Research and design of an expert diagnosis system for rail vehicle driven by data mechanism models

Purpose-The aim of this work is to research and design an expert diagnosis system for rail vehicle driven by data mechanism models.Design/methodology/approach-The expert diagnosis system utilizes statistical and deep learning methods to model the real-time status and historical data features of rail vehicle.Based on data mechanism models,it predicts the lifespan of key components,evaluates the health status of the vehicle and achieves intelligent monitoring and diagnosis of rail vehicle.Findings-The actual operation effect of this system shows that it has improved the intelligent level of the rail vehicle monitoring system,which helps operators to monitor the operation of vehicle online,predict potential risks and faults of vehicle and ensure the smooth and safe operation of vehicle.Originality/value-This system improves the efficiency of rail vehicle operation,scheduling and maintenance through intelligent monitoring and diagnosis of rail vehicle.

基于Design-Expert的电链锯锯齿结构参数优化

为提高电链锯的锯切效率,对电链锯锯齿的齿形结构参数进行研究,以单位锯切功为电链锯锯切效率的衡量指标,通过对电链锯锯切过程的仿真研究,得出不同结构锯齿的单位锯切功。以电链锯锯齿中的外形前角、侧刃楔角和顶刃楔角等结构参数作为影响因子,采用Box-Benhnken中心组合试验方法设计多因素正交试验,使用Design-expert软件进行数据分析得出最优齿形结构参数组合。研究结果表明,所选取的齿形结构参数对单位锯切功影响程度由大到小顺序依次为外形前角、侧刃楔角、顶刃楔角,并获得最优齿形结构参数组合,外形前角为10.92°、侧刃楔角为45.7°、顶刃楔角为45.41°。

An innovative classification system for ranking the biological effects of marine aromatic hydrocarbons based on fish embryotoxicity

Petroleum hydrocarbon pollution is a global concern,particularly in coastal environments.Polycyclic aromatic hydrocarbons(PAHs) are regarded as the most toxic components of petroleum hydrocarbons.In this study,the biomonitoring and ranking effects of petroleum hydrocarbons and PAHs on the marine fish model Oryzias melastigma embryos were determined in the Jiulong River Estuary(JRE) and its adjacent waters in China.The results showed that the levels of petroleum hydrocarbons from almost all sites met the primary standard for marine seawater quality,and the concentrations of the 16 priority PAHs in the surface seawater were lower compared with those in other coastal areas worldwide.A new fish expert system based on the embryotoxicity of O.melastigma(OME-FES) was developed and applied in the field to evaluate the biological effects of petroleum hydrocarbons and PAHs.The selected physiological index and molecular indicators in OME-FES were appropriate biomarkers for indicating the harmful effects of petroleum hydrocarbons and PAHs.The outcome of OME-FES revealed that the biological effect levels of the sampling sites ranged from level Ⅰ(no stress) to level Ⅲ(medium stress),which is further corroborated by the findings of nested analysis of variance(ANOVA) models.Our results suggest that the OME-FES is an effective tool for evaluating and ranking the biological effects of marine petroleum hydrocarbons and PAHs.This method may also be applied to evaluate other marine pollutants based on its framework.

Expert Experience and Data-Driven Based Hybrid Fault Diagnosis for High-SpeedWire Rod Finishing Mills

The reliable operation of high-speed wire rod finishing mills is crucial in the steel production enterprise.As complex system-level equipment,it is difficult for high-speed wire rod finishing mills to realize fault location and real-time monitoring.To solve the above problems,an expert experience and data-driven-based hybrid fault diagnosis method for high-speed wire rod finishing mills is proposed in this paper.First,based on its mechanical structure,time and frequency domain analysis are improved in fault feature extraction.The approach of combining virtual value,peak value with kurtosis value index,is adopted in time domain analysis.Speed adjustment and side frequency analysis are proposed in frequency domain analysis to obtain accurate component characteristic frequency and its corresponding sideband.Then,according to time and frequency domain characteristics,fault location based on expert experience is proposed to get an accurate fault result.Finally,the proposed method is implemented in the equipment intelligent diagnosis system.By taking an equipment fault on site,for example,the effectiveness of the proposed method is illustrated in the system.

Prediction System for Diagnosis and Detection of Coronavirus Disease-2019(COVID-19):A Fuzzy-Soft Expert System

In early December 2019,a new virus named“2019 novel coronavirus(2019-nCoV)”appeared in Wuhan,China.The disease quickly spread worldwide,resulting in the COVID-19 pandemic.In the currentwork,we will propose a novel fuzzy softmodal(i.e.,fuzzy-soft expert system)for early detection of COVID-19.Themain construction of the fuzzy-soft expert systemconsists of five portions.The exploratory study includes sixty patients(i.e.,fortymales and twenty females)with symptoms similar to COVID-19 in(Nanjing Chest Hospital,Department of Respiratory,China).The proposed fuzzy-soft expert systemdepended on five symptoms of COVID-19(i.e.,shortness of breath,sore throat,cough,fever,and age).We will use the algorithm proposed by Kong et al.to detect these patients who may suffer from COVID-19.In this way,the present system is beneficial to help the physician decide if there is any patient who has COVID-19 or not.Finally,we present the comparison between the present system and the fuzzy expert system.

Fully Completed Spherical Fuzzy Approach-Based Z Numbers(PHIModel)for Enhanced Group Expert Consensus

This study aims to establish an expert consensus and enhance the efficacy of decision-making processes by integrating Spherical Fuzzy Sets(SFSs)and Z-Numbers(SFZs).A novel group expert consensus technique,the PHImodel,is developed to address the inherent limitations of both SFSs and the traditional Delphi technique,particularly in uncertain,complex scenarios.In such contexts,the accuracy of expert knowledge and the confidence in their judgments are pivotal considerations.This study provides the fundamental operational principles and aggregation operators associated with SFSs and Z-numbers,encompassing weighted geometric and arithmetic operators alongside fully developed operators tailored for SFZs numbers.Subsequently,a case study and comparative analysis are conducted to illustrate the practicality and effectiveness of the proposed operators and methodologies.Integrating the PHI model with SFZs numbers represents a significant advancement in decision-making frameworks reliant on expert input.Further,this combination serves as a comprehensive tool for decision-makers,enabling them to achieve heightened levels of consensus while concurrently assessing the reliability of expert contributions.The case study results demonstrate the PHI model’s utility in resolving complex decision-making scenarios,showcasing its ability to improve consensus-building processes and enhance decision outcomes.Additionally,the comparative analysis highlights the superiority of the integrated approach over traditional methodologies,underscoring its potential to revolutionize decision-making practices in uncertain environments.

Expert consensus on irrigation and intracanal medication in root canal therapy

Chemical cleaning and disinfection are crucial steps for eliminating infection in root canal treatment. However, irrigant selection or irrigation procedures are far from clear. The vapor lock effect in the apical region has yet to be solved, impeding irrigation efficacy and resulting in residual infections and compromised treatment outcomes.

Interpretation of Chinese Expert Consensus on the Diagnosis and Management Strategy of Patients with Statin Intolerance: A guiding file for helping to lipid management for Chinese population

It is well-known that elevated low-density lipoprotein cholesterol(LDL-C)is a causal risk factor for atheroscler-otic cardiovascular disease(ASCVD),statins are cornerstone drugs for the cause-based treatment of ASCVD,which has created a new era for ASCVD therapy.However,statin intolerance is not clinically uncommon,which there are several issues with confu-sion and misunderstandings.Hence,a file named Chinese Expert Consensus on the Diagnosis and Management Strategy of Pa-tients With Statin Intolerance,like a navigator,has recently been published written by a team of experts from the Cardiovascular Metabolic Medicine Professional Committee,Expert Committee of the National Center for Cardiovascular Diseases aiming to en-hance the standardized clinical application of statins and improve the prevention and clinical outcome.In this article,author briefly summarized the key points of above consensus in order to helping to comprehending the content of the consensus sugges-tions.

UAV maneuvering decision-making algorithm based on deep reinforcement learning under the guidance of expert experience

Autonomous umanned aerial vehicle(UAV) manipulation is necessary for the defense department to execute tactical missions given by commanders in the future unmanned battlefield. A large amount of research has been devoted to improving the autonomous decision-making ability of UAV in an interactive environment, where finding the optimal maneuvering decisionmaking policy became one of the key issues for enabling the intelligence of UAV. In this paper, we propose a maneuvering decision-making algorithm for autonomous air-delivery based on deep reinforcement learning under the guidance of expert experience. Specifically, we refine the guidance towards area and guidance towards specific point tasks for the air-delivery process based on the traditional air-to-surface fire control methods.Moreover, we construct the UAV maneuvering decision-making model based on Markov decision processes(MDPs). Specifically, we present a reward shaping method for the guidance towards area and guidance towards specific point tasks using potential-based function and expert-guided advice. The proposed algorithm could accelerate the convergence of the maneuvering decision-making policy and increase the stability of the policy in terms of the output during the later stage of training process. The effectiveness of the proposed maneuvering decision-making policy is illustrated by the curves of training parameters and extensive experimental results for testing the trained policy.

Practice and Thinking of Agricultural Science and Technology Experts Serving the Grassroots to Promote Rural Revitalization

Provincial agricultural research institutes are local agricultural research institutions.They are familiar with local agricultural and ru-ral conditions,and have advantages in scientific and technological achievements,technical reserves and the construction of scientific and tech-nological talent support systems.In the process of promoting the implementation of the rural revitalization strategy,all the responsibilities and obligations of the agricultural research institute are to identify the focus of scientific and technological support and talent support in rural revital-ization,and break the bottleneck and constraints of rural revitalization.By sorting out the current situation of agricultural science and technolo-gy experts serving the grassroots in the problem of talent support for rural revitalization,this paper analyzed the existing problems and put for-ward countermeasures and recommendations.

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.

British Law Expert:South China Sea Islands Are Chinese Territory

The History and Sovereignty of the South China Sea Islands clarifies the sovereignty over the South China Sea Islands with irrefutable facts.THE English edition of The History and Sovereignty of the South China Sea Islands was released by New Star Press under China International Communications Group at the 2024 Beijing International Book Fair on June 20.Prior to this,the Chinese version of the book,also published by New Star Press,had attracted wide attention from the international community.

企业技术难题与专家精准对接语言模型Expert-ChatGLM

传统方式下,企业引进技术领域的专家时,通常通过简历等信息筛选。但该方式存在同质化高、精准匹配难等问题。为此,建立一个能实现专家与企业需求精准对接的模型迫在眉睫。近年来,随着人工智能的发展,出现了很多大型语言模型,如OpenAI的ChatGPT、斯坦福的Alpaca和清华大学的ChatGLM-6B。虽然这些模型在指令和聊天方面取得了成绩,但对于专家与企业的精准对接尚有不足。因此,提出了专家与企业精准对接语言模型Expert-ChatGLM,该模型对研究采集构建的专家知识图谱以及专家对话数据集进行了微调,能够准确理解企业需求并提供精准的专家信息。该模型能提高寻找专家的效率和质量,具有很大的发展潜力。

基于Design-Expert的碱激发粉煤灰建筑外墙腻子配合比优化试验研究

为了拓展工业固体废弃物粉煤灰的回收利用途径,减少对环境造成的污染,增加其在筑材料中回收利用率。在建筑外墙腻子中加入碱性激发剂(Ca(OH)_(2)、Na_(2)SiO_(3))、粉煤灰,研究碱性激发剂的激发效果。同时通过Design-Expert设计试验,分析主要组分对腻子漆膜粘结强度、吸水量的影响。结果表明:加入碱性激发剂5%,粉煤灰32.5%时,吸水量减少14%,粘结强度增加43%。乳胶粉对吸水量、粘结强度的影响非常显著(P<0.0001),其次是粉煤灰的加入量。通过加入碱性激发剂、提高乳胶粉占比,粉煤灰掺量能达到32%~65%,原配比中水泥的掺量相对减少0%~16%。

基于ANSYS和Design-Expert的农用挖掘机斗杆机构优化设计

JKW-20山地农用挖掘机斗杆机构存在设计冗余,在保证安全可靠的前提下,为解决斗杆机构材料冗余问题,实现轻量化改进,建立了农用挖掘机挖掘装置斗杆机构耦合模型,通过ANSYS软件静力学仿真及拓扑优化,确定了斗杆机构拓扑优化新结构。由于拓扑优化结构不符合实际生产要求,基于优化结果设计斗杆变量,确定优化目标函数,利用Design-Expert进行斗杆机构尺寸优化求解。由优化结果对比可知:运用Design-Expert优化后的斗杆结构相对原结构具备更轻的质量和更大的强度,该方法不仅节约了JKW-20山地农用挖掘机的生产成本,还可为类似的机构设计提供优化思路。

Design and Development of Web-based Expert System for the Diagnosis of Disease and Pests of Fruits and Vegetables

According to the requirements of agricultural production and usem, taking diagnosis and decision-making of prevention for common diseases and pests in fruits and vegetables in southern China as the core, with communication and sharing as principle, adopted diagnosis, inquiries and guiding prevention of diseases and pests in fruits and vegetables as purpose, expert examination system of plant disease and pests in fruits and vegetables based on Web highly integrates the knowledge and prevention techniques of common diseases and pests for main fruit and vegetable in south China. In this system, the users can browse and inquiry the information about the fruit and vegetable diseases and pests, as well as their diagnosis and control. The implementation of the system plays an active role in promo- ting plant protection knowledge and guiding farms to scientifically control diseases and pests in fruits and vegetables

Variable universe fuzzy expert system for aluminum electrolysis

In aluminum electrolytic process, the variables affect the current efficiency and the stability of electrolysis cells. AIF3 addition and aluminum tapping volume are two important factors that affect economic benefits of aluminum electrolytic production. Fuzzy logic provides a suitable mechanism to describe the relationship between the process variables and the current efficiency. Fuzzy expert system based on Mamdani fuzzy inference process for aluminum electrolysis was adopted to adjust A1F3 addition and aluminum tapping volume. A novel variable universe approach was applied in the system to solve the problem that different electrolysis cells have different universes of variables. The system was applied to 300 kA aluminum electrolysis cells in a aluminum plant. Experimental results showed that the electrolyte temperature was kept stably between 945 and 955℃, the current efficiency reached 93.5%, and the DC power consumption was 13 000 kW.h per ton aluminum.

An Analysis of the Structure of Carbide-tool Utilization Expert System

The necessity and feasibility of an expert system for carbide-tool utilization are analyzed and a practical system named CUES(carbide-tool utilization expert system ) is developed and realized. The system concept, module structure, data management, inference strategy and the interface design of the system are discussed in.detail. The system would be useful not only for the preparation of tool bank of FMS or CIMS, but the for the proper application of cemented carbide tools in conventional machining Processes.

OBJECT-ORIENTED IMPLEMENTATION OF EXPERT SYSTEMS FOR ENGINE LUBRICATING OIL INSPECTION

The inspection of engine lubricating oil can give an indication of the internal condition of an engine. By means of the Object-Oriented Programming (OOP), an expert system is developed in this paper to computerize the inspection. The traditional components of an expert system, such us knowledge base, inference engine and user interface are reconstructed and integrated, based on the Microsoft Foundation Class (MFC) library. To testify the expert system, an inspection example is given at the end of this paper.

REALIZATION OF OBJECT-ORIENTED RULE-TYPE EXPERT SYSTEM TEMPLATE

Expert systems (ESs) are being increasingly applied to the fault diagnosis of engines. Based on the idea of ES template (EST), an object-oriented rule-type EST is emphatically studied on such aspects as the object-oriented knowledge representation, the heuristic inference engine with an improved depth-first search (DFS) and the graphical user interface. A diagnositic ES instance for debris on magnetic chip detectors (MCDs) is then created with the EST. The spot running shows that the rule-type EST enhances the abilities of knowledge representation and heuristic inference, and breaks a new way for the rapid construction and implementation of ES.