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This paper presents a hybrid approach for online fault detection in nonlinear processes. To solve the possible monitoring difficulties caused by nonlinear characteristics of industrial process data, two applications of the Kernel Method: Hypersphere Support Vector Machine (HSSVM) and Kernel Principal Component Analysis (KPCA) are used as fault detection methods. On top of that, to obtain the adaptive...
The multi-level inverter system is becoming a very promising candidate to replace the conventional two-level inverter, but system reliability remains an open issue. The most common reliability problem is that power switch transistors have open-circuit or short-circuit faults during operation. In order to improve the accuracy of the fault diagnosis and accelerate the operation speed in a cascaded H-bridge...
The failure rate of non-steady conditions is much higher than the failure rate of steady conditions. So, it is important to monitor non-steady conditions of system. The systems' monitoring results indicate that there are large false alarms or missing alarms based on traditional process control methods. The primary problems are higher data dimension, more complex correlation among variables, non-Gaussian...
In order to improve the accuracy of the fault diagnosis and accelerate the operation speed in a cascaded H-bridge multilevel inverter system (CHMLIS), a fault diagnosis strategy based on Relative Principle Component Analysis-Support Vector Machine (RPCA-SVM) is presented in this paper. In this strategy, the output voltage of CHMLIS, which is preprocessed through the fast Fourier transform (FFT), is...
The principal component analysis method is usually used for fault detection under the steady conditions, however, when system works under the non-steady conditions, the false alarm rate and the missing alarm rate, tested by the T2 control limit, are so high. The main reason for this situation is that the sampled data is accord with normal distribution under the steady conditions, whereas the data...
In the process of industrial production, motors sometimes work in the second or fourth quadrant, namely, in the state of braking generation. In order to recycle the regenerative energy from these motors, a common DC bus, which is shared by multi-motors, could be adopted. To realize this idea, this paper presents a structure of common DC bus multi-motors AC drive system. At the same time, this paper...
This paper presents a multi-dimension predictive model PDRNN based on the diagonal recurrent neural networks with a parallel learning algorithm. This model can be used to predict not only values, but also some points in the multi-dimension space. And also its applications in multi-dimension prediction will be discussed in the paper. Some analysis results show the significant improvement to multi parameters...
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