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Fault detection method and system for complex process considering dynamic relationship in advance

A fault detection and dynamic technology, applied in the general control system, control/regulation system, program control, etc., can solve the problem of no detection method and achieve a strong and robust effect

Active Publication Date: 2020-03-27
中国人民解放军火箭军工程大学
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

Currently, there is no relevant detection method

Method used

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  • Fault detection method and system for complex process considering dynamic relationship in advance
  • Fault detection method and system for complex process considering dynamic relationship in advance
  • Fault detection method and system for complex process considering dynamic relationship in advance

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Experimental program
Comparison scheme
Effect test

Embodiment 1

[0081] figure 1 The flow chart of the fault detection method for the complex process of pre-considering the dynamic relationship in Embodiment 1 of the present invention, such as figure 1 As shown, the present embodiment provides a fault detection method for a complex process that considers dynamic relationships in advance, including the following steps:

[0082] Step 101: Obtain normal measurement data and normal quality data in a complex industrial process during normal operation, and perform preprocessing on the normal measurement data and the normal quality data.

[0083] Step 102: Establish a dynamic orthogonal signal correction model according to the preprocessed normal measurement data and normal quality data.

[0084] For a complex industrial process with normal operation, m sensors are used to detect its key input variables (such as flow, pressure, liquid level, temperature, etc.) n times, which is called normal measurement data, and the normal measurement data set i...

Embodiment 2

[0142] In order to achieve the above object, the present invention also provides a fault detection system that considers the complex process of dynamic relationship in advance, such as image 3 shown, including:

[0143] The first preprocessing module 201 is configured to acquire normal measurement data and normal quality data in complex industrial processes during normal operation, and perform preprocessing on the normal measurement data and the normal quality data.

[0144] The dynamic quadrature signal correction model establishment module 202 is used to establish a dynamic quadrature signal correction model according to the preprocessed normal measurement data and normal quality data.

[0145] The improved partial least squares model establishment module 203 is configured to establish an improved partial least squares model according to the dynamic orthogonal signal correction model and the preprocessed normal measurement data and normal quality data.

[0146] The second ...

Embodiment 3

[0174] The present invention verifies the performance of the proposed algorithm through the built Tennessee Eastman Process, which is an important platform for algorithm performance testing and evaluation, and also an important data source for multivariate process monitoring method testing. The TE process contains many measured variables, manipulated variables, output variables and disturbances, etc. It is a typical complex industrial process. Its rich degrees of freedom can provide many researchers engaged in algorithm development with precious and massive test data, and it is widely used in the field of fault detection and fault diagnosis in industrial processes.

[0175] The Tennessee Eastman Process was created by Eastman Chemical Company to provide a realistic industrial process for evaluating process control and monitoring methods. The process consists of five main units: reactor, condenser, compressor, separator, and stripper, and it contains eight components: A, B, C, ...

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Abstract

The invention discloses a fault detection method and system for a complex process considering a dynamic relationship in advance. The method comprises the steps of obtaining and preprocessing normal measurement data and normal quality data in the complex industrial process during normal operation; establishing a dynamic orthogonal signal correction model according to the preprocessed normal measurement data and normal quality data; establishing an improved partial least square model according to the dynamic orthogonal signal correction model and the preprocessed normal measurement data and normal quality data; acquiring and preprocessing real-time measurement data and real-time quality data in the complex industrial process in operation; obtaining expected real-time measurement data according to the dynamic orthogonal signal correction model and the preprocessed real-time measurement data; based on an improved partial least squares model, expected real-time measurement data and preprocessed real-time quality data, detecting quality-related faults in the running complex industrial process. The reliability and safety of a complex system are improved, and major accidents are reduced.

Description

technical field [0001] The invention relates to the technical field of fault monitoring, in particular to a fault detection method and system for a complex process with dynamic relationships considered in advance. Background technique [0002] The existing industrial process monitoring methods are mainly divided into two categories: univariate process monitoring and multivariable process monitoring. Because of the singularity of the variable it monitors, the monitoring efficiency of single-variable process monitoring is very limited in the production process of large-scale and complex industrial equipment. The production of modern industrial equipment, whether it is military or civilian, is a series of complex processes with multiple variables, multiple outputs, and a huge amount of data collection. The multi-variable process monitoring method has higher precision and faster speed in dealing with the complex characteristics of big data, and has stronger applicability in dea...

Claims

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Application Information

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IPC IPC(8): G05B19/418
CPCG05B19/41885G05B2219/32339Y02P90/02
Inventor 孔祥玉胡昌华李强解建司小胜
Owner 中国人民解放军火箭军工程大学
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