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

Fault detection method and device for principal component correlation degree sensor based on density clustering

A technology of sensor failure and density clustering, which is applied in the direction of instrumentation, computing, character and pattern recognition, etc., can solve problems such as difficulty in detecting sensor failure, economic loss, and performance degradation of the control system, and achieve the effect of fast and accurate fault diagnosis

Active Publication Date: 2019-06-14
NORTH CHINA ELECTRICAL POWER RES INST +3
View PDF8 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Once the sensor fails, the performance of the control system will decline, and it may lead to serious accidents and major economic losses.
There are many sensors in the thermal process of thermal power plants, which are distributed in multiple parts of various equipment. It is very difficult to detect sensor failures by manpower

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
  • Fault detection method and device for principal component correlation degree sensor based on density clustering
  • Fault detection method and device for principal component correlation degree sensor based on density clustering
  • Fault detection method and device for principal component correlation degree sensor based on density clustering

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0095] Randomly select all measuring points within a certain period of time for clustering, and divide them into several typical working condition clusters. 500 sets of data are used as the fixed time window length, and the last 500 sets of data are used as test data. In this case, the test data is superimposed with 5% deviation fault data, and the average length of the sliding window is selected as 5. After combining the fixed window and the sliding window, real-time Computes the correlation between the measured points within the window.

[0096] exist Figure 7 ~ Figure 11 In , the meaning expressed by the axis of ordinate is: the correlation degree between measuring points, and the meaning expressed by the axis of abscissa is; time series. For example: 1 represents time 1, 2 represents time 2, and so on.

[0097] Figure 7 It is the change curve of the correlation between measuring point 1 and measuring point 2. It can be seen that the correlation between measuring point...

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 present invention relates to a method and device for detecting faults of principal component correlation degree sensors based on density clustering, wherein the method includes: judging the working condition data of the monitoring sensors by using the multi-working condition model of the unit, classifying the monitoring sensors, and obtaining the working conditions Condition cluster; Wherein, the working condition information of all monitoring sensors in the described working condition cluster constitutes matrix X; Utilize the working condition information of any two monitoring sensors in the described working condition cluster to form matrix K; Carry out principal component analysis to matrix K, obtain The main characteristic T of matrix K; Utilize the matrix X and main characteristic T after the normalization process to determine the degree of correlation of any two monitoring sensors; The degree of correlation is compared with a threshold, and the monitoring corresponding to the degree of correlation greater than the threshold The sensor performs fault detection.

Description

technical field [0001] The invention relates to the technical field of fault detection, in particular to a method and device for fault detection of a principal component correlation sensor based on density clustering. Background technique [0002] As an essential underlying component in thermal power plants, sensors play an important role in the safe and stable operation of the unit. During the normal operation of thermal power units, a large number of various types of sensors are used to measure important thermal process parameters, such as main steam temperature, main steam pressure, steam turbine speed, and drum water level. Once the sensor breaks down, the performance of the control system will be degraded, or it may cause serious accidents and cause major economic losses. There are many sensors in the thermal process of thermal power plants, which are distributed in multiple parts of various equipment. It is very difficult to detect sensor failures by manpower. Theref...

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): G06K9/62
CPCG06F18/2321
Inventor 黄葆华仇晓智周卫庆王超司派友
Owner NORTH CHINA ELECTRICAL POWER RES INST
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

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com