A dam underwater crack detection method, device and equipment based on a transparent long mirror and a storage medium

Abstract

This disclosure provides a method, apparatus, device, and storage medium for detecting underwater cracks in dams based on a transparent telescope. The method includes establishing an optical observation channel using a transparent telescope, acquiring and analyzing images of the dam surface in a target area to obtain optical detection results; acquiring and analyzing echo information of the dam body in the target area using a sonar array deployed at the telescope's end to obtain acoustic detection results; acquiring the crack leakage situation in the target area using a pre-set leakage monitoring sensor to obtain leakage monitoring results; fusing the optical, acoustic, and leakage monitoring results to obtain a fusion result; calculating the total confidence level and the overall probability of crack presence; and outputting the crack detection result for the target area. This improves the accuracy and completeness of crack identification, and multi-modal fusion and dynamic updates enhance detection reliability, meeting the requirements for precise underwater crack detection in dams.

Description

Technical Field

[0001] This disclosure relates to the field of structural inspection technology, and in particular to a method, apparatus, equipment and storage medium for detecting underwater cracks in dams based on a transparent long lens. Background Technology

[0002] Dams, as critical hydraulic structures, play a vital role in flood control, water supply, and ecological security. However, the formation and propagation of underwater cracks in dams are often difficult to detect in a timely manner, especially in turbid water environments. Conventional optical imaging detection methods are limited by suspended solids and sediment, resulting in extremely low visibility and hindering accurate observation. Currently used detection methods include sonar detection, underwater robots and cameras, and manual diving inspections.

[0003] While sonar detection can detect the general distribution of cracks, its resolution is limited, making it difficult to identify small cracks. Underwater robots and cameras are limited by turbid water, resulting in blurry images and low recognition rates. Manual diving inspections are highly dangerous and greatly restricted by water quality and visibility. These methods are insufficient to meet the requirements for accurate detection of underwater cracks in dams, necessitating a new method that can improve optical detection conditions in turbid water, thereby enabling visual detection of underwater cracks in dams. Summary of the Invention

[0004] In order to solve the above-mentioned technical problems, or at least partially solve the above-mentioned technical problems, this disclosure provides a method, apparatus, equipment and storage medium for detecting underwater cracks in dams based on a transparent long lens.

[0005] This disclosure provides a method for detecting underwater cracks in dams based on a transparent long lens. The method includes: An optical observation channel is established using a transparent long lens. The dam surface image of the target area on the dam is acquired through the optical observation channel. The dam surface image is analyzed to obtain optical detection results, which include the location of cracks on the dam surface, crack geometric parameters, and optical detection confidence level. The sonar arranged at the end of the transparent long lens is used to obtain the dam echo information of the target area. The dam echo information is analyzed based on the optical detection results to obtain the acoustic detection results, which include the probability of acoustic cracks and the acoustic detection confidence level. The leakage situation of cracks in the target area is obtained by using a preset leakage monitoring sensor, and the leakage monitoring results include leakage index and leakage judgment confidence level. The optical detection results, acoustic detection results, and leakage monitoring results are fused to obtain a fusion result. Based on the fusion result, the total confidence score and the overall probability of crack existence are calculated. The crack detection result of the target area is output according to the total confidence score and the overall probability of crack existence.

[0006] The method provided in this disclosure involves an adjustable light source and an imaging device configured at the end of the transparent long mirror. The end of the transparent long mirror is located in the air environment and connected to the imaging device, while the end of the transparent long mirror is located in the water environment and on the surface of the dam, thus forming an optical observation channel. The process involves establishing an optical observation channel using a transparent long lens, acquiring images of the dam surface of the target area through this channel, analyzing the dam surface images, and obtaining optical detection results, including: The adjustable light source is used to provide directional illumination to the underwater surface of the dam. The imaging results of the directional illumination are transmitted to the imaging device through the low-scattering optical path constructed by the optical observation channel to obtain an image of the dam surface. The dam surface image is preprocessed, geometric parameters are extracted based on the image preprocessing results, and optical detection results are obtained based on the extracted geometric parameters.

[0007] The method provided in this disclosure, which utilizes a sonar array arranged at the end of the transparent long lens to acquire dam echo information of the target area, and analyzes the dam echo information based on the optical detection results to obtain acoustic detection results, includes: Using the sonar arranged at the end of the transparent long mirror, acoustic pulses are directionally emitted toward the dam body in the target area to obtain the dam body echo signal; The echo signal of the dam body is subjected to echo feature extraction. Based on the extracted echo features, the structural discontinuity region of the target area is identified. The probability of acoustic cracks in the structural discontinuity region and the acoustic detection confidence are calculated based on the echo features to obtain the acoustic detection result of the target area.

[0008] The method provided in this disclosure uses a preset leakage monitoring sensor to acquire information about crack leakage in the target area, and obtains leakage monitoring results, which include a leakage index and a leakage determination confidence level. The transparent long mirror is equipped with a leakage monitoring sensor at its water inlet end. The leakage monitoring sensor includes a bubble sensor and a pressure sensor, comprising: Based on the bubble sensor, the bubble frequency is obtained, and based on the pressure sensor, the pressure fluctuation is obtained. The bubble frequency and pressure fluctuation are compared with a preset sensor baseline model under normal conditions. Based on the comparison results, the leakage risk points of the target area are determined, and the leakage monitoring results of the target area are determined based on the leakage risk points.

[0009] The method provided in this disclosure fuses the optical detection results, acoustic detection results, and leakage monitoring results to obtain a fused result, including: The confidence levels of optical detection, acoustic detection, and leakage determination in the optical detection results, acoustic detection results, and leakage monitoring results are standardized. Based on the optical signal-to-noise ratio, acoustic signal-to-noise ratio, and leakage monitoring signal-to-noise ratio corresponding to the optical detection results, acoustic detection results, and leakage monitoring results; Based on the optical signal-to-noise ratio and the standardized optical detection confidence level, the optical modal reliability is determined; based on the acoustic signal-to-noise ratio and the standardized acoustic detection confidence level, the acoustic modal reliability is determined; based on the leakage monitoring signal-to-noise ratio and the standardized leakage determination confidence level, the leakage determination modal reliability is determined. The optical modal adaptive weights are determined based on the optical modal reliability, the acoustic modal adaptive weights are determined based on the acoustic modal reliability, and the leakage determination modal adaptive weights are determined based on the leakage determination modal reliability. The optical modal reliability, acoustic modal reliability, and leakage determination modal reliability are fused based on the optical modal adaptive weight, acoustic modal adaptive weight, and leakage determination modal adaptive weight to obtain the fusion result.

[0010] The method provided in this disclosure fuses the optical modal reliability, acoustic modal reliability, and leakage determination modal reliability based on the optical modal adaptive weight, acoustic modal adaptive weight, and leakage determination modal adaptive weight to obtain a fusion result, including: The preset conflict handling logic is executed based on the adaptive weights of optical modality, acoustic modality, and leakage determination modality, as well as the confidence levels of optical detection, acoustic detection, and leakage determination. The first conflict situation is determined according to the conflict handling logic. If the difference between the optical detection confidence and the acoustic confidence is greater than the preset difference, it is the first conflict situation. The leakage monitoring results are used to verify the optical detection results and the acoustic detection results. If the leakage index value in the leakage monitoring result is greater than a preset threshold, then the acoustic detection result is supported and a support relationship is obtained; if the leakage index value in the leakage monitoring result is less than a preset threshold, then the optical detection result is supported and a verification result is obtained based on the support relationship. According to the conflict handling logic, a second conflict situation is determined. If the confidence levels of optical detection, acoustic detection, and leakage determination are all less than the preset confidence levels, then it is a second conflict situation, and the target area is determined as an uncertain area. The uncertain area must be reacquired. According to the conflict handling logic, a third conflict situation is determined. If the confidence level of acoustic detection and the confidence level of leakage determination are greater than the preset confidence level, and the confidence level of optical detection is less than the preset confidence level, then it is a third conflict situation, and the target area is marked as a potential hidden crack. The result obtained by integrating all conflict handling logics is the fused result.

[0011] The method provided in this disclosure calculates a total confidence level and a comprehensive crack presence probability based on the fusion result, and outputs a crack detection result for the target area according to the total confidence level and the comprehensive crack presence probability, including: The total confidence level is calculated by weighting the fusion results, and the overall probability of the existence of cracks in the target area is calculated based on the total confidence level and the prior probability derived from historical data. Based on the fusion results, the crack geometric parameters and the corresponding leakage risk level are determined; A trend sequence over a short period of time is generated for the target area based on the probability of the existence of the comprehensive cracks; The crack detection results for the target area are output based on the comprehensive crack existence probability, leakage index, crack geometric parameters, and trend sequence.

[0012] This disclosure also provides a device for detecting underwater cracks in dams based on a transparent long mirror, the device comprising: The first detection module is used to establish an optical observation channel using a transparent long lens, acquire dam surface images of the target area on the dam through the optical observation channel, analyze the dam surface images, and obtain optical detection results, which include the location of cracks on the dam surface, crack geometric parameters, and optical detection confidence level. The second detection module is used to acquire the dam echo information of the target area using the sonar arranged at the end of the transparent long lens, analyze the dam echo information based on the optical detection results, and obtain acoustic detection results, which include the probability of acoustic cracks and the confidence level of acoustic detection. The monitoring module is used to acquire the crack leakage situation in the target area using a preset leakage monitoring sensor, and obtain leakage monitoring results, which include leakage index and leakage judgment confidence level. The output module is used to fuse the optical detection results, acoustic detection results, and leakage monitoring results to obtain a fusion result, calculate the total confidence score and the overall crack existence probability based on the fusion result, and output the crack detection result of the target area according to the total confidence score and the overall crack existence probability.

[0013] The apparatus provided in this disclosure includes an adjustable light source and an imaging device at the end of the transparent long mirror. The end of the transparent long mirror is located in the air environment and connected to the imaging device, while the end of the transparent long mirror is located in the water environment and on the surface of the dam, thus forming an optical observation channel. The first detection module is specifically used for: The adjustable light source is used to provide directional illumination to the underwater surface of the dam. The imaging results of the directional illumination are transmitted to the imaging device through the low-scattering optical path constructed by the optical observation channel to obtain an image of the dam surface. The dam surface image is preprocessed, geometric parameters are extracted based on the image preprocessing results, and optical detection results are obtained based on the extracted geometric parameters.

[0014] The apparatus provided in this disclosure, wherein the second detection module is specifically used for: Using the sonar arranged at the end of the transparent long mirror, acoustic pulses are directionally emitted toward the dam body in the target area to obtain the dam body echo signal; The echo signal of the dam body is subjected to echo feature extraction. Based on the extracted echo features, the structural discontinuity region of the target area is identified. The probability of acoustic cracks in the structural discontinuity region and the acoustic detection confidence are calculated based on the echo features to obtain the acoustic detection result of the target area.

[0015] The monitoring module provided in this embodiment of the invention The transparent long mirror is equipped with a leakage monitoring sensor at its water inlet end. The leakage monitoring sensor includes a bubble sensor and a pressure sensor, specifically used for: Based on the bubble sensor, the bubble frequency is obtained, and based on the pressure sensor, the pressure fluctuation is obtained. The bubble frequency and pressure fluctuation are compared with a preset sensor baseline model under normal conditions. Based on the comparison results, the leakage risk points of the target area are determined, and the leakage monitoring results of the target area are determined based on the leakage risk points.

[0016] The monitoring module in the apparatus provided in this disclosure is specifically used for: The confidence levels of optical detection, acoustic detection, and leakage determination in the optical detection results, acoustic detection results, and leakage monitoring results are standardized. Based on the optical signal-to-noise ratio, acoustic signal-to-noise ratio, and leakage monitoring signal-to-noise ratio corresponding to the optical detection results, acoustic detection results, and leakage monitoring results; Based on the optical signal-to-noise ratio and the standardized optical detection confidence level, the optical modal reliability is determined; based on the acoustic signal-to-noise ratio and the standardized acoustic detection confidence level, the acoustic modal reliability is determined; based on the leakage monitoring signal-to-noise ratio and the standardized leakage determination confidence level, the leakage determination modal reliability is determined. The optical modal adaptive weights are determined based on the optical modal reliability, the acoustic modal adaptive weights are determined based on the acoustic modal reliability, and the leakage determination modal adaptive weights are determined based on the leakage determination modal reliability. The optical modal reliability, acoustic modal reliability, and leakage determination modal reliability are fused based on the optical modal adaptive weight, acoustic modal adaptive weight, and leakage determination modal adaptive weight to obtain the fusion result.

[0017] The output module of the apparatus provided in this disclosure embodiment is specifically used for: The preset conflict handling logic is executed based on the adaptive weights of optical modality, acoustic modality, and leakage determination modality, as well as the confidence levels of optical detection, acoustic detection, and leakage determination. The first conflict situation is determined according to the conflict handling logic. If the difference between the optical detection confidence and the acoustic confidence is greater than the preset difference, it is the first conflict situation. The leakage monitoring results are used to verify the optical detection results and the acoustic detection results. If the leakage index value in the leakage monitoring result is greater than a preset threshold, then the acoustic detection result is supported and a support relationship is obtained; if the leakage index value in the leakage monitoring result is less than a preset threshold, then the optical detection result is supported and a verification result is obtained based on the support relationship. According to the conflict handling logic, a second conflict situation is determined. If the confidence levels of optical detection, acoustic detection, and leakage determination are all less than the preset confidence levels, then it is a second conflict situation, and the target area is determined as an uncertain area. The uncertain area must be reacquired. According to the conflict handling logic, a third conflict situation is determined. If the confidence level of acoustic detection and the confidence level of leakage determination are greater than the preset confidence level, and the confidence level of optical detection is less than the preset confidence level, then it is a third conflict situation, and the target area is marked as a potential hidden crack. The result obtained by integrating all conflict handling logics is the fused result.

[0018] The output module of the apparatus provided in this disclosure embodiment is specifically used for: The total confidence level is calculated by weighting the fusion results, and the overall probability of the existence of cracks in the target area is calculated based on the total confidence level and the prior probability derived from historical data. Based on the fusion results, the crack geometric parameters and the corresponding leakage risk level are determined; A trend sequence over a short period of time is generated for the target area based on the probability of the existence of the comprehensive cracks; The crack detection results for the target area are output based on the comprehensive crack existence probability, leakage index, crack geometric parameters, and trend sequence.

[0019] This disclosure also provides an electronic device, comprising: a processor; a memory for storing executable instructions of the processor; the processor being configured to read the executable instructions from the memory and execute the instructions to implement the underwater crack detection method for dams based on a transparent telescope provided in this disclosure.

[0020] This disclosure also provides a computer-readable storage medium storing a computer program for executing the underwater crack detection method for dams based on a transparent telescope, as provided in this disclosure.

[0021] The technical solution provided in this disclosure has the following advantages compared with the prior art: The underwater crack detection method for dams based on a transparent telescope, as disclosed in this embodiment, acquires images of the dam surface by constructing an optical observation channel using a transparent telescope, analyzes the optical detection results, acquires echo information using a sonar at the telescope tip, analyzes the acoustic detection results, and acquires leakage information using a leakage sensor, analyzes the leakage monitoring results. The optical, acoustic, and leakage monitoring results are fused, and the overall confidence level and comprehensive crack existence probability are calculated based on the fusion result, outputting the detection results for the target area. By establishing a low-scattering optical path using a transparent telescope, high-definition imaging of cracks is achieved in turbid water. Combined with acoustic and leakage monitoring, the accuracy and completeness of crack identification are improved. Multimodal fusion and dynamic updates enhance detection reliability, meeting the requirements for accurate underwater crack detection in dams. Attached Figure Description

[0022] The above and other features, advantages, and aspects of the embodiments of this disclosure will become more apparent from the accompanying drawings and the following detailed description. Throughout the drawings, the same or similar reference numerals denote the same or similar elements. It should be understood that the drawings are schematic, and the originals and elements are not necessarily drawn to scale.

[0023] Figure 1 A schematic flowchart illustrating the underwater crack detection method for dams based on a transparent long mirror, as provided in this embodiment of the disclosure; Figure 2 This is a schematic diagram of the optical detection principle according to an embodiment of the present disclosure; Figure 3 This is a schematic diagram of the acoustic detection principle according to an embodiment of the present disclosure; Figure 4 This is a schematic diagram of leakage monitoring according to an embodiment of the present disclosure; Figure 5 This is a flowchart illustrating the fusion determination process in an embodiment of this disclosure; Figure 6 A schematic diagram of the underwater crack detection device for dams based on a transparent long mirror provided in an embodiment of this disclosure; Figure 7 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this disclosure. Detailed Implementation

[0024] Embodiments of this disclosure will now be described in more detail with reference to the accompanying drawings. While some embodiments of this disclosure are shown in the drawings, it should be understood that this disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of this disclosure. It should be understood that the accompanying drawings and embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of protection of this disclosure.

[0025] It should be understood that the steps described in the method embodiments of this disclosure may be performed in different orders and / or in parallel. Furthermore, the method embodiments may include additional steps and / or omit the steps shown. The scope of this disclosure is not limited in this respect.

[0026] The term "comprising" and its variations as used herein are open-ended inclusions, meaning "including but not limited to". The term "based on" means "at least partially based on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". Definitions of other terms will be given in the description below.

[0027] It should be noted that the concepts of "first" and "second" mentioned in this disclosure are used only to distinguish different devices, modules or units, and are not used to limit the order of functions performed by these devices, modules or units or their interdependencies.

[0028] It should be noted that the terms "a" and "a plurality of" used in this disclosure are illustrative rather than restrictive, and those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0029] The names of messages or information exchanged between multiple devices in the embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.

[0030] To address the aforementioned issues, this disclosure provides a method for detecting underwater cracks in dams based on a transparent telescope. The method will be described below with reference to specific embodiments.

[0031] Figure 1This is a flowchart illustrating a method for detecting underwater cracks in dams based on a transparent long lens, provided in an embodiment of this disclosure. This method can be executed by a device for detecting underwater cracks in dams based on a transparent long lens, wherein the device can be implemented using software and / or hardware, and is generally integrated into an electronic device.

[0032] Example 1: This embodiment of the present disclosure provides a method for detecting underwater cracks in dams based on a transparent telescope, comprising: S101: Establish an optical observation channel using a transparent long lens, acquire dam surface images of the target area on the dam through the optical observation channel, analyze the dam surface images, and obtain optical detection results, including the location of cracks on the dam surface, crack geometric parameters, and optical detection confidence level. S102: Use the sonar arranged at the end of the transparent long lens to obtain the dam echo information of the target area, analyze the dam echo information based on the optical detection results, and obtain the acoustic detection results, which include the probability of acoustic cracks and the acoustic detection confidence level. S103: Use a preset leakage monitoring sensor to obtain the crack leakage situation in the target area and obtain leakage monitoring results, which include leakage index and leakage judgment confidence level; S104: The optical detection results, acoustic detection results, and leakage monitoring results are fused to obtain a fusion result. Based on the fusion result, the total confidence level and the overall probability of crack existence are calculated. The crack detection result of the target area is output according to the total confidence level and the overall probability of crack existence.

[0033] In this embodiment, such as Figure 2 As shown, the optical detection module corresponds to S101, the acoustic detection module corresponds to S102, the leakage monitoring module corresponds to S103, and the multimodal fusion, final judgment, and result output corresponds to S104. The detection execution sequence is: optical detection module startup → image acquisition and preliminary recognition; acoustic module synchronous scanning → echo signal feature extraction; leakage sensor recording bubble and pressure waveforms; three-modal data sent to the fusion module → output judgment result. The corresponding data processing architecture is that the fusion algorithm runs in the edge computing unit or embedded processor, which has parallel computing capabilities; the AI ​​model (CNN / U-Net) is deployed on the GPU module to output crack recognition results in real time; all modules are synchronized through a unified timestamp to ensure multimodal data alignment. Among them, the relevant steps for calibration and error control are: optical calibration: establishing pixel-physical mapping relationship using a scale target plate; acoustic calibration: calibrating the reflection intensity and crack depth of standard samples; pressure / bubble sensor: establishing response threshold through a constant pressure water tank.

[0034] In this embodiment, such as Figure 3As shown, the transparent telescope is the core optical element of this method. Made of high-transmittance, water-pressure-resistant optical glass or resin, it is long and cylindrical. It is inserted into the water, with one end contacting the dam surface (water entry end) and the other end in the air and connected to the imaging equipment (lens end). Its core function is to establish a stable, low-loss physical optical path from the instrument in the air to the underwater dam surface, directly transmitting light (illumination light and reflected imaging light), avoiding severe scattering and attenuation caused by suspended matter in the water. This is the foundation for achieving high-definition underwater optical imaging.

[0035] In this embodiment, the optical observation channel refers to an integrated system consisting of the transparent long mirror itself and the entire light transmission path it establishes, which physically isolates the imaging device in the air from the underwater observation target but keeps them optically connected.

[0036] In this embodiment, the dam surface image is a two-dimensional digital image that is ultimately captured and output by the imaging device. It records the brightness, texture, and geometric morphology information of the underwater target area of ​​the dam under specific lighting conditions. The pixel grayscale value distribution in the image corresponds to the undulations, cracks, erosion, and other conditions of the dam surface.

[0037] In this embodiment, geometric parameters refer to the characteristic values ​​describing the crack morphology that are quantitatively measured from the preprocessed dam surface image using image analysis algorithms. The main parameters include crack length, average width, maximum width, direction, area, and bifurcation.

[0038] In this embodiment, the optical detection results are structured conclusions generated by the optical detection module based on the dam surface image and extracted geometric parameters. These conclusions include qualitative judgment of cracks, precise location of cracks, detailed list of geometric parameters, and optical detection confidence level.

[0039] In this embodiment, the dam echo signal is a general term for various acoustic wave signals, such as reflection and scattering, generated when an acoustic pulse encounters the dam structure. An echo is generated when an acoustic pulse encounters an interface where the density or elastic modulus of the structure changes.

[0040] In this embodiment, the probability of the existence of an acoustic crack is a probability value calculated based on the quantitative analysis and pattern recognition of the echo characteristics of the structural discontinuity region. It represents the likelihood that the discontinuity in this region is caused by a specific defect type, a crack. During calculation, the probability is estimated by comparing the characteristic model of the crack echo and integrating multiple characteristic parameters.

[0041] In this embodiment, the acoustic detection confidence level is a reliability assessment value for the acoustic detection process and the probability of the existence of acoustic cracks. It reflects the quality of the acoustic data obtained under the current measurement conditions and the credibility of the judgment.

[0042] In this embodiment, the acoustic detection results are a comprehensive, structured output of the acoustic detection module. This includes not only the probability of acoustic crack presence for each structural discontinuity region, but also the corresponding acoustic detection confidence level and the location information of these regions.

[0043] In this embodiment, the leakage monitoring sensor includes a bubble sensor and a pressure sensor.

[0044] In this embodiment, the leakage index is a quantitative indicator calculated by processing data from leakage monitoring sensors. It is used to characterize the severity or likelihood of leakage in a target area. This index comprehensively considers factors such as the frequency of bubble escape, the abnormal amplitude of pressure fluctuations, and the degree of deviation from historical normal baselines. After normalization, it is typically represented as a standardized value. A higher value indicates more significant leakage activity or a higher risk in the area.

[0045] In this embodiment, the leakage determination confidence level is a quantitative assessment of the reliability or certainty of the obtained leakage index and leakage determination conclusion based on the sensor data quality and processing process. The confidence level calculation considers multiple factors such as the signal-to-noise ratio of the sensor signal, the stability and continuity of the data, the degree of matching between abnormal features and the leakage model, and the consistency of the dual-sensor data. A high confidence level indicates good data quality in this leakage monitoring, and the obtained leakage index has high credibility; a low confidence level suggests that the results may have significant uncertainty and should be given lower weight in subsequent multimodal fusion decision-making.

[0046] In this embodiment, the fusion result is the core output of the adaptive fusion process. It is a comprehensive confidence score obtained by multiplying the standardized optical detection confidence score, acoustic detection confidence score, and leakage determination confidence score by their respective adaptive weights, and then summing them by weight.

[0047] In this embodiment, by using preset conflict handling logic, three situations are judged in sequence: optical and acoustic confidence conflict, all three confidences are low, and acoustic and leakage confidences are high but optical confidence is low. Different conflict handling logics are triggered for each situation, and all processing results are integrated to obtain a fusion result.

[0048] In this embodiment, the overall confidence score is an indicator used to quantitatively evaluate the overall reliability and determinism of the final fusion result after completing multimodal adaptive fusion and conflict resolution. It is a comprehensive score calculated by adaptively weighting the confidence scores of optical, acoustic, and leakage monitoring results.

[0049] In this embodiment, the overall crack existence probability is the final quantitative likelihood of a crack existing in the target area, derived by integrating current detection evidence with historical prior information. Typically, Bayes' theorem or other probabilistic fusion methods are applied to combine the total confidence level based on the current fusion result with the prior probability based on historical data.

[0050] In this embodiment, the crack detection result is the final, structured output report of the entire detection method process. It includes a comprehensive crack presence probability, leakage index, detailed crack geometric parameters, leakage risk level, and trend sequence analysis reflecting historical changes.

[0051] The working principle and beneficial effects of this embodiment are as follows: An optical observation channel is constructed using a transparent long lens to acquire images of the dam surface, and the optical detection results are analyzed. Echo information is acquired using a sonar at the lens end, and the acoustic detection results are analyzed. A leakage sensor acquires leakage information, and the leakage monitoring results are analyzed. The optical, acoustic, and leakage monitoring results are fused, and the overall confidence level and the probability of crack existence are calculated based on the fusion results. The detection results for the target area are then output. A low-scattering optical path is established using the transparent long lens, enabling high-definition imaging of cracks in turbid water. Combined with acoustic and leakage monitoring, the accuracy and completeness of crack identification are improved. Multimodal fusion and dynamic updates enhance detection reliability, meeting the requirements for accurate underwater crack detection in dams.

[0052] Example 2: The method provided in this embodiment of the present disclosure, wherein the end of the transparent long mirror is equipped with an adjustable light source and an imaging device. The end of the transparent long mirror is located in the air environment and connected to the imaging device, while the end of the transparent long mirror is located in the water environment and on the surface of the dam, thus forming an optical observation channel. The process involves establishing an optical observation channel using a transparent long lens, acquiring images of the dam surface of the target area through this channel, analyzing the dam surface images, and obtaining optical detection results, including: The adjustable light source is used to provide directional illumination to the underwater surface of the dam. The imaging results of the directional illumination are transmitted to the imaging device through the low-scattering optical path constructed by the optical observation channel to obtain an image of the dam surface. The dam surface image is preprocessed, geometric parameters are extracted based on the image preprocessing results, and optical detection results are obtained based on the extracted geometric parameters.

[0053] In this embodiment, the adjustable light source is an illumination device installed at the end of a transparent long mirror, whose brightness, spectrum, and illumination angle can be adjusted as needed. Its function is to provide active illumination with controllable intensity and direction for the dam surface in the dim underwater environment, thereby enhancing the contrast of dam surface features, especially for the identification of defects such as cracks and holes, while simultaneously suppressing the interference of water-scattered light on imaging quality by optimizing illumination parameters.

[0054] In this embodiment, directional illumination is an illumination strategy implemented by an adjustable light source. This refers to the beam of light emitted by the light source being projected onto the target area on the underwater surface of the dam at a specific direction and concentrated angle after passing through the optical channel of a transparent long lens. Its purpose is to create an illumination effect that highlights the surface morphology, reduces ineffective ambient light diffusion, and thus obtains a high-contrast image with distinct shadows and clear details in the imaging process. This is a key technical aspect for improving the accuracy of crack detection.

[0055] In this embodiment, the low-scattering optical path represents an ideal light transmission state pursued and achieved within the optical observation channel. Because the transparent long lens is made of pure material with a smooth surface, and because the internal light propagates primarily through total internal reflection, the probability and extent of random scattering of light by suspended particles in the water are greatly reduced compared to direct propagation in murky water. The characteristics of the low-scattering optical path ensure the directionality and energy concentration of the imaging light, resulting in a final image with low background noise, sharp target edges, and high clarity.

[0056] In this embodiment, the imaging device is an image sensor mounted on the end of a transparent long lens, typically a high-performance industrial camera, possibly equipped with a dedicated optical lens. It is responsible for receiving reflected light signals from the underwater surface of the dam, transmitted back through the transparent long lens, and converting them into digital electrical signals, thus forming the original image of the dam surface.

[0057] In this embodiment, image preprocessing is a series of digital image processing operations performed on the original dam surface image in a computer. The aim is to improve image quality and prepare for subsequent feature extraction. This may include noise filtering, contrast enhancement, image sharpening, geometric correction, and possibly color correction specific to underwater images.

[0058] The working principle and beneficial effects of this embodiment are as follows: A transparent long lens connects the air-end imaging device and the water-entry dam surface, forming a low-scattering optical path. An adjustable light source illuminates the underwater dam surface directionally through this channel. The reflected light is imaged and transmitted back, preprocessing the dam surface image and extracting crack geometric parameters to generate optical detection results. This reduces water scattering interference, obtains high-definition images of the underwater dam surface, and achieves accurate extraction of crack geometric parameters, providing a reliable optical data foundation for multimodal fusion detection. By establishing a stable low-scattering optical channel in turbid water through the transparent long lens, the visibility and contrast of underwater targets are significantly improved. Under typical working conditions, crack edge and orientation information can still be clearly obtained, meeting the intuitive identification requirements of millimeter-level defects and providing a reliable image foundation for subsequent quantitative analysis.

[0059] Example 3: The method provided in this embodiment of the present disclosure uses a sonar array arranged at the end of the transparent long lens to acquire dam echo information of the target area, analyzes the dam echo information based on the optical detection results, and obtains acoustic detection results, including: Using the sonar arranged at the end of the transparent long mirror, acoustic pulses are directionally emitted toward the dam body in the target area to obtain the dam body echo signal; The echo signal of the dam body is subjected to echo feature extraction. Based on the extracted echo features, the structural discontinuity region of the target area is identified. The probability of acoustic cracks in the structural discontinuity region and the acoustic detection confidence are calculated based on the echo features to obtain the acoustic detection result of the target area.

[0060] In this embodiment, the acoustic pulse is a short, specific frequency acoustic signal actively emitted by a sonar transducer mounted at the end of a transparent long mirror. Its frequency is typically chosen to be within a range that allows for effective propagation in water while also providing a sensitive response to defects in the internal structure of the dam's concrete.

[0061] In this embodiment, the echo characteristics are quantitative descriptive parameters extracted after signal processing and analysis of the dam echo signal. The main characteristics include: echo arrival time, echo amplitude / intensity, echo waveform, spectral characteristics, and multiple reflection characteristics.

[0062] In this embodiment, the structural discontinuity region is a spatial location identified based on echo characteristic analysis, where the acoustic properties inside or on the surface of the dam body undergo abnormal changes. This manifests as a significant anomaly in the echo signal.

[0063] In this embodiment, the formula for calculating the intensity of the dam echo signal is: , where A represents the actual echo amplitude or echo intensity measured at the receiver, which reflects the amount of energy returned by the sound wave after propagation and reflection; It represents the initial amplitude of the sound wave at the sonar transmitter or reference distance, used to characterize the reference energy level of the sonar emitted sound wave, or the theoretical echo amplitude under conditions of no significant propagation attenuation; denoted as the sound wave attenuation coefficient. The depth and location of the crack can be determined by analyzing the echo peak value and delay time; d represents the effective propagation distance of the sound wave in the water and structural medium, which is usually the propagation path length between the sonar transmitter and the reflecting interface (such as cracks or discontinuous areas of the structure).

[0064] The working principle and beneficial effects of this embodiment are as follows: the sonar at the end of the transparent long lens emits acoustic pulses in a directional manner toward the target area, receives and analyzes the echo signal of the dam body, extracts echo features to identify structural discontinuities in the target area, calculates the probability of acoustic cracks in the area and the confidence level of acoustic detection, the acoustic detection can penetrate the optical shielding area, identify internal discontinuities in the structure, provide acoustic probability evidence of cracks, and enhance the detection capability of hidden cracks and deep structural defects.

[0065] Example 4: The method provided in this embodiment of the present disclosure uses a preset leakage monitoring sensor to acquire the leakage situation of cracks in the target area, and obtains leakage monitoring results. The leakage monitoring results include a leakage index and a leakage determination confidence level. The transparent long mirror is equipped with a leakage monitoring sensor at its water inlet end. The leakage monitoring sensor includes a bubble sensor and a pressure sensor, comprising: Based on the bubble sensor, the bubble frequency is obtained, and based on the pressure sensor, the pressure fluctuation is obtained. The bubble frequency and pressure fluctuation are compared with a preset sensor baseline model under normal conditions. Based on the comparison results, the leakage risk points of the target area are determined, and the leakage monitoring results of the target area are determined based on the leakage risk points.

[0066] In this embodiment, the bubble sensor is a sophisticated underwater gas detection device, typically operating based on optical, acoustic, or capacitive principles. It is mounted near the dam surface at the water inlet end of a transparent long lens. Its core function is to monitor and count tiny bubbles escaping from the dam structure into the water, thereby dynamically capturing the direct products of seepage.

[0067] In this embodiment, bubble frequency refers to the number of bubbles or pulse signals detected by the bubble sensor per unit time that escape from a specific target area of ​​the dam.

[0068] In this embodiment, the normal state refers to the background environmental data characteristics collected by the leakage monitoring sensors (bubble and pressure sensors) when the dam structure is intact and there is no leakage. Specifically, it is characterized by an extremely low bubble frequency (close to zero) and stable pressure fluctuations with predictable periodicity or within a stable range.

[0069] In this embodiment, the pressure sensor is a device for measuring fluid pressure, which is usually integrated into the water inlet of the long mirror. It is used to continuously monitor the static and dynamic pressure changes of the water near the dam surface. Its function is to capture local pressure anomalies caused by phenomena such as seepage flow, cavitation, or vortex, as indirect but sensitive physical evidence of leakage.

[0070] In this embodiment, pressure fluctuation refers to the dynamic change in pressure sensor readings that deviates from their long-term average steady-state value, typically manifested as anomalies in amplitude, frequency, or waveform. In the context of leakage, it specifically refers to localized water pressure disturbances with non-periodic or specific spectral characteristics caused by unstable flow resulting from leakage water flow.

[0071] In this embodiment, the sensor baseline model is a mathematical or statistical reference standard used to distinguish between normal background and abnormal leakage signals. The input is a historical dataset of bubble frequency and pressure fluctuations collected over a long period under various operating conditions, in the absence of leakage or under known normal conditions. The output is a model describing the statistical characteristics of sensor readings under normal conditions, serving as a benchmark for determining whether the current data is abnormal.

[0072] In this embodiment, the comparison result is the quantitative difference or anomaly level obtained by statistically analyzing the bubble frequency and pressure fluctuation data acquired by real-time monitoring with the pre-established sensor baseline model.

[0073] In this embodiment, leakage risk points are spatial locations identified based on comparative results, where sensor data shows persistent or significant anomalies. Specific locations deemed to have a high probability of leakage are suspected points of leakage activity and serve as the basis for risk warning and focused review.

[0074] In this embodiment, such as Figure 4 As shown, the crack leakage points include leakage risk points and actual leakage points. The sensor components include bubble sensors and pressure sensors. The main signal processing is to determine the signal spectrum and characteristics through the sensor limit model, and finally obtain the leakage monitoring results.

[0075] The working principle and beneficial effects of this embodiment are as follows: the frequency of bubbles escaping from cracks is monitored by a bubble sensor, and abnormal fluctuations in water pressure are monitored by a pressure sensor. The monitoring data is compared with the sensor baseline model to identify abnormal points as leakage risk points. Based on this, leakage monitoring results are generated, directly capturing physical evidence of leakage activities. Through cross-validation of bubble and pressure parameters, the reliability and accuracy of leakage judgment are improved, and early warning of leakage risks is achieved.

[0076] Example 5: The method provided in this embodiment of the present disclosure fuses the optical detection results, acoustic detection results, and leakage monitoring results to obtain a fused result, including: The confidence levels of optical detection, acoustic detection, and leakage determination in the optical detection results, acoustic detection results, and leakage monitoring results are standardized. Based on the optical signal-to-noise ratio, acoustic signal-to-noise ratio, and leakage monitoring signal-to-noise ratio corresponding to the optical detection results, acoustic detection results, and leakage monitoring results; Based on the optical signal-to-noise ratio and the standardized optical detection confidence level, the optical modal reliability is determined; based on the acoustic signal-to-noise ratio and the standardized acoustic detection confidence level, the acoustic modal reliability is determined; based on the leakage monitoring signal-to-noise ratio and the standardized leakage determination confidence level, the leakage determination modal reliability is determined. The optical modal adaptive weights are determined based on the optical modal reliability, the acoustic modal adaptive weights are determined based on the acoustic modal reliability, and the leakage determination modal adaptive weights are determined based on the leakage determination modal reliability. The optical modal reliability, acoustic modal reliability, and leakage determination modal reliability are fused based on the optical modal adaptive weight, acoustic modal adaptive weight, and leakage determination modal adaptive weight to obtain the fusion result.

[0077] In this embodiment, standardization is a data processing method that uses mathematical transformation to map confidence scores from different detection modalities (optical, acoustic, and leakage) to a common comparable range. This eliminates direct comparison biases caused by differences in units and evaluation scales between different sensors or algorithms, establishing a fair numerical basis for subsequent weight calculation and fusion.

[0078] In this embodiment, the optical signal-to-noise ratio (SNR), acoustic signal-to-noise ratio (SNR), and leakage monitoring SNR are used to measure the quality of the original signals for each mode. The optical SNR is the ratio of the useful signal intensity to the background noise level in the dam surface image, reflecting image clarity. The acoustic SNR is the ratio of the useful defect reflection signal intensity to the environmental noise intensity in the dam echo signal, reflecting acoustic signal quality. The leakage monitoring SNR is the ratio of the abnormal signal intensity representing leakage to the normal environmental background fluctuation intensity in the bubble frequency and pressure fluctuation data, reflecting the significance of the leakage monitoring signal.

[0079] In this embodiment, optical modal reliability, acoustic modal reliability, and leakage determination modal reliability are quantitative indicators that comprehensively evaluate the overall reliability of each detection modality in this detection.

[0080] In this embodiment, the adaptive weights for the optical mode, acoustic mode, and leakage detection mode are calculated based on the reliability of each mode and are dynamic weight coefficients assigned to the modality results during multi-source data fusion. These weights are not fixed but are adaptively adjusted according to the actual data quality (signal-to-noise ratio and confidence level) of each mode in each detection.

[0081] In this embodiment, the multimodal dataset ,in, L represents the length of the crack; W represents the width of the crack. Indicates the direction angle of the crack; Indicates the signal-to-noise ratio of optical detection; ; Indicates the confidence level of the acoustic detection; Indicates the signal-to-noise ratio of acoustic detection; ; Indicates the confidence level of the leakage determination; The signal-to-noise ratio of leakage monitoring is represented by the leakage index, which is a quantitative indicator of leakage risk calculated based on monitoring results such as bubble frequency and pressure fluctuation.

[0082] In this embodiment, the calculation formula corresponding to the fusion process is: , , ,in, represents the confidence level of the i-th mode; k represents the smoothing coefficient; P0 represents the neutral threshold; This represents the reliability of the i-th mode; This represents the signal-to-noise ratio of the i-th mode; represents the adaptive weight of the i-th mode; j and i both represent the index of the mode.

[0083] In this embodiment, such as Figure 5 As shown, the final crack detection results are obtained based on the optical detection results, acoustic detection results, and leakage monitoring results.

[0084] The working principle and beneficial effects of this embodiment are as follows: the confidence level of each detection result is standardized, the reliability of each modality is calculated by combining the confidence-to-noise ratio of each result, the adaptive weight of each modality is determined based on the reliability of each modality, the standardized confidence level is weighted and fused using the weights to obtain the fusion result, and the modal weights are dynamically adjusted according to the data quality and confidence level to achieve quantitative evaluation and fusion of reliability, improve the scientific nature of decision-making, enhance the robustness and accuracy of the overall detection system in complex underwater environments, construct a collaborative detection framework of optical, acoustic and leakage three modes, adopt an adaptive fusion weight with confidence level and signal-to-noise ratio as the core, and cooperate with conflict identification and long-term dynamic update mechanism to effectively reduce false judgment and missed detection, and improve stability and robustness under complex environment and operating condition disturbances.

[0085] Example 6: The method provided in this embodiment of the present disclosure fuses the optical modal reliability, acoustic modal reliability, and leakage determination modal reliability based on the optical modal adaptive weight, acoustic modal adaptive weight, and leakage determination modal adaptive weight to obtain a fusion result, including: The preset conflict handling logic is executed based on the adaptive weights of optical modality, acoustic modality, and leakage determination modality, as well as the confidence levels of optical detection, acoustic detection, and leakage determination. The first conflict situation is determined according to the conflict handling logic. If the difference between the optical detection confidence and the acoustic confidence is greater than the preset difference, it is the first conflict situation. The leakage monitoring results are used to verify the optical detection results and the acoustic detection results. If the leakage index value in the leakage monitoring result is greater than a preset threshold, then the acoustic detection result is supported and a support relationship is obtained; if the leakage index value in the leakage monitoring result is less than a preset threshold, then the optical detection result is supported and a verification result is obtained based on the support relationship. According to the conflict handling logic, a second conflict situation is determined. If the confidence levels of optical detection, acoustic detection, and leakage determination are all less than the preset confidence levels, then it is a second conflict situation, and the target area is determined as an uncertain area. The uncertain area must be reacquired. According to the conflict handling logic, a third conflict situation is determined. If the confidence level of acoustic detection and the confidence level of leakage determination are greater than the preset confidence level, and the confidence level of optical detection is less than the preset confidence level, then it is a third conflict situation, and the target area is marked as a potential hidden crack. The result obtained by integrating all conflict handling logics is the fused result.

[0086] In this embodiment, the conflict handling logic is a set of pre-defined procedural decision rules designed to resolve the judgment problem when there are contradictions or inconsistencies between the output results of the three detection modes: optical, acoustic, and leakage. Several specific conflict scenarios are defined, and corresponding verification, decision, or marking steps are specified for each scenario to ensure that the fusion process can still produce a logically consistent and reasonable final conclusion when data conflicts occur.

[0087] In this embodiment, the first conflict situation is a typical conflict scenario defined in the conflict handling logic. Its triggering condition is that the numerical difference (absolute value) between the optical detection confidence and the acoustic detection confidence is greater than a preset difference, indicating that there is a significant difference between the two methods of optical and acoustic in judging the same area, and a third type of evidence needs to be introduced for arbitration.

[0088] In this embodiment, the preset difference is a pre-set numerical threshold used to determine whether there is a significant discrepancy between optical and acoustic confidence levels. Only when the absolute difference between the two confidence levels exceeds this value is it considered a first conflict situation, triggering the conflict handling logic. The preset threshold is a numerical threshold used to determine the level of the leakage index when handling the first conflict situation. Comparing the leakage index with this threshold is the arbitration basis for deciding whether to ultimately support the optical or acoustic result.

[0089] In this embodiment, the support relationship is a judgment relationship that is clearly derived in the arbitration of the first conflict situation, which tends to support the optical detection result or the acoustic detection result.

[0090] In this embodiment, the verification result is an intermediate conclusion generated after adjudicating conflicting optical and acoustic results based on the support relationship. This resolves the direct conflict between the current modes and provides a key input for generating the final fusion result.

[0091] In this embodiment, the second conflict situation is another scenario defined by the conflict handling logic. Its triggering condition is that the confidence levels of optical detection, acoustic detection, and leakage judgment are all lower than the preset confidence levels, indicating that the data quality of all detection modes in the current area is unreliable, and a reliable judgment cannot be made. The system cannot trust any single result.

[0092] In this embodiment, the uncertain region is the target region that is marked as uncertain when the second conflict situation is triggered.

[0093] In this embodiment, data reacquisition is a follow-up operation instruction taken for uncertain areas. That is, it is necessary to re-detect the area one or more times to obtain higher quality data, aiming to solve the problem of generally low confidence caused by the harsh environment of a single detection.

[0094] In this embodiment, the third conflict scenario is another scenario defined by the conflict handling logic. Its triggering condition is that the confidence levels of acoustic detection and leakage determination are both higher than the preset confidence levels, while the confidence level of optical detection is lower than the preset confidence level. This indicates that both acoustic and leakage evidence point to structural anomalies (the presence of cracks and potential leakage), but optical inspection fails to clearly see surface cracks.

[0095] In this embodiment, potential hidden cracks are special markers for target areas when a third conflict condition is triggered. These markers indicate that the area is highly likely to contain internal cracks or hidden cracks covered by surface materials (such as dirt or biofouling), requiring close monitoring and potentially necessitating verification using other methods (such as close-up high-definition re-inspection or surface cleaning).

[0096] The working principle and beneficial effects of this embodiment are as follows: by pre-setting conflict handling logic, three situations are judged in sequence: optical and acoustic confidence conflict, all three confidences are low, and acoustic and leakage confidence are high but optical confidence is low. Different conflict handling logics are triggered respectively, and all processing results are integrated to obtain fusion results. This resolves the contradiction of multi-source data, improves the credibility of the results, identifies uncertain areas to guide retesting, effectively discovers potential hidden cracks, and improves detection coverage and risk warning capabilities.

[0097] Example 7: The method provided in this embodiment of the present disclosure calculates the total confidence score and the overall crack existence probability based on the fusion result, and outputs the crack detection result of the target area according to the total confidence score and the overall crack existence probability, including: The total confidence level is calculated by weighting the fusion results, and the overall probability of the existence of cracks in the target area is calculated based on the total confidence level and the prior probability derived from historical data. Based on the fusion results, the crack geometric parameters and the corresponding leakage risk level are determined; A trend sequence over a short period of time is generated for the target area based on the probability of the existence of the comprehensive cracks; The crack detection results for the target area are output based on the comprehensive crack existence probability, leakage index, crack geometric parameters, and trend sequence.

[0098] In this embodiment, historical data refers to a structured data set accumulated from previous periodic inspections of this dam or other similar dams. This includes crack geometry parameters, leakage indices, environmental conditions, and corresponding visual or professional assessment conclusions measured at different historical periods and locations.

[0099] In this embodiment, ,in, This represents the overall confidence level.

[0100] The formula corresponding to the probability of the existence of cracks in this embodiment is: ,in, This indicates the overall probability of cracks existing in the target area at time t+1 after this detection; This represents the prior probability of the target region before this detection, i.e., at time t; This represents the multimodal dataset obtained from the detection at time t. This indicates that, assuming the existence of a crack, D was observed. t The probability of; This indicates that D was observed under the assumption that the crack does not exist. t The probability of.

[0101] In this embodiment, the prior probability is an initial estimate of the likelihood of cracks existing in the target area, based on statistical analysis of historical data, prior to the actual detection. It reflects the inherent risk level of the area in a historical statistical sense. For example, an area that has experienced cracks or leaks multiple times historically would have a higher prior probability. This probability is then combined with the total confidence level derived from the current detection within a Bayesian framework to calculate the final comprehensive probability of crack presence.

[0102] In this embodiment, crack geometry parameters refer to a series of quantitative characteristic values ​​ultimately determined from the fusion results to describe the crack morphology. Combining the preliminary geometric parameters from optical detection with verification or correction from acoustic / leakage evidence, the final output includes crack length, width, depth, orientation, area, and bifurcation.

[0103] In this embodiment, the leakage risk level is a category label that classifies the leakage hazard associated with the target crack based on the fusion results and crack geometric parameters, according to a preset risk matrix or grading standard. For example, it can be divided into levels such as no risk, low risk, medium risk, and high risk.

[0104] In this embodiment, the trend sequence is a time series data formed by arranging the comprehensive crack presence probability or key geometric parameters calculated in the current detection cycle with the corresponding data from multiple historical detections of the target area in chronological order. By analyzing this sequence, the stability, propagation rate, and development trend of cracks can be evaluated, providing dynamic data support for predictive maintenance.

[0105] In this embodiment, the overall solution is modular and easy to integrate, and can be deployed collaboratively with existing equipment and platforms, covering various hydraulic structures such as dams, bridge piers, and water intakes; the detection results can be directly accessed to the safety database to achieve visualized, traceable, and trend-based management, supporting inspection decision-making, maintenance priority ranking, and risk warning closed loop.

[0106] The working principle and beneficial effects of this embodiment are as follows: the total confidence level is calculated by weighting the fusion results, the comprehensive probability of crack existence is calculated by combining the prior probability derived from historical data, the geometric parameters of cracks and leakage risk level are extracted, a crack probability trend sequence of the target area is generated, all information is integrated to output crack detection results, multimodal information is integrated to output quantitative and structured diagnostic reports, and crack development trends are analyzed by combining historical data to provide comprehensive and dynamic data support for risk assessment and maintenance decisions.

[0107] To achieve the above embodiments, this disclosure also proposes a device for detecting underwater cracks in dams based on a transparent telescope.

[0108] Figure 6 This is a schematic diagram of the underwater crack detection device for dams based on a transparent long mirror, provided in an embodiment of this disclosure. The device 200 can be implemented by software and / or hardware, and is generally integrated into an electronic device. For example... Figure 6 As shown, the device 200 includes: a first detection module 201, a second detection module 202, a monitoring module 203, and an output module 204, wherein, The first detection module 201 is used to establish an optical observation channel using a transparent long lens, acquire dam surface images of the target area on the dam through the optical observation channel, analyze the dam surface images, and obtain optical detection results, including the location of cracks on the dam surface, crack geometric parameters, and optical detection confidence level. The second detection module 202 is used to acquire the dam echo information of the target area using the sonar arranged at the end of the transparent long lens, analyze the dam echo information based on the optical detection results, and obtain acoustic detection results, which include the probability of acoustic cracks and the confidence level of acoustic detection. Monitoring module 203 is used to acquire the crack leakage situation in the target area using a preset leakage monitoring sensor, and obtain leakage monitoring results, the leakage monitoring results including leakage index and leakage judgment confidence level; The output module 204 is used to fuse the optical detection results, acoustic detection results and leakage monitoring results to obtain a fusion result, calculate the total confidence score and the overall crack existence probability based on the fusion result, and output the crack detection result of the target area according to the total confidence score and the overall crack existence probability.

[0109] The apparatus provided in this disclosure includes an adjustable light source and an imaging device at the end of the transparent long mirror. The end of the transparent long mirror is located in the air environment and connected to the imaging device, while the end of the transparent long mirror is located in the water environment and on the surface of the dam, thus forming an optical observation channel. The first detection module 201 is specifically used for: The adjustable light source is used to provide directional illumination to the underwater surface of the dam. The imaging results of the directional illumination are transmitted to the imaging device through the low-scattering optical path constructed by the optical observation channel to obtain an image of the dam surface. The dam surface image is preprocessed, geometric parameters are extracted based on the image preprocessing results, and optical detection results are obtained based on the extracted geometric parameters.

[0110] The apparatus provided in this embodiment of the present disclosure, wherein the second detection module 202 is specifically used for: Using the sonar arranged at the end of the transparent long mirror, acoustic pulses are directionally emitted toward the dam body in the target area to obtain the dam body echo signal; The echo signal of the dam body is subjected to echo feature extraction. Based on the extracted echo features, the structural discontinuity region of the target area is identified. The probability of acoustic cracks in the structural discontinuity region and the acoustic detection confidence are calculated based on the echo features to obtain the acoustic detection result of the target area.

[0111] The monitoring module 203 is provided in the embodiment of this disclosure. The transparent long mirror is equipped with a leakage monitoring sensor at its water inlet end. The leakage monitoring sensor includes a bubble sensor and a pressure sensor, specifically used for: Based on the bubble sensor, the bubble frequency is obtained, and based on the pressure sensor, the pressure fluctuation is obtained. The bubble frequency and pressure fluctuation are compared with a preset sensor baseline model under normal conditions. Based on the comparison results, the leakage risk points of the target area are determined, and the leakage monitoring results of the target area are determined based on the leakage risk points.

[0112] The monitoring module 203 in the apparatus provided in this embodiment is specifically used for: The confidence levels of optical detection, acoustic detection, and leakage determination in the optical detection results, acoustic detection results, and leakage monitoring results are standardized. Based on the optical signal-to-noise ratio, acoustic signal-to-noise ratio, and leakage monitoring signal-to-noise ratio corresponding to the optical detection results, acoustic detection results, and leakage monitoring results; Based on the optical signal-to-noise ratio and the standardized optical detection confidence level, the optical modal reliability is determined; based on the acoustic signal-to-noise ratio and the standardized acoustic detection confidence level, the acoustic modal reliability is determined; based on the leakage monitoring signal-to-noise ratio and the standardized leakage determination confidence level, the leakage determination modal reliability is determined. The optical modal adaptive weights are determined based on the optical modal reliability, the acoustic modal adaptive weights are determined based on the acoustic modal reliability, and the leakage determination modal adaptive weights are determined based on the leakage determination modal reliability. The optical modal reliability, acoustic modal reliability, and leakage determination modal reliability are fused based on the optical modal adaptive weight, acoustic modal adaptive weight, and leakage determination modal adaptive weight to obtain the fusion result.

[0113] The output module 204 of the apparatus provided in this embodiment is specifically used for: The preset conflict handling logic is executed based on the adaptive weights of optical modality, acoustic modality, and leakage determination modality, as well as the confidence levels of optical detection, acoustic detection, and leakage determination. The first conflict situation is determined according to the conflict handling logic. If the difference between the optical detection confidence and the acoustic confidence is greater than the preset difference, it is the first conflict situation. The leakage monitoring results are used to verify the optical detection results and the acoustic detection results. If the leakage index value in the leakage monitoring result is greater than a preset threshold, then the acoustic detection result is supported and a support relationship is obtained; if the leakage index value in the leakage monitoring result is less than a preset threshold, then the optical detection result is supported and a verification result is obtained based on the support relationship. According to the conflict handling logic, a second conflict situation is determined. If the confidence levels of optical detection, acoustic detection, and leakage determination are all less than the preset confidence levels, then it is a second conflict situation, and the target area is determined as an uncertain area. The uncertain area must be reacquired. According to the conflict handling logic, a third conflict situation is determined. If the confidence level of acoustic detection and the confidence level of leakage determination are greater than the preset confidence level, and the confidence level of optical detection is less than the preset confidence level, then it is a third conflict situation, and the target area is marked as a potential hidden crack. The result obtained by integrating all conflict handling logics is the fused result.

[0114] The output module 204 of the apparatus provided in this embodiment is specifically used for: The total confidence level is calculated by weighting the fusion results, and the overall probability of the existence of cracks in the target area is calculated based on the total confidence level and the prior probability derived from historical data. Based on the fusion results, the crack geometric parameters and the corresponding leakage risk level are determined; A trend sequence over a short period of time is generated for the target area based on the probability of the existence of the comprehensive cracks; The crack detection results for the target area are output based on the comprehensive crack existence probability, leakage index, crack geometric parameters, and trend sequence.

[0115] The underwater crack detection device for dams based on a transparent long lens provided in this disclosure can execute the underwater crack detection method for dams based on a transparent long lens provided in any embodiment of this disclosure, and has the corresponding functional modules and beneficial effects of the method.

[0116] To implement the above embodiments, this disclosure also proposes a computer program product, including a computer program / instruction, which, when executed by a processor, implements the underwater crack detection method for dams based on a transparent telescope as described in the above embodiments.

[0117] Figure 7 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this disclosure.

[0118] The following is a detailed reference. Figure 7 The diagram illustrates a structural schematic suitable for implementing the electronic device 300 in the embodiments of this disclosure. The electronic device 300 in the embodiments of this disclosure may include, but is not limited to, mobile terminals such as mobile phones, laptops, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and fixed terminals such as digital TVs and desktop computers. Figure 7 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments disclosed herein.

[0119] like Figure 7 As shown, the electronic device 300 may include a processor (e.g., a central processing unit, a graphics processing unit, etc.) 301, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 302 or a program loaded from a memory 308 into a random access memory (RAM) 303. The RAM 303 also stores various programs and data required for the operation of the electronic device 300. The processor 301, ROM 302, and RAM 303 are interconnected via a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.

[0120] Typically, the following devices can be connected to I / O interface 305: input devices 306 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 307 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; memory devices 308 including, for example, magnetic tapes, hard disks, etc.; and communication devices 309. Communication device 309 allows electronic device 300 to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 7 An electronic device 300 with various devices is shown; however, it should be understood that it is not required to implement or possess all of the devices shown. More or fewer devices may be implemented or possessed alternatively.

[0121] In particular, according to embodiments of this disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this disclosure include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program including program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication device 309, or installed from memory 308, or installed from ROM 302. When the computer program is executed by processor 301, it performs the functions defined in the underwater crack detection method for dams based on transparent long lenses according to embodiments of this disclosure.

[0122] It should be noted that the computer-readable medium described above in this disclosure can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this disclosure, a computer-readable storage medium can be any tangible medium that includes or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this disclosure, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can also be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code included on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0123] In some implementations, clients and servers can communicate using any currently known or future-developed network protocol such as HTTP (Hypertext Transfer Protocol) and can interconnect with digital data communication (e.g., communication networks) of any form or medium. Examples of communication networks include local area networks (“LANs”), wide area networks (“WANs”), the Internet (e.g., the Internet of Things), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future-developed networks.

[0124] The aforementioned computer-readable medium may be included in the aforementioned electronic device; or it may exist independently and not assembled into the electronic device.

[0125] The aforementioned computer-readable medium carries one or more programs, which, when executed by the electronic device, cause the electronic device to perform the aforementioned method for detecting underwater cracks in dams based on a transparent long lens.

[0126] Electronic devices can be programmed with computer program code in one or more programming languages ​​or combinations thereof to perform the operations of this disclosure. These programming languages ​​include, but are not limited to, object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as "C" or similar languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0127] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code, which includes one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0128] The units described in the embodiments of this disclosure can be implemented in software or hardware. The names of the units are not, in some cases, intended to limit the specific unit.

[0129] The functions described above in this document can be performed at least in part by one or more hardware logic components. For example, exemplary types of hardware logic components that can be used, without limitation, include: field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), system-on-a-chip (SoCs), complex programmable logic devices (CPLDs), and so on.

[0130] In the context of this disclosure, a machine-readable medium can be a tangible medium that may include or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0131] The above description is merely a preferred embodiment of this disclosure and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of this disclosure is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-described concept. For example, technical solutions formed by substituting the above features with (but not limited to) technical features disclosed in this disclosure that have similar functions.

[0132] Furthermore, while the operations are described in a specific order, this should not be construed as requiring these operations to be performed in the specific order shown or in a sequential order. In certain environments, multitasking and parallel processing may be advantageous. Similarly, while several specific implementation details are included in the above discussion, these should not be construed as limiting the scope of this disclosure. Certain features described in the context of individual embodiments may also be implemented in combination in a single embodiment. Conversely, various features described in the context of a single embodiment may also be implemented individually or in any suitable sub-combination in multiple embodiments.

[0133] Although the subject matter has been described using language specific to structural features and / or methodological logic, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or actions described above. Rather, the specific features and actions described above are merely illustrative examples of implementing the claims.

Claims

1. A method for detecting underwater cracks in dams based on a transparent long lens, characterized in that, include: An optical observation channel is established using a transparent long lens. The dam surface image of the target area on the dam is acquired through the optical observation channel. The dam surface image is analyzed to obtain optical detection results, which include the location of cracks on the dam surface, crack geometric parameters, and optical detection confidence level. The sonar arranged at the end of the transparent long lens is used to obtain the dam echo information of the target area. The dam echo information is analyzed based on the optical detection results to obtain the acoustic detection results, which include the probability of acoustic cracks and the acoustic detection confidence level. The leakage situation of cracks in the target area is obtained by using a preset leakage monitoring sensor, and the leakage monitoring results include leakage index and leakage judgment confidence level. The optical detection results, acoustic detection results, and leakage monitoring results are fused to obtain a fusion result. Based on the fusion result, the total confidence score and the overall probability of crack existence are calculated. The crack detection result of the target area is output according to the total confidence score and the overall probability of crack existence.

2. The method according to claim 1, characterized in that, The transparent long mirror is equipped with an adjustable light source and imaging device at its end. The end of the transparent long mirror is located in the air environment and connected to the imaging device, while the end of the transparent long mirror is located in the water environment and on the surface of the dam, thus forming an optical observation channel. The process involves establishing an optical observation channel using a transparent long lens, acquiring images of the dam surface of the target area through this channel, analyzing the dam surface images, and obtaining optical detection results, including: The adjustable light source is used to provide directional illumination to the underwater surface of the dam. The imaging results of the directional illumination are transmitted to the imaging device through the low-scattering optical path constructed by the optical observation channel to obtain an image of the dam surface. The dam surface image is preprocessed, geometric parameters are extracted based on the image preprocessing results, and optical detection results are obtained based on the extracted geometric parameters.

3. The method according to claim 1, characterized in that, The sonar array at the end of the transparent long lens acquires the dam echo information of the target area. Based on the optical detection results, the acoustic detection results are obtained by analyzing the dam echo information, including: Using the sonar arranged at the end of the transparent long mirror, acoustic pulses are directionally emitted toward the dam body in the target area to obtain the dam body echo signal; The echo signal of the dam body is subjected to echo feature extraction. Based on the extracted echo features, the structural discontinuity region of the target area is identified. The probability of acoustic cracks in the structural discontinuity region and the acoustic detection confidence are calculated based on the echo features to obtain the acoustic detection result of the target area.

4. The method according to claim 1, characterized in that, The leakage monitoring results are obtained by using a preset leakage monitoring sensor to acquire information about crack leakage in the target area. The transparent long mirror is equipped with a leakage monitoring sensor at its water inlet end. The leakage monitoring sensor includes a bubble sensor and a pressure sensor, comprising: Based on the bubble sensor, the bubble frequency is obtained, and based on the pressure sensor, the pressure fluctuation is obtained. The bubble frequency and pressure fluctuation are compared with a preset sensor baseline model under normal conditions. Based on the comparison results, the leakage risk points of the target area are determined, and the leakage monitoring results of the target area are determined based on the leakage risk points.

5. The method according to claim 1, characterized in that, The optical detection results, acoustic detection results, and leakage monitoring results are fused to obtain a fused result, including: The confidence levels of optical detection, acoustic detection, and leakage determination in the optical detection results, acoustic detection results, and leakage monitoring results are standardized. Based on the optical signal-to-noise ratio, acoustic signal-to-noise ratio, and leakage monitoring signal-to-noise ratio corresponding to the optical detection results, acoustic detection results, and leakage monitoring results; Based on the optical signal-to-noise ratio and the standardized optical detection confidence level, the optical modal reliability is determined; based on the acoustic signal-to-noise ratio and the standardized acoustic detection confidence level, the acoustic modal reliability is determined; based on the leakage monitoring signal-to-noise ratio and the standardized leakage determination confidence level, the leakage determination modal reliability is determined. The optical modal adaptive weights are determined based on the optical modal reliability, the acoustic modal adaptive weights are determined based on the acoustic modal reliability, and the leakage determination modal adaptive weights are determined based on the leakage determination modal reliability. The optical modal reliability, acoustic modal reliability, and leakage determination modal reliability are fused based on the optical modal adaptive weight, acoustic modal adaptive weight, and leakage determination modal adaptive weight to obtain the fusion result.

6. The method according to claim 5, characterized in that, The optical modal reliability, acoustic modal reliability, and leakage determination modal reliability are fused based on the optical modal adaptive weights, acoustic modal adaptive weights, and leakage determination modal adaptive weights to obtain a fusion result, including: The preset conflict handling logic is executed based on the adaptive weights of optical modality, acoustic modality, and leakage determination modality, as well as the confidence levels of optical detection, acoustic detection, and leakage determination. The first conflict situation is determined according to the conflict handling logic. If the difference between the optical detection confidence and the acoustic confidence is greater than the preset difference, it is the first conflict situation. The leakage monitoring results are used to verify the optical detection results and the acoustic detection results. If the leakage index value in the leakage monitoring result is greater than a preset threshold, then the acoustic detection result is supported and a support relationship is obtained; if the leakage index value in the leakage monitoring result is less than a preset threshold, then the optical detection result is supported and a verification result is obtained based on the support relationship. According to the conflict handling logic, a second conflict situation is determined. If the confidence levels of optical detection, acoustic detection, and leakage determination are all less than the preset confidence levels, then it is a second conflict situation, and the target area is determined as an uncertain area. The uncertain area must be reacquired. According to the conflict handling logic, a third conflict situation is determined. If the confidence level of acoustic detection and the confidence level of leakage determination are greater than the preset confidence level, and the confidence level of optical detection is less than the preset confidence level, then it is a third conflict situation, and the target area is marked as a potential hidden crack. The result obtained by integrating all conflict handling logics is the fused result.

7. The method according to claim 1, characterized in that, Based on the fusion results, a total confidence score and a comprehensive crack presence probability are calculated. The crack detection results for the target area are then output according to the total confidence score and the comprehensive crack presence probability, including: The total confidence level is calculated by weighting the fusion results, and the overall probability of the existence of cracks in the target area is calculated based on the total confidence level and the prior probability derived from historical data. Based on the fusion results, the crack geometric parameters and the corresponding leakage risk level are determined; A trend sequence over a short period of time is generated for the target area based on the probability of the existence of the comprehensive cracks; The crack detection results for the target area are output based on the comprehensive crack existence probability, leakage index, crack geometric parameters, and trend sequence.

8. A device for detecting underwater cracks in dams based on a transparent long mirror, the device comprising: The first detection module is used to establish an optical observation channel using a transparent long lens, acquire dam surface images of the target area on the dam through the optical observation channel, analyze the dam surface images, and obtain optical detection results, which include the location of cracks on the dam surface, crack geometric parameters, and optical detection confidence level. The second detection module is used to acquire the dam echo information of the target area using the sonar arranged at the end of the transparent long lens, analyze the dam echo information based on the optical detection results, and obtain acoustic detection results, which include the probability of acoustic cracks and the confidence level of acoustic detection. The monitoring module is used to acquire the crack leakage situation in the target area using a preset leakage monitoring sensor, and obtain leakage monitoring results, which include leakage index and leakage judgment confidence level. The output module is used to fuse the optical detection results, acoustic detection results, and leakage monitoring results to obtain a fusion result, calculate the total confidence score and the overall crack existence probability based on the fusion result, and output the crack detection result of the target area according to the total confidence score and the overall crack existence probability.

9. An electronic device, characterized in that, include: Memory; processor; as well as Computer programs; The computer program is stored in the memory and configured to be executed by the processor to implement the underwater crack detection method for dams based on a transparent telescope as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, It stores a computer program / instruction thereon, which, when executed by a processor, implements the steps of the method described in any one of claims 1-7.

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