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Quality-related fault detection method based on two variable blocks

A quality-related, fault-detecting technology that can be used in overall factory control, instrumentation, overall factory control, etc., to solve problems such as rejection

Active Publication Date: 2018-07-31
NINGBO UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, if such methods are not implemented properly, information related to the output will be removed at the same time.
However, how to implement quality-related fault detection from the perspective of distinguishing quality-related or irrelevant variables has not received much attention and attention

Method used

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  • Quality-related fault detection method based on two variable blocks
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  • Quality-related fault detection method based on two variable blocks

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Embodiment Construction

[0056] The method of the present invention will be described in detail below with reference to the accompanying drawings and specific implementation cases.

[0057] like figure 1 As shown, the present invention discloses a quality-related fault detection method based on a two-variable block. The specific implementation process of the method of the present invention and the advantages compared with the existing method are described below in conjunction with an example of a specific industrial process.

[0058] The application object is from the chemical process experiment of Tennessee-Eastman (TE) in the United States, and the prototype is an actual process flow of the Eastman chemical production workshop. At present, the TE process has been widely used as a standard experimental platform for fault detection research due to its complexity. The entire TE process includes 22 measured variables, 12 manipulated variables, and 19 component measured variables. The collected data i...

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Abstract

The invention discloses a quality-related fault detection method based on two variable blocks. According to the method, a genetic algorithm is combined with a neighbor component analysis algorithm, the input variables are divided into the two variable blocks which are related and not related to quality. Then, a partial least squares (PLS) model between the quality-related variable block and the output is established for carrying out the quality-related fault detection, and the quality non-related variable block is combined with the PLS model input residual error to carry out the quality non-related fault detection. Compared with a traditional moving method, according to the method disclosed by the invention, the quality-related and quality non-related measurement variables are distinguished optimally by combining the genetic algorithm with the NCA. In addition, according to the method disclosed by the invention, the PLS model input residual error of the quality-related variable is combined with the quality non-related measurement variable to carry out the quality non-related fault detection, and all the quality non-related component information is comprehensively utilized. Therefore, the method provided by the invention can give more accurate quality-related fault detection results.

Description

technical field [0001] The invention relates to a data-driven fault detection method, in particular to a quality-related fault detection method based on a two-variable block. Background technique [0002] Maintaining the stability of product quality is an important technical means to ensure the profitability of an enterprise, and implementing quality-related fault detection has a deeper meaning. In recent years, due to the vigorous promotion of industrial informatization construction, massive process data and quality index data can be collected and stored, which has laid a solid data foundation for data-driven fault detection research. In the existing scientific literature and patents, most of the fault detection methods are aimed at detecting abnormal operating states, and relatively few fault detection methods related to product quality are involved. Different from the pure fault detection purpose, quality-related fault detection needs to distinguish whether the detected ...

Claims

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Application Information

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IPC IPC(8): G05B19/418
CPCG05B19/41885G05B2219/32339Y02P90/02
Inventor 童楚东朱莹俞海珍
Owner NINGBO UNIV
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