Residual Life Research Articles

Residual Life Prediction of Rotating Machinery Guided by Quantum Deep Neural Network

In order to avoid the low prediction rate and high evaluation rate in estimating the service balance life of rotating machinery, this paper presents a quantum gene chain encoded bidirectional neural network (QGCCBNN) for estimating the service balance life of rotating machinery. In QGCCBNN, quantum bidirectional transmission mechanism has been developed. In order to improve the global optimization ability and convergence speed, we have developed a quantum gene chain encoding method to transform the gradient descent into the data transmission and updating. Because of the advantages of QGCCBNN in nonlinear estimation ability and convergence speed, the proposed QGCCBNN for predicting the remaining service life of rotating machinery can achieve higher prediction precision and optimization.The predicted value of the proposed method for the remaining service life of double row roller bearings is 6.33h (actual value is 7.17h), with a prediction error of only 0.84h and a relative prediction error of only 11.72%. The experimental results demonstrate the effectiveness of the proposed method.

Safety Evaluation and Influential Factor Analysis of Urban Expressway Diversion Areas Based on Non-Stationary Conflict Extremes

To evaluate the safety conditions of expressway exit areas with different exit forms, a safety analysis method based on the conflict extreme model is proposed. Based on video data from four typical urban expressway diversion areas, longitudinal conflicts and lateral conflicts were identified using time to collision and cross time to collision methods, respectively, and traffic parameters such as traffic flow were extracted. A Bayesian hierarchical conflict extreme model for joint conflict types was constructed by integrating the peak over threshold and Bayesian hierarchical approach. The threshold for conflicts was determined using the mean residual life plot and the threshold stability plot. Subsequently, a logarithmic link function for the scale parameter was established by combining different covariates. Then, the model parameters were estimated using the Markov chain Monte Carlo simulation method. Finally, based on the fitted distribution, a comprehensive safety evaluation and influential factor analysis were conducted for each diversion area. The results show that an increase in traffic flow and the ratio of large vehicles leads to a higher probability of traffic accidents. However, an increase in the average speed reduces the probability of traffic accidents. The construction form of the diversion area and the number of off-ramp lanes do not demonstrate an explicit relationship with the probability of traffic accidents. The research conclusion indicates that the Bayesian hierarchical extreme model can effectively utilize short-term observed conflicts for long-term crash estimation, and it has the potential to be applied in the field of safety evaluation.

Studying the Structure of the Road Pavement and Specifying the Repair Method

Studying the structural condition of road pavement is essential for making effective decisions about the type of maintenance or rehabilitation that will be carried out on a pavement section. Reliable quantitative assessment of the volume of necessary repairs will ensure the performance characteristics and durability throughout the entire service life at minimal cost. This article presents detailed results from Falling Weight Deflectometer (FWD) and Ground Penetrating Radar (GPR) studies. In addition, an analysis of these results and recommendations for strengthening the road pavement for the Sh-176 “Sighnaghi-Saint Nino Monastery” road to develop rehabilitation and maintenance scenarios. FWD results combined with road pavement layer thickness and traffic load information to determine residual service life and necessary treatment type. Thus, using the nonlinear theory of layered halfspace elasticity, pavement structure analyzed in the same way as other civil engineering structures.

Prediction of Residual Life of In-Service P91 Steel Joints Based on Fracture Behavior.

P91 steel and P91 steel joints experience performance degradation after serving for 30,000 h in working conditions. To clarify the damage and failure behavior and remaining life of the joints during subsequent service, further creep testing was conducted on the welded joints of P91 steel that had been in service for 30,000 h at three temperatures: 550 °C, 575 °C, and 600 °C. The fracture surface and the cross-section damage behavior were characterized by SEM and EBSD methods. The results show that there are two types of fracture modes in the joints at different temperatures: ductile cracking occurring at the BM, and type IV cracking occurring in the FGHAZ. The threshold stress for fracture mode transition decreases with an increase in working temperature. Type IV cracking near the HAZ is the main reason for the premature failure of joints during service. And based on the fracture mode, the dual-constant L-M method was proposed to predict the strength of in-service joint materials. The testing data are discussed and classified based on the fracture mode in this method, which has high accuracy and can prevent the premature failure of joints.

Equilibrium Reinsurance Strategy and Mean Residual Life Function

Equilibrium Reinsurance Strategy and Mean Residual Life Function

Detecting and Estimating Local Corrosion Damages in Long-Service Aircraft Structures by the Eddy Current Method with Double-Differential Probes

ABSTRACT Monitoring corrosion in aircraft structures through nondestructive testing is crucial for maintaining long-term aircraft serviceability. Corrosion monitoring is particularly challenging when corrosion damage is situated on internal surfaces of multilayer aircraft structures. The eddy current method is one of the most promising techniques for detecting and measuring such subsurface corrosion damage without direct contact or disassembly. However, due to their low sensitivity traditional eddy current probes with coaxial coils are not well suited for detecting corrosion damages of the local type, such as pitting or corrosion pits, in multilayer aircraft structures. This study tested the use of low-frequency eddy current probes of the double-differential type, characterized by 8 and 10 mm operational diameters, in detecting and measuring hidden corrosion damages of this local type. Such corrosion damages were simulated by means of flat-bottomed drilled holes of differing diameters and depths (or different diameters and residual thicknesses of the inspected sheet in the damaged area). The signals from the eddy current probes were evaluated in the complex plane using a universal eddy current flaw detector. The correlations between the amplitude and phase of the eddy current signal and depth of location of the local corrosion damages were analyzed. Results indicate that it is possible to estimate the residual thickness of the skin in locally corroded areas by measuring the eddy current signal phase, independently of the local corrosion damage diameter (size), providing useful information for residual service life determination.

3D scanning techniques in power engineering

Information about component geometry is a key parameter for assessing residual life and monitoring degradation processes during the life cycle of a technology. High-precision optical measurement systems are complex metrology devices that enable the collection of complex data on the physical properties of components and their rapid evaluation in CAD-based programs. These solutions offer an analysis of changes in component characteristics over time and comparing them with as-built documentation. The quality of production can be evaluated by comparing the condition of the equipment with the product documentation or monitoring the influence of service conditions on the degradation of the equipment and the trend of future development of defects. All this in digital form of data, which enables new progressive approaches to repair and maintenance programs of monitored equipment. The use of advanced metrology and diagnostic systems and the procedures they offer can reduce the time required for measurement by conventional methods and multiply the data yield from metrology, which in conjunction with modern IT technologies can detect new degradation mechanisms and increase safety service and extend projected lifetime. Up-to-date technology data can significantly save on maintenance costs or even eliminate maintenance procedures. It also provides important data for the setup of LTO.

Residual Life Assessment of Steel Truss Bridge due to Coupled Action of Corrosion and Fatigue

Residual Life Assessment of Steel Truss Bridge due to Coupled Action of Corrosion and Fatigue

An extended Rayleigh Weibull model with actuarial measures and applications

In this article, we discuss a new extension of the Rayleigh-Weibull model using the Marshall-Olkin family of distributions. The proposed model is called the Marshall-Olkin-Rayleigh-Weibull (MORW) model. Various statistical properties of the MORW distribution are discussed, including explicit expressions for quantiles, moments, incomplete and conditional moments, some inequality measures, moment generating function, moments of the residual and reversed residual life, the Rényi entropy, and order statistics. Six different estimation methods are considered to investigate the behavior of the model parameters within the MORW model. A Monte Carlo simulation study is conducted to evaluate the performance of these different estimators. In addition, some actuarial measures, such as the Value-at-Risk, the expected shortfall, the tail Value-at-Risk, the tail variance, the tail variance premium, the tail conditional expectation, and the tail standard deviation premium, are calculated. Finally, applying the model to real data sets illustrates the applicability and usefulness of the MORW distribution.

Разработка методики диагностирования и определения остаточного ресурса механических демпферов крутильных колебаний машинно-движительных комплексов судов

Import substitution issues in modern conditions remain an urgent topic today, especially in terms of periodic maintenance of mechanical torsional vibration dampers of foreign manufacture (they are also called spring dampers). Diagnostics of such devices is impossible due to the influence of sanctions against Russia, namely, in the absence of the possibility of the arrival of defect specialists from leading specialized organizations and manufacturing plants. A method for developing a model mechanical damper is presented, taking into account all conditions of similarity: geometric, kinematic and dynamic. Through the use of modern Autodesk Fusion 360 software, a digital model of a real Geislinger marine damper model D90/37 (Austria) has been developed. The results of diagnostics of the Kogalym and Langepas ship propulsion systems, which include mechanical dampers, are also reflected, and the dynamics of changes in torsional vibration parameters is analyzed. It is noted that non-selective diagnostics (torsiography procedure) is possible only in coordination with the supervisory authorities, usually with a small operating time of the damper. All further diagnostics are allowed only if there is an approved standard methodology, which currently does not exist, which confirms the relevance of the chosen research topic. An initial version of the methodology for diagnosing and determining the residual life of mechanical torsional vibration dampers of ship propulsion systems is presented.

Modeling to COVID-19 and cancer data: Using the generalized Burr-Hatke model

This paper describes an extended version of the Burr–Hatke distribution via generalizing its survival function. This model is called as the generalized Burr-Hatke distribution. The suggested model's hazard rate function can be non-increasing (decreasing) form. Related statistical characteristics of the proposed model are identified. We provide closed-form expressions for the density function, hazard rate function, moments and their related metrics. In addition, some of the proposed model's reliability attributes, such as mean residual life and mean inactivity time, are determined both empirically and visually. The characterization of GBH model based on hazard rate, truncated and conditional moments is also provided. The maximum likelihood technique is employed for estimating the unknown model parameters. To explore the behavior of the estimates, Monte Carlo Simulation can be used. Finally, the new model's performance is verified using two sets of real data.

Rolling Bearing Residual Useful Life Prediction Model Based on the Particle Swarm Optimization-Optimized Fusion of Convolutional Neural Network and Bidirectional Long–Short-Term Memory–Multihead Self-Attention

Rolling Bearing Residual Useful Life Prediction Model Based on the Particle Swarm Optimization-Optimized Fusion of Convolutional Neural Network and Bidirectional Long–Short-Term Memory–Multihead Self-Attention

Integrated structural and energy building retrofit by reinforced concrete wall addition

In light of the paramount considerations of environmental sustainability and the protection of both life and property, a significant number of existing reinforced concrete (RC) buildings fall short of meeting contemporary standards in terms of their structural and energy performances. In response to these pressing concerns, there is an imperative need for comprehensive building retrofitting processes that integrate both structural and energy considerations. One such approach, the addition of RC walls, is commonly employed as a structural retrofitting technique. However, its potential to enhance overall building efficiency has been relatively underexplored in previous research. In this study, we focus on a representative RC building and utilize two key performance indices: structural residual life and energy consumption, to comprehensively evaluate the impact of RC wall retrofitting on both structural and energy performance. Our investigation considers retrofitting on both the exterior and interior sides of the building. It is observed that the structural performance exhibits notable improvement with the addition of RC walls on either side, and this improvement becomes even more pronounced when complemented by local retrofits to adjacent beams. While the RC walls added on the interior side have negligible impact on the building energy efficiency, those installed on the exterior side could obviously reduce the energy consumption of the HVAC system by 7.9%. Hence, the outcomes of this study indicate that employing the RC wall retrofitting on the exterior side of the existing building is an efficient way to reach structural and energy performance targets simultaneously.

ON THE MOMENTS OF THE 3-PARAMETER GOMPERTZ DISTRIBUTION

Gompertz distribution is a classical probability distribution extensively used in actuarial science, reliability, and survival analysis. Gompertz distribution also plays a role in various fields, such as biology, economics, and marketing analysis. Some extensions of this distribution have been studied and applied to various problems. In this article, we are concerned with some statistical properties of a 3-parameter Gompertz distribution. This extension of the Gompertz distribution introduced has been used in studying competing risk survival analysis. Our main results are the derivation of moments of this distribution and other statistical properties related to moments, such as moment generating function, mean residual life function, mean inactivity time and Lorenz curve. These results will serve as a complement to the theoretical aspect of the analysis of the distribution.

Additional study of failure behavior for ship propeller: The comparative analysis of life evaluation approaches between BP neural network, LSTM and TV-HSMM

The study focuses on investigating the appropriate method for evaluating the residual life of a propeller and analyzing its fracture characteristics. A fluid-structure interaction simulation is conducted to qualitatively analyze the stress distribution of the propeller during operation, identifying regions prone to stress concentration. Subsequently, fracture surface characteristics are examined, revealing quasi-cleavage fracture features such as tongue striations, dimples, and tearing ridges in the initiation and propagation regions. Additionally, composite fracture characteristics and geometric mutations are observed on the edge of the fracture surface. Three residual life evaluation methods are then proposed, utilizing BP neural network, LSTM, and TV-HSMM. Comparative analysis suggests that the TV-HSMM method offers the advantage of minimal error in residual life evaluation. However, the models based on BP neural network and LSTM are preferred for their lower average error and distribution trends that closely resemble actual life data.

Reliability and Residual Life of Cold Standby Systems

In this study, we conduct a reliability characterisation study of cold standby systems. Utilising synthetic rectangular formulas and cold preparedness equivalent models for cold standby systems, we analyse the lifetimes of several typical configurations, including series, parallel, and k/n:m voting systems. This study proposes system equivalent models for various types of cold standby systems, all composed of components that follow the same exponential distribution. We use the equivalent model to determine the optimal timing for the use of cold spares and derive the reliability function and residual lifetime function for each type of system. To demonstrate the validity of our model, the Monte Carlo simulation is strategically designed based on the system failure rate function. The experimental results are then compared with those obtained from the numerical model, highlighting that the numerical method incurs a lower time cost.

A Remaining Useful Life Prediction Method of Mechanical Equipment Based on Particle Swarm Optimization-Convolutional Neural Network-Bidirectional Long Short-Term Memory

In industry, forecast prediction and health management (PHM) is used to improve system reliability and efficiency. In PHM, remaining useful life (RUL) prediction plays a key role in preventing machine failures and reducing operating costs, especially for reliability requirements such as critical components in aviation as well as for costly equipment. With the development of deep learning techniques, many RUL prediction methods employ convolutional neural network (CNN) and long short-term memory (LSTM) networks and demonstrate superior performance. In this paper, a novel two-stream network based on a bidirectional long short-term memory neural network (BiLSTM) is proposed to establish a two-stage residual life prediction model for mechanical devices using CNN as the feature extractor and BiLSTM as the timing processor, and finally, a particle swarm optimization (PSO) algorithm is used to adjust and optimize the network structural parameters for the initial data. Under the condition of lack of professional knowledge, the adaptive extraction of the features of the data accumulated by the enterprise and the effective processing of a large amount of timing data are achieved. Comparing the prediction results with other models through examples, it shows that the model established in this paper significantly improves the accuracy and efficiency of equipment remaining life prediction.

Some New Results on Stochastic Comparisons of Spacings of Generalized Order Statistics from One and Two Samples

Generalized order statistics (GOSs) are often adopted as a tool for providing a unified approach to several stochastic models dealing with ordered random variables. In this contribution, we first recall various useful results based on the notion of total positivity. Then, some stochastic comparisons between spacings of GOSs from one sample, as well as two samples, are developed under the more general assumptions on the parameters of the model. Specifically, the given results deal with the likelihood ratio order, the hazard rate order and the mean residual life order. Finally, an application is demonstrated for sequential systems.

Cyclic response and residual life prediction of Inconel 718 superalloy after overloading under hybrid stress-strain controlled creep-fatigue loading

Inconel 718 is a material for manufacturing turbine disks, which is subjected to complex loads of creep-fatigue during service. This paper examines the effect of constant stress overloading at various lifespan stages on subsequent cyclic deformation, fracture behavior, and residual lifetime in hybrid stress and strain-controlled creep-fatigue interaction (HCFI) experiments conducted at 650℃. Overloading of 800 MPa constant stress with 180 min dwell time is applied at the 10 %, 25 %, 50 %, 65 %, and 70 % lifespan of HCFI tests. Results show that overloading reduces the residual life of the material obviously and makes a significant impact on the subsequent creep-fatigue deformation behavior, and additional damage is induced when overloading is applied towards the end of the lifespan. Moreover, more severe grain boundary damage leading to the final intergranular fracture is identified through microstructural analysis following overloading. Finally, equivalent damage is proposed to quantify the creep-fatigue damage affected by overloading, resulting in accurate life prediction outcomes.

Expérience du Sénégal sur les pacemakers reconditionnés : à propos de 161 patients au centre hospitalo-universitaire Aristide Le Dantec

IntroductionThe reuse pacemakers is a beneficial technique for patients in countries with a low economic standard of living where health care is almost non-existent. We offered to share the experience of Senegal on the reconditioning of pacemakers. MethodologyWe conducted a retrospective study over a period from January 2015 to December 2020 including all patients who benefited from a reconditioned pacemaker for primary implantation or reimplantation. The criteria for reconditioning pacemakers are the absence of dysfunction or damage and a residual battery life of more than 5 years of the pacemaker. Refurbished pacemakers are acquired either from deceased families or from extraction centers. Sterilization is carried out using phenoxypropanol + benzalkonium chloride solution, 70% ethanol and ethylene oxide. ResultsWe collected 161 patients during the study period, including 77 men (48%) and 84 women (52%), i.e. a M/F sex ratio of 0.94. The average age of the population was 65 years. Functional symptomatology was dominated by syncope in 54%. Electrocardiographically, 72% of patients were in complete atrioventricular block. A primary implantation was noted in 91.5% of patients. The vascular approach most used during implantation was cephalic in 49.5% of cases. In our series, we noted that 58% of patients had benefited from temporary stimulation before implantation. At implantation, single-chamber stimulation was used in 60% of patients and 46.5% of patients had programming in VVI mode. We had 5.5% major complications with 3% box infection occurring between 3 and 6 months post-implantation and 2.5% pacemaker syndrome. We noted 1 case of death linked to underlying heart disease. ConclusionReconditioning of cardiac pacemakers is a safe and beneficial therapeutic strategy for patients. In Senegal, reconditioning has shown satisfactory results. In our countries this technique can be an alternative for certain patients.