Conference Program of WCICA 2012

Conference Program WCICA 2012
idate that both the control strategies and Modeling methods discussed
in this paper are efficient.
◁ PFrA-57
Turbine Machine Fault Diagnosis Using Modified Redundant Second
Generation Wavelet Packet Transform, pp.3126–3130
Li, Ning
Zhou, Rui
Shanghai Second Polytechnic Univ.
China Ship Development & Design Center
Faulty features extraction is an essential problem in the field of largescale
electromechanical equipment faulty diagnosis. Classical vibration
faulty features extraction is based on spectral analysis method, while
the wavelet transform provides a novel tool to solve this problem. In
this paper, the problem of frequency band derangement inhering in redundant
second generation wavelet packet transform (RSGWPT) was
explained and the causes were pointed out. Then a modified redundant
second generation wavelet packet transform which can make the
order of decomposed subband signals to be consistent with the linear
partition order of frequency band is proposed. The modified RSGW-
PT discards the split and merge operations in the decomposition and
reconstruction stages and directly use the constructed operators to accomplish
prediction and update steps. Thus the signal length at each
level is the same with the original signal, accordingly more information
of the time domain features can be preserved, and at the same
time the aliasing of RSGWPT can be inhibited effectively. This method
was applied to analyze the simulated signals and the practical turbine
machine vibration faulty signals. Testing results show that the proposed
improved RSGWPT method is quite effective in extracting the faulty features
from the vibration signal, so it can be effectively applied to the fault
diagnosis of turbine machine.
◁ PFrA-58
Study on Time Registration method for Photoelectric TheodoliteData
Fusion, pp.3137–3139
YANG, Hong Tao
GAO, Hui-bin
Changchun Univ. of Tech.
Changchun Inst. of Optics, Fine Mechanics &
Physics,Chinese Acad. of Sci.
In range measurement, theodolite and radar constitute a real-time
tracking system at different sites to track the same target in the air and
get useful information exactly and timely.As the optical theodolite and
radar have different sampling frequency and measurement system, the
data is sent to the fusion center is asynchronous.This paper proposed
a time registration method based on multi-sensor data using Wavelet
neural network algorithm,which not only better solved the basic problems
of theodolite fusion tracking but also improve the efficiency of data
fusion.Simulation experiment and comparison with other time registration
method have shown the advantage of this method.
◁ PFrA-59
Parameter Identifiability of Quantized Linear Systems, pp.3140–3145
Shen, Ying
Zhang, Hui
Zhejiang Univ.
Zhejiang Univ.
The parameter identifiability of quantized linear systems with Gauss-
Markov parameters was discussed from information theoretic point of
view. The presented definition of parameter identifiability was reviewed
and extended to quantized systems by considering the intrinsic property
of the system. Then the parameter identifiability of linear systems with
quantized outputs was analyzed and the criterion of parameter identifiability
was proposed based on the measure of mutual information.
Furthermore, the convergence property of the quantized parameter i-
dentifiability Gramian was analyzed.
◁ PFrA-60
Nonlinear Process Fault Diagnosis based on Slow Feature Analysis,
pp.3152–3156
Deng, Xiaogang
Tian, Xue-Min
Hu, Xiangyang
China Univ. of Petroleum
China Univ. of Petroleum
Hekou Production Factory of Shengli Oilfield
Invariant features of temporally varying signals are very useful for process
monitoring. A novel nonlinear process fault diagnosis method is
proposed in this paper based on slow feature analysis (SFA) which is
a new invariant learning method. In the proposed method, input-output
transformation functions are optimized to extract the nonlinear slowly
varying components as invariant features. Based on feature variables,
two monitoring statistics are constructed for fault detection and their
confidence limits are computed by kernel density estimation. Simulation
using continuous stirred tank reactor (CSTR) system shows that the
proposed method outperforms the traditional PCA and KPCA method.
◁ PFrA-61
Fault Diagnosis of Hydraulic Variable Pitch for Wind Turbine Based on
Qualitative and Quantitative Analysis, pp.3181–3185
Han, Xiaojuan
Zhang, Hao
Chen, Yueyan
Zhang, Xilin
Wang, Chengmin
North China Electrical Power Univ.
North China Electrical Power Univ.
North China Electrical Power Univ.
Changchun Power Supply Company
Shanghai Jiao Tong Univ.
Qualitative analysis and quantitative analysis are combined to carry on
hydraulic variable pitch system fault diagnosis of wind turbine. Fault tree
model of hydraulic system is established by the analysis of hydraulic
system fault symptoms set. Petri net model of hydraulic system fault
can be obtained by fault tree using the matrix operations of Petri net to
achieve the conversion from qualitative to quantitative which can make
up the shortcoming of fault tree model inclining to qualitative analysis
when the basic event is difficult to determine its occurrence probability.
The validity of the model is verified by simulation example.
◁ PFrA-62
Modeling and Control Simulation for Force Couple Leveling System of
Hydraulic Press, pp.3186–3190
Du, Chunyan
Xing, Guansheng
Jia, Chao
Tianjin Univ.
Hebei Univ. of Tech.
tianjin Univ. of Tech.
This paper studies force couple leveling system of heavy hydraulic
press. A multi-input and multi-output nonlinearmodel is established on
the basis of analyzing hydraulic structure and block kinematics. A cascade
control structure is designed for the leveling system. In the outer
loop, each corner follows the average displacement other two corners
adjacent to it using PI method, and the desired pressure of inner loop
is given. In the inner loop the cylinder pressure is controlled using parameter
variable PD method. Modeling and control simulation in Matlab
show that the designed control method has a good synchronization effect
.
◁ PFrA-63
Research on the Application and Compensation for Startup Process of
FOG Based on RBF Neural Network, pp.3195–3199
SHEN, Jun
MIAO, Ling-juan
GUO, ZIWEI
Beijing Inst. of Tech.
Beijing Inst. of Tech.,
Beijing Inst. of Tech.
As the core components of Fiber Optic Gyroscope (FOG) are sensitive
to temperature, there is a certain temperature drift error in the working
process of FOG. In particular, during the period from supplying power
to achieving the nominal precision, the temperature drift of FOG is
much higher. In this paper, for reducing the drift in the startup process
of FOG and shortening the time of FOG startup, a scheme based on
Radial Basis Function (RBF) neural networks is designed to compensate
the drift in the startup process of FOG. The RBF neural network
use the two inputs and single output scheme that use the temperature
of FOG and the temperature change rate as the inputs and use the drift
of FOG as the output. In the room temperature, the RBF neural network
is used to compensate for the startup process of FOG, and the results
show that the method can effectively reduce the drift and startup time
of the FOG. This method is used in a certain type of FOG North Finder
and can greatly reduce the North Finder preparation time and improve
the north-seeking accuracy.
◁ PFrA-64
Short-Term Wind Speed Prediction Model of LS-SVM Based on Genet-
118