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Data-driven information modeling method for complex electromechanical system in process industry

An electromechanical system and process industry technology, applied in electrical digital data processing, special data processing applications, instruments, etc., can solve problems such as specific applications and noise sensitivity without complex electromechanical system information modeling in process industry, and achieve auxiliary scientific maintenance. The effect of maintaining and improving the level of digital monitoring

Inactive Publication Date: 2017-10-24
XI AN JIAOTONG UNIV
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Problems solved by technology

[0006] Although there are some transfer entropy methods that can measure information transfer, there are no specific applications for information modeling of complex electromechanical systems in the process industry
Noise is unavoidable in industrial data. The traditional method is based on the probability density distribution or conditional probability of the empirical distribution, which is sensitive to noise. The ability to resist noise is a huge challenge for the transfer entropy method and its extension method

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  • Data-driven information modeling method for complex electromechanical system in process industry
  • Data-driven information modeling method for complex electromechanical system in process industry
  • Data-driven information modeling method for complex electromechanical system in process industry

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Embodiment Construction

[0049] The present invention will be further explained below in conjunction with specific embodiments and accompanying drawings.

[0050] see figure 1 , the present invention comprises the following steps:

[0051] 1) Obtain the monitoring data of the complex electromechanical system, and establish a high-dimensional historical monitoring data set. The historical monitoring data set is an n-dimensional monitoring time series matrix: this step is the original data collection step, and the process industry complex electromechanical system monitoring system (DCS, SCADA etc.), from the historical monitoring data of n sensors, the original data set is extracted at the same sampling frequency as the monitoring time series matrix, and an n-dimensional monitoring time series matrix D is obtained:

[0052]

[0053] where: X i is the i-th sample point in the matrix; d i,j is the j-th attribute value in the i-th sample point, and each column in the matrix is ​​the monitoring time s...

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Abstract

The invention discloses a data-driven information modeling method for a complex electromechanical system in the process industry. The data-driven information modeling method for the complex electromechanical system in the process industry is employed. The overall modeling process does not need prior knowledge of physical topology. In the modeling process, an information flow relationship is taken as a reference for analyses of coupling relations among different functional components of the system. By taking the anti-noise property and information loss into full consideration, a symbolization process of the system for monitoring time sequences is optimized. By binary coding and decimal decoding of symbolized phase points, the integration between the symbolization process with automated analyses and calculations is achieved. Therefore, the difficulty in building an information model of the complex electromechanical system in the process industry based on monitored data under the noise condition is resolved.

Description

technical field [0001] The invention belongs to the field of data-driven information modeling, and relates to a method for constructing an information model of an industrial production system, in particular to a data-driven method for information modeling of a complex electromechanical system in a process industry. Background technique [0002] The modern process industry production system is a distributed complex electromechanical system composed of many mechanical equipment, chemical reactors, etc. through the coupling of fluid, electricity, and control signals. With the development of sensing technology and control technology, modern process industry production systems are often equipped with distributed control system (DCS), data acquisition and supervisory control system (SCADA), etc. Monitoring data and analysis basis. [0003] System operation state analysis based on complex electromechanical system monitoring data is divided into two main lines: "forward" system fau...

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Application Information

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IPC IPC(8): G06F17/50
CPCG06F30/20
Inventor 王荣喜高建民高智勇亢嘉妮
Owner XI AN JIAOTONG UNIV
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