Nondestructive testing method and device for internal damage of ancient tree by stress wave micro drill resistance fusion

Abstract

The application provides a stress wave micro drill resistance fusion ancient tree internal residual damage nondestructive detection method and device, the method comprises the following steps: a plurality of outer circumferential detection nodes are arranged around the trunk to be detected section, candidate abnormal areas are determined according to unit length propagation time, normalized amplitude decay and path waveform correlation; the sound bridge type micro drill probe is controlled to advance along the drilling path, drilling depth, advancing resistance and drill needle rotary drive current are collected, and a micro drill resistance sequence is generated; a migration type endogenous sound mark is formed at a preset depth position, and a depth coding internal sound field sequence is obtained; the sound bridge difference feature set is generated by switching the sound bridge to the state of being cancelled and the state of being established at the candidate residual damage depth position; the crack interface, the cavity edge and the continuous decay area are identified according to the sound bridge difference feature set and the micro drill resistance sequence, and the internal residual damage boundary is generated.

Description

Technical Field

[0001] This invention relates to the field of tree internal damage detection technology, and in particular to a non-destructive testing method and device for the internal damage of ancient trees using stress wave micro-drilling resistance fusion. Background Technology

[0002] Over long periods of growth, ancient trees are susceptible to damage from pests and diseases, mechanical injury, rainwater infiltration, and wood aging, which can easily lead to cracks, cavities, or continuous decay areas within the trunk. Therefore, accurate detection of internal damage to ancient tree trunks is crucial. Current technologies primarily employ stress wave detection and micro-drill resistance testing for detecting internal damage in ancient trees.

[0003] First, stress wave detection involves setting up detection nodes around the outer perimeter of the tree trunk and collecting the propagation response of stress waves between different nodes to determine whether there are abnormal regions inside the trunk. This method can obtain overall information about the cross-section of the trunk, but stress waves may detour after encountering cracks, cavities, or decaying wood. The response collected by the peripheral detection nodes is a comprehensive result of the entire propagation path, making it difficult to accurately determine the specific depth and true boundary of abnormal regions.

[0004] Secondly, micro-drilling resistance detection determines the state of the wood along the drilling path by recording changes in resistance during the advancement of a small-diameter drill bit. This method can obtain local depth information, but a single drill bit can only generate one linear detection record. When the drilling path does not pass through the damaged edge, or when the two sides of a closed fissure remain in partial contact, the change in advancement resistance may not be obvious, easily leading to missed fissure interfaces or misjudgment of cavity edges. Increasing the number of drill holes to improve coverage will increase tree damage. Summary of the Invention

[0005] To address the challenges in existing technologies of how to deeply correlate peripheral stress wave detection with micro-drilling resistance detection while controlling the number of boreholes, and how to accurately identify the type of damage and the boundary of internal damage by utilizing the local propagation response at suspected damage locations, this invention provides a non-destructive testing method and apparatus for internal damage detection of ancient trees by fusing stress wave and micro-drilling resistance.

[0006] The technical solution provided by this invention is as follows: A non-destructive testing method for internal damage of ancient trees using stress wave micro-drilling resistance fusion includes the following steps: S1: Set up multiple peripheral detection nodes around the cross section of the tree trunk to be tested, and perform stress wave excitation and response acquisition in sequence. Based on the propagation time per unit length, normalized amplitude attenuation and path waveform correlation of each node combination, determine the candidate abnormal area and the initial drilling direction. S2: Based on the candidate anomaly area and the initial drilling direction, control the acoustic bridge micro-drilling probe to advance along the drilling path, collect drilling depth, propulsion resistance, drill bit rotation drive current and propulsion speed, and generate a micro-drilling resistance sequence and a preliminary anomaly depth segment table; S3: Pause the acoustic bridge micro-drilling probe at each preset depth position to form a migrating internal acoustic beacon. Collect the internal propagation time, internal normalized amplitude attenuation and internal waveform correlation of each peripheral detection node to generate a table of abrupt sound field segments. S4: Determine the candidate residual depth location based on the preliminary abnormal depth segment table and the sound field abrupt change segment table, control the sound bridge micro-drilling probe to sequentially form the sound bridge cancellation state and the sound bridge establishment state, and generate the sound bridge difference feature set. S5: Identify the fracture interface, cavity edge and continuous decay area based on the sound bridge difference feature set and micro-drill resistance sequence, and generate the set of internal residual boundary anchor points and internal residual boundary.

[0007] A non-destructive testing device for internal damage of ancient trees using stress wave micro-drilling resistance fusion includes: The candidate anomaly region determination module is used to set up multiple peripheral detection nodes around the cross section of the tree trunk to be detected, and to sequentially perform stress wave excitation and response acquisition. Based on the propagation time per unit length, normalized amplitude attenuation and path waveform correlation of each node combination, the candidate anomaly region and the initial drilling direction are determined. The micro-drilling resistance acquisition module is used to control the acoustic bridge micro-drilling probe to advance along the drilling path based on candidate abnormal areas and the initial drilling direction, and to acquire drilling depth, propulsion resistance, drill bit rotation drive current and propulsion speed, and generate micro-drilling resistance sequence and preliminary abnormal depth segment table. The internal sound field construction module is used to pause the acoustic bridge micro-drilling probe at each preset depth position to form a migrating internal sound beacon, collect the internal propagation time, internal normalized amplitude attenuation and internal waveform correlation corresponding to each peripheral detection node, and generate a sound field abrupt change segment table. The acoustic bridge counterfactual response generation module is used to determine the candidate residual depth location based on the preliminary abnormal depth segment table and the acoustic field abrupt change segment table, control the acoustic bridge micro-drilling probe to sequentially form the acoustic bridge cancellation state and the acoustic bridge establishment state, and generate the acoustic bridge difference feature set. The internal damage boundary generation module is used to identify the crack interface, cavity edge and continuous decay area based on the acoustic bridge difference feature set and micro-drill resistance sequence, and generate the internal damage boundary anchor point set and internal damage boundary.

[0008] The beneficial effects of the technical solution provided by this invention include: This invention acquires the stress wave propagation characteristics of the cross section of the tree trunk to be tested through peripheral detection nodes and maps the abnormal propagation path to the cross section grid cell. This can reduce the impact of irregular tree trunk shape and propagation path detour on the location of abnormal areas and improve the accuracy of candidate abnormal area identification. By using a sound bridge micro-drilling probe to simultaneously collect propagation resistance, drill bit rotation drive current and drilling depth, the peripheral stress wave anomaly is deeply correlated with the micro-drilling resistance change. This can improve the positioning accuracy of cracks, cavities and continuous decay areas while controlling the number of boreholes.

[0009] This invention obtains a depth-coded internal sound field sequence that propagates from the inside of the tree to the outer detection nodes by forming migrating internal sound markers at different drilling depths. This can compensate for the insufficiency of the outer stress wave detection, which can only obtain the comprehensive propagation response, and improve the precision of damage boundary identification. By switching between the sound bridge cancellation state and the sound bridge establishment state at the candidate damage depth position, and identifying the damage type based on the response difference before and after the sound bridge establishment, it can discover closed cracks with no significant change in propulsion resistance and reduce the risk of missing latent cracks.

[0010] This invention generates void boundaries, continuous decay area boundaries, and crack interface lines based on internal damage boundary anchor points, and plans supplementary drilling paths for unconfirmed boundary sections, which can reduce aimless drilling and improve the completeness of internal damage detection and tree protection effect. Real-time acquisition and calculation are completed through on-site edge controllers, and feature data and detection results are sent using narrowband IoT communication modules, which can reduce the impact of remote communication latency on the on-site detection process and facilitate the formation of internal damage detection archives for ancient trees. Attached Figure Description

[0011] Figure 1 A flowchart illustrating the non-destructive testing method for internal damage of ancient trees based on stress wave micro-drilling resistance fusion provided in an embodiment of the present invention; Figure 2 This is a schematic diagram illustrating the determination of candidate anomaly regions and initial drilling paths provided in an embodiment of the present invention. Figure 3 This is a schematic diagram illustrating the correspondence between the degree of micro-drilling resistance anomaly, the degree of internal sound field abrupt change, and the sound bridge recovery score in the drilling depth direction, as provided in an embodiment of the present invention. Figure 4 This is a schematic diagram illustrating the relationship between the number of boreholes and the degree of closure of the internal damaged boundary, provided in an embodiment of the present invention. Figure 5 This is a schematic diagram of the frame of the stress wave micro-drilling resistance fusion non-destructive testing device for internal damage of ancient trees provided in an embodiment of the present invention. Detailed Implementation

[0012] Example 1: As Figure 1As shown, this embodiment provides a non-destructive testing method for internal damage of ancient trees using stress wave micro-drilling resistance fusion, including the following steps: S1: Set up multiple peripheral detection nodes around the cross section of the tree trunk to be tested, and perform stress wave excitation and response acquisition in sequence. Based on the propagation time per unit length, normalized amplitude attenuation and path waveform correlation of each node combination, determine the candidate abnormal area and the initial drilling direction.

[0013] In one possible implementation, S1 specifically includes sub-steps S110 to S130: S110: Determine the cross-section of the trunk to be inspected at a preset height of the ancient tree to be inspected. The cross-section of the trunk to be inspected is a detection plane perpendicular to the local axis of the trunk at that height. When the trunk shape is irregular, select a detection plane whose angle with the local axis of the trunk is within the preset cross-section deviation range. The local axis of the trunk is a reference axis that passes through the center of the trunk near the cross-section to be inspected and extends along the height direction of the trunk.

[0014] An intelligent sensing system is deployed around the cross-section of the tree trunk to be inspected. The intelligent sensing system includes a contour acquisition unit, multiple peripheral detection nodes, a field edge controller, a sound-bridge micro-drilling probe, a probe driving mechanism, and a narrowband IoT communication module. The contour acquisition unit uses a flexible contour measurement strip or a two-dimensional contour scanning unit to collect the set of location points on the outer boundary of the cross-section of the tree trunk to be inspected, forming the outer contour data.

[0015] Using fixed markers on the tree trunk surface as the origin of the cross-section coordinate system, the direction from the origin of the cross-section coordinate system to the geometric center of the outer contour is taken as the direction of the first cross-section coordinate axis, and the direction perpendicular to the first cross-section coordinate axis is taken as the direction of the second cross-section coordinate axis, thus establishing a two-dimensional cross-section detection coordinate system.

[0016] Each peripheral detection node is set along the periphery of the section of the tree trunk to be tested and numbered sequentially in a clockwise direction. Each peripheral detection node includes a stress wave excitation unit, a peripheral excitation reference acquisition unit, a stress wave response acquisition unit, and a contact pressure detection unit.

[0017] The acoustic bridge micro-drilling probe includes a drill bit body, a front coupling section, a lateral vibration isolation sleeve, a micro-vibration excitation unit, an internal excitation reference acquisition unit, a depth encoder, a first radial micro-contact section, and a second radial micro-contact section.

[0018] In specific implementation, the first and second radial micro-contact sections are respectively equipped with radial expansion drive components, radial contact pressure sensors, and radial displacement sensors. The radial expansion drive component adopts a wedge-shaped pusher structure driven by a micro piezoelectric ceramic actuator or a micro motor. Through voltage control or motor rotation, it pushes the arc-shaped metal contact plate outside the probe to expand radially outward to fit tightly against the inner wall of the borehole. The micro-vibration excitation unit integrates a high-frequency piezoelectric vibrator to apply controlled stress wave pulses to the borehole. The lateral vibration isolation sleeve covers the sidewall area of ​​the drill bit body except for the front coupling section, the first radial micro-contact section, and the second radial micro-contact section. The material can be polyurethane damping material to reduce vibration bypass caused by random contact between the drill bit sidewall and the inner wall of the borehole.

[0019] Record the coordinates of the i-th peripheral detection node based on the outer contour data. Where i represents the trigger node number. This represents the coordinate value of the i-th peripheral detection node along the coordinate axis of the first cross section; This represents the coordinate value of the i-th peripheral detection node along the coordinate axis of the second section. For a node combination consisting of the i-th and j-th peripheral detection nodes, calculate the geometric chord length of the node combination. :

[0020] Where j represents the response acquisition node number. This represents the straight-line distance between two peripheral detection nodes in the two-dimensional cross-sectional detection coordinate system. This represents the coordinate value of the j-th peripheral detection node along the coordinate axis of the first cross section; This represents the coordinate value of the j-th peripheral detection node along the coordinate axis of the second section.

[0021] The contact pressure detection unit collects the installation pressure of each peripheral detection node and only includes nodes whose installation pressure is within the preset contact pressure range in subsequent scans. The field edge controller summarizes the ancient tree number to be detected, the height of the trunk section to be detected, the outer contour data, the coordinates of the peripheral detection nodes, and the geometric chord length of the node combination into a peripheral detection node topology table.

[0022] S120: The field edge controller selects excitation nodes sequentially according to the peripheral detection node topology table, and uses the remaining nodes as response acquisition nodes. When the excitation node applies stress wave excitation, the peripheral excitation reference acquisition unit synchronously records the time of peripheral excitation occurrence and the peripheral excitation reference amplitude, and each response acquisition node synchronously acquires the response waveform. At least three stress wave excitations are performed continuously for the same node combination. When the peripheral excitation reference amplitude is not within the preset peripheral excitation amplitude range, or the difference between repeated response waveforms exceeds the preset peripheral scan repeatability range, the corresponding record is discarded and re-excitation is performed.

[0023] For node combinations that pass the verification, the time difference between the occurrence of the peripheral excitation and the first time the response waveform reaches the preset arrival threshold is determined as the peripheral stress wave propagation time. Then, the following calculations are performed: The propagation time per unit length is calculated, which is equal to the calculated peripheral stress wave propagation time divided by the geometric chord length of the node combination. The normalized amplitude attenuation is calculated, which is equal to the ratio of the maximum response amplitude acquired by the response acquisition node within the stress wave arrival time window to the peripheral excitation reference amplitude, multiplied by the logarithm to base 10, and then multiplied by -20.

[0024] The aforementioned propagation time per unit length is used to eliminate differences in the geometric chord length of the node combination, and the normalized amplitude attenuation is used to eliminate differences in the peripheral excitation intensity. The field edge controller simultaneously aligns the repetitive response waveforms according to their arrival times and calculates the correlation coefficient between the response waveforms to obtain the path waveform correlation. Finally, the node number, node coordinates, node combination geometric chord length, propagation time per unit length, normalized amplitude attenuation, and path waveform correlation are summarized into a node combination propagation record, generating a peripheral stress wave response set.

[0025] For example, the geometric chord lengths of the two node combinations are 420 mm and 600 mm, respectively, and the propagation times of the peripheral stress waves are 0.42 ms and 0.60 ms, respectively. The propagation time per unit length for both is 0.001 ms / mm, and the second node combination cannot be judged as abnormal simply because its initial propagation time is longer.

[0026] S130: Group the node combination propagation records according to the node combination geometric chord length and propagation direction. Multiple node combination propagation records with node combination geometric chord lengths within the same preset length range and propagation directions within the same preset direction range are grouped into the same comparable path group. For each comparable path group, calculate the median of the propagation time per unit length and the normalized amplitude attenuation, and use the median values ​​of the response waveforms within the group at the same sampling point to form a reference response waveform. Perform point-by-point correlation calculations between the current response waveform and the reference response waveform to obtain the correlation of the corresponding path waveforms.

[0027] Node combinations that exceed the corresponding healthy reference range in at least two of the following factors—increased propagation time per unit length, increased normalized amplitude attenuation, and decreased path waveform correlation—are identified as anomalous node combinations. The healthy reference range is primarily derived from the median and discrete range of the current comparable path groups. When more than half of the node combinations in any comparable path group exceed the current healthy reference range, adjacent reference sections avoiding visible wounds and tree holes are selected on the same ancient tree. Data is re-acquired according to steps S110 and S120, and the healthy reference range is corrected based on the peripheral stress wave response set of the adjacent reference sections.

[0028] Based on the outer contour data, the interior of the tree trunk section to be inspected is divided into cross-sectional mesh units with side lengths ranging from 10mm to 20mm. The lines connecting the two peripheral detection nodes corresponding to each abnormal node combination are projected onto the cross-sectional mesh units, and the number of times each cross-sectional mesh unit is traversed by the abnormal propagation path is counted. Cross-sectional mesh units that reach a preset number of intersections are identified as abnormal mesh units, and spatially continuous abnormal mesh units are merged into candidate abnormal regions. The preset number of intersections is determined based on the total number of peripheral detection nodes, the size of the cross-sectional mesh units, and the equipment calibration results.

[0029] For multiple peripheral candidate drilling entrances, candidate drilling paths pointing towards the center of the candidate anomaly region are generated. The candidate drilling path that passes through the most anomaly grid cells is preferentially selected. When multiple candidate drilling paths pass through the same number of anomaly grid cells, the path with the shortest path length among those that meet the avoidance requirements is selected as the initial drilling direction. The field edge controller summarizes the cross-sectional location, coverage area, corresponding anomaly propagation path, and initial drilling direction of the candidate anomaly region into a candidate anomaly region record and sends it to step S210.

[0030] For example, if 5 out of 7 abnormal propagation paths pass through the continuous grid area at the lower right of the cross section to be detected on the tree trunk, and the preset number of intersections is 3, then this continuous grid area is identified as a candidate abnormal area.

[0031] like Figure 2 The figure illustrates the supporting role of the convergence of peripheral stress wave anomaly paths in locating candidate anomaly regions. As can be seen from the figure, multiple anomaly propagation paths form a concentrated convergence area in the lower right quadrant of the trunk section, and the initial drilling path can pass through this high convergence area. This demonstrates that by mapping the anomaly paths selected through a combination of propagation time per unit length, normalized amplitude attenuation, and path waveform correlation onto the cross-sectional mesh, a clearer candidate region and drilling direction can be provided for subsequent micro-drilling detection without directly increasing the number of boreholes.

[0032] S2: Based on the candidate abnormal region and the initial drilling direction, control the acoustic bridge micro-drilling probe to advance along the drilling path, collect drilling depth, propulsion resistance, drill bit rotation drive current and propulsion speed, and generate micro-drilling resistance sequence and preliminary abnormal depth segment table.

[0033] In one possible implementation, S2 specifically includes sub-steps S210 to S230: S210: Read the candidate abnormal area record and initial drilling direction output in step S130, and determine the drilling entry point on the outer periphery of the section to be inspected on the tree trunk. The drilling entry point is the position where the acoustic bridge micro-drill probe first enters the tree. The field edge controller calls the outer contour data formed in step S110, excludes visible wounds, branch joints, existing drill holes, installation positions of peripheral detection nodes, and peripheral sections less than a preset avoidance distance from the above positions, and then selects the position intersecting the initial drilling direction from the remaining peripheral sections as the drilling entry point.

[0034] Starting from the drill inlet, a drilling path is formed along the initial drilling direction. The drilling path sequentially includes a surface removal section, an outer stable wood section, a candidate anomaly area passage section, and a verification extension section. The surface removal section is the section between the zero drilling depth and the preset surface removal depth, which is not involved in establishing the healthy wood resistance benchmark. The preset surface removal depth is determined based on the on-site bark thickness measurement results.

[0035] The outer stable timber section is the timber path located between the surface exclusion section and the candidate anomaly area, used to establish a healthy reference depth section. The candidate anomaly area passage section is the portion of the drilling path that overlaps with the candidate anomaly area. The verification extension section is a preset length by which the acoustic bridge micro-drilling probe continues to advance after crossing the distal boundary of the candidate anomaly area, used to determine whether the propulsion resistance has been restored.

[0036] The maximum permissible drilling depth is calculated as follows:

[0037] in, For the maximum permissible drilling depth, It is the distance from the drill inlet to the intersection of the outer contour of the far side of the drill path. The distance from the drill entry point to the far boundary of the candidate anomaly region. To verify the extension length, To preserve the thickness. This indicates taking the minimum value. Derived from outer contour data, Originating from the boundary of the candidate anomaly region, and The parameters are determined based on the trunk diameter, the size of the candidate anomaly area, the outer diameter of the acoustic bridge micro-drilling probe, and the preset maximum drilling ratio. If the length of the current drilling path is less than the sum of the far boundary of the candidate anomaly region and the verification extension length, the current drilling path is marked as an unusable drilling path, and a new drilling inlet is selected or the drilling direction is adjusted. The field edge controller generates probe drilling commands based on the available drilling paths and sends them to the probe drive mechanism.

[0038] For example, when For 360mm, 210mm 15mm When it is 20mm, It is 225mm.

[0039] S220: The probe drive mechanism controls the acoustic bridge micro-drill probe to advance step by step according to the probe drilling command. The probe drive mechanism includes an axial force sensor, a rotary motor current acquisition interface, a rotary speed encoder, and a timing unit. The axial force sensor is used to collect the propulsion resistance experienced by the acoustic bridge micro-drill probe along the drilling direction. The rotary motor current acquisition interface is used to collect the drill bit rotation drive current. The rotary speed encoder is used to collect the drill bit rotation speed. The depth encoder is used to record the displacement of the drill bit tip relative to the drill inlet. The timing unit is used to record the sampling time.

[0040] When the acoustic bridge micro-drilling probe first contacts the outer surface of the tree trunk and the propulsion resistance reaches the preset contact judgment value, the current depth encoder reading is set to the zero point of the drilling depth. During the propulsion of the acoustic bridge micro-drilling probe, the axial force sensor, the rotary motor current acquisition interface, the rotary speed encoder, and the depth encoder synchronously acquire data at the same sampling time.

[0041] propulsion speed The calculation is as follows:

[0042] in, Let r be the propulsion speed corresponding to the r-th synchronous sampling point. Let r be the drilling depth corresponding to the r-th synchronous sampling point. This represents the r-th sampling time. r denotes the synchronous sampling point number. Originating from the timing unit, It originates from a depth encoder. This represents the sampling time corresponding to the (r-1)th synchronous sampling point. This represents the drilling depth corresponding to the (r-1)th synchronous sampling point. The field edge controller divides the depth into segments according to a preset depth interval, and saves the drilling depth, propulsion resistance, drill bit rotation drive current, drill bit rotation speed, and propulsion speed in each depth segment, forming a depth synchronous micro-drilling response record.

[0043] In one embodiment, the preset depth interval is 1 mm, the preset target advance speed is 2 mm / s, the allowable deviation is 0.3 mm / s, and at least 5 valid sampling points are retained for each depth segment. Only sampling points whose advance speed is within the preset advance speed range, whose drill bit rotation speed is within the preset rotation speed range, and whose probe is not in a pause, retraction, or repositioning phase are determined as valid sampling points.

[0044] S230: The field edge controller performs effective sampling point screening and segment-level consistency verification on the depth-synchronous micro-drilling response records. The specific calculation methods for each indicator are as follows: Extract all effective thrust resistance sampling values ​​within a certain depth segment, and take the median of these sampling values ​​as the segment thrust resistance of that segment. Calculate the relative resistance reduction degree, which is equal to the difference between the median segment thrust resistance of the healthy reference depth segment and the segment thrust resistance of the current depth segment, divided by the median segment thrust resistance of the healthy reference depth segment. Calculate the resistance collapse degree of adjacent segments, which is equal to the difference between the segment thrust resistance of the previous adjacent depth segment and the segment thrust resistance of the current depth segment, divided by the median segment thrust resistance of the healthy reference depth segment.

[0045] The field edge controller simultaneously calculates the median of the drill bit rotation drive current after deducting the no-load rotation current. When the drill bit rotation drive current and the section advance resistance continuously change in opposite directions within adjacent depth sections reaching a preset number of consecutive sections, the corresponding section is marked as a depth section to be retested, and the process returns to step S220 for re-acquisition. Continuous depth sections where both the section advance resistance and drill bit rotation drive current remain stable after the surface exclusion section and before the candidate abnormal area are identified as healthy reference depth sections. When the outer stable wood sections are insufficient to form three consecutive healthy reference depth sections, the process returns to step S210 to reselect the drill entry point.

[0046] When the relative resistance decrease of adjacent depth segments reaching a preset number of consecutive segments all exceeds a preset decrease threshold, it is identified as a continuously decreasing type of initial abnormal depth segment. When the resistance collapse of adjacent segments corresponding to any depth segment exceeds a preset collapse threshold, it is identified as an instantaneous collapse type of initial abnormal depth segment. When the ratio of the segment advance resistance of any depth segment to the median segment advance resistance of the healthy reference depth segment is lower than a preset near-zero threshold, and the drill bit rotation drive current is close to the no-load rotation current, it is identified as a near-zero resistance type of initial abnormal depth segment.

[0047] For example, if the median thrust resistance of the healthy reference depth segment is 18N, and the thrust resistance of six consecutive depth segments within the range of 95mm to 101mm is all below 11N, with the corresponding relative resistance decrease exceeding 0.35, then the 95mm to 101mm segment is identified as a continuously decreasing initial abnormal depth segment. The field edge controller generates a micro-drilling resistance sequence and an initial abnormal depth segment table in ascending order of drilling depth, and sends them to steps S310 and S410.

[0048] S3: Pause the acoustic bridge-type micro-drilling probe at each preset depth position to form a migrating internal acoustic beacon. Collect the internal propagation time, internal normalized amplitude attenuation, and internal waveform correlation corresponding to each peripheral detection node to generate a sound field abrupt change segment table.

[0049] In one possible implementation, S3 specifically includes sub-steps S310 to S330: S310: Read the healthy reference depth segment and preliminary abnormal depth segment table output in step S230, and set the preset depth position on the drilling path. The healthy reference depth segment uses a normal depth sampling interval. The preliminary abnormal depth segment and its adjacent segments on both sides use an encrypted depth sampling interval, and the encrypted depth sampling interval is less than or equal to the normal depth sampling interval.

[0050] The acoustic bridge-type micro-drilling probe is controlled to advance sequentially to each preset depth position, then the advancement and rotation are paused, and the first and second radial micro-contact sections are kept in a contracted state. When the advancement resistance fluctuation collected by the axial force sensor is within the preset advancement resistance stability range, the coded stress wave excitation is repeatedly executed at least 3 times through the micro-vibration excitation unit.

[0051] Encoded stress wave excitation consists of a preset number of pulses at preset intervals, with the intrinsic excitation reference amplitude within a preset range. The excitation frequency, number of pulses, and pulse interval are derived from equipment calibration results for healthy wood specimens, cracked simulated specimens, and cavity simulated specimens.

[0052] In one specific embodiment, the coded stress wave excitation uses a Hanning window modulated sinusoidal pulse with a center frequency of 5 kHz to 15 kHz, the number of pulses is 3 to 5 cycles, the pulse interval is 10 milliseconds to 20 milliseconds, and the driving voltage corresponding to the intrinsic excitation reference amplitude is 50V to 100V.

[0053] Migrating intrinsic sound markers are internal excitation locations formed at a predetermined depth by the front-end coupling segment, which can be identified through drilling depth and excitation encoding. They are not physical markers implanted in the tree structure. The calculation is as follows:

[0054] in, The location of the migrating intrinsic sound beacon corresponding to the p-th preset depth position. This represents the drilling depth corresponding to the p-th preset depth position. The coordinates of the drill inlet are... Let p be the unit direction vector in the drilling direction, and p represent the preset depth position number. Derived from a depth encoder, and This originates from step S210. The intrinsic excitation reference acquisition unit records the occurrence time and reference amplitude of the intrinsic excitation. The field edge controller summarizes the preset depth position, migrating intrinsic sound beacon position, intrinsic excitation occurrence time, excitation code, and intrinsic excitation reference amplitude into an intrinsic sound beacon excitation record.

[0055] For example, when the initial abnormal depth range is 95mm to 101mm, preset depth positions can be set at 1mm intervals within the range of 93mm to 103mm, and preset depth positions can be set at 2mm intervals within the healthy reference depth range.

[0056] S320: Each peripheral detection node receives the sampling trigger signal sent by the field edge controller through the field synchronous sampling link and acquires the response waveform according to a unified sampling clock. The narrowband IoT communication module does not participate in the real-time synchronization between the coded stress wave excitation and the sampling of the peripheral detection nodes; it is only used to send feature data packets and detection result data packets.

[0057] For each preset depth location, the response waveforms corresponding to at least three repeated excitations are stored according to the peripheral detection node numbers. The repeated response waveforms are aligned according to their arrival times, and the correlation coefficient between them is calculated. When the maximum response amplitude is lower than the preset effective response amplitude, or the correlation coefficient is lower than the preset intrinsic acoustic beacon response correlation threshold, the corresponding peripheral detection node is marked as an invalid response node. When the number of effective response nodes is lower than the preset number of effective nodes, re-acquisition is performed. If the requirements are still not met after re-acquisition, the current preset depth location is marked as the depth location to be re-measured, and the process returns to step S310.

[0058] The following calculations are then performed: The internal propagation time is calculated, which is equal to the arrival time of the response at the peripheral detection node minus the occurrence time of the internal excitation. The internal normalized amplitude attenuation is calculated, which is equal to the ratio of the maximum response amplitude acquired by the peripheral detection node within the arrival time window to the reference amplitude of the internal excitation, multiplied by the logarithm to base 10, and then multiplied by -20.

[0059] The field edge controller aligns the response waveforms corresponding to the health reference depth positions according to their arrival times, and takes the median amplitude of the same sampling points to form an internal health reference waveform. Then, the correlation coefficient between each response waveform and the internal health reference waveform is calculated to obtain the internal waveform correlation. The migrating internal sound beacon positions, internal propagation times, internal normalized amplitude attenuation, internal waveform correlations, and valid response node numbers are summarized into an internal sound beacon response group.

[0060] S330: Arrange the internal acoustic beacon response groups in ascending order of drilling depth to generate a depth-coded internal acoustic field sequence. The depth-coded internal acoustic field sequence is a data set used to represent the propagation relationship between the locations of different migrating internal acoustic beacons and each peripheral detection node.

[0061] For each peripheral detection node, a healthy fluctuation range is established based on the internal propagation time, internal normalized amplitude attenuation, and internal waveform correlation corresponding to the healthy reference depth position. The changes in three characteristics between adjacent preset depth positions are compared. When at least two characteristic changes exceed the corresponding healthy fluctuation range, and the number of peripheral detection nodes meeting the conditions reaches the preset number of abnormal response nodes, the current preset depth position is determined as the sound field abrupt change depth position. Continuous sound field abrupt change depth positions are merged into a sound field abrupt change segment, and the starting depth, ending depth, and abnormal peripheral detection node number are recorded.

[0062] An anomaly propagation direction is generated based on the direction from the location of the migrating internal acoustic beacon to the coordinates of the anomaly peripheral detection node. The field edge controller sends the depth-coded internal sound field sequence, the sound field abrupt change segment table, and the anomaly propagation direction to step S410.

[0063] For example, if four out of the twelve peripheral detection nodes simultaneously exhibit an increase in internal propagation time, an increase in internal normalized amplitude attenuation, and a decrease in internal waveform correlation within the range of 97mm to 99mm, and the preset number of abnormal response nodes is three, then the range of 97mm to 99mm is determined as the abrupt change zone of the sound field.

[0064] S4: Determine the candidate residual depth location based on the preliminary abnormal depth segment table and the sound field abrupt change segment table, control the sound bridge micro-drilling probe to sequentially form the sound bridge cancellation state and the sound bridge establishment state, and generate the sound bridge difference feature set.

[0065] In one possible implementation, S4 specifically includes sub-steps S410 to S430: S410: Read the preliminary anomaly depth segment table output in step S230, the sound field abrupt change segment table output in step S330, and the anomaly propagation direction, and call the candidate anomaly region passing segment and verification extension segment formed in step S210. Compare the preliminary anomaly depth segments and the sound field abrupt change segments according to the drilling depth.

[0066] For the overlapping areas, at least the starting and ending positions of the overlapping area, as well as the position with the greatest change in the internal sound field, are selected to generate the first type of candidate residual depth positions. When the distance between two adjacent positions is less than or equal to the encrypted depth sampling interval, only the position with the greater change in the internal sound field is retained. The degree of change in the internal sound field is determined as follows: the number of peripheral detection nodes exceeding the healthy fluctuation range is counted for changes in internal propagation time, changes in internal normalized amplitude attenuation, and changes in internal waveform correlation. The position with the largest number of abnormal peripheral detection nodes is selected first. When the number is the same, the position with the largest cumulative offset of the three features relative to the healthy fluctuation range is selected.

[0067] For locations within the candidate anomaly region passing through the segment or verification extension segment, falling into the sound field abrupt change segment but not falling into the initial anomaly depth segment, a second type of candidate residual depth location is generated. The second type of candidate residual depth location is used to retain the detection location of closed cracks where the propulsion drag has not reached the preset drag reduction threshold, but the internal sound field has changed.

[0068] Let the depth of any abrupt change in the sound field be... The initial depth and the final depth of any initial anomaly depth segment are a and b, respectively, and the distance between them is... ,but:

[0069] The field edge controller generates a candidate damage depth location table according to the rule of prioritizing the first type of candidate damage depth location and sorting the second type of candidate damage depth locations in ascending order of distance, and sends it to step S420.

[0070] S420: Controls the acoustic bridge micro-drilling probe to sequentially stop at each candidate damage depth, ensuring that the first and second radial micro-contact segments are located on either side of the candidate damage depth. Acoustic bridge bridging center depth. The calculation is as follows:

[0071] in, The depth of the first radial micro-contact segment corresponding to the k-th candidate damage depth location. This represents the depth of the second radial micro-contact segment corresponding to the k-th candidate damage depth location. k indicates the candidate damage depth location number, and the corresponding depths of the two radial micro-contact segments are determined by the depth encoder reading and the fixed installation distance.

[0072] For each candidate residual depth location, the following state acquisition processes are performed sequentially: pre-cancellation state acquisition, establishment state acquisition, and post-cancellation state acquisition. During pre-cancellation state acquisition, the two radial micro-contact segments remain contracted, and the radial contact pressure is below the preset upper limit of cancellation pressure, forming a sound bridge cancellation state. During establishment state acquisition, the two radial micro-contact segments expand towards the borehole wall. When both radial contact pressures are within the preset effective contact pressure range, the radial expansion displacement remains stable within the preset stabilization time, and the radial contact pressure does not exceed the preset upper limit of safe pressure, a sound bridge establishment state is formed.

[0073] In one specific embodiment, expansion is achieved by gradually increasing the output force through controlling the radial expansion drive. The preset upper limit of the retraction pressure can be set to within 0.5N, the preset effective contact pressure range can be set to 5N to 10N, the preset stabilization time can be 2 seconds, and the preset upper limit of the safe pressure can be set to 15N, so as to ensure the formation of a stable acoustic bridge coupling in the wood while preventing excessive expansion from damaging the wood of the pore wall.

[0074] When the state acquisition is cancelled, the two radial micro-contact segments resume contraction, and the response waveform is acquired again after a preset recovery time.

[0075] For each state, at least three coded stress wave excitations with identical excitation codes and internal excitation reference amplitudes within the preset internal excitation reference amplitude range are repeated. When any radial micro-contact segment fails to reach the preset effective contact pressure range, the probe position is adjusted forward or backward within the local search range according to the encryption depth sampling interval, and the establishment action is re-executed. If stable contact cannot be formed simultaneously after a preset number of adjustments, the corresponding position is recorded as a position where the acoustic bridge cannot be established and sent to step S510.

[0076] S430: Each peripheral detection node acquires the response waveforms corresponding to the pre-cancellation state, the established state, and the post-cancellation state through the on-site synchronous sampling link. The median of the internal propagation time, internal normalized amplitude attenuation, and internal waveform correlation obtained from at least three valid acquisitions under the same state is taken as the characteristic value corresponding to the current state.

[0077] For internal propagation features (internal propagation time, internal normalized amplitude attenuation, or internal waveform correlation), the reference value for sound bridge removal is calculated as the arithmetic mean of the feature value in the state before removal and the feature value in the state after removal. The current detection result is retained only if the difference between the state before and after removal is within the preset sound bridge reset repeatability range. Otherwise, step S420 is re-executed.

[0078] After obtaining the establishment state values ​​and sound bridge removal reference values ​​for each feature, the difference features are calculated: the reduction in internal propagation time equals the sound bridge removal reference value of internal propagation time minus the internal propagation time in the establishment state. The reduction in internal normalized amplitude attenuation equals the sound bridge removal reference value of internal normalized amplitude attenuation minus the internal normalized amplitude attenuation in the establishment state. The increase in internal waveform correlation equals the internal waveform correlation in the establishment state minus the sound bridge removal reference value of internal waveform correlation. The field edge controller generates the sound bridge counterfactual response group and the sound bridge difference feature set, and sends them to step S510.

[0079] S5: Identify the fracture interface, cavity edge and continuous decay area based on the sound bridge difference feature set and micro-drill resistance sequence, and generate the set of internal residual boundary anchor points and internal residual boundary.

[0080] In one possible implementation, S5 specifically includes sub-steps S510 to S530: S510: Read the healthy reference depth segment output in step S230, and the acoustic bridge counterfactual response group, acoustic bridge difference feature set, and acoustic bridge unestablishable positions output in step S430. Within the healthy reference depth segment, select no fewer than three healthy acoustic bridge reference positions according to the three-state acquisition method of step S420. A healthy acoustic bridge reference position is a position where the difference between the state before and after cancellation is within the preset acoustic bridge reset repeatability range, and both the first and second radial micro-contact segments can form stable contact. If there are fewer than three valid positions, return to step S210 to reselect the drilling entry point.

[0081] A sound bridge difference judgment range is established for the reduction in internal propagation time, the decrease in internal normalized amplitude attenuation, and the increase in internal waveform correlation. The upper limit of this sound bridge difference judgment range is defined. The calculation is as follows:

[0082] in, Let f be the upper limit of the range for determining acoustic bridge differences, and let f be any acoustic bridge difference feature. This represents the median in the set of healthy sound bridge reference locations. This represents the median absolute deviation. This is the threshold amplification factor. It is the smallest positive number to determine the value. and This is derived from equipment calibration results. `max` indicates taking the maximum value. In a specific embodiment, the threshold amplification factor is used to determine the reduction in internal propagation time. The value can be between 2.5 and 3.0, and is the minimum positive number for determination. 0.02ms is acceptable.

[0083] Then the acoustic bridge recovery score between the k-th candidate damage depth location and the j-th peripheral detection node. The calculation is as follows:

[0084] in, , and These represent the weights of the three features, and the sum of the three is 1. , and These represent the upper limits of the sound bridge difference judgment range corresponding to the reduction in internal propagation time, the decrease in internal normalized amplitude attenuation, and the increase in internal waveform correlation, respectively. This represents the reduction in internal propagation time between the k-th candidate damage depth location and the j-th peripheral detection node. This indicates the decrease in the corresponding internal normalized amplitude attenuation. This indicates the increase in the correlation of the corresponding internal waveform.

[0085] The peripheral detection nodes whose sound bridge recovery scores reach the preset recovery score threshold are identified as valid sound bridge response nodes.

[0086] Effective node ratio of sound bridge The calculation is as follows:

[0087] in, The effective node ratio of the sound bridge. To the total number of valid response nodes, This represents the number of effective response nodes in the sound bridge. When... When the preset effective ratio of the acoustic bridge is reached, and at least one effective response node of the acoustic bridge is located in the abnormal propagation direction recorded in step S330, the corresponding position is determined as the effective depth position of the acoustic bridge. The field edge controller summarizes the position number, the acoustic bridge bridging center depth, the effective node ratio of the acoustic bridge, the effective response node number of the acoustic bridge, and the abnormal propagation direction to generate an effective depth position table of the acoustic bridge, and sends it to step S520.

[0088] S520: The acoustic bridge bridging center depth recorded in step S430 is correlated with the micro-drilling resistance sequence formed in step S230 according to the drilling depth. When the acoustic bridge bridging center depth falls into a certain depth segment, the segment's advance resistance, relative resistance reduction degree, adjacent segment resistance collapse degree, and drill bit rotation drive current are correlated with the corresponding effective node ratio of the acoustic bridge.

[0089] When a location falls within the effective depth of the acoustic bridge and the corresponding propulsion resistance exhibits a momentary collapse followed by recovery, that location is identified as a crack interface. When a location falls within the effective depth of the acoustic bridge, the propulsion resistance does not reach the preset resistance reduction threshold, but step S330 records the corresponding abrupt change in the sound field, that location is identified as a closed crack interface. A crack interface is an interface where the internal wood continuity is partially interrupted or the contact is unstable.

[0090] When a location is adjacent to a continuous near-zero resistance initial anomaly depth section, and the drill bit rotation drive current is close to the no-load rotation current, the location where the propulsion resistance changes from a stable value to a near-zero value is identified as the cavity entry edge, and the location where the propulsion resistance recovers from a near-zero value to a stable value is identified as the cavity exit edge. Locations where a sound bridge cannot be established serve as reinforcing evidence of the cavity edge.

[0091] When the thrust resistance of the adjacent depth segment corresponding to the preset number of continuous segments is lower than the range corresponding to the healthy reference depth segment, the drill bit rotation drive current decreases synchronously but does not continuously approach the no-load rotation current, and the internal sound field is abnormally continuous, the corresponding segment is identified as a continuous decay area.

[0092] When the propulsion resistance decreases but the drill bit rotation drive current increases, the corresponding position is marked as the depth position to be verified, and the process returns to step S220. When the state before cancellation and the state after cancellation do not meet the preset repeatability range of the acoustic bridge reset, the process returns to step S420. If the verification still fails after reaching the preset number of retests, a mark for manual verification is generated.

[0093] For the identified locations, the location calculation method from step S310 is invoked to map the corresponding drilling depth into two-dimensional coordinates, generating internal damage boundary anchor points. These internal damage boundary anchor points are two-dimensional coordinate points obtained along the drilling path, used to constrain the location of the damage boundary. The field edge controller summarizes the drilling path number, two-dimensional coordinates, damage type, boundary entry or exit attributes, effective node ratio of the sound bridge, and anomaly propagation direction to generate a set of internal damage boundary anchor points, which is then sent to step S530.

[0094] like Figure 3 The figure illustrates the role of the acoustic bridge counterfactual response mechanism in identifying closed fractures. As shown, within the 98mm to 100mm closed fracture range, the micro-drilling resistance anomaly score does not exceed the judgment threshold, the intrinsic acoustic field mutation score is only close to the threshold, while the acoustic bridge recovery score exceeds the judgment threshold of 0.60. This indicates that when the two sides of a closed fracture maintain local contact, simple changes in propagation resistance may not be sufficient to form a stable judgment. The acoustic bridge establishment state can change the local propagation coupling conditions, amplifying the difference in propagation recovery at the fracture location, thus helping to reduce the risk of missed detection of closed fractures.

[0095] S530: Call the cross-sectional mesh element formed in step S110 and map the internal damaged boundary anchor points to the cross-section to be inspected on the tree trunk. Assign region numbers to the separated damaged regions and do not forcibly merge spatially discontinuous anchor points.

[0096] For anchor points at the edge of cavities and boundary anchor points of continuous decay areas, the cross-sectional mesh elements between adjacent anchor points are used as candidate connection mesh elements. Prioritize selecting the mesh path located within the candidate anomaly region formed in step S130, consistent with the anomaly propagation direction output in step S330, and with the shortest cumulative connection length as the boundary connection path.

[0097] When no matching grid path exists, the corresponding segment is marked as an unconfirmed boundary segment. Connecting the anchor points at the cavity edge forms the cavity boundary; connecting the entry and exit boundary anchor points of the continuous decay region forms the continuous decay region boundary. Connecting the anchor points at the crack interface along the direction of anomaly propagation forms the crack interface line. The crack interface line is a linear structure and does not need to be closed. The crack end is considered confirmed when its end connects to the cavity boundary, the continuous decay region boundary, the outer contour of the tree trunk, or when it no longer extends after supplementary testing.

[0098] For the g-th cavity boundary or the boundary of a continuous decaying region, the degree of boundary closure... The calculation is as follows:

[0099] in, The degree of boundary closure For the confirmed boundary length, Length of the unconfirmed boundary. g represents the damaged region number. When the boundary closure degree is lower than the preset closure threshold, the unconfirmed boundary segment with the longest length is identified as a supplementary candidate anomaly region. When the fracture end has not yet been confirmed, the adjacent cross-sectional mesh element outside the unconfirmed fracture end is identified as a supplementary candidate anomaly region.

[0100] Among the supplementary candidate drilling paths that meet the avoidance requirements, the path with the shortest length that passes through the middle of the supplementary candidate anomaly region is selected as the supplementary drilling direction. The supplementary candidate anomaly region replaces the candidate anomaly region output in step S130, and the supplementary drilling direction replaces the initial drilling direction output in step S130. Then, return to step S210.

[0101] Set a preset maximum number of supplementary drilling operations. When the number of supplementary inspections reaches the preset maximum number of supplementary drilling operations, but there are still unconfirmed boundary sections or unconfirmed fracture ends, stop adding new drilling operations and output the confirmed damaged boundary, unconfirmed boundary section, unconfirmed fracture end, and manual verification mark.

[0102] When the boundary closure degree of the cavity boundary and the continuous decay area boundary reaches the preset closure threshold, and the crack end is confirmed, the internal damage detection results of the ancient tree are output. The internal damage detection results of the ancient tree include at least the height of the trunk section to be tested, the cavity boundary, the continuous decay area boundary, the crack interface line, the set of internal damage boundary anchor points, the number of supplementary tests, and the manual verification mark. The field edge controller encapsulates the detection results into a detection result data packet and sends it to the remote detection platform through the narrowband IoT communication module. The complete original response waveform is stored in the field edge controller.

[0103] like Figure 4As shown in the figure, to demonstrate the effectiveness of this scheme in improving boundary closure under low-damage detection conditions, it can be seen that the boundary closure of this scheme is approximately 0.91 under the condition of 3 boreholes, which has reached the set closure threshold, while the traditional multi-point drilling method is still approximately 0.86 under the condition of 5 boreholes. This indicates that by using feedback planning of supplementary drilling paths through candidate abnormal areas, internal damaged boundary anchor points, and unconfirmed boundary sections, aimless drilling can be reduced, and the integrity of damaged boundaries can be improved while controlling the number of tree interventions.

[0104] Example 2: Figure 5 As shown, this embodiment provides a non-destructive testing device for internal damage of ancient trees using stress wave micro-drilling resistance fusion, comprising: The candidate anomaly region determination module 101 is used to set up multiple peripheral detection nodes around the cross section to be detected on the tree trunk, and sequentially perform stress wave excitation and response acquisition. Based on the propagation time per unit length, normalized amplitude attenuation and path waveform correlation of each node combination, the candidate anomaly region and the initial drilling direction are determined.

[0105] The micro-drilling resistance acquisition module 102 is used to control the acoustic bridge micro-drilling probe to advance along the drilling path according to the candidate abnormal area and the initial drilling direction, and to acquire the drilling depth, propulsion resistance, drill bit rotation drive current and propulsion speed, and generate a micro-drilling resistance sequence and a preliminary abnormal depth section table.

[0106] The internal sound field construction module 103 is used to pause the acoustic bridge micro-drilling probe at each preset depth position to form a migrating internal sound beacon, collect the internal propagation time, internal normalized amplitude attenuation and internal waveform correlation corresponding to each peripheral detection node, and generate a sound field abrupt change section table.

[0107] The acoustic bridge counterfactual response generation module 104 is used to determine the candidate residual depth position based on the preliminary abnormal depth segment table and the acoustic field abrupt change segment table, control the acoustic bridge micro-drilling probe to sequentially form the acoustic bridge cancellation state and the acoustic bridge establishment state, and generate the acoustic bridge difference feature set.

[0108] The internal damage boundary generation module 105 is used to identify the crack interface, cavity edge and continuous decay area based on the sound bridge difference feature set and the micro-drill resistance sequence, and generate the internal damage boundary anchor point set and internal damage boundary.

[0109] The calculation logic and weight allocation in the above formula do not constitute the only limitation of the present invention; the preset parameters and thresholds involved in the formula can be conventionally calibrated and adaptively adjusted by those skilled in the art according to the physical constraints of the actual tree species being detected and the application scenario.

[0110] Those skilled in the art will recognize that the modules and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0111] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. The scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A non-destructive testing method for internal damage of ancient trees using stress wave micro-drilling resistance fusion, characterized in that, Includes the following steps: S1: Set up multiple peripheral detection nodes around the cross section of the tree trunk to be tested, and perform stress wave excitation and response acquisition in sequence. Based on the propagation time per unit length, normalized amplitude attenuation and path waveform correlation of each node combination, determine the candidate abnormal area and the initial drilling direction. S2: Based on the candidate anomaly area and the initial drilling direction, control the acoustic bridge micro-drilling probe to advance along the drilling path, collect drilling depth, propulsion resistance, drill bit rotation drive current and propulsion speed, and generate a micro-drilling resistance sequence and a preliminary anomaly depth segment table; S3: Pause the acoustic bridge micro-drilling probe at each preset depth position to form a migrating internal acoustic beacon. Collect the internal propagation time, internal normalized amplitude attenuation and internal waveform correlation of each peripheral detection node to generate a table of abrupt sound field segments. S4: Determine the candidate residual depth location based on the preliminary abnormal depth segment table and the sound field abrupt change segment table, control the sound bridge micro-drilling probe to sequentially form the sound bridge cancellation state and the sound bridge establishment state, and generate the sound bridge difference feature set. S5: Identify the fracture interface, cavity edge and continuous decay area based on the sound bridge difference feature set and micro-drill resistance sequence, and generate the set of internal residual boundary anchor points and internal residual boundary.

2. The method for non-destructive testing of internal damage in ancient trees using stress wave micro-drilling resistance fusion as described in claim 1, characterized in that, S1 specifically includes: Multiple peripheral detection nodes are set around the cross section to be detected on the tree trunk to collect outer contour data, establish two-dimensional cross section detection coordinates, and generate a topology table of peripheral detection nodes; The stress wave excitation and response acquisition are executed sequentially at each peripheral detection node. The propagation time per unit length is calculated based on the geometric chord length of the node combination, and the normalized amplitude attenuation and path waveform correlation are obtained to generate a set of peripheral stress wave responses. Based on the set of peripheral stress wave responses, comparable path groups are divided, abnormal node combinations are identified, corresponding abnormal propagation paths are mapped to cross-sectional mesh elements, abnormal mesh elements are merged to form candidate abnormal regions, and the initial drilling direction is determined based on the number of abnormal mesh elements passed through.

3. The method for non-destructive testing of internal damage in ancient trees using stress wave micro-drilling resistance fusion as described in claim 1, characterized in that, S2 specifically includes: The drilling inlet and drilling path are determined based on the candidate anomaly area and the initial drilling direction. The maximum allowable drilling depth is calculated by combining the outer contour data, verification extension length and protection retention thickness, and probe drilling instructions are generated. The acoustic bridge micro-drilling probe is controlled to advance gradually, and drilling depth, propulsion resistance, drill bit rotation drive current, drill bit rotation speed and propulsion speed are collected simultaneously to generate a depth-synchronous micro-drilling response record. Valid sampling points are selected, section advance resistance is calculated, healthy reference depth sections are determined, and micro-drilling resistance sequence and preliminary abnormal depth section table are generated based on the degree of relative resistance decrease, the degree of resistance collapse in adjacent sections and near-zero resistance changes, and depth sections to be retested are marked.

4. The method for non-destructive testing of internal damage in ancient trees using stress wave micro-drilling resistance fusion as described in claim 3, characterized in that, The specific steps for selecting valid sampling points include: Sampling points where the advance speed is within the preset advance speed range, the drill bit rotation speed is within the preset rotation speed range, and the acoustic bridge micro-drilling probe is not in the pause, retraction, or repositioning stage are determined as valid sampling points.

5. The method for non-destructive testing of internal damage in ancient trees using stress wave micro-drilling resistance fusion as described in claim 1, characterized in that, S3 specifically includes: Read the healthy reference depth segment and the preliminary abnormal depth segment table, set the preset depth position on the drilling path, control the acoustic bridge micro-drilling probe to pause advance and rotate, form a migrating internal acoustic beacon through the micro-vibration excitation unit, and generate an internal acoustic beacon excitation record; The response waveforms of each migrating internal sound beacon are synchronously collected by the peripheral detection nodes. The internal propagation time, internal normalized amplitude attenuation and internal waveform correlation are calculated to generate an internal sound beacon response group. The internal acoustic beacon response groups are arranged according to the drilling depth to generate a depth-coded internal sound field sequence. Based on the characteristic changes of adjacent preset depth positions, the abrupt sound field segments are identified, and a table of abrupt sound field segments and abnormal propagation directions are generated.

6. The method for non-destructive testing of internal damage in ancient trees using stress wave micro-drilling resistance fusion as described in claim 5, characterized in that, The formation of migratory endogenous sound markers specifically involves: The coded stress wave excitation is performed by modulating sinusoidal pulses using the Hanning window. The coded stress wave excitation consists of multiple pulses within a preset intrinsic excitation reference amplitude range at preset pulse intervals.

7. The method for non-destructive testing of internal damage in ancient trees using stress wave micro-drilling resistance fusion as described in claim 1, characterized in that, S4 specifically includes: The preliminary abnormal depth section table and the acoustic field abrupt change section table are compared according to the drilling depth to determine the location of the first type of candidate residual depth and the location of the second type of candidate residual depth, and a candidate residual depth location table is generated. The acoustic bridge micro-drilling probe is controlled to stop at each candidate residual depth position in sequence, and the first radial micro-contact segment and the second radial micro-contact segment are driven to perform state acquisition before cancellation, state acquisition after cancellation, and state acquisition after cancellation, and record the position where the acoustic bridge cannot be established. Based on the internal propagation time, internal normalized amplitude attenuation, and internal waveform correlation corresponding to each state, the acoustic bridge cancellation reference value, acoustic bridge counterfactual response group, and acoustic bridge difference feature set are generated.

8. The method for non-destructive testing of internal damage in ancient trees using stress wave micro-drilling resistance fusion as described in claim 7, characterized in that, During the state acquisition process, the radial micro-contact segment expands in the following manner: A wedge-shaped pusher structure driven by a micro piezoelectric ceramic actuator or a micro motor pushes the arc-shaped metal contact plate on the outside of the acoustic bridge micro-drilling probe to expand radially outward so as to fit tightly against the inner wall of the borehole.

9. The method for non-destructive testing of internal damage in ancient trees using stress wave micro-drilling resistance fusion as described in claim 1, characterized in that, S5 specifically includes: Based on the counterfactual response group of the acoustic bridge corresponding to the healthy reference depth segment, establish the acoustic bridge difference judgment range, calculate the acoustic bridge recovery score and the proportion of effective nodes of the acoustic bridge at the candidate damaged depth position, and generate the effective depth position table of the acoustic bridge. The effective depth location table of the sound bridge, the location where the sound bridge cannot be established, and the micro-drilling resistance sequence are associated with the drilling depth to identify the fracture interface, cavity edge, and continuous decay area, and generate a set of internal residual boundary anchor points. The set of internal damaged boundary anchor points is mapped to the cross section of the tree trunk to be inspected, generating the boundary of cavities, the boundary of continuous decayed areas, and the interface line of cracks. Supplementary candidate abnormal areas are generated for unconfirmed boundary sections, and the results of internal damage detection of ancient trees are output.

10. A non-destructive testing device for internal damage of ancient trees using stress wave micro-drilling resistance fusion, employing the non-destructive testing method for internal damage of ancient trees using stress wave micro-drilling resistance fusion as described in any one of claims 1 to 9, characterized in that, include: The candidate anomaly region determination module is used to set up multiple peripheral detection nodes around the cross section of the tree trunk to be detected, and to sequentially perform stress wave excitation and response acquisition. Based on the propagation time per unit length, normalized amplitude attenuation and path waveform correlation of each node combination, the candidate anomaly region and the initial drilling direction are determined. The micro-drilling resistance acquisition module is used to control the acoustic bridge micro-drilling probe to advance along the drilling path based on candidate abnormal areas and the initial drilling direction, and to acquire drilling depth, propulsion resistance, drill bit rotation drive current and propulsion speed, and generate micro-drilling resistance sequence and preliminary abnormal depth segment table. The internal sound field construction module is used to pause the acoustic bridge micro-drilling probe at each preset depth position to form a migrating internal sound beacon, collect the internal propagation time, internal normalized amplitude attenuation and internal waveform correlation corresponding to each peripheral detection node, and generate a sound field abrupt change segment table. The acoustic bridge counterfactual response generation module is used to determine the candidate residual depth location based on the preliminary abnormal depth segment table and the acoustic field abrupt change segment table, control the acoustic bridge micro-drilling probe to sequentially form the acoustic bridge cancellation state and the acoustic bridge establishment state, and generate the acoustic bridge difference feature set. The internal damage boundary generation module is used to identify the crack interface, cavity edge and continuous decay area based on the acoustic bridge difference feature set and micro-drill resistance sequence, and generate the internal damage boundary anchor point set and internal damage boundary.

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