Identification of Steady State and Transient State

Sheng Yu1, Xiangshun Li1
1School of Automation, Wuhan University of Technology, Wuhan, China

Tóm tắt

Identification of steady state and transient state plays an important role in modeling, control, optimization, and fault detection of industrial processes. Many existing methods for state identification are not satisfactory in practical applications due to problems of ideal hypothesis, too many parameters, and poor robustness. In this paper, a novel state identification approach is proposed. The problem of state identification is transformed into finding the noise band of differential signal. For practical application, automatic selection of noise band amplitude is proposed to make the method convenient to be used. Problems of gross errors, low signal-to-noise ratio and online identification are considered. And comparison with other two methods shows that the proposed method has better identification performance. Simulations and experiments also prove the effectiveness and practicability of the proposed method.

Tài liệu tham khảo

TIAN Y, ZOU Q, HAN J. Data-driven fault diagnosis for automotive PEMFC systems based on the steady-state identification [J]. Energies, 2021, 14(7): 1918.

LI J Z, GAO M, LÜ Y, et al. Overview on the steady-state detection methods of process operating data [J]. Chinese Journal of Scientific Instrument, 2013, 34(8): 1739–1748 (in Chinese).