Expert System Supporting the Diagnosis of the Wind Farm Equipments

2018 ◽  
pp. 432-441
Author(s):  
Dariusz Bernatowicz ◽  
Stanisław Duer ◽  
Paweł Wrzesień
Keyword(s):  
Expert System ◽  
Wind Farm

scholarly journals Knowledge base of wind farm devices in the computer expert system

2018 ◽  
Vol 67 (2) ◽  
pp. 179-190
Author(s):  
Radosław Duer ◽  
Paweł Wrzesień ◽  
Stanisław Duer ◽  
Dariusz Bernatowicz
Keyword(s):  
Artificial Intelligence ◽  
Expert System ◽  
Knowledge Base ◽  
Wind Farm ◽  
Diagnostic Information ◽  
Diagnostic Model ◽  
Technical Diagnostics ◽  
Wind Power Plant ◽  
Power Plant Equipment ◽  
Plant Equipment

The article presents the problems of determining diagnostic information for the needs of testing the state of wind farm equipment. To this end, the essence of developing a functional and diagnostic model on the example of wind power plant equipment has been presented and described. Based on the developed model of the examined object, diagnostic information was determined in the form of a set of basic elements and a set of diagnostic signals, which are developed by the designated j-elements in the i-functional units of the object. The article presents a description of the process of building a knowledge base for an expert system. Keywords: technical diagnostics, diagnostic reasoning, multivalent logic, artificial intelligence

scholarly journals Knowledge base for wind farm devices in the computer expert system

2020 ◽  
Vol 68 (4) ◽  
pp. 107-118
Author(s):  
Radosław Duer ◽  
Stanisław Duer ◽  
Lech Drawski
Keyword(s):  
Artificial Intelligence ◽  
Renewable Energy ◽  
Expert System ◽  
Knowledge Base ◽  
Wind Farm ◽  
Expert Knowledge ◽  
Diagnostic Information ◽  
Diagnostic Model ◽  
Technical Diagnostics ◽  
Model Based

The article presents the issue of determining diagnostic information for the needs of testing the condition of wind farm equipment. To this end, the essence of the structure of an intelligent expert system was presented and described. The structure of the tested object is shown in the form of a functional and diagnostic model. Based on the developed model of the examined object, diagnostic information was determined in the form of a set of basic elements and a set of diagnostic signals, which are later used in the construction of an expert knowledge base. The expert knowledge base is determined by sets of facts and rules applied. An important part of this article is description of the structure of the expert system and the expert knowledge base used in it. Keywords: wind farm, renewable energy, technical diagnostics, diagnostic inference, artificial intelligence

An expert system for FMS control

1993 ◽  
Vol 2 (4) ◽  
pp. 223 ◽  
Author(s):  
Wang Chengen ◽  
Zhu Jianying ◽  
Wei Zhongxin
Keyword(s):  
Expert System

HAZARD: An Expert System for Risk Assessment of Environmental Chemicals

1987 ◽  
Vol 26 (01) ◽  
pp. 13-23 ◽  
Author(s):  
H. W. Gottinger
Keyword(s):  
Expert System ◽  
Structural Information ◽  
Chemical Carcinogenesis ◽  
Structural Features ◽  
Environmental Chemicals ◽  
Chemical Carcinogens ◽  
Carcinogenic Activity ◽  
Current State ◽  
Structure Activity ◽  
Carcinogenic Potential

AbstractThe purpose of this paper is to report on an expert system in design that screens for potential hazards from environmental chemicals on the basis of structure-activity relationships in the study of chemical carcinogenesis, particularly with respect to analyzing the current state of known structural information about chemical carcinogens and predicting the possible carcinogenicity of untested chemicals. The structure-activity tree serves as an index of known chemical structure features associated with carcinogenic activity. The basic units of the tree are the principal recognized classes of chemical carcinogens that are subdivided into subclasses known as nodes according to specific structural features that may reflect differences in carcinogenic potential among chemicals in the class. An analysis of a computerized data base of known carcinogens (knowledge base) is proposed using the structure-activity tree in order to test the validity of the tree as a classification scheme (inference engine).

ANALYSIS OF PLANT FRAGARIA XANANASSA DISEASE DIAGNOSES USING PRODUCTION RULES BASE ON EXPERT SYSTEM

2020 ◽  
Vol 16 (1) ◽  
pp. 25-32
Author(s):  
Basiroh Basiroh ◽  
Wiji Lestari
Keyword(s):  
Expert System ◽  
Early Diagnosis ◽  
General Public ◽  
Insect Pests ◽  
Fruit Rot ◽  
Proper Treatment ◽  
Harvest Time ◽  
Production Rules

Errors that occur in solving problems in strawberry plants (Fragaria Xananassa) such as the presence of leaf patches, fruit rot, perforated leaves, and insect pests can be the cause of not maximum in harvest time. The farmers and the general public who planted strawberry (Fragaria Xananassa) need to know the proper treatment of diseases and pests so that future yields as expected. Therefore, it takes an application as a solution in the delivery of information related to the problems that are often encountered in strawberry plants (Fragaria Xananassa). Methods of production rules can be used to diagnose the disease strawberry (Fragaria Xananassa) based on signs or symptoms that occur in the parts of plants and strawberry, the results of diagnosis using this method are the same as we do Consultation on experts.  The purpose of this study was to determine the early diagnosis of disease in strawberry plants (Fragaria Xananassa) based on signs or symptoms that occur in the plant and fruit parts. The results of the analysis of this study showed that the validation of disease and symptom data in strawberry plants (Fragaria Xananassa) reached 99%, meaning that between the data of symptoms and disease understudy the accuracy was guaranteed with the experts.

Sign in / Sign up

Export Citation Format

Share Document