This paper proposes a new approach of plant fault diagnosis which is based on detecting the characteristic pattern signals and associating them with the corresponding faults. The new approach does not require analytic modeling of the target system but best reflects the expertise embedded in the experienced human operation by mimicking them in a systematic way. This paper intends to illustrate the feasibility of the proposed by developing the algorithms to detect and estimate the typical characteristic pattern signals, I. e., oscillatory patterns, and applying them to the diagnosis of various faults of a 500MW boiler control system including tube rupture, feed-water leak, and controller failure.