Industrial process nonlinear fault diagnosis system and method based on fisher

A fault diagnosis system and industrial process technology, applied in the direction of comprehensive factory control, comprehensive factory control, electrical program control, etc., can solve problems such as poor diagnostic effect and poor applicability

Inactive Publication Date: 2008-12-03
ZHEJIANG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In order to overcome the disadvantages of poor applicability and poor diagnostic effect of the existing fault diagnosis system, the present invention provides a non-linear fault diagnosis system and method based on fisher for industrial process with wide application range and good fault diagnosis effect

Method used

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  • Industrial process nonlinear fault diagnosis system and method based on fisher
  • Industrial process nonlinear fault diagnosis system and method based on fisher
  • Industrial process nonlinear fault diagnosis system and method based on fisher

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Experimental program
Comparison scheme
Effect test

Embodiment 1

[0051] Refer to figure 1 , figure 2 , image 3 , A fisher-based industrial process non-linear fault diagnosis system, including field intelligent instrument 2, DCS system and upper computer 6 connected with industrial process object 1. Said DCS system consists of data interface 3, control station 4, and database 5. Composition; the intelligent instrument 2, the DCS system, and the upper computer 6 are connected in sequence via a field bus, and the upper computer 6 includes:

[0052] The standardization processing module 7 is used to standardize the data so that the mean value of each variable is 0, the variance is 1, and the input matrix X is obtained, which is completed by the following process:

[0053] 1) Calculate the mean value: TX ‾ = 1 N Σ i = 1 N TX i , ...

Embodiment 2

[0098] Reference figure 1 , figure 2 , image 3 , A fisher-based industrial process nonlinear fault diagnosis system method. The fault diagnosis method includes the following steps:

[0099] (1) Determine the key variables used for fault diagnosis, and collect the data of the variables when the system is normal and when the system fails from the historical database of the DCS database 5 as the training sample TX;

[0100] (2) In the fisher discriminant analysis module 8 of the host computer 6, set the number of discriminant functions N and other parameters, and set the sampling period in the DCS;

[0101] (3) The training sample TX is in the host computer, and the data is standardized in the standardization module 7, so that the mean value of each variable is 0, the variance is 1, and the input matrix X is obtained, which is completed by the following process:

[0102] 3.1) Calculate the mean value: TX ‾ = 1 ...

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Abstract

A nonlinear failure diagnostic system based fisher industrial process comprises industrial process object connected on site intelligent meter, DCS system, upper position machine, with the said DCS system made of data interface, control station, data base, the intelligent meter DCS system and the upper position machine connected sequentially, with the upper position machine composed of standardized handling module, fisher judging analysis module and diagnostic module. It also puts forward a failure diagnostic method. It provides a good failure diagnostic effect with extensive application based on fisher industrial process nonlinear failure diagnostic system and method.

Description

(1) Technical field [0001] The present invention relates to the field of industrial process fault diagnosis, in particular, to a fisher-based industrial process nonlinear fault diagnosis system and method. (2) Background technology [0002] Due to the requirements of product quality, economic efficiency, safety and environmental protection, industrial processes and related control systems have become very complex. In order to ensure the normal operation of industrial systems, fault diagnosis and detection play a very important role in industrial processes. In recent years, the application of statistical analysis to process monitoring and fault diagnosis has been extensively studied. [0003] Using industrial measured data and using statistical methods for fault diagnosis, complicated mechanism analysis is avoided, and the solution is relatively convenient. However, most of the current fault diagnosis methods have certain requirements on the distribution or covariance distribution...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G05B19/418
CPCY02P90/02
Inventor 刘兴高阎正兵
Owner ZHEJIANG UNIV
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