Alternate path reasoning in intelligent instrument fault diagnosis for gas chromatography

Abstract

elligent instrument fault diagnosis is addressed in this orks, a hybrid technique which sed expert systems with neural style training. One of the most difficult aspects ment fault diagnosis is developing an appropriate rk. Beginning with an initial rts, a more accurate representation can be found using example data. ning alternate paths of reaand incorporating them into the expert network is oses interaction and cotended to be used with stance of the expert to incorporate knowledge disfrom the data into the intelligent diagnosis tool. this methodology are conducted within the problem chromatography. Pereficacy of automating the asoning into the diagnostic 1 introduction