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ABSTRACT: Principal component analysis (PCA) is a popular fault detection technique. It has been widely used in process industries, especially in the chemical industry. In industrial applications, achieving a sensitive system capable of detecting incipient faults, which maintains the false alarm rate to a minimum, is a crucial issue. Although a lot of research has been focused on these issues for PCA-based fault detection and diagnosis methods, sensitivity of the fault detection scheme versus false alarm rate continues to be an important issue. In this paper, an improved PCA method is proposed to address this problem. In this method, a new data preprocessing scheme and a new fault detection scheme designed for Hotelling's T2 as well as the squared prediction error are developed. A dynamic PCA model is also developed for boiler leak detection. This new method is applied to boiler water/steam leak detection with real data from Syncrude Canada's utility plant in Fort McMurray, Canada. Our results demonstrate that the proposed method can effectively reduce false alarm rate, provide effective and correct leak alarms, and give early warning to operators.
ISA Transactions 08/2005; 44(3):379-97. · 1.11 Impact Factor
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ABSTRACT: Boilers are important processes in chemical and refinery industries: they are normally operated for an extended period of time, leading to (water/steam) tube leaks because of aging and corrosion. To maintain production in normal and safe conditions, detecting the possible boiler leaks in time is crucial. In this paper, a process model is proposed to describe the boiler tube leak problem. On the basis of this model and the boiler characteristics, a least-squares method with a forgetting factor is derived to detect boiler leakage. The analysis of leak estimation properties for the proposed method is given under certain conditions of boiler operation. The applications based on both simulation and real plant data show that the proposed method is capable of detecting boiler leaks effectively and efficiently.
10/2002;
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ABSTRACT: In industrial processes, pipes and tanks may leak and sensors may
have biases since corrosion, measuring noises and instrument faults
exist. In order to maintain production in normal and safe conditions,
detecting possible faults of production equipment on time is crucial. In
the paper, a process model is proposed to describe a boiler tube leak
problem. Based on this model, least-squares methods with constant and
time-varying forgetting factors are presented to detect the leakage and
sensor bias. The application in a boiler system shows that the proposed
methods can detect the boiler tube leakage more effectively than the
method without forgetting factors
Decision and Control, 2001. Proceedings of the 40th IEEE Conference on; 02/2001
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ABSTRACT: This paper presents a new adaptive decoupling controller for
multivariable bilinear systems with non-diagonal coefficient matrix of
stochastic noises. The controller combines the feedforward control
strategy with the generalized minimum variance approach and performs the
decoupling of the control loop dynamically as well as in the steady
state. It can control the bilinear systems whose linear part is not
necessarily of minimum phase. The proof of global convergence for the
algorithm is also provided. Simulation results demonstrate the
effectiveness of the controller
IEEE Transactions on Automatic Control 05/2000; · 2.11 Impact Factor
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ABSTRACT: This paper presents an intelligent multivariable fault tolerant
control method in the presence of actuator failures. This method employs
multiple controllers for different operating environment and condition.
Those controllers are designed to regulate system in normal condition
and actuator failures, respectively, and can maintain closed loop system
stability as well as system outputs within previous given limits under
failures. In order to improve the system performance during the time of
actuator failures, online manual control in combination with an pole
placement controller is introduced. Simulation result demonstrate that
the proposed fault tolerance control method can effectively improves
control system behaviors
Systems, Man, and Cybernetics, 1998. 1998 IEEE International Conference on; 11/1998
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ABSTRACT: This paper presents a new self-tuning decoupling controller for a
class of multivariable bilinear systems. The controller employs a
slightly modified recursive least-squares estimator and uses a
generalized minimum variance control technique. The proof of global
convergence of the controller is given
Industrial Technology, 1996. (ICIT '96), Proceedings of The IEEE International Conference on; 01/1997
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ABSTRACT: For a class of deterministic and stochastic bilinear systems,
“modified self-tuning regulators” are given by using
recursive least-squares and modified recursive least-squares,
respectively. The closed-loop systems are shown globally stable and
asymptotically optimal in some sense without any restriction on location
of poles or zeros of nominal linear part of the open-loop system
considered. Simulations show that the methods used here work very well
IEEE Transactions on Automatic Control 02/1994; · 2.11 Impact Factor
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ABSTRACT: This paper presents a new one-step-ahead adaptive control
algorithm for deterministic bilinear systems (DBLS). The global
convergence of this algorithm is established. It is proved that the
algorithm will ensure the system input and output are bounded and the
generalized tracking error achieves its global minimum possible value
for any feedback control, even for nonminimum phase systems. Simulation
results verify its effectiveness and applicability
Industrial Electronics, 1992., Proceedings of the IEEE International Symposium on; 06/1992
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ABSTRACT: A model-based least-squares algorithm with a time-varying forgetting factor is developed for leak detection in boiler steam-water systems. The algorithm has been tested using real industrial data from Syncrude Canada, and has proven to be effective in detection of boiler tube or steam leaks; proper implementation of the algorithm would lead to early leak warning, which is important in maintaining safe operation of the plant.
