Экспертная система диагностики легочных заболеваний

Стаття присвячена розробці експертної системи діагностики легеневих захворювань. Розглянуті основні проблеми галузі проектування експертних медичних систем, та з їх врахуванням відображена практична схема побудови програмної частини системи. Запропонований комплексний підхід в аналізуванні даних. Проектування відбувається мовою програмування Delphi 7.0 за допомогою середовища керування базами даних Paradox 7-8.The report devoted to development of expert diagnostic system of diseases of lungs. The basis branch's problems of design program part of medicine expert system examined. The practical scheme of program part offered. The complex analyses of data are proposed. The expert diagnostic system of diseases of lungs works out in instrumental cover of system building Delphi 7.0 and data base system Paradox 7-8

Diagnostics in the Extendable Integrated Support Environment (EISE)

Extendable Integrated Support Environment (EISE) is a real-time computer network consisting of commercially available hardware and software components to support systems level integration, modifications, and enhancement to weapons systems. The EISE approach offers substantial potential savings by eliminating unique support environments in favor of sharing common modules for the support of operational weapon systems. An expert system is being developed that will help support diagnosing faults in this network. This is a multi-level, multi-expert diagnostic system that uses experiential knowledge relating symptoms to faults and also reasons from structural and functional models of the underlying physical model when experiential reasoning is inadequate. The individual expert systems are orchestrated by a supervisory reasoning controller, a meta-level reasoner which plans the sequence of reasoning steps to solve the given specific problem. The overall system, termed the Diagnostic Executive, accesses systems level performance checks and error reports, and issues remote test procedures to formulate and confirm fault hypotheses

Деякі питання реалізації експертної діагностичної системи

Розглядаються питання реалізації експертної діагностичної системи з мірою вираженості симптомів. Пропонується підхід до розв’язання задач діагностики на основі лінгвістичних моделей.Рассматриваются вопросы реализации экспертной диагностической системы с мерой выраженности симптомов. Предлагается подход к решению задач диагностики на основе лингвистических моделей.The problems of implementing expert diagnostic system with a measure of severity of symptoms are considered. The approach to solving problems of diagnostics based on linguistic models is proposed

Experdite : a model based expert diagnostic system using a high level test description language

To be competitive in the development and production of complex electronic systems, a company must constantly scrutinize its manufacturing processes to find ways to reduce costs and increase productivity. One of the more costly problems is the inability to troubleshoot and repair faulty circuit boards on the spot. Rather, they must be divert.ed off the manufacturing line to a senior technician for diagnosis and repair. The purpose of Experdite is to provide a practical expert diagnostic system for manufacturing line personnel so they can quickly troubleshoot and repair most circuit board faults, thereby eliminating the need to send the board off line. Experdite also addresses other inherent manufacturing line issues, including the need to have a general purpose and easily adaptable system to work with many different circuit boards. It addresses the need for an expert diagnostician before anyone has bad the time to become an expert troubleshooter on the circuit board. The final issue addressed is the ability to quickly and easily modify the knowledge base to handle any inevitable hardware changes. The component and self-test behavior for the target circuit board is abstracted and then modeled with a high level Test Description Language, or TDL. A TDL to C++ translator converts the TDL description into a knowledge base of C++ classes. Then the inference engine traces the thread of causality to a fault on a circuit board by gleaning information from the knowledge base and comparing it to the actual behavior of the circuitry. This paper elaborates on each of these points. Also included in the paper are descriptions of the implementation and application of Experdite to a production circuit board

Using new and novel techniques to develop a process diagnostic system in basic oxygen steelmaking

The thesis will outline work done on developing an expert diagnostic system within the Basic Oxygen Steelmaking (BOS) at Tata Steel’s Port Talbot integrated steel works. The site in Port Talbot specialises in strip products, where this describes sheet steel for applications in car bodies, tin cans and a wide array of consumer white goods and construction. The flow chart below outlines the chapters of this thesis, briefly describing the main focus of each chapter, and how these sections relate to the BOS process stages

The ILIAD Program: An Expert Computer Diagnostic Program

journal articleBiomedical Informatic

Expert diagnosis of polymer electrolyte fuel cells

Diagnosing faulty conditions of engineering systems is a highly desirable process within control structures, such that control systems may operate effectively and degrading operational states may be mitigated. The goal herein is to enhance lifetime performance and extend system availability. Difficulty arises in developing a mathematical model which can describe all working and failure modes of complex systems. However the expert's knowledge of correct and faulty operation is powerful for detecting degradation, and such knowledge can be represented through fuzzy logic. This paper presents a diagnostic system based on fuzzy logic and expert knowledge, attained from experts and experimental findings. The diagnosis is applied specifically to degradation modes in a polymer electrolyte fuel cell. The defined rules produced for the fuzzy logic model connect observed operational modes and symptoms to component degradation. The diagnosis is then tested against common automotive stress conditions to assess functionality

The Galileo PPS expert monitoring and diagnostic prototype

The Galileo PPS Expert Monitoring Module (EMM) is a prototype system implemented on the SUN workstation that will demonstrate a knowledge-based approach to monitoring and diagnosis for the Galileo spacecraft Power/Pyro subsystems. The prototype will simulate an analysis module functioning within the SFOC Engineering Analysis Subsystem Environment (EASE). This document describes the implementation of a prototype EMM for the Galileo spacecraft Power Pyro Subsystem. Section 2 of this document provides an overview of the issues in monitoring and diagnosis and comparison between traditional and knowledge-based solutions to this problem. Section 3 describes various tradeoffs which must be considered when designing a knowledge-based approach to monitoring and diagnosis, and section 4 discusses how these issues were resolved in constructing the prototype. Section 5 presents conclusions and recommendations for constructing a full-scale demonstration of the EMM. A Glossary provides definitions of terms used in this text

Long –term load forecasting of power systems using Artificial Neural Network and ANFIS

Load forecasting is very important for planning and operation in power system energy management. It reinforces the energy efficiency and reliability of power systems. Problems of power systems are tough to solve because power systems are huge complex graphically, widely distributed and influenced by many unexpected events. It has taken into consideration the various demographic factors like weather, climate, and variation of load demands. In this paper, Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) models were used to analyse data collection obtained from the Metrological Department of Malaysia. The data sets cover a seven-year period (2009- 2016) on monthly basis. The ANN and ANFIS were used for long-term load forecasting. The performance evaluations of both models that were executed by showing that the results for ANFIS produced much more accurate results compared to ANN model. It also studied the effects of weather variables such as temperature, humidity, wind speed, rainfall, actual load and previous load on load forecasting. The simulation was carried out in the environment of MATLAB software