Availability of Systems Subject to Multiple Failure Modes Under Calendar-based Inspection

2020 ◽  
pp. 2150022
Author(s):  
Himani Pant ◽  
S. B. Singh ◽  
Neelam Chantola
Keyword(s):  
Wind Turbine ◽  
Failure Mode ◽  
Functional State ◽  
Failure Modes ◽  
Failure Time ◽  
Random Time ◽  
Multiple Failure Modes ◽  
Periodic Inspection ◽  
Wind Turbine System ◽  
Inspection Policy

The availability of a maintained system subject to multiple failure modes undergoing periodic inspection is studied in this paper. Calendar-based inspection policy is being incorporated. Explicitly, a system with a functional state and [Formula: see text] failure modes is taken into account. Failure time of each failure mode is random. As the [Formula: see text]th ([Formula: see text]) failure occurs, the respective corrective repair taking a random time [Formula: see text] [Formula: see text] is carried out. Some theorems on the point availability and limiting average availability are obtained in this study. The application of the derived result is explained through an example of wind turbine system.

Progress on the Development of a Holistic Coupled Model of Dynamics for Offshore Wind Farms: Phase I — Aero-Hydro-Servo-Elastic Model, With Drive Train Model, for a Single Wind Turbine

2018 ◽  
Author(s):  
Z. Lin ◽  
D. Cevasco ◽  
M. Collu
Keyword(s):  
Wind Turbine ◽  
Failure Mode ◽  
Wind Turbines ◽  
Wind Farm ◽  
Failure Modes ◽  
Coupled Model ◽  
Offshore Wind ◽  
Offshore Wind Turbine ◽  
Elastic Model ◽  
Offshore Wind Turbines

Currently, around 1500 offshore wind turbines are operating in the UK, for a total of 5.4GW, with further 3GW under construction, and 13GW consented. Until now, the focus of the research on offshore wind turbines has been mainly on how to minimise the CAPEX, but Operation and maintenance (O&M) can represent up to 39% of the lifetime costs of an offshore wind farm, due mainly to the high cost of the assets and the harsh environment, limiting the access to these assets in a safe mode. The present work is a part of a larger project, called HOME Offshore (www.homeoffshore.org), and it has as aim an advanced interpretation of the fault mechanisms through a holistic multiphysics modelling of the wind farm. The first step (presented here) toward achieving this aim consists of two main tasks: first of all, to identify and rank the most relevant failure modes within a wind farm, identifying the component, its mode of failure, and the relative environmental conditions. Then, to assess (for each failure mode) how the full-order, nonlinear model of dynamics used to represent the dynamics of the wind turbine can be reduced in order, such that is less computationally expensive (and therefore more suitable to be scaled up to represent multiple wind turbines), but still able to capture and represent the relevant dynamics linked with the inception of the chosen failure mode. A methodology to rank the failure modes is presented, followed by an approach to reduce the order of the Aero-Hydro-Servo-Elastic (AHSE) model of dynamics adopted. The results of the proposed reduced-order models are discussed, comparing it against the full-order coupled model, and taking as case study a fixed offshore wind turbine (monopile) in gearbox failure condition.

scholarly journals Addition laws of failure probability and their applications in reliability analysis of structural system with multiple failure modes

2012 ◽  
Vol 227 (1) ◽  
pp. 120-136 ◽  
Author(s):  
Pengfei Wei ◽  
Zhenzhou Lu ◽  
Longfei Tian
Keyword(s):  
Linear Programming ◽  
Failure Mode ◽  
Failure Probability ◽  
Failure Modes ◽  
Programming Model ◽  
Small Scale ◽  
Structural System ◽  
Third Order ◽  
Multiple Failure Modes ◽  
Basic Principles

Compared with the methods solving failure probability of the structural system with multiple failure modes, those solving failure probability of a single failure mode are simpler and more well-developed, thus in order to employ the latter to establish the former, the addition laws of the failure probability are derived mathematically by use of the basic principles of probability theory. In the derived addition laws, the failure probability of the structural system with n failure modes is expressed as a combination of the failure probabilities of 2 n−1 single failure modes. Therefore, the failure probability of the structural system with multiple failure modes can be solved by the well-developed methods for the failure probability of a single failure mode. After reviewing the boundary theories, such as the second-order boundary, the third-order boundary, and the linear programming based boundary for analyzing the failure probability of the structural system with multiple failure modes, the derived addition laws are applied to evaluate several former order joint failure probability involved in those boundary theories. Additionally, a new small-scale linear programming based boundary theory which can sufficiently reduce the scale of the linear programming model involved is proposed. Two numerical examples, including a series and a parallel structural system, are employed to demonstrate the accuracy and efficiency of proposed techniques.

Failure Mode and Effects Analysis of Compressor Blades of Aeroengines Using Dempster-Shafer Evidence Theory

2011 ◽  
Author(s):  
Jianping Yang ◽  
Hong-Zhong Huang ◽  
Li-Ping He ◽  
Dunwei Wen ◽  
Shun-Peng Zhu
Keyword(s):  
Failure Mode ◽  
Failure Modes ◽  
Evidence Theory ◽  
Mean Value ◽  
Multiple Sources ◽  
Multiple Failure Modes ◽  
Compressor Blades ◽  
Priority Order ◽  
Multiple Experts ◽  
Evaluation Information

Compressor blades are a major component of an aeroengine. Failure mode and effects analysis (FMEA), especially, the risk priority order of failure modes, is essential in its design. The risk priority number (RPN) has been extensively used to the risk priority order of failure modes. When multiple experts give their different risk evaluation information to one failure mode, which may be imprecise and uncertain, the traditional RPN cannot deal with the problem. In this paper, the modified Dempster-Shafter (D-S) is adopted to aggregate the different evaluation information by considering multiple experts’ evaluation opinions, multiple failure modes and three risk factors respectively. The simplified discernment frame is proposed according to the practical application. Moreover, the mean value of the new RPN is used to risk priority order of multiple failure modes. Finally, the method is used to deal with the risk priority evaluation of the failure modes of compressor blades of an aeroengine under multiple sources of different and uncertain evaluation information. The consequence of the method is rational and efficient.

Statistical Analysis of Linear Degradation and Failure Time Data with Multiple Failure Modes

2004 ◽  
Vol 10 (1) ◽  
pp. 65-81 ◽  
Author(s):  
Vilijandas Bagdonavičius ◽  
Algimantas Bikelis ◽  
Vytautas Kazakevičius
Keyword(s):  
Statistical Analysis ◽  
Failure Modes ◽  
Failure Time ◽  
Failure Time Data ◽  
Time Data ◽  
Multiple Failure Modes

scholarly journals A Fuzzy-FMEA Risk Assessment Approach for Offshore Wind Turbines

2020 ◽  
Vol 4 (3) ◽  
Author(s):  
F. Dinmohammadi ◽  
M. Shafiee
Keyword(s):  
Risk Factors ◽  
Wind Turbine ◽  
Failure Mode ◽  
Failure Modes ◽  
Wind Farms ◽  
Offshore Wind ◽  
Mode Analysis ◽  
Offshore Wind Turbine ◽  
Relative Importance ◽  
Fuzzy Fmea

Failure Mode and Effects Analysis (FMEA) has been extensively used by wind turbine assembly manufacturers for risk and reliability analysis. However, several limitations are associated with its implementation in offshore wind farms: (i) the failure data gathered from SCADA system is often missing or unreliable, and hence, the assessment information of the three risk factors (i.e., severity, occurrence, and fault detection) are mainly based on experts’ knowledge; (ii) it is rather difficult for experts to precisely evaluate the risk factors; (iii) the relative importance among the risk factors is not taken into consideration, and hence, the results may not necessarily represent the true risk priorities; and etc. To overcome these drawbacks and improve the effectiveness of the traditional FMEA, we develop a fuzzy-FMEA approach for risk and failure mode analysis in offshore wind turbine systems. The information obtained from the experts is expressed using fuzzy linguistics terms, and a grey theory analysis is proposed to incorporate the relative importance of the risk factors into the determination of risk priority of failure modes. The proposed approach is applied to an offshore wind turbine system with sixteen mechanical, electrical and auxiliary assemblies, and the results are compared with the traditional FMEA.

Research on Compilation Method of Multi-Axial Loading Spectrum for Cylindrical Shock Absorber

2017 ◽  
Vol 24 (05) ◽  
pp. 1750023 ◽  
Author(s):  
Qi Gao ◽  
Jinzhi Feng ◽  
Songlin Zheng ◽  
Xuyun Qiu
Keyword(s):  
Failure Mode ◽  
Failure Modes ◽  
Failure Time ◽  
Axial Loading ◽  
Bench Test ◽  
Cylinder Wall ◽  
Vertical Loading ◽  
Field Samples ◽  
The Mean ◽  
Loading Spectrum

The main failure mode of cylindrical shock absorbers (CSAs) used by taxis in China’s Zhejiang Province is oil leakage because of a large horizontal force loaded on the cylinder wall by a questionnaire survey. The previous CSA durability bench test methods, which do not involve the interaction between horizontal load and vertical load and do not consider the user road spectrum, cannot simulate the real fatigue phenomena of it. In order to preferably reproduce the failure mode and accurately to predict the failure time of the CSA used in the area, a compilation method of multi-axial loading spectrum is proposed based on the road spectrum. The vertical loading spectrum is compiled by using the way of sine on sine, in which high frequency (HF) signal superimposed on low frequency (LF) signal. The LF is determined by the half-power bandwidth theory, which can reflect the power spectral density distribution of the random road spectrum. The HF is determined by the maximum line velocity principle to effectively reduce test time. The loading cycles and amplitudes of them are determined by using the rain-flow counting method. In addition, the horizontal loading force is taken into consideration in the multi-axial loading spectrum. To prove the validation and efficiency of the method described in this paper, the compiled multi-axial loading spectrum was used to conduct the durability bench test. The results show that the mean failure mileage of specimens is close to the mean mileage time of field samples. The failure modes of the specimens are the same as those of field samples. Thus the proposed method can be used as a reference for durability bench test of CSA. The test data can also be used to accurately study the reliability of CSA.

Combine Nanoprobing Technique with Difference Analysis to Identify Nonvisual Failures

2006 ◽  
Author(s):  
Cha-Ming Shen ◽  
Tsan-Cheng Chuang ◽  
Jie-Fei Chang ◽  
Jin-Hong Chou
Keyword(s):  
Failure Mode ◽  
Failure Modes ◽  
Electrical Characteristic ◽  
The Novel ◽  
Difference Analysis ◽  
Original Idea ◽  
Deductive Method ◽  
Complete Measurement

Abstract This paper presents a novel deductive methodology, which is accomplished by applying difference analysis to nano-probing technique. In order to prove the novel methodology, the specimens with 90nm process and soft failures were chosen for the experiment. The objective is to overcome the difficulty in detecting non-visual, erratic, and complex failure modes. And the original idea of this deductive method is based on the complete measurement of electrical characteristic by nano-probing and difference analysis. The capability to distinguish erratic and invisible defect was proven, even when the compound and complicated failure mode resulted in a puzzling characteristic.

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