Hinge wear depth dynamic simulation method based on random event
By constructing a random event time function matrix and setting a bidirectional wear factor, the mean function of the hinge wear process is dynamically adjusted, which solves the problem of the instantaneous and continuous impact of mechanical stress collision on wear depth and improves the accuracy and reliability of wear prediction.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- XIAN TECH UNIV
- Filing Date
- 2025-12-04
- Publication Date
- 2026-05-05
AI Technical Summary
Existing methods for simulating the wear depth of aircraft hinges cannot effectively reflect the instantaneous and continuous impact of mechanical stress collisions on the wear depth, resulting in insufficient accuracy in wear prediction.
A random event time function matrix is constructed to determine the duration of the collision effect. A two-way wear factor is set, and the mean function of the IG process is dynamically adjusted to reflect the nonlinear effect of collision events with consistent and opposite stress directions on the wear depth.
It improves the accuracy and reliability of aircraft hinge wear prediction and enables accurate modeling of nonlinear and non-stationary wear processes.
Smart Images
Figure CN121980735A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of aircraft hinge wear modeling and life prediction technology, and in particular to a dynamic simulation method for hinge wear depth based on random events. Background Technology
[0002] As a critical moving component of an aircraft structural system, the wear depth of aircraft hinges directly affects the structural safety and service life of the aircraft. Existing research simulating the dynamic changes in hinge wear depth relies on stochastic algorithms, such as the IG process. However, during mechanical motion, stress-induced collisions inevitably occur. At the moment of impact, these collisions affect the operating hinges. For example, under the same stress direction, the wear depth increases instantaneously and persists for a period; conversely, under the opposite stress direction, the wear depth decreases instantaneously and also persists for a period. Summary of the Invention
[0003] The main objective of this invention is to provide a method for dynamic simulation of hinge wear depth based on random events.
[0004] Another objective of this invention is to provide a dynamic simulation device for hinge wear depth based on random events.
[0005] The third objective of this invention is to provide an electronic device.
[0006] A fourth objective of this invention is to provide a non-transitory computer-readable storage medium.
[0007] To achieve the above objectives, a first aspect of the present invention proposes a method for dynamically simulating hinge wear depth based on random events, comprising: S1, construct the random event time function matrix, and generate the occurrence time of periodic collision events based on the design life of the aircraft hinge and the predefined time unit; S2, determine the duration of the collision impact by calculating the duration of the collision event's continuous impact on the wear process based on the minimum or maximum value of the time difference between adjacent collision events in the random event time function matrix; S3 sets a bidirectional wear factor to characterize the doubling or halving effect of collision events with the same and opposite stress directions on the wear depth, respectively. S4. Establish the wear process function. Based on whether the current time point belongs to the collision event occurrence time and its duration of influence in the random event time function matrix, dynamically adjust the mean function of the IG process to reflect the nonlinear impact of the collision event.
[0008] Optionally, the parameters in the random event time function matrix T include the number of periods p, which is calculated using the following formula: The random event time function matrix T is expressed as: T=[1,2,...,p]*[12,17,23,24,35,45,57,61,76,87,91,94,98,101,112,135,141,154,165,172,187,192]; Or, T=[1,2,...,p]*[2,4,7,9]; Or, T=[1,2,...,p]*[17,31,47,65,81,102,131,154,169,181]; Alternatively, T = [1,2,...,p] * [31,65,102,154,181]; Or, T=[1,2,...,p]*[17,47,81,131,169].
[0009] Optionally, the duration d of the collision effect is represented as: Constant 1; Or, a positive integer greater than 1; Alternatively, depending on the values in matrix T, d equals 50% of the smallest nearest neighbor difference, rounded down; Alternatively, depending on the values in the T matrix, d equals 50% of the smallest nearest neighbor difference, rounded up.
[0010] Alternatively, depending on the values in the T matrix, d equals 50% of the largest nearest neighbor difference, rounded down.
[0011] Alternatively, depending on the values in the T matrix, d equals 50% of the largest nearest neighbor difference, rounded up.
[0012] Optionally, the wear process function is expressed as:
[0013] or
[0014] in, For the wear process function, For wear factor, The wear factor is influenced by stress impacts and wear forces acting in the same direction. The wear factor is the effect of stress collisions and wear forces acting in opposite directions.
[0015] To achieve the above objectives, a second aspect of the present invention provides a dynamic simulation device for hinge wear depth based on random events, comprising: The first module is used to construct a random event time function matrix and generate the occurrence time of periodic collision events based on the design life of the aircraft hinge and a predefined time unit. The second module is used to determine the duration of the impact of the collision. It calculates the duration of the impact of the collision event on the wear process based on the minimum or maximum value of the time difference between adjacent collision events in the random event time function matrix. The third module is used to set bidirectional wear factors, which respectively characterize the doubling or halving effect of collision events with the same and opposite stress directions on the wear depth; The fourth module is used to establish the wear process function. Based on whether the current time point belongs to the time of occurrence of the collision event in the random event time function matrix and its duration of influence, the mean function of the IG process is dynamically adjusted to reflect the nonlinear impact of the collision event.
[0016] To achieve the above objectives, a third aspect of this application provides an electronic device, including a processor and a memory; wherein the processor runs a program corresponding to the executable program code stored in the memory to implement the method described in the first aspect.
[0017] To achieve the above objectives, a fourth aspect of this application provides a non-transitory computer-readable storage medium having a computer program stored thereon that, when executed by a processor, implements the method described in the first aspect.
[0018] The embodiments of the present invention have the following beneficial effects: they can effectively simulate the dynamic changes in wear depth of aircraft hinges under random stress collision events, improve the accuracy and reliability of wear prediction, and achieve accurate modeling of nonlinear and non-stationary wear processes. Attached Figure Description
[0019] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein: Figure 1 A flowchart of a method for dynamically simulating hinge wear depth based on random events, provided for embodiments of the present invention; Figure 2 The diagram shows a structure of a dynamic simulation device for hinge wear depth based on random events, provided in an embodiment of the present invention. Detailed Implementation
[0020] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.
[0021] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.
[0022] Before describing the proposed method and apparatus for dynamic simulation of hinge wear depth based on random events, the background of this invention should be explained first. The quasi-Gaussian distribution inverse Gaussian (IG) process, with its independent non-negative increments, has been proven effective in simulating monotonically progressive degradation processes such as wear, corrosion, and creep of materials. The IG process can be used to simulate the dynamic variation characteristics of hinge wear depth. Since the wear on the bushing in the hinge is non-uniform, this study mainly focuses on the variation characteristics of the maximum wear depth of the hinge over time.
[0023] The wear process of a clearance hinge can be represented by the IG process:
[0024] In the formula: —Maximum cumulative wear depth of the bushing; —Mean function; —Scale parameter.
[0025] exist ( At time >0), the maximum cumulative wear depth of the hinge It has the following attributes: (1) ,and .
[0026] (2) It has stable and independent incremental growth, and ,in , It is a monotonically increasing function. .
[0027] Wear increment The probability density function is:
[0028] When wear increment When the change is not linear, a time-domain transformation function is used
[66] . , This represents the converted time, in order to make... ,use ,in It is a positive number. The IG process of time-domain transformation can be represented as: .
[0029] However, during mechanical motion, stress-induced collisions inevitably occur to varying degrees. At the moment of impact, these collisions affect the operating hinges. For example, under the same stress direction, the wear depth increases instantaneously and persists for a period of time; conversely, under the opposite stress direction, the wear depth decreases instantaneously and also persists for a period of time. To accurately reflect the stochastic process, methods for simulating the dynamic changes in hinge wear depth during the IG process need to be enhanced.
[0030] In order to solve the above problems, this invention proposes a method and apparatus for dynamic simulation of hinge wear depth based on random events.
[0031] The following description, with reference to the accompanying drawings, describes a method and apparatus for dynamic simulation of hinge wear depth based on random events, according to an embodiment of the present invention.
[0032] This embodiment provides a method for dynamically simulating hinge wear depth based on random events. For example... Figure 1 As shown, the method includes the following steps: S1, construct the random event time function matrix, and generate the occurrence time of periodic collision events based on the design life of the aircraft hinge and the predefined time unit.
[0033] In step S1, a random event time function matrix T is constructed. Based on the design life of the aircraft hinge and a predefined time unit, the occurrence times of stress-induced collision events that occur periodically during the entire life evolution of the hinge are generated. This is used to time-calibrate stress-induced collisions (such as gap abrupt changes, transient impacts on the hinge sub-face, and instantaneous impacts caused by door swing) during the hinge wear process, thereby providing a unified time-driven input for subsequent wear state evolution modeling, stress event triggering response, life assessment, and maintenance decisions.
[0034] In this embodiment, the time unit is a pre-defined basic unit used to uniformly express the hinge lifespan. The time unit can be selected as seconds, minutes, hours, days, weeks, months, or years. The designed lifespan of the hinge is expressed as L (measured in the selected time unit), for example, 400 months, 200 hours, or 10 days. To adapt to the statistical conclusions of large-scale stress monitoring experiments, this embodiment pre-defines a "baseline period length" L0 (also measured in the aforementioned time unit). The baseline period length is used to divide the entire lifespan into several periods, and within each period, the occurrence times of stress collision events are generated according to a fixed "relative event time sequence."
[0035] The parameters in the random event time function matrix T include the number of cycles p, which represents the number of cycles that need to be repeated within the design life. In this embodiment, the number of cycles p can be calculated from the design life L and the reference cycle length L0, preferably using an up-rounding method to ensure coverage of the entire lifespan, i.e.: p = L / L0
[0036] in, · The value is rounded up; L is the hinge design life (measured in time units); L0 is the baseline cycle length (measured in the same time unit). In some implementations, rounding down or rounding to the nearest integer can also be used to meet different event trigger coverage strategies, but rounding up is preferred to avoid missing end-of-life events. When L is less than or equal to L0, p can be either 1 or 2; to meet the engineering constraint that "p is a positive integer greater than 1", in this embodiment, p=2 can be used when L≤L0 to ensure that at least two cycles are repeated for statistical stability and model training stability.
[0037] It should be noted that in the embodiments of the present invention, "mechanism design life 200 time units" or "mechanism design life 10 time units" are used to specify the typical value of the reference cycle length L0 used in the corresponding option. When the option uses L0=200, it means that every 200 time units constitutes one cycle; when the option uses L0=10, it means that every 10 time units constitute one cycle.
[0038] It should be noted that although this step is called the "random event time function matrix", its "randomness" is reflected in the fact that the relative time sequence b is derived from the probability distribution of stress collision occurrence obtained from statistical experiments or empirical samples. At the implementation level, a fixed sequence can be used to generate repeatable events. In other implementations, a small random perturbation (e.g., a jitter of ±1 time unit) can be superimposed on b or b can be generated by sampling to enhance the coverage of different working conditions, but the embodiments of this application are not limited thereto.
[0039] In this embodiment, based on different monitoring scales, stress event densities, and reference period lengths, various options for predefined relative time sequences b are provided to construct the time function matrix T: Option 1: With a base period length L0 = 200 time units, define b = [12,17,23,24,35,45,57,61,76,87,91,94,98,101,112,135,141,154,165,172,187,192] and construct T = [1,2,…,p] × b, where p is the number of periods, a positive integer greater than 1, generally calculated from the mechanism's design life L and L0 = 200. The time unit can be seconds, minutes, hours, days, weeks, months, or years.
[0040] Option 2: With a base period length L0 = 10 time units, define b = [2,4,7,9] and construct T = [1,2,…,p] × b, where p is the number of periods, a positive integer greater than 1, generally calculated from the mechanism's design life L and L0 = 10. The time unit can be seconds, minutes, hours, days, weeks, months, or years.
[0041] Option 3: With a base period length L0 = 200 time units, define b = [17,31,47,65,81,102,131,154,169,181] and construct T = [1,2,…,p]×b, where p is the number of periods, a positive integer greater than 1, generally calculated from the mechanism's design life L and L0 = 200. The time unit can be seconds, minutes, hours, days, weeks, months, or years.
[0042] Option 4: With a base period length L0 = 200 time units, define b = [31, 65, 102, 154, 181] and construct T = [1, 2, ..., p] × b, where p is the number of periods, a positive integer greater than 1, generally calculated from the mechanism's design life L and L0 = 200. The time unit can be seconds, minutes, hours, days, weeks, months, or years.
[0043] Option 5: With a base period length L0 = 200 time units, define b = [17,47,81,131,169] and construct T = [1,2,…,p]×b, where p is the number of periods, a positive integer greater than 1, generally calculated from the mechanism's design life L and L0 = 200. The time unit can be seconds, minutes, hours, days, weeks, months, or years.
[0044] In one embodiment of the present invention, taking Option 1 as an example, the design service life of the aircraft door hinge is 400 months, and the unit of time measurement is selected as "month". With the baseline cycle length L0 = 200 months set for Option 1, the number of cycles p is determined as follows: p = 400 / 200 = 2 = 2 Therefore, construct T=[1,2]*[12,17,23,24,35,45,57,61,76,87,91,94,98,101,112,135,141,154,165,172,187,192] months.
[0045] The timing of the stress-induced collision event can be determined by unfolding the data. The events corresponding to the first cycle occur in the months [12,17,23,24,35,45,57,61,76,87,91,94,98,101,112,135,141,154,165,172,187,192]. The events corresponding to the second cycle occur in the months of [12*2, 17*2, 23*2, 24*2, 35*2, 45*2, 57*2, 61*2, 76*2, 87*2, 91*2, 94*2, 98*2].
[0046] Therefore, at the aforementioned point in time, this embodiment of the application determines that a stress collision event occurs during the hinge wear process, and uses this event as the trigger input for the stress response, wear increment correction, damage accumulation and life prediction models in subsequent steps.
[0047] S2, determine the duration of the collision effect, and calculate the duration of the collision event's continuous impact on the wear process based on the minimum or maximum value of the time difference between adjacent collision events in the random event time function matrix.
[0048] In step S2, the duration d of the collision effect is determined to characterize the duration of the sustained impact of the stress-induced collision event on the hinge wear process after the event occurs. Since stress-induced collisions often cause abrupt changes in contact state, local stress concentration, transient impact energy input, and increased damage to the friction pair, these effects do not disappear immediately after the event but typically persist for a period of time, manifesting as an increase in wear rate, a bias in wear increment, or an acceleration of damage accumulation. Therefore, in this embodiment, by introducing the duration parameter d, the impact of the stress-induced collision event on wear calculation is extended to d consecutive time units after the event, making the wear evolution model more consistent with engineering reality.
[0049] In this embodiment, the duration d is an integer measured in time units, representing the number of consecutive time units after the event occurs within which the wear calculation needs to be superimposed with the collision effect. The value of d can be a constant or adaptively determined based on the distribution of event times in the random event time function matrix T. Specifically, it is preferable to extract the minimum nearest neighbor difference or the maximum nearest neighbor difference based on the time difference between adjacent collision events in the random event time function matrix T, and then calculate the duration of the continuous effect using a certain proportion (e.g., 50%), to avoid situations where the collision effect intervals completely overlap or the effect interval is too short to reflect the continuous effect.
[0050] In this embodiment, establishing the number 'd' of the duration of the impact after a stress-induced collision event can provide several optional schemes to adapt to different hinge structure types, different stress event densities, and different model detail requirements: Option 1: d is a constant of 1. In this case, it is assumed that the stress collision event only affects the period in which it occurs (or the next time unit), which is suitable for scenarios where the impact of the event is very short or the time resolution is coarse.
[0051] Option 2: d is a positive integer greater than 1 and can be given by engineering experience or experimental calibration. For example, d=3, d=5, or d=10. This option is suitable for scenarios where there are already mature empirical parameters or where the duration of the effect can be obtained through experimental fitting.
[0052] Option 3: d depends on the values in matrix T, and d is equal to 50% of the minimum nearest neighbor difference Δmin, rounded down. That is: d = 0.5 × Δmin
[0053] in · This option indicates rounding down. Its purpose is to ensure that the length of the influence interval does not exceed half the interval between the closest events, thereby reducing the probability of significant overlap between the influence intervals of adjacent events and making it easier to distinguish the wear contribution of different events.
[0054] Option 4: d depends on the values in matrix T, and d is equal to 50% of the minimum nearest neighbor difference Δmin, rounded up. That is: d = 0.5 × Δmin
[0055] in · This option indicates rounding up. Compared to option 3, this option moderately increases the duration when Δmin is odd, making the duration effect more fully expressed. It is suitable for scenarios where wear recovery after a collision is slow or the effect decays more gradually.
[0056] Option 5: d depends on the values in matrix T, and d is equal to 50% of the maximum nearest neighbor difference Δmax, rounded down. That is: d = 0.5 × Δmax
[0057] This option determines the duration of the impact based on the sparser event intervals, which often results in a longer duration. It is suitable for scenarios with fewer collision events but significant aftereffects from a single event, requiring coverage of a longer impact window.
[0058] Option 6: d depends on the values in matrix T, and d is equal to 50% of the maximum nearest neighbor difference Δmax, rounded up. That is: d = 0.5 × Δmax
[0059] This option further enhances the duration interval length based on option 5, and is suitable for modeling strategies that aim to minimize the omission of collision aftereffects and are willing to expand the influence window.
[0060] In one embodiment of the present invention, based on the random event time function matrix defined in option 4 of step S1, the following is taken: T = [1,2] × [31,65,102,154,181] The event times within one period are [31, 65, 102, 154, 181]. Calculate the nearest neighbor difference between adjacent events: Proximity difference 1 = 65 31 = 34; Neighboring difference 2 = 102 65 = 37; The nearest neighbor difference 3 = 154 102 = 52; The nearest neighbor difference 4 = 181 154 = 27; The minimum nearest neighbor difference Δmin = 27. Following the calculation method of "rounding down to the nearest 50% of the minimum nearest neighbor difference", we have: d = 27 / 2 = 13 Therefore, in the embodiments of this application, once a stress-induced collision event occurs at time ti, the collision event will affect the wear calculation for the next 13 consecutive time units. That is, the wear model needs to superimpose the collision effect term, adjust the wear rate, or introduce additional damage increments in the interval [ti, ti+13] (or from ti onwards 13 discrete time steps) to reflect the continuous aftereffect of the collision event.
[0061] S3 sets a bidirectional wear factor to characterize the doubling or halving effect of collision events with the same and opposite stress directions on the wear depth.
[0062] In step S3, a bidirectional wear factor is set to characterize the amplification or suppression effect of stress-induced collision events on wear depth (or wear increment, wear rate) under two conditions: "stress direction is consistent with wear force direction" and "stress direction is opposite to wear force direction". Since hinges in actual service not only have a stable main load wear direction, but are also subjected to transient impacts and reverse loads caused by door opening and closing, aerodynamic loads, and structural vibrations, collision events have both positive and negative stress directions. Positive collisions usually exacerbate contact stress and friction damage, causing wear to double in a short period; negative collisions, under certain operating conditions, may cause contact surfaces to re-fit, gaps to spring back, or loads to unload, resulting in a reduced wear contribution, or even, in a model sense, suppression of wear growth. Therefore, in this embodiment, an influencing wear factor r is introduced, and corresponding r1 and r2 are constructed to achieve a quantitative expression of the "bidirectional" collision effect.
[0063] In this embodiment, the wear factor *r* is used to modulate the base wear calculation results within the duration of the stress-induced collision event. To reflect the bidirectional nature of the stress direction, two types of wear factors are set in this embodiment: r1: The wear factor that affects the stress direction of a stress-induced collision event when it aligns with the wear force direction; r2: The wear factor when the stress direction of a stress-induced collision event is opposite to the wear force direction.
[0064] Therefore, within the collision influence window, the corresponding magnification factor is selected according to the direction criterion, enabling the model to distinguish between the different mechanisms of "intensifying wear" and "reducing wear".
[0065] In this embodiment, the wear factor r can be configured as a constant, which facilitates engineering implementation and parameter calibration. It can also be obtained through experimentation or fitting historical data. Specifically, the following optional solutions are provided: Option 1: r is a constant and an integer greater than 1, representing the wear factor. This setting is used to describe the situation where stress impacts significantly amplify wear within the influence window; a value of 2 is preferred, meaning that wear is calculated at twice the rate during the impact period.
[0066] Option 2: r is a constant and a real number greater than 1, representing the wear factor. This setting is used to describe cases where the wear amplification is not an integer multiple, such as 1.2, 1.5, 2.5, etc., and is more suitable for engineering scenarios that require fine-grained fitting.
[0067] Option 3: r is a constant and a real number greater than 0 and less than 1, representing the wear factor. This setting is used to describe the situation where stress impacts reduce or suppress wear, and is preferably 0.5, meaning that wear is calculated as 0.5 times during the impact period.
[0068] In this embodiment, r1 is preferably taken from option 1 or option 2 and is greater than 1 to reflect the wear multiplication effect caused by unidirectional collisions; r2 is taken from option 3 and is between 0 and 1 to reflect the wear halving or suppression effect caused by reverse collisions. Through this bidirectional factor configuration, both aggravated and reduced wear responses can be covered within a unified framework.
[0069] In this embodiment, "stress direction is consistent with wear force direction" indicates that the main stress direction generated during transient impact of a collision event is in the same direction as the main force direction of long-term hinge wear, thus leading to an increase in contact pressure and frictional work input; "stress direction is opposite to wear force direction" indicates that the main stress direction generated by the collision event is opposite to or has a canceling effect on the main wear direction, thus resulting in a reduced wear contribution. The specific determination method can be based on the sign relationship between the load direction, hinge constraint force direction, door movement direction, and friction tangential direction measured by sensors, or it can be based on the phase relationship or characteristic direction of strain / acceleration signals. However, this embodiment does not limit the specific determination algorithm; the key is to map the direction classification results to different wear-affecting factors.
[0070] In one embodiment of the present invention, the wear factor for stress collisions and wear forces in the same direction is set to r1=2, indicating that wear is calculated at twice the normal rate within the collision duration window; simultaneously, the wear factor for stress collisions and wear forces in opposite directions is set to r2=0.5, indicating that wear is calculated at 0.5 times the normal rate within the collision duration window. Through these settings, in this embodiment, when a stress collision event is detected (or triggered by a random event time function matrix), r1 or r2 is selected based on the direction determination result, and within the continuous time unit corresponding to the duration d determined in step S2, the wear increment or wear depth is recursively modulated to achieve differentiated characterization of the influence of bidirectional stress collisions.
[0071] S4. Establish the wear process function. Based on whether the current time point belongs to the collision event occurrence time and its duration of influence in the random event time function matrix, dynamically adjust the mean function of the IG process to reflect the nonlinear impact of the collision event.
[0072] In step S4, a wear process function K is established. Based on whether the current time point falls within the occurrence time of a collision event in the random event time function matrix T and its duration of influence, the mean function Y(t) of the wear process (IG process) of the clearance hinge is dynamically adjusted to reflect the nonlinear impact of the collision event. The hinge wear process is not only related to normal loads and operating conditions but is also significantly affected by stress-induced collision events. Therefore, incorporating a dynamic adjustment function for collision events into the model is essential. The core of this step is to define a wear process function K and adjust the mean function of the IG process based on whether the current time point is within the influence range of a collision event, thereby more accurately reflecting the nonlinear wear changes during actual use.
[0073] The wear process function K represents the wear increment or wear depth of the hinge at a given time point t. Its variation depends not only on the wear process Y(t) of the foundation but also on the modulation effect of stress-induced collision events. Specifically, the expression for K can dynamically adjust the mean function Y(t) according to the occurrence time and duration of the collision event, thereby reflecting the nonlinear effect of the collision event on wear.
[0074] In this embodiment of the invention, two options are provided for selection: Option 1: .
[0075] In this scenario, the wear process will increase by a factor of r when a collision event occurs. That is, the wear will double during the window of impact from the collision; while during periods without collision events, the wear will remain constant compared to the baseline wear process Y(t).
[0076] In one embodiment of the present invention, it is assumed that Y(t) is an IG process, r=2, d=1, T=[1]*[17,47,81,131,169], and the time unit is days. Then the calculation of the hinge simulation process on the 17th, 47th, 81st, 131st, and 169th days will double, while the calculation value of the IG process will remain unchanged on the others.
[0077] Option 2: .
[0078] In this scheme, two distinct impact intervals, T1 and T2, are defined for each collision event. Different wear factors, r1 and r2, are used for different types of collision events. This approach is suitable for multi-collision scenarios where different stress-related collisions may have varying degrees of impact; for example, a stronger impact may lead to a higher wear factor, while a weaker impact may result in less wear.
[0079] In one embodiment of the present invention, assuming Y(t) is an IG process, r1=2, r2=0.5, d=1, T1=[1]*[17,47,81,131,169], T2=[1]*[31,65,102,154,181], and the time unit is days. Then the calculation amount of the hinge simulation process on days 17, 47, 81, 131, and 169 will double, the calculation amount of the hinge simulation process on days 31, 65, 102, 154, and 181 will be halved, and the calculation values of the IG process will remain unchanged for the others.
[0080] This invention also provides a device for dynamically simulating hinge wear depth based on random events, such as... Figure 2 As shown, the device includes: The first module 100 is used to construct a random event time function matrix and generate the occurrence time of periodic collision events based on the design life of the aircraft hinge and a predefined time unit. The second module 200 is used to determine the duration of the impact of the collision, and calculates the duration of the impact of the collision event on the wear process based on the minimum or maximum value of the time difference between adjacent collision events in the random event time function matrix. The third module 300 is used to set bidirectional wear factors, which respectively characterize the doubling or halving effect of collision events with the same and opposite stress directions on the wear depth; The fourth module 400 is used to establish the wear process function. Based on whether the current time point belongs to the time of occurrence of the collision event in the random event time function matrix and its duration of influence, the mean function of the IG process is dynamically adjusted to reflect the nonlinear effect of the collision event.
[0081] To implement the methods of the above embodiments, the present invention also provides an electronic device, which includes a memory and a processor; wherein the processor reads executable program code stored in the memory to run a program corresponding to the executable program code, so as to implement the various steps of the methods described above.
[0082] To implement the above embodiments, this application also proposes a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the method described in the foregoing embodiments.
[0083] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.
[0084] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.
[0085] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.
Claims
1. A dynamic simulation method for hinge wear depth based on random events, characterized in that, include: S1, construct the random event time function matrix, and generate the occurrence time of periodic collision events based on the design life of the aircraft hinge and the predefined time unit; S2, determine the duration of the collision impact by calculating the duration of the collision event's continuous impact on the wear process based on the minimum or maximum value of the time difference between adjacent collision events in the random event time function matrix; S3 sets a bidirectional wear factor to characterize the doubling or halving effect of collision events with the same and opposite stress directions on the wear depth, respectively. S4. Establish the wear process function. Based on whether the current time point belongs to the collision event occurrence time and its duration of influence in the random event time function matrix, dynamically adjust the mean function of the IG process to reflect the nonlinear impact of the collision event.
2. The method according to claim 1, characterized in that, The parameters in the random event time function matrix T include the number of periods p, which is calculated using the following formula: The random event time function matrix T is expressed as: T=[1,2,...,p]*[12,17,23,24,35,45,57,61,76,87,91,94,98,101,112,135,141,154,165,172,187,192]; Or, T=[1,2,...,p]*[2,4,7,9]; Or, T=[1,2,...,p]*[17,31,47,65,81,102,131,154,169,181]; Alternatively, T = [1,2,...,p] * [31,65,102,154,181]; Or, T=[1,2,...,p]*[17,47,81,131,169].
3. The method according to claim 2, characterized in that, The duration d of the collision effect is expressed as: Constant 1; Or, a positive integer greater than 1; Alternatively, depending on the values in matrix T, d equals 50% of the smallest nearest neighbor difference, rounded down; Alternatively, depending on the values in the T matrix, d equals 50% of the smallest nearest neighbor difference, rounded up. Alternatively, depending on the values in the T matrix, d equals 50% of the largest nearest neighbor difference, rounded down. Alternatively, depending on the values in the T matrix, d equals 50% of the largest nearest neighbor difference, rounded up.
4. The method according to claim 3, characterized in that, The wear process function is expressed as: or in, For the wear process function, For wear factor, The wear factor is influenced by stress impacts and wear forces acting in the same direction. The wear factor is the effect of stress collisions and wear forces acting in opposite directions.
5. A dynamic simulation device for hinge wear depth based on random events, characterized in that, include: The first module is used to construct a random event time function matrix and generate the occurrence time of periodic collision events based on the design life of the aircraft hinge and a predefined time unit. The second module is used to determine the duration of the impact of the collision. It calculates the duration of the impact of the collision event on the wear process based on the minimum or maximum value of the time difference between adjacent collision events in the random event time function matrix. The third module is used to set bidirectional wear factors, which respectively characterize the doubling or halving effect of collision events with the same and opposite stress directions on the wear depth; The fourth module is used to establish the wear process function. Based on whether the current time point belongs to the time of occurrence of the collision event in the random event time function matrix and its duration of influence, the mean function of the IG process is dynamically adjusted to reflect the nonlinear impact of the collision event.
6. An electronic device, characterized in that, Including processor and memory; The processor reads executable program code stored in the memory to run a program corresponding to the executable program code, so as to implement the method as described in any one of claims 1-4.
7. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the method as described in any one of claims 1-4.