Nondestructive testing method and system for interior of ancient building wood structure

Abstract

The invention relates to the technical field of nondestructive testing, in particular to an ancient building wood structure interior nondestructive testing method and system.The method includes the steps that an initial defect area is obtained by analyzing propagation wave velocity characteristics of direct wave signals; acquiring a noise reduction reflection wave signal, analyzing the distance from a reflection point of the noise reduction reflection wave signal to the sensor to obtain a newly added wave velocity normal area, and correcting the initial defect area through the newly added wave velocity normal area to obtain a corrected defect area; according to the method, the defect area is preliminarily positioned through the direct wave signal, the defect area is corrected through the reflected wave signal, the direct wave and reflected wave signal analysis is creatively fused, the geometric boundary of the defect is reconstructed, and the star-shaped crack defect and the cavity defect are successfully distinguished. Besides, according to the area of the corrected defect area, defect grades are divided, and a matched maintenance strategy is formulated, so that the defects, positions, sizes, defect severity and graded maintenance schemes can be visually displayed.

Description

Technical Field

[0001] The present invention relates to the technical field of non-destructive testing, and in particular to a method and system for non-destructive testing of the interior of a wooden structure of an ancient building. Background Art

[0002] The timber of ancient buildings carries non-renewable information, including history, paintings, and carvings. Traditional drilling and sampling methods can damage the integrity of ancient wooden structures and violate the principle of minimal intervention in cultural heritage preservation. Non-destructive testing technology can assess the internal condition of ancient buildings without damaging the original structure. Promptly identifying defects allows for the development of maintenance plans and slows material degradation.

[0003] Stress wave testing technology is a nondestructive testing method based on the propagation characteristics of elastic waves in wood. By analyzing the propagation velocity, attenuation pattern, 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. As the waves propagate within the material, defects such as decay, voids, or cracks will cause the wave velocity to decrease, the energy to decay, or the path to be deflected. By capturing waveform signals through a high-sensitivity sensor array and combining them with tomography algorithms such as the Algebra Reconstruction Technique (ART) or the Simultaneous Iterative Reconstruction Technique (SIRT), a 2D / 3D 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 drawbacks: Due to the limitations of the stress wave imaging mechanism, current stress wave testing technology can qualitatively depict the macroscopic state of defects, but it cannot achieve the submillimeter accuracy of medical CT or industrial X-rays, resulting in its detection ability being significantly affected by the shape of the defect. For example, stress wave testing technology can present a similar geometric shape for block-shaped defects such as voids. However, when detecting star-shaped cracks in wood, due to the stress wave imaging mechanism, the unique structure of star-shaped cracks is often mistakenly detected as a block-shaped defect, making it impossible to effectively distinguish between voids and star-shaped cracks using this detection technology. Summary of the Invention

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

[0006] According to a first aspect of an embodiment of the present invention, a method for non-destructive testing of the interior of a wooden structure of an ancient building is provided, and the technical solution adopted is as follows: Detect direct wave signals and reflected wave signals inside wooden structures; Analyzing the propagation velocity characteristics of the direct wave signal inside the wooden structure to obtain the initial defect area inside the wooden structure; Analyzing the radial diffusion depth and the total energy of the reflected wave signal, quantifying the probability that the reflecting boundary is a real crack, and obtaining a de-noised reflected wave signal; Based on the noise reduction reflected wave signal, analyzing the distance from the reflection point of the noise reduction reflected wave signal to the sensor to obtain a newly added normal wave velocity area; Correcting the initial defective area by using the newly added normal wave velocity area to obtain a corrected defective area inside the wooden structure; According to the area of ​​the defect area to be corrected, the defect level is divided and a matching maintenance strategy is formulated.

[0007] In some embodiments of the present invention, detecting a direct wave signal and a reflected wave signal inside a wooden structure includes: 24 circular array sensors were evenly spaced around the ancient building, and 24 automatic electromagnetic pulsers were simultaneously deployed at the locations of the 24 circular array sensors; When one of the automatic electromagnetic pulsers emits a stress wave, the remaining 23 sensors detect the direct wave signal, and the sensors at the same location as the automatic electromagnetic pulser detect the reflected wave signal.

[0008] 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 area inside the wooden structure includes: sequentially emitting stress waves through the automatic electromagnetic pulser at each position, recording the propagation time of the stress waves to the sensors at all other positions, and measuring the straight-line distance of the propagation path of the stress waves to the sensors at all other positions; Calculating the propagation wave velocity of each propagation path according to the propagation time and the straight-line distance; Divide the wooden structure cross section into several pixel grids; According to the propagation wave speed of all propagation paths, the local wave speed of each pixel grid is obtained by reverse calculation; A wave velocity threshold is set, and an initial defect area inside the wood structure is obtained according to the local wave velocity.

[0009] In some embodiments of the present invention, analyzing the radial diffusion depth of the reflected wave signal includes: The stress wave is emitted by the automatic electromagnetic pulser at each position in turn, and the reflected wave signals in various directions are received at the same position as the automatic electromagnetic pulser, and the start time when the sensor starts to receive the reflected wave signal and the end time when the reflected wave signal disappears are recorded; The radial diffusion depth of the reflected wave signal is obtained according to the start time and the end time.

[0010] In some embodiments of the present invention, analyzing the total energy of the reflected wave signal includes: Within a time range between the start time and the end time, the total energy of the reflected wave signal is obtained according to the amplitude of the reflected wave signal.

[0011] In some embodiments of the present invention, quantifying the probability that a reflecting boundary is a real crack and obtaining a noise-reduced reflected wave signal includes: Obtaining a probability that the reflection boundary is a real crack according to the radial diffusion depth and the total energy; A probability threshold is set, and a noise-reduced reflected wave signal is obtained according to the probability of the real crack.

[0012] In some embodiments of the present invention, analyzing 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 newly added normal wave velocity area includes: For each sensor receiving the noise-reduced reflected wave signal, recording the emission time of the stress wave of the automatic electromagnetic pulser at the same location as the sensor, and recording the start time of the sensor starting to receive the reflected wave signal; According to the emission time and the start time, 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; Within the cross-section of the wooden structure, with the sensor as the center and the distance as the radius, a newly added normal wave velocity area is obtained.

[0013] In some embodiments of the present invention, the defect level is divided according to the area of ​​the corrected defect area, and a matching maintenance strategy is formulated, including: Normalizing the area of ​​the corrected defect region to obtain a normalized area of ​​the corrected defect region; Setting a level threshold and dividing the defect severity of the corrected defect area into three defect levels according to the normalized area; According to the defect level, a matching maintenance strategy is formulated.

[0014] According to a second aspect of an embodiment of the present invention, a non-destructive detection system for the interior of a wooden structure of an ancient building is provided, comprising: a memory and a processor, wherein: The memory is used to store program code; The processor is configured to read the program code stored in the memory and execute the method described in the first aspect of the embodiment of the present invention.

[0015] In some embodiments of the present invention, the processor includes: Signal acquisition module, used to detect direct wave signals and reflected wave signals inside the wooden structure; a direct wave signal analysis module, configured to analyze the propagation velocity characteristics of the direct wave signal within the wood structure and obtain an initial defect area within the wood structure; a reflected wave signal analysis module, which analyzes the radial diffusion depth and the total energy of the reflected wave signal, quantifies the probability that the reflecting boundary is a real crack, and obtains a de-noised reflected wave signal; a defect area correction module for analyzing 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 newly added normal wave velocity area; and correcting the initial defect area using the newly added normal wave velocity area to obtain a corrected defect area inside the wooden structure; The defect grade classification module is used to classify the defect grades according to the area of ​​the defect correction area and formulate a matching maintenance strategy.

[0016] Compared with the existing technology, the present invention provides a method and system for non-destructive testing of the interior of the wooden structure of an ancient building, which has the following beneficial effects: The present invention obtains the initial defect area within the wooden structure by analyzing the propagation velocity characteristics of the direct wave signal within the wooden structure. Furthermore, by obtaining the noise-reduced reflected wave signal and analyzing the distance from the reflection point of the noise-reduced reflected wave signal to the sensor, a new normal velocity area is obtained. The initial defect area is then corrected using the new normal velocity area to obtain a corrected defect area within the wooden structure. The present invention uses the direct wave signal to initially locate the defect area and the reflected wave signal to correct the defect area. This innovative integration of direct and reflected wave signal analysis reconstructs the defect geometric boundary and successfully distinguishes between star-shaped crack defects and cavity defects. Furthermore, the present invention classifies the defect grade of star-shaped cracks into three levels based on the area of ​​the corrected defect area, and formulates a matching maintenance strategy for the defect grade classification. This strategy can intuitively display the defect, location, size, and severity of the defect, as well as a graded maintenance plan that matches the severity of the defect. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0018] Figure 1 A schematic diagram of the basic process of a non-destructive testing method for the interior of a wooden structure of an ancient building provided by one embodiment of the present invention; Figure 2A schematic diagram of an initial defect area obtained through a direct wave signal provided by an embodiment of the present invention; Figure 3 A schematic diagram of a newly added normal wave velocity area provided by one embodiment of the present invention; Figure 4 A schematic diagram of a defect correction area inside a wooden structure provided by one embodiment of the present invention; Figure 5 A schematic diagram of the basic components of a non-destructive testing system for the interior of a wooden structure of an ancient building provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0019] To further illustrate the technical means and effectiveness of the present invention in achieving its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, describes in detail a method and system for nondestructive testing of the interior of a historic building's wooden structure, including its specific implementation, structure, features, and effectiveness. In the following description, references to "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.

[0020] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this invention pertains. Terms such as "comprises," "comprising," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a circuit structure, article, or device comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such article or device. In the absence of further limitations, the phrase "comprising a ..." to define an element does not preclude the presence of other identical elements in the article or device comprising the element.

[0021] The specific scenario targeted by the embodiment of the present invention is: in the process of stress wave detection of wood cross-sectional defects, for special star-shaped crack defects, when the stress wave passes through the crack area, the medium in the crack is missing. At this time, the wave will detour along the crack, causing the propagation path of the stress wave to become longer, and this similar effect occurs during the propagation of stress waves in all directions. A block-shaped area with low speed in the center will appear in the wave velocity distribution diagram. In addition, when the wood cross-sectional defect is a cavity defect, since the stress wave cannot pass through the cavity, it must detour a longer distance, resulting in a longer direct wave propagation time, and a low-speed block-shaped area will also appear inside the wood. Therefore, in the process of detecting star-shaped cracks in ancient building wood by traditional stress wave detection methods, it is impossible to effectively distinguish the difference between star-shaped crack defects and cavity defects by only analyzing the defect area through direct waves. Therefore, the purpose of the embodiment of the present invention is to solve the problem that it is impossible to effectively distinguish the difference between star-shaped crack defects and cavity defects by only analyzing the defect area through direct waves. In an embodiment of the present invention, based on the traditional stress wave detection of only direct wave signals, the reflected wave signals generated when the automatic electromagnetic pulser transmits waves encountering star-shaped crack defects are collected to correct the shape of the defect area.

[0022] The following describes in detail a specific solution of a non-destructive testing method for the interior of a wooden structure of an ancient building provided by the present invention in conjunction with the accompanying drawings.

[0023] See also Figure 1 , which shows the basic process of a non-destructive testing method for the interior of an ancient building's wooden structure provided by an embodiment of the present invention.

[0024] like Figure 1 As shown, an embodiment of the present invention provides a method for non-destructive testing of the interior of a wooden structure of an ancient building, specifically comprising: S100: Detect direct wave signals and reflected wave signals inside the wooden structure.

[0025] Because the painted and carved areas of ancient timber, surface dust, and ambient temperature and humidity all affect the velocity of stress wave defects, prior preparation is required to eliminate these environmental factors before testing direct and reflected waves. Specifically, the ambient temperature and humidity are recorded to allow for correction of the collected results using prior data. A reversible peak wax coupling agent is applied to the painted and carved areas of the timber to ensure a smooth surface. Finally, dust is removed with a soft brush to minimize dust interference with the collected results.

[0026] After completing the preliminary preparations, the signal acquisition equipment was deployed to detect direct and reflected wave signals within the wooden structure. Specifically, 24 circular array sensors were evenly spaced around the timber structure. These sensors used multi-probe array sensors, which not only capture direct wave data but also detect micro-reflection wave details. Furthermore, 24 automatic electromagnetic pulsers were deployed simultaneously at the positions of the 24 circular array sensors. When one of the automatic electromagnetic pulsers emits a stress wave, the remaining 23 sensors detect the direct wave signal, while the sensors in the same position as the automatic electromagnetic pulser detect the reflected wave signal.

[0027] S200: Analyze the propagation velocity characteristics of the direct wave signal inside the wooden structure to obtain the initial defect area inside the wooden structure.

[0028] The ability of stress wave technology to measure internal defects in wood stems primarily from the physical relationship between changes in the velocity of stress waves propagating through wood and its density, elastic modulus, and internal structural integrity. When a momentary mechanical impact is applied to the wood surface, a low-frequency stress wave is generated. This stress wave propagates through the wood as a longitudinal wave, with its propagation velocity directly related to the dynamic elastic modulus and density.

[0029] Because healthy wood has a uniform density and intact structure, stress waves propagate at a high and stable velocity. However, when internal defects, such as cavities, occur within the wood, the stress waves propagate without the continuity of the medium. They must traverse a certain path, resulting in a longer propagation time and slower propagation speed. Similarly, when defects such as star-shaped cracks are present within the wood, they block the stress wave's propagation path, forcing the stress wave to traverse a longer path, which also manifests as a decrease in propagation speed.

[0030] Based on the above analysis, in an embodiment of the present invention, the initial defect area within the wood structure is first determined by analyzing the propagation velocity characteristics of the direct wave signal within the wood structure. Specifically, direct wave detection is first employed, and by analyzing the propagation velocity characteristics of the direct wave signal within the wood structure, a velocity map is obtained for each location on the wood cross section. The propagation velocity of the wood cross section is used to determine the region of abnormal velocity, which is the initial defect area within the wood structure detected by the direct wave. The specific implementation method is as follows: First, the stress wave is emitted by the automatic electromagnetic pulser at each position in turn, and the propagation time of the stress wave to the sensors at all other positions is recorded, and the straight-line distance of the propagation path of the stress wave to the sensors at all other positions is measured. It should be noted that if there are n (24) sensors at this time, all the sensors are combined to form a total of transmission paths.

[0031] Then, based on the propagation time and straight-line distance, the propagation wave speed of each propagation path is calculated as:

[0032] Where, Indicates the The propagation wave speed along the propagation path; Indicates the The straight-line distance between the automatic electromagnetic pulser and the sensor along the propagation path; Indicates the The propagation time of a propagation path.

[0033] Then, the cross section of the wooden structure is divided into several pixel grids with a length and width of 1 cm.

[0034] The intersection-fitting-based defect detection in woods (IFDD) algorithm uses the propagation velocity of all propagation paths to infer the local velocity of each pixel grid. This involves solving the velocity of each path in a large linear system of equations and performing an optimization to obtain the local velocity of each pixel grid. Based on the local velocity of each pixel grid, a velocity map of the stress wave propagating through the wood cross-section is obtained.

[0035] Finally, the wave velocity threshold is set, which can be 20% of the stress wave emission velocity. According to the local wave velocity, the initial defect area inside the wood structure is obtained. That is, when the local wave velocity is lower than 20% of the stress wave emission velocity, the local wave velocity at that location is set as the abnormal wave velocity. The area composed of pixel grids corresponding to all abnormal wave velocities is the initial defect area inside the wood structure, as shown in the following example: Figure 2 The middle black area shown is .

[0036] S300: Analyze the radial diffusion depth and total energy of the reflected wave signal, quantify the probability that the reflecting boundary is a real crack, and obtain a de-noised reflected wave signal.

[0037] To correct the initial defect region identified by the direct wave signal, it is necessary to further obtain the reflected wave signal caused by the star-shaped crack when the stress wave encounters the star-shaped crack defect region. Because the reflected wave signal is relatively weak and the reflection path is complex, it is necessary to estimate the probability that the reflected wave signal is caused by the star-shaped crack reflection. This is done by denoising the reflected wave signal to eliminate the interference of non-star-shaped crack noise signals and retain only the reflecting boundary with a high probability of being a true defect.

[0038] Because rays are the weakest areas of wood, star-shaped cracks extend strictly along the radially arranged ray parenchyma under drying stress. Therefore, star-shaped cracks spread radially from the center of the tree. Therefore, 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 is reflected by a star-shaped crack, the deeper the crack, the longer it takes for the reflected wave signal to reach the sensor. Therefore, the time from the start of the sensor's reception of the reflected wave signal to the end of the reflected wave signal can be used to indirectly determine the depth of the star-shaped crack, and based on this, the probability that the reflected wave boundary detected by the reflected wave signal is a true crack can be inferred.

[0039] During the defect map overlay process, the reflected wave boundaries can be assigned corresponding weights based on the characteristics of the reflected wave defect map. First, during the reflection process of the reflected wave signal from a star-shaped crack, the greater the reflected wave signal's rebound intensity, the wider the star-shaped crack. The wider the width, the greater the material difference between the wood and the air at the crack boundary of the stress wave signal. This material difference determines the impedance of the stress wave. The greater the impedance, the greater the rebound force of the stress wave. In narrow cracks, the stress wave can continue to propagate through the narrow crack, resulting in a predominantly projected wave, with only a partial rebound, resulting in minimal rebound intensity. The greater the total energy of the reflected wave signal, the greater the probability that it is a true star-shaped crack, and vice versa. Therefore, the total energy of the reflected wave signal can be used to determine the probability that the reflection boundary detected by the reflected wave signal is a true star-shaped crack.

[0040] Based on the above analysis, in an embodiment of the present invention, the radial diffusion depth of the reflected wave signal and the total energy of the reflected wave signal are analyzed to quantify the probability that the reflecting boundary is a real crack and obtain a de-noised reflected wave signal. The specific method for analyzing the radial diffusion depth of the reflected wave signal is as follows: First, a stress wave is emitted by the automatic electromagnetic pulser at each location in turn. The reflected wave signals in various directions are received at the same location as the automatic electromagnetic pulser. 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. Then, based on the start and end times (that is, the time difference between the end time and the start time), the radial diffusion depth of the reflected wave signal is calculated as:

[0041] Where, Indicates the radial diffusion depth of the reflected wave signal; Indicates the time when the sensor at the same position as the automatic electromagnetic pulser that emits the stress wave begins to receive the reflected wave signal; Indicates the end time when the reflected wave signal received by the sensor disappears.

[0042] It is the time window from when the sensor receives the reflected wave signal until the reflected wave signal disappears. The longer the time is, the deeper the radial diffusion depth of the star-shaped crack is, and the greater the probability that the reflection boundary detected by its reflected wave signal is a real star-shaped crack.

[0043] The total energy of the reflected wave signal is analyzed. The specific implementation method is: within the time range of the start time and the end time, the total energy of the reflected wave signal is obtained according to the amplitude of the reflected wave signal. More specifically, the total energy of the reflected wave signal during the signal receiving period is plotted. Amplitude changes within a time frame curve, due to the energy density and amplitude The square of is proportional to the value of the receiver, so the following formula can be used to calculate the value of the receiver in the receiving cycle: The total energy of the reflected wave signal within the time range for:

[0044] Where, Indicates that during the receiving cycle The total energy of the reflected wave signal within the time range; Indicates the amplitude of the reflected wave signal; Indicates the time when the sensor at the same position as the automatic electromagnetic pulser that emits the stress wave begins to receive the reflected wave signal; Indicates the end time when the reflected wave signal received by the sensor disappears. Represents the absolute value function.

[0045] Indicates the time when the reflected wave signal is received from the sensor When the reflected wave disappears The total energy of the reflected wave signal within the time range of , the larger the value, the greater the probability that the reflecting boundary detected by the reflected wave signal is a real defect.

[0046] Through the above analysis, due to the duration of the reflected wave signal, and the total energy of the reflected wave signal within the time window of the reflected wave, They are all positively correlated with the probability that the reflecting boundary is a real crack. Therefore, the probability that the reflecting boundary is a real crack is quantified to obtain the noise-reduced reflected wave signal. The specific implementation method is as follows: First, based on the radial diffusion depth and total energy, the probability that the reflection boundary is a real crack is obtained as:

[0047] Where, represents the probability that the reflecting boundary is a real crack; Indicates the radial diffusion depth of the reflected wave signal; Indicates that during the receiving cycle The total energy of the reflected wave signal within the time range; represents the linear normalization function.

[0048] Then, the probability threshold is set, which can be 0.5. According to the probability of a real crack, the noise-reduced reflected wave signal is obtained, that is, when the reflection boundary corresponding to the reflected wave signal is the probability P of a real crack, When , the reflected wave signal is retained, otherwise it is regarded as a noise reflected wave signal and removed to obtain a noise-reduced reflected wave signal.

[0049] At this point, the reflected wave signal of the real star-shaped crack with noise interference eliminated is obtained.

[0050] S400: Based on the noise reduction reflected wave signal, a distance from a reflection point of the noise reduction reflected wave signal to a sensor is analyzed to obtain a newly added normal wave velocity area.

[0051] By further analyzing the obtained noise-reduced reflected wave signal, the initial defect area detected by the direct wave signal can be further corrected.

[0052] Therefore, in an embodiment of the present invention, firstly, based on the noise reduction reflected wave signal, the distance from the reflection point of the noise reduction reflected wave signal to the sensor is analyzed to obtain a newly added normal wave velocity area. Specifically, the analysis includes: First, for each sensor that receives the noise-reduced reflected wave signal, the emission time of the stress wave of the automatic electromagnetic pulser at the same position as the sensor is recorded, the start time when the sensor starts to receive the reflected wave signal is recorded, and the emission wave velocity of the stress wave emitted by the automatic electromagnetic pulser is recorded.

[0053] Then, based on the emission time and start time, 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 as:

[0054] Where, Indicates the distance from the reflection point of the reflected wave signal to the sensor; Indicates the emission time of the stress wave of the automatic electromagnetic pulser; Indicates the time when the sensor at the same position as the automatic electromagnetic pulser that emits the stress wave begins to receive the reflected wave signal; Indicates the emission wave velocity of the stress wave emitted by the automatic electromagnetic pulser.

[0055] Since the stress wave travels back and forth from the emission point to the sensor receiving the reflected wave signal, the overall motion path during this period of time is divided by 2.

[0056] Finally, within the cross section of the wooden structure, with the sensor as the center and the distance from the reflection point to the sensor as the radius, the newly added normal wave velocity area is obtained, such as Figure 3 The sector-shaped area shown is denoted as N.

[0057] S500: The initial defect area is corrected by adding a normal wave velocity area to obtain a corrected defect area inside the wooden structure.

[0058] The initial defect area is corrected by adding a normal wave velocity area to obtain the corrected defect area inside the wooden structure. On the above, we can get the radius of The normal area of ​​wood wave velocity is obtained, and all the newly acquired normal wave velocity areas are used to correct the initial defect area. Specifically, the area in the initial defect area that overlaps with the newly acquired normal wave velocity area is removed, and the remaining initial defect area is the corrected defect area inside the wood structure, such as Figure 4 The middle black area shown is .

[0059] S600: Defect levels are classified based on the area of ​​the corrected defect area, and a matching maintenance strategy is formulated.

[0060] The corrected star-shaped crack defect contour (corrected defect area) obtained can be used to further analyze the degree of wood damage. Since the larger the area of ​​the corrected defect area, the smaller the effective load-bearing cross-section of the wood, the more significant the stress concentration, and the greater the degree of wood damage, the degree of wood damage can be graded according to the area of ​​the corrected defect area.

[0061] Based on the above analysis, in the embodiment of the present invention, the defect level is divided according to the area of ​​the corrected defect area, and a matching maintenance strategy is formulated. Further including: First, the area of ​​the corrected defect region is obtained and normalized to obtain the normalized area of ​​the corrected defect region, which is recorded as .

[0062] Then, set the level threshold according to the normalized area , the severity of the defect in the corrected defect area is divided into three defect levels. Specifically, the level thresholds are set to 0.4 and 0.7, and the three defect levels are: , the wood is slightly defective; if , the wood is moderately defective; if , the wood is seriously defective.

[0063] Finally, a maintenance strategy is developed based on the defect level. Specifically, different maintenance strategies are applied based on the defect level: for areas with minor defects, temperature and humidity sensors are installed to prevent dry-wet cycles; for areas with moderate defects, a hidden mortise and tenon reinforcement system can be embedded to prevent changes in appearance; for areas with severe defects, a bionic wood structure is implanted through minimally invasive holes to increase load capacity.

[0064] See also Figure 5 , which shows the basic composition of a non-destructive testing system for the interior of a wooden structure of an ancient building provided by an embodiment of the present invention.

[0065] like Figure 5 As shown, a non-destructive testing system for the interior of a wooden structure of an ancient building includes: a memory 10 and a processor 20, wherein: Memory 10, for storing program code; The processor 20 is used to read the program code stored in the memory 10 and execute the detection of the direct wave signal and the reflected wave signal inside the wooden structure; analyze the propagation wave velocity 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 of the reflected wave signal and the total energy of the reflected wave signal, 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 a newly added normal wave velocity area; correct the initial defect area by using the newly added normal wave velocity area to obtain a 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.

[0066] 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. Among them: Signal acquisition module 21, used to detect direct wave signals and reflected wave signals inside the wooden structure; The direct wave signal analysis module 22 is used to analyze the propagation velocity characteristics of the direct wave signal inside the wooden structure and obtain the initial defect area inside the wooden structure; The reflected wave signal analysis module 23 analyzes the radial diffusion depth and the total energy of the reflected wave signal, quantifies the probability that the reflecting boundary is a real crack, and obtains a de-noised reflected wave signal; The defect area correction module 24 is configured to analyze the distance from the reflection point of the de-noised reflected wave signal to the sensor based on the de-noised reflected wave signal to obtain a newly added normal wave velocity area; and to correct the initial defect area using the newly added normal wave velocity area to obtain a corrected defect area inside the wooden structure. The defect grade classification module 25 is used to classify the defect grades according to the area of ​​the defect correction region and formulate a matching maintenance strategy.

[0067] It should be noted that the order in which the embodiments of the present invention are described above is for illustrative purposes only and does not necessarily represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0068] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.

Claims

1. A non-destructive testing method for the interior of a wooden structure of an ancient building, characterized in that: The method comprises: Detect direct wave signals and reflected wave signals inside wooden structures; Analyzing the propagation velocity characteristics of the direct wave signal inside the wooden structure to obtain the initial defect area inside the wooden structure; Analyzing the radial diffusion depth and the total energy of the reflected wave signal, quantifying the probability that the reflecting boundary is a real crack, and obtaining a de-noised reflected wave signal; Based on the noise reduction reflected wave signal, analyzing the distance from the reflection point of the noise reduction reflected wave signal to the sensor to obtain a newly added normal wave velocity area; Correcting the initial defective area by using the newly added normal wave velocity area to obtain a corrected defective area inside the wooden structure; According to the area of ​​the defect area to be corrected, the defect level is divided and a matching maintenance strategy is formulated.

2. The non-destructive testing method for the interior of the ancient building wooden structure according to claim 1 is characterized in that: Detect direct wave signals and reflected wave signals inside wooden structures, including: 24 circular array sensors were evenly spaced around the ancient building, and 24 automatic electromagnetic pulsers were simultaneously deployed at the locations of the 24 circular array sensors; When one of the automatic electromagnetic pulsers emits a stress wave, the remaining 23 sensors detect the direct wave signal, and the sensors at the same location as the automatic electromagnetic pulser detect the reflected wave signal.

3. The non-destructive testing method for the interior of the ancient building wooden structure according to claim 2 is characterized in that: Analyzing the propagation velocity characteristics of the direct wave signal inside the wooden structure to obtain the initial defect area inside the wooden structure includes: sequentially emitting stress waves through the automatic electromagnetic pulser at each position, recording the propagation time of the stress waves to the sensors at all other positions, and measuring the straight-line distance of the propagation path of the stress waves to the sensors at all other positions; Calculating the propagation wave velocity of each propagation path according to the propagation time and the straight-line distance; Divide the wooden structure cross section into several pixel grids; According to the propagation wave speed of all propagation paths, the local wave speed of each pixel grid is obtained by reverse calculation; A wave velocity threshold is set, and an initial defect area inside the wood structure is obtained according to the local wave velocity.

4. The non-destructive testing method for the interior of the ancient building wooden structure according to claim 2 is characterized in that: Analyzing the radial diffusion depth of the reflected wave signal, including: The stress wave is emitted by the automatic electromagnetic pulser at each position in turn, and the reflected wave signals in various directions are received at the same position as the automatic electromagnetic pulser, and the start time when the sensor starts to receive the reflected wave signal and the end time when the reflected wave signal disappears are recorded; The radial diffusion depth of the reflected wave signal is obtained according to the start time and the end time.

5. The non-destructive testing method for the interior of the ancient building wooden structure according to claim 4 is characterized in that: Analyzing the total energy of the reflected wave signal includes: Within a time range between the start time and the end time, the total energy of the reflected wave signal is obtained according to the amplitude of the reflected wave signal.

6. The non-destructive testing method for the interior of the ancient building wooden structure according to claim 5 is characterized in that: Quantify the probability that the reflecting boundary is a real crack and obtain a noise-reduced reflected wave signal, including: Obtaining a probability that the reflection boundary is a real crack according to the radial diffusion depth and the total energy; A probability threshold is set, and a noise-reduced reflected wave signal is obtained according to the probability of the real crack.

7. The non-destructive testing method for the interior of the ancient building wooden structure according to claim 3 is characterized in that: Analyzing 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 newly added normal wave velocity area includes: For each sensor receiving the noise-reduced reflected wave signal, recording the emission time of the stress wave of the automatic electromagnetic pulser at the same location as the sensor, and recording the start time of the sensor starting to receive the reflected wave signal; According to the emission time and the start time, 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; Within the cross-section of the wooden structure, with the sensor as the center and the distance as the radius, a newly added normal wave velocity area is obtained.

8. The non-destructive testing method for the interior of the ancient building wooden structure according to claim 1 is characterized in that: According to the area of ​​the defect to be corrected, the defect level is divided and a matching maintenance strategy is formulated, including: Normalizing the area of ​​the corrected defect region to obtain a normalized area of ​​the corrected defect region; Setting a level threshold and dividing the defect severity of the corrected defect area into three defect levels according to the normalized area; According to the defect level, a matching maintenance strategy is formulated.

9. A non-destructive testing system for the interior of a wooden structure of an ancient building, characterized in that: The system comprises: a memory and a processor, wherein: The memory is used to store program code; The processor is configured to read the program code stored in the memory and execute the method according to any one of claims 1 to 8.

10. The non-destructive testing system for the interior of the ancient building wooden structure according to claim 9, characterized in that: The processor includes: Signal acquisition module, used to detect direct wave signals and reflected wave signals inside the wooden structure; a direct wave signal analysis module, configured to analyze the propagation velocity characteristics of the direct wave signal within the wood structure and obtain an initial defect area within the wood structure; A reflected wave signal analysis module analyzes the radial diffusion depth and total energy of the reflected wave signal, quantifies the probability that the reflecting boundary is a real crack, and obtains a de-noised reflected wave signal; a defect area correction module for analyzing 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 newly added normal wave velocity area; and correcting the initial defect area using the newly added normal wave velocity area to obtain a corrected defect area inside the wooden structure; The defect grade classification module is used to classify the defect grades according to the area of ​​the defect correction area and formulate a matching maintenance strategy.

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