A Design of a Monitoring Expert System of Flight Parameter

2013 ◽  
Vol 791-793 ◽  
pp. 874-877
Author(s):  
Yan Song Zhang ◽  
Hui Feng Zhang ◽  
Wei Ye ◽  
Chao Jiang Wang ◽  
Zhen Dong Xu
Keyword(s):  
Expert System ◽  
Real Time ◽  
Flight Test ◽  
Information Control ◽  
Digital Information ◽  
Video Information ◽  
Test Technology ◽  
Flight Controls ◽  
Flight Parameters ◽  
Special Circumstances

In order to meet the trend for flight test technology, this paper presents a monitoring expert system of flight parameters based on embedded technology , which can achieve real-time interpretation of flight data air and provide the parameters for the AHRS, engines, flight controls for aircraft crew members as well as the disposal of the special circumstances operating. It can be used for real-time collection and record a variety of digital information, control information and video information transmitting by the missiles and fiber during the fly testing process.

Storage Test Techniques and Wireless Transmission Based on Embedded System

2011 ◽  
Vol 128-129 ◽  
pp. 1020-1024
Author(s):  
Hong Wu ◽  
Tao Han ◽  
Can Wang
Keyword(s):  
Embedded System ◽  
Real Time ◽  
Moving Objects ◽  
Effective Means ◽  
Wireless Transmission ◽  
Storage Test ◽  
Sample Data ◽  
Test Technology ◽  
Long Time ◽  
Special Circumstances

Memory test technology is the most effective means to record the parameters of moving objects under special circumstances. This paper introduced the development of storage test systems based on ARM7LPC21XX. PHILIPS chip 16/32-bit microcontroller-LPC21XX was a 16/32-bit ARM7 TDMI-S CPU microcontroller based on a real-time emulation and embedded trace. It had two powers-saving modes-power down and idles, which could ensure the battery to work for a long time. The microcontroller internal 10-bit AD was used to sample data as well as SPI and NRF24L01 modules to realize communication.

A Real-Time Expert System Status Monitor

1991 ◽  
Author(s):  
R. Doraiswami ◽  
W. Liu
Keyword(s):  
Expert System ◽  
Real Time

An expert system for real-time well field management

2012 ◽  
Vol 12 (5) ◽  
pp. 699-706 ◽  
Author(s):  
B. S. Marti ◽  
G. Bauser ◽  
F. Stauffer ◽  
U. Kuhlmann ◽  
H.-P. Kaiser ◽  
...  
Keyword(s):  
Drinking Water ◽  
Expert System ◽  
Knowledge Base ◽  
Real Time ◽  
Urban Areas ◽  
Industrial Sites ◽  
Water Wells ◽  
Well Field ◽  
Field Management ◽  
Historical Management

Well field management in urban areas faces challenges such as pollution from old waste deposits and former industrial sites, pollution from chemical accidents along transport lines or in industry, or diffuse pollution from leaking sewers. One possibility to protect the drinking water of a well field is the maintenance of a hydraulic barrier between the potentially polluted and the clean water. An example is the Hardhof well field in Zurich, Switzerland. This paper presents the methodology for a simple and fast expert system (ES), applies it to the Hardhof well field, and compares its performance to the historical management method of the Hardhof well field. Although the ES is quite simplistic it considerably improves the water quality in the drinking water wells. The ES knowledge base is crucial for successful management application. Therefore, a periodic update of the knowledge base is suggested for the real-time application of the ES.

Expert system for real-time aircraft monitoring

1992 ◽  
Vol 29 (1) ◽  
pp. 79-84
Author(s):  
Joey B. Flanders ◽  
Charles H. Jones ◽  
Robin M. Madison
Keyword(s):  
Expert System ◽  
Real Time

scholarly journals Diagnostics and Prognostics of Energy Conversion Processes via Knowledge-Based Systems

Proceedings ◽  
2020 ◽  
Vol 58 (1) ◽  
pp. 1
Author(s):  
Roberto Melli ◽  
Enrico Sciubba
Keyword(s):  
Expert System ◽  
Knowledge Base ◽  
Real Time ◽  
System Analysis ◽  
Intelligent System ◽  
Time Derivative ◽  
Time History ◽  
Control Procedure ◽  
Time Data ◽  
Ongoing Research

This paper presents a critical and analytical description of an ongoing research program aimed at the implementation of an expert system capable of monitoring, through an Intelligent Health Control procedure, the instantaneous performance of a cogeneration plant. The expert system is implemented in the CLIPS environment and is denominated PROMISA as the acronym for Prognostic Module for Intelligent System Analysis. It generates, in real time and in a form directly useful to the plant manager, information on the existence and severity of faults, forecasts on the future time history of both detected and likely faults, and suggestions on how to control the problem. The expert procedure, working where and if necessary with the support of a process simulator, derives from the available real-time data a list of selected performance indicators for each plant component. For a set of faults, pre-defined with the help of the plant operator (Domain Expert), proper rules are defined in order to establish whether the component is working correctly; in several instances, since one single failure (symptom) can originate from more than one fault (cause), complex sets of rules expressing the combination of multiple indices have been introduced in the knowledge base as well. Creeping faults are detected by analyzing the trend of the variation of an indicator over a pre-assigned interval of time. Whenever the value of this ‘‘discrete time derivative’’ becomes ‘‘high’’ with respect to a specified limit value, a ‘‘latent creeping fault’’ condition is prognosticated. The expert system architecture is based on an object-oriented paradigm. The knowledge base (facts and rules) is clustered—the chunks of knowledge pertain to individual components. A graphic user interface (GUI) allows the user to interrogate PROMISA about its rules, procedures, classes and objects, and about its inference path. The paper also presents the results of some simulation tests.

Sign in / Sign up

Export Citation Format

Share Document