Non-destructive inspection method, its application in cranes and system

Abstract

The application discloses a nondestructive flaw detection method and application and system thereof in a crane, and the method is characterized in that regular mechanical vibration is applied to a preset area of a target object, which acts on fine cracks on the target object to generate a certain vibration effect, so that the width of the cracks fluctuates to improve the probability of being detected, in addition, the regular mechanical vibration applied to the target object forms artificial noise, so that, after the ultrasonic guided wave detection module is started, the ultrasonic incident signal emitted by the target object and the artificial noise are mixed, the returned ultrasonic echo is the guided wave detection data doped with the artificial noise, and after denoising, if the target object has a crack, the width of the crack changes due to the external vibration, a characteristic echo signal indicating the existence of the crack is formed, and therefore, the detection reliability and reference value are improved.

Description

Technical Field

[0001] This invention relates to quality and safety technology, testing technology, and crane quality monitoring technology, and particularly to non-destructive testing methods and their applications and systems in cranes. Background Technology

[0002] Guided wave testing, as one of the latest methods in the field of non-destructive testing in quality and safety inspection technology, utilizes mechanical stress waves propagating along an extended structure, characterized by long propagation distances and low attenuation. Currently, guided wave testing is widely used for inspecting and scanning numerous engineering structures, especially metal pipelines worldwide; sometimes, single-location inspections can reach hundreds of meters. Besides pipeline inspection, some literature also documents its application in inspecting structures such as rails, bars, and metal plates.

[0003] Ports and docks are crucial transshipment points for maritime cargo transportation, handling large volumes of goods. Containers, as carriers of uniformly packaged goods, are typically transferred within the yard using lifting and hoisting equipment due to their large size and weight. Cranes, as one of the most important transfer tools in ports and docks, are frequently used in cargo yard transfers. Since the main beam of a crane bears the primary load-bearing load during cargo transfer, its load-bearing capacity largely determines the crane's reliability and transfer capability. Currently, crane main beams are primarily box girder and I-beam structures. Among these, box girder structures, due to their more complex load-bearing structure and higher load-bearing capacity, are widely used in high-load-capacity cranes (such as bridge cranes, beam cranes, and gantry cranes used in production workshops, ports, docks, and warehouses). Since cranes used in ports and docks are mostly used in open-air operations and are assembled in open environments, they are not only exposed to wind and sun during their service, but also to humidity and the possibility that sea breezes may carry components that promote corrosion of metals. Therefore, cranes need to undergo frequent component inspections and maintenance. In particular, it is crucial to focus on monitoring the condition of some components with slight corrosion or damage to prevent sudden damage during operation, which could lead to safety accidents or work stoppages.

[0004] Due to the complex and irregular structure of crane components, there is currently little literature documenting the application of guided wave testing to crane components, especially the combination of guided wave testing and crane operation monitoring technology. Cranes operating in ports and docks experience peak and off-peak periods, while their regular quality inspection cycles are relatively fixed. This makes it difficult for equipment managers and users to flexibly conduct preliminary flaw detection when abnormalities occur during equipment use. Especially under short-term, high-frequency use, the probability of malfunctions or abnormalities increases. For some minor cracks, especially axial or short ones, ultrasonic guided wave testing equipment is often difficult to detect. Therefore, a flexible and convenient damage monitoring mechanism for quality inspection, combined with preliminary flaw detection when crane operation monitoring shows abnormalities, to provide assessment results for on-site management to arrange maintenance, would have significant practical implications for crane safety early warning systems. Summary of the Invention

[0005] In view of this, the purpose of this invention is to propose a non-destructive testing method that is reliable in implementation, flexible in application, and provides good reference for test results, as well as its application and system in cranes.

[0006] To achieve the above-mentioned technical objectives, the technical solution adopted by this invention is as follows:

[0007] A non-destructive testing method, comprising:

[0008] S01. Deploy an ultrasonic guided wave detection module in a preset area of ​​the target object according to preset requirements for ultrasonic guided wave detection of the target object.

[0009] S02. The ultrasonic guided wave detection module starts according to preset conditions, performs ultrasonic guided wave detection on the target object, and generates the first guided wave detection data.

[0010] S03. Apply regular mechanical vibration to the preset area of ​​the target object as artificial noise, and then perform ultrasonic guided wave detection on the target object again through the ultrasonic guided wave detection module to generate noisy guided wave detection data.

[0011] S04. Obtain the acoustic wave data corresponding to the man-made noise, perform noise reduction processing on the noisy guided wave detection data, and generate the second guided wave detection data.

[0012] S05. Acquire the first guided wave detection data and the second guided wave detection data, and perform waveform judgment on them according to preset requirements. Then, based on the judgment results, generate a detection result to indicate whether the target object has damage according to preset conditions.

[0013] As one possible implementation, further, the frequency corresponding to the acoustic wave data generated by the regular mechanical vibration described in this solution is not an integer multiple of the acoustic wave frequency output by the ultrasonic guided wave detection module; and the preset area where mechanical vibration is applied to the target object is different from the location where the ultrasonic guided wave detection module is deployed.

[0014] As a preferred implementation method, preferably, in S02 and S03 of this solution, when the ultrasonic guided wave detection module performs ultrasonic guided wave detection on the target object, the target object is in a static state.

[0015] As a preferred implementation, the target object in this solution preferably has at least one feature structure that can return an ultrasonic incident wave within the detection range of the ultrasonic guided wave detection module, and the first guided wave detection data has at least feature waveform data indicating the wave returned by the feature structure.

[0016] As a preferred implementation method, in S03 of this solution, when generating noisy guided wave detection data, its characteristic waveform data is located and judged to determine whether the noisy guided wave detection data has the characteristic waveform data of the ultrasonic guided wave returned by the characteristic structure of the target object in the detection range of the ultrasonic guided wave detection module. If it does not have it, the parameters for applying regular mechanical vibration to the preset area of ​​the target object are changed, and then the ultrasonic guided wave detection module is used to perform ultrasonic guided wave detection on the target object again until noisy guided wave detection data with characteristic waveform data corresponding to the characteristic structure is generated.

[0017] As a preferred implementation method, in S05 of this solution, when the waveform judgment results of the first guided wave detection data and the second guided wave detection data are both that damage exists, a detection result of damage to the target object is generated.

[0018] When only one of the waveform judgment results from the first waveguide detection data and the second waveguide detection data indicates the presence of damage, a detection result indicating suspected damage to the target object is generated.

[0019] When the waveform judgment results of the first guided wave detection data and the second guided wave detection data are both normal, a normal detection result for the target object is generated.

[0020] Based on the above, the present invention also provides a method for monitoring damage to a port crane, which includes the non-destructive testing method described above; the target object is the box girder of the port crane.

[0021] As a preferred implementation method, in S05 of this solution, the waveform of the first guided wave detection data and the second guided wave detection data is judged by a trained detection neural network to generate judgment results respectively.

[0022] As a preferred implementation, the box girder of the crane described in this solution is preferably equipped with a vibration acquisition module for collecting vibrations and a sound acquisition module for collecting sound, which includes:

[0023] A01. In response to the crane's start-up signal, monitor the vibration and sound data of the crane's box girder during operation, and generate vibration monitoring data and sound detection data respectively.

[0024] A02. The vibration monitoring data and sound detection data are judged and statistically analyzed according to the preset thresholds to obtain the number of times the box beam vibrates abnormally and the number of times abnormal noise is generated on its periphery during the operation of the crane, D.

[0025] A03. Monitor the crane's startup status.

[0026] When it is in the start-up state, the number of abnormal vibrations D and the number of abnormal noises X after the crane starts up are monitored in real time. When the number of abnormal vibrations D and / or the number of abnormal noises X during the start-up process of the crane is greater than the preset first threshold N, the crane operation abnormality information is generated and the crane is intervened to stop operation; then the non-destructive testing method of any one of claims 1 to 5 is executed in steps S01 to S05.

[0027] When it is in the off state, enter A04;

[0028] A04. Obtain the number of abnormal vibrations D and the number of abnormal noises X monitored by the crane from startup to shutdown. When the number of abnormal vibrations D and / or the number of abnormal noises X are greater than the preset second threshold M, execute S01 to S05 of the non-destructive testing method according to any one of claims 1 to 5.

[0029] Among them, the first threshold N in A03 is greater than the second threshold M in A04.

[0030] Based on the above, the present invention also provides a flaw detection system, comprising:

[0031] The ultrasonic guided wave detection module is used to be deployed on a preset area of ​​the target object according to preset requirements for ultrasonic guided wave detection of the target object.

[0032] The instruction generation unit is used to generate detection instructions to start the ultrasonic guided wave detection module, perform ultrasonic guided wave detection on the target object, and generate first guided wave detection data or noisy guided wave detection data.

[0033] The vibration application unit is used to apply regular mechanical vibration to a preset area of ​​the target object as artificial noise.

[0034] The data processing unit is used to acquire acoustic wave data corresponding to man-made noise, perform noise reduction processing on the noisy guided wave detection data, and generate second guided wave detection data.

[0035] The data detection unit is used to acquire the first guided wave detection data and the second guided wave detection data, perform waveform judgment on them according to preset requirements, and then generate a detection result indicating whether the target object has damage based on the judgment result and preset conditions.

[0036] Based on the above, the present invention also provides a computer-readable storage medium storing at least one instruction, at least one program, code set, or instruction set, wherein the at least one instruction, at least one program, code set, or instruction set is loaded and executed by a processor to implement the non-destructive testing method or the port crane damage monitoring method as described above.

[0037] By adopting the above technical solution, the present invention has the following beneficial effects compared with the prior art: This solution applies regular mechanical vibration to a preset area of ​​the target object, which generates a certain vibration effect on the fine cracks on the target object, causing the cracks to fluctuate in width (provided that the applied mechanical vibration force is less than the range that the target object can withstand and does not cause plastic deformation on its surface), thereby increasing the probability of detection. In addition, applying regular mechanical vibration to the target object creates artificial noise, which allows the ultrasonic incident signal emitted by the ultrasonic guided wave detection module to the target object after startup to be mixed with artificial noise. The returned ultrasonic echo is guided wave detection data mixed with artificial noise. After denoising, if there is a crack on the target object, when the width of the crack changes due to the applied vibration, a characteristic echo signal can be formed to indicate the existence of the crack, thereby improving the detection reliability and reference value. Attached Figure Description

[0038] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0039] Figure 1 This is a simplified implementation flowchart of the non-destructive testing method of the present invention;

[0040] Figure 2 This is a simplified schematic diagram of the ultrasonic guided wave detection module installed on the box girder of a port crane when the non-destructive testing method of the present invention is applied to a port crane; only the box girder and the part of the structure connected to the box girder are shown in the diagram.

[0041] Figure 3 This is a simplified implementation flowchart of the port crane damage monitoring method of the present invention;

[0042] Figure 4 This is a simplified schematic diagram of the unit module connections of the system of the present invention. Detailed Implementation

[0043] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be particularly noted that the following embodiments are for illustrative purposes only and do not limit the scope of the invention. Similarly, the following embodiments are only some, not all, embodiments of the present invention, and all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0044] Combination Figure 1 As shown in the figure, this embodiment provides a non-destructive testing method, which includes:

[0045] S01. Deploy an ultrasonic guided wave detection module in a preset area of ​​the target object according to preset requirements for ultrasonic guided wave detection of the target object.

[0046] S02. The ultrasonic guided wave detection module starts according to preset conditions, performs ultrasonic guided wave detection on the target object, and generates the first guided wave detection data.

[0047] S03. Apply regular mechanical vibration to the preset area of ​​the target object as artificial noise, and then perform ultrasonic guided wave detection on the target object again through the ultrasonic guided wave detection module to generate noisy guided wave detection data.

[0048] S04. Obtain the acoustic wave data corresponding to the man-made noise, perform noise reduction processing on the noisy guided wave detection data, and generate the second guided wave detection data.

[0049] S05. Acquire the first guided wave detection data and the second guided wave detection data, and perform waveform judgment on them according to preset requirements. Then, based on the judgment results, generate a detection result to indicate whether the target object has damage according to preset conditions.

[0050] In this solution, the target object can be the box girder of a crane. Since the box girder of a crane is made of multiple metal plates welded together, its structure is relatively stable over a certain length and has fewer bends and irregular shapes.

[0051] This solution applies regular mechanical vibration to a preset area of ​​the target object. This vibration causes slight cracks on the target object to fluctuate in width, increasing the probability of detection. Furthermore, the regular mechanical vibration creates artificial noise, mixing the ultrasonic incident signal emitted by the ultrasonic guided wave detection module with this noise after startup. The returned ultrasonic echo is then the guided wave detection data mixed with this artificial noise. Additionally, if the target object has a crack, the change in crack width due to the applied vibration generates a characteristic echo signal indicating the presence of the crack, thus improving detection reliability and reference value.

[0052] To improve the reliability and convenience of guided wave detection data analysis, as a preferred implementation method, in S02 and S03 of this solution, the target object is in a stationary state when the ultrasonic guided wave detection module performs ultrasonic guided wave detection on the target object. Furthermore, the target object in this solution has at least one feature structure capable of returning an ultrasonic incident wave within the detection range of the ultrasonic guided wave detection module, and the first guided wave detection data includes at least characteristic waveform data indicating the return wave from this feature structure.

[0053] To avoid significant interference from external mechanical vibrations to the transmitted signal of the ultrasonic guided wave detection module, as a possible implementation, the frequency of the acoustic wave data generated by the regular mechanical vibrations described in this solution is not an integer multiple of the frequency of the acoustic wave output by the ultrasonic guided wave detection module; and the preset area where mechanical vibrations are applied to the target object is different from the location where the ultrasonic guided wave detection module is deployed.

[0054] In addition, as a preferred implementation method, in S03 of this solution, when generating noisy guided wave detection data, its characteristic waveform data is located and judged to determine whether the noisy guided wave detection data has the characteristic waveform data of the ultrasonic guided wave returned by the characteristic structure of the target object in the detection range of the ultrasonic guided wave detection module. If it does not have it, the parameters for applying regular mechanical vibration to the preset area of ​​the target object are changed, and then the ultrasonic guided wave detection module is used to perform ultrasonic guided wave detection on the target object again until noisy guided wave detection data with characteristic waveform data corresponding to the characteristic structure is generated.

[0055] In terms of data judgment, as a preferred implementation method, in this solution S05, when the waveform judgment results of the first guided wave detection data and the second guided wave detection data are both that there is damage, a detection result of damage to the target object is generated.

[0056] When only one of the waveform judgment results from the first waveguide detection data and the second waveguide detection data indicates the presence of damage, a detection result indicating suspected damage to the target object is generated.

[0057] When the waveform judgment results of the first guided wave detection data and the second guided wave detection data are both normal, a normal detection result for the target object is generated.

[0058] To facilitate and expedite waveform data judgment, as a preferred implementation method, in S05 of this solution, a trained detection neural network is used to judge the waveforms of the first guided wave detection data and the second guided wave detection data, so as to generate judgment results respectively.

[0059] Regarding the training of the detection neural network, the training method for the detection neural network may include:

[0060] M01. Construct a training database, which stores a guided wave dataset, including guided wave data, its corresponding detection objects, and damage information.

[0061] M02. Extract different preset amounts of data from the training database to serve as training data and validation data, respectively.

[0062] M03. Import the training data into the neural network for training to obtain a trained detection neural network;

[0063] M04. Import the validation data into the trained detection neural network for validation. When the validation results meet the preset requirements, the model converges and the training is completed; otherwise, return to M03.

[0064] Since the training mechanism of the detection neural network is an existing technology, it will not be elaborated on here.

[0065] Combination Figure 3 As shown, based on the above, the non-destructive testing method of this embodiment can be used in the damage monitoring method of port cranes. In this case, the target object is the box girder of the port crane; a vibration acquisition module for collecting vibration and a sound acquisition module for collecting sound are arranged on the box girder of the crane. The monitoring method includes:

[0066] A01. In response to the crane's start-up signal, monitor the vibration and sound data of the crane's box girder during operation, and generate vibration monitoring data and sound detection data respectively.

[0067] A02. The vibration monitoring data and sound detection data are judged and statistically analyzed according to the preset thresholds to obtain the number of times the box beam vibrates abnormally and the number of times abnormal noise is generated on its periphery during the operation of the crane, D.

[0068] A03. Monitor the crane's startup status.

[0069] When it is in the start-up state, the number of abnormal vibrations D and the number of abnormal noises X after the crane starts up are monitored in real time. When the number of abnormal vibrations D and / or the number of abnormal noises X during the start-up process of the crane is greater than the preset first threshold N, the crane operation abnormality information is generated and the crane is intervened to stop operation; then the non-destructive testing method of any one of claims 1 to 5 is executed in steps S01 to S05.

[0070] When it is in the off state, enter A04;

[0071] A04. Obtain the number of abnormal vibrations D and the number of abnormal noises X monitored by the crane from startup to shutdown. When the number of abnormal vibrations D and / or the number of abnormal noises X are greater than the preset second threshold M, execute S01 to S05 of the non-destructive testing method according to any one of claims 1 to 5.

[0072] Among them, the first threshold N in A03 is greater than the second threshold M in A04.

[0073] Through the above scheme, in the damage monitoring of port cranes, abnormal vibrations and noises during operation can trigger damage detection of the box girder of the crane, thereby promptly knowing whether the box girder has been damaged when the crane is operating abnormally.

[0074] Combination Figure 4 As shown, based on the above, this embodiment also provides a flaw detection system, which includes:

[0075] An ultrasonic guided wave detection module is used to be deployed on a preset area of ​​a target object according to preset requirements for ultrasonic guided wave detection of the target object. The ultrasonic detection module includes a guided wave emitting unit and a guided wave receiving unit. The guided wave emitting unit is used to excite the ultrasonic guided wave and emit ultrasonic guided wave signals in the preset area of ​​the target object according to preset conditions. The guided wave receiving unit is used to receive the returned signals and form guided wave detection data.

[0076] The instruction generation unit is used to generate detection instructions to start the ultrasonic guided wave detection module, perform ultrasonic guided wave detection on the target object, and generate first guided wave detection data or noisy guided wave detection data.

[0077] The vibration application unit is used to apply regular mechanical vibration to a preset area of ​​the target object as artificial noise.

[0078] The data processing unit is used to acquire acoustic wave data corresponding to man-made noise, perform noise reduction processing on the noisy guided wave detection data, and generate second guided wave detection data.

[0079] The data detection unit is used to acquire the first guided wave detection data and the second guided wave detection data, perform waveform judgment on them according to preset requirements, and then generate a detection result indicating whether the target object has damage based on the judgment result and preset conditions.

[0080] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0081] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute all or part of the steps of the methods of various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0082] The above description is only a part of the embodiments of the present invention and does not limit the scope of protection of the present invention. Any equivalent device or equivalent process transformation made based on the content of the present invention specification and drawings, or direct or indirect application in other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A non-destructive testing method, characterized in that, It includes: S01. Deploy an ultrasonic guided wave detection module in a preset area of ​​the target object according to preset requirements for ultrasonic guided wave detection of the target object. S02. The ultrasonic guided wave detection module starts according to preset conditions, performs ultrasonic guided wave detection on the target object, and generates the first guided wave detection data. S03. Apply regular mechanical vibration to the preset area of ​​the target object as artificial noise, and then perform ultrasonic guided wave detection on the target object again through the ultrasonic guided wave detection module to generate noisy guided wave detection data. S04. Obtain the acoustic wave data corresponding to the man-made noise, perform noise reduction processing on the noisy guided wave detection data, and generate the second guided wave detection data. S05. Acquire the first guided wave detection data and the second guided wave detection data, perform waveform judgment on them according to preset requirements, and then generate a detection result to indicate whether the target object has damage based on the judgment result and preset conditions. The frequency of the acoustic wave data generated by the regular mechanical vibration is not an integer multiple of the frequency of the acoustic wave output by the ultrasonic guided wave detection module; and the preset area where mechanical vibration is applied to the target object is different from the location where the ultrasonic guided wave detection module is deployed. In S02 and S03, when the ultrasonic guided wave detection module performs ultrasonic guided wave detection on the target object, the target object is in a static state. The target object has at least one feature structure that can return an ultrasonic incident wave within the detection range of the ultrasonic guided wave detection module, and the first guided wave detection data has at least feature waveform data that indicates the wave returned by the feature structure. In S03, when generating noisy guided wave detection data, its characteristic waveform data is located and judged to determine whether the noisy guided wave detection data has the characteristic waveform data of the ultrasonic guided wave returned by the characteristic structure of the target object in the detection range of the ultrasonic guided wave detection module. If it does not have it, the parameters for applying regular mechanical vibration to the preset area of ​​the target object are changed, and then the ultrasonic guided wave detection module is used to perform ultrasonic guided wave detection on the target object again until noisy guided wave detection data with characteristic waveform data corresponding to the characteristic structure is generated. In S05, when the waveform judgment results of the first guided wave detection data and the second guided wave detection data are both that damage exists, the detection result of the target object damage is generated. When only one of the waveform judgment results from the first waveguide detection data and the second waveguide detection data indicates the presence of damage, a detection result indicating suspected damage to the target object is generated. When the waveform judgment results of the first guided wave detection data and the second guided wave detection data are both normal, a normal detection result for the target object is generated.

2. A method for monitoring damage to port cranes, characterized in that, It includes the non-destructive testing method as described in claim 1; the target object is the box girder of a port crane.

3. The port crane damage monitoring method as described in claim 2, characterized in that, In S05, the waveform of the first guided wave detection data and the second guided wave detection data is judged by a trained detection neural network to generate judgment results respectively.

4. The port crane damage monitoring method as described in claim 2, characterized in that, The box girder of the crane is equipped with a vibration acquisition module for collecting vibrations and a sound acquisition module for collecting sound, which includes: A01. In response to the crane's start-up signal, monitor the vibration and sound data of the crane's box girder during operation, and generate vibration monitoring data and sound detection data respectively. A02. The vibration monitoring data and sound detection data are judged and statistically analyzed according to the preset thresholds to obtain the number of times the box beam vibrates abnormally and the number of times abnormal noise is generated on its periphery during the operation of the crane, D. A03. Monitor the crane's startup status. When it is in the start-up state, the number of abnormal vibrations D and the number of abnormal noises X after the crane starts up are monitored in real time. When the number of abnormal vibrations D and / or the number of abnormal noises X during the start-up process of the crane is greater than the preset first threshold N, the crane operation abnormality information is generated and the crane is intervened to stop operation; then S01 to S05 of the non-destructive testing method of claim 1 are executed. When it is in the off state, enter A04; A04. Obtain the number of abnormal vibrations D and the number of abnormal noises X monitored by the crane from startup to shutdown. When the number of abnormal vibrations D and / or the number of abnormal noises X are greater than the preset second threshold M, execute S01 to S05 of the non-destructive testing method described in claim 1. Among them, the first threshold N in A03 is greater than the second threshold M in A04.

5. A flaw detection system, which applies the non-destructive testing method of claim 1, characterized in that, It includes: The ultrasonic guided wave detection module is used to be deployed on a preset area of ​​the target object according to preset requirements for ultrasonic guided wave detection of the target object. The instruction generation unit is used to generate detection instructions to start the ultrasonic guided wave detection module, perform ultrasonic guided wave detection on the target object, and generate first guided wave detection data or noisy guided wave detection data. The vibration application unit is used to apply regular mechanical vibration to a preset area of ​​the target object as artificial noise. The data processing unit is used to acquire acoustic wave data corresponding to man-made noise, perform noise reduction processing on the noisy guided wave detection data, and generate second guided wave detection data. The data detection unit is used to acquire the first guided wave detection data and the second guided wave detection data, perform waveform judgment on them according to preset requirements, and then generate a detection result indicating whether the target object has damage based on the judgment result and preset conditions.

6. A computer-readable storage medium, characterized in that: The storage medium stores at least one instruction, at least one program, code set, or instruction set, wherein the at least one instruction, at least one program, code set, or instruction set is loaded and executed by a processor to implement the non-destructive testing method as described in claim 1 or the port crane damage monitoring method as described in any one of claims 2 to 4.

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