Research on Fault Diagnosis Method of Heat Pipe Network

2012 ◽  
Vol 550-553 ◽  
pp. 3155-3159
Author(s):  
Yu Kun Lv ◽  
Hai Feng Liu ◽  
Bao Jun Song ◽  
Kai Zhao
Keyword(s):  
Fault Diagnosis ◽  
Heat Pipe ◽  
Pipe Network ◽  
Before And After ◽  
Positioning Method ◽  
Diagnosis Method ◽  
Urban Heat ◽  
Flow Conservation ◽  
Network Fault ◽  
Size Relation

The urban heat pipe network fault diagnosis was studied in this paper. According to differential equations and boundary conditions, the author deduces the function relations between pressure and flow in unsteady flow. On the base of above investigations, a heat pipe network leak pipeline diagnosis method and a leak positioning method are proposed here, the pipeline alarm valve ε0 and the leak alarm valve εF are designed. We can judge whether heat pipe network leaks or not through the law of flow conservation, and search out the leak pipeline by judging the size relation of pressure drop, ε1 and ε0, before and after pipeline leaks. It then locates the leak point by judging the size relation of ε2 and εF before and after the pipeline leaks. Moreover, the location accuracy is 5%.

Research on Fault Diagnosis System of Heat Pipe Network

2012 ◽  
Vol 193-194 ◽  
pp. 619-623
Author(s):  
Yu Kun Lv ◽  
Hai Feng Liu ◽  
Shuai Chang ◽  
Bao Jun Song ◽  
Kai Zhao
Keyword(s):  
Fault Diagnosis ◽  
Heat Pipe ◽  
Calculation Method ◽  
Pipe Network ◽  
Positioning Accuracy ◽  
Diagnosis System ◽  
Simulation Calculation ◽  
Urban Heat ◽  
Fault Diagnosis System ◽  
Network Fault

The urban heat pipe network fault diagnosis system was designed in this paper so as to realize the automation diagnosis. The paper uses the simulation calculation method and the heat pipe network fault diagnosis system to analyze and study an urban heat pipe network leak fault. The diagnosis results of the heat pipe network fault diagnosis system are almost the same to that of the simulation calculation method. Moreover, the system can accurately locate the leak point and the positioning accuracy is 5%. Thus the heat pipe network fault diagnosis system which is designed has a certain practical value.

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.

Wireless Sensor Network Fault Diagnosis Method of Optimization Research and Simulation

2013 ◽  
Vol 347-350 ◽  
pp. 955-959
Author(s):  
Qiang Li
Keyword(s):  
Wireless Sensor Network ◽  
Fault Diagnosis ◽  
Sensor Network ◽  
False Positive Rate ◽  
False Negative ◽  
False Negative Rate ◽  
Wireless Sensor ◽  
Sensor Fault ◽  
Diagnosis Method ◽  
Network Fault

The traditional method of wireless sensor network fault diagnosis based on linear modeling rather than actually complicated and nod-linear relationship results in error data and leads to wrong decisions, therefore, this paper presents a sensor fault diagnosis method based on ARIMA and LSSVM integration control system which used to diagnosis sensor fault whose results are input LSSVM to fusion and get the final results of fault diagnosis. The simulation test results show that the proposed method improves the sensor node fault diagnosis accuracy, reduce the false negative rate and false positive rate.

scholarly journals An open-circuit fault-diagnosis method for inverters based on phase current

2020 ◽  
Vol 2 (2) ◽  
pp. 148-160 ◽  
Author(s):  
Shu Cheng ◽  
Jundong Zhao ◽  
Chunyang Chen ◽  
Kaidi Li ◽  
Xun Wu ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Open Circuit ◽  
Integration Algorithm ◽  
Phase Current ◽  
Fault Features ◽  
Before And After ◽  
Power Switches ◽  
Diagnosis Method ◽  
Circuit Fault Diagnosis ◽  
The Mathematical Model

Abstract The inverter is an indispensable part of a power electronics system. Its safety and stability are important indicators for evaluating the reliability of the system. Inverter faults are usually caused by operating faults in the switch elements. This paper therefore proposes a non-intrusive fault-diagnosis method for open-circuit faults in inverter semiconductor power switches. This method requires only a current signal. It is simple and economical. Faults can be diagnosed quickly using the proposed algorithm. First, the phase current waveforms before and after the open-circuit fault are analysed based on the mathematical model. Then, based on the analysis of the phase currents, the fault features are extracted and the fault is located using the proposed integration algorithm. Finally, the effectiveness and reliability of the proposed fault-diagnosis method are verified using a hardware-in-the-loop experiment.

Study of the Fault Diagnosis Method Based on Wavelet Time and Frequency Analysis

2012 ◽  
Vol 472-475 ◽  
pp. 2166-2170
Author(s):  
Qun Qi ◽  
Xue Zhang Zhao
Keyword(s):  
Neural Network ◽  
Wavelet Transform ◽  
Fault Diagnosis ◽  
Asynchronous Motor ◽  
Wavelet Neural Network ◽  
Experiment Data ◽  
Complex Fault ◽  
Diagnosis Method ◽  
Neural Network Algorithm ◽  
Network Fault

In order to better solve asynchronous motor complex fault characteristics, improve the reliability of the diagnosis and accuracy, combined with wavelet transform technique, construct a wavelet neural network, wavelet transform technology feature extraction asynchronous motor as a signal wavelet neural network's input vector, and the wavelet neural network algorithm was used to optimize, realize the motor identify types of fault, through the simulation experiment data diagnosis results show that this method is effective and feasible. Based on the wavelet analysis and neural network fault diagnosis method of research.

Power System Fault Diagnosis Method Summary

2014 ◽  
Vol 670-671 ◽  
pp. 1179-1183
Author(s):  
Yu Zhao ◽  
Wei Xiong ◽  
Huang Qiang Li ◽  
Shi Yong Yang
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Fault Diagnosis ◽  
Expert System ◽  
Power System ◽  
Bayesian Network ◽  
Current Situation ◽  
Advantages And Disadvantages ◽  
Diagnosis Method ◽  
Network Fault

Combined with the power system fault diagnosis current situation, fault diagnosis methods are important to shorten fault outage time, prevent accident expanding and restore power quickly. We summed up expert system, artificial neural network, Petri network and Bayesian network fault diagnosis methods. The diagnosis principle, advantages and disadvantages of different methods were discussed.

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