As disturbances and other factors often lead to shifting of work point in industrial process

it is particularly important to timely and accurately identify process changes. Current working condition identification methods mainly focus on whether or what fault occurs

but few consider process conditions from viewpoint of safety

economy

fault and other aspects. Decision criteria at different safety and economic conditions were proposed by combination of historical process data and related operational requirements. With these criteria

data characteristics was extracted by DAE method and extracted feature data was clustered by SOM method. Then

the process state was visually projected to two-dimensional maps. In this method

the DAE method can reduce influence of industrial process disturbance on data and the SOM method can better visually monitor process performance. Experimental study showed that the DAE-SOM multi-layer mapping method can determine security level

type of failure

and current economic efficiency of the system.