Mechanical Reliability Analysis Research Articles

Time-Varying Reliability Analysis of Mechanisms with Strength Degradation Considering Clearances and Local Stiffness Effects

Mechanism systems are important components of dynamic mechanical systems. The time-varying reliability assessment of mechanism systems is of great significance for the safety and fault diagnosis of mechanical products. In this paper, a time-varying reliability evaluation method for mechanisms under the fatigue failure mode is proposed, which takes into account the joint effects of clearance, local structural stiffness, random load and random strength degradation. The proposed mechanism reliability models are established by nonlinear dynamic analysis considering failure factors and establishing random stress history characterization matrices. Additionally, the models are validated by the Monte Carlo simulation method. The results show that the mechanism clearance, local stiffness, and initial strength dispersion have a significant effect on the time-varying reliability of the mechanisms. Furthermore, both local stiffness and initial strength dispersion have a greater influence on the effect of clearance on the time-varying reliability of the mechanisms. The proposed reliability models can quantitatively analyze the dynamic effects of failure factors on the reliability of the mechanisms, which can be used for the stochastic remaining life evaluation and fault diagnosis of the mechanism systems.

Time-dependent kinematic reliability of motion mechanisms with dynamic factors

Time-dependent kinematic reliability of a motion mechanism is critical for optimizing its operational performance. Dynamic factors, including material deterioration and wear in the joints, are disregarded in the prior study. As such, the envelope method is employed to undertake time-dependent kinematic reliability analysis of motion mechanisms, accounting for dynamic factors. Firstly, a decoupling strategy is proposed for decoupling the time-dependent motion error stemming from motion input and the dynamic factors. Thus, the kinematic reliability is delineated into two distinct temporal parameter-dependent issues. Subsequently, the envelope function is extended to solve the kinematic reliability. The expansion temporal points determination function (ETPDF) in the envelope function is approximated using a first-order method coupled with an active learning Kriging mode. After the expansion temporal points are found, the time-dependent reliability can be efficiently calculated via a multivariate Gaussian integral. Finally, the effectiveness and accuracy of the proposed method is verified by means of a 4-bar function generating mechanism.

Reliability Analysis and Optimization Method of a Mechanical System Based on the Response Surface Method and Sensitivity Analysis Method

Mechanical system reliability analysis constitutes a primary research focus in the field of engineering. This study aims to address the issue of complex mechanical systems with intricate mechanisms and nonlinear reliability equations that are challenging to solve. To this end, we present a reliability analysis and optimization methodology that merges the response surface and sensitivity analysis methods. A comprehensive formation of reliability assessment and optimization of complex mechanical systems is achieved by creating a response surface model to fit the complex state function and solving the reliability parameters, followed by an error sensitivity analysis to determine the mechanical system’s reliability adjustment strategy. Finally, these methods are applied to a cylindrical material transport device to preliminarily realize the reliability assessment and average reliability optimization goals. The study’s findings may offer a theoretical framework and research opportunities to evaluate and enhance the reliability of intricate mechanical systems.

Temperature-dependent mechanical properties of graphene nanoplatelet reinforced polymer nanocomposites: Micromechanical modeling and interfacial analysis

One of the challenges to be addressed in the reasonable prediction of the mechanical properties of nanocomposites at elevated temperatures is the quantitative characterization of the temperature-dependent interfacial behavior. In this study, the temperature-dependent mechanical properties for graphene nanoplatelets (GNPs) reinforced polymer-matrix nanocomposites are modeling based on the nonlinear interfacial shear stress transfer mechanism. Besides, the influence of interfacial debonding, polymer matrix plasticity, thermomechanical parameters of components, and their evolution with temperature, as well as the orientation, dimensions and volume fractions of GNPs is considered. The Young's modulus, yield/ultimate strength, and stress-strain relationships at elevated temperatures are predicted and are verified by the available experimental data. Compared to the extended room-temperature models previously established, the proposed model considering the microscopic structures achieves higher prediction accuracy with only basic material parameters input. Furthermore, the temperature-dependent interfacial mechanical behavior is analyzed. The initial strain of debonding and the maximum debonding ratio of the interface at elevated temperatures are calculated. The micromechanical modeling establishes the quantitative relationships between the temperature-dependent interfacial behavior and the mechanical properties of nanocomposites. This study deepens the understanding of the mechanical behavior of the interface and their evolution with temperature, which contributes to the prediction of the high-temperature mechanical performance and reliability analysis of nanocomposites.

Time-dependent reliability analysis of planar mechanisms considering truncated random variables and joint clearances

The dimension variables and joint clearances are key factors affecting the motion accuracy of a mechanism. The existing time-dependent reliability analysis methods usually assume that the dimension variables follow ideal distribution, ignoring the truncation restrictions due to production and manufacturing. In addition, improper handling of the correlation between joint clearance variables leads to inaccurate calculation results. To address the above issues, this paper proposes a time-dependent kinematic reliability analysis method, in which the truncated random variables and joint clearances are comprehensively considered. Firstly, the complex correlation of clearance variables in the motion error function is processed by the dimension reduction method. Then, the truncated variables are converted into truncated standard normal variables. Furthermore, the envelope function method with expansion at the most probable point (MPP) is used to transform time-dependent reliability into time-independent reliability at multiple time points, greatly reducing computational complexity. On this basis, the saddlepoint method is used to fit the motion error cumulative distribution function at each time point, and the upper and lower bounds of failure probability are obtained through the Copula function and second-order narrow reliability bounds. The effectiveness of the proposed method is verified by a typical 4-bar linkage and a single crank double rocker mechanism.

Electrical and mechanical reliability and failure mechanism analysis of electrically conductive adhesives

For electrically conductive adhesives (ECAs) interconnection, adequate electrical, mechanical and thermal performance are crucial for long-term service reliability. The work focused primarily on analyzing the effects of environmental aging on the reliability and failure mechanism of ECAs joints. In this paper, high temperature and humidity (85 °C, 85%RH, 1000 h), thermal shock (−40 °C to 125 °C, 1000 cycles) and thermal aging (125 °C, 1000 h) tests were performed to study the reliability of the ECAs. Additionally, the fracture modes were investigated by mechanical shear strength testing before and after the reliability tests. The interfacial microstructure of the ECAs was investigated and the fracture mechanism of ECAs was characterized. The study showed that the reliability of the ECAs was improved compared with conventional ECA1 and ECA2.

Mechanical Performance and Reliability Analysis of “Structure-Insulation” Integrated Wall Panel under Grain Load

As a new type of grain barn wall component, the “Structure-Insulation” integrated wall panel (SIW) has excellent characteristics such as a high-bearing capacity and good insulation performance. In order to study its mechanical properties under grain load, this paper designed three wall panels with different thicknesses, carried out static loading tests on them, studied their cracking and ultimate load, and analyzed the development trend of the wall panel’s crack and deflection. In order to study the reliability of wall panels under stochastic conditions, the performance functions of the wall panel under deflection and strength control conditions were established. The reliability analysis was carried out by using the response surface method and finite element software. The sensitivity degree of each random parameter to different performance functions was quantified. The results show that, under the maximum grain load condition, the deflection of the designed specimens is less than l0/250, and the crack width is less than 0.2 mm, both of which meet the requirements of the normal use limit state. The cracking loads of the three specimens are 13.02, 14.75, and 16.49 kN/m2, respectively, with corresponding crack widths of 0.06, 0.07, and 0.06 mm. The ultimate load is 65.1, 75.52, and 82.47 kN/m2, with corresponding maximum crack widths of 1.66, 1.60, and 1.61 mm, respectively. The reliability indexes of the deflection and strength of the thinnest specimens are β1=2.60 and β2=3.26, respectively, which meet the safety conditions of ductile failure. The parameter affecting the reliability of concrete deflection is the grain gravity density, with a correlation coefficient of −0.707. The parameter affecting the reliability of concrete strength is concrete strength, with a correlation coefficient of 0.935. Combined with the static load test and reliability analysis, the designed wall panel can meet the normal use of grain under full load and has good reliability. Sensitivity analysis can provide a reference for the optimization of practical engineering design.

Failure modeling and reliability analysis for motion mechanism with clearance joints under plastic deformation and wear

The performance failure and reliability of motion mechanism has a significant effect on industry reliability, operation safety and production economy. Motion precise is one of the typical performance indicators especially for motion mechanism with multibody and joints. Size of joint clearance degenerates with usage such as wear and deformation. Repeated start-stop lead to impact stress and plastic deformation for clearance joint particularly for mechanism with high load and long working cycles. This study attempts to investigate the wear process and performance failure model of multibody mechanism with clearance joints considering plastic deformation and wear. Quantification of plastic deformation caused by repeated impact stress of joints is studied by formulation. Then, a novel wear process model is established, after which performance failure indicator is conducted. A linkage motion mechanism with multi revolution joints is studied to demonstrate proposed methods. This study provides valuable guidelines for degeneration prediction and reliability analysis of motion mechanism.

Intelligent Assessment Method of Structural Reliability Driven by Carrying Capacity Sustainable Target: Taking Bearing Capacity as Criterion

Large-scale building structures are subject to numerous uncertain loads during their service life, leading to a decrease in structural reliability. Real-time analysis and accurate prediction of structural reliability is a key step to improve the bearing capacity of buildings. This study proposes an intelligent assessment method for structural reliability driven by a sustainability target, which incorporated digital twin technology to establish an intelligent evaluation framework for structural reliability. Under the guidance of the evaluation framework, the establishment method of a structural high-fidelity twin model is formed. The mechanical properties and reliability analysis mechanism are established based on the high-fidelity twin model. The theoretical method was validated by experimental analysis of a rigid cable truss construction. The results showed the simulation accuracy of the high-fidelity twin model formed by the modeling method is up to 95%. With the guidance of the proposed evaluation method, the mechanical response of the structure under different load cases was accurately analyzed, and the coupling relationship between component failure and reliability indicators was obtained. The twinning model can be used to analyze the reliability of the structure in real time and help to set maintenance measures of structural safety. By analyzing the bearing capacity and reliability index of the structure, the safety of the structure under load is guaranteed. The sustainability of structural performance is achieved during the normal service period of the structure. The proposed reliability assessment method provides a new approach to improving the sustainability of building bearing capacity.

A mechanism reliability analysis method considering environmental influence and failure modes’ correlation: a case study of rifle automaton

In order to overcome the challenge of quantifying the influence of environmental conditions and the coexistence of multiple failure modes involved in mechanism reliability modelling under different environments. In this paper, we propose a method for the analysis of mechanism reliability that takes into account the influence of environmental factors and failure modes’ correlation, quantifies the influence of environmental factors as the random distribution and degradation path of parameters, and derives the Copula description of failure mode correlation from the historical data of environmental experiments. On the basis of the discrete mechanism dynamics model, the output parameters of the characteristic points are calculated, and the failure rate of each failure mode is calculated based on the failure criterion and the performance margin theory. Additionally, the dynamic change pattern of the mechanism reliability is compared with the Kaplan-Meier estimation of the corresponding environmental test history data to assess the validity of the calculation results. The reliability modelling problem of a motion mechanism of an automatic rifle automaton in a high and low temperature environment is applied to the method, and the reliability calculation results are close to those of Kaplan-Meier estimation of the test history data, and all are within the upper and lower bounds given by the reliability boundary theory, demonstrating the method's validity.

Reliability analysis of mechanisms with mixed uncertainties using polynomial chaos expansion

AbstractIn order to quantify the effect of mixed uncertainties on the reliability of mechanisms, this paper proposes a method for analyzing the reliability of mechanisms with mixed uncertainties using polynomial chaos expansion. Based on the performance margin theory, a mechanism reliability model considering mixed uncertainties is developed, and the Sobol indices can be easily calculated by an arbitrarily polynomial chaos expansion (aPCE) of the reliability function to quantify the independent contribution of each parameter to the global sensitivity and the effect of parameter coupling. Additionally, this paper also introduces a mixed uncertainties propagation method based on PCE, which treats cognitive uncertainties as fuzzy variables, converts the fuzzy variable into an interval variable using cut set theory, and transforms the PCE containing interval uncertainties into a Bernstein polynomial to calculate the membership function of the output quantity and the non‐probabilistic reliability index by area method. The final case study of a simplified automaton motion mechanism illustrates that the proposed method is effective and convincing, and the mechanism reliability decreases with increasing mixed uncertainties. The mechanism reliability index considering mixed uncertainties will give a more conservative reliability estimation.

The time varying reliability analysis for space focusing mechanism based on probability model

The time varying reliability analysis for space focusing mechanism based on probability model

Mechanical Reliability Analysis of Flexible Power Cables for Marine Energy

Marine power cables connected to moving devices at sea may experience millions of load cycles per year, and thus they need to be flexible due to the movements of the cable and designed for mechanical loads. In this study, the focus is on the mechanical life of flexible low- and medium voltage power cables connecting devices to hubs. The reliability design method Variational Mode and Effect Analysis (VMEA) is applied, based on identifying and quantifying different types of uncertainty sources, including scatter, model and statistical uncertainties. It implements a load–strength approach that combines numerical simulations to assess the loads on the cable and experimental tests to assess the strength of the cable. The VMEA method is demonstrated for an evaluation of bending fatigue, and is found to be a useful tool to evaluate uncertainties in fatigue life for WEC (Wave Energy Converter) system cables during the design phase. The results give a firm foundation for the evaluation of safety against fatigue and are also helpful for identifying weak spots in the reliability assessment, thereby motivating actions in the improvement process. Uncertainties in terms of scatter, statistical uncertainty and model uncertainty are evaluated with respect to the WaveEL 3.0, a WEC designed by the company Waves4Power, and deployed in Runde, Norway. A major contribution to the overall uncertainty is found to originate from the fatigue life model, both in terms of scatter and model uncertainty.

Kinematic reliability evaluation of high-precision planar mechanisms experiencing non-uniform wear in revolute joints

Joint clearance significantly influences the motion accuracy of a mechanism. Most of the existing studies assumed that the clearance is regular with constant size. The effect of irregular joint clearance due to wear on the kinematic accuracy is ignored. Hence, this study conducts kinematic reliability analysis of high-precision planar mechanisms experiencing non-uniform wear. Firstly, under the framework of multi-body dynamics, an efficient wear prediction method based on Archard’s wear model is presented for parameterized description of the clearance boundary. Secondly, fractional moments of the motion output considering the uncertainties of driving actuators, link dimensions and non-uniform joint clearance are derived with the dimension reduction method. On this basis, the maximum entropy model constrained by fractional moments is employed to approximate the distribution of the motion output. Then the kinematic reliability is accordingly calculated using the numerical integral. Meanwhile, a Monte Carlo simulation (MCS) based method is developed for kinematic reliability analysis by virtue of slicing sampling technique to provide a reference solution. Finally, experimental testing of a slider-crank mechanism is presented to verify the wear prediction method. The slider-crank mechanism is also used to demonstrate the effectiveness of the proposed kinematic reliability evaluation method.

Mechanical Equipment Reliability Analysis: Case Study

In civil and mining industries, Wheel loaders are an important component and their cost capability at effective operation. The environmental and operational factors dramatically affect the performance of loaders. In many cases, failure data are often collected from multiple and distributed units in different operational conditions, which can introduce heterogeneity into the data. Part of such heterogeneity can be explained and isolated by the observable covariates, whose values and the way they can affect the item's reliability are known. However, some factors that may affect the item's reliability are typically unknown and lead to unobserved heterogeneity. These factors are categorized as unobserved covariates. In most reliability studies, the effect of unobserved covariates is neglected. This may lead to erroneous model selection for the time to failure of the item, as well as wrong conclusions and decisions. There is a lack of sufficient knowledge, theoretical background, and a systematic approach to model the unobserved covariate in reliability analysis. This paper aims to present a framework for reliability analysis in the presence of unobserved and observed covariates. The unobserved covariates will be analyzed using frailty models (Such as Mixed Proportional Hazard).A case will illustrate the application of the framework.

A time-varying mechanical structure reliability analysis method based on performance degradation

In mechanical engineering, most mechanical structural systems are composed of many parts, so their structures are complex. When a mechanical structure fails, it is generally caused by various failure modes. When designers want to improve the quality of mechanical products in the design of mechanical products, reliability analysis can play an important role. It is indispensable in the design and manufacture of mechanical products, engineering use, repair and maintenance. Research on time-varying reliability of mechanical structures is of great significance in improving the quality of mechanical products and bringing more economic benefits to engineering. It has received extensive attention in both academic fields and practical engineering applications. This paper takes the time-varying reliability analysis of mechanical structures based on performance degradation as the research topic, focusing on the reliability analysis methods and techniques of mechanical structures such as Gamma degradation process, material P-S-N curve, mixed Copula function, and nested Copula function. The main research content is divided into three parts. (1) The Gamma degradation process and the P-S-N material probabilistic fatigue life curve are used when establishing the strength degradation random model of the mechanical system. It provides the theoretical basis of strength degradation level for time-varying reliability analysis of mechanical structure based on performance degradation. (2) Combine the mixed Copula function and the nested Copula function to establish a comprehensive failure correlation analysis model of the mechanical system. It provides a theoretical basis for failure correlation for time-varying reliability analysis of mechanical structures based on performance degradation. (3) The time-varying reliability analysis of the one-stage gear transmission system in the engineering example is carried out. Researched and analyzed the time-varying reliability of the large and small gears in the one-stage gear transmission system and the mechanical structure of the system itself under the correlation of strength degradation and failure.

Mechanical Reliability Analysis of Control Rod Assembly for HTR-PM

The article analyzes the forces and weaknesses of the control rod assembly in the high temperature gas cooled reactor (HTGR) demonstration project-pebble bed modular HTGR plant (HTR-PM), using the the mechanical reliability theory and mechanical simulation, and identifies the weaknesses at the connection of the control rod assembly. In the reliability-life calculation method based on the probabilistic fracture mechanics, in combination with the influence of irradiation on the fatigue life model and in consideration of the stress, the authors establish the reliability-life model to calculate the reliability-life of HTR-PM control rod assembly at the irradiation attenuation coefficient of 0.7. The calculation results show that at the reliability level of 0.99, the life of HTR-PM control rod assembly is about 150,000 action cycles, and that the irradiation has a great influence on the life of the control rod assembly. In view of what mentioned above, this paper can provide reference for the equipment reliability management of the HTR-PM control rod assembly.

Mechanical reliability analysis of nanoencapsulated phase change materials combining Monte Carlo technique and the finite element method

Nanoencapsulated phase change materials (nePCMs) are one of the technologies currently under research for energy storage purposes. These nePCMs are composed of a phase change core surrounded by a shell which confines the core material when this one is in liquid phase. One of the problems experimentally encountered when applying thermal cycles to the nePCMs is that their shell fails mechanically and the thermal stresses arising may be one of the causes of this failure. In order to evaluate the impact of the uncertainties of material and geometrical parameters available for nePCMs, the present work presents a probabilistic numerical tool, which combines Monte Carlo techniques and a finite element thermomechanical model with phase change, to study two key magnitudes of nePCMs for energy storage applications of tin and aluminium nePCMs: the maximum Rankine's equivalent stress and the energy density capability. Then, both uncertainty and sensitivity analyses are performed to determine the physical parameters that have the most significant influence on the maximum Rankine's stress, which are found to be the melting temperature and the thermal expansion of the core. Finally, both a deterministic and a probabilistic failure criterion are considered to analyse its influence on the number of predicted failures, specially when dispersion on tensile strength measurements exists as well. Only 1.87% of tin nePCMs are expected to fail mechanically while aluminium ones are not likely to resist.

Intelligent Extremum Surrogate Modeling Framework for Dynamic Probabilistic Analysis of Complex Mechanism

The reliability analysis of complex mechanisms involves time-varying, high-nonlinearity, and multiparameters. The traditional way is to employ Monte Carlo (MC) simulation to achieve the reliability level, but this method consumes too much computing resources and is even computationally intractable. To improve the efficiency and accuracy of dynamic probabilistic analysis of complex mechanisms, an intelligent extremum surrogate modeling framework (IESMF, short for) is proposed based on extremum response surface method (ERSM), combined with artificial neural network (ANN) method and an improved optimize particle swarm optimization (PSO) method. Hereinto, the ERSM is used to simplify the dynamic process of output response to the extremum value of transient analysis; ANN is applied to establish a mathematical model between input variables and response, and the improved PSO method is utilized in search of initial weights and thresholds of the model. The effectiveness of the IESMF is demonstrated to perform the Rack-and-pinion steering mechanism (RPSM) reliability analysis. The results show that when the allowable value of gear root stress is equal to 850 MPa, the RPSM has a reliability degree of 0.9971. Through the validation process, it is illustrated that IESMF is accurate and efficient in dynamic probabilistic analysis of complex mechanisms, and its comprehensive performance is better than the MC method and ERSM. The research effort offers new ideas for the reliability estimation of a complex mechanism, thus enriching the method and theory of mechanical reliability design.

Mechanism reliability and sensitivity analysis of landing gear under multiple failure modes

For a certain type of aircraft landing gear retraction-extension mechanism, a multi-body dynamic simulation model is established, and the time-dependent curves of force and angle are obtained. Considering the random uncertainty of friction coefficient, assembly error, and the change of hinge wear under different retraction times, the reliability model is built including three failure modes of landing gear, i.e. blocking failure, positioning failure and accuracy failure. Based on the adaptive Kriging model, the reliability and sensitivity of retraction-extension system under the condition of single failure mode and multiple failure modes in series are analyzed, and the rule of reliability and sensitivity changing with the number of operations is given. The results show that the system failure probability of landing gear mechanism tends to decrease first and then increase when considering the given information of random factors, and the influences of random factors on the failure probability vary with the number of operations. This work provides a viable tool for the reliability analysis and design of landing gear mechanisms.