WO2020237800A1 - 一种振动工况下螺栓松弛主要影响参数评定及其松弛缓减方法 - Google Patents

一种振动工况下螺栓松弛主要影响参数评定及其松弛缓减方法 Download PDF

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WO2020237800A1
WO2020237800A1 PCT/CN2019/096264 CN2019096264W WO2020237800A1 WO 2020237800 A1 WO2020237800 A1 WO 2020237800A1 CN 2019096264 W CN2019096264 W CN 2019096264W WO 2020237800 A1 WO2020237800 A1 WO 2020237800A1
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bolt
test
parameters
clamping force
relaxation
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PCT/CN2019/096264
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English (en)
French (fr)
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程强
徐文祥
蔡力钢
刘志峰
杨聪彬
赵永胜
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北京工业大学
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Priority to GB2202617.3A priority Critical patent/GB2601094A/en
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    • GPHYSICS
    • G01MEASURING; TESTING
    • G01MTESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
    • G01M13/00Testing of machine parts
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10Complex mathematical operations
    • G06F17/18Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
    • FMECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F16ENGINEERING ELEMENTS AND UNITS; GENERAL MEASURES FOR PRODUCING AND MAINTAINING EFFECTIVE FUNCTIONING OF MACHINES OR INSTALLATIONS; THERMAL INSULATION IN GENERAL
    • F16BDEVICES FOR FASTENING OR SECURING CONSTRUCTIONAL ELEMENTS OR MACHINE PARTS TOGETHER, e.g. NAILS, BOLTS, CIRCLIPS, CLAMPS, CLIPS OR WEDGES; JOINTS OR JOINTING
    • F16B31/00Screwed connections specially modified in view of tensile load; Break-bolts
    • F16B31/04Screwed connections specially modified in view of tensile load; Break-bolts for maintaining a tensile load
    • FMECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F16ENGINEERING ELEMENTS AND UNITS; GENERAL MEASURES FOR PRODUCING AND MAINTAINING EFFECTIVE FUNCTIONING OF MACHINES OR INSTALLATIONS; THERMAL INSULATION IN GENERAL
    • F16BDEVICES FOR FASTENING OR SECURING CONSTRUCTIONAL ELEMENTS OR MACHINE PARTS TOGETHER, e.g. NAILS, BOLTS, CIRCLIPS, CLAMPS, CLIPS OR WEDGES; JOINTS OR JOINTING
    • F16B5/00Joining sheets or plates, e.g. panels, to one another or to strips or bars parallel to them
    • F16B5/02Joining sheets or plates, e.g. panels, to one another or to strips or bars parallel to them by means of fastening members using screw-thread
    • F16B5/0241Joining sheets or plates, e.g. panels, to one another or to strips or bars parallel to them by means of fastening members using screw-thread with the possibility for the connection to absorb deformation, e.g. thermal or vibrational
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01MTESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
    • G01M7/00Vibration-testing of structures; Shock-testing of structures
    • G01M7/02Vibration-testing by means of a shake table

Definitions

  • the invention relates to a method for evaluating the main influencing parameters of bolt slack under vibration conditions and its slack mitigation method, belonging to the field of mechanical engineering.
  • Bolt is a typical mechanical fastener commonly used in the engineering field. Due to the existence of vibration and alternating load environment during the service process of the connection system, especially when the bolt connection in the rotating mechanism is in a combination of dynamic tension, compression and shear When under load, the bolt connection is easier to loosen, and the bolt pre-tightening force will be loosened, causing the bolt connection structure to fail. Statistics found that the factors affecting the loosening of bolt connections involve many aspects such as mechanical processing methods, assembly processes, mechanical properties of materials and working environment, and their coupling effects aggravate the loosening process of bolts and make the problem more complicated. In the past, most of the experimental studies on bolt relaxation were based on the influence principle of a single factor.
  • the technical problem to be solved by the present invention is to overcome the technical deficiencies that cannot be evaluated for the bolt slack influence parameters under current vibration conditions, and provide a secondary universal rotation combination method to evaluate the main influence parameters of bolt slack, and reduce bolts under vibration conditions through lingo
  • the best combination of the three influencing parameters of relaxation effectively reduces test time and material consumption.
  • the secondary universal rotation combination design and lingo optimization of the present invention include the following steps:
  • the three bolt relaxation influencing parameters are selected as load amplitude, vibration frequency and initial tightening torque.
  • the test in the step (3) uses a fatigue tensile testing machine, and the cycle time is 14.4 ⁇ 10 3 .
  • the present invention provides a method for evaluating the main influencing parameters of bolt relaxation under vibration conditions and its relaxation mitigation method.
  • the main influencing parameters and the proportion of the influence of each factor on the bolt relaxation are obtained, and It also obtains the best combination of numerical values to reduce bolt slack. Realize that within a limited time, through scientific test design and analysis, find the parameter selection that can effectively reduce the bolt relaxation under vibration conditions; solve the problem of traditional technical means, the number of tests, the long time of program exploration, and the large consumption of materials Insufficient technology.
  • Figure 1 is a system block diagram of bolt relaxation test design and analysis.
  • Figure 2 is the bolt relaxation test model diagram under cyclic alternating load.
  • Figure 3 is the residual scatter plot of the bolt clamping force attenuation rate
  • Figure 4 is a graph showing the influence of various influencing parameters on the attenuation rate of bolt clamping force.
  • Figure 5 shows the interactive effect of the initial tightening torque and load amplitude on the attenuation rate of bolt clamping force.
  • Figure 6 is the optimized bolt clamping force change diagram
  • test pieces, methods and equipment used in the present invention are common test pieces, methods and equipment in the technical field.
  • the load amplitude, vibration frequency, and initial tightening torque that affect the bolt clamping force are used as three test factors, and the bolt clamping force attenuation rate is set as the target, and a three-factor five-level secondary universal rotation combination design is made, a total of 20
  • the combination of test values is used to determine the best combination of the three test factors.
  • each test factor is shown in Table 2.
  • the Smacq data acquisition card is used to monitor the clamping force obtained under each set of test parameter combinations in real time, and the 14.4 ⁇ 10 3 cycle test is carried out respectively. After the test, the data is processed and the clamping force attenuation rate is defined It is the percentage of the difference between the bolt pre-tightening force obtained by the initial tightening torque and the bolt clamping force finally measured by the pressure sensor to the bolt pre-tightening force, expressed as:
  • test data of 20 groups of influencing parameter combinations under cyclic alternating loads are shown in Table 3.
  • the determination coefficient R 2 is the ratio of the regression sum of squares to the total sum of squares (0 ⁇ R 2 ⁇ 1), that is, the degree of approximation of the regression equation to the observed value.
  • the determination coefficient of the quadratic regression model of bolt clamping force attenuation rate R 2 0.8875, indicating that the initial tightening torque, load amplitude, and vibration frequency in the regression model have an effect of 88.75% on the attenuation rate of bolt clamping force, while the influence and error of other factors only account for 11.25%.
  • the regression equation fits the actual measurement situation very well.
  • Durbin-Watson statistical test Since the estimation of the regression model is based on the assumption that the residuals of the model obey the normal distribution, if the residuals do not obey the normal distribution, then all estimation analyses performed on the regression model are unreliable.
  • the Durbin-Watson (DW) statistic is used to test whether the residual distribution is a normal distribution:
  • the DW distribution test shows that when 1.676 ⁇ DW ⁇ 2.324, there is no autocorrelation in the model residuals and obeys a normal distribution.
  • the prediction axis of Fig. 3 is the horizontal axis, and the fitting error is the residual scatter of the regression model on the vertical axis. It can be seen that the scatter points do not show obvious regularity.
  • the absolute value of the partial regression coefficient of the established regression model can identify the importance of the factor, and the positive or negative of the coefficient indicates the direction of the effect of the factor. Therefore, the influence of each influencing parameter on the attenuation rate of bolt clamping force within the test value range is in order: X 2 (load amplitude)>X 1 (initial tightening torque)>X 3 (load frequency). Among them, X 2 and X 3 are positive effects, and X 1 is a negative effect.
  • FIG. 4 is a diagram showing the interactive effect of the initial tightening torque and load amplitude on the attenuation rate of the bolt clamping force.
  • the X and Y axes are the horizontal coding values of the initial tightening torque and load amplitude, respectively, and the Z axis is the bolt clamp Tightness decay rate. It can be seen from Figure 5 that when the initial tightening torque increases: the greater the amplitude, the more obvious the clamping force attenuation; the smaller the amplitude, the smaller the clamping force attenuation rate. In the case of reduced amplitude: the smaller the initial tightening torque, the attenuation rate of bolt clamping force gradually increases; the greater the initial tightening torque, the smaller the attenuation amplitude of bolt clamping force, and the maximum and amplitude The minimum bolt clamping force decay rate reaches the global minimum.
  • the data is processed. Before the test, the clamping force obtained by the digital torque wrench is 26.58KN. After the test, the changed clamping force is 25.25KN as shown in Figure 6, and then the clamping force attenuation can be obtained. The rate is only 5.01%.

Abstract

一种振动工况下螺栓松弛主要影响参数评定及其松弛缓减方法,包括如下步骤:(1)根据振动工况下螺栓松弛的影响参数,可选择载荷幅值、振动频率、初始紧固力矩作为三大试验影响因子;(2)通过三因素五水平的二次通用旋转组合,设计20组三大影响参数的不同数值组合进行试验;(3)根据二次通用旋转组合以及二次回归分析原理,有三因变量的螺栓夹紧力衰减率的目标函数;(4)根据20组三大影响参数的不同数值组合的试验结果,计算出目标函数的各项系数,得到二次回归模型;(5)为判断回归模型的可靠性,对试验结果进行方差分析,再对回归方程进行失拟项检验和统计量检验;(6)通过分析得到在振动工况下螺栓松弛的最主要影响参数以及各影响参数对螺栓夹紧力衰减的影响占比,并利用lingo优化三大影响参数并得到缓减螺栓夹紧力衰减的最佳值。

Description

一种振动工况下螺栓松弛主要影响参数评定及其松弛缓减方法 技术领域
本发明涉及一种振动工况下螺栓松弛主要影响参数评定及其松弛缓减方法,属于机械工程领域。
背景技术
螺栓是工程领域普遍采用的一种典型机械紧固件,其连接系统服役过程中由于振动、交变载荷环境的存在,特别是当旋转机构中的螺栓连接处于动态拉伸压缩和剪切组合的负载下时,螺栓连接更容易松动,螺栓预紧力会出现松弛现象,导致螺栓连接结构失效。统计发现:影响螺栓连接松弛的因素涉及机械加工方式、装配工艺、材料机械性能及工作环境等多方面,且其耦合作用加剧了螺栓的松弛过程,使问题更加复杂。以往对螺栓松弛的实验研究大都基于单一因素的影响原理,根据经验选择某几个影响参数组合进行试验,缺乏系统性和科学性,与实际松弛情况并不相符。国内外学者通过正交实验方法来探究影响螺栓连接的因素以及对参数的优化,但由于正交试验法所获得的最优解只能限制在已定的水平上,不是一定试验范围的最优解。
为了在振动工况下科学地对螺栓松弛的主要影响参数进行评定并优化缓减螺栓松弛的参数组合,需要耗时少效率高又实用的研究方法和测试精度较高的装置。
发明内容
本发明所要解决的技术问题是克服目前振动工况下螺栓松弛影响参数无法评定的技术不足,提供一种二次通用旋转组合方法评定螺栓松弛主要影响参数,通过lingo到振动工况下缓减螺栓松弛的三个影响参数的最佳组合,有效降低了试验时间和材料消耗。
本发明的二次通用旋转组合设计和lingo优化,包括以下步骤:
(1)根据实际振动工况,判断并选择三种螺栓松弛影响参数;
(2)通过三因素五水平的二次通用旋转组合,设计20组三大影响参数的不同数值组合进行试验;
(3)根据二次通用旋转组合以及二次回归分析原理,有三因变量的螺栓夹紧力衰减率的目标函数
Figure PCTCN2019096264-appb-000001
式中:i、j为影响因子序数,且i=1、2、3;j=1、2、3;X为试验数据的编码水平。
(4)根据20组三大影响参数的不同数值组合的试验结果,计算出目标函数的各项系数,得到二次回归模型;
(5)为判断回归模型的可靠性,对试验结果进行方差分析,再对回归方程进行失拟项检验和统计量检验;
(6)通过分析得到在振动工况下螺栓松弛的最主要影响参数以及各因素对螺栓松弛的影响占比,并利用lingo优化三大影响参数并得到缓减螺栓夹紧力衰减的最佳值。
所述的步骤(1)中三种螺栓松弛影响参数选择的是载荷幅值、振动频率和初始紧固力矩。
所述的步骤(3)中试验是采用疲劳拉伸试验机,循环周次是14.4×10 3
本发明提供了一种振动工况下螺栓松弛主要影响参数评定及其松弛缓减方法,通过采用二次通用旋转组合和lingo,得到最主要影响参数以及各因素对螺栓松弛的影响占比,并且还得到缓减螺栓松弛的最佳数值组合。实现了在限定的时间内,通过科学地试验设计和分析,找到在振动工况下能有效缓减螺栓松弛的参数选值;解决了传统技术手段试验次数多、方案摸索时间长、材料消耗大等技术不足。
附图说明
图1是螺栓松弛试验设计及分析的系统框图。
图2是循环交变载荷下螺栓松弛试验模型图。
图3是螺栓夹紧力衰减率的残差散点图
图4是各影响参数对螺栓夹紧力衰减率的影响曲线图。
图5是初始紧固力矩与载荷幅值对螺栓夹紧力衰减率的交互影响。
图6是优化后的螺栓夹紧力变化图
具体实施方式
以下结合附图和具体实例,进一步阐述本发明。应理解,这些实施仅用于说明本发明而不用限制本发明的范围。除非特别说明,本发明采用的试件、方法和设备为本技术领域常用试件、方法和设备。
1.振动工况下影响螺栓松弛的参数选择
将影响螺栓夹紧力的载荷幅值、振动频率、初始紧固力矩为三个试验因子,以螺栓夹紧力衰减率为目标,做三因素五水平的二次通用旋转组合设计,总共20个试验数值组合,用来确定三个试验因子的最佳组合。
2.试验各因素范围确定及水平编码
采用二次通用回归旋转组合对振动工况下影响螺栓松弛的初始紧固力矩、载荷幅值、振动频率进行实验,确定三因素的上、下水平如表1所示。
表1试验各因素取值范围
Figure PCTCN2019096264-appb-000002
根据二次通用旋转组合回归设计原理各试验因素水平编码如表2所示,将实际试验中有单位的自然变量因素Z m(m=1,2,3)通过编码公式转换成无单位的规范变量编码因素X m(m=1,2,3)。
表2各试验因素水平编码表
Figure PCTCN2019096264-appb-000003
采用Smacq数据采集卡对每一组试验参数组合下获得的夹紧力进行实时监测,分别进行14.4×10 3个循环周期试验,试验完对数据进行处理,定义夹紧力衰减率
Figure PCTCN2019096264-appb-000004
为初始紧固力矩所获得的螺栓预紧力和压力传感器最终测得的螺栓夹紧力的差值与螺栓预紧力的百分比,表示为:
Figure PCTCN2019096264-appb-000005
3.根据二次通用旋转组合设计和分析目标函数
20组影响参数组合在循环交变载荷下的试验数据如表3所示。
表3二次通用回归旋转组合试验设计及试验结果
Figure PCTCN2019096264-appb-000006
4.螺栓夹紧力衰减率二次回归数学模型的建立与分析
根据二次回归分析原理,有三个因变量的螺栓夹紧力衰减率二次数学回归模型:
Figure PCTCN2019096264-appb-000007
其中,i、j为影响因子序数,且i=1、2、3;j=1、2、3;y是螺栓夹紧力衰减率,b i、b ij为各自自变量的交互系数;X 1、X 2、X 3分别代表初始紧固力矩、载荷幅值、振动频率。
按照结果计算处所拟合的回归方程的各项系数,从而得到如下的二次回归模型:
Figure PCTCN2019096264-appb-000008
5.对试验结果进行方差分析并对回归方程进行统计检验
对回归模型进行统计检验,以判断回归模型的可靠性以及对真实情况的拟合 优度,以下对试验结果进行方差分析,再对回归方程失拟项检验、显著性检验、判断系数检验和Durbin-Watson统计量检验,以全面验证回归方程的可靠度。螺栓夹紧力衰减率实验结果的方差分析情况如表4所示。
表4螺栓夹紧力衰减率试验结果方差分析表
Figure PCTCN2019096264-appb-000009
F 1为失拟项检验,用来检验失拟平方和中是否含有不可忽略的其他因素对试验结果造成影响。由表4可知,F 1=4.37363<F 0.01(5,5)=10.97,即F 1在0.01水平上不显著,表示在此显著水平下失拟平方和中不含有对试验结果造成影响的不可忽略因素。
F 2显著检验统计量,是平均回归平方和与平均剩余平方和之比,用来检验因变量同多个自变量的整体影响是否显著,根据表4可知,F 2=8.7665>F 0.01(9,10)=4.94,达到了显著水平,说明初始紧固力矩、载荷幅值、振动频率3个因变量对螺栓夹紧力衰减率的影响高度显著,回归模型成立。
判定系数R 2是回归平方和与总平方和之比(0≤R 2≤1),即回归方程对观测值的近似程度,通过检验,螺栓夹紧力衰减率的二次回归模型的判定系数R 2=0.8875,说明该回归模型中初始紧固力矩、载荷幅值、振动频率3个因素对螺栓夹紧力衰减率的影响为88.75%,而其他因素的影响和误差仅占11.25%,说 明回归方程对实际测量情况的拟合度很好。
Durbin-Watson统计量检验。由于回归模型的估计是基于模型残差服从正态分布的假设,如果残差不服从正态分布,那么对回归模型进行的所有估计分析都是不可靠的。Durbin-Watson(DW)统计量即是用来检验残差分布是否为正态分布为:
Figure PCTCN2019096264-appb-000010
式中:
Figure PCTCN2019096264-appb-000011
为回归方程中的残差。
当正常情况下,统计量在2附近时,说明残差是服从正态分布的,若不在2附近,偏离比较远,即该回归模型对螺栓衰减的实际情况的解释能力不强。
根据样本个数和因子个数,通过DW分布检验可知,当1.676<DW<2.324时,模型残差不存在自相关,服从正态分布。通过对回归方程进行Durbin-Watson统计量检验,得到DW=1.915。因此,本回归方程的残差服从正态分布,假设成立,回归模型是可靠的。附图3的预测轴为横轴,拟合误差为纵轴的回归模型残差散点,可以看出其中的散点没有呈现出明显的规律性。
通过以上四种检验方法,可以得出回归模型可靠,且对真实情况的拟合优度很好。
6.试验结果的应用分析
(1)主要影响因素分析
所建立的回归模型的偏回归系数绝对值的大小可判明因子的重要程度,系数的正负表示因子效应作用的方向。所以各影响参数在试验取值范围内对螺栓夹紧力衰减率的影响大小依次为:X 2(载荷幅值)>X 1(初始紧固力矩)>X 3(载荷频率)。其中X 2和X 3为正效应,X 1为负效应。
(2)单因素效应分析
根据附图4可知,在螺栓松弛过程中,载荷幅值和载荷频率的实验水平为1.682时,螺栓夹紧力衰减率最高。初始紧固力矩在-1.682水平时对螺栓夹紧力衰减最快。这表明初始紧固力矩、载荷幅值与振动频率存在一个最佳的数值组合范围。
(3)多因素效应分析
在螺栓连接试验结果分析中,单因素往往不能完全解释试验结果的情况,这就需要从因素见的相互作用效应进行分析。从表4可知,3个交互效应组合中只有X 1X 2对因变量对螺栓夹紧力衰减率的影响显著,即初始紧固力矩和载荷幅值的互作效应对螺栓夹紧力衰减率影响较大。附图5为初始紧固力矩与载荷幅值对螺栓夹紧力衰减率的交互效应关系图,X、Y轴分别为初始紧固力矩和载荷幅值的水平编码取值,Z轴为螺栓夹紧力衰减率。由附图5可知,在初始紧固力矩增大的情况下:振幅越大,夹紧力衰减越明显;振幅减小,夹紧力衰减率越小。在振幅减小的情况下:初始紧固力矩越小,螺栓夹紧力衰减率逐渐增大;初始紧固力矩越大,螺栓夹紧力衰减幅度越小,并在初始紧固力矩最大和振幅最小时螺栓夹紧力衰减率达到全局最小值。
7.基于夹紧力衰减率回归模型的影响参数优化
由上述影响参数对螺栓夹紧力衰减率的影响分析可知,由于螺栓夹紧力衰减率受单因素效应和各因素间互作效应共同影响,因此不能直接由各影响关系的结果得到最佳参数组合,需采用非线性规划优化方法对回归模型进行优化,利用lingo将螺栓夹紧力衰减率二次回归数学模型作为目标函数,设定变量X 1,X 2,X 3的范围均为(-1.682,1.682),对目标函数进行优化,得到全局最优解,即缓减螺栓夹紧力衰减的最佳因素组合:紧固力矩为85.23N·m、加载振幅为2.5KN、振动频率2.477Hz,在最优参数的基础上对螺栓连接试件进行14.4×10 3个循环周期振动实验,采用Smacq数据采集卡对夹紧力进行实时监测。试验完对数据进行处理,试验前通过数显扭矩扳手获得夹紧力为26.58KN,试验后根据附图6所示得到变化后的夹紧力为25.25KN,进而可以得到该次夹紧力衰减率仅为5.01%。

Claims (4)

  1. 一种振动工况下螺栓松弛主要影响参数评定及其松弛缓减方法,其特征在于,包括如下步骤:
    (1)根据振动工况下螺栓松弛的影响参数,可选择载荷幅值、振动频率、初始紧固力矩作为三大试验影响因子;
    (2)通过三因素五水平的二次通用旋转组合,设计20组三大影响参数的不同数值组合进行试验;
    (3)根据二次通用旋转组合以及二次回归分析原理,有三因变量的螺栓夹紧力衰减率的目标函数
    Figure PCTCN2019096264-appb-100001
    式中:i、j为影响因子序数,且i=1、2、3;j=1、2、3;
    X为试验数据的编码水平;
    (4)根据20组三大影响参数的不同数值组合的试验结果,计算出目标函数的各项系数,得到二次回归模型;
    (5)为判断回归模型的可靠性,对试验结果进行方差分析,再对回归方程进行失拟项检验和统计量检验;
    (6)通过分析得到在振动工况下螺栓松弛的最主要影响参数以及各影响参数对螺栓夹紧力衰减的影响占比,并利用lingo优化三大影响参数并得到缓减螺栓夹紧力衰减的最佳值。
  2. 根据权利要求1所述的一种在振动工况下缓减螺栓松弛的优化设计方法,其特征在于:载荷幅值、振动频率和初始紧固力矩判定为振动工况下影响螺栓松弛的主要影响参数。
  3. 根据权利要求1所述的一种振动工况下螺栓松弛主要影响参数评定及其松弛缓减方法,其特征在于:所述的20种三大影响参数不同数值的组合试验,振动循环周次为14.4×10 3
  4. 根据权利要求1所述的一种振动工况下螺栓松弛主要影响参数评定及其松弛缓减方法,其特征在于:所述的载荷幅值、振动频率和初始紧固力矩是根据实际的振动工况中测得。
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Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112507915A (zh) * 2020-12-15 2021-03-16 西安交通大学 一种基于振动响应信息的螺栓连接结构松动状态识别方法
CN113356836A (zh) * 2021-07-19 2021-09-07 中国石油天然气股份有限公司 页岩气压裂井口装置螺栓松动的分析方法
CN113916477A (zh) * 2021-09-30 2022-01-11 东风商用车有限公司 一种螺栓连接副的防松性能测试评价方法
CN115031942A (zh) * 2022-05-27 2022-09-09 南京航空航天大学 一种复合材料结构装配用螺栓拧紧工艺参数确定的方法
WO2023024303A1 (zh) * 2021-11-19 2023-03-02 江苏徐工工程机械研究院有限公司 螺栓预紧力衰减预测装置及方法

Families Citing this family (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110222311B (zh) * 2019-05-29 2022-03-08 北京工业大学 一种振动工况下螺栓松弛主要影响参数评定及其松弛缓减方法
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CN112525520B (zh) * 2021-02-08 2021-05-04 国能大渡河流域水电开发有限公司 机组顶盖螺栓在线监测方法及系统
CN113239467A (zh) * 2021-06-09 2021-08-10 宝能(广州)汽车研究院有限公司 汽车悬架零部件连接螺栓的紧固力矩推算方法
CN113530944B (zh) * 2021-07-13 2022-08-09 哈电风能有限公司 一种螺栓预紧方法及系统

Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2002061295A2 (en) * 2001-02-01 2002-08-08 The Timken Company Method of measuring preload in a multirow bearing assembly
CN102208274A (zh) * 2011-01-05 2011-10-05 蒋雪峰 电力变压器铁心柱截面的优化设计方法
CN102708262A (zh) * 2012-06-07 2012-10-03 蒋雪峰 一种综合节能与减噪的电力变压器多目标优化设计方法
TW201337233A (zh) * 2012-03-14 2013-09-16 Nat Univ Chung Cheng 監測滾珠螺桿於進給系統中預壓變化之方法
CN105961860A (zh) * 2016-05-23 2016-09-28 四川农业大学 一种羊用抗球虫舔砖及其制备方法
CN107192494A (zh) * 2017-05-14 2017-09-22 北京工业大学 一种考虑结合面特性的测定轴向螺栓松弛的装置及方法
CN108388696A (zh) * 2018-01-28 2018-08-10 北京工业大学 一种表征螺栓连接结构松弛特性的实验方法
CN109759022A (zh) * 2018-11-29 2019-05-17 运城学院 处理印染废水中碱性品红的生物吸附剂的制备方法
CN110222311A (zh) * 2019-05-29 2019-09-10 北京工业大学 一种振动工况下螺栓松弛主要影响参数评定及其松弛缓减方法

Family Cites Families (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP4862978B2 (ja) * 2001-06-15 2012-01-25 トヨタ自動車株式会社 加工機の振動検出装置
SM201000089B (it) * 2010-06-29 2013-01-14 Biancalani Srl Macchina e metodo perfezionati per il trattamento combinato meccanico e termico di tessuti, specialmente tessuti a maglia
CN102606609A (zh) * 2012-03-21 2012-07-25 苏州新凌电炉有限公司 一种止退螺栓
CN103708885B (zh) * 2013-12-18 2015-01-21 江苏大学 一种提高茶叶产量的复合肥及其配制方法
CN103823974B (zh) * 2014-02-25 2017-11-03 北京科技大学 无取向硅钢磁性能影响因素的主成分回归分析法
CN105136449B (zh) * 2015-08-24 2018-05-18 哈尔滨工程大学 一种基于磨损机理的车用传动装置的磨损随机过程试验预测方法
CN106407607B (zh) * 2016-10-27 2020-09-15 北京航空航天大学 一种机载多轴隔振系统及优化方法
CN107402126B (zh) * 2017-08-07 2019-12-13 北京工业大学 一种基于模态参数表征的切向单螺栓松弛测量装置和方法
CN107576440B (zh) * 2017-09-21 2019-11-15 北京工业大学 一种残余应力对切向双螺栓连接结构松弛影响的测量方法
CN108827455B (zh) * 2018-04-24 2019-10-18 中国科学院武汉岩土力学研究所 一种节理岩体爆破振动衰减参数预测方法及装置
CN109238546A (zh) * 2018-08-24 2019-01-18 大连理工大学 一种基于机器学习的螺栓预紧力预测方法

Patent Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2002061295A2 (en) * 2001-02-01 2002-08-08 The Timken Company Method of measuring preload in a multirow bearing assembly
CN102208274A (zh) * 2011-01-05 2011-10-05 蒋雪峰 电力变压器铁心柱截面的优化设计方法
TW201337233A (zh) * 2012-03-14 2013-09-16 Nat Univ Chung Cheng 監測滾珠螺桿於進給系統中預壓變化之方法
CN102708262A (zh) * 2012-06-07 2012-10-03 蒋雪峰 一种综合节能与减噪的电力变压器多目标优化设计方法
CN105961860A (zh) * 2016-05-23 2016-09-28 四川农业大学 一种羊用抗球虫舔砖及其制备方法
CN107192494A (zh) * 2017-05-14 2017-09-22 北京工业大学 一种考虑结合面特性的测定轴向螺栓松弛的装置及方法
CN108388696A (zh) * 2018-01-28 2018-08-10 北京工业大学 一种表征螺栓连接结构松弛特性的实验方法
CN109759022A (zh) * 2018-11-29 2019-05-17 运城学院 处理印染废水中碱性品红的生物吸附剂的制备方法
CN110222311A (zh) * 2019-05-29 2019-09-10 北京工业大学 一种振动工况下螺栓松弛主要影响参数评定及其松弛缓减方法

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
ZHANG, ZHEN ET AL.: "Preload Relaxation Characteristics in Composite Bolted Joints Based on Vibration Fatigue Test", ACTA MATERIAE COMPOSITAE SINICA, vol. 33, no. 01, 31 January 2016 (2016-01-31), ISSN: 1000-3851, DOI: 9160302 *

Cited By (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112507915A (zh) * 2020-12-15 2021-03-16 西安交通大学 一种基于振动响应信息的螺栓连接结构松动状态识别方法
CN113356836A (zh) * 2021-07-19 2021-09-07 中国石油天然气股份有限公司 页岩气压裂井口装置螺栓松动的分析方法
CN113356836B (zh) * 2021-07-19 2024-03-26 中国石油天然气股份有限公司 页岩气压裂井口装置螺栓松动的分析方法
CN113916477A (zh) * 2021-09-30 2022-01-11 东风商用车有限公司 一种螺栓连接副的防松性能测试评价方法
CN113916477B (zh) * 2021-09-30 2023-09-29 东风商用车有限公司 一种螺栓连接副的防松性能测试评价方法
WO2023024303A1 (zh) * 2021-11-19 2023-03-02 江苏徐工工程机械研究院有限公司 螺栓预紧力衰减预测装置及方法
CN115031942A (zh) * 2022-05-27 2022-09-09 南京航空航天大学 一种复合材料结构装配用螺栓拧紧工艺参数确定的方法

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