Mine Fan Fault Diagnosis Based on EMD and SVM

2011 ◽  
Vol 63-64 ◽  
pp. 449-452 ◽  
Author(s):  
Jun Fa Leng ◽  
Shuang Xi Jing
Keyword(s):  
Fault Diagnosis ◽  
Condition Monitoring ◽  
Pattern Classification ◽  
Diagnostic System ◽  
New Method ◽  
Intelligent Diagnosis ◽  
Linear Pattern ◽  
Non Linear ◽  
On Line ◽  
Integrative Method

In this research, a new method based on EMD and SVM for mine fan fault diagnosis is introduced. With EMD, fault feature can be extracted quickly and accurately, and taken as the input samples for SVM with the outstanding non-linear pattern classification performances. 5 two-class SVM classifiers are designed in order to classify and diagnosis 5 typical fault patterns of mine fan. The result of this research shows that the integrative method of EMD and SVM is very fit for the intelligent diagnosis and fault patterns recognition, and it will lead to the possible development of an automated and on-line mine fan condition monitoring and diagnostic system.

Internet/Intranet Based Remote Condition Monitoring and Fault Diagnosis Scheme and System for Steam Turboset

2005 ◽  
Vol 293-294 ◽  
pp. 365-372 ◽  
Author(s):  
Yong Yong He ◽  
Wen Xiu Lu ◽  
Fu Lei Chu
Keyword(s):  
Fault Diagnosis ◽  
Power System ◽  
Electric Power ◽  
Condition Monitoring ◽  
Economic Benefits ◽  
Electric Power System ◽  
The Internet ◽  
Time Data ◽  
On Line ◽  
Line Condition

The steam turboset is the key equipment of the electric power system. Thus, it is very important and necessary to monitor and diagnose the running condition and the faults of the steam turboset for the safe and normal running of the electric power system. In this paper, the Internet/Intranet based remote condition monitoring and fault diagnosis scheme is proposed. The corresponding technique and methods are discussed in detail. And a real application system is developed for the 300MW steam turboset. In this scheme, the system is built on the Internet/Intranet and the Client/Server construction and Web/Server model are adopted. The proposed scheme can guarantee real-time data acquisition and on-line condition analysis simultaneously. And especially, the remote condition monitoring and fault diagnosis can be implemented effectively. The developed system has been installed in a power plant of China. And the plant has obtained great economic benefits from it.

A New Design Method for the Fault Diagnosis on the Rotating Rectifier of Aeronautic Synchronous Generator

2012 ◽  
Vol 548 ◽  
pp. 544-547
Author(s):  
Yong Zhi Liu ◽  
Cong Liu
Keyword(s):  
Fault Diagnosis ◽  
Feature Vector ◽  
Design Method ◽  
Synchronous Generator ◽  
New Method ◽  
Test Analysis ◽  
Exciting Current ◽  
On Line

A new method of fault diagnosis on the rotating rectifier of aeronautic synchronous is raised in the work. Firstly, the condition, truth and approach of EMD are introduced, and the method and steps of building up the feature vector are also included, Secondly the theories of LS-SVM and the arithmetic in the classification are also included. Finally taking the faults of one and two diodes turning off for example, after extracting the feature vector of exciting current based on EMD and establishing the classifying method based on Gauss RBF LS-SVM, the test, analysis and comparison can be on between LS-SVM and NN the conclusion can be got that the classified method referred in the work owns higher exactness, takes less time and has more application on the on-line fault diagnosis NN.

Fuzzy model-based condition monitoring and fault diagnosis of a diesel engine cooling system

2002 ◽  
Vol 216 (3) ◽  
pp. 215-224 ◽  
Author(s):  
J A Twiddle ◽  
N B Jones
Keyword(s):  
Fault Diagnosis ◽  
Diesel Engine ◽  
Condition Monitoring ◽  
Cooling System ◽  
Fuzzy Model ◽  
Operating Conditions ◽  
Experimental Simulation ◽  
Model Based ◽  
Potential System ◽  
On Line

This paper describes a fuzzy model-based diagnostic system and its application to the cooling system of a diesel engine. The aim is to develop generic cost-effective knowledge-based techniques for condition monitoring and fault diagnosis of engine systems. A number of fuzzy systems have been developed to model the cooling system components. Residuals are generated on line by comparison of measured data with model outputs. The residuals are then analysed on line and classified into a number of fuzzy classes symptomatic of potential system conditions. A fuzzy rule-based system is designed to infer a number of typical fault conditions from the estimated state of the valve and patterns in the residual classes. The ability to diagnose certain faults in the system depends on the state of the thermostatic valve. The diagnostic systems have been tested with data obtained by experimental simulation of a number of target fault conditions on a diesel generator set test bed. In five test cases for separate cooling system operating conditions, the diagnostic system's successful diagnosis rate ranged between 73 and 97.7 per cent of the test data.

Engine Fault Diagnostic System Based on Non-Linear Support Vector Machine

2012 ◽  
Vol 229-231 ◽  
pp. 534-537
Author(s):  
Gao Huan Xu ◽  
Jun Xiang Ye
Keyword(s):  
Support Vector Machine ◽  
Fault Diagnosis ◽  
Diagnostic System ◽  
Support Vector ◽  
Linear Support Vector Machine ◽  
Diagnosis System ◽  
The Core ◽  
Wavelet Energy ◽  
Non Linear ◽  
Fault Diagnosis System

The car engine failures in the course of time and place have many possibilities. The engine fault diagnosis system developed in .NET platform. The core of the system make use of noise wavelet energy features and non-linear support vector machine classification. After the experiment, the system has fairly good results.

A Correlative Method of Machine Condition Monitoring Based on the Choi-Williams Distribution

2005 ◽  
Vol 293-294 ◽  
pp. 777-784
Author(s):  
Guoan Yang ◽  
Zhenhuan Wu ◽  
Jin Ji Gao
Keyword(s):  
Fault Diagnosis ◽  
Correlation Analysis ◽  
Condition Monitoring ◽  
New Method ◽  
Time Varying ◽  
Machine Condition ◽  
Time Frequency ◽  
Machine Condition Monitoring ◽  
Machine Fault Diagnosis ◽  
Feature Extractor

In this paper, a new method for time-varying machine condition monitoring is proposed. By Choi-Williams distribution, the interference terms produced by the bilinear time-frequency transform are reduced and the fault signal is processed by the correlation analysis of the Choi-Williams distribution. For machine fault diagnosis, both the feature extractor and classifier are combined to make a decision. It is particularly suited to those who are not experts in the field. Satisfactory results have been obtained from a real example and the effectiveness of the proposed method is demonstrated.

Enhancing off-line and on-line condition monitoring and fault diagnosis

1995 ◽  
Vol 3 (11) ◽  
pp. 1515-1528 ◽  
Author(s):  
R.A. Vingerhoeds ◽  
P. Janssens ◽  
B.D. Netten ◽  
M. Aznar Fernández-Montesinos
Keyword(s):  
Fault Diagnosis ◽  
Condition Monitoring ◽  
On Line ◽  
Line Condition

Fault Knowledge Acquisition of Electronic Equipment

2013 ◽  
Vol 397-400 ◽  
pp. 1145-1147
Author(s):  
Feng Hua Zou ◽  
Hong Zhang ◽  
Lu Wang ◽  
Dan Li
Keyword(s):  
Fault Diagnosis ◽  
Data Collection ◽  
Knowledge Acquisition ◽  
Fault Location ◽  
Original Data ◽  
Electronic Equipment ◽  
New Method ◽  
Difficult Situation ◽  
Diagnosis System ◽  
Intelligent Diagnosis

The difficulties of acquiring fault knowledge severely handicap the development of intelligent diagnosis system (IDS) of military electronic equipment (MEE) in our country.For MEE fault diagnosis of fault original data collection difficult situation, a new method is presented,Which auto-acquires fault knowledge by simulating all possible faults of equipment.The approach presented in this paper makes the work of KA engineer easier, and makes fast diagnosis fault location and fault reasons possible.

Research of Polymerization Reactor Fault Diagnosis Based on Acoustic Emission

2011 ◽  
Vol 221 ◽  
pp. 550-554
Author(s):  
Yi Hu Huang ◽  
Jin Li Wang ◽  
Hui Qiong Jiang ◽  
Xi Mei Jia ◽  
Hong Lei Chong ◽  
...  
Keyword(s):  
Acoustic Emission ◽  
Fault Diagnosis ◽  
Location Theory ◽  
Polymer Processing ◽  
New Method ◽  
Loading Process ◽  
Polymerization Reactor ◽  
Safety Production ◽  
On Line ◽  
Ae Signals

With the development and improvement of polymer processing technology, safety production requires higher and higher levels of reactor fault diagnosis and assessment. In this paper, a new method is put forward for the polymer reactor on-line fault diagnosis basing on acoustic emission (AE). During the loading process of the reactor, sensors detect the AE signals. According to the acoustic emission and location theory, the fault or flaws of the reactor can be found and located. Further, the assessment of the reactor can be got and it can guide the safety production of the reactor.

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