Multi-stage fermentation process fault monitoring method of semi-supervised FCM and SAE based on information entropy

A fermentation process and fault monitoring technology, which is applied in the direction of instruments, adaptive control, control/regulation systems, etc., can solve the problems of weakened ability of AE to extract sample characteristics and poor model generalization ability, so as to improve monitoring performance and improve Generalization performance and accurate clustering results

Pending Publication Date: 2022-04-05
BEIJING UNIV OF TECH
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Problems solved by technology

However, when there are more AE hidden layer nodes than input nodes, the ability of AE to extract sample features will be greatly weakened, and the generalization ability of the model will also deteriorate.

Method used

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  • Multi-stage fermentation process fault monitoring method of semi-supervised FCM and SAE based on information entropy
  • Multi-stage fermentation process fault monitoring method of semi-supervised FCM and SAE based on information entropy
  • Multi-stage fermentation process fault monitoring method of semi-supervised FCM and SAE based on information entropy

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Embodiment Construction

[0044] Penicillin (penicillin) Penicillin (penicillin) is a very broad clinical value of antibiotics. This paper uses the international platform Pensim2.0 simulation platform to conduct fault monitoring research on the penicillin fermentation process.

[0045] In this platform, for the convenience of the experiment, the working conditions were set as 400 hours for each batch of continuous fermentation, and the sampling interval was 1 hour. The initial conditions of each batch were slightly changed within the allowable range. 40 batches of normal data are used for simulation, and 10 process variables are selected to obtain 40×400×10 data for offline modeling. The process variables are shown in Table 1. In order to better simulate the actual production situation, a certain amount of Gaussian noise interference is added to the training samples. In order to verify the performance of the proposed method in fault monitoring, this paper selects three groups of fault batch samples ...

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Abstract

The invention discloses a multi-stage fermentation process fault monitoring method of semi-supervised FCM and SAE based on information entropy. The method comprises the following steps: firstly, completing stable stage division on data in a fermentation process by using a semi-supervised fuzzy C-means clustering algorithm based on information entropy; and then a Silhouette coefficient is introduced to divide a transition stage of every two stable stages, and the fault monitoring comprises the steps of establishing a monitoring model for each stable stage and each transition stage by using a sparse automatic encoder, and constructing a reconstruction error as a statistic index. Then determining a control limit of each sample statistic index by using a kernel density estimation method; and finally, substituting test batch samples into the model, calculating a statistic index of the test batch samples, comparing the statistic index with a normal sample control limit, and if the control limit is exceeded, determining that the sample is a fault sample. The method is more sensitive to faults, enhances the robustness of a monitoring model, improves the accuracy of fault monitoring, and can reduce the occurrence of false alarms and missing alarms in process monitoring.

Description

technical field [0001] The invention relates to the field of data-driven fault monitoring technology, in particular to a fault monitoring technology for fermentation process. The data-driven method of the present invention is a specific application in the monitoring of fermentation process faults. Background technique [0002] With the rapid development of industrial automation technology, the integration and complexity of modern industrial systems are getting higher and higher. In order to enable the system to detect the occurrence of faults in time, it is particularly important to improve the reliability of system fault monitoring performance. Fermentation process is an industrial process mainly based on batch process, which refers to making raw materials into small batches and high value-added products within a limited time. Due to the high daily demand for these products, fault monitoring has been of high interest in the industry for the safe and orderly production of ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05B13/04
Inventor 高学金李学凤高慧慧韩华云
Owner BEIJING UNIV OF TECH
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