scholarly journals Reliability Assessment with Varying Operating Conditions

Procedia CIRP ◽  
2016 ◽  
Vol 50 ◽  
pp. 796-801
Author(s):  
Julia Lindén ◽  
Anders Söderberg ◽  
Ulf Sellgren
Author(s):  
Марина Николаевна Ильина ◽  
Дмитрий Васильевич Ларюшкин

Источником информации о техническом состоянии трубопроводов тепловых сетей объектов магистральных нефтепроводов ПАО «Транснефть» являются результаты их обслуживания и ремонта, технического освидетельствования, гидравлических испытаний и т. д. На основании этих данных проводятся расчеты показателей надежности, по итогам анализа которых осуществляется планирование дальнейшего технического обслуживания и ремонта. Однако при оценке надежности систем теплоснабжения необходимо учитывать не только срок эксплуатации и величину амортизационного износа, но и реальное состояние в конкретных условиях функционирования. Учесть многообразие факторов, которые влияют на работоспособность трубопроводов системы теплоснабжения, и тем самым повысить точность расчетов при оценке их остаточного ресурса позволяет применение кластерного анализа в дополнение к используемой методике оценки надежности тепловых сетей. В рамках настоящей работы оценка надежности объектов АО «Связьтранснефть» с применением кластерного анализа проведена на примере равнозначных участков тепловых сетей двух узлов связи, расположенных в Краснодарском крае и Республике Саха (Якутия). Currently, information about technical condition of pipelines of heat supply systems at the facilities of the main oil pipelines of PJSC Transneft is formed based on the results of maintenance and repair, technical inspection, hydraulic tests, etc. Upon these data, calculations of reliability indicators of heat networks are carried out, based on the analysis of calculations further maintenance and repairs are planned. However, when assessing the reliability of heat supply systems, it is necessary to take into account not only the service life and the amount of depreciation wear of heat network elements, but also their real state in specific operating conditions. The use of cluster analysis in addition to the currently used method of heat network reliability assessment allows us to take into account the variety of factors that affect the operability of pipelines of the heat supply system, and thereby increase the accuracy of calculations when assessing their residual resource. Within the framework of this work, the reliability assessment of Svyaztransneft JSC facilities using cluster analysis was carried out on the example of equivalent sections of heat networks of two communication nodes located in the Krasnodar Territory and the Republic of Sakha (Yakutia).


10.29007/m56l ◽  
2018 ◽  
Author(s):  
Orazio Giustolisi

Mechanical reliability refers to the assessment of the capacity of the water distribution network (WDN) to provide a correct service to the different type of costumers under abnormal operating conditions due to a failure of a system component. It depends on the effectiveness of the isolation valve system (IVS) and on the failure probability of components. Starting from the calculation of the actual customer demands during abnormal operating conditions of the hydraulic systems due to valve shutdowns and the failure probability of the separated segments, the work develops a metric for WDN reliability assessment. The finding is that the topologic part of WDN reliability assessment, relating to the IVS, is based on the risk of disconnection. Starting from it, the works develops a special modularity index for IVS reliability assessment.


2021 ◽  
Vol 19 (1) ◽  
pp. 47-52
Author(s):  
Doru LUCULESCU ◽  

This paper analyzes a method of evaluating the reliability of the rolling bearing in anti-aircraft guns. In evaluating its reliability, the factors that depend on the operating conditions of the anti-aircraft gun are taken into account, as well as the factors of design, technology, materials and assembly


2020 ◽  
Vol 12 (1) ◽  
pp. 168781402090359
Author(s):  
Binjie Wang ◽  
Shouguang Sun ◽  
Shuang Ma ◽  
Xi Wang

Fatigue cracks developed on subway train bogie frames before reaching the designed lifetime, which poses great challenges to operational safety. This article presents a structural fatigue reliability assessment method combining both the in-service measurement of dynamic stress and probabilistic approach for lifetime prediction. It was found that curved interval with rail corrugation can induce the elastic vibration and the modal stress on the frame, which caused the accelerated accumulation of the fatigue damage. The predicted failure mileage for the welding joint with 99% reliability was only 340,000 km, which agreed well with the real operation situation.


2015 ◽  
Vol 56 ◽  
Author(s):  
Tomas Iešmantas ◽  
Robertas Alzbutas

It is often the case that data used for the systems reliability assessment comes from more than one information source. Whether they are power plants at different geographical locations, gas transmission pipelines operating in different environment or power transmission networks deployed within various areas. Therefore, different operating conditions, varying maintenance programs and efficiencies have its share in influencing the vulnerability and variability of reliability data. However, in practice it is usually the case that this heterogeneity is neglected leading to the underestimation of underlying uncertainty of the data. Bayesian models are capable of dealing with this kind of uncertainty as opposedto the frequentists statistical methods. Hierarchical Bayesian modelling technique provides means to quantify not only within-source, but also between-source uncertainties. Even in the case of small data samples it performs well, unlike for example the classical likelihood method which may provide degenerate estimates. In this paper authors investigate the possibility to incorporate this kind of uncertainty into the systems reliability and vulnerability assessment through the Bayesian framework in several cases: gas transmission networks and power transmission grids.


Author(s):  
Shenglei Du ◽  
Jingmei Guo ◽  
Lin Yi ◽  
Chen Zhang ◽  
Shi Liu

Abstract The high cost of operation and maintenance (O&M) management has become an important factor hindering the sustainable development of the wind power industry. Performing accurate condition assessment of wind turbine components to optimize the structural design and O&M strategy has become a research trend. However, the random and varying operating conditions of wind turbines make this problem difficult and challenging. A Supervisory Control and Data Acquisition (SCADA) system collects signals that contain a large amount of raw and useful information from critical wind turbine sub-assemblies. Extracting key information from the SCADA data is an economical and effective way for condition assessment. A real-time reliability assessment method of wind turbine components using a Back-Propagation Neural Network (BPNN) and SCADA data is presented in this paper. The normal behavior models are established with the processed SCADA data, and the real-time reliability of wind turbine components are assessed based on the prediction result. For verification, the BPNN-based reliability assessment method is applied to a gearbox with real SCADA data of a 1.5MW onshore wind turbine located along the southeast coast of China. The results show the capability of the proposed model in assessing the reliability of wind turbine components continuously and in real time.


2020 ◽  
Vol 140 ◽  
pp. 1-13
Author(s):  
Nima Golestani ◽  
Rouzbeh Abbassi ◽  
Vikram Garaniya ◽  
Mohsen Asadnia ◽  
Faisal Khan

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
M. López-Campos ◽  
F. Kristjanpoller ◽  
P. Viveros ◽  
R. Pascual

Experience reveals that reliability varies depending on the characteristics of operation. The manufacturing process based on multifunction equipment gives a usual case of variation in operating conditions. This work presents a methodology for the reliability analysis of multifunction processes, using the RCM approach, and a modification of the Universal Generating Function (UGF) under a massive manufacturing context. The result is a characterization of reliability, for each piece of equipment and for the production system. The methodology is applied in a workshop of a textile industry, where there is prior evidence that the failure behavior varies according to the type of function executed by multifunction machines.


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