It's a evident phenomenon when rub any two different material will
generate static electricity. Sometimes in
industrial processelectrostatic
discharge is dangerous when ambience is instinct with flammable gas.
This project tries to solve the problem of EEIC prediction using the
ANFIS[Jang93]approach. The problem of EEIC prediction
is concerned with the use of attributes of a specific electrostatic eliminator
and surrounding condition, such as eliminator brand ,between eliminator
and object interval, object voltage, and so on, in order to estimate the
ion current of the electrostatic eliminator which can eliminate static electricity.
The EEIC prediction problem is first making experiment to get useful data then
ANFIS model this definite system. Finally the finished model
has been traned we will implement by cgi of WWW and provide
indurial process or safety engineer a powerful way to avoid explosive
accident by electrostatic discharge.
Description:
The data concerns electrostatic eliminator ion current(EEIC), to be
predicted in terms of 3 multivalued discrete and 5 continuous
continuous inputs. There are totally 2953 instances, each with 8 inputs and
1 output:
Data Collection and Input Selection: according to physical attribute and get 8 inputs.
but some inputs is dependence, so remain three most
decisive inputs, including bland,voltage and interval.
Model Selection: ANFIS.
ANFIS Training: adjust ANFIS internal parameter such as iterative epochs,
the number of partition rembership function,and so on.
implement cgi of WWW from final ANFIS parameter: when capture optimal
ANFIS parameter we will implement forwrad pass program
on WWW by c language.and anyone can access to predict
industral process hazardous rate.
We get final optimal ANFIS parameter then used c language to convert CGI program and provide any factory
to prevent explosion caused by electrostatic discharge。