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Method for detecting intermittent faults in industrial process

A technology of industrial process and detection method, applied in electrical testing/monitoring and other directions, can solve the problems of poor detection effect, high fault detection and detection rate, high fault omission rate and false alarm rate

Active Publication Date: 2019-05-10
CHINA UNIV OF PETROLEUM (EAST CHINA) +1
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The present invention aims at the problem of poor detection effect due to the high rate of false alarms and false positives when the existing fault detection method detects intermittent faults, and provides a detection method for intermittent faults in industrial processes, which has a high fault detection rate and low false alarm low rate

Method used

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  • Method for detecting intermittent faults in industrial process
  • Method for detecting intermittent faults in industrial process
  • Method for detecting intermittent faults in industrial process

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Experimental program
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Effect test

Embodiment 1

[0117] The Tennessee-Eastman (hereinafter referred to as: TE) process is an experimental platform established by Downs and Vogel of Eastman Chemical Company in the United States based on an actual chemical process. It is now widely used to verify the pros and cons of control algorithms and process monitoring methods. . The TE industrial process is mainly composed of five units, including reactor, product condenser, gas-liquid separator, cycle compressor and stripping column. The TE industrial process has a total of 53 variables, including 12 operating variables and 41 measured variables. The data set generated by this process has been widely used to evaluate the quality of process detection and fault diagnosis methods. However, the 21 faults preset in this dataset are all continuous faults, and the fault is introduced at the 161st sampling point until the end of the simulation. Therefore, in this embodiment, the failure mode is changed according to the Simulink closed-loop co...

Embodiment 2

[0160] Based on the matlab tool, numerical simulation is used to simulate intermittent faults, fully considering the characteristics of intermittent faults, that is, the amplitude and duration of intermittent faults are small in the early stage of occurrence, and the amplitude and duration of intermittent faults increase significantly as time goes by , the effect of the detection method of the present invention is illustrated in conjunction with the accompanying drawings.

[0161] In this embodiment, the detection method of the present invention includes two stages of offline modeling and online monitoring, the steps of which are the same as in Embodiment 1, and will not be repeated here. The generation of data and the introduction of intermittent failures is as follows:

[0162] Utilize equation (12) to produce N=5000 normal samples after standardization as training data, equation (12) is expressed as:

[0163] x=As+ξ (12)

[0164] In the formula, s means the mean is [0.9...

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Abstract

The invention relates to a method for detecting intermittent faults in an industrial process. The method comprises the steps of: establishing a canonical variate analysis model according to data in anormal working condition in the industrial process to obtain canonical variates and divide to form two parts consisting of a state space and a residual space, introducing a sliding time window to establish a principal component analysis model for average data matrixes of the state space and the residual space, giving a significance level, calculating the control limit of fault detection indexes, collecting real-time data of the industrial process as test data, employing the established principal component analysis model to calculate the fault detection indexes of the test data, and comparing the fault detection indexes of the test data with the control limit to determine whether faults are generated or not. Based on the traditional canonical variate analysis (CVA), the sliding time windowis introduced to provide a new fault detection index to perform averaging of the data of the state space and the residual space to make the fault detection index more sensitive for faults so as to timely and effectively achieve detection of intermittent faults, effectively improve the fault detection rate and reduce the false alarm rate.

Description

technical field [0001] The invention belongs to the technical field of industrial process monitoring and fault diagnosis, and relates to a detection method for intermittent faults in industrial processes. Background technique [0002] Modern industrial systems are characterized by large scale and complexity, and research on industrial process monitoring and fault diagnosis technology to improve the safety and reliability of industrial systems has attracted more and more attention. After decades of extensive research by researchers, fault diagnosis techniques can be roughly divided into three categories: model-based, knowledge-based and data-driven fault diagnosis methods. With the widespread use of distributed control systems, a large amount of operating data has been recorded, and data-driven fault diagnosis methods have gradually become a research hotspot. However, most of the existing model-based, knowledge-based and data-driven fault diagnosis methods are aimed at perma...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05B23/02
Inventor 盛立高晗高明周东华
Owner CHINA UNIV OF PETROLEUM (EAST CHINA)
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