Contents I. Introduction
The essential concept of cause-effect space of resources is pioneered in this paper, along with the cause-effect grey relational analysis which is predicated on the basis. Practically, establishing expert diagnosis models to identify the normal objects or conditions automatically is important for engineers or researchers. The applications of diagnosis model, ranging from failure detecting through hazard preventing to pattern recognizing [5]–[8], are widely discussed and demonstrated for the essentiality. Process plant operators often have to respond to many alarms. Nuisance alarms often clutter and obscure an operator's view of critical and important information, with potentially severe consequences [1]–[3]. Although the diagnosis problems have been widely discussed in various studies and comprehensively utilized in different fields, literatures show that there still are some limitations in practice. An alarm management system for acquiring message data for alarms issued from a process and analyzing alarm behaviors, comprising: alarm selection means for automatically selecting unnecessary alarms from said message data; and alarm suppression processing means for preventing said unnecessary alarms from being issued according to the results of selection by said alarm selection means. The intelligent alarm management system suppresses nuisance alarms and provides valuable advisory information to help operators quickly focus on important alarm information and take correct actions [4].
