Multi-stage incremental bolt tensile force loading control method and system

Abstract

The invention discloses a multi-stage incremental bolt tensile force loading control method and system, and the method comprises the steps: collecting an initial strain value of a bolt in real time through a high-precision strain sensor, and calculating an initial tensile force based on the elastic modulus of a material; after each stage of loading, the elongation of the bolt is measured through a laser displacement sensor, and whether the next stage of loading is triggered or not is determined according to a preset threshold value; if the elongation still does not reach the standard after three times of continuous loading, a stress redistribution algorithm is started, and a load transmission path is optimized through a finite element analysis module; meanwhile, a Boltzmann function is combined to predict a strain value; in the calculation of the final drawing force, a Gaussian error function is adopted, and the final drawing force is accurately controlled in combination with the elongation and the measurement standard deviation. The method has the advantages of being high in precision, high in adaptability, perfect in multi-stage loading strategy, high in multi-source data fusion capacity and the like, is suitable for bolt loading control under various complex working conditions, and has wide application prospects and good technical effects.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of industrial manufacturing and mechanical assembly, and particularly relates to a multi-stage incremental bolt tensile force loading control method and system. BACKGROUND

[0002] In modern engineering structures, bolt connections are widely used in key fields such as bridges, buildings, ships, etc., and their performance directly affects the safety and durability of the entire structure. Bolt tensile force control is an important means to ensure its reliability and stability under complex stress environment. Traditional bolt tensile force loading methods usually rely on empirical formulas or static calculation models, lacking dynamic response capability to complex factors such as material nonlinear behavior, temperature changes, creep effects, etc., resulting in insufficient loading accuracy and difficulty in meeting the needs of high-precision engineering applications.

[0003] In recent years, with the continuous development of sensor technology and computational methods, bolt loading methods based on real-time monitoring and feedback control have gradually attracted attention. For example, some studies have proposed dynamic loading control methods based on strain sensors, which collect real-time strain data of the bolt, calculate the tensile force based on the elastic modulus, and adjust the loading strategy during the loading process according to the strain change. However, these methods mostly only consider the linear elastic stage of the material, ignoring the nonlinear behavior of the material under high stress or long-time loading, such as plastic deformation, fatigue accumulation, and creep effect, resulting in deviations between the loading results and the actual working conditions.

[0004] In addition, the existing technology rarely involves multi-stage incremental loading strategies, i.e., using different force increments and decay coefficients in different loading stages to adapt to the response characteristics of the material under different stress states. At the same time, existing methods have deficiencies in handling multi-source data fusion, noise suppression, and predictive modeling, making it difficult to achieve high-precision and high-reliability bolt loading control.

[0005] Therefore, there is an urgent need for a bolt tensile force loading control method that can comprehensively consider material nonlinear behavior, temperature effects, creep effects, multi-stage loading strategies, and multi-source data fusion to improve loading accuracy and system stability, meeting the needs of modern engineering for high-precision bolt connections. SUMMARY

[0006] In view of the defects in the prior art, the present application provides a multi-stage incremental bolt tensile force loading control method, comprising the following steps: Step S101, real-time acquisition of the initial strain value of the bolt , and calculating the initial tensile force based on the material elastic modulus E ; Step S103, setting the target tensile force increment ΔF, and based on the fatigue limit σ fConstructing dynamic adjustment function ΔF adjusted ; Step S105, multi-stage loading is performed based on the first loading model using a recursive formula, wherein the first loading model is expressed by the following formula: where λ is the attenuation coefficient, t n represents the time point at the n-th stage of recording, ε n-1 is the real-time strain value at the n-th stage of loading, ε(t) represents the real-time strain value at time t, and the integral term is used to suppress the accumulation of nonlinear deformation; Step S107, after each stage of loading, the bolt elongation ΔL is measured by a laser displacement sensor, and if ΔL does not reach the preset threshold L th , the next stage of loading is triggered; Step S109, when ΔL meets the standard, the loading is terminated and the final tensile force F final is output.

[0007] In the step S101, the initial strain value of the bolt is collected in real time by a high-precision strain sensor .

[0008] In the step S103, the dynamic adjustment function is calculated by the following formula: where ΔF=100kN, σ max is the maximum stress in the current loading cycle, σ avg is the historical average stress, and σ f is the fatigue limit.

[0009] In the step S107, the preset threshold L th is determined by the following formula: where α i is the i-th stage elongation weight coefficient, β is the cycle correction factor, γ is the material creep coefficient, N cycle is the current loading cycle number, and ΔL i represents the actual measured bolt elongation during the i-th stage of loading.

[0010] In the step S107, if ΔL still does not meet the standard after 3 consecutive loadings, stress redistribution is started.

[0011] The stress redistribution includes calculating the stress field distribution of the bolt surrounding structure by a finite element analysis module and adjusting the loading point position to optimize the load transfer path.

[0012] The finite element analysis module uses an adaptive mesh division strategy, and the mesh density is adjusted according to the local stress gradient Dynamic adjustment, wherein x, y, z are spatial coordinates.

[0013] Wherein, the step S107 further comprises: using Kalman filter to strain data ε n Noise reduction processing is carried out to obtain the optimal estimation value , wherein K is the gain coefficient, ε pred The strain prediction value based on the Boltzmann function.

[0014] Wherein, the following formula is used to calculate ε pred : , ε ∞ Saturation strain, k is the temperature sensitivity coefficient, T is the real-time temperature, and T0 is the reference temperature.

[0015] The application also provides a multi-stage incremental bolt tension force loading control system, comprising: High-precision strain sensor module, for real-time acquisition ; Dynamic force adjustment module, for calculating ΔF adjusted ; Finite element analysis module, for executing stress redistribution algorithm; Kalman filter module, for outputting ; Control terminal, for iteratively executing the steps of the above method and outputting F final .

[0016] Compared with the prior art, the application has the following advantages: High-precision loading control. By real-time acquisition of strain data of the bolt, combined with the elastic modulus and cross-sectional area of the material, the initial tension force is calculated, and the elongation is measured by the laser displacement sensor after each loading to ensure accurate control of the loading force.

[0017] Dynamic adjustment of force increment. Based on the fatigue limit of the bolt material and the current loading state, a dynamic adjustment function is constructed to adjust the force increment of each loading in real time, avoid exceeding the fatigue limit of the material, and prolong the service life of the bolt.

[0018] Inhibit the accumulation of nonlinear deformation. Through the integral term in the recursive formula, the accumulation of nonlinear deformation of the bolt during the loading process is inhibited to ensure the stability of the loading process.

[0019] Multi-stage loading strategy. A multi-stage incremental loading strategy is adopted to dynamically adjust the loading force according to the elongation of the bolt and the historical loading data to ensure the response characteristics of the bolt in different loading stages.

[0020] Multi-source data fusion. Real-time strain data is denoised by a Kalman filter, and strain values are predicted using a Boltzmann function to improve the accuracy and reliability of the strain data.

[0021] Stress redistribution optimization. During loading, if the elongation of the bolt does not reach the preset threshold, a stress redistribution algorithm is started, the stress field distribution of the surrounding structure of the bolt is calculated by the finite element analysis module, and the loading point position is adjusted to optimize the load transmission path and improve the loading efficiency.

[0022] Gaussian error function application. In the calculation of the final tensile force, a Gaussian error function is used in combination with elongation and measurement standard deviation to achieve precise control of the final tensile force.

[0023] System adaptability enhancement. By introducing adaptive meshing strategies and temperature sensitivity coefficients, the robustness and adaptability of the system are improved, enabling it to meet the bolt loading requirements under different working conditions.

[0024] Multi-level weight adjustment. In the calculation of the elongation threshold, multi-level weight coefficients are introduced to ensure that the influence of elongation at different loading stages on the final tensile force is reasonably evaluated. BRIEF DESCRIPTION OF DRAWINGS

[0025] The above and other objects, features and advantages of the exemplary embodiments of the present disclosure will be more apparent from the following detailed description taken in conjunction with the accompanying drawings, in which several embodiments of the present disclosure are shown by way of example, and wherein like or corresponding elements show like or corresponding parts, in which: Figure 1 is a flow chart showing a multi-stage incremental bolt tensile force loading control method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0026] In order to make the objects, technical solutions and advantages of the present invention clearer, the present invention will be described in further detail below with reference to the drawings. Obviously, the described embodiments are only some of the embodiments of the present invention, but not all the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present invention.

[0027] The terms used in the embodiments of the present invention are only for the purpose of describing specific embodiments, and are not intended to limit the present invention. The singular forms "a", "an" and "the" used in the embodiments of the present invention and the appended claims are also intended to include the plural forms, unless the context clearly indicates otherwise. "Multiple" generally includes at least two.

[0028] It should be understood that, although the terms first, second, third, etc. can be employed in describing the … in the embodiments of the present application, these … should not be limited to these terms. These terms are only used to distinguish one … from another. For example, without departing from the scope of the embodiments of the present application, the first … can also be referred to as the second …, and similarly, the second … can also be referred to as the first ….

[0029] It should be understood that the term "and / or" used herein only describes the association relationship of the associated objects, which means that there can be three relationships, for example, A and / or B can mean that A exists alone, A and B exist together, and B exists alone. In addition, the character " / " herein generally represents that the associated objects before and after are in an "or" relationship.

[0030] Depending on the context, the word "if" as used herein can be interpreted as "when" or "upon" or "in response to determining" or "in response to detecting". Similarly, depending on the context, the phrase "if determined" or "if detecting (a stated condition or event)" can be interpreted as "when determined" or "in response to determining" or "when detecting (a stated condition or event)" or "in response to detecting (a stated condition or event)".

[0031] It should also be noted that the terms "comprising", "including", or any other variant thereof are intended to cover non-exclusive inclusion, so that a product or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such product or device. Without more limitations, the element defined by the sentence "comprising a …" does not exclude the presence of another identical element in the product or device comprising the element.

[0032] The optional embodiments of the present application will be described in detail below with reference to the accompanying drawings.

[0033] Embodiment one, As Figure 1 shown, the present application discloses a multi-stage incremental bolt tensile force loading control method, comprising the following steps: Step S101, real-time acquisition of initial strain value of bolt , and calculation of initial tensile force based on material elastic modulus E ; Step S103, setting target tensile force increment ΔF, and based on bolt material fatigue limit σ f , constructing dynamic adjustment function ΔF adjusted ; Step S105, multi-stage loading based on recursive formula using first loading model, wherein the first loading model is represented by the following formula: where λ is the attenuation coefficient, t n represents the time point of the n-th level record, ε n-1 is the real-time strain value at the n-th level loading, ε(t) represents the real-time strain value at time t, and the integral term is used to suppress the accumulation of nonlinear deformation; Step S107, after each level of loading, the bolt elongation ΔL is measured by a laser displacement sensor, if ΔL does not reach the preset threshold L th , the next level of loading is triggered; Step S109, when ΔL meets the standard, the loading is terminated and the final tensile force F final .

[0034] Example two, The application provides a multistage incremental bolt tensile force loading control method, which comprises the following steps: Step S101, real-time acquisition of the initial strain value of the bolt , and calculation of the initial tensile force based on the material elastic modulus E ; Step S103, setting of a target tensile force increment ΔF, and construction of a dynamic adjustment function ΔF f based on the bolt material fatigue limit σ adjusted ; Step S105, multistage loading based on a first loading model by using a recursive formula, wherein the first loading model is represented by the following formula: where λ is the attenuation coefficient, t n represents the time point of the n-th level record, ε n-1 is the real-time strain value at the n-th level loading, ε(t) represents the real-time strain value at time t, and the integral term is used to suppress the accumulation of nonlinear deformation; Step S107, after each level of loading, the bolt elongation ΔL is measured by a laser displacement sensor, if ΔL does not reach the preset threshold L th , the next level of loading is triggered; Step S109, when ΔL meets the standard, the loading is terminated and the final tensile force F final .

[0035] In the step S101, the initial strain value of the bolt is collected in real time by using a high-precision strain sensor .

[0036] The initial tensile force is calculated by the following formula , wherein A is the cross-sectional area of the bolt.

[0037] In the step S103, the dynamic adjustment function is calculated by the following formula: , wherein ΔF=100kN, σmax σ is the maximum stress during the current loading cycle. avg For historical average stress, σ f This represents the fatigue limit.

[0038] The purpose of this function is to adjust the target tensile force increment ΔF based on the fatigue limit of the bolt material and the difference between the maximum stress and the historical average stress during the current loading cycle. Specifically, the output range of the tanh function (hyperbolic tangent function) is between -1 and 1, but here it varies due to σ. f / (σ max -σ avg The value of σ is usually positive, so the output range of the tanh function is actually between 0 and 1. This means that when σ... max Approaching σ avg At that time, tanh(σ) f / (σ max -σ avg The value of )) will be close to 0, thus making ΔF adjusted Approaching 0; while when σ max Much greater than σ avg At that time, tanh(σ) f / (σ max -σ avg The value of )) will be close to 1, thus making ΔF adjusted Approximately ΔF. This adjustment mechanism helps to maximize the load-bearing capacity of the bolt while ensuring that the bolt does not fail due to fatigue.

[0039] Furthermore, for the tensile fatigue problem of bolts, the bolt stress amplitude needs to be satisfied. The stress amplitude must be less than the bolt's tensile fatigue limit (no tensile fatigue occurs). This aligns with the objective of the dynamic adjustment function constructed in this invention, which controls the bolt stress amplitude by adjusting the target tensile force increment ΔF to ensure it does not exceed the bolt's tensile fatigue limit.

[0040] In one embodiment, the tanh function in step S103 is replaced by the sigmoid function. τ is a stress transition interval constant.

[0041] In step S105, the attenuation coefficient λ is obtained through... Dynamic calculation is performed, where κ is the strain rate sensitivity factor, μ is the stress offset correction coefficient, and the integral term is used to evaluate strain rate fluctuations.

[0042] Temperature sensitivity coefficient k through correction, ζ is the base coefficient, and ζ is the temperature correction factor.

[0043] The recursive formula in the present application consists of the response of the previous stage plus an adjusted increment multiplied by an exponential decay term. The exponential part of the exponential decay term contains λ and the integral term, which gradually reduces the influence on the system response as the strain changes accumulate during loading, thereby preventing excessive accumulation of nonlinear deformation.

[0044] In the present application, the recursive formula updates the system response step by step, allowing each stage of loading to be adjusted based on the state of the previous stage, thereby achieving effective control of the multi-stage loading process.

[0045] From the formula structure of the decay coefficient, λ consists of two parts: the first part is κ multiplied by the square integral of strain rate, i.e., κ × ∫(dε / dt)²dt. This part reflects the influence of strain rate fluctuations on energy dissipation during deformation. The strain rate sensitivity factor κ is an important parameter that describes the change in mechanical behavior of the material at different strain rates. Therefore, the value of κ directly affects the size of the integral term, and in turn affects the calculation result of the decay coefficient λ.

[0046] The second part is μ multiplied by the absolute value of the difference between the maximum stress and the yield stress, i.e., μ × |σ_max-σ_f|. This part reflects the influence of stress deviation on energy dissipation during deformation. The stress deviation correction coefficient μ is used to adjust the energy dissipation characteristics of the material under different stress states. Therefore, the value of μ needs to be adjusted according to the specific performance of the material to ensure the accuracy of the calculation result.

[0047] The integral term ∫(dε / dt)²dt is used to evaluate the influence of strain rate fluctuations on energy dissipation, and needs to consider the behavior change of the material at different temperatures.

[0048] wherein the preset threshold L th The following formula is used to determine it: wherein α i is the i-th level elongation weight coefficient, β is the cycle correction factor, γ is the material creep coefficient, N cycle is the current loading cycle number, ΔL i represents the actual measured bolt elongation during the i-th level loading process.

[0049] The introduction of this formula makes the pre-tightening force control more intelligent, allowing dynamic adjustment of the loading strategy according to the creep characteristics of the material, avoiding the problem of insufficient or excessive loading of the pre-tightening force due to material fatigue or creep. At the same time, the use of laser displacement sensors ensures the non-contact and high precision of the measurement process, especially suitable for bolted connections that are difficult to access or in harsh environments.

[0050] wherein the cycle correction factor β is determined by dynamic adjustment, is the initial value, τ β is the cycle attenuation time constant. It describes the change of β with the cycle number N cycle , and its change trend is gradually approaching a stable value, rather than immediately reaching the value. Specifically, with the increase of the cycle number, the exponential term exp(-N cycle / τ β ) gradually decreases, so the value of β gradually approaches a stable value (i.e. ) from the initial value , but it does not immediately equal .

[0051] If ΔL still does not meet the standard after being loaded for three consecutive times, stress redistribution is started.

[0052] The stress redistribution includes calculating the stress field distribution of the bolt peripheral structure through a finite element analysis module, and adjusting the loading point position to optimize the load transmission path.

[0053] The finite element analysis module adopts an adaptive mesh division strategy, and the mesh density is dynamically adjusted according to the local stress gradient , where x, y, and z are spatial coordinates.

[0054] The core of the stress redistribution algorithm is to use finite element analysis (FEM) technology to simulate the stress field of the bolt connection area with high precision. By establishing a three-dimensional model, the stress distribution of the material around the bolt hole can be analyzed in detail, including contact stress, shear stress, and tensile stress. This analysis helps to identify stress concentration areas and determine which parts have weak links in the load transmission process.

[0055] In the present invention, first, the structure needs to be meshed to ensure that the model can accurately reflect the interaction between the bolt and the plate. For example, in a high-strength bolted joint, a pre-tightening force is usually applied first to put the bolt in an initial stress state, and then external loads are gradually applied to observe the stress changes of the bolt and the connecting plate. In this way, the stress response of the bolt under different load conditions can be simulated, and the position and number of loading points can be optimized to achieve more uniform load distribution.

[0056] In this embodiment, the adaptive mesh division process includes the following steps: Initial meshing. First, a coarse mesh is used for preliminary analysis to quickly obtain an approximate solution.

[0057] Error Estimation: Based on the current mesh solution, error estimates are computed. Common error estimation methods include residual-based methods, Zienkiewicz-Zhu error estimation, etc.

[0058] Mesh Refinement: Based on the error estimates, determine areas that need refinement or coarsening. For example, if a certain element has a large error, refine the mesh for that element; if a certain element has a small error, coarsen the mesh appropriately.

[0059] Mesh Redivision: Regenerate the mesh using specific redivision algorithms (such as quadtree or triangulation techniques) to adapt to the new error distribution.

[0060] Iterative Loop: Repeat the above steps until the error reaches the preset threshold or reaches the user-defined number of solutions.

[0061] The advantage of adaptive meshing is that it can automatically adjust the mesh density according to actual needs, thereby reducing unnecessary consumption of computing resources while ensuring calculation accuracy.

[0062] After step S107, it further includes: using a Kalman filter to process the real-time collected strain data ε n to obtain the optimal estimated value , where K is the gain coefficient, ε pred is the strain prediction value based on the Boltzmann function.

[0063] , where the gain coefficient K is updated as follows: , where P pred is the prediction covariance matrix, R is the measurement noise matrix, and , Φ is the state transition matrix, P prev is the covariance of the previous time, and Q is the process noise matrix.

[0064] , where the following formula is used to calculate ε pred : , ε ∞ is the saturated strain, k is the temperature sensitivity coefficient, T is the real-time temperature, and T0 is the reference temperature.

[0065] The core idea of Kalman filtering is to estimate the state of the system by combining the system model and the observation data. It is done through two main steps: prediction and update.

[0066] Prediction: Based on the state estimation of the previous time and the system model, predict the state at the current time.

[0067] Update: Combine the observation value at the current time to correct the prediction value and obtain a more accurate estimated value.

[0068] In the embodiments of the present application, the implementation steps of Kalman filtering are as follows: Initialization, set the initial state estimation value and error covariance.

[0069] Prediction, according to the system model and the estimation value at the last time, predict the state at the current time.

[0070] Update, combine the observation value at the current time, calculate the Kalman gain, and update the state estimation value.

[0071] Iteration, repeat the above steps until the optimal estimation value is obtained.

[0072] wherein, step S109 specifically comprises: when ΔL meets the standard, terminating the loading and outputting the final stretching force , wherein erf is the Gaussian error function, and σ is the elongation measurement standard deviation.

[0073] The formula is used to calculate the stretching force adjustment value corresponding to the deviation between the bolt elongation ΔL and the preset threshold L th under certain conditions. Wherein, σ is the standard deviation of elongation measurement, which is used to measure the uncertainty of measurement. When ΔL reaches or exceeds L th , the value of erf function will tend to 1, so as to maximize the contribution of ΔF adjusted to the final stretching force F final ; on the contrary, if ΔL is less than L th , the value of erf will tend to 0, so as to limit the further increase of the stretching force.

[0074] wherein, erf represents the Gaussian error function, which is defined as: .

[0075] wherein, the input parameter of the Gaussian error function erf is calculated by , wherein w i is the credibility weight of the i-th level elongation, and σ is the measurement standard deviation of the i-th level elongation.

[0076] The formula is used to calculate the input parameter of the Gaussian error function erf, which is used to determine the value of the final stretching force F final in the subsequent steps. By introducing the weight w i , the influence of the elongation of different levels of loading on the final stretching force can be more accurately evaluated, so as to improve the precision and reliability of the loading control method.

[0077] Embodiment three, The present application also provides a multi-level incremental bolt stretching force loading control system, comprising: a high-precision strain sensor module for real-time acquisition ; Dynamic force adjustment module for calculating ΔF adjusted ; Finite element analysis module for executing stress redistribution algorithm Kalman filter module for outputting ; Control terminal for iteratively executing steps of the above method and outputting F final .

[0078] High-precision strain sensor module typically works based on the principle of resistance strain gauge. When an object is subjected to external force, its surface will undergo slight deformation, which will cause the resistance value of the strain gauge attached to the object's surface to change. By measuring the change in resistance, the strain of the object can be calculated. The specific process is as follows: Strain gauge installation. Strain gauges are usually made of metal foil, with good flexibility and conductivity. They are pasted on the surface of the measured object to capture the slight deformation caused by external force.

[0079] Signal conversion. When the object deforms, the resistance value of the strain gauge changes, which is amplified and converted by the Wheatstone bridge circuit to generate a voltage signal proportional to the strain.

[0080] Data acquisition. High-precision strain sensor module has built-in high-precision A / D converter to convert analog voltage signal to digital signal for further processing and storage.

[0081] Communication and transmission. The collected digital signal can be transmitted to the host computer software through RS485, CAN or other communication protocols for real-time monitoring and analysis.

[0082] Performance characteristics of high-precision strain sensor module: High precision. High-precision A / D converter and advanced signal processing technology are used to ensure the accuracy of measurement results. For example, some modules have a sampling resolution of 24 bits, capable of capturing small strain changes.

[0083] Real-time. The module has high-speed sampling capability, capable of collecting a large number of data points in a short time, meeting the needs of real-time monitoring.

[0084] Anti-interference ability. Through four-wire power supply and optical coupling isolation technology, the anti-interference ability of the system is improved, ensuring stable operation in complex environments.

[0085] Multifunctional input. Supports multiple types of signal input, including analog voltage, current signal, etc., suitable for different types of sensors.

[0086] Easy integration. Provides standard interfaces and communication protocols for easy integration with other industrial automation systems, improving system compatibility and scalability.

[0087] The system of the present invention is a highly integrated automated control system designed to achieve precise control over bolt tension, ensuring stability and reliability under complex working conditions. The system consists of multiple functional modules connected through standardized interfaces and communication protocols, forming a closed-loop control system capable of real-time monitoring, adjustment, and optimization of the bolt loading process.

[0088] The high-precision strain sensor module is responsible for real-time acquisition of bolt strain data, using high-precision strain sensors such as resistance strain gauges, fiber optic grating sensors, etc. to obtain the strain values of the bolt at different loading stages . These data are the basis for subsequent calculations and controls, ensuring real-time and accuracy of the system.

[0089] The dynamic force adjustment module is based on the fatigue limit of the bolt material and the current loading state, constructing a dynamic adjustment function ΔF adjusted to calculate the force increment for each load. This module adjusts the force increment in real time to ensure that the bolt does not exceed its fatigue limit during the loading process, thereby extending its service life.

[0090] The finite element analysis module is used to perform stress redistribution algorithms, calculating the stress field distribution of the bolt's surrounding structure using finite element analysis software and adjusting the loading point position based on the calculation results to optimize the load transfer path. The output results of this module directly affect the loading strategy of the system, ensuring the response characteristics of the bolt at different loading stages.

[0091] The Kalman filter module performs noise reduction on the real-time collected strain data to obtain the optimal estimate value , where is the strain prediction value based on the Boltzmann function. The output results of this module are used to improve the accuracy and reliability of the strain data, ensuring the accuracy of subsequent calculations.

[0092] The control terminal serves as the control center of the system, responsible for iteratively executing the calculation and control steps of the above modules and outputting the final tension force. This module ensures that the system can dynamically adjust the control strategy according to the loading state of the bolt through real-time feedback mechanisms, achieving high-precision loading control.

[0093] The real-time strain data collected by the high-precision strain sensor module is transmitted to the dynamic force adjustment module through digital signal transmission protocols such as CAN bus or Ethernet. The dynamic force adjustment module calculates the current force increment based on the real-time strain data And the results are fed back to the control terminal through the communication interface. The force increment output by the dynamic force adjustment module is transmitted to the finite element analysis module through the communication interface. The finite element analysis module calculates the stress field distribution of the bolt peripheral structure and adjusts the loading point position to optimize the load transmission path. The stress field distribution of the bolt peripheral structure is calculated, and the loading point position is adjusted to optimize the load transmission path.

[0094] The stress distribution results output by the finite element analysis module are transmitted to the control terminal through the communication interface. The control terminal adjusts the loading strategy according to the stress distribution results to ensure the response characteristics of the bolt in different loading stages.

[0095] The optimal strain estimation value output by the Kalman filter module is transmitted to the control terminal through the communication interface. The control terminal adjusts the loading strategy according to The tensile force of the bolt is calculated, and the loading strategy is adjusted to ensure the high precision and stability of the system.

[0096] The final tensile force output by the control terminal is transmitted to the high-precision strain sensor module through the communication interface. The high-precision strain sensor module calculates the stress field distribution of the bolt peripheral structure according to F final The loading strategy is adjusted to ensure the response characteristics of the bolt in different loading stages.

[0097] The system of the present application has the following advantages: High-precision loading control. By real-time acquisition and processing of strain data, the accuracy of bolt tensile force control is ensured.

[0098] Dynamic adjustment of force increment. Based on the material fatigue limit and the current loading state, the force increment is dynamically adjusted to ensure the service life of the bolt.

[0099] Multi-stage loading strategy. Through the multi-stage loading strategy, the response characteristics of the bolt in different loading stages are ensured.

[0100] Multi-source data fusion. Through the Kalman filter and the Boltzmann function, the accuracy and reliability of the strain data are improved.

[0101] Modular design. The modules are connected through standardized interfaces and communication protocols to ensure the scalability and maintainability of the system.

[0102] Example four, The present disclosure provides a non-volatile computer storage medium, which stores computer executable instructions. The computer executable instructions can execute the method steps of the above embodiments.

[0103] Note that the computer readable medium described above can be a computer readable signal medium or a computer readable storage medium or any combination thereof. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus or device, or any suitable combination of the foregoing. More specific examples of the computer readable storage medium can include, but are not limited to, an electrical connection having 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. In the disclosure, the computer readable storage medium can be any tangible medium that contains or stores a program used by or in connection with an instruction execution system, apparatus or device. In the disclosure, the computer readable signal medium can include a computer readable program code propagated on or through a computer readable medium, in baseband or as part of a carrier wave. The computer readable signal medium can take a variety of forms, including but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. The computer readable signal medium can be any computer readable medium that can be used to carry or store computer readable program code for use by or in connection with an instruction execution system, apparatus or device. The program code contained on the computer readable medium can be transmitted or received over any suitable medium, including but not limited to, wire, cable, fiber optic, RF (radio frequency), or any suitable combination of the foregoing.

[0104] The computer readable medium described above can be included in the electronic device described above; alternatively, the computer readable medium can exist as a separate entity in which the electronic device is enclosed.

[0105] Computer program code for carrying out operations of the disclosure can be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C++ or the like, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code can execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection can be made to an external computer (for example, through the Internet using an Internet Service Provider).

[0106] The computer program product of the present disclosure can be a computer program embodied on a non-transitory computer readable medium. When the program runs on a computer, the flowchart and / or block diagram in the flowchart and / or block diagram can be implemented.

[0107] The units described in the embodiments of the present disclosure can be implemented by software or by hardware. In some cases, the name of the unit does not constitute a limitation on the unit itself.

[0108] The above describes the preferred embodiments of the present disclosure, which aims to make the spirit of the present disclosure clearer and easier to understand, and is not intended to limit the present disclosure. Any modification, replacement, improvement made within the spirit and principle of the present disclosure shall be included in the protection scope of the appended claims of the present disclosure.

Claims

1. A multi-stage incremental bolt tension force loading control method, characterized by, The method comprises the following steps: Step S101, collect the initial strain value of the bolt in real time And calculate the initial tension force based on the material elastic modulus E ; Step S103, set the target tensile force increment ΔF, and based on the bolt material fatigue limit σ f Constructing the dynamic adjustment function ΔF adjusted ; Step S105, multi-stage loading is performed based on the first loading model using a recursive formula, wherein the first loading model is expressed by the following formula: where λ is an attenuation coefficient, t n denotes a time point at the n-th stage of recording, ε n-1 is a real-time strain value at the n-th stage of loading, ε(t) denotes a real-time strain value at time t, and the integral term is used to suppress the accumulation of nonlinear deformation; Step S107, after loading at each level, the bolt elongation AL is measured by the laser displacement sensor, if AL does not reach the preset threshold L th , the next level of loading is triggered; Step S109, when the ΔL is met, terminate the loading and output the final tensile force F final .

2. The method of claim 1, wherein, The initial strain value of the bolt is collected in real time by using a high-precision strain sensor in the step S101 .

3. The method of claim 1, wherein, The dynamic adjustment function in the step S103 is calculated by the following formula: where ΔF = 100 kN, σ max is the maximum stress in the current loading cycle, σ avg is the historical average stress, σ f is the fatigue limit.

4. The method of claim 1, wherein, The preset threshold L in the step S107 th The determination is made using the following formula: wherein, a i is the i-th level elongation weight coefficient, β is the cycle correction factor, γ is the material creep coefficient, N cycle is the current loading cycle number, ΔL i represents the actual measured bolt elongation during the i-th level loading.

5. The method of claim 1, wherein, The step S107 further comprises: if ΔL is still not up to standard after three times of loading, stress redistribution is started.

6. The method of claim 5, wherein, The stress redistribution comprises calculating the stress field distribution of the bolt peripheral structure by a finite element analysis module, and adjusting the loading point position to optimize the load transmission path.

7. The method of claim 6, wherein, The finite element analysis module adopts an adaptive meshing strategy, and the mesh density is adjusted according to the local stress gradient Dynamic adjustment, wherein x, y, z are spatial coordinates.

8. The method of claim 1, wherein, The step S107 further comprises: using a Kalman filter to process the real-time collected strain data ε n Carrying out noise reduction processing to obtain an optimal estimation value Wherein K is a gain coefficient, ε pred is a strain prediction value based on a Boltzmann function.

9. The method of claim 8, wherein, The ε is calculated by the following formula pred : , ε ∞ is the saturated strain, k is the temperature sensitive coefficient, T is the real-time temperature, and T0 is the reference temperature.

10. A multi-stage incremental bolt tensile force loading control system comprising High-precision strain sensor module for real-time acquisition ; a dynamic force adjustment module for calculating ΔF adjusted ; a finite element analysis module for executing a stress redistribution algorithm; a Kalman filter module for outputting ; A control terminal is configured to iteratively perform the steps of the method of any one of claims 1-9 and output F final .

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