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 Research of Avionics Systems Based on Testing

2014 ◽  
Vol 519-520 ◽  
pp. 1149-1154
Author(s):  
Wen Jun Zhao
Keyword(s):  
Fault Diagnosis ◽  
Fault Location ◽  
Diagnostic Testing ◽  
Automatic Test Equipment ◽  
Testing Strategy ◽  
Automatic Test ◽  
Location Accuracy ◽  
Diagnosis Method ◽  
Diagnosis Model ◽  
The Relationship

As for this problem that the equipment/devices maintenance and troubleshooting of new avionics systems is very difficult, the fault Diagnosis Method based on testing is proposed. This method is used to build fault diagnosis model and generate diagnostic testing strategy by establishing the relationship between the fault and test, and then the automatic test equipment is used to test for fault under the reasoning of the diagnosis inference, finally, fault conclusions are drawn. Application shows that this method is feasible, fault location accuracy is high and application prospect is broad.

Method on the Fault Detection and Diagnosis for the Railway Turnout Based on the Current Curve of Switch Machine

2013 ◽  
Vol 427-429 ◽  
pp. 1022-1027 ◽  
Author(s):  
Xue Mei Mo ◽  
Yu Fang ◽  
Yun Guo Yang
Keyword(s):  
Fault Diagnosis ◽  
Fault Detection ◽  
Fault Location ◽  
Fault Detection And Diagnosis ◽  
Curve Matching ◽  
Reference Curve ◽  
Current Curve ◽  
Diagnosis Method ◽  
Detection And Diagnosis ◽  
Railway Turnout

This paper proposes a method of the fault detection and diagnosis for the railway turnout based on the current curve of switch machine. Exact curve matching fault detection method and SVM-based fault diagnosis method are adopted in the paper. Based on envelope and morpheme match algorithm, exact curve matching method is used to match the detected current curve with the reference curve so as to predict whether the curve would have fault or not. Moreover, the SVM-based fault diagnosis method is used to make sure that the fault conditions could be diagnosed intelligently. Finally, the experimental results show that the proposed method can accurately identify the turnout fault status in the conversion process, and the accuracy rate in the diagnosis of the fault location is above 98%, which verify the effectiveness of the method in the fault detection and diagnosis.

Hierarchical Information Fault Diagnosis Method for Power System Based on Fireworks Algorithm

2021 ◽  
Author(s):  
Feng Haixun ◽  
Yi Kenan ◽  
Jia Zihang ◽  
Bi Huijing
Keyword(s):  
Fault Diagnosis ◽  
Power System ◽  
Fault Location ◽  
Stable Operation ◽  
Specific Situation ◽  
Fireworks Algorithm ◽  
Protection Information ◽  
Diagnosis Method ◽  
Important Means ◽  
Fault Recording

Power system fault diagnosis is an important means to ensure the safe and stable operation of power system. According to the specific situation of China’s current power grid automation level, a hierarchical fault diagnosis method based on switch trip signal, protection information and fault recording information is proposed. This method can not only diagnose simple fault and complex fault, but also judge fault type and phase, and complete fault location, which provides reliable guarantee for operators to quickly remove fault and resume operation. The diagnosis method based on this principle has good application effect in simulation test.

scholarly journals Research on Fault Diagnosis Method Based on Rule Base Neural Network

2017 ◽  
Vol 2017 ◽  
pp. 1-7 ◽  
Author(s):  
Zheng Ni ◽  
Zhang Lin ◽  
Wang Wenfeng ◽  
Zhang Bo ◽  
Liu Yongjin ◽  
...  
Keyword(s):  
Neural Network ◽  
Fault Diagnosis ◽  
Fault Location ◽  
Fuzzy Theory ◽  
Learning Rule ◽  
Rule Base ◽  
Fuzzy Neural ◽  
Diagnosis Method ◽  
Construction Model ◽  
Network Fault

The relationship between fault phenomenon and fault cause is always nonlinear, which influences the accuracy of fault location. And neural network is effective in dealing with nonlinear problem. In order to improve the efficiency of uncertain fault diagnosis based on neural network, a neural network fault diagnosis method based on rule base is put forward. At first, the structure of BP neural network is built and the learning rule is given. Then, the rule base is built by fuzzy theory. An improved fuzzy neural construction model is designed, in which the calculated methods of node function and membership function are also given. Simulation results confirm the effectiveness of this method.

scholarly journals Model-Based Fault Diagnosis Approach for Rotor System with Unidentified Supporting Parameters

2011 ◽  
Vol 2-3 ◽  
pp. 773-778
Author(s):  
Hong Liang Yao ◽  
Hong Bin Ma ◽  
Qing Kai Han ◽  
Bang Chun Wen
Keyword(s):  
Fault Diagnosis ◽  
Fault Location ◽  
Synthesis Method ◽  
Strong Impact ◽  
Rotor Systems ◽  
Modal Test ◽  
Model Based ◽  
Diagnosis Method ◽  
Fixed Interface ◽  
Improved Model

The model based diagnosis method can detect both the fault location and the fault extent of the rotating machinery at the same time as it can combine the dynamics and fault diagnosis method together. However, the modal test of the supporting part is necessary when using the existing model based method, and the precision of the modal test results make a strong impact on the diagnosis results. In order to improve this case, an improved model based diagnosis method is presented herein by combining the fixed-interface modal synthesis method with the traditional model based diagnosis method. The DOF of the unidentified parameter due to the supporting parts are partitioned to interface DOF, and the displacement information of the supporting parts can be measured by the mounted sensors. Therefore, the model based diagnosis method can be carried out by only using the parameters of the rotor without considering the effects from the supporting, which can greatly improve the diagnosis precision and efficiency. This method is fit for the rotor systems with unidentified supporting parameter, and the rotor systems with unknown nonlinear supporting parameter. Both the numerical simulation results and the experiment results in the example proved the efficiency of this method.

Sensor Fault Diagnosis Based on SOFM Neural Network

2014 ◽  
Vol 511-512 ◽  
pp. 193-196
Author(s):  
Shuo Ding ◽  
Xiao Heng Chang ◽  
Qing Hui Wu
Keyword(s):  
Neural Network ◽  
Fault Diagnosis ◽  
High Accuracy ◽  
Classification Methods ◽  
Statistical Classification ◽  
Sensor Fault ◽  
Discriminant Functions ◽  
Fast Speed ◽  
Diagnosis Method ◽  
Simulation Results

Traditional sensor fault diagnosis is mainly based on statistical classification methods. The discriminant functions in these methods are extremely complex, and typical samples of reference modes are not easy to get, therefore it is difficult to meet the actual requirements of a project. In view of the deficiencies of conventional sensor fault diagnosis technologies, a fault diagnosis method based on self-organizing feature map (SOFM) neural network is presented in this paper. And it is applied to the fault diagnosis of pipeline flow sensor in a dynamic system. The simulation results show that the fault diagnosis method based on SOFM neural network has a fast speed, high accuracy and strong generalization ability, which verifies the practicality and effectiveness of the proposed method.

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