured yield strength and tensile strength are less than 85% of the design value or the impact toughness is less than 85% of the design value, , it is judged to be an unqualified component and needs to be reinforced or replaced immediately.

[0078] The hierarchical and progressive detection method and system can effectively improve detection efficiency, accuracy, and reliability by refining the detection process by steps and levels, gradually deepening it according to different complexity or detection requirements. The following describes its beneficial effects from multiple dimensions:

[0079] Tiered testing: First, use primary testing to quickly exclude samples without problems, and only conduct in-depth testing on suspicious samples to avoid the high-cost analysis of the entire sample.

[0080] Progressive analysis: Dynamically adjust the detection strategy based on the detection results to avoid repeated operations.

[0081] Allocate resources on demand: For samples that pass primary testing, there is no need to invest in advanced testing resources (such as manpower, equipment, and time), reducing overall costs.

[0082] In this step, standard specimens are cut from non-critical locations of high-risk components and tested for yield strength, tensile strength, and impact toughness according to the mechanical properties testing standards for metal materials. Specimens should be cut to avoid affecting the overall structural performance of the component, and their size and shape should comply with the requirements of the relevant testing standards.

[0083] For example, for a Q345 steel member with a design yield strength of 345 MPa and a tensile strength of 490 MPa, if the measured yield strength is 280 MPa (85% lower than the design value, i.e. 293.25 MPa), or the measured tensile strength is 400 MPa (85% lower than the design value, i.e. 416.5 MPa), or the impact toughness is (lower than threshold), it should be judged as an unqualified component and reinforcement or replacement measures should be taken immediately.

[0084] Step 3.2: If the measured yield strength is ≥ 85% of the design value or the impact toughness is The components are collected and input into the finite element analysis software, trained in the corrosion rate model, and the remaining bearing capacity and corrosion life of the components are calculated. If the remaining life is less than 5 years, it is marked as an emergency component and given priority in the renovation plan.

[0085] For high-risk components whose mechanical properties test results meet the requirements, further evaluation of their long-term performance is required. Data such as the component's geometric dimensions, material properties, and damage state are input into finite element analysis software. A corrosion rate model is developed based on environmental parameters. Numerical simulations are then used to calculate the component's residual bearing capacity and expected corrosion life in its current state.

[0086] For example, after mechanical property testing, a steel column has a yield strength of 320MPa (85% higher than the design value of 345MPa), a tensile strength of 450MPa (85% higher than the design value of 490MPa), and an impact toughness of (higher than threshold value). The measured geometric size, material performance and corrosion state data are input into the finite element analysis software, and the environmental corrosion parameters are simulated and calculated, if the prediction result shows that the remaining service life of the steel column is 4 years, which is lower than the threshold value of 5 years, the component should be marked as emergency treatment component, and be preferentially listed in the reconstruction plan.

[0087] Example two

[0088] A building material structure performance grading progressive detection system, referring to Figure 3 , for performing the detection method described in example one, specifically comprising: a main control device, and a rust layer detection device, a coating detection device, an environment detection device, a geometric deformation detection device, a crack detection device, a stress state detection device, a mechanical property detection device, a life prediction device and a strategy making device connected with the main control device.

[0089] The rust layer detection device is used to detect the rust area proportion and rust layer color of the appearance of the exposed steel structure of the building. The rust layer detection device includes a high-resolution digital camera and image analysis software. By shooting the image of the steel structure surface, the image processing technology is used to automatically calculate the rust area proportion, and the color recognition algorithm is used to judge whether the rust layer color is black rust or red rust.

[0090] The coating detection device is used to detect the coating thickness and coating adhesion of the appearance of the exposed steel structure of the building. The coating detection device includes a coating thickness gauge and an adhesion tester. The coating thickness gauge adopts electromagnetic induction principle and can non-destructively measure the thickness of non-magnetic coating on the metal substrate; the adhesion tester adopts pull-out method and evaluates the adhesion of the coating by measuring the force required to pull the coating away from the substrate.

[0091] The environment detection device is used to detect the temperature and humidity, the concentration of and in the air. The environment detection device includes a temperature and humidity sensor, a chloride ion concentration detector and a sulfur dioxide concentration detector. The temperature and humidity sensor adopts a capacitive sensing element, has high precision and good long-term stability; the chloride ion concentration detector adopts ion selective electrode technology; the sulfur dioxide concentration detector adopts electrochemical sensing technology and can monitor the concentration of air pollutants in real time.

[0092] The geometric deformation detection device is used to measure component wall thickness (at one point every 100mm), record the thinning rate (compared to the design value), scan the component topography, and calculate deflection and node offset. The geometric deformation detection device includes an ultrasonic thickness gauge, a 3D laser scanner, and a data processing unit. The ultrasonic thickness gauge uses the pulse reflection principle to accurately measure the wall thickness of metal components. The 3D laser scanner emits a laser beam and receives the reflected signal to quickly obtain the component's three-dimensional geometric shape. The data processing unit compares the measured data with the design value to calculate the thinning rate, deflection, and node offset.

[0093] The crack detection device is used to perform UT testing on stress concentration areas such as welds and joints, recording crack depth, and MT testing on surface crack-sensitive areas, marking crack length and distribution. The crack detection device includes an ultrasonic flaw detector (UT), a magnetic particle flaw detector (MT), and a defect data recording system. The ultrasonic flaw detector uses the pulse reflection principle to detect cracks and defects within components. The magnetic particle flaw detector generates a magnetic field on the component surface, exploiting the phenomenon of magnetic particles gathering at cracks to indicate surface cracks. The defect data recording system digitally records and visualizes the detected crack information.

[0094] The stress state detection device is used to detect the internal stress amplitude and vibration spectrum of a component over a 72-hour period. It includes a strain gauge, an accelerometer, a data acquisition system, and spectrum analysis software. The strain gauge indirectly measures the stress state by measuring minute surface deformations of the component; the accelerometer measures the component's vibration characteristics; the data acquisition system continuously records stress and vibration data over a 72-hour period; and the spectrum analysis software performs a Fourier transform on the collected data to obtain the vibration spectrum characteristics.

[0095] The mechanical properties testing device is used to test yield strength, tensile strength, elongation, and impact toughness. It includes a universal testing machine, an impact testing machine, and specimen preparation equipment. The universal testing machine is used to perform tensile tests to measure yield strength, tensile strength, and elongation; the impact testing machine is used to measure the impact toughness of the material; and the specimen preparation equipment is used to cut standard specimens from the component and perform necessary processing.

[0096] The life prediction device is used to predict and calculate the remaining bearing capacity and corrosion life of a component. It includes a high-performance computer, finite element analysis software, and a corrosion rate model. The high-performance computer provides powerful computing power; the finite element analysis software is used to build a numerical model of the component and perform structural analysis; and the corrosion rate model, based on measured data and environmental parameters, predicts the component's corrosion behavior and structural performance degradation during future use.

[0097] The strategy-making device is used to formulate a corresponding risk mitigation strategy based on the risk level of the detected steel structure. The strategy-making device includes an expert knowledge base, a decision support system, and a report generation module. The expert knowledge base stores solutions and technical specifications for various steel structure issues; the decision support system recommends appropriate treatment measures based on the test results and risk level; and the report generation module automatically generates test reports and repair recommendations.

[0098] The main control device controls the rust layer detection device and the strategy formulation device to be normally open, and controls the coating detection device, the environment detection device, the geometric deformation detection device, the crack detection device, the stress state detection device, the mechanical property detection device and the life prediction device to be normally closed.

[0099] The rust layer detection device detects the rust area ratio and rust layer color of the exposed steel structure of the building. If the detection result shows that the rust area is greater than 30% and the rust layer color is red rust, the steel structure has a large structural risk. The main control device controls the coating detection device to start and detect the coating thickness and coating adhesion. If the detection result shows that the coating thickness is less than 50% of the design value or the adhesion is less than 3MPa, the detection result is abnormal and a risk mark is performed. It is marked as a low-risk component and the main control device controls the next level of risk detection.

[0100] The main control device activates the geometric deformation detection device, crack detection device, and stress state detection device. The geometric deformation detection device measures the component wall thickness (measured at one point every 100mm), records the thinning rate (compared with the design value), scans the component morphology, and calculates the deflection and node offset. If the wall thickness thinning rate is greater than 15% or the deflection is greater than L / 300 (L is the span of the component), or the offset is greater than H / 400 (H is the vertical height of the component), the component is marked as a candidate for structural failure. The crack detection device performs UT testing on stress concentration areas such as welds and nodes, recording the crack depth, and performs MT testing on surface crack-sensitive areas, marking the crack length and distribution. If the crack depth is greater than t / 6 (t is the wall thickness) or the crack length is greater than 10mm, the component is marked as a fracture risk component. The stress state detection device records the stress amplitude and vibration spectrum of the steel structure within 72 hours. If the stress amplitude is greater than 0.5f_y (f_y is the yield strength of the material) or the vibration frequency is close to the natural frequency of the component, the component is marked as a candidate for dynamic instability.

[0101] The structural failure candidate components, fracture risk components and dynamic instability candidate components are risk-marked and marked as high-risk components for the next level of risk detection.

[0102] The main control device controls the mechanical properties testing device to start, and the mechanical properties testing device tests the yield strength, tensile strength, and impact toughness; if the measured yield strength and tensile strength are less than 85% of the design value or the impact toughness is less than 85% of the design value, , determined to be an unqualified component.

[0103] If the measured yield strength ≥ 85% of the design value or the impact toughness The main control device controls the life prediction device to start, collects the data and inputs it into the finite element analysis software, trains it in the corrosion rate model, calculates the remaining bearing capacity and corrosion life of the component, and if the remaining life is less than 5 years, it is marked as an emergency treatment component.

[0104] During the inspection of steel structure materials, the main control device controls the strategy formulation device to start, and generates corresponding risk elimination strategies for steel structures with different inspection results, including:

[0105] Non-risk components: Develop a routine maintenance plan, including regular cleaning, anti-corrosion coating inspection, and environmental monitoring, with a comprehensive inspection every 12 months. For non-risk components in areas with accelerated corrosion, shorten the inspection cycle to three months and increase the frequency of anti-corrosion coating maintenance.

[0106] Low-risk components: Develop an enhanced maintenance plan, including localized corrosion treatment, coating repairs, and regular monitoring, with a comprehensive inspection every six months. Preventive coating renewal is recommended for components with corrosion areas approaching 30% or coating thickness approaching critical values.

[0107] High-risk components: Develop a dedicated monitoring plan, including the installation of permanent monitoring sensors, regular non-destructive testing and structural performance assessments, and comprehensive inspections every three months. For components with a remaining life of 5-10 years, it is recommended to include them in a mid-term renovation plan and increase the frequency of inspections.

[0108] For non-compliant components: Develop an emergency response plan, including temporary supports, load limits, and emergency reinforcement or replacement. For critical load-bearing components, immediate reinforcement or replacement is recommended; for non-critical components, treatment can be completed within three months, while ensuring safety.

[0109] The test results of the rust layer detection device are normal and marked as risk-free components. The temperature and humidity of the environment where the risk-free components are located, and the concentration in the air are tested. If the relative humidity is greater than 80%, and or , the test result is judged to be abnormal, marked as corrosion acceleration area, and the re-inspection cycle is shortened to 3 months.

[0110] Example 3

[0111] A storage medium having a computer program stored thereon, wherein the computer program, when executed, executes a hierarchical and progressive detection method for structural performance of building materials as described in the first embodiment.

[0112] The storage medium can be a read-only memory (ROM), a random access memory (RAM), a magnetic disk, an optical disk, or other forms of computer-readable storage medium. The computer program stored on the storage medium includes program code for implementing the building material structure performance hierarchical progressive detection method, which can control the computer system to execute the various steps described in embodiment one when the program code is executed by the processor.

[0113] The main modules of the computer program include:

[0114] Data acquisition module: responsible for receiving data from various detection devices, including rust layer detection data, coating detection data, environmental parameter data, geometric deformation data, crack detection data, stress state data, and mechanical property test data.

[0115] Data processing module: processes and analyzes the collected data, including calculating parameters such as rust area ratio, thinning rate, deflection, and offset, and comparing them with preset thresholds.

[0116] Risk assessment module: based on the data processing results, the steel structure components are classified into risk levels, including no-risk components, low-risk components, high-risk components, and unqualified components.

[0117] Life prediction module: based on finite element analysis and corrosion rate model, the remaining carrying capacity and expected service life of the component are calculated.

[0118] Strategy generation module: based on the risk assessment results and life prediction results, the corresponding risk elimination strategies and maintenance recommendations are generated.

[0119] Report generation module: automatically generates a detection report, including component status, risk level, processing recommendations, and next inspection time.

[0120] When the computer program is run, first, the data acquisition module obtains various detection data of the steel structure components, and then the data processing module analyzes and processes these data. Next, the risk assessment module classifies the components according to the processing results. For high-risk components, the life prediction module further calculates their remaining service life. Finally, the strategy generation module and the report generation module generate risk elimination strategies and detection reports, respectively.

[0121] It should be noted that embodiment one, embodiment two, and embodiment three are all building material structure performance hierarchical progressive detection methods.

[0122] In the technical solution system elaborated in detail in this application, each key device used to build the entire system, without exception, belongs to a software or hardware module that is clearly existing and widely known in the prior art. These devices have clear definitions, functional descriptions, and application scenarios in the existing technical system. Those skilled in the art, with their own professional knowledge, technical experience, and full understanding of the prior art, can, after carefully studying the technical content recorded in this application, implement and operate this solution in its entirety without deviation, accurately, and efficiently, thereby ensuring that the technical solution can be smoothly implemented and implemented according to the expected goals and exert its due technical effects.

[0123] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A method for progressively testing the structural performance of building materials, characterized in that: include: Step 1: Inspect the appearance and coating of the exposed steel structure of the building. If the test results are abnormal, mark the risk as a low-risk component and proceed to the next level of risk inspection; Step 2: Further detect and quantify the damage of low-risk components. The damage of low-risk components specifically includes: geometric deformation, cracks and stress state of low-risk components. If the test results are abnormal, risk marking is performed and the component is marked as high-risk and proceeds to the next level of risk detection; Step 3: Perform destructive testing on high-risk components, including cutting specimens from high-risk components to test and verify their key properties, including yield strength, tensile strength and impact toughness. If the test results are abnormal, risk marking is performed and the component is marked as unqualified.

2. A method for progressively testing the structural performance of building materials according to claim 1, characterized in that: The step 1 specifically includes: testing the rust area ratio, rust layer color, coating thickness and coating adhesion of the exposed steel structure of the building. If the test results show that the rust area is less than 30%, the rust layer color is black rust, the coating thickness is greater than 50% of the design value, and the adhesion is greater than 3MPa, the test result is normal, and it is marked as a risk-free component and re-inspected every 12 months; on the contrary, if the test result is abnormal, it is risk marked and marked as a low-risk component, and the next level of risk detection is carried out.

3. A method for progressively testing the structural performance of building materials according to claim 2, characterized in that: The ambient temperature and humidity of the non-risk components, the air and Concentration is tested, if the relative humidity is greater than 80%, and or , the test result is judged to be abnormal, marked as corrosion acceleration area, and the re-inspection cycle is shortened to 3 months.

4. A method for progressively testing the structural performance of building materials according to claim 1, characterized in that: The step 2 specifically includes: Step 2.1: Measure the component wall thickness, record the thinning rate, scan the component morphology, calculate the deflection and node offset, and mark the component as a candidate for structural failure if the wall thickness thinning rate is greater than 15% or the deflection is greater than L / 300 or the offset is greater than H / 400. L is the span of the component and H is the vertical height of the component. Step 2.2: Perform UT testing on welds and stress concentration areas at nodes, record the crack depth, perform MT testing on surface crack-sensitive areas, mark the crack length and distribution, and mark components with a risk of fracture if the crack depth is greater than 1 / 6 of the wall thickness or the crack length is greater than 10 mm. Step 2.3: Install sensors on high-stress components and record the stress amplitude and vibration spectrum for 72 hours. If the stress amplitude is greater than 0.5f_y or the vibration frequency is close to the component's natural frequency, mark it as a candidate for dynamic instability, where f_y is the yield strength of the component material. Step 2.4: Risk marking is performed on the structural failure candidate components, fracture risk components, and dynamic instability candidate components, and they are marked as high-risk components for the next level of risk detection.

5. A method for progressively testing the structural performance of building materials according to claim 1, characterized in that: The step 3 comprises: Step 3.1: If the measured yield strength and tensile strength are less than 85% of the design value or the impact toughness , it is determined to be an unqualified component and needs to be reinforced or replaced immediately; Step 3.2: If the measured yield strength is ≥ 85% of the design value or the impact toughness is The components are collected and input into the finite element analysis software, trained in the corrosion rate model, and the remaining bearing capacity and corrosion life of the components are calculated. If the remaining life is less than 5 years, it is marked as an emergency component and included in the renovation plan.

6. A building material structural performance graded progressive detection system, characterized in that: Used to perform the detection method described in any one of claims 1 to 5, specifically comprising: a main control device and a rust layer detection device, a coating detection device, an environment detection device, a geometric deformation detection device, a crack detection device, a stress state detection device, a mechanical property detection device, a life prediction device, and a strategy formulation device connected to the main control device; The rust layer detection device is used to detect the rust area ratio and rust layer color of the exposed steel structure of the building; The coating detection device is used to detect the coating thickness and coating adhesion of the exposed steel structure of the building; The environment detection device is used to detect the temperature and humidity of the environment, the and Concentration was tested; The geometric deformation detection device is used to measure the wall thickness of the component, record the thinning rate, scan the component morphology, and calculate the deflection and node offset; The crack detection device is used to perform UT testing on welds and stress concentration areas of nodes, record the crack depth, and perform MT testing on surface crack sensitive areas, marking the crack length and distribution; The stress state detection device is used to detect the internal stress amplitude and vibration spectrum of the component within 72 hours; The mechanical properties testing device is used to test yield strength, tensile strength, elongation, and impact toughness; The life prediction device is used to predict the remaining bearing capacity and corrosion life of the calculated component; The strategy formulation device is used to formulate a corresponding risk elimination strategy according to the risk level of the detected steel structure.

7. A building material structural performance graded progressive detection system according to claim 6, characterized in that: The main control device controls the rust layer detection device and the strategy formulation device to be normally open, and controls the coating detection device, the environment detection device, the geometric deformation detection device, the crack detection device, the stress state detection device, the mechanical property detection device and the life prediction device to be normally closed; The rust layer detection device detects the rust area ratio and rust layer color of the exposed steel structure of the building. If the detection result shows that the rust area is greater than 30% and the rust layer color is red rust, the steel structure has a large structural risk. The main control device controls the coating detection device to start and detect the coating thickness and coating adhesion. If the test result shows that the coating thickness is less than 50% of the design value or the adhesion is less than 3MPa, the test result is abnormal and a risk mark is performed. If it is marked as a low-risk component, the main control device controls the next level of risk detection; The main control device controls the geometric deformation detection device, crack detection device, and stress state detection device to start. The geometric deformation detection device measures the wall thickness of the component, records the thinning rate, scans the component morphology, and calculates the deflection and node offset. If the wall thickness thinning rate is greater than 15% or the deflection is greater than L / 300 or the offset is greater than H / 400, it is marked as a candidate component for structural failure. The crack detection device performs UT testing on welds and node stress concentration areas, records the crack depth, and performs MT testing on surface crack sensitive areas, marking the crack length and distribution. If the crack depth is greater than 1 / 6 of the wall thickness or the crack length is greater than 10mm, it is marked as a component with fracture risk. The stress state detection device records the stress amplitude and vibration spectrum of the steel structure within 72 hours. If the stress amplitude is greater than 0.5f_y or the vibration frequency is close to the natural frequency of the component, it is marked as a candidate component for dynamic instability. Marking the structural failure candidate components, fracture risk components, and dynamic instability candidate components as high-risk components for the next level of risk detection; The main control device controls the mechanical properties testing device to start, and the mechanical properties testing device tests the yield strength, tensile strength, and impact toughness; If the measured yield strength and tensile strength are less than 85% of the design value or the impact toughness , determined to be an unqualified component; If the measured yield strength is ≥ 85% of the design value or the impact toughness , the main control device controls the life prediction device to start, collects the data and inputs it into the finite element analysis software, trains it in the corrosion rate model, calculates the component's remaining bearing capacity and corrosion life, and if the remaining life is less than 5 years, it is marked as an emergency treatment component; During the inspection process of steel structure materials, the main control device controls the strategy formulation device to start, and generates corresponding risk elimination strategies for steel structures with different inspection results.

8. A building material structural performance graded progressive detection system according to claim 7, characterized in that: The test results of the rust layer detection device are normal and marked as risk-free components. The temperature and humidity of the environment where the risk-free components are located, the air and Concentration is tested, if the relative humidity is greater than 80%, and or , the test result is judged to be abnormal, marked as corrosion acceleration area, and the re-inspection cycle is shortened to 3 months.

9. A storage medium, characterized in that: The storage medium stores a computer program, which, when executed, executes a hierarchical and progressive detection method for structural performance of building materials according to any one of claims 1 to 5.

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