Fault detection of the boiler unit using state space neural networks
نویسندگان
چکیده
This paper deals with the application of state space neural network models to fault detection of the boiler unit. The work describes problems such us selecting the proper threshold for compromising both fault sensitivity and early fault detection, designing proper neural network structure or calculating performance indexes. All the simulation data used in experiments are collected from the simulator of the boiler unit implemented in Matlab/Simulink.
منابع مشابه
Robust Fault Detection on Boiler-turbine Unit Actuators Using Dynamic Neural Networks
Due to the important role of the boiler-turbine units in industries and electricity generation, it is important to diagnose different types of faults in different parts of boiler-turbine system. Different parts of a boiler-turbine system like the sensor or actuator or plant can be affected by various types of faults. In this paper, the effects of the occurrence of faults on the actuators are in...
متن کاملRobust fault detection and accommodation of the boiler unit using state space neural networks
This paper deals with the application of state space neural network models to fault detection and accommodation of the boiler unit. The work describes two aspects. First one is the fault detection and in this paper to diagnose the fault the three methods are described and compared: simple and adaptive threshold and more robust method which is model error modelling. The second part of the paper ...
متن کاملDetection of Single and Dual Incipient Process Faults Using an Improved Artificial Neural Network
Changes in the physicochemical conditions of process unit, even under control, may lead to what are generically referred to as faults. The cognition of causes is very important, because the system can be diagnosed and fault tolerated. In this article, we discuss and propose an artificial neural network that can detect the incipient and gradual faults either individually or mutually. The mai...
متن کاملOptimal Rotor Fault Detection in Induction Motor Using Particle-Swarm Optimization Optimized Neural Network
This study examined and presents an effective method for detection of failure of conductor bars in the winding of rotor of induction motor in low load conditions using neural networks of radial-base functions. The proposed method used Hilbert method to obtain the stator current signal push. The frequency and signal amplitude of the push stator were used as the input of the neural network and th...
متن کاملStability Analysis of the Neural Network Based Fault Tolerant Control for the Boiler Unit
This paper deals with the stability analysis of the fault accommodation control system. When a fault is detected, the fault tolerant control tries to compensate the fault effect by adding to the standard control the auxiliary signal. This auxiliary control constitutes the additional control loop which can influence the stability of the entire control system. This paper focuses on the stability ...
متن کامل