Abstract
The reliability and safety of the cascade system, which is widely applied, have attached attention increasingly. Fault detection and diagnosis can play a significant role in enhancing its reliability and safety. On account of the complexity of the double closed-loop system in operation, the problem of fault diagnosis is relatively complex. For the single fault of the second-order valued system sensors, a real-time fault diagnosis method based on data-driven is proposed in this study. Off-line data is employed to establish static fault detection, location, estimation, and separation models. The static models are calibrated with on-line data to obtain the real-time fault diagnosis models. The real-time calibration, working flow and anti-interference measures of the real-time diagnosis system are given. Experiments results demonstrate the validity and accuracy of the fault diagnosis method, which is suitable for the general cascade system.
Highlights
College of Mechanical and Electrical Engineering, China Jiliang University, Hangzhou 310018, China; Abstract: The reliability and safety of the cascade system, which is widely applied, have attached attention increasingly
This study proposes a real-time single fault diagnosis of sensors in a cascade system based on data-driven by studying the off-line historical data of the double tank
When the major loop sensor fails, the level fluctuation value (LLFV) in the lower water tank (LWT) at the failure sampling moment can be known by the fault detection algorithm, and the fault occurrence time is known as tMF by the fault location algorithm Formulas (10) and (11)
Summary
Cascade System Based on Currently, the control system is showing a trend of complexity and large-scale. This study proposes a real-time single fault diagnosis of sensors in a cascade system based on data-driven by studying the off-line historical data of the double tank. This method solves the shortcomings of the above techniques and has the following advantages. First, establishes the static models of sensor fault detection, fault location, fault estimation and fault separation in cascade system; The second is proposes a method of calibrating static models by using on-line data to obtain real-time fault diagnosis models; gives the workflow and anti-interference measures of the real-time diagnosis system. The effectiveness and accuracy of fault diagnosis were verified by experiments
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