Reliability Assessment Method Research Articles

Multi-performance degradation reliability assessment method for a cabin door locking mechanism

A crucial part of the aircraft, the landing gear cabin door locking mechanism directly affects how well the landing gear retracts and how stealthily the aircraft operates. A reliability evaluation approach under multiple deterioration is provided, with a focus on the features of high reliability, small sample, and multiple performance degradation of the locking mechanism. The locking angle of the lock hook and the locking displacement offset of the lock hook are chosen as the characteristic quantities based on the analysis of the factors influencing the life of the locking mechanism; next, the Wiener process is used to model the degradation process of the selected characteristic quantities in order to obtain the failure probability density function for both; then, the multiple performance degradation reliability evaluation model is established using the Copula function, which can precisely and effectively characterize the coupled competitive relationships of multiple performance degradations. This model characterizes the stochastic correlation between the locking angle and the locking displacement of the lock hook. Following that, the Akaike information criteria (AIC) is used to choose the Copula function. Finally, the locking mechanism’s reliability assessment is carried out, as well as the evaluation findings are contrasted with those of the usual technique, which only takes into account a single failure performance characteristic quantity. A series of data analyses led to the conclusion that the approach is more relevant and accurate than that of the conventional method, and that it is not prudent to undervalue its dependability.

Explicit reliability incorporated switches planning of smart distribution system with high flexibility

Different types of switches play different roles in the fault management procedure in particular context of smart grid, which have different impact on system reliability. The motivation behind this paper is to develop an explicit reliability assessment method adapting to flexible deployment of circuit breakers (CBs), remote-controlled switches (RCSs), and manual switches (MSs), which can be further integrated into switch planning models analytically. The peculiar of this paper is to use the propagation constraints of fictitious power flows to model three stages of fault management procedures. Based on the fictitious power flows, the placement and action for CBs, RCSs, and MSs are modeled in detail as linear constraints, considering power flow constraints in fault management procedure. Therefore, this MILP model can be easily integrated into an exact mathematical optimization model. Finally, the proposed method is tested in 37, 85, 137, 417 node distribution network systems to verify the efficiency of the algorithm. Besides, the necessity of considering flexible location of three types of switches and its application on switch planning are verified.

Establishing the True Dynamic Bending Moment of Propeller Shaft Using a Single Bridge of Strain Gauge

The measurement of shaft bending (whirling) moment can be performed via a telemetry system including strain gauges which can obtain the bending stress. By using a single bridge of strain gauge, it was possible to obtain only the nominal bending moment. However, in case of the propeller shaft vibration measurement, the true dynamic bending moment is needed to evaluate the effect of propeller forces on the stability of the bearings. To deal with this, typically two bridges of strain gauge at 90 degrees are needed. This research presents a novel reliability assessment method in establishing the true dynamic bending moment using only one bridge of strain gauge. This is achieved by using the actual bending stress measured by strain gauge combined with its own phase lag stress at an angle of 90 degrees. To validate this technique, the experiments were performed under the rapid turning transient states during a sea trial of a 50,000 DWT oil/chemical tanker. As a result, great fluctuations in propeller force were detected, resulting in a non-uniform oil film in the bearings. The displacement sensor was also installed and confirmed the established true dynamic bending moment.

Global Reliability Sensitivity of the Structure Under Fuzzy Uncertainty and Its Estimations

Global reliability sensitivity (GRS) index under fuzzy uncertainty is defined as the mean of the absolute difference between unconditional failure credibility and conditional failure credibility, which is important to quantify the effect of fuzzy inputs on failure credibility of the structure. The solution of this index requires nested analysis of conditional failure credibility and fuzzy mean, which introduces a large amount of computation. To efficiently estimate the GRS under fuzzy uncertainty, a method combining fuzzy simulation (FS) with fuzzy first-order and second moment (FS–FFOSM) method as well as a fuzzy sequential optimization and reliability assessment (FSORA) method are proposed. Compared with the direct double-loop FS method, in which both the conditional failure credibility and the fuzzy mean are estimated by FS, the proposed FS–FFOSM uses a more efficient FFOSM method to estimate the conditional failure credibility in the inner loop, which improves the computational efficiency of estimating GRS under fuzzy uncertainty. To further improve the computational efficiency, this paper also transforms the estimation of GRS into the solution of the optimization model under the constraint of failure credibility and establishes the FSORA method to solve the optimization model. The FSORA method uses a series of cycles of deterministic optimization and inverse design point analysis corresponding to the required fuzzy reliability index by GRS to reduce the iterations, and then the computational efficiency is further improved. Several examples illustrate the computational efficiency and accuracy of the proposed methods.

Reliability assessment methods to address fast transient of reactor core

In order to enhance the safety of new advanced reactors, reliability based approach to the design of thermal hydraulic system becomes necessary. In this work, “load exceeds capacity” based approach of structural reliability analysis is employed and probability of failure of the system was then assessed in terms of a limit state function while probabilistic measure of limit state function violation is performed through different methods of reliability assessment. Here, we have focused on TRIGA core subjected to reactivity initiated fast transient. Initially, response surface design method has been used for approximating true failure surface, and then FORM-SORM analysis has been carried out. But, due to non linearity involved with failure surface, there have been noticed instability in FORM-SORM implementation. Later, directional simulation approach of Monte Carlo variance reduction techniques has been employed to illustrate such fast transient. In the investigation, there have been several aspects considered and in each case directional simulation method has shown its ability to give valid results. Hence, the method could be recommended as a viable and efficient scheme to solve even fast transient problem in design and analysis of any reactor.

Reliability testing of solder joints under combined cyclic thermal and bending load for automotive applications

The cost and time efficient reliability qualification process of solder joints in automotive electronic assemblies requires accelerated temperature cycling (ATC) testing. This work introduces a load-dependent reliability assessment method on board level for solder joints of multilayer ceramic capacitors (MLCC) under superimposed cyclic thermal and 3-point bending load. For this purpose, a testing setup is developed to enable statistical testing of solder connections under accelerated load scenarios. The condition of solder joints is monitored online by means of impedance measurement until failure.In this work, solder joint failure of a large amount of MLCC 1206 components is experimentally investigated, where the following lifetime influencing factors are studied: solder volume variation and MLCC 1206 components from different suppliers.The resulting lifetime of solder joints with volume variation reveals, that under the same loading conditions smaller solder joints show a significantly lower survival probability compared to solder joints with larger volumes. Furthermore, significant differences in solder joint lifetime between components from two different suppliers are observed.In order to derive a load-dependent failure criterion using impedance measurement data, finite element (FE) simulation is performed under consideration of test boundary conditions. In this way, printed circuit board (PCB) deformation is determined, taking into account both the thermally and mechanically induced strains. It is shown, that the relationship between calculated load-dependent PCB strain amplitudes and experimentally detected solder joint failures are described by a power law leading to component Woehler curves for different failure probabilities.

HEART Hybrid Methods for Assessing Human Reliability in Coal-Fired Thermal Power Plant Process

The assessment of human reliability is crucial in serious processes and operations, such as planned maintenance, unplanned maintenance, and troubleshooting in a coal-fired thermal power plant, as the nature of these processes poses significant threats. When the literature is examined, the evaluation of human reliability in any type of power plant, especially coal-fired thermal power plants, is limited. In order to fill this gap, we systematically assessed human reliability in an accident that occurred during a repair of a tube failure in a boiler in a coal-fired thermal power plant. The HEART (human error assessment and reduction technique) method was used in a hybrid way alongside the fuzzy AHP and SWARA (step weight assessment ratio analysis) methods. Although the HEART method is a practical, understandable, and easy-to-implement human reliability assessment method, the APOE (assessment of the proportion effect) value depends on the decision of a single decision maker. This study aimed to eliminate this deficiency and compare human error possibilities using HEART–fuzzy AHP and HEART–SWARA methods. This hybrid method can be used in the operation of all coal-fired thermal power plants and provides practical contributions to minimize human error.

A Comprehensive Reliability Assessment Method for Existing Railway Bridges Based on Bayesian Theory

The increase in traffic volume and train load poses new challenges to the reliability assessment of existing railway bridges. To construct a comprehensive assessment method for the safety and reliability of existing railway bridges, firstly, the risk factors of railway bridge structures are analyzed and the evaluation criteria are determined; secondly, based on the accident tree theory, a multilevel Bayesian network model with key points is established, and the ability of the Bayesian network bidirectional reasoning and sensitivity analysis is used to evaluate the structural safety; finally, the result was applied to the marina northern Songhua River extra-large bridge to verify the applicability of the comprehensive evaluation of the reliability of an existing railway bridge. This approach provides a theoretical basis for the maintenance and reinforcement of the Songhua River Bridge along the Bin-North Line.

Reliability Assessment Method for Simply Supported Bridge Based on Structural Health Monitoring of Frequency with Temperature and Humidity Effect Eliminated

Structural health monitoring (SHM) has been widely used for the performance assessment of bridges, especially the methods based on dynamic characteristics. Meanwhile, bridge modal frequency is influenced significantly by environmental factors, such as temperature and humidity. Combined with SHM, a reliability assessment of bridges with the temperature and humidity effects eliminated is proposed. Firstly, the bridge deflection verification coefficient is adopted as the evaluation indicator for bridge condition, which is the ratio of deflection-measured value to deflection-calculated value. It is obtained from the relationship between verification coefficient and modal frequency through theoretical derivation. Secondly, a back propagation (BP) neural network is improved by using an artificial bee colony algorithm and employed as a surrogate model to eliminate the effect of temperature and humidity on frequency. Thirdly, a dynamic Bayesian network is applied to establish the reliability analysis model combined with the monitoring results, so that the probability distribution of bridge parameters is updated to improve the accuracy of the reliability analysis. Finally, a simply supported bridge is used as the case study, based on the proposed method in this work. The results indicate that the proposed method can eliminate the temperature and humidity effect on frequency precisely and effectively. With the effect of temperature and humidity on frequency eliminated, the bridge condition assessment can be evaluated accurately through the reliability analysis based on SHM and the dynamic Bayesian network.

Reliability analysis-based investigation of the historical Széchenyi Chain Bridge deck system

Before the recent reconstruction, significant corrosion damages were observed on the deck system of the ∼170-year-old Széchenyi Chain Bridge. Therefore, an advanced reliability analysis-based study is executed to assess the risk of failure of the structure in its situation until the refurbishment starts. The current paper has the aim to introduce the applied assessment method for the risk analysis and damage grade determination of the historical structure. The novel method combines the following techniques: (i) input data coming from on-site measurements implemented into state-of-the-art corrosion models, (ii) advanced finite element model-based resistance calculation (GMNI analysis) implemented into (iii) Monte Carlo simulation-based stochastic reliability assessment method to determine the risk of the bridge deck system failure. It is concluded that the introduced method is a powerful tool for risk assessment of existing aging structures.

Failure probability analysis of corroded RC structures considering the effect of spatial variability

A reasonable assessment of the probability of structural failure is essential to ensure the safe performance of corroded reinforced concrete (RC) structures. In this paper, a novel cross-sectional area loss model of corroded steel bars is proposed and the scale of fluctuation of some key parameters is estimated using the semi-variogram function method. A stochastic resistance deterioration model considering the effect of unbalanced corrosion and spatial variability and a time-dependent reliability assessment method of corroded concrete structures (CCSs) are then presented. A simple case analysis of a CCS is used to illustrate the application of the proposed method. The case analysis results show that the cumulative failure probability (CFP) is overestimated using the popular pit area model, while it is underestimated without considering the spatial variability of calculation parameters. Random field parameter analysis shows that an appropriate choice of the element size is very important for the safety evaluation of RC structures. Additionally, compared with a marine atmospheric environment, the CFP of a case study structure in tidal and splash environments was found to be increased by 20.15% and 70.40%, respectively, due to the gradual increase of corrosion current density. Of the three service environments, the splash environment thus has the greatest impact on structural failure probability.

Reliability Assessment of the Integrated Energy System Considering Gas–Thermal Inertia

The electrical–thermal coupling integrated energy system (IES) has multi-timescale characteristics, and the gas–thermal slow dynamic characteristics of the IES contain rich flexibilities. The state of the gas–thermal system changes relatively with a time delay when the external conditions change, which can provide power support for the system over a certain timescale. Based on the gas–thermal inertia power support capability, a reliability assessment method of the IES considering gas–thermal inertia is proposed. According to research, the reliability assessment of the IES based on gas–thermal inertia can reduce the size and frequency of load shedding, alleviate the system operation risk caused by heavy load, reduce the system operation cost, and improve the system long-term operation reliability and economy. The greater the importance assessment index of energy conversion equipment, the greater its impact on system reliability, which is the weak node that should be focused on and protected.

Time-Dependent Reliability Assessment Method for RC Simply Supported T-Beam Bridges Based on Lateral Load Distribution Influenced by Reinforcement Corrosion

The safety and reliability of bridges gradually decrease over time under the influence of disadvantageous environmental factors, primarily due to reinforcement corrosion caused by chloride ingress. The traditional lateral load distribution (LLD) theory does not consider the influence of corrosion, which degrades the accuracy of bridge performance and reliability calculation. A time-dependent reliability assessment method for simply supported T-beam bridges is proposed in this paper, which considers the influence of reinforcement corrosion on LLD. Firstly, the steel corrosion process and degree are predicted based on the chloride ingress model, into which the water/cement ratio and concrete strength are innovatively introduced in order to improve the prediction accuracy. Secondly, the effective stiffness calculation method for corroded reinforcement bridges is established with the moment of inertia and section crack condition employed. Thirdly, the modified eccentric compression method is improved by the effective stiffness and iterative algorithm, which is suitable for the LLD calculation of corroded reinforcement bridges. The time-dependent vehicle load effect can be computed combined with the probability distribution of live load. Finally, the time-dependent reliability of the flexural bearing capacity is obtained by the Monte Carlo method and Bayesian theory without prior information. A simply supported bridge with five T-beams is taken as an example for analysis. It is indicated that the results calculated by the traditional reliability method are conservative, which cannot make a true and accurate evaluation. The method proposed in this paper can effectively reduce the assessment error caused by model uncertainty while considering the interaction between reinforcement corrosion and vehicle live load effect.

Analytical reliability evaluation method of smart micro‐grids considering the cyber failures and information transmission system faults

The reliability of smart micro-grids (SMGs), as a cyber-physical system (CPS), might be influenced by cyber failures and information transmission faults. Several Monte Carlo simulation (MCS)-based approaches have been reported to assess the reliability of SMGs and smart grids. On the other hand, analytical reliability assessment methods have been presented in some research works, while the cyber system has not been concerned. However, the literature shows a research gap in developing an accurate and fast reliability evaluation method for SMGs based on the unavailability of cyber elements and information transmission faults. This article tries to fill the discussed gap by adding the analytical modelling of cyber-physical interdependencies and information transmission faults to available analytical methods, focusing on physical uncertainties. Comparing the proposed model with existing MCS-based and analytical reliability evaluation methods illustrates the advantages of this research. Test results show that less than 5.7% expected energy not supplied (EENS) error occurs by the proposed method, which would be much faster than MCS-based ones. Moreover, the sensitivity analyses highlight the impacts of the cyber network topologies on the cyber-physical interdependencies.

Development of a comprehensive system for assessing the reliability of thermal power equipment

The article reveals the necessity of monitoring the reliability of the electric power system as a complex technical system. Based on the consideration of the main regulatory documents, governing the assessment of the reliability of thermal power equipment and electrical networks, the article indicates the imperfections of the available methods of reliability assessment. A proposed comprehensive reliability assessment system allows a detailed assessment of the reliability of a complex system. The reliability of the power unit of the thermal power plant (TPP) was estimated by the logical-probabilistic method using the domestic software package. The existing problems of forecasting reliability indicators at various technical impacts are considered to obtain reliable calculation results.

상대 관측 정보 신뢰도 판단을 통한 다중자율무인잠수정의 정밀한 위치 추정

This paper describes a reliability assessment of relative observations for multiple autonomous underwater vehicles (multiple-AUVs). Swarm control and collision avoidance, the primary issues of a multiple-AUV system, intrinsically need precise localization of Multiple-AUVs, and relative observations of each autonomous underwater vehicle (AUV) are critical to improving localization precision. However, because relative observations are usually measured by ultrasonic sensors, the reliability of sensor data varies depending on the characteristics of each AUVs’ trajectories, as implied in previous our study. Therefore, this paper proposed a reliability assessment method based on the trajectories of each AUV and integrated the derived reliability of relative observations into the multiple-AUV localization algorithm. Consequently, localization performance with real sea experimental data is improved up to 77.4% compared with the previous independent navigation algorithm of each AUV and 60.6% compared with the previous study without the reliability assessment. We conclude that the proposed method is suitable for precise localization through relative observations.

Morphological Component Analysis-Based Hidden Markov Model for Few-Shot Reliability Assessment of Bearing

Reliability is of great significance in ensuring the safe operation of modern industry, which mainly relies on data analysis and life tests. However, as the life of mechanical systems becomes increasingly longer with the rapid development of the manufacturing industry, the collection of historical failure data becomes progressively more time-consuming. In this paper, a few-shot reliability assessment approach is proposed in order to overcome the dependence on historical data. Firstly, the vibration response of a bearing was illustrated. Then, based on a vibration response analysis, a morphological component analysis (MCA) method based on sparse representation theory was used to decompose vibration signals and extract impulse signals. After the impulse components’ reconstruction, their statistical indexes were utilized as the input observation vector of a Mixture of Gaussians Hidden Markov Model (MoG-HMM) for a reliability estimation. Finally, the experimental dataset of an aerospace bearing was analyzed via the proposed method. The comparison results illustrate the effectiveness of the proposed method of a few-shot reliability assessment.

Reliability assessment of a floating offshore wind turbine mooring system based on the TLBO algorithm

Aiming at failure problems associated with floating offshore wind turbine (FOWT) mooring systems, a new reliability assessment method is established based on an intelligent algorithm. Using the NREL 5 MW OC4 semi-submersible wind turbine as the research object, the hydrodynamic is obtained, together with the aerodynamic, and axial tension forces of the mooring chains under different working gust conditions through integrated simulations. The intelligent teaching-learning-based optimization (TLBO) and improved teaching-learning-based optimization (ITLBO) algorithms are proposed to calculate the reliability of the FOWT mooring system. The results show that the reliability index of the windward chain is 4.21 under an extreme working gust, which is less than the code recommended value 4.26 and should be further evaluated. The penalty coefficient, teaching factor, and population number have a great impact on the convergence speed of the TLBO algorithm. Compared with traditional reliability algorithms, such as the first-order second-moment algorithm and Monte Carlo algorithm, the TLBO algorithm has higher efficiency, especially the ITLBO algorithm, which has the fastest convergence speed by constantly adjusting the teaching factor. Therefore, it is recommended to use the TLBO or ITLBO algorithm to evaluate the reliability of FOWT mooring systems.

Reliability of high-speed electric multiple units in terms of the expanded multi-state flow network

This paper proposes a new reliability assessment method for a high-speed electric multiple unit (HSEMU) system based on the expanded multi-state flow network. An HSEMU system is abstracted as a multi-layer multi-source multi-commodity multi-state flow network (M-LSCSFN), where minimum maintenance units (MMUs) and three types of connections form nodes and edges in different layers, and functional characteristics are regarded as network parameters. In the M-LSCSFN, multi layers describe different types of connections and their relationships; multi-source and multi-commodity reflect system features; whereas multi-state flow indicates the dynamic realization of system functions. Considering that an HSEMU system can be divided into multiple independent holistic functions, each holistic function has a corresponding sub-M-LSCSFN, and each layer of this sub-M-LSCSFN is a multi-source multi-commodity multi-state flow network (M-SCSFN). In order to assess system reliability, layer reliability (i.e., the M-SCSFN reliability) is first defined as the probability that the amounts of each commodity transmitted successfully from source nodes to sink nodes will not be less than the required demands. A corresponding algorithm is proposed to calculate layer reliability in terms of minimal paths (MPs) using the quick inclusion-exclusion technique (QIE). The sub-M-LSCSFN reliability is subsequently calculated based on the layer reliability and the conditional relationships among different layers. Based on these, the HSEMU system reliability is defined as the ability of a system to complete specified multiple functions under stated conditions for a specified period of time, and can be evaluated using the reliability of sub-M-LSCSFNs via the proposed operator. Finally, a case study of the “Fuxing” HSEMU system is analyzed to demonstrate the applicability of the proposed method and algorithm the effectiveness of the proposed method is demonstrated in an HSEMU system reliability assessment case study.

Reliability Assessment Method Based on Condition Information by Using Improved Proportional Covariate Model

If sufficient historical failure life data exist, the failure distribution of the system can be estimated to identify the system initial hazard function. The conventional proportional covariate model (PCM) can reveal the dynamic relationship between the response covariates and the system hazard rate. The system hazard rate function can be constantly updated by the response covariates through the basic covariate function (BCF). Under the circumstances of sparse or zero failure data, the key point of the PCM reliability assessment method is to determine the proportional factor between covariates and the hazard rate for getting BCF. Being devoid of experiments or abundant experience of the experts, it is very hard to determine the proportional factor accurately. In this paper, an improved PCM (IPCM) is put forward based on the logistic regression model (LRM). The salient features reflecting the equipment degradation process are extracted from the existing monitoring signals, which are considered as the input of the LRM. The equipment state data defined by the failure threshold are considered as the output of the LRM. The initial reliability can be first estimated by LRM. Combined with the responding covariates, the initial hazard function can be calculated. Then, it can be incorporated into conventional PCM to implement the reliability estimation process on other equipment. The conventional PCM and the IPCM methods are respectively applied to aero-engine rotor bearing reliability assessment. The comparative results show that the assessing accuracy of IPCM is superior to the conventional PCM for small failure sample. It provides a new method for reliability estimation under sparse or zero failure data conditions.