scholarly journals Gas path fault diagnosis system of aero-engine based on Grey Relationship Degree

2011 ◽  
Vol 15 ◽  
pp. 4774-4779 ◽  
Author(s):  
Lingping Jiang
Keyword(s):  
Fault Diagnosis ◽  
Diagnosis System ◽  
Aero Engine ◽  
Fault Diagnosis System ◽  
Gas Path Fault

A Monitoring and Fault Diagnosis System for Aero-Engine Pipeline Based on Distributed Fiber Bragg Grating Sensor

2014 ◽  
Vol 556-562 ◽  
pp. 3112-3116
Author(s):  
Dong Liu ◽  
Quan Liu ◽  
Fen Chen ◽  
Qin Wei ◽  
Qing Song Ai
Keyword(s):  
Fault Diagnosis ◽  
Fiber Bragg Grating ◽  
Condition Monitoring ◽  
Online Monitoring ◽  
Fiber Bragg Grating Sensor ◽  
Bragg Grating ◽  
Diagnosis System ◽  
Aero Engine ◽  
Fault Diagnosis System ◽  
Bragg Grating Sensor

Aero-engine pipeline is the cardiovascular of aero-engine, which directly affects the safety and reliability of planes. However, the pipeline has complex structure and is easily broken by the harsh operation environment. Therefore, the condition monitoring and fault diagnosis of aero-engine pipeline play one of the most important role to ensure the aero-engine safe and reliable. Fiber Bragg Grating Sensor (FBGS) owns several characteristics, such as anti-electromagnetic interference, corrosion resistance, small size, performance stability, long lifecycle, as well as easy to constitute distributed multi-point system. In this paper, a condition monitoring and fault diagnosis system for aero-engine pipeline, including online monitoring and offline diagnosis, is proposed. Moreover, online monitoring based on temperature and strain signals and offline fault diagnosis based on simulated vibration signals of aero-engine pipeline are explained in details. According to the experimental results, the proposed system is useful and effective.

Study on Remote Control and Fault Diagnosis for Ultrahigh Speed Grinding

2007 ◽  
Vol 359-360 ◽  
pp. 518-522
Author(s):  
Wan Shan Wang ◽  
Tian Biao Yu ◽  
Xing Yu Jiang ◽  
Jian Yu Yang
Keyword(s):  
Remote Control ◽  
Fault Diagnosis ◽  
Knowledge Acquisition ◽  
Rough Set ◽  
Theoretical Research ◽  
Reduction Rule ◽  
Diagnosis System ◽  
Linear Speed ◽  
Fault Diagnosis System ◽  
Diagnosis Model

Remote control and fault diagnosis of ultrahigh speeding grinding is studied, which is based on the theory of rough set. Knowledge acquisition and reduction rule of fault diagnosis, realization method of remote control for ultrahigh speed grinding are studied, diagnosis model is established. Based on the theoretical research and ultrahigh speed grinder with a linear speed of 250 m/s, the remote control and fault diagnosis system of ultrahigh speed grinding is developed. Results of the system running show that the environment is improved, the mental pressure of workers is relieved and the efficiency is improved. At the same time, it proves that the ability to diagnosis and the accuracy of diagnosis for the ultrahigh speed grinding are improved and the time for diagnosis is shortened by applying rough set.

scholarly journals Power transformer fault diagnosis system based on Internet of Things

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Guoshi Wang ◽  
Ying Liu ◽  
Xiaowen Chen ◽  
Qing Yan ◽  
Haibin Sui ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Internet Of Things ◽  
Power Transformer ◽  
Fault System ◽  
Ratio Method ◽  
Diagnosis System ◽  
Network Training ◽  
Fault Diagnosis System ◽  
Training Error ◽  
Transformer Fault

Abstract Transformer is the most important equipment in the power system. The research and development of fault diagnosis technology for Internet of Things equipment can effectively detect the operation status of equipment and eliminate hidden faults in time, which is conducive to reducing the incidence of accidents and improving people's life safety index. Objective To explore the utility of Internet of Things in power transformer fault diagnosis system. Methods A total of 30 groups of transformer fault samples were selected, and 10 groups were randomly selected for network training, and the rest samples were used for testing. The matter-element extension mathematical model of power transformer fault diagnosis was established, and the correlation function was improved according to the characteristics of three ratio method. Each group of power transformer was diagnosed for four months continuously, and the monitoring data and diagnosis were recorded and analyzed result. GPRS communication network is used to complete the communication between data acquisition terminal and monitoring terminal. According to the parameters of the database, the working state of the equipment is set, and various sensors are controlled by the instrument driver module to complete the diagnosis of transformer fault system. Results The detection success rate of the power transformer fault diagnosis system model established in this paper is as high as 95.6%, the training error is less than 0.0001, and it can correctly identify the fault types of the non training samples. It can be seen that the technical support of the Internet of Things is helpful to the upgrading and maintenance of the power transformer fault diagnosis system.

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