Expert system for supervision of real time control processes

An Expert System for Crude Unit Process Supervision

An integrated supervision & control system is the most critical segment in urban rail transit. Particularly, in recent years, the importance of supervision & control systems is also more and more evident with fast development of cloud-platform information processing technology and unattended driving technology in urban rail transit. As important infrastructure in urban rail transit, it is independently equipped and independently managed in actual application and has caused extreme impact on enhancement of operational levels. Based on conventional distribution of integrated supervision & control systems in urban transit, the article herein introduces cloud-platform information processing technology and analyzes requirements on in-depth combination of the automatic supervision system (ATS) related to an unattended driving system of signaling and an integrated supervision & control system, performs optimization design of integrated supervision & control system distribution from perspectives of investment reduction, resource sharing, operation & maintenance costs, and in-depth combination, etc. and describes distribution schemes and concepts of the Traffic Integrated Automated Supervision based on a Cloud platform (TIAS-C). Through comparison of the TIAS-C and the conventional ISCS, the advantages of intelligentization and high informationalization of cloud calculation are better understood, which will create conditions for in-depth combination of a train supervision system with an integrated supervision & control system.KeywordsUrban rail transitIntegrated supervision and control SystemSystem distributionCloud platformAutomatic supervision systemTraffic integrated automated supervision based on a cloud platformUnattended train operation

The new requirements of modern real-time distributed supervision and control systems such as more flexibility, interoperability, and cost savings, have motivated the use of software-intensive solutions both in academia and industry. Following this trend we have presented, in a previous publication, the design rationale and implementation issues of a flexible and reusable software platform (ARCOS) that relies on the CORBA component model (CCM/CIAO), the DAIS (data acquisition from industrial systems) standard, and framework technologies. This paper builds on this previous publication by presenting a new assembly tool that allows for the visual component-based implementation of ARCOS-based systems and the automatic generation of the related CCM/CIAO/ARCOS artifacts. To demonstrate the power of such a tool, two example applications are presented.

To meet the ever-increasing demand of the rapidly-growing semiconductor manufacturing industry it is critical to have a comprehensive methodology integrating techniques for process optimization real-time monitoring and adaptive process control. To this end we have accomplished an integrated knowledge-based approach combining latest expert system technology machine learning method and traditional statistical process control (SPC) techniques. This knowledge-based approach is advantageous in that it makes it possible for the task of process optimization and adaptive control to be performed consistently and predictably. Furthermore this approach can be used to construct high-level and qualitative description of processes and thus make the process behavior easy to monitor predict and control. Two software packages RIST (Rule Induction and Statistical Testing) and KARSM (Knowledge Acquisition from Response Surface Methodology) have been developed and incorporated with two commercially available packages G2 (real-time expert system) and ULTRAMAX (a tool for sequential process optimization).© (1991) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

A real-time underground environment monitoring system for sustainable tourism of caves

The object of the study is the process of operation of traction and external power supply systems as objects of inextricable interconnection while reducing energy costs in the cost of railway transportation in real time. One of the most problematic areas is the technology for choosing energy-efficient power supply schemes for railway traction networks in real time. The methods of forming and transforming graphs of complex schemes of traction and external power supply systems and building expert control systems for the implementation of energy-saving technologies of electrified railways were further developed in the work. In the course of the study, to increase the efficiency of simulation modeling of electric traction networks, the statistical characteristics of the loads of feeders that supply the final boundary sections, stations, depot access tracks, railway junctions and idle voltages on the traction substation tires were obtained. Methods of calculation and modeling of traction power supply have been developed, which take into account the inseparable relationship with power systems and allow choosing rational modes with minimal power flows and energy losses. Proposed methods of managing the modes of operation of the traction power supply system based on a vague description of their states and an expert system that allow solving new problems. Including, the choice of energy-saving power supply schemes in the case of power flows, economic modes of network operation in case of intensification of the transportation process. Thanks to this, ways of reducing power consumption and minimizing energy losses of traction power supply systems are proposed, which allow minimizing power flows and power losses by adjusting load flow parameters and voltage levels of traction substations. And also to increase the energy efficiency of electrified railway lines. The technique of technical and economic feasibility of power supply schemes of traction networks and evaluation of the possibility of switching to cantilever or loop power supply schemes with parallel connection points has been developed. The implemented recommendations save about 25 thousand kWh per 1 km of two-track section.

This paper considers the possible enhancement of the capabilities of an expert system tool. Most of the commercial tools currently available are not particularly suitable for developing expert systems that involve routine design calculations. To overcome this drawback for engineering applications, numerical computations may be carried out by conventional computer programs which can be linked to an expert system tool through its external program interface. This type of expert systems is called a "hybrid" or "coupled" expert system. Practicing engineers will, sooner or later, face the need to use hybrid expert systems. This paper presents a case study which shows how the capabilities of a commercial expert system tool can be enhanced by integrating it with a conventional computer program. The hybrid expert system developed by the authors for illustration purpose can be used for the analysis of plane steel trusses and the evaluation of member design forces. It utilizes an in-house program called “Manager” to integrate two commercial software packages: an expert system tool called KES and a structural analysis package named PFRAME. The capabilities of the hybrid system appear to exceed those of the individual software packages. Key words: knowledge based expert systems, expert system building tools, hybrid expert systems, structural analysis, structural design.

We have implemented a real-time expert system as part of a supervisory control and data acquisition system for the Public Utilities Board of Singapore, controlling its 22 kV distribution network. It works as an operator support tool by diagnosing network disturbances and device malfunctions, and by presenting a switching sequence which can be executed immediately to restore supply. In this paper we describe how the expert system is integrated into a large supervisory control and data acquisition system for power distribution networks. The necessary techniques to cover on-line processing of real-time data, intelligent alarm processing and network reconfiguration/restoration are discussed. The expert system is based on a hierarchic multi-level problem-solving architecture, integrating model-based, heuristic and algorithmic techniques acting on an object-oriented data structure. Techniques such as the automatic creation and update of the knowledge base, event filtering, on-line event processing, and structural and temporal focusing have been implemented to enable the system to perform its task on-line and in real time.

8 - Real-time fault-tolerant control systems

Delivered software is often late and over budget, while offering fewer features than requested by the user. Many software developers have difficulties establishing and adhering to a project plan and in delivering what the user wants within the budget and schedule. Developers also have difficulty in obtaining user involvement in the development process. This paper discusses a Web-enabled expert system, Project Management Advisor (PMA), which will provide alerts and corrective actions for some of the common problems that plague software development projects. PMA was developed as a part of a CyberCollaboratory built to facilitate collaborative project work. The development and evaluation of a collaborative generic expert system for identification and analysis of anomalies in project plan data is expected to be useful to many software development teams and managers in a wide variety of organizations PMA is a field prototype and was evaluated rising 11 real world project plans. The preliminary analysis of the findings is presented and discussed.

A technique is described for inductively deriving decision rules for gait event detection in an FES (functional electrical stimulation) control system, based on a collection of examples of the events to be detected. Results are presented for learning the control strategy of a manually operated two-channel stimulation system, and the general applicability of this technique to the control of FES orthoses is outlined. It is shown that inductive learning techniques represent an efficient and accurate method of deriving rules for the control of FES. In the example described the knowledge gained by the subject's experience of controlling the stimulator is effectively captured by the program. >

Bare-bones languages serve small systems with ease: Cushmann, R HEDN Vol 25 No 16 (5 September 1980) pp 171–177

Computer-based solutions offer enhanced efficacy and ease of automation in every walk of life. Computer-based systems for real time monitoring and control of corrosion testing equipment provide significantly improved measurement precision as well as a basis for improved accuracy in data acquisition for complex tests. This paper discusses one such system called a Constant Extension Rate Tester (CERT) used to automate slow strain rate (SSR) testing. SSR testing is an effective means to assess material susceptibility to environmentally assisted cracking (EAC) in corrosive systems.

Artificial intelligence (AI) has made enormous progress in recent decades, significantly influencing various industries, including the medical field. An expert system is a type of artificial intelligence that deliver specialized services in addition to experts by gathering specialty knowledge and expert information in a specific field. In light of the swift rise of Internet technology, the way expert systems are created and supplied has changed. The study used Google Scholar as the online database that provides published content about expert systems that apply AI in the medical field and covers the period of 2019 to 2024 to collect the latest data. The influence and effectiveness of utilizing an expert system with AI across various specializations are emphasized in this study's analysis of their uses in medicine. By using expert systems, they can mimic the decision-making of a human expert, improving healthcare results. Several medical specialties, including gynecology, neurology, orthopedics, ophthalmology, and cardiology, use these solutions based on AI. However, every field has its own set of difficulties, and technological developments are impacting the accuracy and reliability of diagnosis, especially gynecological diseases, which are more complex and diverse. Despite the difficulties, expert systems with AI can provide innovative solutions that can improve patient care. Understanding how AI works can pave the way for future innovation and progress in medical technologies, creating better patient results and more efficient healthcare systems. Educating medical personnel about AI and its applications could help them use these tools more efficiently to provide better patient care.

Development of a machine vision system for real-time monitoring and control of batch flotation process