Fault detection method of MKPCA batch process based on Limited-DTW

A technology for fault monitoring and fermentation process, which is applied in program control, electrical program control, comprehensive factory control, etc. It can solve the problems of unequal length of batches and unequal length of batch data, so as to improve real-time performance and reduce the amount of calculation , the effect of reducing the computational complexity

Active Publication Date: 2017-07-28
BEIJING UNIV OF TECH
View PDF3 Cites 6 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] Aiming at the problem of unequal length of batch data in batch process, the present invention provides a MKPCA batch process fault monitoring method based on Limited-...

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Fault detection method of MKPCA batch process based on Limited-DTW
  • Fault detection method of MKPCA batch process based on Limited-DTW
  • Fault detection method of MKPCA batch process based on Limited-DTW

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0041] The Dynamic Time Warping (DTW) algorithm was first used in the field of speech recognition. It is a nonlinear warping technology that combines time warping and distance measurement calculations. It is a common method for calculating the similarity between time vector sequences. The dynamic time warping algorithm is a flexible pattern matching algorithm, which can match the patterns with global or local expansion, compression or deformation, and solve the similarity measurement and classification problems of dynamic patterns. Find a path automatically. Although this method performs dynamic matching according to the pattern of points in the trajectory, the complexity of its processing and its offline nature make its practical application difficult. Therefore, the present invention proposes a MKPCA intermittent process fault monitoring method based on Limited-DTW. This method increases the global path limit and sets the distortion threshold limit to the DTW algorithm, redu...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a fault detection method of an MKPCA batch process based on Limited-DTW. In order to overcome the inherent shortcomings of the batch unequal length of the intermittent process, and in order to overcome the serious defects of the traditional method of solving the inter-batch synchronization problem such as data waste, and the distortion of the variable autocorrelation and the cross-correlation relation between the variables of the original process, the method introduces the global path limit and the distortion threshold limit to improve the dynamic time warping (DTW) method, so as to avoid the monitoring shortcomings of the long-term operation of the algorithm and to solve the complexity of the processing and the practical application difficulty caused by the off-line performance. Limited-DTW and an MKPCA-based monitoring method are combined for offline and online implementation. The experiment design is completed by the penicillin fermentation simulation platform and the recombinant Escherichia coli practical production process, and the result displays the feasibility and validity of the method provided by the invention.

Description

technical field [0001] The invention relates to the technical field of data-driven multivariate statistical process monitoring (Multivariate Statistical Process Monitoring, MSPM), in particular to a Limited-DTW-based MKPCA intermittent process fault monitoring method. Background technique [0002] When the data-driven multivariate statistical method is used for the process monitoring of the batch process, it does not need to consider the complex process mechanism characteristics. Through the modeling and analysis of historical data, it can be judged whether the operation status of the production process is abnormal. As one of the important production methods in the modern process industry, the batch process is widely used in the preparation of biomedicine, food and biochemical products, especially the preparation of penicillin (Penicillin, or transliterated penicillin). Compared with the continuous production process, the batch process has obvious differences, among which th...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G05B19/418
CPCY02P90/02G05B19/41885
Inventor 高学金黄梦丹王普
Owner BEIJING UNIV OF TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap