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A Distillation Column Fault Diagnosis Method Based on Improved Particle Swarm Optimization Support Vector Machine

A technology of support vector machine and improved particle swarm, which is applied in computer components, data processing applications, prediction, etc., to improve the effect of easily falling into local optimum and improve classification accuracy

Active Publication Date: 2021-10-08
HANGZHOU DIANZI UNIV
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  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to provide a rectification tower fault diagnosis method that improves the particle swarm optimization support vector machine, effectively improves the problem that the particle swarm is trapped in a local optimum, thereby improving the classification and identification accuracy of the rectification tower fault diagnosis, to solve the above background questions raised in technology

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  • A Distillation Column Fault Diagnosis Method Based on Improved Particle Swarm Optimization Support Vector Machine
  • A Distillation Column Fault Diagnosis Method Based on Improved Particle Swarm Optimization Support Vector Machine
  • A Distillation Column Fault Diagnosis Method Based on Improved Particle Swarm Optimization Support Vector Machine

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Embodiment Construction

[0036] Such as figure 1 As shown, a rectification column fault diagnosis method for improved particle swarm optimization support vector machine, the method specifically includes the following steps:

[0037] Step 1: Setting of initial value of particle swarm, given input data X={X 1 ,...,X n} and learning objective y={y 1 ,...,y n} are all derived from the failure data of the rectification tower, where T max The maximum number of iterations is 300, set w as the inertia weight of 0.9, and the acceleration factor c 1 is 1.6, the acceleration factor c 2 1.5, V max The initial maximum set speed is 120, X max Set the position to 180 for the initial maximum. Given the parameter C, the range of σ is [0,100], C is the penalty coefficient, and σ is the selected RBF function (K(x i ,x j ) = exp(||x i -x j || 2 / σ 2 )) As a kernel, a parameter of this function, i=1,2,...n,j=1,2,...n,x i =[x 1 ,...,x n ]∈X represents the multiple feature space contained in each sample of ...

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Abstract

The present invention provides a rectification tower fault diagnosis method based on improved particle swarm optimization support vector machine. The present invention performs optimization according to the following steps: (1) setting the initial value of the subgroup, and specifying the range of parameters C and σ. (2) Randomly generate the position and velocity of particles, and evaluate the fitness value of each particle according to the fitness function. (3) Update the speed and position according to the corresponding improved formula. (4) Check whether the termination condition is satisfied, if it is satisfied, end the search, if not, return to step 2 for recalculation. (5) Obtain the parameters of the optimized support vector machine, and establish an improved particle swarm optimization support vector machine model. The invention effectively improves the problem of falling into local optimum caused by too large or too small speed limit value selection at the beginning of ordinary particle swarm optimization support vector.

Description

technical field [0001] The invention belongs to the technical field of optimization algorithm application, and in particular relates to a method for diagnosing a rectification tower fault by improving a particle swarm optimization support vector machine. Background technique [0002] In the production process of the petrochemical industry, the distillation column occupies an important position. The rectification tower is a tower-type vapor-liquid contact device that utilizes the different volatilities of each component in the mixture to achieve the purpose of separation, thereby achieving rectification. In the petrochemical industry and other industries, the quality of the distillation column equipment in the operation process is directly related to the economic benefits of the enterprise. Therefore, fault diagnosis of distillation columns can improve process safety and product quality. [0003] In today's rapidly developing technological society, fault diagnosis begins to...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q10/04G06K9/62G06Q50/04
CPCY02P90/30
Inventor 郑松裘虹飞葛铭郑小青魏江
Owner HANGZHOU DIANZI UNIV
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