Artificial intelligence in electrostatic risk management

In the last two decades protection against electrostatic hazards became a very important topic. The increase in the range of possible faults fast automated systems and complex fault analysis is required.The tools of artificial intelligence and expert systems have been applied successfully on this field and this paper aims to take a step further. While giving some insight to the currently used tools, another AI method, the 'support vector machines' are introduced in this paper. Besides a brief review on SVMs they are introduced to the SCOUT system, a novel approach to electrostatic hazard management.     

Optoelectronic instrumentation enhancement using data mining feedback for a 3D measurement system

3D measurement by a cyber-physical system based on optoelectronic scanning instrumentation has been enhanced by outliers and regression data mining feedback. The prototype has applications in (1) industrial manufacturing systems that include: robotic machinery, embedded vision, and motion control, (2) health care systems for measurement scanning, and (3) infrastructure by providing structural health monitoring. This paper presents new research performed in data processing of a 3D measurement vision sensing database. Outliers from multivariate data have been detected and removal to improve artificial intelligence regression algorithm results. Physical measurement error regression data has been used for 3D measurements error correction. Concluding, that the joint of physical phenomena, measurement and computation is an effectiveness action for feedback loops in the control of industrial, medical and civil tasks.     

A knowledge-based adaptive control environment for an industrial laser cutting system

A hierarchically structured environment that integrates a knowledge- based expert system, adaptive process control and pattern recognition techniques for controlling a laser cutting process is described. Knowledge of the laser cutting process for different materials is organised and encoded into a rule-based system. An adaptive control algorithm based on on-line recursive parameter estimation and on-line control law synthesis was adopted for the highly non-linear cutting process control. Cutting speed was selected as the major control variable. Irradiance emitted from the cut front is used for the feedback signal to this adaptive controller. The irradiance signal feeds the recursive parameter estimator for system identification. Techniques of pattern recognition, which have been well developed in coherent optics, were applied to assess cut quality by characterising the exit spark cone images of the gas assisted laser cutting process. Images from the cutting processes were grabbed, edge enhanced and correlated with a synthetic discriminant function filter which was synthesised from reference images to give good cut quality. Results from digital simulations based on these pattern recognition algorithms are also presented.     

HL-2A控制系统及其放电管理

HL-2A控制系统由时序控制系统,逻辑控制系统和反馈控制系统三个部分组成。介绍了这三个部分的硬件和软件构成,并给出了主要被控对象极向场线圈的电气参数。在此基础上,讨论了HL-2A控制系统采用的放电管理软件的特点和功能,以及该控制系统的工作过程。最后给出了初始等离子体放电的实验结果。     

A197Au and57Fe mössbauer study of the roasting of refractory gold ores

The transformation of chemically bound gold into metallic gold during industrial scale roasting of an arsenical gold ore concentrate from the Fairview Mine, Eastern Transvaal, has been studied quantitatively by¹⁹⁷Au Mössbauer spectroscopy. The iron compounds in the concentrate, mainly FeAsS and FeS₂ and their transformations during roasting have been studied by⁵⁷Fe Mössbauer spectroscopy. The bound gold is found to convert into the metal in parallel to the decomposition of FeAsS and the increase in cyanide leachability. this shows that the refractory character of the ore is caused by the chemical bonding of the gold rather than by the physical inclusion of small, discrete metallic particles in the matrix of FeAsS or FeS₂. The ratio of thef-factors of gold bound in the FeAsS component of a refractory ore and of metallic gold was determined to bef(Au:FeAsS)/f(Au)=1.48±0.09.     

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J-TEXT装置由许多相关子系统组成,其中央控制系统的主要功能和作用是统一调度和协调各个子系统,控制装置的运行状态。J-TEXT中央控制系统是基于Windows和QNX操作系统平台,并采用工业控制计算机结合PCI工业控制卡来实现的。该系统已经完成了相关测试并获得满意结果。在首轮的J-TEXT放电调试中,该系统运行稳定可靠,控制效果良好。     

Explainable AI: A Review of Machine Learning Interpretability Methods

Recent advances in artificial intelligence (AI) have led to its widespread industrial adoption, with machine learning systems demonstrating superhuman performance in a significant number of tasks. However, this surge in performance, has often been achieved through increased model complexity, turning such systems into “black box” approaches and causing uncertainty regarding the way they operate and, ultimately, the way that they come to decisions. This ambiguity has made it problematic for machine learning systems to be adopted in sensitive yet critical domains, where their value could be immense, such as healthcare. As a result, scientific interest in the field of Explainable Artificial Intelligence (XAI), a field that is concerned with the development of new methods that explain and interpret machine learning models, has been tremendously reignited over recent years. This study focuses on machine learning interpretability methods; more specifically, a literature review and taxonomy of these methods are presented, as well as links to their programming implementations, in the hope that this survey would serve as a reference point for both theorists and practitioners.     

Distributed optical-fibre sensors for the measurement of pressure,strain and temperature

An analysis has been made of fully distributed optical-fibre measurement sensor (DOFS) systems, with particular reference to the measurement of pressure, strain and temperature in industrial environments. The analysis derives relationships between the primary system parameters; these relationships allow appropriate trade-offs to be made in order to meet any given set of industrial requirements; they also allow quantitative comparisons to be made between different kinds of DOFS system. The various physical phenomena which may be used in DOFS are considered, leading to the conclusion that, for performance likely to be generally attractive for industrial application, systems which use optical phase modulation by the measurand should be used. A review of systems which have already been studied illustrates the application of the analysis, and highlights the practical problems which are encountered in attempting to implement DOFS ideas. The proposed way forward is to begin research on two novel approaches to DOFS which use phase modulation and simplified signal processing. Implications in respect of the component technology and the industrial economics are considered for these novel system approaches.     

Information Field Theory and Artificial Intelligence

Information field theory (IFT), the information theory for fields, is a mathematical framework for signal reconstruction and non-parametric inverse problems. Artificial intelligence (AI) and machine learning (ML) aim at generating intelligent systems, including such for perception, cognition, and learning. This overlaps with IFT, which is designed to address perception, reasoning, and inference tasks. Here, the relation between concepts and tools in IFT and those in AI and ML research are discussed. In the context of IFT, fields denote physical quantities that change continuously as a function of space (and time) and information theory refers to Bayesian probabilistic logic equipped with the associated entropic information measures. Reconstructing a signal with IFT is a computational problem similar to training a generative neural network (GNN) in ML. In this paper, the process of inference in IFT is reformulated in terms of GNN training. In contrast to classical neural networks, IFT based GNNs can operate without pre-training thanks to incorporating expert knowledge into their architecture. Furthermore, the cross-fertilization of variational inference methods used in IFT and ML are discussed. These discussions suggest that IFT is well suited to address many problems in AI and ML research and application.     

关于建立智能型光学CAD系统的初步设想

本文讨论了光学设计专家系统的概念及如何将专家系统应用在光学设计某些过程中的方法,初步探讨了确定光学系统初始结构参数及在优化过程中克服局部极值等问题。文章最后指出通过将专家系统与现有的CAD技术结合起来建立智能型光学CAD系统是光学计算机辅助设计的方向。     

Automation of seismic network signal interpolation: an artificial intelligence approach

Summary After discussing the current status of the autonomation in signal interpretation from seismic networks, a new approach, based on artificial-intelligence tecniques, is proposed. The knowledge of the human expert analyst is examined, with emphasis on its objects, strategies and reasoning techniques. It is argued that knowledge-based systems (or expert systems) provide the most appropriate tools for designing an automatic system, modelled on the expert behaviour. To speed up publication, the authors of this paper has agreed to not receive the proofs for correction.     

Subordinated α-stable Ornstein–Uhlenbeck process as a tool for financial data description

The classical financial models are based on the standard Brownian diffusion-type processes. However, in the exhibition of some real market data (like interest or exchange rates) we observe characteristic periods of constant values. Moreover, in the case of financial data, the assumption of normality is often unsatisfied. In such cases the popular Vasi?ek model, that is a mathematical system describing the evolution of interest rates based on the Ornstein–Uhlenbeck process, seems not to be applicable. Therefore, we propose an alternative approach based on a combination of the popular Ornstein–Uhlenbeck process with a stable distribution and subdiffusion systems that demonstrate such characteristic behavior. The probability density function of the proposed process can be described by a Fokker–Planck type equation and therefore it can be examined as an extension of the basic Ornstein–Uhlenbeck model. In this paper, we propose the parameters’ estimation method and calibrate the subordinated Vasi?ek model to the interest rate data.     

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基于ITERCHHCSBTBM的设计特点,设计了相关的氚工艺辅助系统。描述了氚提取系统(TES)、冷却剂纯化系统(CPS)、氚测量系统(TMS)的功能、设计参数和工艺流程等。TES用于氚提取、储存、同位素的分离;CPS实现氧氮等杂质和氚的去除及冷却剂的定量处理和分析等功能;TMS不仅可以定量分析氚含量,而且必要时可替代TES。氚渗透及氚安全的分析表明,通过CHHCSBTBM以及辅助系统向环境释放的氚可控制在ITER的氚安全限度内。     

碰撞诱导离解(CID)(Ⅰ)——含时量子理论

本文采用含时量子力学微扰理论研究了分子碰撞诱导离解(CID)动力学过程。分子系统具有Morse振子和分子间指数排斥相互作用势的类型。所建立的分析理论公式能方便地用来讨论有关CID过程的各种物理化学问题。以(I₂,He)分子系统为例所进行的计算表明,在总能量一定的条件下,分子振动能比相对平动能更有效地促进CID过程的进行。而且,除必须克服离解能量势垒外,CID过程并没有额外的动力学阈值限制。 关键词：     

Knowledge-based hybrid expert system for automated interferometric data reduction

In order to accomplish the ultimate goal of automated interferogram evaluation, the utilization of artificial neural networks or expert systems in artificial intelligence has been expected. In this paper, a new PC-based fringe evaluation technique, which is based on hybridization of an expert system and a conventional fringe tracking method, is presented together with some test results of noise-ridden interferograms in high-speed aerodynamics. This technique incorporates algorithmic image processing with expert-system-driven knowledge manipulation in a single structure to provide an optimal solution for noisy interferogram evaluation. A new approach for regional phase unwrapping based on the technique is also proposed. This concept is applicable to interferometry such as phase shifting and Fourier transform that provides phase-wrapped information. It is based on conservative decision making in defining phase-wrapped regions by utilizing global/regional knowledge in the expert system. The approach is thus believed to reduce computation time and memory space in processing complex or noisy interferograms that require frequent operator interactions.     

压力对TlPbxBaCa3Cu3O超导电性的影响

 在零电阻温度T_c0达到120 K的TlBaCa₃Cu₃O_y超导体中，掺入不同含量的Pb后，超导电性受到抑制，点阵常数减小。加压时，T_c先随压力p的增加而上升，样品1（x_Pb=0.05）的dT_c0/dp=1.7 K/GPa，样品2（x_Pb=0.5）的dT_c0/dp=2.2 K/GPa。T_c的峰值随Pb的增加而减小。加压时，对由于Pb的加入引起的Cu—O层的精细结构变化起到调制作用。     

ADS注入器Ⅱ低温恒温器控制系统

设计了用于ADS注入器Ⅱ超导腔的低温恒温器控制系统。采用了基于EPICS 的分布式控制系统架构,以PLC 和串口服务器等为核心控制硬件,用PID 算法实现了恒温器内氦压和液氦量的自动控制,压力控制精度约为100 Pa,液氦高度误差约10 mm。利用EPICS 和LabVIEW 在局域网发布过程数据,实现了操作员界面对低温恒温器分布式系统的统一管理,控制系统设计性能满足使用需求,已经在ADS注入器Ⅱ超导高频腔水平测试中发挥了重要作用。Cryogenic module provides important low temperature environment for half wave resonance superconducting cavity in C-ADS injector Ⅱ, to ensure the effective operation of cryogenic module, a remote control system which is based on the physical and experimental industrial control systems (EPICS) is introduced in this paper. PLC and serial port server are used as field controllers. Host computer runs EPICS and LabVIEW which are capable of getting and releasing data in local area net. Operators manage all the equipments through a CSS interface which is linked to local area net. The control system which is simple structure and reliable work, has played an important role in the level test of HWR superconducting cavity.     

Monitoring of multiphase flows for superconducting accelerators and others applications

This paper is a review on implementation of measuring systems for two-phase helium, hydrogen, liquefied natural gas (LNG), and oil-formation/salty water flows. Two types of such systems are presented. The first type is based on two-phase flow-meters combining void fraction radio-frequency (RF) sensors and narrowing devices. They can be applied for superconducting accelerators cooled with two-phase helium, refueling hydrogen system for space ships and some applications in oil production industry. The second one is based on combination of a gamma-densitometer and a narrowing device. These systems can be used to monitor large two-phase LNG and oil-formation water flows. An electronics system based on a modular industrial computer is described as well. The metrological characteristics for different flow-meters are presented and the obtained results are discussed. It is also shown that the experience gained allows separationless flow-meter for three-phase oil-gas-formation water flows to be produced.     

High temperature thermoelectric properties of highly c-axis oriented Bi₂Sr₂Co₂O_y thin films fabricated by pulsed laser deposition

High-temperature thermoelectric transport property measurements have been performed on the highly c-axis oriented Bi2Sr2Co2Oy thin films prepared by pulsed laser deposition on LaAlO3(001).Both the electric resistivity ρ and the seebeck coefficient S of the film exhibit an increasing trend with the temperature from 300 K-1000 K and reach up to 4.8 m·Ω· cm and 202 μV/K at 980 K,resulting in a power factor of 0.85 mW/mK which are comparable to those of the single crystalline samples.A small polaron hopping conduction can be responsible for the conduction mechanism of the film at high temperature.The results demonstrate that the Bi2Sr2Co2Oy thin film has potential application in high temperature thin film thermoelectric devices.