The Fault Diagnosis for the Unplanned Downtime of the Roller Disassembly Machine

2012 ◽  
Vol 201-202 ◽  
pp. 469-472
Author(s):  
Yu Jing Jia ◽  
Guang Zhen Cheng ◽  
Ying Jun Dai
Keyword(s):  
Fault Diagnosis ◽  
Maximum Load ◽  
Control Circuit ◽  
Electrical Control ◽  
Power Failure ◽  
Diagnosis Method ◽  
Failure Point

This paper provides a kind of fault diagnosis method. It introduces the principles of the electrical control of roller Disassembly machine and the phenomenon of sudden power failure in the work. By analyzing a variety of factors that may lead to fault, and taking some appropriate solution, According to calculations, replaced the control transformer as the BK-300 that keep the roller disassembly machine safe and reliable, and avoid the phenomenon of power failure. Point out That the control transformer capacity should meet the required transformer capacity of the control circuit when it has the maximum load; Some control components have been working, when other control components is started, it still remains active.

Analysis of the Fault Diagnosis Method to Coal Mine Electrical Control Circuit

2013 ◽  
Vol 329 ◽  
pp. 334-337
Author(s):  
Ming Li
Keyword(s):  
Fault Diagnosis ◽  
Coal Mine ◽  
Work Experience ◽  
Rapid Development ◽  
Repair Process ◽  
Coal Industry ◽  
Control Circuit ◽  
Electrical Control ◽  
Maintenance Work ◽  
Circuit Fault Diagnosis

At this stage it is electrical automation of coal industry with a rapid development period, the degree of automation is also more and more high, therefore, the electric control circuit requirements will be getting higher and higher, in such circumstances to improve coal mine electrical control circuit fault diagnosis and maintenance is very important. Based on the above factors, this article on the electrical control circuit repair process as the research object, how to carry on fault diagnosis are analyzed, in combination with the associated data and real work experience, put forward to some suitable methods of diagnosis, and these methods have a careful introduction, hope that through this article related to this, future electrical maintenance work to provide some help.

Fault Diagnosis for Electrical Control System of Automobile Based on Support Vector Machine

2014 ◽  
Vol 666 ◽  
pp. 203-207
Author(s):  
Jian Hua Cao
Keyword(s):  
Neural Network ◽  
Support Vector Machine ◽  
Control System ◽  
Fault Diagnosis ◽  
Bp Neural Network ◽  
Experimental Results ◽  
Support Vector ◽  
Electrical Control ◽  
Diagnosis Method ◽  
The Common

This paper is to present a fault diagnosis method for electrical control system of automobile based on support vector machine. We collect the common fault states of electrical control system of automobile to analyze the fault diagnosis ability of electrical control system of automobile based on support vector machine. It can be seen that the accuracy of fault diagnosis for electrical control system of automobile by support vector machine is 92.31%; and the accuracy of fault diagnosis for electrical control system of automobile by BP neural network is 80.77%. The experimental results show that the accuracy of fault diagnosis for electrical control system of automobile of support vector machine is higher than that of BP neural network.

Application on State Evaluation of the Grounding Conductor Based on Fault Diagnosis Method

2014 ◽  
Vol 635-637 ◽  
pp. 815-818
Author(s):  
Da Xing Wang ◽  
Shou Bao Liu ◽  
De Gang Gan ◽  
Bin He
Keyword(s):  
Sensitivity Analysis ◽  
Fault Diagnosis ◽  
Network Theory ◽  
Electrical Network ◽  
Large Area ◽  
Power Failure ◽  
Grounding Grid ◽  
State Evaluation ◽  
Diagnosis Method ◽  
Diagnosis Model

In this paper, fault diagnosis model of grounding grid is established combining electrical network theory with sensitivity analysis. A new method which is used to select the node pairs to calculate the corrosion situation of grounding grid is presented. Based on this method, the fault branch of grounding grid can be efficiently judged through topology diagram and port resistance without power failure and the excavation of large area. Field test was carried out at 220 kV electrical substations using the diagnosis method. The conductors diagnosed as severely corroded was excavated. The result was identical to the diagnosis results, indicating that this diagnosis method has engineering practicality.

Helicopter main reduction planetary gear fault diagnosis method based on SVDD

2020 ◽  
Vol 64 (1-4) ◽  
pp. 137-145
Author(s):  
Yubin Xia ◽  
Dakai Liang ◽  
Guo Zheng ◽  
Jingling Wang ◽  
Jie Zeng
Keyword(s):  
Fault Diagnosis ◽  
Planetary Gear ◽  
Gaussian Kernel ◽  
Support Vector ◽  
Support Vector Data Description ◽  
Vector Data ◽  
Energy Characteristics ◽  
Gear Fault ◽  
Channel Information ◽  
Diagnosis Method

Aiming at the irregularity of the fault characteristics of the helicopter main reducer planetary gear, a fault diagnosis method based on support vector data description (SVDD) is proposed. The working condition of the helicopter is complex and changeable, and the fault characteristics of the planetary gear also show irregularity with the change of working conditions. It is impossible to diagnose the fault by the regularity of a single fault feature; so a method of SVDD based on Gaussian kernel function is used. By connecting the energy characteristics and fault characteristics of the helicopter main reducer running state signal and performing vector quantization, the planetary gear of the helicopter main reducer is characterized, and simultaneously couple the multi-channel information, which can accurately characterize the operational state of the planetary gear’s state.

Towards High Accuracy Fault Diagnosis of Digital Circuits

2004 ◽  
Author(s):  
Camelia Hora ◽  
Stefan Eichenberger
Keyword(s):  
Fault Diagnosis ◽  
Fault Location ◽  
Digital Circuits ◽  
High Accuracy ◽  
Manufacturing Processes ◽  
Diagnosis Method ◽  
Technology Trend

Abstract Due to the development of smaller and denser manufacturing processes most of the hardware localization techniques cannot keep up satisfactorily with the technology trend. There is an increased need in precise and accurate software based diagnosis tools to help identify the fault location. This paper describes the software based fault diagnosis method used within Philips, focusing on the features developed to increase its accuracy.

Fault Diagnosis Method of Mine Motor Based on Support Vector Machine

2019 ◽  
Vol 13 ◽  
Author(s):  
Yan Zhang ◽  
Ren Sheng
Keyword(s):  
Support Vector Machine ◽  
Fault Diagnosis ◽  
Optimization Method ◽  
Support Vector ◽  
Optimal Parameters ◽  
Instantaneous Power ◽  
Practical Usefulness ◽  
Sample Data ◽  
Diagnosis Method ◽  
Fault Characteristic

Background: In order to improve the efficiency of fault treatment of mining motor, the method of model construction is used to construct the type of kernel function based on the principle of vector machine classification and the optimization method of parameters. Methodology: One-to-many algorithm is used to establish two kinds of support vector machine models for fault diagnosis of motor rotor of crusher. One of them is to obtain the optimal parameters C and g based on the input samples of the instantaneous power fault characteristic data of some motor rotors which have not been processed by rough sets. Patents on machine learning have also shows their practical usefulness in the selction of the feature for fault detection. Results: The results show that the instantaneous power fault feature extracted from the rotor of the crusher motor is obtained by the cross validation method of grid search k-weights (where k is 3) and the final data of the applied Gauss radial basis penalty parameter C and the nuclear parameter g are obtained. Conclusion: The model established by the optimal parameters is used to classify and diagnose the sample of instantaneous power fault characteristic measurement of motor rotor. Therefore, the classification accuracy of the sample data processed by rough set is higher.

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