Device and method for intelligently sensing and judging health state of hydraulic metal structure

Abstract

The invention provides an intelligent sensing and judging device and method for the health state of a hydraulic metal structure, belongs to the technical field of monitoring and detection of the health state of the hydraulic metal structure, and can at least partially solve the problems that the existing health state detection efficiency is low, the intelligent sensing capability is insufficient, and the detection result cannot be visualized. The device comprises a detection frame, a magnetic adsorption assembly arranged at the bottom of the detection frame, an elastic detection needle assembly arranged in the detection frame, a displacement amplification mechanism matched with the elastic detection needle assembly, and an image acquisition assembly used for identifying the displacement amount of the displacement amplification mechanism. The driving assembly is used for driving the elastic detection needle assembly to move; and the terminal equipment is used for intelligent sensing and judgment. According to the invention, the surface contour of the detected metal is re-engraved through the elastic detection needle assembly and is amplified into recognizable displacement, and then the image acquisition assembly performs intelligent recognition, so that automatic intelligent sensing of the health state of the metal structure and scientific evaluation of the health level are realized.

Description

Technical Field

[0001] This invention belongs to the field of health status monitoring and detection technology for hydraulic metal structures, specifically relating to an intelligent sensing and evaluation device and method for the health status of hydraulic metal structures. Background Technology

[0002] As key load-bearing components in water conservancy and hydropower projects, the health status of hydraulic metal structures directly affects the safe operation of the project. Health status testing of hydraulic metal structures refers to the process of assessing the health status of various metal structures with beams, slabs, and columns, such as gates and hoists, after a certain number of years of use or service. Due to environmental factors, various forms of oxidation and electrochemical corrosion occur on the surface, leading to a certain degree of degradation in the mechanical properties of the structure. If the metal structure is a major load-bearing component and its health status is severely deteriorated, the decline in its mechanical properties will affect the safe operation of the structure. If not addressed in time, it may deform or even collapse under its original design conditions. Therefore, intelligent sensing and scientific assessment of the health status of hydraulic metal structures are of great significance for the timely detection of structural defects and the prevention of safety accidents.

[0003] According to relevant standards for the safety inspection of metal structures in water conservancy and hydropower projects, such as the Technical Specifications for Safety Inspection of Hydraulic Steel Gates and Hoists, and the Technical Specifications for Safety Inspection of Pressure Steel Pipes, health status testing and evaluation are required during the safety inspection of metal structural equipment such as gates, hoists, and pressure steel pipes. The evaluation area for health status testing is uniformly defined as a 300mm x 300mm area in the aforementioned standards.

[0004] Currently, the health status inspection of hydraulic metal structures such as gates, hoists, and pressure steel pipes mainly relies on manual on-site inspections using equipment such as ultrasonic thickness gauges and depth calipers. However, these traditional inspection methods have the following defects and shortcomings.

[0005] Insufficient intelligent sensing capabilities: In terms of detection efficiency, current traditional metal structure health status detection mainly uses depth sounders or thickness gauges, requiring point-by-point measurements, resulting in very low detection efficiency. Detecting a 300mm x 300mm area takes approximately 30 minutes, which is inefficient and cannot achieve rapid intelligent sensing of the metal structure's surface condition.

[0006] Low level of intelligence in data acquisition and processing: Currently, traditional metal structure health status inspections primarily use depth sounders or thickness gauges, which cannot automatically record and statistically analyze the test data. On-site, one person often needs to manually operate the instrument while another manually records the data. After manual recording, the data must be entered into a computer spreadsheet for statistical analysis. This entire process is cumbersome, error-prone, and makes intelligent acquisition and automated processing of test data difficult.

[0007] Lack of scientific assessment capability for health status: In terms of output of test results, the current traditional metal structure health status test mainly adopts manual inspection, and the results are entered into a table. Then, the health level is judged based on the analysis of the test data. This results in the inability to judge the test conclusion on the spot. It is often necessary to wait for a certain period of time before the test conclusion is obtained after being entered into the computer and calculated. It is impossible to report the test results and conclusions on the spot, nor can it directly generate a health status contour map. The test results cannot be visualized, making it difficult to make timely and accurate comprehensive assessment of the health status of metal structures.

[0008] Existing intelligent devices suffer from poor applicability: While current laser profile scanners can detect surface contours in small areas, their application in large-scale health status monitoring at hydraulic engineering sites faces significant limitations. Laser profile scanners are highly integrated, bulky, and heavy, making them inconvenient for mobile operations. Hydraulic structures are often located at heights, near water, or in confined spaces, requiring frequent movement and climbing by personnel. The cumbersome equipment significantly reduces inspection efficiency and introduces safety risks. Laser profile scanners are susceptible to strong ambient light interference, while creating darkroom conditions at hydraulic engineering sites is difficult. Furthermore, oxide layers and residual water films formed on metal structures outdoors can absorb or scatter laser light, leading to point cloud data loss or noise, affecting the accuracy of health status perception. The purchase and maintenance costs of laser profile scanners are high. High-precision line laser sensors are expensive, and integrated systems can cost hundreds of thousands of yuan. For hydraulic management units that need multiple devices, this represents a heavy economic burden, severely hindering their widespread adoption.

[0009] Therefore, there is an urgent need to develop an alternative detection scheme for intelligent sensing and evaluation of the health status of hydraulic metal structures that is cost-effective, lightweight, flexible, and insensitive to complex surface conditions. This scheme would enable automated intelligent sensing of the surface condition of metal structures and scientific evaluation of their health levels, which is of urgent practical significance for promoting the normalization and intelligent development of health status detection of hydraulic engineering metal structures. Summary of the Invention

[0010] The present invention aims to solve at least one of the technical problems existing in the prior art, and to provide an intelligent sensing and evaluation device and method for the health status of hydraulic metal structures.

[0011] This invention provides an intelligent sensing and evaluation device for the health status of hydraulic metal structures, comprising: Detection framework; A magnetic adsorption component is disposed at the bottom of the detection frame to fix the detection frame to the surface of the metal structure being tested during detection. An elastic probe assembly is disposed within the detection frame, including a probe fixing plate and a plurality of probes disposed on the probe fixing plate. Each probe is connected to the probe fixing plate via an elastic element. The probe includes a needle tip for contacting the surface of the metal structure being tested and following the contour undulation of the surface by means of the elastic force of the elastic element. A displacement amplification mechanism, configured to cooperate with the elastic detection needle assembly, includes a slider that cooperates with the tail of each of the probes; An image acquisition component is disposed above the displacement magnification mechanism and is used to acquire the displacement image of the slider; A driving component, connected to the elastic detection probe assembly, is used to drive the elastic detection probe assembly to move within the detection frame; and The terminal device is electrically connected to the image acquisition component and the driving component, and is used to receive the displacement image acquired by the image acquisition component and the position information fed back by the driving component, and to calculate the corrosion pit depth data of the measured area based on the displacement image and the position information.

[0012] Furthermore, the plurality of probes in the elastic detection probe assembly are arranged in a single row, and the spacing between adjacent probes is a preset spacing value; Each probe has a boss structure in the middle, and the elastic element is a miniature spring sleeved on the probe and abutting against the boss structure. The miniature spring is used to provide a preset elastic pressure to the probe.

[0013] Furthermore, the probe is made of tungsten carbide material, and the tip of the probe is machined into a dome shape.

[0014] Furthermore, the slider is a wedge-shaped slider, which uses the principle of inclined plane to convert the vertical displacement of the probe into horizontal displacement; The displacement amplification mechanism further includes a slider guide frame, and the wedge-shaped slider is disposed on the slider guide frame to constrain the wedge-shaped slider to move in the horizontal direction; Each of the wedge-shaped sliders is connected to the slider guide frame via a slider spring, and the slider spring uses elastic force to keep the wedge-shaped slider in contact with the tail of the corresponding probe.

[0015] Furthermore, each of the wedge-shaped sliders has a scale mark on its top, which is used by the image acquisition component to identify the horizontal displacement of the wedge-shaped slider relative to the zero position; The wedge-shaped slider has a preset tilt angle, so that the displacement amplification factor of the displacement amplification mechanism is a preset amplification factor.

[0016] Furthermore, the drive assembly includes a dual-axis linear guide and a miniature servo motor for driving the dual-axis linear guide; The elastic detection needle assembly, the displacement amplification mechanism, and the image acquisition assembly are connected by a linkage frame structure to form an integrated module. The integrated module is connected to the dual-axis linear guide rail, so that the integrated module can be moved within the detection frame along the X-axis and Y-axis directions via the dual-axis linear guide rail.

[0017] A method for intelligent sensing and evaluation of the health status of hydraulic metal structures includes the following steps: S1: Clean the surface of the test area of ​​the metal structure to be tested, removing the anti-corrosion coating and contaminants; S2: Place the detection frame above the test area, and fix the detection frame to the surface of the metal structure to be tested by the magnetic adsorption component, so that each of the probes of the elastic detection probe assembly contacts the surface of the metal structure to be tested. S3: The driving component drives the elastic detection needle assembly to scan within the test area. During the scanning process, each of the probes follows the contour undulation of the surface of the metal structure being tested. The displacement amplification mechanism converts and amplifies the displacement of each probe into the displacement of the corresponding slider. S4: The image acquisition component acquires displacement images of each slider in real time and transmits the displacement images to the terminal device; S5: The terminal device identifies the displacement of each slider based on the displacement image, combines the position information fed back by the drive component, calculates the corrosion pit depth data at each location in the test area, and evaluates the corrosion level based on the corrosion pit depth data.

[0018] Further, in step S3, the driving component drives the elastic detection needle assembly to move according to a preset scanning path, wherein the preset scanning path is: After scanning a measurement line along the X-axis at a preset X-axis moving speed, move a preset step distance along the Y-axis at a preset Y-axis moving speed, and then scan the next measurement line in the opposite direction along the X-axis. Repeat the above process until the entire measurement area is scanned, so that each probe moves in an S-shaped trajectory to traverse the measurement area.

[0019] Furthermore, in step S5, the terminal device is also used to perform the following processing based on the corrosion pit depth data: Draw isodepth maps, depth histograms, and frequency statistics charts for the survey area; The corrosion pit depth data is smoothed and features are extracted to identify the shape, area and distribution pattern of the corrosion pits; A three-dimensional corrosion model of the test area is constructed based on the corrosion pit depth data.

[0020] Further, in step S5, the corrosion level assessment includes: The total number of corrosion pits, the maximum depth of corrosion pits, and the average depth of corrosion pits within the survey area were statistically analyzed. Calculate the percentage of the average pit depth to the thickness of the measured metal structural plate and the percentage of the maximum pit depth to the thickness of the measured metal structural plate. According to the preset corrosion level assessment standard, the corrosion status of the test area is assessed as Grade A, Grade B, Grade C or Grade D.

[0021] The beneficial effects of this invention are as follows: This invention replicates the contour of the metal surface being tested by setting an elastic detection probe assembly, and uses a displacement amplification mechanism to convert and amplify the tiny displacement of the probe into a identifiable displacement amount, which is then intelligently identified by an image acquisition component. This achieves automated intelligent perception of the health status of the metal structure surface, with a detection resolution of up to 0.05mm, enabling precise detection of minute surface defects.

[0022] This invention uses a driving component to drive an elastic detection probe component to automatically scan the tested area, realizing rapid and intelligent perception of health status, greatly shortening the detection time of each test area. The detection time for a 300mm by 300mm test area is about 2 minutes, which is 15 times more efficient than the 30 minutes required by the traditional method.

[0023] The terminal device of this invention can receive and process detection data in real time, and automatically perform health status assessment through built-in intelligent algorithms, including health level assessment (A / B / C / D level), three-dimensional model reconstruction, feature extraction and analysis, etc., realizing direct reporting of on-site detection conclusions and visualization of detection results. It eliminates the need for manual data recording and subsequent computer input and calculation, and significantly improves the intelligent assessment capability.

[0024] The invention features a lightweight and flexible overall structure, weighing approximately 10kg, making it easy to carry. It is suitable for intelligent sensing and assessment of the health status of hydraulic metal structures in high-altitude, water-adjacent, or space-constrained locations, and has strong adaptability to various testing environments.

[0025] This invention adopts the principle of mechanical displacement detection, is not affected by ambient light, is not sensitive to adverse factors such as oxide layers and water films on metal surfaces, has high reliability in health status sensing, and has low implementation and maintenance costs, making it suitable for widespread application.

[0026] This invention is applicable to the intelligent sensing and evaluation of the health status of various hydraulic metal structures, such as planar gates, arc gates, flap gates and their hoists, and pressure steel pipes. It has a wide range of applications and provides scientific and technical support for the safe operation and management of hydraulic metal structures. Attached Figure Description

[0027] Figure 1 This is a schematic diagram of the overall structure of an intelligent sensing and evaluation device for the health status of hydraulic metal structures according to a specific embodiment of the present invention. Figure 2 A bottom view of a specific embodiment of the intelligent sensing and evaluation device for the health status of hydraulic metal structures according to the present invention. Figure 3 This is a side sectional view of an intelligent sensing and evaluation device for the health status of hydraulic metal structures according to a specific embodiment of the present invention. Figure 4 This is a schematic diagram illustrating the cooperation between the probe and the wedge-shaped slider according to a specific embodiment of the present invention; Figure 5 This is a top view of a displacement amplification mechanism according to a specific embodiment of the present invention; Figure 6 This is a schematic diagram of a parameter setting interface according to a specific embodiment of the present invention; Figure 7 This is a block diagram illustrating the working principle of one specific embodiment of the present invention; Figure 8 This is a flowchart illustrating a specific embodiment of the intelligent sensing and evaluation method for the health status of hydraulic metal structures according to the present invention.

[0028] The components include: 1. Detection frame; 2. Magnetic suction strip; 3. Elastic detection needle assembly; 4. Displacement amplification mechanism; 5. Image acquisition assembly; 6. Dual-axis linear guide rail; 7. Miniature servo motor; 8. Terminal equipment; 9. Probe; 10. Probe miniature spring; 11. Probe fixing plate; 12. Wedge slider; 13. Wedge slider spring; 14. Wedge slider guide rail frame. Detailed Implementation

[0029] To make the objectives, technical solutions, and beneficial effects of this application clearer, the following detailed description, in conjunction with the accompanying drawings and specific embodiments, further illustrates this application. It should be understood that the specific embodiments described in this specification are merely for explaining this application and are not intended to limit it.

[0030] like Figures 1 to 7 As shown in the figure, the present invention provides an intelligent sensing and evaluation device for the health status of hydraulic metal structures, including a detection frame 1, a magnetic suction strip 2, an elastic detection needle assembly 3, a displacement amplification mechanism 4, an image acquisition assembly 5, a dual-axis linear guide rail 6, a micro servo motor 7, and a terminal device 8.

[0031] Specifically, the detection frame 1 is the outer shell and load-bearing structure of the entire device, used to support and encapsulate all detection components, providing installation space and protection for the internal elastic detection probe assembly 3, displacement amplification mechanism 4, image acquisition assembly 5, dual-axis linear guide rail 6, and micro servo motor 7. The detection frame 1 is made of aluminum alloy, with an overall rectangular shape, and its external dimensions are designed to be 400mm x 400mm x 150mm, with a total weight controlled within 10kg, making it easy for inspection personnel to carry and move.

[0032] Furthermore, magnetic suction strips 2 are located on both sides of the bottom of the detection frame 1, used to fix the entire device to the surface of the metal structure being tested. The magnetic suction strips 2 are made of neodymium iron boron permanent magnet material, with a single magnetic suction strip 2 having an adsorption force of no less than 200N, and two magnetic suction strips 2 together providing an adsorption force of no less than 400N, enabling reliable fixation to the surfaces of various hydraulic metal structures such as gates, hoists, and pressure steel pipes. The magnetic suction strips 2 also include a release switch to allow the entire device to detach from the surface of the metal structure being tested at the end of the test.

[0033] Based on the above basic implementation method, the elastic detection probe assembly 3 is the core detection unit of this invention, used to replicate the contour shape of the tested metal surface. The elastic detection probe assembly 3 consists of 50 independent probes 9, which are integrated together by a probe fixing plate 11 to form a single row of elastic detection probe assemblies 3. The probe fixing plate 11 is used to fix all probes 9, ensuring that they move vertically and do not interfere with each other. The spacing between each independent probe 9 is 6mm, and the 50 probes 9 arranged in a row have a total length of 294mm, which can cover a measurement area width of 300mm by 300mm.

[0034] Furthermore, the probe 9 has a diameter of 1 mm and is made of hard, wear-resistant, and spark-resistant tungsten carbide material. The probe tip is machined into a tiny dome shape with a diameter of 1 mm to reduce secondary scratches on the corroded metal surface and ensure good contact with the bottom of the corrosion pit. Each probe 9 has a boss structure in the middle for housing a probe micro-spring 10. The probe micro-spring 10 provides a constant and moderate contact pressure for each probe 9, designed to be 20g. This ensures that the probe 9 can follow the contour of the metal surface being measured without getting stuck in the rough corrosion pit due to excessive pressure.

[0035] In one specific embodiment, the displacement amplification mechanism 4 is configured in conjunction with the elastic detection needle assembly 3 to convert the small vertical displacement of the probe 9 into a larger horizontal displacement so that the image acquisition assembly 5 can identify it.

[0036] In this embodiment, the displacement amplification mechanism 4 adopts a wedge-shaped slider amplification structure. The tail of each probe 9 is in contact with a wedge-shaped slider 12. The wedge-shaped slider 12 uses the principle of inclined plane to convert the small vertical movement of the probe 9 into a larger horizontal movement of the wedge-shaped slider 12.

[0037] like Figure 4 As shown, based on the geometric relationship of the inclined plane, the horizontal displacement... With vertical displacement The relationship is: ,in It is the inclination angle of the wedge, that is, the horizontal displacement is equal to the vertical displacement removed by the tangent of the inclination angle of the wedge surface.

[0038] In this embodiment, the wedge-shaped slider 12 has a wedge surface inclination angle of 5.7 degrees, and the tangent of this inclination angle is approximately 0.1, which achieves 10x magnification. If the probe 9 produces a 1mm vertical displacement, it is converted into a 10mm horizontal displacement of the wedge-shaped slider 12. The displacement amplification factor of the displacement amplification mechanism 4 is 10x.

[0039] Furthermore, the displacement amplification mechanism 4 also includes a wedge-shaped slider guide frame 14, in which 50 wedge-shaped sliders 12 are integrated. The wedge-shaped slider guide frame 14 is used to constrain the wedge-shaped sliders 12 to move only in the horizontal direction. Each wedge-shaped slider 12 is pushed by a wedge-shaped slider spring 13, making it tightly fit with the tail of the probe 9. The surface of the area where the wedge-shaped slider 12 contacts the probe 9 is machined smoothly to minimize the friction between the wedge-shaped slider 12 and the probe 9.

[0040] In another specific embodiment, each wedge-shaped slider 12 has clearly marked etched lines on its top, and each wedge-shaped slider 12 has a clearly marked 50mm scale with a scale division value of 0.5mm. The image acquisition component 5 is positioned directly above the displacement amplification mechanism 4, and is used to accurately identify the horizontal displacement of the marked scale on each wedge-shaped slider 12 relative to its zero position using an image recognition algorithm. The displacement amplification mechanism 4 has a displacement amplification factor of 10 times, and the scale division value on the top of the wedge-shaped slider 12 is 0.5mm, ultimately achieving a pit detection resolution of 0.05mm.

[0041] In one specific embodiment, the image acquisition component 5 is a slider displacement recognition industrial camera, used to acquire displacement images of each wedge slider 12 and transmit them to the terminal device 8. The image acquisition component 5 uses a 2-megapixel industrial camera with a resolution of 1920 x 1080 and a frame rate of 30fps, which can meet the requirements of real-time detection. The image acquisition component 5 is connected to the terminal device 8 via a USB interface, transmitting the acquired image data to the terminal device 8 for processing in real time.

[0042] Furthermore, the elastic detection needle assembly 3, displacement amplification mechanism 4, and image acquisition assembly 5 are connected into a rigid whole through a linkage frame structure, preventing relative displacement between the three parts. These three units combine to form an integrated module that can move within the detection frame 1. This integrated module is connected and fixed to the dual-axis linear guide rail 6. The X and Y axes of the dual-axis linear guide rail 6 are driven by two micro servo motors 7 to achieve automatic movement of the elastic detection needle assembly 3. The X-axis direction is along one of the linear guide rails, and the Y-axis direction is along the other linear guide rail. The two linear guide rails are perpendicular to each other in the horizontal plane, allowing the elastic detection needle assembly 3 to traverse rows and scan the measured area. The micro servo motors 7 can transmit the absolute position of the elastic detection needle assembly 3 to the terminal device 8 in real time.

[0043] In another specific embodiment, the terminal device 8 is a computer or tablet computer with data analysis software installed. The terminal device 8 is used to receive displacement images transmitted by the image acquisition component 5 and position information fed back by the micro servo motor 7, and calculates the corrosion pit depth data of the measured area based on the displacement images and position information. The data analysis software within the terminal device 8 can receive and store displacement image data from the image acquisition component 5 in real time, while simultaneously recording the corresponding coordinate position information.

[0044] Specifically, the terminal device 8 analyzes the horizontal displacement of the marked scale on each wedge slider 12 relative to its zero position using an image recognition algorithm, and then calculates the vertical displacement of the corresponding probe 9, i.e., the corrosion pit depth value, based on the displacement magnification factor. Combined with the position information fed back by the micro servo motor 7, the terminal device 8 can obtain the coordinate values ​​of different positions within the detection area and the corresponding corrosion pit depth values ​​at each point, thereby constructing complete corrosion detection data.

[0045] Furthermore, terminal device 8 also has data statistical analysis functions. Terminal device 8 can perform statistical analysis on corrosion pit depth data, and draw visualized isodepth maps, depth histograms, frequency statistics charts, etc. Terminal device 8 can also perform comprehensive analysis and smoothing of data, extract features from corrosion areas, and identify features such as the shape, size, and distribution pattern of corrosion pits. Terminal device 8 uses morphological operations such as dilation, erosion, and opening / closing operations to clean up the binarized corrosion pit outlines and fill small holes. Terminal device 8 applies edge detection algorithms to highlight the boundaries of corrosion pits, providing a foundation for subsequent feature description. Terminal device 8 calculates the geometric characteristics of each corrosion pit region, such as area, perimeter, roundness, and ellipse fitting parameters, and analyzes the depth distribution of corrosion pits, including maximum depth, average depth, and depth standard deviation.

[0046] Furthermore, terminal device 8 also features 3D image reconstruction capabilities. Based on the spatial resolution of the corrosion pit depth data, terminal device 8 creates a 2D grid in the world coordinate system, with each grid point corresponding to a depth value. This forms the basic framework of the 3D model. Terminal device 8 uses the depth data to fill in each point in the aforementioned grid, thereby generating a preliminary 3D surface. For missing depth values, interpolation methods can be used to estimate them, ultimately constructing a 3D corrosion model of the survey area.

[0047] In another specific embodiment, the terminal device 8 also has a corrosion level assessment function. The terminal device 8 can assess the corrosion level based on the corrosion pit depth data. The assessment content includes: the total number of corrosion pits within a 300mm x 300mm range; the number of densely packed corrosion pits within a 300mm x 300mm range; the maximum corrosion pit depth within a 300mm x 300mm range; the average corrosion pit depth within a 300mm x 300mm range; the percentage of the average corrosion pit depth within a 300mm x 300mm range to the total plate thickness; and the percentage of the maximum corrosion pit depth within a 300mm x 300mm range to the total plate thickness.

[0048] Furthermore, terminal equipment 8 assesses the corrosion status of the tested components according to relevant standards and specifications, such as the Technical Regulations for Safety Inspection of Hydraulic Steel Gates and Hoists or the Technical Regulations for Safety Inspection of Pressure Steel Pipes. The corrosion status is assessed according to four levels: A, B, C, and D, where A represents slight corrosion, B represents general corrosion, C represents moderate corrosion, and D represents severe corrosion. Terminal equipment 8 can output the corrosion level assessment results on-site in real time, enabling direct reporting of on-site inspection conclusions.

[0049] like Figure 8 As shown, the present invention also provides a method for intelligent sensing and evaluation of the health status of hydraulic metal structures. This method is implemented using the aforementioned intelligent sensing and evaluation device for the health status of hydraulic metal structures and includes the following steps: Step S1: Clean the surface of the test area of ​​the metal structure to be tested, removing the anti-corrosion coating and contaminants.

[0050] Specifically, in step S1, the location of the test area for the metal structure to be tested is first determined, with an area of ​​300mm x 300mm. A grinding tool is used to grind and clean the surface of the test area, removing anti-corrosion coatings, paint, rust products, and contaminants to expose the original surface of the metal structure. The cleaned test area surface should be free of obvious coating residue and debris to ensure the accuracy of the test results.

[0051] Step S2: Place the detection frame 1 above the test area and fix the detection frame 1 to the surface of the metal structure to be tested by the magnetic suction strip 2, so that each probe 9 of the elastic detection probe assembly 3 is in contact with the surface of the metal structure to be tested.

[0052] Specifically, in step S2, the detection frame 1 is placed above the area to be tested, with the bottom of the detection frame 1 aligned with the surface of the area. The magnetic strip 2 at the bottom of the detection frame 1 is used to fix the intelligent sensing and evaluation device for the health status of the hydraulic metal structure to the area being tested, ensuring a firm connection between the device and the surface of the metal structure. When the detection frame 1 contacts the area being tested, the tips of each probe 9 of the elastic detection probe assembly 3 will make close contact with the surface of the metal structure, and the 50 independent probes 9 will replicate the concave and convex states of the corresponding measurement points. All 50 independent probes 9 can follow the contour of the surface of the metal structure being tested. Each probe 9 has a boss structure in the middle for housing a micro-spring 10, providing a constant and moderate contact pressure for each probe 9. This ensures that the probe 9 can follow the contour of the surface without getting stuck in rough pits due to excessive pressure.

[0053] Step S3: The driving component drives the elastic detection needle assembly 3 to scan within the test area. During the scanning process, each probe 9 follows the contour undulation of the surface of the metal structure being tested. The displacement amplification mechanism 4 converts and amplifies the displacement of each probe 9 into the displacement of the corresponding slider.

[0054] Specifically, in step S3, in this embodiment, the displacement amplification mechanism 4 adopts a wedge-shaped slider amplification structure. The tail of each probe 9 is in contact with the wedge-shaped slider 12. The wedge-shaped slider 12 utilizes the principle of inclined plane to convert the small vertical movement of the probe 9 into a larger horizontal movement of the wedge-shaped slider 12. In this embodiment, the wedge-shaped slider 12 has a wedge angle of 5.7 degrees and a displacement amplification factor of 10 times. If the probe 9 produces a vertical displacement of 1 mm, it is converted into a horizontal displacement of 10 mm by the wedge-shaped slider 12.

[0055] Further, in step S3, after clicking the "Start Detection" button on the control panel of the terminal device 8, the X-axis micro servo motor 7 will drive the X-axis of the dual-axis linear guide rail 6 to move at a speed of 10 mm / s, causing the elastic detection probe assembly 3 to scan the surface of the metal structure being tested at a uniform speed. The scanning area length is 300 mm. The X-axis moving speed can be adjusted according to the set value.

[0056] Furthermore, after scanning one test line, the Y-axis micro servo motor 7 drives the Y-axis of the dual-axis linear guide 6 at a speed of 1 mm / s, moving the elastic detection probe assembly 3 1 mm along the Y-axis. The Y-axis movement speed can be adjusted according to a set value. Then, following the same X-axis scanning method, the second test line is scanned. From a microscopic perspective, each probe 9 exhibits an S-shaped motion trajectory. The above actions are repeated 5 times until the test lines overlap. At this point, it means that the elastic detection probe assembly 3 has completed a traversal scan of the 300 mm by 300 mm detection area.

[0057] Step S4: The image acquisition component 5 acquires the displacement images of each slider in real time and transmits the displacement images to the terminal device 8.

[0058] Specifically, in step S4, each wedge slider 12 has clearly marked etched lines on its top, with a clearly marked 50mm graduation of 0.5mm. The image acquisition component 5 is positioned directly above the displacement amplification mechanism 4, and is used to accurately identify the horizontal displacement of each wedge slider 12 relative to its zero position using an image recognition algorithm. The image acquisition component 5 transmits the displacement images of the 50 wedge sliders 12 to the terminal device 8 in real time for acquisition, recording, and analysis. The displacement amplification mechanism 4 has a displacement magnification factor of 10x, and the top graduation of the wedge slider 12 is 0.5mm, ultimately achieving a pit detection resolution of 0.05mm.

[0059] Step S5: The terminal device 8 identifies the displacement of each slider based on the displacement image, combines the position information fed back by the drive component, calculates the corrosion pit depth data at each location in the test area, and evaluates the corrosion level based on the corrosion pit depth data.

[0060] Specifically, in step S5, during the scanning of the elastic detection needle assembly 3, the micro servo motor 7 can transmit the absolute position of the elastic detection needle assembly 3 at each moment to the terminal device 8 in real time. Simultaneously, the image acquisition assembly 5 also transmits images of the displacement of each wedge slider 12 to the terminal device 8 in real time. Finally, the terminal device 8 will acquire the coordinate values ​​of different positions within a 300mm x 300mm detection area, as well as the corresponding pit depth values.

[0061] Further, in step S5, the terminal device 8 uses the corrosion pit depth data to perform statistical analysis and generate visualized isodepth maps, depth histograms, frequency statistics charts, etc. The terminal device 8 performs comprehensive analysis and smoothing of the data, extracts features from the corrosion area, and identifies the shape, size, distribution pattern, and other characteristics of the corrosion pits. The terminal device 8 performs corrosion pit distribution pattern recognition, using cluster analysis to identify the spatial distribution pattern of the corrosion pits, and analyzes the distance statistics between the corrosion pits to understand whether they tend to appear in groups or exist in isolation.

[0062] Furthermore, in step S5, the terminal device 8 performs 3D image reconstruction based on the corrosion pit depth data. A 2D grid is created in the world coordinate system based on the spatial resolution of the corrosion pit depth data, with each grid point corresponding to a depth value. This forms the basic framework of the 3D model. The depth values ​​from the corrosion pit depth data are used to fill in each point in the grid, thereby generating a preliminary 3D surface. For missing depth values, interpolation methods can be used to estimate them, ultimately obtaining a 3D corrosion model of the survey area.

[0063] In step S5, the terminal device 8 also assesses the corrosion level based on the corrosion pit depth data. The terminal device 8 counts the total number of corrosion pits, the maximum pit depth, and the average pit depth within the test area, and calculates the percentage of the average pit depth to the thickness of the tested metal structural plate, as well as the percentage of the maximum pit depth to the thickness of the tested metal structural plate. Based on preset corrosion level assessment standards, the terminal device 8 classifies the corrosion status of the test area as Grade A, Grade B, Grade C, or Grade D. Grade A represents slight corrosion, Grade B represents general corrosion, Grade C represents moderate corrosion, and Grade D represents severe corrosion. The terminal device 8 outputs the corrosion level assessment results in real-time at the testing site, achieving direct reporting of on-site testing conclusions.

[0064] To improve testing accuracy, a test block with a stepped shape and known standard unevenness depth can be fabricated to verify the equipment's performance. Before each test, this test block is used to verify the reliability of the device.

[0065] In summary, the embodiments disclosed herein have at least the following technical effects: This invention replicates the contour of the metal surface being tested by setting an elastic detection probe assembly, and uses a displacement amplification mechanism to convert and amplify the tiny displacement of the probe into a larger displacement of the slider, which is then intelligently identified by an image acquisition component, thereby realizing automated intelligent sensing of the health status of the metal structure with a detection resolution of up to 0.05mm. This invention uses a dual-axis linear guide and a micro servo motor to drive the elastic detection needle assembly to automatically scan the tested area, realizing rapid and intelligent perception of health status, greatly shortening the detection time of each test area. The detection time of a 300mm by 300mm test area is about 2 minutes, which is 15 times more efficient than the 30 minutes required by the traditional method. The terminal device of this invention can receive and process detection data in real time, and automatically assess health status through intelligent algorithms. It realizes direct reporting of on-site detection conclusions and visualization of detection results, eliminating the need for manual data recording and subsequent computer input and calculation, and has a high degree of intelligence. The invention has a lightweight and flexible overall structure, with a total weight of about 10kg, making it easy to carry. It is suitable for intelligent sensing and evaluation of the health status of hydraulic metal structures in high-altitude, water-adjacent, or space-constrained locations, and has strong adaptability to detection environments. This invention adopts the mechanical displacement detection principle, is not affected by ambient light, is not sensitive to adverse factors such as oxide layers and water films on metal surfaces, has high reliability in health status sensing, and has low implementation and maintenance costs, making it suitable for widespread application. This invention is applicable to the intelligent sensing and evaluation of the health status of various hydraulic metal structures, such as planar gates, arc gates, flap gates and their opening and closing mechanisms, and pressure steel pipes. It has a wide range of applications and provides a scientific and technical means for the full life cycle safety management of hydraulic metal structures.

[0066] It is understood that the above embodiments are merely exemplary implementations used to illustrate the principles of the present invention, and the present invention is not limited thereto. For those skilled in the art, various modifications and improvements can be made without departing from the spirit and essence of the present invention, and these modifications and improvements are also considered to be within the scope of protection of the present invention.

Claims

1. A smart sensing and evaluation device for the health status of hydraulic metal structures, characterized in that, include: Detection framework; A magnetic adsorption component is disposed at the bottom of the detection frame to fix the detection frame to the surface of the metal structure being tested during detection. An elastic probe assembly is disposed within the detection frame, including a probe fixing plate and a plurality of probes disposed on the probe fixing plate. Each probe is connected to the probe fixing plate via an elastic element. The probe includes a needle tip for contacting the surface of the metal structure being tested and following the contour undulation of the surface by means of the elastic force of the elastic element. A displacement amplification mechanism, configured to cooperate with the elastic detection needle assembly, includes a slider that cooperates with the tail of each of the probes; An image acquisition component is disposed above the displacement magnification mechanism and is used to acquire the displacement image of the slider; A driving component, connected to the elastic detection needle assembly, is used to drive the elastic detection needle assembly to move within the detection frame; as well as The terminal device is electrically connected to the image acquisition component and the driving component, and is used to receive the displacement image acquired by the image acquisition component and the position information fed back by the driving component, and to calculate the corrosion pit depth data of the measured area based on the displacement image and the position information.

2. The intelligent sensing and evaluation device for the health status of hydraulic metal structures according to claim 1, characterized in that, The multiple probes in the elastic detection probe assembly are arranged in a single row, and the spacing between adjacent probes is a preset spacing value. Each probe has a boss structure in the middle, and the elastic element is a miniature spring sleeved on the probe and abutting against the boss structure. The miniature spring is used to provide a preset elastic pressure to the probe.

3. The intelligent sensing and evaluation device for the health status of hydraulic metal structures according to claim 2, characterized in that, The probe is made of tungsten carbide, and the tip of the probe is machined into a dome shape.

4. The intelligent sensing and evaluation device for the health status of hydraulic metal structures according to claim 1, characterized in that, The slider is a wedge-shaped slider, which uses the principle of inclined plane to convert the vertical displacement of the probe into horizontal displacement; The displacement amplification mechanism further includes a slider guide frame, and the wedge-shaped slider is disposed on the slider guide frame to constrain the wedge-shaped slider to move in the horizontal direction; Each of the wedge-shaped sliders is connected to the slider guide frame via a slider spring, and the slider spring uses elastic force to keep the wedge-shaped slider in contact with the tail of the corresponding probe.

5. The intelligent sensing and evaluation device for the health status of hydraulic metal structures according to claim 4, characterized in that, Each of the wedge-shaped sliders has a scale mark on its top, which is used by the image acquisition component to identify the horizontal displacement of the wedge-shaped slider relative to the zero position; The wedge-shaped slider has a preset tilt angle, so that the displacement amplification factor of the displacement amplification mechanism is a preset amplification factor.

6. The intelligent sensing and evaluation device for the health status of hydraulic metal structures according to any one of claims 1 to 5, characterized in that, The drive assembly includes a dual-axis linear guide and a miniature servo motor for driving the dual-axis linear guide. The elastic detection needle assembly, the displacement amplification mechanism, and the image acquisition assembly are connected by a linkage frame structure to form an integrated module. The integrated module is connected to the dual-axis linear guide rail, so that the integrated module can be moved within the detection frame along the X-axis and Y-axis directions via the dual-axis linear guide rail.

7. A method for intelligent sensing and evaluation of the health status of hydraulic metal structures, characterized in that, The method is implemented using the intelligent sensing and evaluation device for the health status of hydraulic metal structures according to any one of claims 1 to 6, and includes the following steps: S1: Clean the surface of the test area of ​​the metal structure to be tested, removing the anti-corrosion coating and contaminants; S2: Place the detection frame above the test area, and fix the detection frame to the surface of the metal structure to be tested by the magnetic adsorption component, so that each of the probes of the elastic detection probe assembly contacts the surface of the metal structure to be tested. S3: The driving component drives the elastic detection needle assembly to scan within the test area. During the scanning process, each of the probes follows the contour undulation of the surface of the metal structure being tested. The displacement amplification mechanism converts and amplifies the displacement of each probe into the displacement of the corresponding slider. S4: The image acquisition component acquires displacement images of each slider in real time and transmits the displacement images to the terminal device; S5: The terminal device identifies the displacement of each slider based on the displacement image, combines the position information fed back by the drive component, calculates the corrosion pit depth data at each location in the test area, and evaluates the corrosion level based on the corrosion pit depth data.

8. The intelligent sensing and evaluation method for the health status of hydraulic metal structures according to claim 7, characterized in that, In step S3, the driving component drives the elastic detection needle assembly to move according to a preset scanning path, wherein the preset scanning path is: After scanning a measurement line along the X-axis at a preset X-axis moving speed, move a preset step distance along the Y-axis at a preset Y-axis moving speed, and then scan the next measurement line in the opposite direction along the X-axis. Repeat the above process until the entire measurement area is scanned, so that each probe moves in an S-shaped trajectory to traverse the measurement area.

9. The intelligent sensing and evaluation method for the health status of hydraulic metal structures according to claim 7, characterized in that, In step S5, the terminal device is further configured to perform the following processing based on the corrosion pit depth data: Draw isodepth maps, depth histograms, and frequency statistics charts for the survey area; The corrosion pit depth data is smoothed and features are extracted to identify the shape, area and distribution pattern of the corrosion pits; A three-dimensional corrosion model of the test area is constructed based on the corrosion pit depth data.

10. The intelligent sensing and evaluation method for the health status of hydraulic metal structures according to claim 9, characterized in that, In step S5, the corrosion level assessment includes: The total number of corrosion pits, the maximum depth of corrosion pits, and the average depth of corrosion pits within the survey area were statistically analyzed. Calculate the percentage of the average pit depth to the thickness of the measured metal structural plate and the percentage of the maximum pit depth to the thickness of the measured metal structural plate. According to the preset corrosion level assessment standard, the corrosion status of the test area is assessed as Grade A, Grade B, Grade C or Grade D.

Images