Monitoring index switching based multi-operating-mode process monitoring method and system

A technology for monitoring indicators and process monitoring, applied in general control systems, control/regulation systems, instruments, etc., can solve problems such as inaccuracy, inability to monitor equipment working conditions, and lack of working condition identification to achieve high applicability.

Active Publication Date: 2014-03-12
TSINGHUA UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

And although it is simpler to establish a unified model for multiple working conditions than the method of building multiple models, it lacks real-time identification of working conditions, which will make it impossible to monitor the working conditions of the current equipment
Although the multi-working cond

Method used

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  • Monitoring index switching based multi-operating-mode process monitoring method and system
  • Monitoring index switching based multi-operating-mode process monitoring method and system
  • Monitoring index switching based multi-operating-mode process monitoring method and system

Examples

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no. 1 example

[0040] figure 1 It is a flowchart of a multi-working-condition process monitoring method based on monitoring index switching according to an embodiment of the present invention. Combine below figure 1 This method will be described in detail.

[0041] Step S110, collecting normal data under different working conditions (that is, the working status of the power equipment under certain conditions) as a training sample set.

[0042] Specifically, the normal data under different working conditions are obtained from the chemical process database as the training sample set: in, (i=1,...M) is the data sample of the i-th working condition, Represents a real number matrix with N rows and m columns, N i Indicates the number of samples of the i-th working condition, N indicates the total number of samples, and m indicates the number of sensors.

[0043] Step S120, obtain the hidden Markov model based on the training sample set, and obtain the control limit corresponding to the mo...

example 1

[0067] Example 1: Numerical Simulation

[0068] Generate data using the following linear system:

[0069] x 1 x 2 x 3 = 0.3723 0.6815 0.4890 0.2954 0.9842 0.1793 s 1 s 2 + ...

example 2

[0083] Example 2: Continuous Stirred Heating Tank (CSTH)

[0084] Figure 10 Shown is a schematic structural diagram of a continuous stirring heating tank. In the figure, TC is a temperature controller, FT is a flow transmitter, FC is a flow controller, TT is a temperature transmitter, LC is a liquid level controller, and LT is a liquid level transmitter.

[0085] In a continuously stirred heated tank, hot and cold water are thoroughly mixed in the tank and heated by steam. There are multiple control loops in the system to ensure that the liquid level, flow and temperature work at the set operating point. Table 3 reflects the parameters corresponding to the two standard working conditions of the continuous stirring heating tank, where the unit of each physical measurement (electrical signal) is milliampere (mA).

[0086] Table 3. The parameters corresponding to the two standard working conditions of the continuous stirring heating tank

[0087]

[0088] Table 4 is a des...

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Abstract

The invention discloses a monitoring index switching based multi-operating-mode process monitoring method and system. The method includes: acquiring normal data in different operating modes to serve as a training sample set; obtaining a hidden Markov model on the basis of the training sample set, and acquiring control limits corresponding to monitoring indexes of the hidden Markov model; respectively establishing statistical pattern analysis models of corresponding operating modes on the basis of training samples of each operating mode, and acquiring control limits corresponding to monitoring indexes of each statistical pattern analysis model; computing operating mode vectors on the basis of process data acquired in real time, and further computing differential operating mode vectors; computing corresponding real-time monitoring indexes according to norms of the differential operating mode vectors, and comparing the real-time monitoring indexes with the control limits corresponding to the monitoring indexes of the corresponding models so as to monitor running states of the operating modes. The method has the advantages that the process data are acquired in real time, reliability in monitoring is guaranteed, data in each operating mode need not to obey Gaussian distribution, and applicability is higher.

Description

technical field [0001] The invention relates to the field of process monitoring, in particular to a multi-working-condition process monitoring method and system based on monitoring index switching. Background technique [0002] For process monitoring and fault diagnosis, traditional methods mostly use multivariable statistical process control (MSPC), in which principal component analysis (PCA) and partial least squares (Partial Least Squares, PLS) ) as the representative method has been successfully applied in industrial process monitoring. The traditional MSPC method assumes that the process runs under a single operating condition, but in fact, due to product changes, capacity adjustments, etc., the process often switches frequently among multiple operating conditions. [0003] Multi-condition process monitoring methods based on principal component analysis and support vector data description all assume that the data of each working condition obeys a Gaussian distribution,...

Claims

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Application Information

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IPC IPC(8): G05B17/00
Inventor 周东华宁超陈茂银
Owner TSINGHUA UNIV
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