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.

Canadian children’s and youth’s adherence to the 24-h movement guidelines during the COVID-19 pandemic: A decision tree analysis

Purpose:The purpose of this study was to use decision tree modeling to generate profiles of children and youth who were more and less likely to meet the Canadian 24-h movement guidelines during the coronavirus disease-2019(COVID-19)outbreak.Methods:Data for this study were from a nationally representative sample of 1472 Canadian parents(Meanage=45.12,SD=7.55)of children(511 years old)or youth(1217 years old).Data were collected in April 2020 via an online survey.Survey items assessed demographic,behavioral,social,micro-environmental,and macro-environmental characteristics.Four decision trees of adherence and non-adherence to all movement recommendations combined and each individual movement recommendation(physical activity(PA),screen time,and sleep)were generated.Results:Results revealed specific combinations of adherence and non-adherence characteristics.Characteristics associated with adherence to the recommendation(s)included high parental perceived capability to restrict screen time,annual household income ofCAD 100,000,increases in children’s and youth’s outdoor PA/sport since the COVID-19 outbreak began,being a boy,having parents younger than 43 years old,and small increases in children’s and youth’s sleep duration since the COVID-19 outbreak began.Characteristics associated with non-adherence to the recommendation(s)included low parental perceived capability to restrict screen time,youth aged 1217 years,decreases in children’s and youth’s outdoor PA/sport since the COVID-19 outbreak began,primary residences located in all provinces except Quebec,low parental perceived capability to support children’s and youth’s sleep and PA,and annual household income ofCAD 99,999.Conclusion:Our results show that specific characteristics interact to contribute to(non)adherence to the movement behavior recommendations.Results highlight the importance of targeting parents’perceived capability for the promotion of children’s and youth’s movement behaviors during challenging times of the COVID-19 pandemic,paying particular attention to enhancing parental perceived capability to restrict screen time.

Single-event-effect propagation investigation on nanoscale system on chip by applying heavy-ion microbeam and event tree analysis

The propagation of single-event effects(SEEs)on a Xilinx Zynq-7000 system on chip(SoC)was inves-tigated using heavy-ion microbeam radiation.The irradia-tion results reveal several functional blocks’sensitivity locations and cross sections,for instance,the arithmetic logic unit,register,D-cache,and peripheral,while irradi-ating the on-chip memory(OCM)region.Moreover,event tree analysis was executed based on the obtained microbeam irradiation results.This study quantitatively assesses the probabilities of SEE propagation from the OCM to other blocks in the SoC.

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）.

Flotation tree analysis for recovery of sillimanite from red sediments

In this paper an attempt is made to recover sillimanite by flotation tree analysis process and conventional flotation process from non magnetic fraction of red sediments.The experimental results of both the processes are presented.The data reveal that the deslimed sample contains 33.2%(by weight) total heavy minerals and out of which the sillimanite mineral content is 3.6%(by weight).It is observed that flotation tree analysis needs 10 cells to get five output products and where as conventional flotation process needs 15 cells to recover similar grade of five output products.Thus,flotation tree analysis is not only economic process but also efficient process(to say efficient process,the tree analysis product should be higher grade).

Interval Fault Tree Analysis of Excavator VariableFrequency Speed Control System

In consideration of the uncertainty of basic events failure rate and lack of probability statistical information in fault tree analysis( FTA) of excavator variable-frequency speed control system, the interval theory was employed and combined with conventional FTA method. The basic events failure probabilities were described by interval numbers,and the interval operators of logical gates in FTA were deduced based on interval theory. Finally,the reliability assessment of excavator variable-frequency speed control system was done by interval FTA method. The result shows that the interval FTA method is suitable for the complex system with insufficient failure data.

Fault Tree Analysis of CNC Machine Tool Based on BDD Technology

CNC machine tool is a large complex system which contains both mechanical and electrical components.As one of these components,the spindle is crucial for the performance of CNC machine tool.To improve the quality of CNC machine,the reliability of spindle was evaluated in this paper using a fault tree analysis(FTA)method.The FTA method is a set of calculation methods based on Boolean algebra.However,it is difficult to analyze a large and complex fault tree with inaccurate results and low efficiency as well as the complexity of time and space.Both of them will result in the so-called "combinatorial explosion".To overcome this problem,the analysis method based on binary decision diagram(BDD)was introduced in our works,and a sorting method about bottom events was also recommended which can reduce the size of the BDD effectively.

Analysis and Control Measures of Hazardous Chemical Explosions Based on Fault Tree Analysis

In view of the environmental and safety risks of hazardous chemical explosions in chemical enterprises,the fault tree analysis was used to establish a fault tree model of hazardous chemical explosions and comprehensively analyze the possibility of the explosions.The 34 basic events that caused hazardous chemical explosions were expounded,and the minimum cut and path sets were obtained.The structure importance of basic events were calculated.According to the minimum path sets,the basic events when the accident does not occur were determined,and combined with the sequence of structure importance,the preventive measures for hazardous chemical explosion accidents were proposed.The fault tree model intuitively clarified the correlation between the direct causes of hazardous chemical explosion accidents,and proposed directions for effectively reducing the probability of hazardous chemical explosion accidents in the chemical industry.

Unplanned Shutdown Frequency Prediction of FBR MONJU Using Fault Tree Analysis Method

In order to evaluate the operational reliability of Japanese FBR （fast breeder reactor） MONJU, frequencies of important intermediate events and equipment failures resulting during reactor automatic trip are predicted using FTA （fault tree analysis） technique for the plant system model. The targeted devices are the following： PHTS （primary heat transport system）, SHTS （secondary heat transport system）, WS （water and steam system）, PPS （plant protection system） and PCS （plant control system）. In this paper, the frequency of automatic reactor trips was estimated by extracting and analyzing the important intermediate events and equipment failures covering all the derived fault trees of these systems. The analyses predicted 1.2/RY （reactor year） the value of unplanned shut down frequency by the internal factor of the system. The largest contributed event was function failure of SHTS accounting for 42.6% of total events followed by PHTS with 40.1%. The contribution factor of WS was only 4.4%.

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.

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.

Chi-squared Automatic Interaction Detection Decision Tree Analysis of Risk Factors for Infant Anemia in Beijing, China

Background： In the past decades, studies on infant anemia have mainly focused on rural areas of China. With the increasing heterogeneity of population in recent years, available information on infant anemia is inconclusive in large cities of China, especially with comparison between native residents and floating population. This population-based cross-sectional study was implemented to determine the anemic status of infants as well as the risk factors in a representative downtown area of Beijing. Methods： As useful methods to build a predictive model, Chi-squared automatic interaction detection （CHAID） decision tree analysis and logistic regression analysis were introduced to explore risk factors of infant anemia. A total of 1091 infants aged 6-12 months together with their parents/caregivers living at Heping Avenue Subdistrict of Beijing were surveyed from January 1,2013 to December 31, 2014. Results： The prevalence of anemia was 12.60% with a range of 3.47%-40.00% in different subgroup characteristics. The CHAID decision tree model has demonstrated multilevel interaction among risk factors through stepwise pathways to detect anemia. Besides the three predictors identified by logistic regression model including maternal anemia during pregnancy, exclusive breastfeeding in the first 6 months, and floating population, CHAID decision tree analysis also identified the fourth risk factor, the maternal educational level, with higher overall classification accuracy and larger area below the receiver operating characteristic curve. Conclusions： The infant anemic status in metropolis is complex and should be carefully considered by the basic health care practitioners. CHAID decision tree analysis has demonstrated a better performance in hierarchical analysis of population with great heterogeneity. Risk factors identified by this study might be meaningful in the early detection and prompt treatment of infant anemia in large cities.

Fuzzy fault tree analysis of oil and gas leakage in subsea production systems

This paper presents a probabilistic failure analysis of leakage of the oil and gas in a subsea production system using fault tree analysis(FTA).A fault tree was constructed by considering four major areas where the leakages can be initiated.These are:gas and oil wells,pipelines,key facilities and third party damage.Conventional FTA requires precise values for the probability of failure of the basic events.However,since the failure data are uncertain,a fuzzy approach to these data is taken which leads to the so-called fuzzy fault tree analysis(FFTA),a method that employs expert elicitation and fuzzy set theories to calculate the failure probabilities of the intermediate events and the top event through identification of the minimal cut sets of the fault tree.A number of importance measures for minimal cut sets and the basic events have been obtained which helps to identify the nature of dependence of the top event on the basic events and thereby can identify the weakest links that may cause leakage in the subsea production system.

Identification and classification of traditional Chinese medicine syndrome types among senior patients with vascular mild cognitive impairment using latent tree analysis

OBJECTIVE： To treat patients with vascular mild cognitive impairment （VMCI） using traditional Chinese medicine （TCM）, it is necessary to classify the patients into TCM syndrome types and to apply different treatments to different types. In this paper, we investigate how to properly carry out the classification for patients with VMCI aged 50 or above using a novel data-driven method known as latent tree analysis （LTA）. METHOD： A cross-sectional survey on VMCI was carried out in several regions in Northern China between February 2008 and February 2012 which resulted in a data set that involves 803 patients and 93 symptoms. LTA was performed on the data to reveal symptom co-occurrence patterns, and the patients were partitioned into clusters in multiple ways based on the patterns. The patient clusters were matched up with syndrome types, and population statistics of the clusters are used to quantify the syndrome types and to establish classification rules. RESULTS： Eight syndrome types are identified： Qi deficiency, Qi stagnation, Blood deficiency, Blood stasis, Phlegm-dampness, Fire-heat, Yang deficiency, and Yin deficiency. The prevalence and symptom occurrence characteristics of each syndrome type are determined. Quantitative classification rules are established for determining whether a patient belongs to each of the syndrome types. CONCLUSION： A solution for the TCM syndrome classification problem for patients with VMCI and aged 50 or above is established based on the LTA of unlabeled symptom survey data. The results can be used as a reference in clinic practice to improve the quality of syndrome differentiation and to reduce diagnosis variances across physicians. They can also be used for patient selection in research projects aimed at finding biomarkers for the syndrome types and in randomized control trials aimed at determining the efficacy of TCM treatments of VMCI.

Efficient Fault Tree Analysis of Complex Fault Tolerant Multiple-Phased Systems

Fault tolerant multiple phased systems (FTMPS), i.e., systems whose critical components are independently replicated and whose operational life can be partitioned in a set of disjoint periods, are called 'phases'. Because of their deployment in critical applications, their reliability analysis is a task of primary relevance to validate the designs. Fault tree analysis based on binary decision diagram (BDD) is one of the most commonly used techniques for FTMPS reliability analysis. To utilize the technique the fault tree structure of FTMPS needs to be converted into the corresponding BDD format. Our research work shows that the system BDD generation algorithms presented in the literature are too inefficient to be used for industrial complex FTPMS because of the problems, such as variable ordering and combination of large BDDs. This paper presents a more efficient approach consisting of a flatting pre-processing technique, a proved efficient ordering heuristic and a bottom-up generation algorithm. The approach tries to combine share-variable BDDs by complex combination operation firstly and then combine no-share-variable BDDs using simple combination operation, thus to alvoid the intensive computations caused by large BDD combination operations. An example FTMPS is analyzed to illustrate the advantages of our approach.

Applying latent tree analysis to classify Traditional Chinese Medicine syndromes(Zheng)in patients with psoriasis vulgaris

OBJECTIVE:To treat patients with psoriasis vulgaris using Traditional Chinese Medicine(TCM),one must stratify patients into subtypes(known as TCM syndromes or Zheng)and apply appropriate TCM treatments to different subtypes.However,no unified symptom-based classification scheme of subtypes(Zheng)exists for psoriasis vulgaris.The present paper aims to classify patients with psoriasis vulgaris into different subtypes via the analysis of clinical TCM symptom and sign data.METHODS:A cross-sectional survey was carried out in Beijing from 2005-2008,collecting clinical TCM symptom and sign data from 2764 patients with psoriasis vulgaris.Roughly 108 symptoms and signs were initially analyzed using latent tree analysis,with a selection of the resulting latent variables then used as features to cluster patients into subtypes.RESULTS:The initial latent tree analysis yielded a model with 43 latent variables.The second phase of the analysis divided patients into three subtype groups with clear TCM Zheng connotations:'blood deficiency and wind dryness';'blood heat';and'blood stasis'.CONCLUSIONS:Via two-phase analysis of clinic symptom and sign data,three different Zheng subtypes were identified for psoriasis vulgaris.Statistical characteristics of the three subtypes are presented.This constitutes an evidence-based solution to the syndromedifferentiation problem that exists with psoriasis vulgaris.

Fault Tree Analysis of Feeding Control System for Computer Numerical Control Heavy-Duty Horizontal Lathes with Multiple Common Cause Failure Groups

The lathes are basic machine tools for manufacturing cylindrical parts. In recent years, the DLseries computer numerical control(CNC) heavy-duty horizontal lathes(HDHLs) have been widely used in the transportation, energy and aviation industries. High availability of the CNC heavy-duty lathes is demanded to guarantee the efficiency and benefit of these manufacturing industries. As one of the key subsystems of the HDHLs, the feeding control system is studied in this paper on reliability modeling and reliability analysis. The fault tree analysis(FTA) method is used for reliability modelling of the feeding control system. Considering the multiple common cause failure groups(CCFGs) existing in the system, a modified beta factor parametric model is introduced to model the common cause failure(CCF) in system. The reliability of feeding control system is then obtained and the effect of CCF on the reliability of the whole system is studied as well.

Building and Analysis of Computer Aided Fuze Fault Tree

A common software to analyze fuze fault tree is developed to simplify the trivialness in generating the fuze fault tree and reduce the manual calculation work. The overall structure, function and implementation of the system are introduced. The software based on Windows platform is used to generate the fuze fault tree in graphics mode. A quantitative analysis of fuze fault tree can be obtained by the method of minimum cut sets. A calculation example is used to verify the function of the software. Consequently, the expected requirements of this software system are achieved to a certain level.

STUDY ON MODULAR FAULT TREE ANALYSIS TECHNIQUE WITH CUT SETS MATRIX METHOD

A new fault tree analysis (FTA) computation method is put forth by using modularization technique in FTA with cut sets matrix, and can reduce NP (Nondeterministic polynomial) difficulty effectively. This software can run in IBM PC and DOS 3.0 and up. The method provides theoretical basis and computation tool for application of FTA technique in the common engineering system

CAUSALITY DIAGRAM BASED SAFETY ANALYSIS OF MICRO TURBOJET ENGINE

An improved safety analysis based on the causality diagram for the complex system of micro aero-engines is presented.The study is examined by using the causality diagram in analytical failure cases due to rupture or pentration in the receiver of micro turbojet engine casing,and the comparisons are also made with the results from the traditional fault tree analysis.Experimental results show two main advantages：（1）Quantitative analysis which is more reliable for the failure analysis in jet engines can be produced by the causality diagram analysis;（2）Graphical representation of causality diagram is easier to apply in real test cases and more effective for the safety assessment.