Vibration Monitoring and Fault Diagnosis System of Turbine-Generator

2007 ◽  
Author(s):  
Dongmei Du ◽  
Qing He ◽  
Hong Li
Keyword(s):  
Fault Diagnosis ◽  
Power Plants ◽  
Vibration Monitoring ◽  
Turbine Generator ◽  
Diagnosis System ◽  
Java Applet ◽  
Java Technology ◽  
Fault Diagnosis System ◽  
The Difference ◽  
Batch Data

It is very important to monitor vibration and diagnose fault for the operating safety of turbine-generator. The remote monitor and diagnosis via the cyber-based technology is a necessity. The difference between browser/server mode and client/server mode is discussed. There are many advantages of applying Java technology. Using Java, a vibration monitoring and fault diagnosis system of turbine-generator based on browser/server mode is developed. The functions as well as the structure of the whole system are analyzed. Online transmission of batch data via Internet is presented, especially for different program languages. Java Applet technology is used to develop client program. With double-buffer method, a lot of graphic interfaces of dynamic making online are presented, which are not blinking. It is proved that the system is already adopted and functions well in several power plants.

scholarly journals Fault diagnosis system for hydraulic turbine generator

2002 ◽  
Vol 122 (4) ◽  
pp. 492-497 ◽  
Author(s):  
Yukiharu Ohga ◽  
Kazuo Moriguchi ◽  
Seiji Honda ◽  
Hiroto Nakagawa
Keyword(s):  
Fault Diagnosis ◽  
Hydraulic Turbine ◽  
Turbine Generator ◽  
Diagnosis System ◽  
Fault Diagnosis System

Studies and Application of Heavy Equipment Fault Diagnosis System

2011 ◽  
Vol 225-226 ◽  
pp. 399-402
Author(s):  
Yi Gan ◽  
Sha Liu ◽  
Wen Bo Zhu
Keyword(s):  
Fault Diagnosis ◽  
Fault Location ◽  
Diagnostic System ◽  
Diagnosis System ◽  
Initial Application ◽  
Heavy Equipment ◽  
Fault Diagnosis System ◽  
The Difference ◽  
Fault Information ◽  
Information Database

Analyze the ways to get fault information for heavy equipment fault diagnosis system, which are the control system of the device, layout sensors to get the key performance parameters, and human-computer interaction. In order to improve accuracy and efficiency of the diagnostic system, the methods of fault location tree retrieval and similar case retrieval are applied respectively according to the difference of fault information content in the diagnosis information database. The diagnosis system introduced in the paper gets effective initial application in the heavy equipment fault diagnosis system.

scholarly journals Distributed Fault Diagnosis Framework for Nuclear Power Plants

2021 ◽  
Vol 9 ◽  
Author(s):  
Wu Guohua ◽  
Duan Zhiyong ◽  
Yuan Diping ◽  
Yin Jiyao ◽  
Liu Caixue ◽  
...  
Keyword(s):  
Neural Network ◽  
Fault Diagnosis ◽  
Decision Tree ◽  
Bp Neural Network ◽  
Nuclear Power ◽  
Power Plants ◽  
Nuclear Power Plants ◽  
Future Research ◽  
Diagnosis System ◽  
Fault Diagnosis System

A fault diagnosis can quickly and accurately diagnose the cause of a fault. Focusing on the characteristics of nuclear power plants (NPPs), this study proposes a distributed fault diagnosis method based on a back propagation (BP) neural network and decision tree reasoning. First, the fault diagnosis was carried out using the BP neural network and decision tree reasoning, and then a global fusion diagnosis was performed by fusing the resulting information. Second, the key technologies of the BP neural network and decision tree sample construction were studied. Finally, the simulation results show that the proposed distributed fault diagnosis system is highly reliable and has strong diagnostic ability, enabling efficient and accurate diagnoses to be realized. The distributed fault diagnosis system for NPPs provides a solid foundation for future research.

Research of Large Excavator Multidimensional Intelligent Vibration Monitoring and Fault Diagnosis System

2013 ◽  
Vol 706-708 ◽  
pp. 928-931
Author(s):  
Ying Li ◽  
Zheng Hua Ru ◽  
Yi Ru
Keyword(s):  
Fault Diagnosis ◽  
Online Monitoring ◽  
Vibration Monitoring ◽  
Life Safety ◽  
Remote Consultation ◽  
Security Risks ◽  
Diagnosis System ◽  
Vibration Detection ◽  
Fault Diagnosis System

Excavator vibration speed not only directly affects the life length of excavator, but also contains security risks which even relate to the life safety. This article focuses on the Large Excavator Multidimensional Intelligent Vibration Monitoring and Fault Diagnosis System, which allows the excavator to perform vibration detection and warning of the key components under normal using state, and realizes online monitoring as well as remote consultation.

scholarly journals Remote Vibration Monitoring and Fault Diagnosis System of Synchronous Motor Based on Internet of Things Technology

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Xinghua Yuan ◽  
Yuling He ◽  
Shuting Wan ◽  
Minghao Qiu ◽  
Hongchun Jiang
Keyword(s):  
Fault Diagnosis ◽  
Internet Of Things ◽  
High Efficiency ◽  
Vibration Monitoring ◽  
Signal Acquisition ◽  
Rotating Machines ◽  
Diagnosis System ◽  
Synchronous Motors ◽  
Fault Diagnosis System ◽  
Internet Of Things Technology

With the rapid growth of the country’s economy and the rapid expansion of the industrial scale, the engine is developing towards high speed, high efficiency, and high power density. Synchronous motors are an important part of the power provided by large-scale chemical enterprises. The protection and control of synchronous motors are related to the long-term and safe operation of enterprise electrical equipment. The purpose of this paper is to realize the remote vibration monitoring and fault diagnosis of multiple rotating machines and real-time online monitoring and data storage function of the vibration state of the monitored equipment. The operation is simple and stable, and therefore, the problem of the equipment can be found at the first time, which provides forward operation of the equipment for a long time. In this paper, vibration caused by unbalanced mechanical equipment is not normally monitored remotely. Taking rigid rotor rotating machine as the research object, we adopt “Web server-database server-client” structure, the structure is the core software and hardware system design, and the application of Internet of Things technology enables users to remotely monitor and analyze the vibration state of multiple rotating mechanical devices at the same time. Hardware design mainly includes processor, function chip, sensor selection, filter circuit, adaptive sampling frequency signal acquisition circuit, and temperature measurement circuit design. Software design mainly includes main program design, signal acquisition subroutine, calibration subroutine, unbalanced calculation subroutine, and GPRS network communication subroutine. Finally, the function and stability of the whole system are verified through multiple experimental analyses. The objective has finally been achieved. The remote vibration monitoring and fault diagnosis system of the rotating machines designed on this paper is of low cost and high efficiency, simple operation, and high stability, and it is essential to identify and eliminate equipment errors in time.

Real-time fault diagnostic system for a steam turbine generator set by using a fuzzy cerebellar model articulation controller

2009 ◽  
Vol 223 (5) ◽  
pp. 1253-1262 ◽  
Author(s):  
C Yan ◽  
H Zhang ◽  
D Peng ◽  
H Li ◽  
L Yang
Keyword(s):  
Fault Diagnosis ◽  
Steam Turbine ◽  
Real Time ◽  
Diagnostic System ◽  
Cerebellar Model Articulation Controller ◽  
Turbine Generator ◽  
Diagnosis System ◽  
The Real ◽  
Fuzzy Cmac ◽  
Fault Diagnosis System

Because a serious fault would result in a reduced amount of electricity supply in a power plant, the real-time fault diagnosis system is extremely important for a steam turbine generator set. A novel real-time intelligent fault diagnosis system is proposed by using a fuzzy cerebellar model articulation controller (CMAC) neural network to detect and identify the faults and failures of critical components. A framework of the fault diagnosis system is described. The model of a novel fault diagnosis system by using a fuzzy CMAC is built and analysed in detail step by step. A case of the diagnosis including three faults is simulated with a fuzzy CMAC. The results show that the real-time fault diagnostic system is of high accuracy, quick convergence, and high noise rejection. Moreover, the model is verified by two examples. It is found that this model is feasible. Finally, the effects of the generalization parameter and address number in fault diagnosis are discussed.

scholarly journals Application of Computer Algorithm in Fault Diagnosis System of RM Equipment

2021 ◽  
Vol 2143 (1) ◽  
pp. 012033
Author(s):  
Xinfeng Zhang ◽  
Guanglu Yang ◽  
Yan Cui ◽  
Xinfeng Wei ◽  
Wensheng Qiao
Keyword(s):  
Fault Diagnosis ◽  
Large Scale ◽  
Automatic Monitoring ◽  
Mechanical Equipment ◽  
Computer Algorithms ◽  
Body Segment ◽  
Turbine Generator ◽  
Diagnosis System ◽  
Core Components ◽  
Fault Diagnosis System

Abstract At present, modern mechanical equipment is gradually developing towards large-scale and intelligent, which leads to more and more complex equipment structure. Therefore, people have higher and higher requirements for intelligent fault diagnosis of mechanical equipment, which leads to the application of various algorithms to mechanical equipment. Among them, rotating machinery (hereinafter referred to as RM) mainly relies on rotating action to complete specific functions, such as gearbox, gas turbine, generator and engine, which are often the core components of mechanical equipment. Therefore, the FSGS (hereinafter referred to as FSGS) of RM equipment has become a very key link in system design and maintenance, which requires designers to constantly overcome the original intelligent diagnosis system. Through a variety of deep learning algorithms, we can improve the diagnosis efficiency of automatic monitoring and diagnosis equipment, which can also reduce the loss caused by untimely diagnosis. Firstly, this paper analyzes the types of application of computer algorithms in the fault body segment system of RM equipment. Then, this paper analyzes an algorithm, which can better improve the diagnosis efficiency of the equipment.

Sign in / Sign up

Export Citation Format

Share Document