Detecting Multiple Plant-wide Oscillations in Process Control Systems Based on Multivariate Intrinsic Chirp Component Decomposition

Abstract

An oscillation originating at one place tends to propagate to other parts of the plant due to underlying interactions and connected process flows, thus causing plant-wide oscillations. The plant-wide oscillations can result in unstable product quality, equipment wear, security degradation. Therefore, it is of importance to detect the plant-wide oscillations to maintain the control system performance. This paper proposes an MICCD-based (multivariate intrinsic chirp component decomposition) detector, which is able to detect and analyze the plant-wide oscillations. Firstly, we present the MICCD algorithm, which is an extension of intrinsic chirp component decomposition (ICCD). Then, the plant-wide oscillations is decomposed into a series of multivariate nonlinear chirp modes by MICCD. Following, the normalized correlation index, regualrity index, and sparseness index are used to identify the oscillation modes. Compared with the existing methods, the proposed method can process both time-invariant and time-varying multiple plant-wide oscillations and provide corresponding time-frequency information. The effectiveness and superiority of the MICCD-based detector are demonstrated via simulations as well as industrial cases.