Pattern Classification

Abstract

Today’s processes are heavily instrumented, with a large amount of data collected on-line and stored in computer databases. Much of the data are usually collected during out-of-control operations. When the data collected during the out-of-control operations have been previously diagnosed, the data can be categorized into separate classes where each class pertains to a particular fault. When the data have not been previously diagnosed, cluster analysis may aid the diagnoses of the operations during which the data were collected [299], and the data can be categorized into separate classes accordingly. If hyperplanes can separate the data in the classes as shown in Figure 3.1, these separating planes can define the boundaries for each of the fault regions. Once a fault is detected using on-line data observations, the fault can be diagnosed by determining the fault region in which the observations are located. Assuming the detected fault is represented in the database, the fault can be properly diagnosed in this manner.