基于mpps 模型的机电系统故障传播路径搜索方法

Wang, Yanhui; Li, Man; Shi, Hao

doi:10.1007/s11771-018-3908-3

Cited by 6 publications

(4 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…(2) Parameter estimation of components fault probability model Assumed that components of CNC machine tool are respectively subject to Weibull distribution [24], then component reliability function and fault probability function are respectively as follows:…”

Section: Modeling Of Component Fault Probabilitymentioning

confidence: 99%

Key fault propagation path identification of CNC machine tools based on maximum occurrence probability

Zhang¹,

Zhou²,

Yang³

et al. 2023

Eksploatacja i Niezawodność – Maintenance and Reliability

View full text Add to dashboard Cite

In order to revise the deviation caused by ignoring the dynamic character of fault propagation in traditional fault propagation path identification methods, a method based on the maximum occurrence probability is proposed to identify the key fault propagation path. Occurrence probability of fault propagation path is defined by dynamic importance, dynamic fault propagation probability and fault rate. Taking the fault information of CNC machine tools which subject to Weibull distribution as an example, this method has been proven to be reasonable through comparative analysis. Result shows that the key fault propagation path of CNC machine tools is not unique, but changes with time. Before 1000 hours, key fault propagation path is electrical component (E) to mechanical component (M); after 1000 hours, key fault propagation path is auxiliary component (A) to mechanical component (M). This change should be taken into account when developing maintenance strategies and conducting reliability analysis.

show abstract

Section: Modeling Of Component Fault Probabilitymentioning

confidence: 99%

Key fault propagation path identification of CNC machine tools based on maximum occurrence probability

Zhang¹,

Zhou²,

Yang³

et al. 2023

Eksploatacja i Niezawodność – Maintenance and Reliability

View full text Add to dashboard Cite

show abstract

“…The specific solution steps are as follows. For function failures and propagation problems, Krus and Grantham [40] analyzed the propagation of failures through function failure chains to improve design defects; Kurtoglu et al [41] proposed an FFIP (function failure propagation mode) to analyze the three elements of functional modeling, behavior simulation and failure reasoning; Wang et al [42] proposed a failure propagation path search approach for electromechanical systems; Mehrpouyan et al [43] introduced an MFIP (model-based failure identification and propagation) framework in avionics systems to identify security issues caused by environmental disturbances and subsystem failures.…”

Section: Conceptual Design Failure Risk Analysismentioning

confidence: 99%

“…Step D4: The speed regulation schemes are sorted based on Q r , and the rank results are verified by Equation (42), so as to select the scheme with the best comprehensive benefits and the least risk.…”

Section: The Optimal Scheme Decision Based On Vikor Model With Considmentioning

confidence: 99%

Conceptual Scheme Decision Model for Mechatronic Products Driven by Risk of Function Failure Propagation

Jing

Sun

et al. 2020

Sustainability

View full text Add to dashboard Cite

Reliability is a major performance index in the electromechanical product conceptual design decision process. As the function is the purpose of product design, the risk of scheme design is easy to be caused when there is a failure (i.e., function failure). However, existing reliability analysis models focus on the failure analysis of functions but ignore the quantitative risk assessment of conceptual schemes when function failures occur. In addition, design information with subjectivity and fuzziness is difficult to introduce the risk index into the early design stage for comprehensive decisions. To fill this gap, this paper proposes a conceptual scheme decision model for mechatronic products driven by the risk of function failure propagation. Firstly, the function structure model is used to construct the function fault propagation model, so as to obtain the influence degree of the subfunction failure. Secondly, the principle solution weight is calculated when the function failure is propagated, and the influence degree of the failure mode is integrated to obtain the severity of the failure mode on the product system. Thirdly, the risk value of failure mode is calculated by multiplying the severity and failure probability of failure mode, and the risk value of the scheme is obtained based on the influence relationship between failure modes. Finally, the VIKOR (Višekriterijumska Optimizacija i kompromisno Rešenje) method is used to make the optimal decision for the conceptual scheme, and then take the cutting speed regulating device scheme of shearer as an example to verify the effectiveness and feasibility of the proposed decision model.

show abstract

“…And Liu et al 4 focused on concerns with the echo state networks (ESNs) based adaptive sensor fault propagation mechanism in the data-based framework. Xu et al 5,6 adopted the ant colony algorithm and different network models to find all possible fault propagation paths. Moreover, a causality graph was proposed by Dong et al 7 to tackle with fault location and propagation path identification.…”

Section: Introductionmentioning

confidence: 99%

A framework for modeling fault propagation paths in air turbine starter based on Bayesian network

Guo

Wang

2021

Proceedings of the Institution of Mechanical Engineers, Part O:

View full text Add to dashboard Cite

Any minor fault may spread, accumulate and enlarge through the causal link of fault in a closed-loop complex system of civil aircraft, and eventually result in unplanned downtime. In this paper, the fault propagation path model (FPPM) is proposed for system-level decomposition and simplifying the process of fault propagation analysis by combining the improved ant colony optimization algorithm (I-ACO) with the Bayesian network (BN). In FPPM, the modeling of the fault propagation path consists of three models, namely shrinking model (SM), ant colony optimization model (ACOM), and assessment model (AM). Firstly, the state space is shrunk by the most weight supported tree algorithm (MWST) at the initial establishment stage of BN. Next, I-ACO is designed to improve the structure of BN in order to study the fault propagation path accurately. Finally, the experiment is conducted from two different perspectives for the rationality of the well-trained BN’s structure. An example of practical application for the propagation path model of typical faults on the A320 air turbine starter is given to verify the validity and feasibility of the proposed method.

show abstract

基于mpps 模型的机电系统故障传播路径搜索方法

Cited by 6 publications

References 30 publications

Key fault propagation path identification of CNC machine tools based on maximum occurrence probability

Key fault propagation path identification of CNC machine tools based on maximum occurrence probability

Conceptual Scheme Decision Model for Mechatronic Products Driven by Risk of Function Failure Propagation

A framework for modeling fault propagation paths in air turbine starter based on Bayesian network

Contact Info

Product

Resources

About