Analysis of traffic safety in airport aircraft activity areas based on bayesian networks and fault trees

To assess road traffic safety risk in civil aviation airports and develop effective accident prevention measures,this study proposed a risk assessment method based on accident tree and Bayesian network for airport aircraft activity areas.It identified influencing factors in the aircraft activity area from the perspectives of person-vehicle-road-environment-management and analyzed their relationships.The Bayesian network was utilized to determine initial probabilities for each influencing factor.Findings indicated a relatively high overall safety level in the airport's road traffic system.Accident trees were employed to qualitatively and quantitatively analyze common human-vehicle accident patterns.The initial probabilities obtained from the Bayesian network served as basic event probabilities in the accident tree to determine the occurrence probability of the top event.Taking a 4F airport in China as an example,accident cause analysis identified five important risk sources in human-vehicle accidents,including blind spots for special vehicles,illegal driving by drivers,pedestrians violating regulations,passengers entering restricted areas,and blind spots at intersections.Corresponding safety management measures were formulated.The study concluded that the integration of Bayesian networks and accident trees effectively determines accident probabilities and offers specific solutions,thus playing a crucial role in enhancing road traffic safety management within aviation airports.

Attribute-driven Fuzzy Fault Tree Model for Adaptive Lubricant Failure Diagnosis

Lubricant diagnosis serves as a crucial accordance for condition-based maintenance(CBM)involving oil changing and wear examination of critical parts in equipment.However,the accuracy of traditional end-to-end diagnosis models is often limited by the inconsistency and random fluctuations in multiple monitoring indicators.To address this,an attribute-driven adaptive diagnosis method is developed,involving three attributes:physicochemical,contamination,and wear.Correspondingly,a fuzzy fault tree(termed FFT)-based model is constructed containing the logic correlations from monitoring indicators to attributes and to lubricant failures.In particular,inference rules are integrated to mitigate conflicts arising from the reverse degradation of multiple indicators.With this model,the lubricant conditions can be accurately assessed through rule-based reasoning.Furthermore,to enhance its intelligence,the model is dynamically optimized with lubricant analysis knowledge and monitoring data.For verification,the developed model is tested with lubricant samples from both the fatigue experiment and actual aero-engines.Fatigue experiments reveal that the proposed model can improve the lubricant diagnosis accuracy from 73.4%to 92.6%compared with the existing methods.While for the engine lubricant test,a high accuracy of 90%was achieved.

Milling Fault Detection Method Based on Fault Tree Analysis and Hierarchical Belief Rule Base

Expert knowledge is the key to modeling milling fault detection systems based on the belief rule base.The construction of an initial expert knowledge base seriously affects the accuracy and interpretability of the milling fault detection model.However,due to the complexity of the milling system structure and the uncertainty of the milling failure index,it is often impossible to construct model expert knowledge effectively.Therefore,a milling system fault detection method based on fault tree analysis and hierarchical BRB(FTBRB)is proposed.Firstly,the proposed method uses a fault tree and hierarchical BRB modeling.Through fault tree analysis(FTA),the logical correspondence between FTA and BRB is sorted out.This can effectively embed the FTA mechanism into the BRB expert knowledge base.The hierarchical BRB model is used to solve the problem of excessive indexes and avoid combinatorial explosion.Secondly,evidence reasoning(ER)is used to ensure the transparency of the model reasoning process.Thirdly,the projection covariance matrix adaptation evolutionary strategies(P-CMA-ES)is used to optimize the model.Finally,this paper verifies the validity model and the method’s feasibility techniques for milling data sets.

Fault Tree Analysis of the Reliability of Electric Vehicles in India

Innovations for electric vehicles have advanced quickly in latest decades. Large-scale business use of these vehicles is still constrained by reliability-related issues. By utilising fault tree (FT) and Monte Carlo simulation, a mathematical prototype is created that includes the reliability traits of all major electrical parts of the vehicle system, including the battery, motor, drive, controllers. The research demonstrates that by raising the component restoration rates, the vehicle’s survivability can be raised. A thorough discussion of this paradigm is provided, along with a presentation and analysis of the reliability estimations based on an electric vehicle. This research on the reliability design and maintenance of an electric vehicle can be supported by the ideas that are outlined in the paper. Additionally, the findings of this study may be helpful to those who build electric vehicle, especially when upgrading the components efficiency and planning for reliability increase.

Risk Assessment of Deep-Water Horizontal X-Tree Installation

Due to the high potential risk and many influencing factors of subsea horizontal X-tree installation,to guarantee the successful completion of sea trials of domestic subsea horizontal X-trees,this paper established a modular risk evaluation model based on a fuzzy fault tree.First,through the analysis of the main process oftree down and combining the Offshore&Onshore Reliability Data(OREDA)failure statistics and the operation procedure and the data provided by the job,the fault tree model of risk analysis of the tree down installation was established.Then,by introducing the natural language of expert comprehensive evaluation and combining fuzzy principles,quantitative analysis was carried out,and the fuzzy number was used to calculate the failure probability of a basic event and the occurrence probability of a top event.Finally,through a sensitivity analysis of basic events,the basic events of top events significantly affected were determined,and risk control and prevention measures for the corresponding high-risk factors were proposed for subsea horizontal X-tree down installation.

System Reliability Analysis Method Based on T-S FTA and HE-BN

For high-reliability systems in military,aerospace,and railway fields,the challenges of reliability analysis lie in dealing with unclear failure mechanisms,complex fault relationships,lack of fault data,and uncertainty of fault states.To overcome these problems,this paper proposes a reliability analysismethod based on T-S fault tree analysis(T-S FTA)and Hyper-ellipsoidal Bayesian network(HE-BN).The method describes the connection between the various systemfault events by T-S fuzzy gates and translates them into a Bayesian network(BN)model.Combining the advantages of T-S fault tree modeling with the advantages of Bayesian network computation,a reliability modeling method is proposed that can fully reflect the fault characteristics of complex systems.Experts describe the degree of failure of the event in the form of interval numbers.The knowledge and experience of experts are fused with the D-S evidence theory to obtain the initial failure probability interval of the BN root node.Then,the Hyper-ellipsoidal model(HM)constrains the initial failure probability interval and constructs a HE-BN for the system.A reliability analysismethod is proposed to solve the problem of insufficient failure data and uncertainty in the degree of failure.The failure probability of the system is further calculated and the key components that affect the system’s reliability are identified.The proposedmethod accounts for the uncertainty and incompleteness of the failure data in complex multi-state systems and establishes an easily computable reliability model that fully reflects the characteristics of complex faults and accurately identifies system weaknesses.The feasibility and accuracy of the method are further verified by conducting case studies.

Development of Fault Diagnosis System for Spacecraft Based on Fault Tree and G2

Some ideas in the development of fault diagnosis system for spacecraft are introduced. Firstly, the architecture of spacecraft fault diagnosis is proposed hierarchically with four diagnosis frames, i.e., system level, subsystem level, component level and element level. Secondly, a hierarchical diagnosis model is expressed with four layers, i.e., sensors layer, function layer, behavior layer and structure layer. These layers are used to work together to accomplish the fault alarm, diagnosis and localization. Thirdly, a fault-tree-oriented hybrid knowledge representation based on frame and generalized rule and its relevant reasoning strategy is put forward. Finally, a diagnosis case for spacecraft power system is exemplified combining the above with a powerful expert system development tool G2.

Application of Maximum Probability Approach to the Fault Diagnosis of a Servo System

In an actual control system, it is often difficult to find out where the faults are if only based on the outside fault phenomena, acquired frequently from a fault system. So the fault diagnosis by outside fault phenomena is considered. Based on the theory of fuzzy recognition and fault diagnosis, this method only depends on experience and statistical data to set up fuzzy query relationship between the outside phenomena (fault characters) and the fault sources (fault patterns). From this relationship the most probable fault sources can be obtained, to attain the goal of quick diagnosis. Based on the above approach, the standard fuzzy relationship matrix is stored in the computer as a system database. And experiment data are given to show the fault diagnosis results. The important parameters can be on line sampled and analyzed, and when faults occur, faults can be found, the alarm is given and the controller output is regulated.

Fault-tree Models of Accident Scenarios of RoPax Vessels

Ro-Ro vessels for cargo and passengers （RoPax） are a relatively new concept that has proven to be popular in the Mediterranean region and is becoming more widespread in Northern Europe. Due to its design characteristics and amount of passengers, although less than a regular passenger liner, accidents with RoPax vessels have far reaching consequences both for economical and for human life. The objective of this paper is to identify hazards related to casualties of RoPax vessels. The terminal casualty events chosen are related to accident and incident statistics for this type of vessel. This paper focuses on the identification of the basic events that can lead to an accident and the performance requirements. The hazard identification is carried out as the first step of a Formal Safety Assessment （FSA） and the modelling of the relation between the relevant events is made using Fault Tree Analysis （FTA）. The conclusions of this study are recommendations to the later steps of FSA rather than for decision making （Step 5 of FSA）. These recommendations will be focused on the possible design shortcomings identified during the analysis by fault trees throughout cut sets. Also the role that human factors have is analysed through a sensitivity analysis where it is shown that their influence is higher for groundings and collisions where an increase of the initial probability leads to the change of almost 90% of the accident occurrence.

A Simple Method to Derive Minimal Cut Sets for a Non-coherent Fault Tree

Minimal cut sets （or prime implicants： minimal combinations of basic event conditions leading to system failure） are important information for reliability/safety analysis and design. To obtain minimal cut sets for general non-coherent fault trees, including negative basic events or multi-valued basic events, a special procedure such as the consensus rule must be applied to the results obtained by logical operations for coherent fault trees, which will require more steps and time. This paper proposes a simple method for a non-coherent fault tree, whose top event is represented as an AND combination of monotonic sub-trees. A ＂monotonic＂ sub-tree means that it does not have both positive and negative representations for each basic event. It is proven that minimal cut sets can be obtained by a conventional method for coherent fault trees. An illustrative example of a simple event tree analysis shows the detail and characteristics of the proposed method.

A SIMULATED ANNEALING METHOD FOR FAULT TREE ANALYSIS

This paper presents an approximate algorithm based on simulated annealing to achieve the maximum probability of the minimal cut sets for a fault tree. Near optimal minimal cut sets and important sequence of the basic events are also solved by the method. Computer simulations show that the algorithm performs very well.

FUZZY PETRI NET FOR FAULT DIAGNOSIS

Because of the stochastic property of fault occurrence and fuzziness offault phenomenon, machine fault diagnosis technique in use, such as fault tree analysis,cause consequence tree method, etc., cannot exactly describe the properties of fault phe-nomenon and coherence of fault space. In this paper, based on the theory of generalPetri net, fault tree technique and theory of fuzzy set, a theory system of fuzzy Petri net(FPN) suitable for fault diagnosis is established, which is applied to an example of faultdiagnosis for FMS. This method has the properties of of rbjectivity, strong expressionability, easy inference, etc., which can solve the problems of stochastic property andfuzziness of fault.

Analysis of superheater's pipe wall overtemperature by fault tree diagnose

After research on a 2000t/h subcritical forced-circulation balanced ventilation were applied boiler and the structure and operation of its auxiliary system builds up this heat transfer model of a superheater's pipe wall and analyze the effect of primary factors on the overtemperature of the pipe wall. Fault tree structure was used to uncover the multiplayer logic between the overtemperature of the superheater's pipe wall and the faults.

DATA TRANSFORMATION OF FAULT TREE BY USING MATRIX OPERATION

On the base of study of the correlation of fault tree's main data-minimum cutsets, minimum path sets, non-intersect minimum cut sets and non-intersect minimum path sets,transformation method among main data are found, i.e. the transformation can be realized by theoperation of cut sets matrixes. This method provides anew way to reduce 'NP' difficulty and simplifyFTA.

Reliability Analysis of Electrical System of CNC Machine Tool Based on Dynamic Fault Tree Analysis Method

The electrical system of CNC machine tool is very complex which involves many uncertain factors and dynamic stochastic characteristics when failure occurs.Therefore,the traditional system reliability analysis method,fault tree analysis(FTA)method,based on static logic and static failure mechanism is no longer applicable for dynamic systems reliability analysis.Dynamic fault tree(DFT)analysis method can solve this problem effectively.In this method,DFT first should be pretreated to get a simplified fault tree(FT);then the FT was modularized to get the independent static subtrees and dynamic subtrees.Binary decision diagram(BDD)analysis method was used to analyze static subtrees,while an approximation algorithm was used to deal with dynamic subtrees.When the scale of each subtree is smaller than the system scale,the analysis efficiency can be improved significantly.At last,the usefulness of this DFT analysis method was proved by applying it to analyzing the reliability of electrical system.

Fault Tree Analysis:Investigation of Epidemic Hemorrhagic Fever Infection Acquired in Animal Laboratories in China

Epidemic hemorrhagic fever has been an ongoing threat to laboratory personnel involved in animal care and use. Laboratory transmissions and severe infections occurred over the past twenty years, even though the standards and regulations for laboratory biosafety have been issued, upgraded, and implemented in China. Therefore, there is an urgent need to identify risk factors and to seek effective preventive measures that can curb the incidences of epidemic hemorrhagic fever among laboratory personnel. In the present study, we reviewed literature that relevant to animals laboratory-acquired hemorrhagic fever infections reported from 1995 to 2015, and analyzed these incidences using fault tree analysis （FTA）.

Fault Tree Analysis of Fire and Explosion Accidents for Dual Fuel （Diesel/Natural Gas） Ship Engine Rooms

In recent years, China's increased interest in environmental protection has led to a promotion of energy-efficient dual fuel(diesel/natural gas) ships in Chinese inland rivers. A natural gas as ship fuel may pose dangers of fire and explosion if a gas leak occurs. If explosions or fires occur in the engine rooms of a ship, heavy damage and losses will be incurred. In this paper, a fault tree model is presented that considers both fires and explosions in a dual fuel ship; in this model, dual fuel engine rooms are the top events. All the basic events along with the minimum cut sets are obtained through the analysis.The primary factors that affect accidents involving fires and explosions are determined by calculating the degree of structure importance of the basic events.According to these results, corresponding measures are proposed to ensure and improve the safety and reliability of Chinese inland dual fuel ships.

Risk Assessment Based on Fault Tree Analysis for Damaged Pipe Repair During Operation in Petrochemical Plant

In petrochemical plant, the in-operation repairing is usually a repairing strategy with pressured inoperation repairing for avoiding huge economic losses caused by unplanned shutdown when some slight local leakage happens in pipes. This paper studies the effects of repairing strategies on the failure probability of the pipe systems in process industries based on the time-average fault tree approach, especially the in-operation repairing strategies including pressured in-operation repairing activities. The fault tree model can predict the effect of different repairing plans on the pipe failure probability, which is significant to the optimization of the repairing plans. At first pipes are distinguished into four states in this model, i.e., successive state, flaw state, leakage state and failure state. Then the fault tree approach, which is usually applied in the studies of dynamic equipment, is adopted to model the pipe failure. Moreover, the effect of pressured in-operation repairing is also considered in the model. In addition, this paper proposes a series of time-average parameters of the fault tree model, all of which are used to calculate node parameters of the fault tree model. At last, a practical case is calculated based on the fault tree model in a repairing activity of pipe thinning.

Fuzzy Fault Diagnosis of a Diesel Engine Non-start

The diesel locomotive plays an important role in the field of transport, and the engine maintenance work is the prerequisite and gnarantee for the locomotive normal working. In this paper, we first establish the fault tree model of locomotive engine 16V240ZJ on the basis of engine non-start as the top event. Then we combines the fitzzy mathematics the- ory and fault tree analysis method for failure diagnosis of 16V240ZJ engine＇s abnormal start-up. We obtained the fuzzy probability curve and top events probability confidence interval by analyzing the fuzzy fault tree qualitatively and quantitatively. It provides a fuzzy analysis basis for solving the problem of 16V240ZJ engine＇s abnormal start-up.

Study on System Failure Probability Model Based on Dynamic Fault Tree

Aiming at the characteristics of complex logic relation and multiple dynamic gates in system,its failure probability model is established based on dynamic fault tree. For the multi-state dynamic fault tree,it can be transferred into Markov chain with continuous parameters. The state transfer diagram can be decomposed into several state transfer chains,and the failure probability models can be derived according to the lengths of the chains. Then,the failure probability of the dynamic fault tree analysis(DFTA) can be obtained by adding each chain's probability. The failure probability calculation of DFTA based on the continuous parameter Markov chain is proposed and proved. Given an example,the analytic method is compared with the conventional methods which have to solve the differential equation. It is known from the results that the analytic method can be applied to engineering easily.