A non-destructive testing method and system for the interior of an ancient building wooden structure

Abstract

The present application relates to the technical field of nondestructive testing, in particular to a kind of ancient building wood structure interior nondestructive testing method and system, the present application is by analyzing the propagation wave velocity characteristics of direct wave signal, obtains initial defect region;And by obtaining noise reduction reflection wave signal, the distance of the reflection point of noise reduction reflection wave signal to sensor is analyzed, and new wave velocity normal region is obtained, and then the initial defect region is corrected by new wave velocity normal region, and corrected defect region is obtained;The present application locates defect region preliminarily by direct wave signal, and reflection wave signal carries out defect region correction, innovatively fuses direct wave and reflection wave signal analysis, reconstructs defect geometric boundary, successfully distinguishes star crack defect and cavity defect.In addition, according to the area of corrected defect region, defect grade is divided, and matching maintenance strategy is formulated, which can intuitively display defect, position, size and defect severity and hierarchical maintenance scheme.

Description

Technical Field

[0001] This invention relates to the field of non-destructive testing technology, specifically to a method and system for non-destructive testing of the interior of ancient wooden structures. Background Technology

[0002] Ancient building timber carries irreplaceable information such as history, paintings, and carvings. Traditional drilling and sampling methods can damage the integrity of the wooden structure of ancient buildings, violating the principle of "minimal intervention" in cultural relic protection. Non-destructive testing technology can assess the internal condition without damaging the timber itself, identify defects in a timely manner, and formulate maintenance plans to slow down material deterioration.

[0003] Stress wave testing technology is a non-destructive testing method based on the propagation characteristics of elastic waves in wood. By analyzing the propagation speed, attenuation mode, and path imaging of stress waves, it accurately assesses the internal structural integrity of wood. Its core principle is to use a hammer or pulse device to excite low-frequency stress waves (typically 1-24kHz) on the wood surface. When the waves propagate within the material, encountering defects such as decay, voids, or cracks causes a decrease in wave velocity, energy attenuation, or path deflection. A high-sensitivity sensor array captures the waveform signals, and combined with tomographic imaging algorithms, such as Algebra Reconstruction Technique (ART) or Simultaneous Iterative Reconstruction Technique (SIRT), a two-dimensional / three-dimensional image of the wood's interior is reconstructed, visually displaying the location, extent, and severity of defects.

[0004] However, current stress wave nondestructive testing technology for wood still has the following limitations: Due to the limitations of the imaging mechanism of stress wave testing technology, it can qualitatively depict the macroscopic state of defects, but cannot achieve the sub-millimeter precision of medical CT or industrial X-rays. This results in its detection capability being greatly affected by the shape of the defect. For example, stress wave testing technology can present an approximate geometric shape for blocky defects such as cavities, but in the detection of star-shaped cracks in wood, due to the imaging mechanism of stress wave testing technology, it often misdetects the special structure of star-shaped cracks as blocky defects, making it impossible to effectively distinguish between cavities and star-shaped cracks using this technology. Summary of the Invention

[0005] In order to solve the above technical problems, the purpose of this invention is to provide a non-destructive testing method and system for the interior of ancient wooden structures.

[0006] According to a first aspect of the present invention, a non-destructive testing method for the interior of ancient wooden structures is provided, the specific technical solution of which is as follows:

[0007] Detecting direct and reflected wave signals inside the wooden structure;

[0008] Analyze the propagation velocity characteristics of the direct wave signal inside the wooden structure to obtain the initial defect area inside the wooden structure;

[0009] By analyzing the radial diffusion depth and total energy of the reflected wave signal, the probability that the reflection boundary is a real crack is quantified, and a noise-reduced reflected wave signal is obtained.

[0010] Based on the noise-reduced reflected wave signal, the distance from the reflection point of the noise-reduced reflected wave signal to the sensor is analyzed to obtain the newly added normal wave velocity region.

[0011] The initial defect area is corrected by adding a normal wave velocity area to obtain a corrected defect area inside the wooden structure.

[0012] Based on the area of ​​the defective region to be corrected, the defect level is classified, and a matching maintenance strategy is formulated.

[0013] In some embodiments of the present invention, detecting direct wave signals and reflected wave signals inside the wooden structure includes:

[0014] Twenty-four ring array sensors were evenly spaced around the wooden structure of the ancient building, and 24 automatic electromagnetic pulse generators were simultaneously deployed at the locations of the 24 ring array sensors.

[0015] When one of the automatic electromagnetic pulse generators emits a stress wave, the other 23 sensors detect the direct wave signal, while the sensors at the same location as the automatic electromagnetic pulse generator detect the reflected wave signal.

[0016] In some embodiments of the present invention, analyzing the propagation velocity characteristics of the direct wave signal inside the wooden structure to obtain the initial defect region inside the wooden structure includes:

[0017] Stress waves are emitted sequentially through an automatic electromagnetic pulse generator at each location. The propagation time of the stress waves to the sensors at all other locations is recorded, as well as the straight-line distance of the propagation path of the stress waves to the sensors at all other locations is measured.

[0018] Calculate the propagation wave speed of each propagation path based on the propagation time and the straight-line distance;

[0019] The cross-section of the wooden structure is divided into several pixel grids;

[0020] Based on the propagation wave speeds of all propagation paths, the local wave speed of each pixel grid can be calculated.

[0021] By setting a wave velocity threshold, the initial defect area inside the wooden structure is obtained based on the local wave velocity.

[0022] In some embodiments of the present invention, analyzing the radial diffusion depth of the reflected wave signal includes:

[0023] Stress waves are emitted sequentially through an automatic electromagnetic pulse generator at each location. Reflected wave signals from various directions are received at the same location as the automatic electromagnetic pulse generator. The start time when the sensor begins to receive the reflected wave signal and the end time when the reflected wave signal disappears are recorded.

[0024] The radial diffusion depth of the reflected wave signal is obtained based on the start time and the end time.

[0025] In some embodiments of the present invention, analyzing the total energy of the reflected wave signal includes:

[0026] Within the time range of the start time and the end time, the total energy of the reflected wave signal is obtained based on the amplitude of the reflected wave signal.

[0027] In some embodiments of the present invention, quantizing the probability that the reflection boundary is a real crack to obtain a denoised reflected wave signal includes:

[0028] Based on the radial diffusion depth and the total energy, the probability that the reflecting boundary is a real crack is obtained;

[0029] By setting a probability threshold, a noise-reduced reflected wave signal is obtained based on the probability of the actual crack.

[0030] In some embodiments of the present invention, based on the noise-reduced reflected wave signal, the distance from the reflection point of the noise-reduced reflected wave signal to the sensor is analyzed to obtain a newly added normal wave velocity region, including:

[0031] For each sensor that receives the noise-reduced reflected wave signal, record the emission time of the stress wave of the automatic electromagnetic pulser at the same location as the sensor, and record the start time when the sensor begins to receive the reflected wave signal.

[0032] Based on the emission time and the start time, and combined with the emission wave velocity of the stress wave, the distance from the reflection point of the reflected wave signal to the sensor is obtained.

[0033] Within the cross-sectional area of ​​the wooden structure, a new normal wave velocity region is obtained with the sensor as the center and the distance as the radius.

[0034] In some embodiments of the present invention, based on the area of ​​the defective region being corrected, defect levels are classified, and matching maintenance strategies are formulated, including:

[0035] The area of ​​the correction defect region is normalized to obtain the normalized area of ​​the correction defect region;

[0036] Set a level threshold and divide the severity of the defect in the corrected defect area into three defect levels based on the normalized area.

[0037] Based on the defect level, develop a matching maintenance strategy.

[0038] According to a second aspect of the present invention, a non-destructive testing system for the interior of an ancient wooden structure is provided, comprising: a memory and a processor, wherein:

[0039] The memory is used to store program code;

[0040] The processor is configured to read program code stored in the memory and execute the method described in the first aspect of the present invention.

[0041] In some embodiments of the present invention, the processor includes:

[0042] The signal acquisition module is used to detect direct wave signals and reflected wave signals inside the wooden structure;

[0043] The direct wave signal analysis module is used to analyze the propagation speed characteristics of the direct wave signal inside the wooden structure and obtain the initial defect area inside the wooden structure.

[0044] The reflected wave signal analysis module analyzes the radial diffusion depth and total energy of the reflected wave signal, quantifies the probability that the reflection boundary is a real crack, and obtains a noise-reduced reflected wave signal.

[0045] The defect area correction module is used to analyze the distance from the reflection point of the noise-reduced reflected wave signal to the sensor based on the noise-reduced reflected wave signal to obtain a new normal wave velocity area; and to correct the initial defect area through the new normal wave velocity area to obtain the corrected defect area inside the wooden structure.

[0046] The defect level classification module is used to classify the defect level according to the area of ​​the defect correction area and formulate a matching maintenance strategy.

[0047] Compared with existing technologies, the non-destructive testing method and system for the interior of ancient wooden structures provided by this invention has the following advantages:

[0048] This invention analyzes the propagation velocity characteristics of direct wave signals within a wooden structure to identify the initial defect region. Furthermore, by acquiring denoised reflected wave signals and analyzing the distance from the reflection point to the sensor, a new region with normal wave velocity is obtained. This new region is then used to correct the initial defect region, resulting in a corrected defect region within the wooden structure. This invention innovatively integrates the analysis of direct and reflected wave signals to reconstruct the geometric boundaries of the defects, successfully distinguishing between star-shaped cracks and voids. Additionally, based on the area of ​​the corrected defect region, this invention classifies star-shaped cracks into three levels and develops matching maintenance strategies for each level. This allows for a clear display of the defect's location, size, and severity, as well as a graded maintenance plan matching the severity of the defect. Attached Figure Description

[0049] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0050] Figure 1 A schematic diagram of the basic process of a non-destructive testing method for the interior of an ancient wooden structure provided in an embodiment of the present invention;

[0051] Figure 2 A schematic diagram of an initial defect region obtained by direct wave signal according to an embodiment of the present invention;

[0052] Figure 3 This is a schematic diagram of a newly added normal wave velocity region provided in one embodiment of the present invention;

[0053] Figure 4 This is a schematic diagram of a defect correction area inside a wooden structure provided in an embodiment of the present invention;

[0054] Figure 5 This is a schematic diagram of the basic components of a non-destructive testing system for the interior of an ancient wooden structure, provided as an embodiment of the present invention. Detailed Implementation

[0055] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a non-destructive testing method and system for the interior of ancient wooden structures proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0056] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. Terms such as “comprising,” “including,” or any other variations thereof are intended to cover a non-exclusive inclusion, such that a circuit structure, article, or device comprising a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such article or device. Without further limitation, an element defined by the phrase “comprising one…” does not exclude the presence of additional identical elements in the article or device that includes the element.

[0057] The specific scenario addressed in this invention is as follows: During stress wave testing of cross-sectional defects in wood, for a particular star-shaped crack defect, when the stress wave passes through the crack area, the lack of internal medium causes the wave to detour along the crack, resulting in a longer propagation path. This effect is present in stress wave propagation in all directions, manifesting as a low-velocity, blocky region in the wave velocity distribution diagram. Furthermore, when the wood cross-sectional defect is a cavity, the stress wave cannot pass through the cavity and must travel a longer distance, extending the direct wave propagation time and also resulting in a low-velocity, blocky region within the wood. Therefore, in the traditional stress wave testing of star-shaped cracks in ancient building timber, analyzing the defect area solely through direct wave analysis cannot effectively distinguish between star-shaped crack defects and cavity defects. Therefore, the purpose of this invention is to solve the problem that analyzing the defect area solely through direct wave analysis cannot effectively distinguish between star-shaped crack defects and cavity defects. In an embodiment of the present invention, based on the traditional stress wave detection which only detects the direct wave signal, the reflected wave signal generated when the emitted wave of the automatic electromagnetic pulser encounters the star-shaped crack defect is collected to correct the shape of the defect area.

[0058] The specific scheme of the non-destructive testing method for the interior of ancient wooden structures provided by the present invention will be described in detail below with reference to the accompanying drawings.

[0059] Please see Figure 1 This illustrates the basic process of a non-destructive testing method for the interior of ancient wooden structures provided by an embodiment of the present invention.

[0060] like Figure 1 As shown, an embodiment of the present invention provides a non-destructive testing method for the interior of ancient wooden structures, specifically including:

[0061] S100: Detects direct and reflected wave signals inside the wooden structure.

[0062] Since the painted and carved areas on the wooden surfaces of ancient buildings, surface dust, and ambient temperature and humidity all affect the wave velocity during stress wave defect detection, it is necessary to eliminate the interference of these environmental factors before detecting direct and reflected wave signals. Specifically, the ambient temperature and humidity should be recorded to correct the collected results using prior data; a reversible peak-coupling agent should be applied to the painted and carved areas of the ancient building's wooden surface to ensure a smooth surface; and surface dust should be cleaned with a soft brush to reduce the interference of dust on the collected results.

[0063] After completing the preliminary preparations, signal acquisition devices were deployed to detect direct and reflected wave signals within the wooden structure. Specifically, 24 ring array sensors were evenly spaced around the perimeter of the ancient wooden structure. These sensors, using multi-probe arrays, were designed to capture not only direct wave data but also detect details of micro-reflected waves. Additionally, 24 automatic electromagnetic pulse (AEP) generators were simultaneously deployed at the locations of the 24 ring array sensors. When one AEP generator emitted a stress wave, the remaining 23 sensors detected the direct wave signal, while sensors at the same locations as the AEP generator detected the reflected wave signal.

[0064] S200: Analyze the propagation speed characteristics of the direct wave signal inside the wooden structure to obtain the initial defect area inside the wooden structure.

[0065] The main reason why stress wave technology can measure internal defects in wood is the physical relationship between the change in the propagation speed of stress waves in wood and the wood's density, modulus of elasticity, and internal structural integrity. When a momentary mechanical impact is applied to the surface of wood, a low-frequency stress wave is generated. This stress wave propagates in the wood as a longitudinal wave, and its propagation speed is directly related to the dynamic modulus of elasticity and density.

[0066] Because healthy wood has a uniform internal density and intact structure, stress waves propagate at a high and stable speed within it. However, when internal defects occur in the wood, such as cavities, the propagation of stress waves lacks a continuous medium, forcing them to take a longer route, thus prolonging the propagation time and slowing the speed. Similarly, when star-shaped cracks exist within the wood, they block the propagation path of stress waves, forcing them to take an even longer route, resulting in a reduced propagation speed.

[0067] Based on the above analysis, in the embodiments of the present invention, the initial defect region inside the wooden structure is first obtained by analyzing the propagation velocity characteristics of the direct wave signal inside the wooden structure. That is, direct wave detection is first employed, and by analyzing the propagation velocity characteristics of the direct wave signal inside the wooden structure, wave velocity maps at various locations on the wood cross-section are obtained. The wave velocity anomaly region is then identified through the propagation velocity of the wood cross-section; this region is the initial defect region inside the wooden structure detected by the direct wave. The specific implementation method is as follows:

[0068] First, stress waves are emitted sequentially through an automatic electromagnetic pulse generator at each location. The propagation time of the stress waves to all other sensors is recorded, as well as the straight-line distance of the propagation path of the stress waves to all other sensors is measured. It should be noted that if there are n (24) sensors, then all sensor combinations form... One transmission path.

[0069] Then, based on the propagation time and straight-line distance, the propagation wave speed of each propagation path is calculated as follows:

[0070]

[0071] In the formula, Indicates the first The propagation wave speed along each propagation path; Indicates the first The straight-line distance between the automatic electromagnetic pulse generator and the sensor along the propagation path; Indicates the first The propagation time of each propagation path.

[0072] Then, the cross-section of the wooden structure is divided into several pixel grids, each 1cm in length and width.

[0073] Based on the propagation wave velocities of all propagation paths, the intersection-fitting-based defect detection in woods (IFDD) algorithm is used to inversely deduce the local wave velocity for each pixel grid. This involves solving a large system of linear equations for the wave velocity along each path and optimizing the solution to obtain the local wave velocity for each pixel grid. Based on the local wave velocity of each pixel grid, a wave velocity map of stress wave propagation in the wood cross-section is obtained.

[0074] Finally, a wave velocity threshold is set, which can be 20% of the emitted wave velocity of the stress wave. Based on the local wave velocity, the initial defect region inside the wooden structure is obtained. That is, when the local wave velocity is lower than 20% of the emitted wave velocity of the stress wave, the local wave velocity at that location is set as an abnormal wave velocity. Then, the region composed of the pixel grid corresponding to all abnormal wave velocities is the initial defect region inside the wooden structure. Figure 2The black area in the middle shown is denoted as .

[0075] S300: Analyzes the radial diffusion depth and total energy of the reflected wave signal, quantifies the probability that the reflection boundary is a real crack, and obtains a denoised reflected wave signal.

[0076] To correct the initial defect region obtained through the direct wave signal, it is necessary to further acquire the reflected wave signal caused by the star-shaped crack when the stress wave encounters the star-shaped crack defect region. Since the reflected wave signal is relatively weak and the reflection path is chaotic, it is necessary to calculate the probability that the reflected wave signal is caused by the star-shaped crack reflection, perform noise reduction on the reflected wave signal, eliminate interference from non-star-shaped crack noise signals, and retain only the reflection boundaries with a higher probability of being true defects.

[0077] Since wood rays are the weakest areas of wood, under drying stress, star-shaped cracks extend strictly along the radially arranged parenchyma tissue of the wood rays. Therefore, star-shaped cracks always radiate radially outward from the heartwood. Thus, the deeper the radial propagation of a star-shaped crack, the greater the probability that it is a true star-shaped crack. When a stress wave encounters and is reflected from a star-shaped crack, the deeper the crack, the longer the time it takes for the reflected wave signal to reach the sensor. Therefore, the depth of the star-shaped crack can be indirectly determined by the time it takes for the sensor to receive the reflected wave signal and for the reflected wave signal to end, thereby inferring the probability that the detected reflection boundary is a true crack.

[0078] During the superposition of defect maps, the reflected wave boundaries can be assigned appropriate weights based on the characteristics of the reflected wave defect maps. Firstly, in the reflection process of a star-shaped crack, the greater the rebound intensity of the reflected wave signal, the wider the star-shaped crack. A wider crack indicates a greater material difference between the wood and air at the crack boundary, which determines the impedance of the stress wave. Greater impedance results in a stronger rebound force. In narrow cracks, the stress wave can propagate through the narrow crack, leading to a predominance of projected waves and only partial rebound, thus resulting in a very small rebound intensity. The greater the total energy of the reflected wave signal, the greater the probability that it represents a true star-shaped crack, and vice versa. Therefore, the probability that the detected reflection boundary represents a true star-shaped crack can be determined by the total energy of the reflected wave signal.

[0079] Based on the above analysis, in the embodiments of the present invention, by analyzing the radial diffusion depth and total energy of the reflected wave signal, the probability that the reflection boundary is a real crack is quantified, thereby obtaining a denoised reflected wave signal. Wherein:

[0080] The radial diffusion depth of the reflected wave signal is analyzed using the following method: First, stress waves are emitted sequentially through an automatic electromagnetic pulse generator at each location. Reflected wave signals from each direction are received at the same location as the automatic electromagnetic pulse generator. The start time when the sensor begins receiving the reflected wave signal and the end time when the reflected wave signal disappears are recorded. Then, based on the start and end times, i.e., the time difference between the end and start times, the radial diffusion depth of the reflected wave signal is calculated as follows:

[0081]

[0082] In the formula, Indicates the radial diffusion depth of the reflected wave signal; This indicates the starting moment when the sensor at the same location as the automatic electromagnetic pulse generator that emits stress waves begins to receive the reflected wave signal; This indicates the end time when the sensor receives the reflected wave signal and it disappears.

[0083] The time window from when the sensor receives the reflected wave signal until the reflected wave signal disappears. The longer the time, the deeper the radial propagation depth of the star-shaped crack, and the greater the probability that the reflected boundary detected by its reflected wave signal is a real star-shaped crack.

[0084] The total energy of the reflected wave signal is analyzed by calculating its total energy over a time range between the start and end times, based on the amplitude of the reflected wave signal. More specifically, the reflected wave signal is plotted over the signal reception period. Amplitude variation over time range The curve, due to energy density and amplitude It is proportional to the square of the value, therefore it can be calculated using the following formula during the receiving period. Total energy of the reflected wave signal within the time range for:

[0085]

[0086] In the formula, Indicates during the receiving period The total energy of the reflected wave signal within the time range; Indicates the amplitude of the reflected wave signal; This indicates the starting moment when the sensor at the same location as the automatic electromagnetic pulse generator that emits stress waves begins to receive the reflected wave signal; This indicates the end time at which the sensor receives the reflected wave signal and it disappears. This represents the function that takes the absolute value.

[0087] Indicates the time from when the sensor begins to receive the reflected wave signal. The moment the reflected wave disappears The greater the total energy of the reflected wave signal within the time range, the greater the probability that the reflected boundary detected by the reflected wave signal is a real defect.

[0088] Based on the above analysis, the duration of the reflected wave signal and the total energy of the reflected wave signal within the time window of the reflected wave's appearance are related to the duration of the reflected wave signal's appearance. Both are positively correlated with the probability that the reflection boundary is a real crack. Therefore, quantifying the probability that the reflection boundary is a real crack and obtaining the noise-reduced reflected wave signal is implemented as follows:

[0089] First, based on the radial diffusion depth and total energy, the probability that the reflecting boundary is a real crack is obtained as follows:

[0090]

[0091] In the formula, This represents the probability that the reflected boundary is a real crack; Indicates the radial diffusion depth of the reflected wave signal; Indicates during the receiving period The total energy of the reflected wave signal within the time range; This represents the linear normalization function.

[0092] Then, a probability threshold is set, which can be 0.5. Based on the probability of a real crack, the denoised reflected wave signal is obtained, that is, the probability P that the reflected boundary corresponding to the reflected wave signal is a real crack. If the reflected wave signal is present, it is retained; otherwise, it is treated as a noise reflected wave signal and discarded to obtain a noise-reduced reflected wave signal.

[0093] Thus, the reflected wave signal of the real star-shaped crack, after eliminating noise interference, was obtained.

[0094] S400: Based on the noise-reduced reflected wave signal, analyze the distance from the reflection point of the noise-reduced reflected wave signal to the sensor to obtain the newly added normal wave velocity area.

[0095] By further analyzing the acquired noise-reduced reflected wave signal, the initial defect area detected by the direct wave signal can be further corrected.

[0096] Therefore, in embodiments of the present invention, firstly, based on the noise-reduced reflected wave signal, the distance from the reflection point of the noise-reduced reflected wave signal to the sensor is analyzed to obtain the newly added normal wave velocity region. Specifically, this includes:

[0097] First, for each sensor that receives the noise-reduced reflected wave signal, record the emission time of the stress wave from the automatic electromagnetic pulser at the same location as the sensor, the start time when the sensor begins to receive the reflected wave signal, and the emission wave velocity of the stress wave emitted by the automatic electromagnetic pulser.

[0098] Then, based on the emission time and start time, and combined with the emission velocity of the stress wave, the distance from the reflection point of the reflected wave signal to the sensor is obtained as follows:

[0099]

[0100] In the formula, This indicates the distance from the reflection point of the reflected wave signal to the sensor; Indicates the moment of stress wave emission from the automatic electromagnetic pulse generator; This indicates the starting moment when the sensor at the same location as the automatic electromagnetic pulse generator that emits stress waves begins to receive the reflected wave signal; This indicates the emission velocity of the stress wave emitted by the automatic electromagnetic pulse generator.

[0101] Since the stress wave travels back and forth from the emission point to the sensor where it receives the reflected wave signal, the overall motion path during that time period is divided by 2.

[0102] Finally, within the cross-sectional area of ​​the wooden structure, using the sensor as the center and the distance from the reflection point to the sensor as the radius, the newly added normal wave velocity region is obtained, such as... Figure 3 The sector-shaped region shown is denoted as N.

[0103] S500: Correcting the initial defect area by adding a normal wave velocity area, thus obtaining the corrected defect area inside the wooden structure.

[0104] By adding a normal wave velocity region to correct the initial defect region, a corrected defect region inside the wooden structure is obtained. Specifically, this is achieved by using a sensor that receives a noise-reduced reflected wave signal. Above, a radius of [missing information] can be obtained. The normal range of wood wave velocity is obtained, and all newly acquired normal ranges are used to correct the initial defect area. Specifically, the overlapping area between the initial defect area and the newly acquired normal range is removed, and the remaining initial defect area is the correction defect area inside the wood structure. Figure 4 The black area in the middle shown is denoted as .

[0105] S600: Based on the area of ​​the defective region to be corrected, the defect level is classified and a matching maintenance strategy is developed.

[0106] By obtaining the corrected star-shaped crack defect profile (corrected defect area), the degree of wood damage can be further analyzed. Since the larger the area of ​​the corrected defect area, the smaller the effective load-bearing cross section of the wood and the more significant the stress concentration, the greater the degree of wood damage. Therefore, the degree of wood damage can be graded by the area of ​​the corrected defect area.

[0107] Based on the above analysis, in embodiments of the present invention, defect levels are classified according to the area of ​​the defective region to be corrected, and matching maintenance strategies are formulated. Further aspects include:

[0108] First, obtain the area of ​​the defect region and normalize it to obtain the normalized area of ​​the defect region, denoted as . .

[0109] Then, set the level threshold based on the normalized area. The severity of defects in the corrected area is divided into three defect levels. Specifically, with level thresholds set at 0.4 and 0.7, the three defect levels are as follows: If 0... If so, the wood has a minor defect; if If so, the wood is considered to have a moderate defect; if If so, the wood is considered to have a serious defect.

[0110] Finally, a matching maintenance strategy is formulated based on the defect level. Specifically, different maintenance strategies can be matched based on different defect levels: for areas with minor defects, temperature and humidity sensors are installed to avoid wet-dry cycles; for areas with moderate defects, a hidden tenon reinforcement system can be embedded to avoid changes in appearance; for areas with severe defects, a biomimetic wood structure is implanted through micro-invasive holes to increase load-bearing capacity.

[0111] Please see Figure 5 This illustrates the basic components of a non-destructive testing system for the interior of an ancient wooden structure provided by an embodiment of the present invention.

[0112] like Figure 5 As shown, a non-destructive testing system for the interior of an ancient wooden structure includes: a memory 10 and a processor 20, wherein:

[0113] Memory 10 is used to store program code;

[0114] The processor 20 is used to read the program code stored in the memory 10 and execute the detection of direct wave signals and reflected wave signals inside the wooden structure; analyze the propagation speed characteristics of the direct wave signal inside the wooden structure to obtain the initial defect area inside the wooden structure; analyze the radial diffusion depth and total energy of the reflected wave signal to quantify the probability that the reflection boundary is a real crack and obtain the noise-reduced reflected wave signal; based on the noise-reduced reflected wave signal, analyze the distance from the reflection point of the noise-reduced reflected wave signal to the sensor to obtain the newly added wave speed normal area; correct the initial defect area through the newly added wave speed normal area to obtain the corrected defect area inside the wooden structure; classify the defect level according to the area of ​​the corrected defect area and formulate a matching maintenance strategy.

[0115] Furthermore, the processor 20 includes a signal acquisition module 21, a direct wave signal analysis module 22, a reflected wave signal analysis module 23, a defect area correction module 24, and a defect level classification module 25. Wherein:

[0116] Signal acquisition module 21 is used to detect direct wave signals and reflected wave signals inside the wooden structure;

[0117] The direct wave signal analysis module 22 is used to analyze the propagation speed characteristics of the direct wave signal inside the wooden structure and obtain the initial defect area inside the wooden structure.

[0118] The reflected wave signal analysis module 23 analyzes the radial diffusion depth and total energy of the reflected wave signal, quantifies the probability that the reflection boundary is a real crack, and obtains a noise-reduced reflected wave signal.

[0119] The defect area correction module 24 is used to analyze the distance from the reflection point of the noise-reduced reflected wave signal to the sensor based on the noise-reduced reflected wave signal to obtain a new normal wave velocity area; the initial defect area is corrected by the new normal wave velocity area to obtain the corrected defect area inside the wooden structure.

[0120] The defect level classification module 25 is used to classify defect levels based on the area of ​​the defect correction area and formulate matching maintenance strategies.

[0121] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0122] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

Claims

1. A non-destructive testing method for the interior of a historic timber structure, characterized in that, The method comprises: detecting direct wave signals and reflected wave signals inside the wood structure; analyzing propagation wave velocity characteristics of the direct wave signals inside the wood structure to obtain an initial defect area inside the wood structure; analyzing radial diffusion depth of the reflected wave signals and total energy of the reflected wave signals to quantify a probability of a reflected boundary being a real star-shaped crack and obtain a denoised reflected wave signal; based on the denoised reflected wave signal, analyzing distances of reflection points of the denoised reflected wave signal to sensors to obtain a newly-added wave velocity normal area; correcting the initial defect area through the newly-added wave velocity normal area to obtain a corrected defect area inside the wood structure; dividing a defect level according to an area of the corrected defect area and formulating a matching maintenance strategy; analyzing the radial diffusion depth of the reflected wave signals, comprising: successively transmitting stress waves through automatic electromagnetic pulse devices at each position, receiving reflected wave signals in each direction at the same positions as the automatic electromagnetic pulse devices, recording start times at which the sensors start receiving the reflected wave signals, and recording end times at which the reflected wave signals disappear; according to the start times and the end times, obtaining the radial diffusion depth of the reflected wave signals as: In the formula, represents the radial diffusion depth of the reflected wave signal; represents the start time at which the sensor at the same position as the automatic electromagnetic pulser that transmits the stress wave starts to receive the reflected wave signal; represents the end time at which the sensor receives the reflected wave signal disappears; The longer the time, the deeper the radial propagation depth of the star-shaped crack, and the greater the probability that the reflection boundary detected by the reflection wave signal is the real star-shaped crack. analyzing the total energy of the reflected wave signals, comprising: within a time range of the start times and the end times, obtaining the total energy of the reflected wave signals according to amplitudes of the reflected wave signals as: In the formula, represents the total energy of the reflected wave signal in the receiving period in the time range; represents the amplitude of the reflected wave signal; represents the start time when the sensor at the same position as the automatic electromagnetic pulse transmitter starts to receive the reflected wave signal; represents the end time when the sensor receives the reflected wave signal disappears, represents the absolute value function; represents the time when the reflected wave signal is received from the sensor to the time when the reflected wave disappears the total energy of the reflected wave signal within the time range, the greater the value, the greater the probability that the reflected boundary detected by the reflected wave signal is a real defect; quantifying the probability of the reflected boundary being the real star-shaped crack to obtain the denoised reflected wave signal, comprising: according to the radial diffusion depth and the total energy, obtaining the probability of the reflected boundary being the real star-shaped crack as: wherein represents the probability that the reflection boundary is a real star-shaped crack; represents the radial spread depth of the reflected wave signal; represents the total energy of the reflected wave signal in the reception period in the time range; represents a linear normalization function; setting a probability threshold, and obtaining the denoised reflected wave signal according to the probability of the real star-shaped crack; based on the denoised reflected wave signal, analyzing distances of reflection points of the denoised reflected wave signal to sensors to obtain a newly-added wave velocity normal area, comprising: for each sensor receiving the denoised reflected wave signal, recording a transmission time of a stress wave of an automatic electromagnetic pulse device at the same position as the sensor, and recording a start time at which the sensor starts receiving the reflected wave signal; according to the transmission time and the start time, and in combination with a transmission wave velocity of the stress wave, obtaining the distance of the reflection points of the reflected wave signal to the sensors; within a cross-section range of the wood structure, taking the sensors as centers and the distances as radii to obtain the newly-added wave velocity normal area.

2. The method for non-destructive testing of the interior of a historic timber structure according to claim 1, characterized in that, detecting direct wave signals and reflected wave signals inside the wood structure, comprising: equidistantly arranging 24 ring array sensors around the wood structure of the ancient building, and synchronously deploying 24 automatic electromagnetic pulse devices at positions of the 24 ring array sensors; when one of the automatic electromagnetic pulse devices transmits a stress wave, the remaining 23 sensors detect direct wave signals, and the sensor at the same position as the automatic electromagnetic pulse device detects a reflected wave signal.

3. The method according to claim 2, wherein, analyzing propagation wave velocity characteristics of the direct wave signals inside the wood structure to obtain an initial defect area inside the wood structure, comprising: successively transmitting stress waves through automatic electromagnetic pulse devices at each position, recording propagation times of the stress waves to reach sensors at all other positions, and measuring straight line distances of propagation paths of the stress waves to reach the sensors at all other positions; According to the propagation time and the straight-line distance, the propagation wave speed of each propagation path is calculated; The wood structure section is divided into a plurality of pixel grids; According to the propagation wave speed of all propagation paths, the local wave speed of each pixel grid is back calculated; A wave speed threshold is set, and according to the local wave speed, an initial defect area inside the wood structure is obtained.

4. The method for non-destructive testing of the interior of a historic timber structure according to claim 1, characterized in that, According to the area of the corrected defect area, the defect grade is divided, and the matching maintenance strategy is formulated, including: The area of the corrected defect area is normalized to obtain the normalized area of the corrected defect area; A grade threshold is set, and according to the normalized area, the defect severity of the corrected defect area is divided into three defect grades; According to the defect grade, the matching maintenance strategy is formulated.

5. A non-destructive testing system for the interior of a historic timber structure, characterized in that The system comprises a memory and a processor, wherein: The memory is used to store program code; The processor is used to read the program code stored in the memory and execute the method according to any one of claims 1 to 4.

6. The system for non-destructive testing of the interior of a historic timber structure according to claim 5, characterized in that, The processor comprises: A signal acquisition module is used to detect the direct wave signal and the reflected wave signal inside the wood structure; A direct wave signal analysis module is used to analyze the propagation wave speed characteristics of the direct wave signal inside the wood structure, and obtain an initial defect area inside the wood structure; A reflected wave signal analysis module is used to analyze the radial diffusion depth of the reflected wave signal and the total energy of the reflected wave signal, quantify the probability of the reflected boundary being a real star-shaped crack, and obtain a denoised reflected wave signal; A defect area correction module is used to analyze the distance from the reflection point of the denoised reflected wave signal to the sensor based on the denoised reflected wave signal, obtain a new wave speed normal area, correct the initial defect area through the new wave speed normal area, and obtain a corrected defect area inside the wood structure; A defect grade division module is used to divide the defect grade according to the area of the corrected defect area, and formulate the matching maintenance strategy.

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