Detection and Diagnosis of Plant‐Wide Oscillations

Abstract

oscillations (Martin et al., 1991;Shunta, 1995). In this paper, we present an overview of some emerging techniques for the detection and diagnosis of plant-wide oscillations and demonstrate their effi cacy through an application to a process at Mitsubishi Chemical Corporation, Mizushima, Japan.Before a full-scale diagnosis exercise is undertaken, it is benefi cial to fi nd all signals oscillating at the same frequency as the root cause generally lies within this set. In contrast to this, most of the available techniques for detection focus on a This paper presents some emerging techniques for detection and root-cause diagnosis of plant-wide oscillations, and demonstrates their effi cacy through a successful industrial case study. The recently proposed autocorrelation function based method (Thornhill et al., J. Proc. Control 13, 91-100, 2003a) is used for detection of oscillations in the process measurements. Signals having common oscillations are analyzed for the presence of valve stiction using higher order statistical methods (Choudhury et al., Automatica 40, 1719-1728, 2004b). A method employing changes in controller gain is proposed for distinguishing an internally generated oscillation from an external oscillatory disturbance. This method of changing controller gain is used to confi rm the presence of control valve stiction. The proposed techniques have been used successfully to identify the root cause of plant-wide oscillations in an industrial case study using routine operating data.On présente dans cet article des techniques émergentes pour la détection et le diagnostic intrinsèques des oscillations à l'échelle de l'usine et on démontre leur effi cacité à travers une étude de cas industrielle réussie. On a recours à une méthode proposée récemment qui repose sur la fonction d'autocorrélation (Thornill et al., J. Proc. Control 13, 91-100, 2003a) pour la détection des oscillations dans les mesures de procédés. Les signaux ayant des oscillations communes sont analysés pour déterminer la présence de friction statique des vannes par des méthodes statistiques d'ordres supérieurs (Choudhury et al., Automatica 40, 1719-1728, 2004b). On propose une méthode employant des changements dans le gain du contrôleur pour distinguer une oscillation générée à l'intérieur du système à partir d'une perturbation oscillatoire externe. Cette méthode de changement du gain du contrôleur est utilisée pour confi rmer la présence de friction statique dans les vannes de régulation. Les techniques proposées sont utilisées avec succès pour déterminer les raisons intrinsèques des oscillations à l'échelle de l'usine dans une étude de cas industrielle utilisant des données opératoires de routine.

Diagnosis of Plantwide Oscillations: A Harmonics Analysis Approach

“…The general approach is to estimate the amplitudes, frequencies and phases for each term of Equation ( 2) and then examine the relationships among the frequencies to identify the presence of harmonics in the signal. [4] Suggested that it suffices to write the above expression only up to fifth harmonics for useful application of the analysis of chemical process data.…”

“…Thus, it is important for process control engineers to detect and diagnose the causes of oscillations or disturbances in a chemical process operation as soon as possible [2], [3]. Over the last few years, some studies were carried out to detect plantwide oscillations [4], [5] and to group the similar oscillations together. For the detection of oscillations in process measurements and identify signals with common oscillatory behavior, the use of spectral principal component analysis (PCA) [6] or autocorrelation function (ACF) [7] is suggested.…”

Improving Root Cause Analysis by Detecting and Removing Transient Changes in Oscillatory Time Series with Application to a 1,3-Butadiene Process

“…Methods for the isolation of the root cause of an oscillatory process disturbance include surrogate testing, , bispectra and related bicoherence, harmonics, and the spectral envelope method . A method using the spectral envelope is proposed by Jiang et al and Yuan and Qin use Granger causality in the spectral domain to isolate the root cause of oscillatory disturbances while Bauer et al adopt transfer entropy, a metric of causality based on information theory introduced by Schreiber, for the root cause analysis of oscillatory as well as nonoscillatory process disturbances.…”

Detection and diagnosis of Oscillation in Shell and Tube Heat Exchanger Process

“…In process measurements, autocorrelation based method is used for oscillation detection. Using higher order statistical methods, signals having oscillations are evaluated for the presence of nonlinearities in control valves [2]. Automatic assessment of loop performance mainly involves the detection of control loop oscillations [3].…”