Roller kiln energy consumption anomaly detection method based on self-adaptive principal component analysis

A principal component analysis and anomaly detection technology, applied in the field of detection, can solve the problems of low detection efficiency and abnormal energy consumption of roller kiln, and achieve the effect of reducing false alarm rate, saving calculation time, and optimizing algorithm process.

Inactive Publication Date: 2020-12-11
GUANGDONG UNIV OF TECH
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Problems solved by technology

[0006] In order to overcome the problem of low detection efficiency of the above-mentioned abnormal situation of the roller kiln, the present invention provides a method for detecting abnormal energy consumption of the roller kiln based on adaptive principal component analysis

Method used

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  • Roller kiln energy consumption anomaly detection method based on self-adaptive principal component analysis
  • Roller kiln energy consumption anomaly detection method based on self-adaptive principal component analysis
  • Roller kiln energy consumption anomaly detection method based on self-adaptive principal component analysis

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Embodiment

[0059] As shown in the figure, an embodiment of an abnormal detection method for energy consumption of a roller kiln based on adaptive principal component analysis of the present invention, the specific steps are as follows:

[0060] (1) First collect the sample L, and calculate the covariance matrix S after standardizing the collected samples;

[0061] (2) Decompose the eigenvalues ​​of S, use the CPV method to calculate the number of principal components k, and intercept the eigenvectors and eigenvalues ​​to obtain the load matrix P and eigenvalue matrix Λ;

[0062] (3) Calculate the initial control limit and

[0063] (4) Continue to collect new samples of sample L after a certain period of time, and perform standardization; and perform abnormal judgment on the new samples, if abnormal, output abnormal information to end, if normal, put the sample into the system to be updated and perform step (5) );

[0064] (5) Loop (1)(2)(3(4) until the number of samples to be updat...

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Abstract

The invention relates to the technical field of detection methods, in particular to a roller kiln energy consumption anomaly detection method based on self-adaptive principal component analysis. The roller kiln energy consumption anomaly detection method comprises the following specific steps that (1) firstly, a sample L is collected, the collected sample is standardized, and then a covariance matrix S is calculated; (2) characteristic decomposition is carried out on S, a principal component number k is obtained through calculation by using a CPV method, and a characteristic vector and a characteristic value are intercepted to obtain a load matrix P and a characteristic value matrix lambda; (3) an initial control limit is calculated; (4) a new sample of the sample L is continuously collected after a certain moment, standardizing is carried out, and abnormal judgment is carried out on the new sample; and (5) the steps (1), (2), (3) and (4) are circulated until the number of the samplesneeding to be updated reaches the number of the samples needing to be updated, the samples are updated and abnormal information judgment is carried out. According to the roller kiln energy consumptionanomaly detection method based on the self-adaptive principal component analysis, the abnormal condition of the roller kiln can be effectively detected, and the detection efficiency is greatly improved.

Description

technical field [0001] The invention relates to the technical field of a detection method, and more specifically, to a method for detecting abnormal energy consumption of a roller kiln based on adaptive principal component analysis. Background technique [0002] Roller kiln is an important type of ceramic kiln, mainly used in the production of building ceramic materials, and is the main energy-consuming equipment in ceramic production. In the process of ceramic production, if the abnormality of the roller kiln occurs due to factors such as materials, parameter control, and personnel, it will lead to product defects and energy waste, causing great economic losses, and even safety accidents in serious cases. In actual situations, manual inspection and observation of instruments and meters based on experience are usually used to check and find abnormal conditions, which have the disadvantages of labor-intensive and untimely discovery. With the development of science and techno...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): F27B9/40G06F30/20G06K9/62
CPCF27B9/40G06F30/20G06F18/2135
Inventor 徐康康杨海东印四华朱成就邹振弘胡罗克
Owner GUANGDONG UNIV OF TECH
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