Method and device for detecting fatigue of ship and electronic equipment

Abstract

The invention discloses a method and device for detecting ship fatigue and electronic equipment. According to the specific scheme, for at least one preset detection position, first strain signals collected by at least two optical fiber sensors deployed at the preset detection position are obtained in the traveling process of a target ship; when it is detected that the acquisition duration reaches a preset period duration, denoising the first strain signal within the acquisition duration to obtain a second strain signal; all the second strain signals are converted into stress data, and target principal stress of the preset detection position is determined according to the stress data; and based on the target principal stress and the historical principal stress at each acquisition moment within the acquisition duration, determining a detection point fatigue attribute of the preset detection position, and determining a ship fatigue attribute of the target ship according to the detection point fatigue attribute. According to the invention, the real-time detection of the ship fatigue attribute is realized, the fatigue damage of the ship structure can be prevented in time, and the safety and reliability of the ship structure of the target ship are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular, to a method, device, and electronic device for detecting the fatigue degree of a ship. Background Art

[0002] In order to ensure the safety, reliability, and economy of the ship structure throughout the service life cycle of a ship, the anti-fatigue performance of the ship under repeated loads is usually detected, and corresponding measures are taken according to the detection results to extend the service life of the ship, reduce the ship maintenance cost, and ensure the safe operation of the ship.

[0003] Currently, in the prior art, the fatigue degree of a ship is mainly detected by simulating the external environment of the ship and according to the given sea condition information. However, there is a certain lag in simulating the external environment, and there are often certain differences between the simulated external environment and the real external environment. Therefore, the detection result of the fatigue degree of the ship obtained by simulating the external environment has a certain lag, and it is impossible to accurately maintain the ship structure in a timely manner, which is extremely likely to cause damage to the ship structure. Summary of the Invention

[0004] The present invention provides a method, device, and electronic device for detecting the fatigue degree of a ship, realizing real-time detection of the fatigue attributes of the ship, being able to prevent fatigue damage of the ship structure in a timely manner, and improving the safety and reliability of the ship structure of the target ship.

[0005] According to an aspect of the present invention, there is provided a method for detecting the fatigue degree of a ship, characterized in that at least two fiber optic sensors are deployed at at least one preset detection position of a target ship, and the at least two fiber optic sensors are installed according to a preset installation method. The method includes:

[0006] For at least one preset detection position, during the driving process of the target ship, obtain the first strain signals collected by the at least two fiber optic sensors deployed at the preset detection position; wherein, the first strain signals are related to the force information acting on the preset detection position;

[0007] When it is detected that the acquisition duration reaches a preset cycle duration, perform denoising processing on the first strain signals within the acquisition duration to obtain second strain signals to be used for analysis;

[0008] Convert all the second strain signals into stress data, and determine the target principal stress of the preset detection position according to the stress data;

[0009] Based on the target principal stress and the historical principal stress at each acquisition moment within the acquisition duration, determine the fatigue degree attribute of the detection point at the preset detection position, and determine the ship fatigue attribute of the target ship according to the fatigue degree attribute of the detection point.

[0010] According to another aspect of the present invention, there is provided a device for detecting the fatigue degree of a ship, characterized in that at least two optical fiber sensors are deployed at at least one preset detection position of the target ship, and the at least two optical fiber sensors are installed according to a preset installation method. The device includes:

[0011] A first strain signal acquisition module, configured to acquire, for at least one preset detection position, first strain signals collected by at least two optical fiber sensors deployed at the preset detection position during the driving process of the target ship; wherein, the first strain signal is related to the force information acting on the preset detection position;

[0012] A second strain signal determination module, configured to perform denoising processing on the first strain signals within the acquisition duration when it is detected that the acquisition duration reaches a preset cycle duration, to obtain second strain signals for analysis and use;

[0013] A principal stress determination module, configured to convert all the second strain signals into stress data, and determine the target principal stress at the preset detection position according to the stress data;

[0014] A ship fatigue attribute determination module, configured to determine the fatigue degree attribute of the detection point at the preset detection position based on the target principal stress and the historical principal stress at each acquisition moment within the acquisition duration, and determine the ship fatigue attribute of the target ship according to the fatigue degree attribute of the detection point.

[0015] According to another aspect of the present invention, there is provided an electronic device, which includes:

[0016] At least one processor; and

[0017] A memory communicatively connected to the at least one processor; wherein,

[0018] The memory stores a computer program executable by the at least one processor. The computer program is executed by the at least one processor so that the at least one processor can execute the method for detecting the fatigue degree of a ship according to any embodiment of the present invention.

[0019] According to another aspect of the present invention, there is provided a computer-readable storage medium, which stores computer instructions for causing a processor to implement the method for detecting the fatigue degree of a ship according to any embodiment of the present invention when executed.

[0020] According to another aspect of the present invention, there is provided a computer program product, including a computer program, characterized in that the computer program implements the method for detecting the fatigue degree of a ship according to any embodiment of the present invention when executed by a processor.

[0021] The technical solution of the embodiment of the present invention ensures that the fiber optic sensors can accurately and real-time collect multiple strain signals at the preset detection positions by deploying at least two fiber optic sensors at at least one preset detection position of the target ship, and installing the at least two fiber optic sensors according to the preset installation method. For at least one preset detection position, during the navigation of the target ship, the first strain signals collected by the at least two fiber optic sensors deployed at the preset detection position are obtained, wherein the first strain signals are related to the force information acting on the preset detection position. Based on this, the comprehensiveness of the collected first strain signals is ensured, and the problem of incomplete and non-comprehensive strain signal collection caused by the fact that a single fiber optic sensor can only collect the strain signals corresponding to the force in one direction at the preset detection position is avoided. When it is detected that the acquisition duration reaches the preset cycle duration, the first strain signals within the acquisition duration are denoised to obtain the second strain signals for subsequent analysis. Based on this, invalid or abnormal data within the first strain signals can be removed, improving the accuracy of subsequent data processing. All the second strain signals are converted into stress data, and the target principal stress at the preset detection position is determined according to the stress data. According to the target principal stress and the historical principal stress at each acquisition moment within each acquisition duration, the fatigue degree attribute of the detection point at the preset acquisition position is determined, and according to the fatigue degree attribute of the detection point at each preset detection position, the ship fatigue attribute of the target ship is determined, realizing the real-time fatigue attribute detection of at least one preset detection position of the target ship, providing a data basis for the subsequent maintenance and optimization of the ship structure of the target ship, and improving the safety and reliability of the ship structure of the target ship. The present invention solves the problem in the prior art that the detection result has a certain lag due to simulating the external environment of the ship for ship fatigue detection, resulting in the inability to accurately maintain the ship structure in time. By installing at least two fiber optic sensors at at least one preset detection position of the target ship according to the preset installation method, the problem of non-comprehensive strain signals collected by a single fiber optic sensor is avoided. By denoising the first strain signals to obtain the second strain signals, and converting the second strain signals into stress data to determine the target principal stress at each preset detection position, and then determining the fatigue degree attribute of the detection point at each preset detection position to obtain the ship fatigue attribute of the target ship, the stress data analysis in multiple directions at each preset detection position of the target ship is realized, the potential fracture risk at the preset detection position can be effectively and quickly determined, the speed of determining the ship fatigue attribute is improved, and thus the safety and reliability of the ship structure of the target ship are improved.

[0022] It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present invention, nor is it used to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. Description of the Drawings

[0023] To more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the accompanying drawings required for the description of the embodiments. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can be obtained based on these drawings.

[0024] Figure 1 It is a flowchart of a method for detecting the fatigue degree of a ship provided by an embodiment of the present invention;

[0025] Figure 2 It is an example diagram of an optical fiber sensor provided by an embodiment of the present invention;

[0026] Figure 3 It is an example diagram of welding three optical fiber sensors at a preset detection position at an angle of 60 degrees provided by an embodiment of the present invention;

[0027] Figure 4 It is an example diagram of denoising the first strain signal by using a wavelet transform denoising method provided by an embodiment of the present invention;

[0028] Figure 5 It is an example diagram of the wavelet decomposition process provided by an embodiment of the present invention;

[0029] Figure 6 It is a flowchart of a method for detecting the fatigue degree of a ship provided by an embodiment of the present invention;

[0030] Figure 7 It is an example diagram of the time series of stress provided by an embodiment of the present invention;

[0031] Figure 8 It is a schematic diagram of the S-N curve provided by an embodiment of the present invention;

[0032] Figure 9 It is a schematic structural diagram of a device for detecting the fatigue degree of a ship provided by an embodiment of the present invention;

[0033] Figure 10 It is a schematic structural diagram of an electronic device for implementing the method for detecting the fatigue degree of a ship according to an embodiment of the present invention. Detailed implementation manners

[0034] In order to enable those skilled in the art to better understand the solutions of the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0035] It should be noted that the terms "first", "second", etc. in the description, claims and above-mentioned drawings of the present invention are used to distinguish similar objects, and do not necessarily have to be used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances, so that the embodiments of the present invention described here can be implemented in an order other than those illustrated or described here. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or are inherent to these processes, methods, products or devices.

[0036] Embodiment 1

[0037] Figure 1 FIG. is a flowchart of a method for detecting the fatigue degree of a ship provided in Embodiment 1 of the present invention. This embodiment is applicable to determining the fatigue degree attribute of a detection point at a predicted detection position according to the strain signals collected by optical fiber sensors deployed at preset detection positions, so as to determine the ship fatigue attribute of a target ship and realize the evaluation of the fatigue degree of the target ship. This method can be executed by a device for detecting the fatigue degree of a ship. The device for detecting the fatigue degree of a ship can be implemented in the form of hardware and / or software, and the device for detecting the fatigue degree of a ship can be configured in an electronic device such as a mobile phone, a computer or a server. As Figure 1 shown, the method includes:

[0038] S110. For at least one preset detection position, during the driving of the target ship, obtain first strain signals collected by at least two optical fiber sensors deployed at the preset detection position.

[0039] Among them, the first strain signal is related to the force information acting on the preset detection position. During the navigation of the ship, the stress fatigue area of ​​the ship is usually detected to determine the fatigue of the ship. Since the technical solution provided by the embodiment of the present invention can be used to determine the fatigue of the ship for each ship, the current ship can be used as the target ship. There may be one or more stress fatigue areas in the target ship, and one or more stress fatigue areas can be used as at least one preset detection position of the target ship. It should be noted that the stress fatigue area can be understood as an area where the ship structure of the target ship is prone to cracks or fractures after a period of time under the action of alternating stress. Using the stress fatigue area as a preset detection position can detect the area in the ship structure of the target ship that is prone to cracks or fractures. It can be understood that the preset detection position can be a pre-set area where the ship structure of the target ship is relatively weak and stress is concentrated. Optionally, the preset detection position can be a weak position of the hull where stress is concentrated, the structure is complex in the hull, or the target ship is easily affected by loads such as waves or vibrations during navigation. For example, the preset detection position can be a position such as the deck of the target ship, the weld in the middle or bottom of the hull, the position where the structure intersects, or the corner.

[0040] During the navigation of the target ship, the preset detection position of the target ship will experience a variety of random loads such as complex marine environment, variable speed driving or wave impact. For example, during the navigation of the target ship, waves will impact the hull of the target ship from all directions. Therefore, in order to ensure the comprehensiveness of the collected strain signals, at least two fiber optic sensors can be deployed at at least one preset detection position of the target ship, and at least two fiber optic sensors are installed according to a preset installation method. That is to say, at each preset detection position, at least two fiber optic sensors are installed in a preset installation method to achieve comprehensive detection of the strain signal at the preset detection position by at least two fiber optic sensors. Among them, the preset installation method can be to install at least two fiber optic sensors at the preset detection position at a certain angle. The fiber optic sensor, that is, the fiber optic strain sensor, can detect small strain changes at the preset detection position of the target ship, and is used to convert the collected optical signal into a strain signal. For example, an example diagram of a fiber optic sensor can be seen in Figure 2 The strain signal collected by the optical fiber sensor can be used as the first strain signal. That is, at least two first strain signals will be collected corresponding to each preset detection position.

[0041] The first strain signal is related to the force information acting on the preset detection position. For example, the first strain signal is related to the wave impact force on the preset detection position, which is only used as an example and does not limit the force information acting on the preset detection position during the navigation of the target ship. The force information acting on the preset detection position can be the information of the force acting on the preset detection position during the navigation of the target ship.

[0042] Specifically, at least one preset detection position of the target ship can be determined according to the ship design drawing of the target ship or the simulated ship model. For at least one preset detection position, at least two fiber optic sensors are deployed at each preset detection position according to a preset installation method, so that the at least two fiber optic sensors collect the first strain signals corresponding to the force information acting on the preset detection position in different directions. That is, during the navigation of the target ship, for at least one preset detection position, the first strain signals collected by the at least two fiber optic sensors deployed at each preset detection position are obtained. It should be noted that the directions of the force information corresponding to the at least two first strain signals corresponding to the preset detection position are different. Based on this, the comprehensiveness of the collected first strain signals is ensured, and the problem of incomplete and non-comprehensive strain signal acquisition caused by the fact that a single fiber optic sensor can only collect the strain signal corresponding to the force from one direction is avoided.

[0043] Optionally, the preset installation method is that at least two fiber optic sensors are welded at the preset detection position according to a preset angle. The method further includes: determining at least one preset detection position on the target ship according to the ship design drawing of the target ship and / or the ship parameters of the target ship; obtaining the material elastic modulus corresponding to the preset detection position to determine the stress data based on the material elastic modulus.

[0044] Among them, the preset angle can be an angle set according to actual needs. Optionally, the preset angle can be 60 degrees. That is, at least two fiber optic sensors are welded at the preset detection position at an angle of 60 degrees. For example, see Figure 3 , Figure 3 is an example diagram of welding three fiber optic sensors at the preset detection position at an angle of 60 degrees. Figure 3 In , three fiber optic sensors are welded at the preset detection position in the form of a strain rosette at an angle of 60 degrees to form a 60-degree planar triaxial strain measurement point to simultaneously measure the strain conditions in multiple directions.

[0045] It should be noted that in order to achieve comprehensive acquisition of the first strain signals corresponding to the force information acting on the preset detection position in each direction, the angular range included in the preset angle of at least two fiber optic sensors can include the angular range corresponding to the direction of the force information.

[0046] The ship design drawing can be the ship drawing during the design and construction process of the target ship. The ship design drawing can include the front view, top view, side view of the target ship, as well as the dimension information, structural information, etc. of the target ship. The ship design drawing can determine the areas on the ship structure of the target ship that are prone to cracks or fractures, and use these areas as preset detection positions. The ship parameters can include the structural parameter information of each component in the ship structure of the target ship. Through the ship parameters, the structural correlation relationship between each component in the target ship can be determined, and the positions with weak structures in the target ship can be used as preset detection positions. Optionally, the target ship can also be modeled based on the ship design drawing and the ship parameters of the target ship, and at least one preset detection position in the target ship can be determined according to the simulation ship model of the target ship.

[0047] The material elastic modulus is a mechanical parameter used to describe the ability of the ship material of the target ship to resist elastic deformation. The material elastic modulus can be understood as the ratio of stress to the corresponding strain within the elastic range of the ship material of the target ship, and is used to characterize the linear relationship between the internal stress and the strain generated in the ship material at the preset detection position when it is subjected to force information. It should be noted that the corresponding material elastic modulus is different for different ship materials. Optionally, the material elastic modulus is a preset value, and the material elastic modulus corresponding to the preset detection position can be determined correspondingly through the ship material at the preset detection position. The stress data can be understood as the force received per unit area by the ship material at the preset detection position, and is a physical quantity used to characterize the internal stress state of the ship material at the preset detection position.

[0048] Specifically, according to the ship design drawing and / or the ship parameters of the target ship, determine the positions on the target ship where the ship structure is relatively weak and stress is concentrated, that is, determine at least one preset detection position. At each preset detection position, at least two fiber optic sensors are welded at the preset detection position according to a preset angle to obtain a first strain signal through the fiber optic sensors at the preset detection position. According to the ship material at each preset detection position, determine the material elastic modulus corresponding to the ship material, so as to convert the strain data corresponding to the first strain signal into stress data through the material elastic modulus. It should be noted that strain is the change in the size or shape of the ship material at the preset detection position relative to its original state when it is subjected to a force. Strain data is a physical quantity used to characterize the degree of deformation of the ship material at the preset detection position.

[0049] Optionally, the relationship between the material elastic modulus, strain data, and stress data can be characterized by the following function.

[0050] σ = E·ε

[0051] Among them, σ represents the stress data, E represents the material elastic modulus, and ε represents the strain data.

[0052] S120. When it is detected that the acquisition duration reaches the preset cycle duration, denoise the first strain signal within the acquisition duration to obtain a second strain signal for analysis.

[0053] Among them, the preset cycle duration can be a preset acquisition duration. The preset cycle duration can include one or more acquisition moments. For example, if the preset cycle duration is 10 seconds and the first strain signal is acquired once every 1 second, then the preset cycle duration corresponds to 10 acquisition moments and 10 first strain signals are acquired. To improve data processing efficiency and reduce the redundant consumption duration of single data processing, when the acquisition duration reaches the preset cycle duration, the first strain signal within the acquisition duration can be uniformly denoised. The denoising process is used to remove invalid or abnormal data in the first strain signal to improve the accuracy of the first strain signal. Optionally, the wavelet transform denoising method can be used to denoise the first strain signal. The second strain signal is the strain signal after the first strain signal is denoised.

[0054] Specifically, when it is detected that the acquisition duration reaches the preset cycle duration, denoise the first strain signal within the acquisition duration to remove invalid or abnormal data in the first strain signal, and obtain a second strain signal for analysis. Based on this, the invalid or abnormal data in the first strain signal can be removed to improve the accuracy of subsequent data processing.

[0055] In the embodiment of the present invention, the wavelet transform denoising method can be used to denoise the first strain signal to obtain a second strain signal. The specific method can be: obtain the target decomposition wave and the decomposition level corresponding to the target decomposition wave; perform frequency domain conversion on the first strain signal to obtain the strain signal to be decomposed; perform wavelet decomposition on the strain signal to be decomposed according to the target decomposition wave and the decomposition level to obtain the wavelet coefficients of the strain signal to be decomposed at each decomposition level; when the wavelet coefficients meet the preset threshold condition, use the first strain signal as the second strain signal.

[0056] Among them, the target decomposition wave can be used to perform wavelet decomposition on the strain signal to obtain components of different frequencies. The components of different frequencies are the wavelet coefficients. Optionally, the target decomposition wave can be Daubechies wavelet, Symlets wavelet, etc. The decomposition level is the number of decomposition times when using the target decomposition wave to decompose the strain signal. The decomposition level affects the detailed degree of the strain signal being decomposed. That is, the more decomposition levels, the more wavelet coefficients are obtained.

[0057] Frequency domain conversion is used to convert the first strain signal from the time domain signal to the frequency domain signal. The strain signal to be decomposed is the frequency domain signal after the frequency domain conversion of the first strain signal. The preset threshold condition can be a standard threshold range that is preset and that the wavelet coefficients need to satisfy. When the wavelet coefficients satisfy the preset threshold condition, the first strain signal can be determined as the second strain signal.

[0058] Specifically, in the process of denoising the first strain signal by using the wavelet transform denoising method, the target decomposition wave and the decomposition level can be obtained first, so as to perform wavelet decomposition processing through the target decomposition wave and the decomposition level. Perform frequency domain conversion on the first strain signal to obtain the strain signal to be decomposed. Perform wavelet decomposition on the strain signal to be decomposed through the target decomposition wave. When decomposing each time, the strain signal to be decomposed is divided into high-frequency part data and low-frequency part data, and the high-frequency part data is used as the wavelet coefficients of the current decomposition level. The low-frequency part data is subjected to wavelet decomposition again by using the target decomposition wave until the wavelet coefficients corresponding to the decomposition level are obtained. That is, the wavelet coefficients of each decomposition level are obtained. For the wavelet coefficients of each decomposition level, determine the wavelet coefficients that satisfy the preset threshold condition, and perform inverse wavelet transform on the wavelet coefficients that satisfy the preset threshold condition to obtain the denoised strain signal, that is, the second strain signal.

[0059] Exemplarily, Figure 4 is an example diagram of denoising the first strain signal by using the wavelet transform denoising method. Figure 4 In, the sensor received signal corresponds to the process of the above-mentioned fiber optic sensor collecting the first strain signal, the noisy signal corresponds to the first strain signal, and the denoised signal corresponds to the second strain signal.

[0060] When collecting the first strain signal through the fiber optic sensor, the collected first strain signal is usually a signal containing noise. The first strain signal can be characterized by the following function.

[0061] s (t) =y (t) +n (t)

[0062] Wherein, s (t) represents the first strain signal collected by the fiber optic sensor at the acquisition time t. y (t) is the true signal at the acquisition time t, and n (t) is the noise signal at the acquisition time t.

[0063] Before performing wavelet decomposition on the noisy signal, that is, the first strain signal, a target decomposition wave of a wavelet basis type can be selected first, and the decomposition level N of the wavelet decomposition can be determined. For the strain signal s (t) corresponding to the strain signal to be decomposed s (t)'Perform N-layer wavelet decomposition to obtain wavelet coefficients at each decomposition level. For example, the specific process of wavelet decomposition can be as follows Figure 5 shown. Figure 5 The decomposition level N = 4. In the first decomposition level, the strain signal s is decomposed. (t) 'Perform wavelet decomposition to obtain the high-frequency data W of the first decomposition level CD1 and low frequency data W CA1 . The high frequency data W CD1 As the wavelet coefficient of the first decomposition level. CA1 As the input of the second decomposition level, that is, the low-frequency data W CA1 Perform wavelet decomposition to obtain the high-frequency data W of the second decomposition level CD2 and low frequency data W CA2 The high-frequency data W of the second decomposition level CD2 As the wavelet coefficients of the second decomposition level, the low-frequency data W of the second decomposition level is CA2 As the input of the third decomposition level, CA2 Perform wavelet decomposition. Repeat the above process to obtain the wavelet coefficients W of four decomposition levels. CD1 , W CD2 , W CD3 , W CD4 and W CA4 Determine the wavelet coefficients that meet the preset threshold conditions, and perform inverse wavelet transform on the wavelet coefficients that meet the preset threshold conditions to obtain Figure 4 The denoised signal is the second strain signal.

[0064] Optionally, when the wavelet coefficient meets a preset threshold condition, using the first strain signal as the second strain signal includes: processing the wavelet coefficient according to a first threshold filter function and a second threshold filter function to obtain a second strain signal after filtering the strain signal to be decomposed.

[0065] The preset threshold condition may be a pre-set standard threshold range that the wavelet coefficient needs to meet. The standard threshold range may include a maximum threshold and a minimum threshold. The first threshold filter function and the second threshold filter function may be used to process the wavelet coefficients that do not meet the preset threshold condition. Optionally, the first threshold filter function may filter the wavelet coefficients that are higher than the maximum threshold. The second threshold filter function may filter the wavelet coefficients that are lower than the minimum threshold.

[0066] Specifically, the wavelet coefficients are processed by the first threshold filter function and the second threshold filter function so that the wavelet coefficients meet the preset threshold condition. The wavelet coefficients meeting the preset threshold condition are subjected to inverse wavelet transformation to obtain the second strain signal.

[0067] S130. Convert all the second strain signals into stress data, and determine the target principal stress at the preset detection position according to the stress data.

[0068] Among them, the stress data can be understood as the force received by the ship material at the preset detection position per unit area, and is a physical quantity used to characterize the internal stress state of the ship material at the preset detection position. The target principal stress can be the maximum principal stress corresponding to the preset detection position.

[0069] Specifically, convert all the second strain signals corresponding to the preset detection position into strain data through a demodulator. Convert the strain data corresponding to the second strain signals into stress data according to the material elastic modulus. Determine the target principal stress at the preset detection position according to the stress data and the corresponding principal stress determination function. It should be noted that the above processing can also determine the principal stress direction of the target principal stress through the corresponding angle determination function.

[0070] S140. Based on the target principal stress and the historical principal stress at each acquisition moment within the acquisition duration, determine the fatigue degree attribute of the detection point at the preset detection position, and determine the ship fatigue attribute of the target ship according to the fatigue degree attribute of the detection point.

[0071] Among them, the historical principal stress can be the target principal stress corresponding to each acquisition moment before the acquisition duration. Optionally, the historical principal stress can be obtained from the corresponding database, and is the maximum principal stress corresponding to each moment corresponding to the acquisition moment before the acquisition duration. The fatigue degree attribute of the detection point can be used to characterize the fatigue strength of the preset detection position. The ship fatigue attribute can be used to characterize the fatigue strength of the target ship. Optionally, the ship fatigue attribute can be obtained by summing the fatigue degree attributes of the detection points corresponding to at least one preset detection position.

[0072] Specifically, based on the target principal stresses at each acquisition moment within the acquisition duration, determine the occurrence times of different target principal stresses. For example, if the acquisition duration is 10 seconds and the acquisition is performed once every second, and the obtained target principal stresses are 20, 20, 40, 40, 40, 30, 30, 20, 20, 50 in sequence. Then it can be obtained that: the occurrence time of the target principal stress 20 is 4, the occurrence time of the target principal stress 30 is 2, the occurrence time of the target principal stress 40 is 3, and the occurrence time of the target principal stress 50 is 1. Correspondingly, obtain the historical principal stresses from the corresponding database and determine the occurrence times of different historical principal stresses. When the target principal stress is consistent with the historical principal stress, regard the target principal stress and the historical principal stress as one kind of principal stress, and sum up the occurrence times of the target principal stress and the occurrence times of the historical principal stress to determine the total number of times of this kind of principal stress. Determine the ratio data of the total number of times of this kind of principal stress to the preset number. According to at least one principal stress corresponding to the preset detection position and the ratio data corresponding to at least one principal stress, perform a summation process on at least one ratio data to obtain the fatigue degree attribute of the detection point. Determine the ship fatigue attribute of the target ship according to the fatigue degree attribute of the detection point at at least one preset detection position in the target ship.

[0073] Optionally, when the ship fatigue attribute reaches the preset attribute threshold, obtain the future environmental data within the target navigation duration range; according to the future environmental data, determine the ship impact data of the target ship within the target navigation duration range.

[0074] Among them, the preset attribute threshold can be understood as the standard value of the ship fatigue attribute set in advance. The target navigation duration range can be understood as the duration range that the target ship can still navigate. The future environmental data can be understood as the surrounding sea condition data corresponding to the target ship when it sails within the target navigation duration range. The ship impact data can be used to characterize the impact on the ship fatigue attribute caused by the force information that impacts or damages the ship structure of the target ship within the target navigation duration range.

[0075] Specifically, when the ship fatigue attribute reaches the preset attribute threshold, obtain the remaining navigable duration range of the entire service life of the target ship, that is, the target navigation duration range. Obtain the future environmental data within the target navigation duration range. Retrieve the historical environmental data according to the future environmental data, and determine how much impact the force information of the target ship corresponding to this environmental data has on the ship fatigue attribute under the same environmental data, that is, determine the ship impact data. Further, according to the ship fatigue attribute of the target ship and the ship impact data corresponding to the future environmental data, the ship service life of the target ship can be determined.

[0076] The technical solution of this embodiment is to deploy at least two fiber optic sensors at at least one preset detection position of the target ship, and the at least two fiber optic sensors are installed according to a preset installation method, ensuring that the fiber optic sensors can accurately and real-time collect multiple strain signals at the preset detection position. For at least one preset detection position, during the navigation of the target ship, the first strain signals collected by the at least two fiber optic sensors deployed at the preset detection position are obtained, where the first strain signals are related to the force information acting on the preset detection position. Based on this, the comprehensiveness of the collected first strain signals is ensured, and the problem of incomplete and non-comprehensive strain signal collection caused by the fact that a single fiber optic sensor can only collect the strain signals corresponding to the force in one direction at the preset detection position is avoided. When it is detected that the acquisition duration reaches the preset cycle duration, the first strain signals within the acquisition duration are denoised to obtain the second strain signals to be used for analysis. Based on this, invalid or abnormal data within the first strain signals can be removed, improving the accuracy of subsequent data processing. All the second strain signals are converted into stress data, and the target principal stress at the preset detection position is determined according to the stress data. According to the target principal stress and the historical principal stress at each acquisition moment within each acquisition duration, the fatigue degree attribute of the detection point at the preset acquisition position is determined, and according to the fatigue degree attribute of the detection point at each preset detection position, the ship fatigue attribute of the target ship is determined, realizing the real-time fatigue attribute detection of at least one preset detection position of the target ship, providing a data basis for the subsequent maintenance and optimization of the ship structure of the target ship, and improving the safety and reliability of the ship structure of the target ship. The present invention solves the problem in the prior art that the detection result has a certain lag due to the detection of ship fatigue degree by simulating the external environment of the ship, resulting in the inability to accurately maintain the ship structure in a timely manner. By installing at least two fiber optic sensors at at least one preset detection position of the target ship according to a preset installation method, the problem of non-comprehensive strain signals collected by a single fiber optic sensor is avoided. By denoising the first strain signals to obtain the second strain signals, and converting the second strain signals into stress data to determine the target principal stress at each preset detection position, and then determining the fatigue degree attribute of the detection point at each preset detection position to obtain the ship fatigue attribute of the target ship, the stress data analysis in multiple directions at each preset detection position of the target ship is realized, the potential fracture risk at the preset detection position can be effectively and quickly determined, the speed of determining the ship fatigue attribute is improved, and thus the safety and reliability of the ship structure of the target ship are improved.

[0077] Embodiment 2

[0078] Figure 6It is a flowchart of a method for detecting the fatigue degree of a ship provided in the second embodiment of the present invention. This embodiment is a refinement of the step of "converting all second strain signals into stress data, and determining the target principal stress and principal stress direction at the preset detection position according to the stress data" on the basis of the above embodiment. The specific implementation manner can refer to the technical solution of this embodiment. Among them, the same or corresponding technical terms as those in the above embodiment will not be elaborated here. As Figure 6 shown, the method includes:

[0079] S210. For at least one preset detection position, during the driving of the target ship, obtain the first strain signals collected by at least two fiber optic sensors deployed at the preset detection position.

[0080] Among them, the first strain signal is related to the force information acting on the preset detection position.

[0081] S220. When it is detected that the acquisition duration reaches the preset cycle duration, perform denoising processing on the first strain signals within the acquisition duration to obtain the second strain signals to be used for analysis.

[0082] S230. For multiple second strain signals at the same acquisition moment, convert the second strain signals into strain values to be used based on the demodulator.

[0083] Among them, for the same acquisition moment, at least two fiber optic sensors at the preset detection position will collect at least two first strain signals. Correspondingly, there are at least two second strain signals corresponding to the same acquisition moment, that is, multiple second strain signals. The demodulator is used to convert the second strain signals into strain data. Strain is the change in the size or shape of the ship material at the preset detection position relative to its original state when it is subjected to a force. Strain data is a physical quantity used to characterize the deformation degree of the ship material at the preset detection position. The strain value to be used is the strain data obtained by converting the second strain signal.

[0084] Specifically, for multiple second strain signals at the same acquisition moment, each second strain signal is converted into a corresponding strain value to be used through the demodulator, so as to determine the target principal stress according to the multiple strain values to be used corresponding to the same acquisition moment.

[0085] S240. Determine the first invariant according to the multiple strain values to be used at the acquisition moment, and determine the tensor shear strain value according to the first invariant and the strain value to be used.

[0086] Among them, the first invariant can be the tensor first invariant obtained according to the multiple strain values to be used and the corresponding invariant determination function. Optionally, the invariant determination function can be expressed as:

[0087]

[0088] Among them, ε1, ε2,... ε N represent multiple strain values to be used, C represents the first invariant, and N represents the number of strain values to be used. Since the strain values to be used are determined according to the second strain signals corresponding to at least two fiber optic sensors at different angles, therefore, the multiple strain values to be used ε1, ε2,... ε N correspond to different force directions. For example, if the preset angle is 60 degrees, at least two fiber optic sensors are 3 fiber optic sensors, and the 3 fiber optic sensors are welded at the preset detection position according to the Figure 3 shown direction. Then, the invariant determination function can be expressed as:

[0089]

[0090] Among them, ε0 represents the strain value to be used corresponding to the fiber optic sensor on the 0° axis, ε 60 represents the strain value to be used corresponding to the fiber optic sensor on the 60° axis, ε 120 represents the strain value to be used corresponding to the fiber optic sensor on the 120° axis, and C represents the first invariant. The tensor shear strain value can be understood as the shear strain component value of the strain matrix caused by shear deformation, and is used to describe the characteristics of the local deformation of the ship material at the preset detection position.

[0091] Specifically, according to the multiple strain values to be used corresponding to the acquisition moment and the above invariant determination function, the first invariant is obtained. According to the first invariant, the multiple strain values to be used corresponding to the acquisition moment, and the tensor shear strain value determination function, the corresponding tensor shear strain value is obtained. For example, if the preset angle is 60 degrees, at least two fiber optic sensors are 3 fiber optic sensors, and the 3 fiber optic sensors are welded at the preset detection position according to the Figure 3 shown direction. Then, the tensor shear strain value determination function can be expressed as:

[0092]

[0093] Among them, ε0 represents the strain value to be used corresponding to the fiber optic sensor on the 0° axis, ε 60 represents the strain value to be used corresponding to the fiber optic sensor on the 60° axis, ε 120 represents the strain value to be used corresponding to the fiber optic sensor on the 120° axis, C represents the first invariant, and R represents the tensor shear strain value.

[0094] S250. Determine the target principal stress at the preset detection position according to the tensor shear strain value, the first invariant, and the material information of the preset detection position.

[0095] Specifically, the tensor shear strain value and the first invariant are summed to obtain the maximum principal strain value. Since the ship materials at the preset detection positions are different, their corresponding material elastic moduli are different. The material information at the preset detection position can be obtained first, and the material elastic modulus corresponding to the material information can be determined according to the material information at the preset detection position. The material elastic modulus and the maximum principal strain value are multiplied to determine the maximum principal stress at the preset detection position, that is, the target principal stress.

[0096] In the embodiment of the present invention, the method for determining the target principal stress at the preset detection position according to the tensor shear strain value, the first invariant, and the material information at the preset detection position may be: determining the maximum principal strain value according to the tensor shear strain value and the first invariant; determining the target principal stress according to the maximum principal strain value and the material elastic modulus corresponding to the material information at the preset detection position.

[0097] Specifically, the tensor shear strain value and the first invariant are summed to obtain the maximum principal strain value. That is, the maximum principal strain value can be determined by the following function.

[0098] e1 = C + R

[0099] Where C represents the first invariant, R represents the tensor shear strain value, and e1 represents the maximum principal strain value. The maximum principal strain value and the material elastic modulus corresponding to the material information at the preset detection position are multiplied to obtain the maximum principal stress, that is, the target principal stress. The target principal stress can be determined by the following function.

[0100] σ = E·e1

[0101] Where σ represents the target principal stress, E represents the material elastic modulus, and e1 represents the maximum principal strain value.

[0102] Optionally, based on the target angle determination function, the tensor shear strain value, the first invariant, and the stress value to be used are used to determine the principal stress direction.

[0103] Where the target angle determination function can be used to determine the included angle between the principal stress direction and the preset horizontal direction, that is, the principal stress direction of the target principal stress can be obtained through the target angle determination function. The principal stress direction can be understood as the direction corresponding to the target principal stress.

[0104] Specifically, the tensor shear strain value, the first invariant, and the stress value to be used are substituted into the target angle determination function to determine the tangent value of the double angle corresponding to the included angle between the principal stress direction and the preset horizontal direction. According to the tangent value of the double angle of this included angle, the included angle between the principal stress direction and the preset horizontal direction is determined, that is, the principal stress direction is obtained.

[0105] Optionally, if the preset included angle is 60 degrees, at least two fiber optic sensors are three fiber optic sensors, and the three fiber optic sensors are welded at the preset detection position in the direction shown by Figure 3 . Then, the target angle determination function can be expressed as the following formula:

[0106]

[0107] where ε0 represents the strain value to be used corresponding to the fiber optic sensor on the 0° axis, ε 60 represents the strain value to be used corresponding to the fiber optic sensor on the 60° axis, ε 120 represents the strain value to be used corresponding to the fiber optic sensor on the 120° axis, C represents the first invariant, and θ1 represents the included angle between the principal component direction and the preset horizontal direction corresponding to the fiber optic sensor on the 0° axis.

[0108] S260. Determine at least one principal stress and the corresponding actual number of times according to the target principal stress and the historical principal stress.

[0109] Among them, when the target principal stress is consistent with the historical principal stress, the target principal stress and the historical principal stress are used as one kind of principal stress. Accordingly, at least one kind of principal stress, that is, at least one principal stress, can be obtained according to the target principal stress and the historical principal stress. Each principal stress has its corresponding number of occurrences, that is, the actual number of times.

[0110] Specifically, according to the target principal stress at each acquisition moment during the acquisition duration, determine the number of occurrences of different target principal stresses. Obtain the historical principal stress corresponding to each acquisition moment before the acquisition duration from the corresponding database, and determine the number of occurrences of different historical principal stresses. When the target principal stress is consistent with the historical principal stress, the target principal stress and the historical principal stress are used as one kind of principal stress, and the number of occurrences of the target principal stress and the number of occurrences of the historical principal stress are added to determine the actual number of times of this kind of principal stress. Based on this, at least one principal stress and the corresponding actual number of times are obtained.

[0111] Exemplarily, a stress time series diagram can be drawn according to the target principal stress and the historical principal stress. Among them, the stress time series diagram contains the target principal stress or the historical principal stress corresponding to each moment. For example, the stress time series diagram can be as shown in Figure 7 . Use the rain flow counting method to analyze the stress time series diagram, that is, divide the principal stress corresponding to the time series by the rain flow counting method to obtain independent and recognizable closed principal stress cycles. After identifying all the principal stress cycles, classify these principal stress cycles to determine the actual number of times of at least one kind of principal stress.

[0112] S270. Determine the fatigue degree attribute of the detection points at the preset detection positions according to the actual number of times and the preset number of times corresponding to at least one principal stress, and determine the ship fatigue attribute of the target ship based on the fatigue degree attribute of the detection points.

[0113] Among them, the preset number of times can be pre-set, which is the number of times that the preset detection position of the target ship can withstand under the action of the principal stress. There is a preset number of times corresponding to each principal stress.

[0114] Specifically, for at least one principal stress, determine the ratio data between the actual number of times and the preset number of times of each principal stress. Perform a summation process on the ratio data corresponding to at least one principal stress to determine the fatigue degree attribute of the detection points at the preset detection positions. Determine the ship fatigue attribute of the target ship according to the fatigue degree attributes of the detection points corresponding to at least one preset detection position.

[0115] Optionally, the S-N curve can be used to determine the fatigue degree attribute of the detection points at the preset detection positions. The S-N curve is a tool for fatigue analysis, which is used to characterize the preset number of times that the ship material at the preset detection position can withstand under different principal stress amplitudes. This curve is usually used to evaluate the durability of the ship material at the preset detection position under cyclic loading, especially to predict when the material will experience fatigue failure when the load is repeatedly applied. See Figure 8 , Figure 8 for the schematic diagram of the S-N curve. In Figure 8 , the abscissa of the S-N curve represents the preset number of times that can be withstood, and the ordinate represents the principal stress. The preset number of times corresponding to each principal stress can be determined through the S-N curve. According to the actual number of times and the preset number of times of each principal stress, determine the ratio data between the actual number of times and the preset number of times of each principal stress. Perform a summation process on the ratio data corresponding to at least one principal stress to determine the fatigue degree attribute of the detection points at the preset detection positions. Among them, the fatigue degree attribute of the detection points can be determined by the following function.

[0116]

[0117] Among them, n i represents the actual number of times of the i-th principal stress, N i represents the preset number of times of the i-th principal stress, and m represents the number of at least one principal stress. Fatigue represents the fatigue degree attribute of the detection points at the preset detection positions. It should be noted that when the fatigue degree attribute fatigue = 1, it means that the fatigue strength of the preset detection position reaches the limit, and fracture or crack will occur.

[0118] The technical solution of this embodiment ensures that multiple strain signals at the preset detection positions can be accurately collected in real time by deploying at least two fiber optic sensors at at least one preset detection position of the target ship, and installing the at least two fiber optic sensors according to the preset installation method. For at least one preset detection position, during the navigation of the target ship, the first strain signals collected by the at least two fiber optic sensors deployed at the preset detection position are obtained. Based on this, the comprehensiveness of the collected first strain signals is ensured, and the problem of incomplete and non-comprehensive strain signal collection caused by the fact that a single fiber optic sensor can only collect the strain signals corresponding to the acting forces in one direction at the preset detection position is avoided. When it is detected that the acquisition duration reaches the preset cycle duration, the first strain signals within the acquisition duration are denoised to obtain the second strain signals for analysis. Based on this, invalid or abnormal data in the first strain signals can be removed, improving the accuracy of subsequent data processing. For multiple second strain signals at the same acquisition moment, the second strain signals are converted into strain values to be used based on a demodulator. According to the strain values to be used at the acquisition moment, a first invariant is determined, and based on the first invariant and the strain values to be used, a tensor shear strain value is determined. According to the tensor shear strain value, the first invariant, and the material information of the preset detection position, the target principal stress of the preset detection position is determined. Based on the target principal stress and the historical principal stress, at least one principal stress and the corresponding actual number of times are determined, so as to determine the fatigue degree attribute of the detection point at the preset detection position through the actual number of times corresponding to the at least one principal stress and the preset number of times, and determine the ship fatigue attribute of the target ship based on the fatigue degree attribute of the detection point, realizing the real-time fatigue attribute detection of at least one preset detection position of the target ship, providing a data basis for the subsequent maintenance and optimization of the ship structure of the target ship, and improving the safety and reliability of the ship structure of the target ship. The present invention solves the problem in the prior art that the detection result has a certain lag due to the detection of ship fatigue degree by simulating the external environment of the ship, resulting in the inability to accurately maintain the ship structure in a timely manner. By installing at least two fiber optic sensors at at least one preset detection position of the target ship according to the preset installation method, the problem of incomplete strain signals collected by a single fiber optic sensor is avoided, the stress data analysis in multiple directions at each preset detection position of the target ship is realized, the potential fracture risk at the preset detection position can be quickly and effectively determined, the speed of determining the ship fatigue attribute is increased, and thus the safety and reliability of the ship structure of the target ship are improved.

[0119] Embodiment III

[0120] Figure 9 is a schematic structural diagram of a device for detecting ship fatigue degree provided in Embodiment III of the present invention. As Figure 9As shown in the figure, at least two optical fiber sensors are deployed at at least one preset detection position of the target ship, and the at least two optical fiber sensors are installed according to a preset installation method. The device includes: a first strain signal acquisition module 310, a second strain signal determination module 320, a principal stress determination module 330, and a ship fatigue property determination module 340.

[0121] The first strain signal acquisition module 310 is configured to acquire, for at least one preset detection position, first strain signals collected by at least two optical fiber sensors deployed at the preset detection position during the navigation of the target ship; wherein, the first strain signal is related to the acting force information acting on the preset detection position; the second strain signal determination module 320 is configured to, when it is detected that the acquisition duration reaches a preset cycle duration, perform denoising processing on the first strain signals within the acquisition duration to obtain second strain signals to be used for analysis; the principal stress determination module 330 is configured to convert all the second strain signals into stress data, and determine the target principal stress of the preset detection position according to the stress data; the ship fatigue property determination module 340 is configured to determine the fatigue degree property of the detection point at the preset detection position based on the target principal stress and the historical principal stress at each acquisition moment within the acquisition duration, and determine the ship fatigue property of the target ship according to the fatigue degree property of the detection point.

[0122] In the technical solution of this embodiment, by deploying at least two fiber optic sensors at at least one preset detection position of the target ship, and installing the at least two fiber optic sensors according to a preset installation method, it is ensured that the fiber optic sensors can accurately and real-time collect a plurality of strain signals at the preset detection position. For at least one preset detection position, during the navigation of the target ship, the first strain signals collected by the at least two fiber optic sensors deployed at the preset detection position are obtained, where the first strain signals are related to the force information acting on the preset detection position. Based on this, the comprehensiveness of the collected first strain signals is ensured, and the problem of incomplete and non-comprehensive strain signal collection caused by only being able to collect the strain signals corresponding to the force in one direction at the preset detection position by a single fiber optic sensor is avoided. When it is detected that the acquisition duration reaches the preset cycle duration, the first strain signals within the acquisition duration are denoised to obtain the second strain signals to be used for analysis. Based on this, invalid or abnormal data in the first strain signals can be eliminated, improving the accuracy of subsequent data processing. All the second strain signals are converted into stress data, and the target principal stress at the preset detection position is determined according to the stress data. According to the target principal stress and the historical principal stress at each acquisition moment within each acquisition duration, the fatigue degree attribute of the detection point at the preset acquisition position is determined, and according to the fatigue degree attribute of the detection point at each preset detection position, the ship fatigue attribute of the target ship is determined, realizing the real-time fatigue attribute detection of at least one preset detection position of the target ship, providing a data basis for the subsequent maintenance and optimization of the ship structure of the target ship, and improving the safety and reliability of the ship structure of the target ship. The present invention solves the problem in the prior art that the detection result has a certain lag due to simulating the external environment of the ship for ship fatigue detection, resulting in the inability to accurately maintain the ship structure in a timely manner. By installing at least two fiber optic sensors at at least one preset detection position of the target ship according to a preset installation method, the problem of non-comprehensive strain signals collected by a single fiber optic sensor is avoided. By denoising the first strain signals to obtain the second strain signals, and converting the second strain signals into stress data to determine the target principal stress at each preset detection position, and then determining the fatigue degree attribute of the detection point at each preset detection position to obtain the ship fatigue attribute of the target ship, the stress data analysis in multiple directions at each preset detection position of the target ship is realized, the potential fracture risk at the preset detection position can be effectively and quickly determined, the speed of determining the ship fatigue attribute is improved, and thus the safety and reliability of the ship structure of the target ship are improved.

[0123] Based on the above embodiments, optionally, the preset installation method is that at least two fiber optic sensors are welded at the preset detection positions according to a preset angle. The device further includes: a material elastic modulus acquisition module, configured to determine at least one preset detection position on the target ship according to the ship design drawing of the target ship and / or the ship parameters of the target ship; acquire the material elastic modulus corresponding to the preset detection position, so as to determine the stress data based on the material elastic modulus.

[0124] Optionally, the second strain signal determination module includes: a decomposition level determination unit, configured to acquire the target decomposition wave and the decomposition level corresponding to the target decomposition wave; a frequency domain conversion unit, configured to perform frequency domain conversion on the first strain signal to obtain a strain signal to be decomposed; a wavelet coefficient determination unit, configured to perform wavelet decomposition on the strain signal to be decomposed according to the target decomposition wave and the decomposition level to obtain the wavelet coefficients of the strain signal to be decomposed at each decomposition level; a second strain signal determination unit, configured to use the first strain signal as the second strain signal when the wavelet coefficients meet the preset threshold condition.

[0125] Optionally, the second strain signal determination unit is configured to process the wavelet coefficients according to a first threshold filtering function and a second threshold filtering function to obtain a second strain signal obtained by filtering the strain signal to be decomposed.

[0126] Optionally, the principal stress determination module includes: a strain value determination unit, configured to convert the second strain signal into a strain value to be used based on a demodulator for multiple second strain signals at the same acquisition moment; a tensor shear strain value determination unit, configured to determine a first invariant according to multiple strain values to be used at the acquisition moment, and determine a tensor shear strain value according to the first invariant and the strain value to be used; a target principal stress determination unit, configured to determine the target principal stress at the preset detection position according to the tensor shear strain value, the first invariant, and the material information of the preset detection position.

[0127] Optionally, the target principal stress determination unit is configured to determine the maximum principal strain value according to the tensor shear strain value and the first invariant; determine the target principal stress according to the maximum principal strain value and the material elastic modulus corresponding to the material information of the preset detection position.

[0128] Optionally, the ship fatigue attribute determination module includes: a detection point fatigue degree attribute determination unit, configured to determine at least one principal stress and the corresponding actual number of times according to the target principal stress and the historical principal stress; determine the detection point fatigue degree attribute at the preset detection position according to the actual number of times corresponding to at least one principal stress and the preset number of times.

[0129] Optionally, the device further includes: a ship impact data determination module, configured to obtain future environmental data within a target navigation duration when the ship fatigue attribute reaches a preset attribute threshold; and determine ship impact data of the target ship within the target navigation duration according to the future environmental data.

[0130] The device for detecting ship fatigue provided by the embodiments of the present invention can execute the method for detecting ship fatigue provided by any embodiment of the present invention, and has corresponding functional modules and beneficial effects for executing the method.

[0131] Embodiment 4

[0132] Figure 10 FIG. 10 is a schematic structural diagram of an electronic device provided by Embodiment 4 of the present invention. The electronic device 10 is intended to represent various forms of digital computers, such as, a laptop computer, a desktop computer, a workbench, a personal digital assistant, a server, a blade server, a mainframe computer, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as, a personal digital processor, a cellular phone, a smart phone, a wearable device (such as a helmet, glasses, a watch, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or claimed herein.

[0133] As Figure 10 shown, the electronic device 10 includes at least one processor 11, and a memory communicatively connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc. The memory stores a computer program executable by the at least one processor. The processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 into the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. The input / output (I / O) interface 15 is also connected to the bus 14.

[0134] A plurality of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a magnetic disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0135] The processor 11 may be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as the method for detecting ship fatigue.

[0136] In some embodiments, the method for detecting ship fatigue may be implemented as a computer program tangibly embodied in a computer-readable storage medium, such as the storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed onto the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the method for detecting ship fatigue described above may be executed. Alternatively, in other embodiments, the processor 11 may be configured to execute the method for detecting ship fatigue by any other suitable means (e.g., by means of firmware).

[0137] Various embodiments of the systems and techniques described above in this document may be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGA), application-specific integrated circuits (ASIC), application-specific standard products (ASSP), system-on-a-chip systems (SOC), complex programmable logic devices (CPLD), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include: implemented in one or more computer programs that may be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a special-purpose or general-purpose programmable processor that receives data and instructions from a storage system, at least one input device, and at least one output device, and transmits the data and instructions to the storage system, the at least one input device, and the at least one output device.

[0138] The computer program for implementing the method for detecting ship fatigue of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to the processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when the computer program is executed by the processor, the functions / operations specified in the flowchart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, as a stand-alone software package partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0139] Example 5

[0140] Example 5 of the present invention further provides a computer-readable storage medium storing computer instructions for causing a processor to execute a method for detecting the fatigue degree of a ship. At least two optical fiber sensors are deployed at at least one preset detection position of the target ship, and the at least two optical fiber sensors are installed according to a preset installation method. The method includes:

[0141] For at least one preset detection position, during the driving of the target ship, obtain the first strain signals collected by the at least two optical fiber sensors deployed at the preset detection position; wherein, the first strain signals are related to the force information acting on the preset detection position; when it is detected that the acquisition duration reaches a preset cycle duration, perform denoising processing on the first strain signals within the acquisition duration to obtain second strain signals for analysis and use; convert all the second strain signals into stress data, and determine the target principal stress of the preset detection position according to the stress data; based on the target principal stress and the historical principal stress at each acquisition moment within the acquisition duration, determine the fatigue degree attribute of the detection point at the preset detection position, and determine the ship fatigue attribute of the target ship according to the fatigue degree attribute of the detection point.

[0142] In the context of the present invention, a computer-readable storage medium may be a tangible medium that can contain or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0143] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or a trackball) through which the user can provide input to the electronic device. Other kinds of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0144] The systems and techniques described herein can be implemented in a computing system including backend components (e.g., as a data server), or a computing system including middleware components (e.g., an application server), or a computing system including frontend components (e.g., a user computer having a graphical user interface or a web browser through which the user can interact with an implementation of the systems and techniques described herein), or a computing system including any combination of such backend components, middleware components, or frontend components. The components of the system can be interconnected to each other by digital data communication in any form or medium (e.g., a communication network). Examples of communication networks include: local area network (LAN), wide area network (WAN), blockchain network, and the Internet.

[0145] The computing system can include a client and a server. The client and the server are generally far from each other and usually interact through a communication network. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or a cloud host, which is a host product in the cloud computing service system and solves the defects of difficult management and weak business scalability existing in traditional physical hosts and VPS services.

[0146] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps recited in the present invention can be executed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution of the present invention can be achieved, and no limitation is imposed herein.

[0147] The above specific embodiments do not constitute a limitation on the protection scope of the present invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for detecting ship fatigue, characterized in that: At least two optical fiber sensors are deployed at at least one preset detection position of the target ship, and the at least two optical fiber sensors are installed according to a preset installation method. The method includes: For the at least one preset detection position, during the travel of the target ship, a first strain signal collected by at least two optical fiber sensors deployed at the preset detection position is obtained; wherein the first strain signal is related to force information acting on the preset detection position; When it is detected that the acquisition time reaches the preset cycle time, the first strain signal within the acquisition time is denoised to obtain a second strain signal to be analyzed and used; converting all the second strain signals into stress data, and determining the target principal stress at the preset detection position according to the stress data; Based on the target principal stress and the historical principal stress at each acquisition moment within the acquisition duration, the fatigue attribute of the detection point of the preset detection position is determined, and the ship fatigue attribute of the target ship is determined according to the fatigue attribute of the detection point.

2. The method according to claim 1, characterized in that: The preset installation method is that the at least two optical fiber sensors are welded at the preset detection position according to a preset angle, and the method further includes: Determining at least one preset detection position on the target ship according to a ship design drawing of the target ship and / or ship parameters of the target ship; The elastic modulus of the material corresponding to the preset detection position is obtained to determine the stress data based on the elastic modulus of the material.

3. The method according to claim 1, characterized in that The denoising process of the first strain signal within the acquisition time to obtain the second strain signal to be analyzed and used includes: Acquire a target decomposition wave and a decomposition level corresponding to the target decomposition wave; Obtaining a strain signal to be decomposed by performing frequency domain conversion on the first strain signal; Performing wavelet decomposition on the strain signal to be decomposed according to the target decomposition wave and the decomposition level to obtain the wavelet coefficients of the strain signal to be decomposed at each decomposition level; When the wavelet coefficient meets a preset threshold condition, the first strain signal is used as the second strain signal.

4. The method according to claim 3, characterized in that: When the wavelet coefficient meets a preset threshold condition, using the first strain signal as the second strain signal includes: The wavelet coefficients are processed according to the first threshold filter function and the second threshold filter function to obtain a second strain signal after filtering the strain signal to be decomposed.

5. The method according to claim 1, characterized in that The converting all the second strain signals into stress data, and determining the target principal stress of the preset detection position according to the stress data, comprises: For a plurality of second strain signals at the same acquisition moment, converting the second strain signals into strain values ​​to be used based on a demodulator; Determine a first invariant according to a plurality of strain values ​​to be used at the acquisition time, and determine a tensor shear strain value according to the first invariant and the strain value to be used; The target principal stress of the preset detection position is determined according to the tensor shear strain value, the first invariant and the material information of the preset detection position.

6. The method according to claim 5, characterized in that The determining the target principal stress of the preset detection position according to the tensor shear strain value, the first invariant and the material information of the preset detection position includes: determining a maximum principal strain value according to the tensor shear strain value and the first invariant; The target principal stress is determined according to the maximum principal strain value and the material elastic modulus corresponding to the material information of the preset detection position.

7. The method according to claim 1, characterized in that The determining of the fatigue attribute of the detection point at the preset detection position based on the target principal stress and the historical principal stress at each acquisition moment within the acquisition duration includes: Determine at least one principal stress and a corresponding actual number according to the target principal stress and the historical principal stress; The fatigue attribute of the detection point of the preset detection position is determined according to the actual number and the preset number corresponding to the at least one principal stress.

8. The method according to claim 1, characterized in that The method further comprises: When the fatigue attribute of the ship reaches a preset attribute threshold, obtaining future environmental data within a target sailing time range; The ship impact data of the target ship within the target sailing time range is determined according to the future environmental data.

9. A device for detecting fatigue of a ship, characterized in that: At least two optical fiber sensors are deployed at at least one preset detection position of the target ship, and the at least two optical fiber sensors are installed according to a preset installation method, and the device includes: A first strain signal acquisition module is used to acquire, for the at least one preset detection position, a first strain signal collected by at least two optical fiber sensors deployed at the preset detection position during the travel of the target ship; wherein the first strain signal is related to force information acting on the preset detection position; A second strain signal determination module is used to perform denoising on the first strain signal within the acquisition time period to obtain a second strain signal to be analyzed and used when it is detected that the acquisition time period reaches a preset cycle time period; a principal stress determination module, used for converting all the second strain signals into stress data, and determining the target principal stress of the preset detection position according to the stress data; The ship fatigue attribute determination module is used to determine the fatigue attribute of the detection point of the preset detection position based on the target principal stress and the historical principal stress at each acquisition moment within the acquisition time, and determine the ship fatigue attribute of the target ship according to the fatigue attribute of the detection point.

10. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the method for detecting ship fatigue according to any one of claims 1 to 8.

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