Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Steam Turbine Fault Diagnosis Method Based on Feature Selection of Stationary and Nonstationary Vibration Signals

A technology of non-stationary signals and vibration signals, which is applied in pattern recognition in signals, engine testing, computer components, etc., can solve problems that have not yet been reported in research, to avoid interference, accurately locate and repair faults, and ensure The effect of safe and reliable operation

Active Publication Date: 2019-12-31
ZHEJIANG UNIV
View PDF2 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Have not yet seen the research reports relevant to the present invention

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Steam Turbine Fault Diagnosis Method Based on Feature Selection of Stationary and Nonstationary Vibration Signals
  • Steam Turbine Fault Diagnosis Method Based on Feature Selection of Stationary and Nonstationary Vibration Signals
  • Steam Turbine Fault Diagnosis Method Based on Feature Selection of Stationary and Nonstationary Vibration Signals

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0040] The present invention will be described in further detail below in conjunction with the accompanying drawings and specific examples.

[0041] The vibration signal of the main engine of the steam turbine unit in thermal power generation is nonlinear and non-stationary. The original signal contains a lot of noise. It is difficult to directly extract information from the original signal. The present invention takes the two typical faults of the airflow excitation fault and the dynamic and static friction fault that occur in the main engine of a steam turbine unit in a thermal power plant as examples, as shown in figure 1 As shown, the method of the present invention is described in detail. Such as figure 2 As shown, the airflow excitation fault is specifically manifested as the vibration of the shaft system increases, and the low-frequency component of the signal increases; the dynamic and static friction friction fault specifically manifests as the "peak" of the vibrati...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a method for fault diagnosis of a steam turbine main engine based on feature selection of stationary and non-stationary vibration signals. The present invention is aimed at the steam turbine in the steam turbine unit of thermal power generation, combined with the integrated empirical mode decomposition (EEMD) and the recursive feature elimination method, decomposes and extracts the key features of the stable and non-stationary signals in detail, and is used for the fault diagnosis of the vibration signal of the steam turbine . The invention fully considers the non-stationary and mixed with a large amount of noise characteristics of the vibration signal of the steam turbine, fully excavates the potential information contained in the fault data, extracts features for the stable and non-stationary data, and overcomes the problem that the characteristics of the non-stationary data are easy to be covered question. At the same time, key features are extracted, which reduces the dimensionality of feature vectors, reduces data redundancy, improves the accuracy of steam turbine vibration signal fault diagnosis, and helps field engineers to accurately repair faults, thereby ensuring that the generator and steam turbine The safe and reliable operation of the equipment improves the production efficiency.

Description

technical field [0001] The invention belongs to the technical field of fault diagnosis of vibration signals, in particular to a fault diagnosis method based on feature selection of stable and non-stationary vibration signals for a steam turbine main engine of a thermal power generating set. Background technique [0002] With the progress of society and the development of science and technology, people's demand for electricity is also increasing. Among them, coal-fired power generation is one of the main power generation methods in my country. In recent years, with the adjustment of the structure of the power generation industry, large-scale units with large capacity, high parameters, and low energy consumption have gradually replaced small units with high energy consumption, and the industrial process has become more and more complicated. As the main equipment for coal-fired power generation, the safe operation of the main engine of the steam turbine affects the operation s...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Patents(China)
IPC IPC(8): G01M15/00G06K9/00
CPCG01M15/00G06F2218/02G06F2218/08G06F2218/12
Inventor 赵春晖田峰
Owner ZHEJIANG UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products