Swarm intelligence optimization fault diagnosis system based on hybrid optimized parameters

Abstract

The invention discloses a swarm intelligence optimization fault diagnosis system based on hybrid optimized parameters. The system is used for performing fault diagnosis on a Tennessee Eastman processand comprises a data preprocessing module, a principal component analysis module, a relevance vector machine module and a swarm intelligence algorithm module. Fault diagnosis prediction of important parameter indexes of the Tennessee Eastman chemical process is performed, the defect that the fault diagnosis effect is affected due to the fact that the instrument test sensitivity of existing chemical fault diagnosis technologies is poor and optimal system parameters are difficult to find is overcome, the swarm intelligence algorithm module is introduced to optimize relevance vector machine parameters, so that the swarm intelligence optimization fault diagnosis system based on hybrid optimized parameters is obtained, and the effects that the test sensitivity of the fault diagnosis system is good and globally optimal solutions are easy to find in the Tennessee Eastman process are realized.

Description

technical field [0001] The invention relates to the field of fault diagnosis, machine learning and swarm intelligence optimization algorithm, in particular to a Tennessee Eastman process chemical fault diagnosis system combining machine learning and swarm intelligence optimization algorithm. Background technique [0002] With the rapid development of industrial modernization technology, industrial automation systems are constantly being upgraded. More and more complex industrial production processes have become more reliable, production has become more stable, and better control of machine operations can be achieved. In recent decades, technologies such as microcontrollers, sensors, communication buses, and integrators have developed rapidly. These components are getting cheaper and more stable and reliable. This has largely promoted the development of contemporary industrial automation systems, making automation systems a very important part of industrial production proces...

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Problems solved by technology

[0003] In order to overcome the disadvantages of poor test agility and difficulty in finding the optimal parameters of the system in the existing fault diagnosis technology, which affects the diagnosis effect, the purpose of the present invention is to provide a group with good agility in system testing and easy to find the global optimal parameters of the system. Intelligent Optimal Fault Diagnosis System

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