2021
DOI: 10.1177/00368504211026110
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Compressor fault diagnosis system based on PCA-PSO-LSSVM algorithm

Abstract: On the basis of the principal components analysis-particle swarm optimization-least squares support vector machine (PCA-PSO-LSSVM) algorithm, a fault diagnosis system is proposed for the compressor system. The relationship between the working principle of a compressor system, the fault phenomenon, and the root cause is analyzed. A fault diagnosis model is established based on the LSSVM optimized using PSO, the compressor fault diagnosis test experimental platform is used to obtain the fault signal of various f… Show more

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Cited by 15 publications
(9 citation statements)
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References 14 publications
(16 reference statements)
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“…At present, the more commonly used parameter optimization methods are swarm intelligence optimization algorithms, such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Ant Colony Algorithm (ACO), Sparrow Search Algorithm (SSA), etc. [20][21][22][23]. In the above algorithms, the SSA method has the advantages of strong optimization ability and fast convergence speed.…”
Section: B Ssa-spamentioning
confidence: 99%
“…At present, the more commonly used parameter optimization methods are swarm intelligence optimization algorithms, such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Ant Colony Algorithm (ACO), Sparrow Search Algorithm (SSA), etc. [20][21][22][23]. In the above algorithms, the SSA method has the advantages of strong optimization ability and fast convergence speed.…”
Section: B Ssa-spamentioning
confidence: 99%
“…Then, the region of interest for target is segmented based on the optimal threshold obtained through the optimization algorithm. PSO has been widely used in image segmentation [16], path planning [17], resource allocation [18], and fault diagnosis [19] due to its simplicity in calculation and image segmentation, and fast convergence. Therefore, this paper used the PSO algorithm to solve Equation (7).…”
Section: Otsu Optimization Based On Apso Algorithmmentioning
confidence: 99%
“…In the mentioned study, the Weibull distribution function was applied by using the leave-one-out cross-validation method to study the failure behavior of air compressors in a deep mine in South Africa. Zhang et al 10 proposed a fault diagnosis system for compressors. In this study, an algorithm based on the least squares supports vector machine was optimized using particle swarm optimization and then applied to create a fault diagnosis model.…”
Section: Introductionmentioning
confidence: 99%