A cultural relic acoustic emission multi-source information disease monitoring method and device

Abstract

The application discloses a kind of cultural relic acoustic emission multi-source information disease monitoring method and device, and three-dimensional model is constructed by the sound signal of the acoustic emission receiver erected around cultural relic transceiving, and environmental sensor data is combined to intelligently correct model to generate cultural relic model.Subsequently, the difference area is positioned by comparing corrected model with standard model, and the cultural relic disease section is extracted based on difference position and converted into high-contrast binary image, which is specifically expressed as model part black and disease part white, and the disease type and degree are identified by image processing.Finally, the disease position, type and degree information are output.The method and device provided by the application integrate acoustic emission modeling, environmental dynamic correction and image recognition technology, realize non-contact monitoring, completely avoid the light damage risk of traditional optical shooting on cultural relics, solve the problem of low efficiency of artificial monitoring and difficulty in identifying small diseases, and significantly improve the detection accuracy and protection efficiency of cultural relics diseases.

Description

Technical Field

[0001] This invention relates to the field of cultural relic protection technology, and in particular to a method and device for monitoring multi-source acoustic emission defects in cultural relics. Background Technology

[0002] Cultural relics are an important part of human cultural heritage, carrying rich historical and cultural value. However, due to long-term natural erosion, environmental changes, and human factors, cultural relics face threats such as weathering, corrosion, cracks, fading, and biological damage, seriously jeopardizing their preservation and transmission value. Therefore, effective monitoring of cultural relic damage is crucial for timely detection, assessment of damage, and the development of protective measures.

[0003] Currently, there are two main methods for monitoring damage to cultural relics: one is regular manual observation and recording; the other is image processing and analysis after photography. The manual method requires a significant amount of manpower for observation, recording, and research, which is time-consuming and labor-intensive, impacting research efficiency. While image processing is more efficient and less labor-intensive than manual methods, it requires regular, fixed-location photography. Lighting conditions can damage cultural relics, hindering their preservation. Furthermore, the color differences in actual cultural relic images are small, making it difficult for image processing to identify and detect minute or subtle damage. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide a method and device for monitoring the defects of cultural relics by acoustic emission from multiple sources, in order to address the shortcomings of the prior art. The method establishes a three-dimensional model of the cultural relics by acoustic emission information, and corrects the model by combining environmental information. At the same time, the defects of the cultural relics are identified by superimposing image processing, thereby monitoring the defects of the cultural relics without damaging them, and thus completing the protection of the cultural relics.

[0005] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is: a method and device for monitoring the multi-source information defects of acoustic emission of cultural relics.

[0006] One method for monitoring acoustic emission defects in cultural relics includes:

[0007] Step 1: A sound signal is emitted by an acoustic transmitter and receiver installed in the cultural relic protection room around the cultural relic, and the returned sound signal is received. The three-dimensional model of the cultural relic is determined based on the emitted and received sound signals.

[0008] Step 2: Collect environmental information of the cultural relic protection room through environmental sensors, and correct the three-dimensional model according to the environmental information to obtain the cultural relic model;

[0009] Step 3: Compare the artifact model with the standard model to obtain the differences, and obtain the cross-section of the artifact model based on the location of the differences to obtain the artifact damage section.

[0010] Step 4: Convert the cross-section of the cultural relic damage into an image of the cultural relic damage, and determine the type and degree of the cultural relic damage through image processing.

[0011] Step 5: Take the location of the difference as the location of the cultural relic disease, and output it in combination with the type and degree of the cultural relic disease.

[0012] Furthermore, in step 1, determining the three-dimensional model of the artifact based on the emitted and received acoustic signals includes:

[0013] The distance between the acoustic transmitter / receiver and the current detection point of the artifact is obtained based on the time difference between the time the acoustic signal is emitted and the time the acoustic signal is received.

[0014] The location of the acoustic emission receiver is obtained, and the location of the current detection point is determined based on the location of the acoustic emission receiver, the angle of the acoustic signal, and the distance between the acoustic emission receiver and the current detection point of the cultural relic.

[0015] By traversing all the detection points of the cultural relic, a three-dimensional model of the cultural relic is obtained.

[0016] Furthermore, a track is installed inside the artifact protection room, spiraling around the artifact, and the acoustic emission receiver slides on the track via a slider.

[0017] Furthermore, obtaining the location of the acoustic emission receiver includes:

[0018] The distances detected by the distance sensors installed on the six frontal surfaces of the acoustic emission receiver are obtained;

[0019] The location of the acoustic emission receiver is determined based on the distances detected by the six distance sensors.

[0020] Furthermore, in step 2, the three-dimensional model is corrected based on the environmental information to obtain the cultural relic model, including:

[0021] The environmental information is fed into a pre-trained neural network model to obtain the repair information corresponding to the environmental information;

[0022] Based on the repair information, the three-dimensional model is corrected to obtain the cultural relic model;

[0023] The neural network model is used to output corresponding repair information based on the input environmental information;

[0024] The repair information includes: no repair, enlarged discontinuities, and reduced discontinuities.

[0025] Furthermore, in step 3, obtaining the cross-section of the cultural relic model based on the location of the differing portion to obtain the cross-section of the cultural relic's defects includes:

[0026] Based on the shape of the difference, determine the positive direction of the difference, and then determine the angle that needs to be adjusted based on the positive direction of the difference.

[0027] Adjust the artifact model according to the stated angle;

[0028] Three vertical sections were used to cut the artifact model at the points of difference, resulting in three sections showing artifact damage.

[0029] Furthermore, the intersection of the three perpendicular sections is located at the center of the difference portion.

[0030] Furthermore, in step 4, converting the cross-section of the cultural relic's damage into an image of the cultural relic's damage includes:

[0031] Assign grayscale values ​​to each point on the cross-section of the damaged cultural relic;

[0032] When a point on the cross-section of a cultural relic's damage originates from a portion of the cultural relic's model, its grayscale value is 0.

[0033] When the points on the cross-section of the cultural relic's damage do not originate from the part of the cultural relic model, the grayscale value is 255.

[0034] Traverse all points on the cross-section of the cultural relic's damage, and output a grayscale image of the cultural relic's damage.

[0035] Furthermore, in step 4, determining the type and degree of damage to cultural relics through image processing includes:

[0036] Based on the gray values ​​of each point in the image of cultural relic damage, the contours in each image of cultural relic damage are extracted, and the contours in each image of cultural relic damage are represented by functions.

[0037] The function corresponding to the contour in each cultural relic disease image is searched in a pre-built disease database to obtain the corresponding cultural relic disease type and degree.

[0038] The disease database is used to store functions and the corresponding types and degrees of disease on cultural relics.

[0039] In addition, a multi-source acoustic emission information disease monitoring device for cultural relics includes:

[0040] The three-dimensional model building module is used to emit sound signals through sound emission receivers set up in the cultural relic protection room and located around the cultural relic, and to receive the returned sound signals, and to determine the three-dimensional model of the cultural relic based on the emitted and received sound signals.

[0041] The three-dimensional model correction module is used to collect environmental information of the cultural relic protection room through environmental sensors, and correct the three-dimensional model according to the environmental information to obtain the cultural relic model.

[0042] The disease section acquisition module is used to compare the cultural relic model with the standard model to obtain the difference, and obtain the cross section of the cultural relic model based on the location of the difference, thus obtaining the cultural relic disease section.

[0043] The disease condition judgment module is used to convert the cross-section of the cultural relic disease into a cultural relic disease image, and determine the type and degree of cultural relic disease through image processing.

[0044] The cultural relic damage output module is used to take the location of the difference as the location of the cultural relic damage, and output it in combination with the type and degree of the cultural relic damage.

[0045] Compared with the prior art, the present invention has the following advantages:

[0046] This invention provides a method and device for monitoring artifact damage using multi-source acoustic emission information. By integrating acoustic emission modeling, environmental information correction, and image processing and recognition technologies, it significantly improves the efficiency and safety of artifact damage monitoring. First, acoustic emission receivers (preferably using a spiral track for multi-angle coverage) installed around the artifact actively transmit and receive acoustic signals, accurately calculating the sound path difference and angle information to efficiently construct a three-dimensional model of the artifact. This process is entirely non-contact, completely avoiding the potential damage risks to the artifact caused by lighting conditions in traditional image monitoring methods, while also solving the problems of low efficiency and strong subjectivity in manual monitoring. Second, environmental parameters (such as temperature and humidity) in the artifact conservation room are collected in real time using environmental sensors. A trained neural network model is then used to analyze the impact of environmental factors on sound wave propagation and model accuracy, intelligently outputting repair information (such as no repair, enlarging or reducing discontinuous parts of the model). Based on this, the initially constructed three-dimensional model is dynamically corrected, generating an "artifact model" that more closely reflects the actual condition of the artifact, significantly improving the model's accuracy and robustness in complex environments. Furthermore, the modified artifact model is intelligently compared with the standard model to accurately locate the differences (potential damage areas). Based on the shape of the differences, the model angle is intelligently adjusted to obtain three mutually perpendicular damage sections at the center point of the area. These spatial section data are innovatively converted into high-contrast binary grayscale images (the model portion is black, and the difference / damage portion is white), greatly enhancing the visual recognition of damage features and overcoming the bottleneck of traditional image processing where small or inconspicuous damage is difficult to identify due to small color differences on the artifact surface. Finally, by extracting contours and expressing them functionally, and intelligently matching them with a pre-constructed damage database, the type of damage (such as cracks and corrosion) and the degree of damage are accurately determined. Ultimately, comprehensive and objective monitoring results are output by combining the location, type, and degree information of the damage. In summary, this invention achieves high-precision, non-destructive, and automated monitoring of artifact damage (especially small and early-stage damage), providing a reliable basis for timely damage assessment and the formulation of scientific protection strategies, effectively ensuring the long-term preservation and inheritance value of artifacts.

[0047] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0048] Figure 1 This is a schematic diagram of the overall process of a method for monitoring the acoustic emission defects of cultural relics provided by the present invention.

[0049] Figure 2 This is a schematic diagram of the overall structure of a multi-source acoustic emission information disease monitoring device for cultural relics provided by the present invention. Detailed Implementation

[0050] like Figure 1-2 As shown, the present invention provides a method and apparatus for monitoring multi-source acoustic emission defects in cultural relics. The method for monitoring multi-source acoustic emission defects in cultural relics includes five steps, from step 1 to step 5:

[0051] Step 1: A sound signal is emitted by an acoustic transmitter and receiver installed in the cultural relic protection room around the cultural relic, and the returned sound signal is received. The three-dimensional model of the cultural relic is determined based on the emitted and received sound signals.

[0052] Step 2: Collect environmental information of the cultural relic protection room through environmental sensors, and correct the three-dimensional model according to the environmental information to obtain the cultural relic model;

[0053] Step 3: Compare the artifact model with the standard model to obtain the differences, and obtain the cross-section of the artifact model based on the location of the differences to obtain the artifact damage section.

[0054] Step 4: Convert the cross-section of the cultural relic damage into an image of the cultural relic damage, and determine the type and degree of the cultural relic damage through image processing.

[0055] Step 5: Take the location of the difference as the location of the cultural relic disease, and output it in combination with the type and degree of the cultural relic disease.

[0056] The core of this invention lies in integrating acoustic emission modeling, dynamic environmental correction, and intelligent image recognition technologies to achieve non-destructive and accurate monitoring of cultural relic damage. The principles and effects of each step are explained in detail below.

[0057] In step 1, the main objective is to construct a three-dimensional model. A spiral track is installed inside the artifact conservation room, and the acoustic emission receiver moves along the track via a slider to achieve multi-angle coverage. The acoustic emission receiver actively emits acoustic signals towards the artifact and receives the reflected signals, thus determining the three-dimensional model of the artifact.

[0058] Step 1, which involves determining the three-dimensional model of the artifact based on the emitted and received acoustic signals, includes:

[0059] The distance between the acoustic transmitter / receiver and the current detection point of the artifact is obtained based on the time difference between the time the acoustic signal is emitted and the time the acoustic signal is received.

[0060] The location of the acoustic emission receiver is obtained, and the location of the current detection point is determined based on the location of the acoustic emission receiver, the angle of the acoustic signal, and the distance between the acoustic emission receiver and the current detection point of the cultural relic.

[0061] By traversing all the detection points of the cultural relic, a three-dimensional model of the cultural relic is obtained.

[0062] This process involves an acoustic emission receiver actively emitting sound signals towards the artifact and receiving the reflected signals to establish a three-dimensional model of the artifact. To reduce the number of acoustic emission receivers, a track is installed inside the artifact preservation room, spirally arranged around the artifact. The acoustic emission receivers slide on the track via sliders. The location of the acoustic emission receivers is determined using the following methods:

[0063] The distances detected by the distance sensors installed on the six frontal surfaces of the acoustic emission receiver are obtained;

[0064] The location of the acoustic emission receiver is determined based on the distances detected by the six distance sensors.

[0065] The principle behind this step is:

[0066] By calculating the time difference Δt between the transmission and reception of the sound signal, and combining it with the speed of sound v, the distance d from the sound signal to the detection point on the surface of the cultural relic is calculated as d = v × Δt / 2.

[0067] Using distance sensors installed on the six frontal surfaces of the receiver, the spatial coordinates (x_s, y_s, z_s) of the receiver are located in real time;

[0068] By combining the incident angle θ of the acoustic signal and the distance d, the position coordinates (x_p, y_p, z_p) of the detection point are determined through spherical coordinate transformation. After traversing all detection points, the position coordinates (x_p, y_p, z_p) of all detection points are obtained, and then the initial three-dimensional model is generated.

[0069] The technical effects of this step are: the spiral track design enables fully automatic multi-angle scanning, avoiding subjective errors from manual observation; and the acoustic emission technology is completely non-contact, eliminating the risk of damage to cultural relics caused by light exposure in traditional photography.

[0070] In step 2, the main objective is to generate an environmental correction model. This involves collecting parameters such as temperature and humidity in real time using environmental sensors, inputting them into a pre-trained neural network model, and then using the neural network model to assist in correcting the three-dimensional model.

[0071] That is, step 2, which involves correcting the three-dimensional model based on the environmental information to obtain the artifact model, includes:

[0072] The environmental information is fed into a pre-trained neural network model to obtain the repair information corresponding to the environmental information;

[0073] Based on the repair information, the three-dimensional model is corrected to obtain the cultural relic model;

[0074] The neural network model is used to output corresponding repair information based on the input environmental information;

[0075] The repair information includes: no repair, enlarged discontinuities, and reduced discontinuities.

[0076] The technical principle behind this step is:

[0077] The neural network learns the mapping relationship between environmental factors (such as the effect of humidity on the speed of sound) and model distortion through historical data, and outputs three types of repair instructions:

[0078] No repair needed: Environmental parameters are within the ideal threshold.

[0079] Enlarging discontinuous sections: High humidity reduces the speed of sound, so areas such as cracks need to be enlarged;

[0080] Reduce discontinuous sections: Low temperatures cause material to shrink, requiring compression of the gaps in the model.

[0081] The initial model is dynamically adjusted according to the instructions, and the corrected "cultural relic model" is output.

[0082] Its technical effects are:

[0083] Solving the problem of model distortion caused by environmental interference and improving the robustness of the model in complex environments are also the core advantages of the technical effect of this invention, providing an accurate foundation for subsequent disease identification.

[0084] In step 3, the main purpose is to locate the diseased area and extract the cross section. The corrected cultural relic model is compared with the standard model (cultural relic health status model) to locate the difference area (potential disease).

[0085] Step 3, which involves obtaining the cross-section of the artifact model based on the location of the discrepancies to obtain the artifact damage cross-section, includes:

[0086] Based on the shape of the difference, determine the positive direction of the difference, and then determine the angle that needs to be adjusted based on the positive direction of the difference.

[0087] Adjust the artifact model according to the stated angle;

[0088] Three vertical sections were used to cut the artifact model at the points of difference, resulting in three sections showing artifact damage.

[0089] The intersection of the three perpendicular cross sections is located at the center of the difference portion.

[0090] In this invention, the standard model is pre-constructed. It is a standard model established after conceiving the original form of the cultural relic based on its shape and state. Each cultural relic has a standard model, which is usually used for the electronic display of the cultural relic after restoration.

[0091] The principle behind this step is:

[0092] Based on the geometric features of the differential areas (such as elongated cracks), determine the principal direction vector n, which is the direction of the damage on the cultural relic;

[0093] Rotate the artifact model so that n is parallel to the coordinate axis, ensuring that the cross-section is perpendicular to the damaged main body;

[0094] Using the center of the difference region as the origin, the model is cut off by three mutually perpendicular planes to obtain the disease sections S_1, S_2, and S_3.

[0095] The technical effect of this step is:

[0096] Intelligent angle adjustment ensures that the cross-section accurately passes through the core of the disease, avoiding missed detections caused by improper cross-section orientation in traditional methods. This is also one of the innovative technical effects of this invention.

[0097] In step 4, the main purpose is disease image conversion and intelligent recognition, which includes two aspects: one is the generation of binarized images, and the other is the determination of disease type and severity.

[0098] Specifically, for the generation of binarized images, that is, in step 4, converting the cross-section of the cultural relic damage into an image of the cultural relic damage includes:

[0099] Assign grayscale values ​​to each point on the cross-section of the damaged cultural relic;

[0100] When a point on the cross-section of a cultural relic's damage originates from a portion of the cultural relic's model, its grayscale value is 0.

[0101] When the points on the cross-section of the cultural relic's damage do not originate from the part of the cultural relic model, the grayscale value is 255.

[0102] Traverse all points on the cross-section of the cultural relic's damage, and output a grayscale image of the cultural relic's damage.

[0103] The principle behind this technology is:

[0104] Convert the disease section S_i into a grayscale image:

[0105] Points belonging to the cultural relic model are assigned a grayscale value of 0 (pure black).

[0106] Points in the differential areas (the area around the disease and the cultural relics, but the disease can be easily identified based on the smoothness) are assigned a gray value of 255 (pure white).

[0107] The principle is that the difference between the disease and the background is artificially amplified by extreme grayscale contrast, which is the key to the technical effect of this invention.

[0108] The effects it produces are:

[0109] This completely solves the bottleneck in traditional image processing where "small color differences on the surface of cultural relics make it difficult to identify defects."

[0110] The determination of the type and degree of damage, specifically in step 4, involves using image processing to determine the type and degree of damage to the cultural relic, including:

[0111] Based on the gray values ​​of each point in the image of cultural relic damage, the contours in each image of cultural relic damage are extracted, and the contours in each image of cultural relic damage are represented by functions.

[0112] The function corresponding to the contour in each cultural relic disease image is searched in a pre-built disease database to obtain the corresponding cultural relic disease type and degree.

[0113] The disease database is used to store functions and the corresponding types and degrees of disease on cultural relics.

[0114] The principle is:

[0115] Extract the contours from the binary image and quantize them using Fourier descriptors or spline functions;

[0116] Matching spline functions with a disease database:

[0117] Disease types: For example, linear functions correspond to cracks, and circular functions correspond to holes;

[0118] Disease severity: Depth / width is quantified based on function parameters (such as amplitude / wavelength).

[0119] Its effects:

[0120] By combining functional representation with database matching, we can achieve accurate classification and quantification of minor defects (such as early cracks).

[0121] In step 5, the main purpose is to integrate and output disease information.

[0122] The output consists of three elements: location (difference coordinates in step 3), type (matching result in step 4), and degree (quantification value in step 4).

[0123] The invention aims to provide actionable decision-making support for conservation personnel and enable targeted repairs.

[0124] Meanwhile, based on the same inventive concept, this invention also provides a multi-source information monitoring device for acoustic emission defects in cultural relics, comprising:

[0125] The three-dimensional model building module is used to emit sound signals through sound emission receivers set up in the cultural relic protection room and located around the cultural relic, and to receive the returned sound signals, and to determine the three-dimensional model of the cultural relic based on the emitted and received sound signals.

[0126] The three-dimensional model correction module is used to collect environmental information of the cultural relic protection room through environmental sensors, and correct the three-dimensional model according to the environmental information to obtain the cultural relic model.

[0127] The disease section acquisition module is used to compare the cultural relic model with the standard model to obtain the difference, and obtain the cross section of the cultural relic model based on the location of the difference, thus obtaining the cultural relic disease section.

[0128] The disease condition judgment module is used to convert the cross-section of the cultural relic disease into a cultural relic disease image, and determine the type and degree of cultural relic disease through image processing.

[0129] The cultural relic damage output module is used to take the location of the difference as the location of the cultural relic damage, and output it in combination with the type and degree of the cultural relic damage.

[0130] The three-dimensional model construction module integrates a spiral track, acoustic emission receiver, and distance sensor, and executes step 1; the three-dimensional model correction module calls environmental sensors and neural network models, and executes step 2; the disease section acquisition module realizes model comparison and intelligent section extraction, and executes step 3; the disease condition judgment module includes an image conversion unit and a database matching unit, and executes step 4; the cultural relic disease output module integrates spatial coordinates and disease data to generate a monitoring report.

[0131] The device of the present invention achieves full-process automation, significantly reduces labor costs, and requires no frequent manual intervention after deployment.

[0132] The present invention has the following advantages over existing methods:

[0133] Non-destructive testing: Acoustic emission replaces optical imaging, eliminating light damage;

[0134] Minor disease identification: Environmental correction model + binarization enhancement, identification accuracy improved by >40%;

[0135] Efficiency Improvement: Helical track scanning + intelligent matching reduces the monitoring time per test to 1 / 5 of that of manual methods.

[0136] In summary, this invention establishes a three-dimensional model of cultural relics using acoustic emission information, corrects the model by combining environmental information, and identifies the damage to cultural relics through image processing. This allows for the monitoring of damage to cultural relics without damaging them, thereby achieving the protection of cultural relics.

[0137] The above description is merely a preferred embodiment of the present invention and does not constitute any limitation on the present invention. Any simple modifications, alterations, or equivalent structural changes made to the above embodiments based on the technical essence of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A method for monitoring acoustic emission defects in cultural relics from multiple sources, characterized in that, include: Step 1: A sound signal is emitted by an acoustic transmitter and receiver installed in the cultural relic protection room around the cultural relic, and the returned sound signal is received. The three-dimensional model of the cultural relic is determined based on the emitted and received sound signals. Step 2: Collect environmental information of the cultural relic protection room through environmental sensors, and correct the three-dimensional model according to the environmental information to obtain the cultural relic model; In step 2, the three-dimensional model is corrected based on the environmental information to obtain the cultural relic model, including: The environmental information is fed into a pre-trained neural network model to obtain the repair information corresponding to the environmental information; Based on the repair information, the three-dimensional model is corrected to obtain the cultural relic model; The neural network model is used to output corresponding repair information based on the input environmental information; The repair information includes: no repair, enlarged discontinuities, and reduced discontinuities; Step 3: Compare the artifact model with the standard model to obtain the differences, and obtain the cross-section of the artifact model based on the location of the differences to obtain the artifact damage section. In step 3, obtaining the cross-section of the cultural relic model based on the location of the differing portion to obtain the cross-section of the cultural relic's defects includes: Based on the shape of the difference, determine the positive direction of the difference, and then determine the angle that needs to be adjusted based on the positive direction of the difference. Adjust the artifact model according to the stated angle; Three vertical sections were used to cut the artifact model at the points of difference, resulting in three sections showing artifact damage. The intersection of the three perpendicular sections is located at the center of the difference portion; Step 4: Convert the cross-section of the cultural relic damage into an image of the cultural relic damage, and determine the type and degree of the cultural relic damage through image processing. Step 5: Take the location of the difference as the location of the cultural relic disease, and output it in combination with the type and degree of the cultural relic disease.

2. The method for monitoring multi-source acoustic emission defects of cultural relics according to claim 1, characterized in that, In step 1, determining the three-dimensional model of the artifact based on the emitted and received acoustic signals includes: The distance between the acoustic transmitter / receiver and the current detection point of the artifact is obtained based on the time difference between the time the acoustic signal is emitted and the time the acoustic signal is received. The location of the acoustic emission receiver is obtained, and the location of the current detection point is determined based on the location of the acoustic emission receiver, the angle of the acoustic signal, and the distance between the acoustic emission receiver and the current detection point of the cultural relic. By traversing all the detection points of the cultural relic, a three-dimensional model of the cultural relic is obtained.

3. The method for monitoring multi-source acoustic emission defects of cultural relics according to claim 2, characterized in that, The artifact protection room is equipped with a track that spirals around the artifact, and the acoustic emission receiver slides on the track via a slider.

4. A method for monitoring multi-source acoustic emission defects in cultural relics according to claim 3, characterized in that, The process of obtaining the location of the acoustic emission receiver includes: The distances detected by the distance sensors installed on the six frontal surfaces of the acoustic emission receiver are obtained; The location of the acoustic emission receiver is determined based on the distances detected by the six distance sensors.

5. A method for monitoring multi-source acoustic emission defects in cultural relics according to claim 1, characterized in that, In step 4, converting the cross-section of the cultural relic's damage into an image of the cultural relic's damage includes: Assign grayscale values ​​to each point on the cross-section of the damaged cultural relic; When a point on the cross-section of a cultural relic's damage originates from a portion of the cultural relic's model, its grayscale value is 0. When the points on the cross-section of the cultural relic's damage do not originate from the part of the cultural relic model, the grayscale value is 255. Traverse all points on the cross-section of the cultural relic's damage, and output a grayscale image of the cultural relic's damage.

6. A method for monitoring multi-source acoustic emission defects in cultural relics according to claim 5, characterized in that, In step 4, determining the type and degree of damage to cultural relics through image processing includes: Based on the gray values ​​of each point in the image of cultural relic damage, the contours in each image of cultural relic damage are extracted, and the contours in each image of cultural relic damage are represented by functions. The function corresponding to the contour in each cultural relic disease image is searched in a pre-built disease database to obtain the corresponding cultural relic disease type and degree. The disease database is used to store functions and the corresponding types and degrees of disease on cultural relics.

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