Drag chain cable life prediction method, apparatus, and system

Abstract

This invention relates to a method, device, and system for predicting the lifespan of drag chain cables. The method includes: obtaining the warranty life of the cable and the application parameter range corresponding to the warranty life; obtaining target operating condition parameter values; if all target operating condition parameter values ​​are within the application parameter range, then obtaining the warranty life as the target predicted lifespan of the cable; if one or more of the target operating condition parameter values ​​exceed the application parameter range, then obtaining one or more predicted lifespans corresponding to the target operating condition parameter values ​​according to a drag chain cable reciprocating motion life prediction model based on operating condition parameters, and obtaining the minimum value of the predicted lifespan as the target predicted lifespan of the cable. This invention solves the problem of difficulty in quickly and accurately assessing the reciprocating motion lifespan of drag chain cables under actual operating conditions, providing scientific and reliable technical support for the maintenance of drag chain cable products.

Description

Technical Field

[0001] This invention relates to a method, device, and system for predicting the lifespan of drag chain cables, belonging to the field of cable lifespan prediction technology. Background Technology

[0002] High-cycle fatigue refers to the fatigue failure phenomenon that occurs in materials under long-term cyclic stress. Its typical characteristics include a relatively low stress level but an extremely high number of cycles, usually requiring tens of thousands of cycles to trigger material failure. Compared to low-cycle fatigue, the stress amplitude in high-cycle fatigue is generally lower than the material's yield strength. Therefore, during cyclic loading, the material mainly exhibits elastic deformation with no significant plastic deformation. This type of fatigue failure is characterized by its sudden onset and high degree of concealment, making it difficult to provide early warning through conventional detection methods in engineering practice, thus posing a potential threat to the safe operation of various engineering structures.

[0003] In the field of industrial automation, drag chain cables are subjected to continuous high-frequency reciprocating motion during operation, and their internal structure constantly experiences complex stress cycles. This makes high-cycle fatigue a key factor affecting the service life of drag chain cables. Given the potentially serious consequences of high-cycle fatigue failure, the industry places great importance on the fatigue life performance of drag chain cables under actual operating conditions. Currently, the industry typically uses dedicated experimental platforms that simulate actual operating conditions to conduct high-cycle fatigue tests on cables, reproducing the mechanical loads experienced by the cable in a real working environment to assess its lifespan. While this method can realistically reflect the fatigue characteristics of the cable and provide a basis for product design and quality control, it has the following significant drawbacks:

[0004] 1. Long testing cycles and high testing costs: Taking fatigue life testing of drag chain cables as an example, even with the most advanced testing equipment and continuous 24 / 7 operation, a single testing device can only complete approximately 10,000 reciprocating motion tests per day at most. However, industrial-grade drag chain cables often require a service life of over one million cycles, thus obtaining a single set of data requires continuous testing for hundreds of days. This lengthy testing cycle also leads to high testing costs, severely limiting the assessment of the actual service life of cables under different operating conditions.

[0005] 2. The test results are abstract and difficult to apply in practice: At present, fatigue life test results are mostly presented in the form of charts of stress amplitude and number of cycles, which makes it difficult to intuitively reflect the actual durability of the cable under different working conditions and to accurately assess the service life and maintenance cost of the product in the real use environment. Summary of the Invention

[0006] To address the shortcomings of existing technologies, this invention provides a method, device, and system for predicting the lifespan of drag chain cables. It proposes a drag chain cable reciprocating motion lifespan prediction model based on operating parameters. By combining a large amount of experimental data and calibrating the key parameters in the model through a parameter fitting algorithm, it achieves rapid prediction of the reciprocating motion lifespan of drag chain cables under arbitrary operating parameters. This provides reliable technical support for the maintenance of drag chain cable products and significantly reduces testing cycles and costs.

[0007] According to a first aspect of the present invention, a method for predicting the lifespan of a drag chain cable is provided, the method comprising:

[0008] Obtain the warranty life of the cable and the range of application parameters corresponding to the warranty life, wherein the application parameters include at least one of stroke, speed, acceleration, and bending radius;

[0009] Obtain target operating condition parameter values, wherein the target operating condition parameter values ​​include at least one of stroke value, speed value, acceleration value, and bending radius value;

[0010] If the target operating condition parameter values ​​are all within the range of the application parameters, then the warranty life is obtained as the target predicted life of the cable.

[0011] If one or more of the target operating condition parameter values ​​exceed the range of the application parameters, then according to the drag chain cable reciprocating motion life prediction model based on the operating condition parameters, one or more predicted lives corresponding to the target operating condition parameter values ​​are obtained, and the minimum value of the predicted life is obtained as the target predicted life of the cable. The life prediction model is as follows:

[0012]

[0013] in, For the predicted lifetime, N G For the aforementioned warranty life, It is the first constant. ξ is the second constant; x For operating condition parameter index factor, The target operating condition parameter value, The target operating condition parameter type is indicated, and the type includes at least one of stroke, speed, acceleration, and bending radius.

[0014] According to one embodiment, obtaining the warranty life of the cable includes:

[0015] Based on the cable's structure and material parameters, a finite element model of the cable is established;

[0016] Finite element simulation was performed to obtain the maximum von Mises stress and the maximum axial strain.

[0017] The internal stress correction factor is obtained, and the formula for calculating the internal stress correction factor is as follows: ,in, The maximum von Mises stress, For elastic modulus, The maximum axial strain;

[0018] Obtain the basic durability limit stress of a single core wire of the cable. and the durability limit life corresponding to the basic durability limit stress. The modified ultimate durability stress of the cable is obtained according to the following model. :

[0019] in, This is the surface smoothness correction factor. This is the size correction factor. ,in, The diameter of the cable;

[0020] Obtain any stress intensity and the fatigue life of the cable corresponding to the stress intensity. ;

[0021] Obtain the fitting parameters b and c of the SN lifetime curve equation. The formulas for calculating the fitting parameters b and c are as follows:

[0022] ;

[0023] Based on the application parameter range, the stress amplitude is obtained. Then, based on the SN life curve equation, the fatigue life of the cable corresponding to the stress amplitude is obtained as the warranty life. The SN life curve equation is:

[0024]

[0025] in, The stress amplitude, The fatigue life of the cable corresponding to the stress amplitude.

[0026] According to one embodiment, the drag chain cable reciprocating motion life prediction model based on operating condition parameters includes: a drag chain cable reciprocating motion life prediction model based on stroke, a drag chain cable reciprocating motion life prediction model based on speed, a drag chain cable reciprocating motion life prediction model based on acceleration, and a drag chain cable reciprocating motion life prediction model based on bending radius.

[0027] According to one embodiment, the stroke-based drag chain cable reciprocating motion life prediction model is as follows: , ,in, For the aforementioned warranty life, The stroke value is the parameter value for the target operating condition. As a travel index factor, This is the maximum travel distance within the range of application parameters.

[0028] According to one embodiment, the speed-based drag chain cable reciprocating motion life prediction model is as follows: , ,in, For the aforementioned warranty life, The speed value is one of the target operating condition parameter values. As the speed exponential factor, This refers to the maximum speed within the range of application parameters.

[0029] According to one embodiment, the acceleration-based drag chain cable reciprocating motion life prediction model is as follows: , In the formula, N G For the aforementioned warranty life, The acceleration value is one of the target operating condition parameter values. For acceleration exponential factor, This refers to the maximum acceleration within the range of application parameters.

[0030] According to one embodiment, the drag chain cable reciprocating motion life prediction model based on bending radius is as follows: , In the formula, N G For the aforementioned warranty life, The bending radius value is one of the target working condition parameter values. The bending radius exponential factor, The minimum bending radius within the range of application parameters.

[0031] According to a second aspect of the present invention, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the method as described in any one of the first aspects.

[0032] According to a third aspect of the present invention, an electronic device is provided, comprising a memory and a processor, the memory being configured to store computer instructions, and the processor being configured to invoke the computer instructions from the memory to perform the method as described in any one of the first aspects.

[0033] According to a fourth aspect of the present invention, a drag chain cable life prediction system is provided, the system comprising:

[0034] The visualization module includes an input module and an output module. The input module is used to obtain the cable specifications and target operating condition parameter values ​​through a graphical user interface. The target operating condition parameter values ​​include at least one of the following: stroke value, speed value, acceleration value, and bending radius value. The output module is used to display the target predicted lifespan.

[0035] The database module is used to obtain the warranty life of the cable and the application parameter range corresponding to the warranty life according to the cable's specifications and model. The application parameters include at least one of stroke, speed, acceleration, and bending radius.

[0036] The calculation module is used to, if all the target operating condition parameter values ​​are within the application parameter range, obtain the warranty life as the target predicted life output of the cable; if one or more of the target operating condition parameter values ​​exceed the application parameter range, obtain one or more predicted lives corresponding to the target operating condition parameter values ​​according to the drag chain cable reciprocating motion life prediction model based on the operating condition parameters, and obtain the minimum value of the predicted life as the target predicted life output of the cable. The life prediction model is as follows:

[0037]

[0038] in, For the predicted lifetime, N G For the aforementioned warranty life, It is the first constant. ξ is the second constant; x For operating condition parameter index factor, The target operating condition parameter value, The target operating condition parameter type is indicated, and the type includes at least one of stroke, speed, acceleration, and bending radius.

[0039] Based on classical fatigue damage theory, this invention proposes a prediction model for the reciprocating life of drag chain cables based on operating parameters. By combining a large amount of experimental data and calibrating key parameters in the model through parameter fitting algorithms, the prediction results are highly consistent with the actual experimental data. This enables rapid and accurate prediction of the reciprocating life of drag chain cables under arbitrary operating parameters, providing scientific and reliable technical support for the formulation of maintenance strategies and the optimization of replacement cycles for drag chain cable products, while significantly saving testing time and costs.

[0040] Based on the SN life curve model, this invention combines finite element simulation data and a small amount of experimental data on cable SN life curves to achieve rapid prediction of the fatigue life of cables under different stress amplitudes. This can significantly reduce the number of experiments, save testing costs, and effectively avoid the inherent random errors of single experimental data, thus significantly improving the reliability of the results.

[0041] This invention presents the complex lifespan prediction process through an intuitive visual interface, allowing users to easily understand the predicted lifespan of a specified cable under specific operating conditions. This invention integrates theoretical calculations, engineering practice, and information technology, significantly improving the efficiency of cable product lifespan assessment and providing users with a scientifically reliable basis for decision-making, thus possessing high engineering application value. Attached Figure Description

[0042] Figure 1 This is a flowchart illustrating a method for predicting the lifespan of a drag chain cable, as provided in an embodiment of the present invention.

[0043] Figure 2 This is a schematic diagram of the process for obtaining the warranty life in a drag chain cable life prediction method provided in an embodiment of the present invention.

[0044] Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention.

[0045] Figure 4 This is a schematic diagram of a drag chain cable life prediction system provided in an embodiment of the present invention. Detailed Implementation

[0046] To enable those skilled in the art to better understand the technical solution of the present invention, the present invention will be further described in detail below with reference to specific embodiments.

[0047] Techniques, methods, and equipment known to those skilled in the art may not be discussed in detail, but where appropriate, such techniques, methods, and equipment should be considered part of the specification.

[0048] In all the examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not as limitations. Therefore, other examples of exemplary embodiments may have different values.

[0049] Figure 1 This is a flowchart illustrating a method for predicting the lifespan of a drag chain cable according to an embodiment of the present invention, as shown below. Figure 1 As shown, the drag chain cable life prediction method of this embodiment may include the following steps S101 to S104.

[0050] Step S101: Obtain the warranty life of the cable and the range of application parameters corresponding to the warranty life. The application parameters include at least one of stroke, speed, acceleration, and bending radius.

[0051] The warranty life of a drag chain cable is the manufacturer's commitment to the number of reciprocating cycles during which the drag chain cable can operate normally and maintain its performance, provided that the application parameters specified by the manufacturer are met.

[0052] In some examples, manufacturers determine the warranty life and application parameter range of drag chain cables through experimental test data. The application parameter range is defined by the maximum stroke, maximum speed, maximum acceleration, minimum bending radius, and the ambient temperature range corresponding to the minimum bending radius.

[0053] In some examples, based on the cable specification and model information, the pre-stored warranty life of the cable and the corresponding application parameter range are retrieved from the database.

[0054] In some examples, based on the SN life curve model, combined with finite element simulation data and laboratory test data, the reciprocating motion life of the drag chain cable under specified application parameter conditions is obtained as the warranty life of the cable. Specifically, such as... Figure 2 As shown, the steps may include steps S201 to S207.

[0055] Step S201: Based on the cable's structure and material parameters, establish the finite element model of the cable.

[0056] In one implementation, the ANSYS finite element analysis software is used to model the cable's core structure (such as copper wire conductors, insulation layers, and outer sheath), key dimensions (such as conductor diameter / number of conductors, thickness of each insulation layer, and total outer diameter of the cable), and physical parameters of the materials (such as Young's modulus, density, and Poisson's ratio).

[0057] Step S202: Perform finite element simulation calculations to obtain the maximum von Mises stress and the maximum axial strain.

[0058] In one implementation, finite element simulation calculations are performed using ANSYS finite element analysis software to read the maximum von Mises stress and maximum axial strain from the maximum von Mises stress contour plot and axial strain contour plot.

[0059] Step S203: Obtain the internal stress correction factor , ,in, For the maximum von Mises stress, For internal axial stress, ,in, For elastic modulus, This represents the maximum axial strain.

[0060] Materials often experience multiaxial stress states (such as combinations of tension, compression, and shear) in actual working conditions. Von Mises stress equates a three-dimensional stress state to uniaxial tensile stress. The maximum von Mises stress is an equivalent stress index that equates the multiaxial stress state of a cable at its most dangerous location (hot spot) to uniaxial stress.

[0061] Material life models are typically based on uniaxial stress data. By obtaining internal stress correction factors, the damage caused to the material by the actual complex multiaxial stress state is scientifically mapped onto the material life model based on uniaxial stress data, thereby achieving a more accurate prediction of the cable's life under actual working conditions.

[0062] Step S204: Obtain the basic durability limit stress of a single core wire of the cable. and the ultimate durability life corresponding to the ultimate durability stress of the foundation. The modified ultimate durability stress of the cable is obtained based on the following model. :

[0063] in, This is the correction factor for the surface smoothness of the cable. This is the size correction factor. ,in, This is the diameter of the cable.

[0064] in, , This is a surface finish correction factor, related to cable surface treatment. This is a surface roughness correction factor, related to the surface roughness of the cable. and The value can be obtained from the technical manual.

[0065] In one implementation, the basic durability limit stress of a single core wire of the cable is obtained through laboratory test data. and the corresponding durability limit life. .

[0066] Step S205: Obtain any stress intensity And the fatigue life of the cable corresponding to this stress intensity. .

[0067] In one implementation, a stress intensity is obtained through laboratory test data. And the fatigue life of the cable corresponding to this stress intensity. .

[0068] Step S206, obtain the fitting parameters b and c of the SN lifetime curve equation:

[0069] .

[0070] Step S207: Obtain the stress amplitude according to the application parameter range. The stress amplitude is obtained based on the SN life curve equation. The corresponding fatigue life of the cable As the warranty period, the SN lifespan curve equation is as follows:

[0071]

[0072] The SN life curve, or stress-life curve, describes the relationship between material stress intensity (S) and the number of stress cycles (N), reflecting the material's lifespan under different stress levels. In one implementation, the stress amplitude is obtained from laboratory test data based on the maximum stroke, maximum speed, maximum acceleration, and minimum bending radius corresponding to the application parameter range.

[0073] Based on the SN life curve model, this embodiment combines finite element simulation data and a small amount of cable SN life curve experimental data to achieve rapid prediction of the fatigue life of cables under different stress amplitudes. This can significantly reduce the number of experiments, save testing costs, and effectively avoid the inherent random errors of single experimental data, thus significantly improving the reliability of the results.

[0074] Step S102: Obtain target working condition parameter values, which include at least one of stroke value, speed value, acceleration value, and bending radius value.

[0075] The fatigue life of drag chain cables in reciprocating motion is affected by a variety of factors, primarily including stroke, speed, acceleration, bending radius, and ambient temperature. Speed ​​directly determines the frequency of stress cycles; higher speeds mean the cable undergoes more bending-restoring cycles per unit time, thus accelerating fatigue damage. Furthermore, higher speeds may increase frictional heat in the cable material, affecting its thermal stability and fatigue life. Changes in acceleration generate dynamic stresses, especially at the start and stop of the cable's movement. These dynamic stresses may be greater than static stresses, accelerating fatigue damage. Acceleration changes can also further increase stress in stress concentration areas, particularly in the cable's bending sections, accelerating crack initiation and propagation. Changes in stroke affect the stress distribution of the cable in the drag chain; longer strokes result in more uniform stress distribution, reducing localized stress concentration. Stroke also affects the cable's bending radius; smaller bending radii introduce greater bending stress, increasing fatigue damage. The cable's bending radius should be as large as possible to reduce stress concentration.

[0076] Step S103: If the target operating condition parameter values ​​are all within the application parameter range corresponding to the warranty life, then the warranty life is obtained as the target predicted life of the cable.

[0077] Step S104: If one or more of the target operating condition parameter values ​​exceed the application parameter range corresponding to the warranty life, then according to the drag chain cable reciprocating motion life prediction model based on operating condition parameters, obtain one or more predicted lifespans corresponding to the target operating condition parameter values, and take the minimum value of the aforementioned one or more predicted lifespans as the target predicted lifespan of the cable. The drag chain cable reciprocating motion life prediction model based on operating condition parameters is as follows:

[0078]

[0079] in, To predict lifetime, N G To ensure the warranty life of the cable, It is the first constant. It is the second constant. The value of ξ is related to the type of target operating condition parameter; x ξ is the exponential factor for operating parameters. x The value is related to the type of the target operating condition parameter. For the target operating condition parameter values, This indicates the type of target operating condition parameter, which includes at least one of stroke, speed, acceleration, and bending radius.

[0080] In some examples, the drag chain cable reciprocating motion life prediction models based on operating condition parameters include: drag chain cable reciprocating motion life prediction models based on stroke, drag chain cable reciprocating motion life prediction models based on speed, drag chain cable reciprocating motion life prediction models based on acceleration, and drag chain cable reciprocating motion life prediction models based on bending radius.

[0081] In one implementation, the stroke-based drag chain cable reciprocating motion life prediction model can be specifically implemented as follows: , , where N G To ensure the warranty life of the cable, The stroke value is the parameter value for the target operating condition. As a travel index factor, The maximum stroke within the application parameter range corresponding to the warranty life.

[0082] In one implementation, the speed-based drag chain cable reciprocating motion life prediction model can be specifically implemented as follows: , ,in, To ensure the warranty life of the cable, The speed value is one of the target operating condition parameter values. As the speed exponential factor, The maximum speed within the range of application parameters corresponding to the warranty life.

[0083] In one implementation, the acceleration-based drag chain cable reciprocating motion life prediction model can be specifically implemented as follows: , In the formula, N G To ensure the warranty life of the cable, The acceleration value is one of the parameters for the target operating condition. For acceleration exponential factor, The maximum acceleration within the range of application parameters corresponding to the warranty life.

[0084] In one implementation, the drag chain cable reciprocating motion life prediction model based on the bending radius can be specifically implemented as follows: , In the formula, N G To ensure the warranty life of the cable, The bending radius value is the parameter value for the target working condition. The bending radius exponential factor, The minimum bending radius within the application parameter range corresponding to the warranty life.

[0085] In some examples, step S104 can be specifically implemented as: judging the operating condition parameter values ​​one by one; if the stroke parameter value in the operating condition parameters is greater than the maximum stroke corresponding to the warranty life... The first predicted life is then obtained based on the stroke-based drag chain cable reciprocating motion life prediction model. If the speed parameter value in the operating condition parameters is greater than the maximum speed corresponding to the warranty period; Then, the second predicted life is obtained based on the speed-based drag chain cable reciprocating motion life prediction model. If the acceleration parameter value in the operating condition parameters is greater than the maximum acceleration corresponding to the warranty period; The third predicted life is obtained from the acceleration-based drag chain cable reciprocating motion life prediction model. If the bending radius parameter value in the operating condition parameters is less than the minimum bending radius corresponding to the warranty period; Then, the fourth predicted life is obtained based on the drag chain cable reciprocating motion life prediction model based on the bending radius. ; Obtain the predicted lifespan based on different operating parameters. , , , The minimum value among them is taken as the target predicted life of the drag chain cable, that is... , , , .

[0086] Based on the SN life curve equation and cable fatigue damage theory, this embodiment uses an exponential function to represent the changing trend of cable life. Through fitting a large amount of experimental data of different drag chain cables under different operating parameter values, a drag chain cable reciprocating motion life prediction model based on operating parameter is established on the basis of the warranty life. This model is used to predict the reciprocating motion life of the drag chain cable when the target operating parameter value exceeds the application parameter range corresponding to the warranty life. Thus, it realizes the rapid and accurate prediction of the reciprocating motion life of the drag chain cable under arbitrary operating parameters, solves the common problems encountered by users in engineering practice, and provides a scientific decision-making basis for the replacement and maintenance of drag chain cables.

[0087] In one embodiment, the target predicted life of different cables is obtained according to the above-mentioned drag chain cable reciprocating motion life prediction model based on operating parameters, and the results are compared with experimental data under the same operating conditions. The results are shown in Table 1.

[0088] Table 1 shows an example of the comparison between the predicted results and the experimental results:

[0089]

[0090] As can be seen from Table 1, the drag chain cable life prediction method provided in this embodiment can quickly and effectively predict the fatigue life of the cable under different working conditions, greatly saving the test cycle and test cost.

[0091] This invention also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements any of the methods described in the foregoing embodiments of this invention. Optionally, the computer-readable storage medium may be a non-transitory storage medium, but is not limited thereto; it may also be a temporary storage medium. A computer-readable storage medium is a tangible device capable of holding and storing instructions used by an instruction execution device. A computer-readable storage medium may include, but is not limited to, electrical storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any suitable combination thereof.

[0092] Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. For example... Figure 3 As shown, the electronic device 300 may include a memory 301 and a processor 302. The memory 301 may be used to store computer instructions, and the processor 302 may be used to retrieve computer instructions from the memory 301 to execute all or part of the steps of any of the methods in the foregoing embodiments of the present invention. The processor may be one or more, and the one or more processors may execute instructions individually or jointly. Similarly, the memory may be one or more, and the one or more memories may store the aforementioned computer instructions individually or jointly.

[0093] like Figure 4 As shown, this embodiment of the invention also provides a drag chain cable life prediction system, the system comprising:

[0094] The visualization module 401 includes an input module 4011 and an output module 4012. The input module 4011 is used to obtain the cable specifications and target operating condition parameter values ​​through a graphical user interface. The target operating condition parameter values ​​include at least one of the following: stroke value, speed value, acceleration value, and bending radius value. The output module 4012 is used to display the target predicted life.

[0095] Database module 402 is used to obtain the warranty life of the cable and the application parameter range corresponding to the warranty life according to the cable's specifications and model. The application parameters include at least one of stroke, speed, acceleration, and bending radius.

[0096] The calculation module 403 is used to obtain the warranty life as the target predicted life of the cable if all the target operating condition parameter values ​​are within the range of the application parameters; if one or more of the target operating condition parameter values ​​exceed the range of the application parameters, it obtains one or more predicted lives corresponding to the target operating condition parameter values ​​according to the drag chain cable reciprocating motion life prediction model based on the operating condition parameters, and obtains the minimum value of all the aforementioned predicted lives as the target predicted life of the cable. The drag chain cable reciprocating motion life prediction model based on the operating condition parameters is as follows:

[0097]

[0098] in, To predict lifetime, N G To ensure the warranty life of the cable, It is the first constant. ξ is the second constant; x For operating condition parameter index factor, For the target operating condition parameter values, The target operating condition parameter type includes one of the following: stroke, speed, acceleration, and bending radius.

[0099] This embodiment presents the complex life prediction process through an intuitive visual interface. Users can easily understand the expected number of cycles, i.e., the target predicted life, of a specified cable under specific operating conditions with simple operations. This embodiment integrates theoretical calculations, engineering practice, and information technology, which not only significantly improves the efficiency of cable product life assessment but also provides users with scientific and reliable technical support for decision-making, possessing high engineering application value.

[0100] It should be noted that the specific implementation methods of each module in the system can be referred to the corresponding descriptions in the foregoing embodiments, and will not be repeated here.

[0101] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of methods, apparatuses, systems, and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of an instruction containing one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than those shown in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions. It should be noted that implementation in hardware, implementation in software, and implementation using a combination of software and hardware are all equivalent.

[0102] It should be understood that the above description is only an exemplary embodiment of the present invention, and the scope of protection of the present invention is not limited thereto. Modifications, substitutions or adaptive changes that can be easily conceived by those skilled in the art without departing from the principle and essence of the present invention should all be covered within the scope of protection of the present invention.

Claims

1. A method for predicting the lifespan of a drag chain cable, characterized in that, include: Obtain the warranty life of the cable and the range of application parameters corresponding to the warranty life, wherein the application parameters include at least one of stroke, speed, acceleration, and bending radius; Obtain target operating condition parameter values, wherein the target operating condition parameter values ​​include at least one of stroke value, speed value, acceleration value, and bending radius value; If the target operating condition parameter values ​​are all within the range of the application parameters, then the warranty life is obtained as the target predicted life of the cable. If one or more of the target operating condition parameter values ​​exceed the range of the application parameters, then according to the drag chain cable reciprocating motion life prediction model based on the operating condition parameters, one or more predicted lives corresponding to the target operating condition parameter values ​​are obtained, and the minimum value of the predicted life is obtained as the target predicted life of the cable. The life prediction model is as follows: in, For the predicted lifetime, N G For the aforementioned warranty life, It is the first constant. ξ is the second constant; x For operating condition parameter index factor, The target operating condition parameter value, The target operating condition parameter type is indicated, and the type includes at least one of stroke, speed, acceleration, and bending radius.

2. The method for predicting the lifespan of a drag chain cable as described in claim 1, characterized in that, The process of obtaining the warranty life of the cable includes: Based on the cable's structure and material parameters, a finite element model of the cable is established; Finite element simulation was performed to obtain the maximum von Mises stress and the maximum axial strain. The internal stress correction factor is obtained, and the formula for calculating the internal stress correction factor is as follows: ,in, The maximum von Mises stress, For elastic modulus, The maximum axial strain; Obtain the basic durability limit stress of a single core wire of the cable. and the durability limit life corresponding to the basic durability limit stress. The modified ultimate durability stress of the cable is obtained according to the following model. : in, This is the surface smoothness correction factor. This is the size correction factor. ,in, The diameter of the cable; Obtain any stress intensity and the fatigue life of the cable corresponding to the stress intensity. ; Obtain the fitting parameters b and c of the SN lifetime curve equation. The formulas for calculating the fitting parameters b and c are as follows: ； Based on the application parameter range, the stress amplitude is obtained. Then, based on the SN life curve equation, the fatigue life of the cable corresponding to the stress amplitude is obtained as the warranty life. The SN life curve equation is: in, The stress amplitude, The fatigue life of the cable corresponding to the stress amplitude.

3. The method for predicting the lifespan of a drag chain cable as described in claim 1, characterized in that, The drag chain cable reciprocating motion life prediction model based on operating condition parameters includes: a drag chain cable reciprocating motion life prediction model based on stroke, a drag chain cable reciprocating motion life prediction model based on speed, a drag chain cable reciprocating motion life prediction model based on acceleration, and a drag chain cable reciprocating motion life prediction model based on bending radius.

4. The method for predicting the lifespan of a drag chain cable as described in claim 3, characterized in that, The stroke-based drag chain cable reciprocating motion life prediction model is as follows: , ,in, For the aforementioned warranty life, The stroke value is the parameter value for the target operating condition. As a travel index factor, This is the maximum travel distance within the range of application parameters.

5. The method for predicting the lifespan of a drag chain cable as described in claim 3, characterized in that, The speed-based drag chain cable reciprocating motion life prediction model is as follows: , ,in, For the aforementioned warranty life, The speed value is one of the target operating condition parameter values. As the speed exponential factor, This refers to the maximum speed within the range of application parameters.

6. The method for predicting the lifespan of a drag chain cable as described in claim 3, characterized in that, The acceleration-based drag chain cable reciprocating motion life prediction model is as follows: , In the formula, N G For the aforementioned warranty life, The acceleration value is one of the target operating condition parameter values. For acceleration exponential factor, This refers to the maximum acceleration within the range of application parameters.

7. The method for predicting the lifespan of a drag chain cable as described in claim 3, characterized in that, The prediction model for the reciprocating life of the drag chain cable based on the bending radius is as follows: , In the formula, N G For the aforementioned warranty life, The bending radius value is one of the target working condition parameter values. The bending radius exponential factor, The minimum bending radius within the range of application parameters.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, The computer program, when executed by a processor, implements the method as described in any one of claims 1 to 7.

9. An electronic device, characterized in that, The device includes a memory and a processor, the memory being used to store computer instructions, and the processor being used to retrieve the computer instructions from the memory to perform the method as described in any one of claims 1 to 7.

10. A drag chain cable life prediction system, characterized in that, include: A visualization module, which includes an input module and an output module; The input module is used to obtain the cable specifications and target operating condition parameter values ​​through a graphical user interface. The target operating condition parameter values ​​include at least one of the following: stroke value, speed value, acceleration value, and bending radius value. The output module is used to display the target predicted lifespan. The database module is used to obtain the warranty life of the cable and the application parameter range corresponding to the warranty life according to the cable's specifications and model. The application parameters include at least one of stroke, speed, acceleration, and bending radius. The calculation module is used to, if all the target operating condition parameter values ​​are within the application parameter range, obtain the warranty life as the target predicted life output of the cable; if one or more of the target operating condition parameter values ​​exceed the application parameter range, obtain one or more predicted lives corresponding to the target operating condition parameter values ​​according to the drag chain cable reciprocating motion life prediction model based on the operating condition parameters, and obtain the minimum value of the predicted life as the target predicted life output of the cable. The life prediction model is as follows: in, For the predicted lifetime, N G For the aforementioned warranty life, It is the first constant. ξ is the second constant; x For operating condition parameter index factor, The target operating condition parameter value, The target operating condition parameter type is indicated, and the type includes at least one of stroke, speed, acceleration, and bending radius.

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