A Health State Prediction Model Based on Belief Rule Base and LSTM for Complex Systems

In industrial production and engineering operations,the health state of complex systems is critical,and predicting it can ensure normal operation.Complex systems have many monitoring indicators,complex coupling structures,non-linear and time-varying characteristics,so it is a challenge to establish a reliable prediction model.The belief rule base(BRB)can fuse observed data and expert knowledge to establish a nonlinear relationship between input and output and has well modeling capabilities.Since each indicator of the complex system can reflect the health state to some extent,the BRB is built based on the causal relationship between system indicators and the health state to achieve the prediction.A health state prediction model based on BRB and long short term memory for complex systems is proposed in this paper.Firstly,the LSTMis introduced to predict the trend of the indicators in the system.Secondly,the Density Peak Clustering(DPC)algorithmis used todetermine referential values of indicators for BRB,which effectively offset the lack of expert knowledge.Then,the predicted values and expert knowledge are fused to construct BRB to predict the health state of the systems by inference.Finally,the effectiveness of the model is verified by a case study of a certain vehicle hydraulic pump.

A Novel Belief Rule-Based Fault Diagnosis Method with Interpretability

Fault diagnosis plays an irreplaceable role in the normal operation of equipment.A fault diagnosis model is often required to be interpretable for increasing the trust between humans and the model.Due to the understandable knowledge expression and transparent reasoning process,the belief rule base(BRB)has extensive applications as an interpretable expert system in fault diagnosis.Optimization is an effective means to weaken the subjectivity of experts in BRB,where the interpretability of BRB may be weakened.Hence,to obtain a credible result,the weakening factors of interpretability in the BRB-based fault diagnosis model are firstly analyzed,which are manifested in deviation from the initial judgement of experts and over-optimization of parameters.For these two factors,three indexes are proposed,namely the consistency index of rules,consistency index of the rule base and over-optimization index,tomeasure the interpretability of the optimizedmodel.Considering both the accuracy and interpretability of amodel,an improved coordinate ascent(I-CA)algorithmis proposed to fine-tune the parameters of the fault diagnosis model based on BRB.In I-CA,the algorithm combined with the advance and retreat method and the golden section method is employed to be one-dimensional search algorithm.Furthermore,the random optimization sequence and adaptive step size are proposed to improve the accuracy of the model.Finally,a case study of fault diagnosis in aerospace relays based on BRB is carried out to verify the effectiveness of the proposed method.

Reliability Analysis of Satellite Turntable System under Multiple Operation Modes Based on Multi-Valued Decision Diagrams

As a payload support system deployed on satellites,the turntable system is often switched among different working modes during the on-orbit operation,which can experience great state changes.In each mode,the missions to be completed are different,consecutive and non-over-lapping,from which the turntable system can be considered to be a phased-mission system(PMS).Reliability analysis for PMS has been widely studied.However,the system mode cycle characteristic has not been taken into account before.In this paper,reliability analysis method of the satellite turntable system is proposed considering its multiple operation modes and mode cycle characteristic.Firstly,the multi-valued decision diagrams(MDD)manipulation rules between two adjacent mission cycles are proposed.On this basis,MDD models for the turntable system in different states are established and the reliability is calculated using the continuous time Markov chains(CTMC)method.Finally,the comparative study is carried out to show the effectiveness of our proposed method.

A New Safety Assessment Method Based on Belief Rule Base With Attribute Reliability

Safety assessment is one of important aspects in health management.In safety assessment for practical systems,three problems exist:lack of observation information,high system complexity and environment interference.Belief rule base with attribute reliability(BRB-r)is an expert system that provides a useful way for dealing with these three problems.In BRB-r,once the input information is unreliable,the reliability of belief rule is influenced,which further influences the accuracy of its output belief degree.On the other hand,when many system characteristics exist,the belief rule combination will explode in BRB-r,and the BRB-r based safety assessment model becomes too complicated to be applied.Thus,in this paper,to balance the complexity and accuracy of the safety assessment model,a new safety assessment model based on BRB-r with considering belief rule reliability is developed for the first time.In the developed model,a new calculation method of the belief rule reliability is proposed with considering both attribute reliability and global ignorance.Moreover,to reduce the influence of uncertainty of expert knowledge,an optimization model for the developed safety assessment model is constructed.A case study of safety assessment of liquefied natural gas(LNG)storage tank is conducted to illustrate the effectiveness of the new developed model.

Recent advances in heterogeneous hydrosilylation of unsaturated carbon-carbon bonds

The hydrosilylation of unsaturated carbon-carbon bonds is one of the most critical reactions in silicone industrial production.The homogeneous Speier's catalyst,Karstedt's catalyst,and other noble metal-based catalysts are widely used.However,simplifying the separation of the homogeneous catalyst from reaction products and reducing the high cost of precious metals is still challenging.This review describes the recent development of heterogeneous catalysts for alkene,alkyne,and allene hydrosilylations,which can effectively solve problems in homogeneous hydrosilylation.

Realizing efficient emission and triple-mode photoluminescence switching in air-stable tin(IV)-based metal halides via antimony doping and rational structural modulation

Recently,many lead-free metal halides with diverse structures and highly efficient emission have been reported.However,their poor stability and single-mode emission color severely limit their applications.Herein,three homologous Sb^(3+)-doped zero-dimensional(0D)air-stable Sn(IV)-based metal halides with different crystal structures were developed by inserting a single organic ligand into SnCl_(4)lattice,which brings different optical properties.Under photoexcitation,(C_(25)H_(22)P)SnC_(l5)@Sb⋅CH_(4O)(Sb^(3+)−1)does not emit light,(C_(25)H_(22)P)_(2)SnC_(l6)@Sb-α(Sb^(3+)−2α)shines bright yellow emission with a photoluminescence quantum yield(PLQY)of 92%,and(C_(25)H_(22)P)_(2)SnC_(l6)@Sb-β(Sb^(3+)−2β)exhibits intense red emission with a PLQY of 78%.The above three compounds show quite different optical properties should be due to their different crystal structures and the lattice distortions.Particularly,Sb^(3+)−1 can be successfully converted into Sb^(3+)−2αunder the treatment of C_(25)H_(22)PCl solution,accompanied by a transition from nonemission to efficient yellow emission,serving as a“turn-on”photoluminescence(PL)switching.Parallelly,a reversible structure conversion between Sb^(3+)−2αand Sb^(3+)−2βwas witnessed after dichloromethane or volatilization treatment,accompanied by yellow and red emission switching.Thereby,a triple-mode tunable PL switching of off-onI-onII can be constructed in Sb^(3+)-doped Sn(IV)-based compounds.Finally,we demonstrated the as-synthesized compounds in fluorescent anticounterfeiting,information encryption,and optical logic gates.

A new interpretable fault diagnosis method based on belief rule base and probability table

It is vital to establish an interpretable fault diagnosis model for critical equipment.Belief Rule Base(BRB)is an interpretable expert system gradually applied in fault diagnosis.However,the expert knowledge cannot be utilized to establish the initial BRB accurately if there are multiple referential grades in different fault features.In addition,the interpretability of BRB-based fault diagnosis is destroyed in the optimization process,which reflects in two aspects:deviation from the initial expert judgment and over-optimization of parameters.To solve these problems,a new interpretable fault diagnosis model based on BRB and probability table,called the BRB-P,is proposed in this paper.Compared with the traditional BRB,the BRB-P constructed by the probability table is more accurate.Then,the interpretability constraints,i.e.,the credibility of expert knowledge,the penalty factor and the rule-activation factor,are inserted into the projection covariance matrix adaption evolution strategy to maintain the interpretability of BRB-P.A case study of the aerospace relay is conducted to verify the effectiveness of the proposed method.

On the evidential reasoning rule for dependent evidence combination

Evidential Reasoning(ER)rule,which can combine multiple pieces of independent evidence conjunctively,is widely applied in multiple attribute decision analysis.However,the assumption of independence among evidence is often not satisfied,resulting in ER rule inapplicable.In this paper,an Evidential Reasoning rule for Dependent Evidence combination(ERr-DE)is developed.Firstly,the aggregation sequence of multiple pieces of evidence is determined according to evidence reliability.On this basis,a calculation method of evidence Relative Total Dependence Coefficient(RTDC)is proposed using the distance correlation method.Secondly,as a discounting factor,RTDC is introduced into the ER rule framework,and the ERr-DE model is formulated.The aggregation process of two pieces of dependent evidence by ERr-DE is investigated,which is then generalized to aggregate multiple pieces of non-independent evidence.Thirdly,sensitivity analysis is carried out to investigate the relationship between the model output and the RTDC.The properties of sensitivity coefficient are explored and mathematically proofed.The conjunctive probabilistic reasoning process of ERr-DE and the properties of sensitivity coefficient are verified by two numerical examples respectively.Finally,the practical application of the ERr-DE is validated by a case study on the performance assessment of satellite turntable system.

凹型结构下保温材料EPS典型垂直火蔓延特性对比研究

本工作通过自主搭建小尺寸火蔓延的实验平台,研究了凹型结构中保温材料EPS垂直向上和向下火蔓延特性。对比分析了火焰结构特性、火蔓延速度、质量损失速率、火焰温度等参数的变化规律。结果表明,在垂直向上蔓延过程中,EPS出现短暂的停滞现象。一方面由于烟囱效应易形成一个大的浮力压力差,导致火焰不稳定性;另一方面由于凹型结构易于烟气的聚集,导致燃烧不充分。而在垂直向下蔓延过程中,由于逆向烟囱效应的影响,火蔓延速度明显加速。火蔓延过程中质量损失速率,很大程度上受其火焰高度的影响,呈现上下振荡的特性。未燃区域部分,火焰温度经历两个温度峰值,向上蔓延过程中第一个温度峰值大于第二个;而向下蔓延过程中第一个温度峰值小于第二个。这主要是由于火焰结构形态及烟囱效应的方向特点,导致产生两个不同大小的峰值。本研究结果可为实际凹型结构下火蔓延特性研究提供前期理论和参考价值。

考虑环境干扰的液体运载火箭结构安全性评估方法

液体运载火箭作为卫星运载的重要平台,对其结构安全性进行准确的评估极其重要.本文针对液体运载火箭实际工作过程中监测数据易受到噪声干扰的问题,基于置信规则库(belief rule base,BRB)提出了一种考虑环境干扰的液体运载火箭结构安全性评估方法.首先,通过分析火箭监测数据的特征,提出了一种基于距离的监测指标不确定度求取方法,通过指标不确定度来反映噪声对于监测数据的影响程度;然后,针对目前置信规则库模型中仅考虑了定性知识的不确定,无法处理监测数据不确定的问题,提出了一种考虑指标不确定度的输入数据匹配度转换方法,监测数据中包含不确定性信息的大小通过剩余匹配度表示;最后,基于BRB构建了液体运载火箭安全性评估模型,对存在不确定性的监测数据进行融合,得到液体运载火箭的安全性状态.通过实验室搭建的基于无线传感网络的运载火箭监测平台验证了所提方法的有效性.

存在环境干扰下航天继电器故障诊断与容错控制方法

航天继电器作为液体运载火箭等大型结构件复杂电子系统中的关键部件之一,其工作状态直接决定整个系统能否正常工作.本文针对航天继电器使用过程中所面临的高价值样本缺乏、系统复杂、复杂环境干扰等难题,基于考虑属性可靠度的置信规则库(belief rule base with attribute reliability,BRB-r)专家系统提出了一种新的考虑环境干扰的航天继电器故障诊断与容错控制框架.在所提出的新框架中,对航天继电器输出监测指标进行分析,基于BRB-r建立航天继电器故障诊断模型,通过其工作状态评估结果,分为功能正常、功能缺陷和功能丧失3种;然后,针对3种状态分别设计3种控制策略:保持原控制输入、重构控制率和切换备份继电器.本文所提方法通过实验室所搭建的JRC-7M航天继电器测试系统进行了实验验证.

Performance evaluation of complex systems using evidential reasoning approach with uncertain parameters

The composition of the modern aerospace system becomes more and more complex.The performance degradation of any device in the system may cause it difficult for the whole system to keep normal working states.Therefore,it is essential to evaluate the performance of complex aerospace systems.In this paper,the performance evaluation of complex aerospace systems is regarded as a Multi-Attribute Decision Analysis(MADA)problem.Based on the structure and working principle of the system,a new Evidential Reasoning(ER)based approach with uncertain parameters is proposed to construct a nonlinear optimization model to evaluate the system performance.In the model,the interval form is used to express the uncertainty,such as error in testing data and inaccuracy in expert knowledge.In order to analyze the subsystems that have a great impact on the performance of the system,the sensitivity analysis of the evaluation result is carried out,and the corresponding maintenance strategy is proposed.For a type of Inertial Measurement Unit(IMU)used in a rocket,the proposed method is employed to evaluate its performance.Then,the parameter sensitivity of the evaluation result is analyzed,and the main factors affecting the performance of IMU are obtained.Finally,the comparative study shows the effectiveness of the proposed method.

A novel combination belief rule base model for mechanical equipment fault diagnosis

Due to the excellent performance in complex systems modeling under small samples and uncertainty,Belief Rule Base(BRB)expert system has been widely applied in fault diagnosis.However,the fault diagnosis process for complex mechanical equipment normally needs multiple attributes,which can lead to the rule number explosion problem in BRB,and limit the efficiency and accuracy.To solve this problem,a novel Combination Belief Rule Base(C-BRB)model based on Directed Acyclic Graph(DAG)structure is proposed in this paper.By dispersing numerous attributes into the parallel structure composed of different sub-BRBs,C-BRB can effectively reduce the amount of calculation with acceptable result.At the same time,a path selection strategy considering the accuracy of child nodes is designed in C-BRB to obtain the most suitable submodels.Finally,a fusion method based on Evidential Reasoning(ER)rule is used to combine the belief rules of C-BRB and generate the final results.To illustrate the effectiveness and reliability of the proposed method,a case study of fault diagnosis of rolling bearing is conducted,and the result is compared with other methods.